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

Evolving NASA's Earth Science Data Systems

Science.gov (United States)

Walter, J.; Behnke, J.; Murphy, K. J.; Lowe, D. R.

2013-12-01

NASA's Earth Science Data and Information System Project (ESDIS) is charged with managing, maintaining, and evolving NASA's Earth Observing System Data and Information System (EOSDIS) and is responsible for processing, archiving, and distributing NASA Earth science data. The system supports a multitude of missions and serves diverse science research and other user communities. Keeping up with ever-changing information technology and figuring out how to leverage those changes across such a large system in order to continuously improve and meet the needs of a diverse user community is a significant challenge. Maintaining and evolving the system architecture and infrastructure is a continuous and multi-layered effort. It requires a balance between a "top down" management paradigm that provides a coherent system view and maintaining the managerial, technological, and functional independence of the individual system elements. This presentation will describe some of the key elements of the current system architecture, some of the strategies and processes we employ to meet these challenges, current and future challenges, and some ideas for meeting those challenges.

Views on Evolvability of Embedded Systems

NARCIS (Netherlands)

Laar, P. van de; Punter, T.

2011-01-01

Evolvability, the ability to respond effectively to change, represents a major challenge to today's high-end embedded systems, such as those developed in the medical domain by Philips Healthcare. These systems are typically developed by multi-disciplinary teams, located around the world, and are in

Views on evolvability of embedded systems

NARCIS (Netherlands)

Laar, van de P.J.L.J.; Punter, H.T.

2011-01-01

Evolvability, the ability to respond effectively to change, represents a major challenge to today's high-end embedded systems, such as those developed in the medical domain by Philips Healthcare. These systems are typically developed by multi-disciplinary teams, located around the world, and are in

Complexity, flow, and antifragile healthcare systems: implications for nurse executives.

Science.gov (United States)

Clancy, Thomas R

2015-04-01

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. In this article, I further discuss the concept of fragility, its impact on system behavior, and ways to reduce it.

PCBA demand forecasting using an evolving Takagi-Sugeno system

NARCIS (Netherlands)

van Rooijen, M.; Almeida, R.J.; Kaymak, U.

2016-01-01

This paper investigates the use of using an evolving fuzzy system for printed circuit board (PCBA) demand forecasting. The algorithm is based on the evolving Takagi-Sugeno (eTS) fuzzy system, which has the ability to incorporate new patterns by changing its internal structure in an on-line fashion.

Evolution of complexity in RNA-like replicator systems

Directory of Open Access Journals (Sweden)

Hogeweg Paulien

2008-03-01

Full Text Available Abstract Background The evolution of complexity is among the most important questions in biology. The evolution of complexity is often observed as the increase of genetic information or that of the organizational complexity of a system. It is well recognized that the formation of biological organization – be it of molecules or ecosystems – is ultimately instructed by the genetic information, whereas it is also true that the genetic information is functional only in the context of the organization. Therefore, to obtain a more complete picture of the evolution of complexity, we must study the evolution of both information and organization. Results Here we investigate the evolution of complexity in a simulated RNA-like replicator system. The simplicity of the system allows us to explicitly model the genotype-phenotype-interaction mapping of individual replicators, whereby we avoid preconceiving the functionality of genotypes (information or the ecological organization of replicators in the model. In particular, the model assumes that interactions among replicators – to replicate or to be replicated – depend on their secondary structures and base-pair matching. The results showed that a population of replicators, originally consisting of one genotype, evolves to form a complex ecosystem of up to four species. During this diversification, the species evolve through acquiring unique genotypes with distinct ecological functionality. The analysis of this diversification reveals that parasitic replicators, which have been thought to destabilize the replicator's diversity, actually promote the evolution of diversity through generating a novel "niche" for catalytic replicators. This also makes the current replicator system extremely stable upon the evolution of parasites. The results also show that the stability of the system crucially depends on the spatial pattern formation of replicators. Finally, the evolutionary dynamics is shown to

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

Architectural Analysis of Complex Evolving Systems of Systems

Science.gov (United States)

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

2009-01-01

The goal of this collaborative project between FC-MD, APL, and GSFC and supported by NASA IV&V Software Assurance Research Program (SARP), was to develop a tool, Dynamic SAVE, or Dyn-SAVE for short, for analyzing architectures of systems of systems. The project team was comprised of the principal investigator (PI) from FC-MD and four other FC-MD scientists (part time) and several FC-MD students (full time), as well as, two APL software architects (part time), and one NASA POC (part time). The PI and FC-MD scientists together with APL architects were responsible for requirements analysis, and for applying and evaluating the Dyn-SAVE tool and method. The PI and a group of FC-MD scientists were responsible for improving the method and conducting outreach activities, while another group of FC-MD scientists were responsible for development and improvement of the tool. Oversight and reporting was conducted by the PI and NASA POC. The project team produced many results including several prototypes of the Dyn-SAVE tool and method, several case studies documenting how the tool and method was applied to APL s software systems, and several published papers in highly respected conferences and journals. Dyn-SAVE as developed and enhanced throughout this research period, is a software tool intended for software developers and architects, software integration testers, and persons who need to analyze software systems from the point of view of how it communicates with other systems. Using the tool, the user specifies the planned communication behavior of the system modeled as a sequence diagram. The user then captures and imports the actual communication behavior of the system, which is then converted and visualized as a sequence diagram by Dyn-SAVE. After mapping the planned to the actual and specifying parameter and timing constraints, Dyn-SAVE detects and highlights deviations between the planned and the actual behavior. Requirements based on the need to analyze two inter-system

Evolving Systems: An Outcome of Fondest Hopes and Wildest Dreams

Science.gov (United States)

Frost, Susan A.; Balas, Mark J.

2012-01-01

New theory is presented for evolving systems, which are autonomously controlled subsystems that self-assemble into a new evolved system with a higher purpose. Evolving systems of aerospace structures often require additional control when assembling to maintain stability during the entire evolution process. This is the concept of Adaptive Key Component Control that operates through one specific component to maintain stability during the evolution. In addition, this control must often overcome persistent disturbances that occur while the evolution is in progress. Theoretical results will be presented for Adaptive Key Component control for persistent disturbance rejection. An illustrative example will demonstrate the Adaptive Key Component controller on a system composed of rigid body and flexible body modes.

The Comet Cometh: Evolving Developmental Systems.

Science.gov (United States)

Jaeger, Johannes; Laubichler, Manfred; Callebaut, Werner

In a recent opinion piece, Denis Duboule has claimed that the increasing shift towards systems biology is driving evolutionary and developmental biology apart, and that a true reunification of these two disciplines within the framework of evolutionary developmental biology (EvoDevo) may easily take another 100 years. He identifies methodological, epistemological, and social differences as causes for this supposed separation. Our article provides a contrasting view. We argue that Duboule's prediction is based on a one-sided understanding of systems biology as a science that is only interested in functional, not evolutionary, aspects of biological processes. Instead, we propose a research program for an evolutionary systems biology, which is based on local exploration of the configuration space in evolving developmental systems. We call this approach-which is based on reverse engineering, simulation, and mathematical analysis-the natural history of configuration space. We discuss a number of illustrative examples that demonstrate the past success of local exploration, as opposed to global mapping, in different biological contexts. We argue that this pragmatic mode of inquiry can be extended and applied to the mathematical analysis of the developmental repertoire and evolutionary potential of evolving developmental mechanisms and that evolutionary systems biology so conceived provides a pragmatic epistemological framework for the EvoDevo synthesis.

Calcium-manganese oxides as structural and functional models for active site in oxygen evolving complex in photosystem II: lessons from simple models.

Science.gov (United States)

Najafpour, Mohammad Mahdi

2011-01-01

The oxygen evolving complex in photosystem II which induces the oxidation of water to dioxygen in plants, algae and certain bacteria contains a cluster of one calcium and four manganese ions. It serves as a model to split water by sunlight. Reports on the mechanism and structure of photosystem II provide a more detailed architecture of the oxygen evolving complex and the surrounding amino acids. One challenge in this field is the development of artificial model compounds to study oxygen evolution reaction outside the complicated environment of the enzyme. Calcium-manganese oxides as structural and functional models for the active site of photosystem II are explained and reviewed in this paper. Because of related structures of these calcium-manganese oxides and the catalytic centers of active site of the oxygen evolving complex of photosystem II, the study may help to understand more about mechanism of oxygen evolution by the oxygen evolving complex of photosystem II. Copyright © 2010 Elsevier B.V. All rights reserved.

Envisioning a New Foundation for Gifted Education: Evolving Complexity Theory (ECT) of Talent Development

Science.gov (United States)

Dai, David Yun

2017-01-01

This article presents a new theory of talent development, evolving complexity theory (ECT), in the context of the changing theoretical directions as well as the landscape of gifted education. I argue that gifted education needs a new foundation that provides a broad psychosocial basis than what the notion of giftedness can afford. A focus on…

A new evolutionary system for evolving artificial neural networks.

Science.gov (United States)

Yao, X; Liu, Y

1997-01-01

This paper presents a new evolutionary system, i.e., EPNet, for evolving artificial neural networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's evolutionary programming (EP). Unlike most previous studies on evolving ANN's, this paper puts its emphasis on evolving ANN's behaviors. Five mutation operators proposed in EPNet reflect such an emphasis on evolving behaviors. Close behavioral links between parents and their offspring are maintained by various mutations, such as partial training and node splitting. EPNet evolves ANN's architectures and connection weights (including biases) simultaneously in order to reduce the noise in fitness evaluation. The parsimony of evolved ANN's is encouraged by preferring node/connection deletion to addition. EPNet has been tested on a number of benchmark problems in machine learning and ANNs, such as the parity problem, the medical diagnosis problems, the Australian credit card assessment problem, and the Mackey-Glass time series prediction problem. The experimental results show that EPNet can produce very compact ANNs with good generalization ability in comparison with other algorithms.

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.

X-ray and vibrational spectroscopy of manganese complexes relevant to the oxygen-evolving complex of photosynthesis

Energy Technology Data Exchange (ETDEWEB)

Visser, Hendrik [Univ. of California, Berkeley, CA (United States)

2001-01-01

Manganese model complexes, relevant to the oxygen-evolving complex (OEC) in photosynthesis, were studied with Mn K-edge X-ray absorption near-edge spectroscopy (XANES), Mn Kb X-ray emission spectroscopy (XES), and vibrational spectroscopy. A more detailed understanding was obtained of the influence of nuclearity, overall structure, oxidation state, and ligand environment of the Mn atoms on the spectra from these methods. This refined understanding is necessary for improving the interpretation of spectra of the OEC. Mn XANES and Kb XES were used to study a di-(mu)-oxo and a mono-(mu)-oxo di-nuclear Mn compound in the (III,III), (III,IV), and (IV,IV) oxidation states. XANES spectra show energy shifts of 0.8 - 2.2 eV for 1-electron oxidation-state changes and 0.4 - 1.8 eV for ligand-environment changes. The shifts observed for Mn XES spectra were approximately 0.21 eV for oxidation state-changes and only approximately 0.04 eV for ligand-environment changes. This indicates that Mn Kb XES i s more sensitive to the oxidation state and less sensitive to the ligand environment of the Mn atoms than XANES. These complimentary methods provide information about the oxidation state and the ligand environment of Mn atoms in model compounds and biological systems. A versatile spectroelectrochemical apparatus was designed to aid the interpretation of IR spectra of Mn compounds in different oxidation states. The design, based on an attenuated total reflection device, permits the study of a wide spectral range: 16,700 (600 nm) - 225

Evolving information systems: meeting the ever-changing environment

NARCIS (Netherlands)

Oei, J.L.H.; Proper, H.A.; Falkenberg, E.D.

1994-01-01

To meet the demands of organizations and their ever-changing environment, information systems are required which are able to evolve to the same extent as organizations do. Such a system has to support changes in all time-and application-dependent aspects. In this paper, requirements and a conceptual

A Conceptual Framework for Evolving, Recommender Online Learning Systems

Science.gov (United States)

Peiris, K. Dharini Amitha; Gallupe, R. Brent

2012-01-01

A comprehensive conceptual framework is developed and described for evolving recommender-driven online learning systems (ROLS). This framework describes how such systems can support students, course authors, course instructors, systems administrators, and policy makers in developing and using these ROLS. The design science information systems…

Etoile Project : Social Intelligent ICT-System for very large scale education in complex systems

Science.gov (United States)

Bourgine, P.; Johnson, J.

2009-04-01

The project will devise new theory and implement new ICT-based methods of delivering high-quality low-cost postgraduate education to many thousands of people in a scalable way, with the cost of each extra student being negligible (Socially Intelligent Resource Mining system to gather large volumes of high quality educational resources from the internet; new methods to deconstruct these to produce a semantically tagged Learning Object Database; a Living Course Ecology to support the creation and maintenance of evolving course materials; systems to deliver courses; and a ‘socially intelligent assessment system'. The system will be tested on one to ten thousand postgraduate students in Europe working towards the Complex System Society's title of European PhD in Complex Systems. Étoile will have a very high impact both scientifically and socially by (i) the provision of new scalable ICT-based methods for providing very low cost scientific education, (ii) the creation of new mathematical and statistical theory for the multiscale dynamics of complex systems, (iii) the provision of a working example of adaptation and emergence in complex socio-technical systems, and (iv) making a major educational contribution to European complex systems science and its applications.

Complexity Theory

Science.gov (United States)

Lee, William H K.

2016-01-01

A complex system consists of many interacting parts, generates new collective behavior through self organization, and adaptively evolves through time. Many theories have been developed to study complex systems, including chaos, fractals, cellular automata, self organization, stochastic processes, turbulence, and genetic algorithms.

Traditional Knowledge of Western Herbal Medicine and Complex Systems Science.

Science.gov (United States)

Niemeyer, Kathryn; Bell, Iris R; Koithan, Mary

2013-09-01

Traditional knowledge of Western herbal medicine (WHM) supports experiential approaches to healing that have evolved over time. This is evident in the use of polyherb formulations comprised of crude plant parts, individually tailored to treat the cause of dysfunction and imbalance by addressing the whole person holistically. The challenge for WHM is to integrate science with traditional knowledge that is a foundation of the practice of WHM. The purpose of this paper is to provide a plausible theoretical hypothesis by applying complex systems science to WHM, illustrating how medicinal plants are complex, adaptive, environmentally interactive systems exhibiting synergy and nonlinear healing causality. This paper explores the conceptual congruence between medicinal plants and humans as complex systems coherently coupled through recurrent interaction. Complex systems science provides the theoretical tenets that explain traditional knowledge of medicinal plants while supporting clinical practice and expanding research and documentation of WHM.

Heat-induced reorganization of the structure of photosystem II membranes: role of oxygen evolving complex.

Science.gov (United States)

Busheva, Mira; Tzonova, Iren; Stoitchkova, Katerina; Andreeva, Atanaska

2012-12-05

The sensitivity of the green plants' photosystem II (PSII) to high temperatures is investigated in PSII enriched membranes and in membranes, from which the oxygen evolving complex is removed. Using steady-state 77 K fluorescence and resonance Raman spectroscopy we analyze the interdependency between the temperature-driven changes in structure and energy distribution in the PSII supercomplex. The results show that the heat treatment induces different reduction of the 77 K fluorescence emission in both types of investigated membranes: (i) an additional considerable decrease of the overall fluorescence emission in Tris-washed membranes as compared to the native membranes; (ii) a transition point at 42°C(,) observed only in native membranes; (iii) a sharp reduction of the PSII core fluorescence in Tris-washed membranes at temperatures higher than 50°C; (iv) a 3 nm red-shift of F700 band's maximum in Tris-washed membranes already at 20°C and its further shift by 1 nm at temperature increase. Both treatments intensified their action by increasing the aggregation and dissociation of the peripheral light harvesting complexes. The oxygen-evolving complex, in addition to its main function to produce O(2), increases the thermal stability of PSII core by strengthening the connection between the core and the peripheral antenna proteins and by keeping their structural integrity. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

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.

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.

Complex Adaptive System of Systems (CASoS) Engineering Applications. Version 1.0.

Energy Technology Data Exchange (ETDEWEB)

Linebarger, John Michael; Maffitt, S. Louise (New Mexico Institute of Mining and Technology, Albuquerque, NM); Glass, Robert John, Jr.; Beyeler, Walter Eugene; Brown, Theresa Jean; Ames, Arlo Leroy

2011-10-01

Complex Adaptive Systems of Systems, or CASoS, are vastly complex eco-socio-economic-technical systems which we must understand to design a secure future for the nation and the world. Perturbations/disruptions in CASoS have the potential for far-reaching effects due to highly-saturated interdependencies and allied vulnerabilities to cascades in associated systems. The Phoenix initiative approaches this high-impact problem space as engineers, devising interventions (problem solutions) that influence CASoS to achieve specific aspirations. CASoS embody the world's biggest problems and greatest opportunities: applications to real world problems are the driving force of our effort. We are developing engineering theory and practice together to create a discipline that is grounded in reality, extends our understanding of how CASoS behave, and allows us to better control those behaviors. Through application to real-world problems, Phoenix is evolving CASoS Engineering principles while growing a community of practice and the CASoS engineers to populate it.

Phoenix : Complex Adaptive System of Systems (CASoS) engineering version 1.0.

Energy Technology Data Exchange (ETDEWEB)

Moore, Thomas W.; Quach, Tu-Thach; Detry, Richard Joseph; Conrad, Stephen Hamilton; Kelic, Andjelka; Starks, Shirley J.; Beyeler, Walter Eugene; Brodsky, Nancy S.; Verzi, Stephen J.; Brown, Theresa Jean; Glass, Robert John, Jr.; Sunderland, Daniel J.; Mitchell, Michael David; Ames, Arlo Leroy; Maffitt, S. Louise; Finley, Patrick D.; Russell, Eric Dean; Zagonel, Aldo A.; Reedy, Geoffrey E.; Mitchell, Roger A.; Corbet, Thomas Frank, Jr.; Linebarger, John Michael

2011-08-01

Complex Adaptive Systems of Systems, or CASoS, are vastly complex ecological, sociological, economic and/or technical systems which we must understand to design a secure future for the nation and the world. Perturbations/disruptions in CASoS have the potential for far-reaching effects due to pervasive interdependencies and attendant vulnerabilities to cascades in associated systems. Phoenix was initiated to address this high-impact problem space as engineers. Our overarching goals are maximizing security, maximizing health, and minimizing risk. We design interventions, or problem solutions, that influence CASoS to achieve specific aspirations. Through application to real-world problems, Phoenix is evolving the principles and discipline of CASoS Engineering while growing a community of practice and the CASoS engineers to populate it. Both grounded in reality and working to extend our understanding and control of that reality, Phoenix is at the same time a solution within a CASoS and a CASoS itself.

On the Critical Role of Divergent Selection in Evolvability

Directory of Open Access Journals (Sweden)

Joel Lehman

2016-08-01

Full Text Available An ambitious goal in evolutionary robotics is to evolve increasingly complex robotic behaviors with minimal human design effort. Reaching this goal requires evolutionary algorithms that can unlock from genetic encodings their latent potential for evolvability. One issue clouding this goal is conceptual confusion about evolvability, which often obscures the aspects of evolvability that are important or desirable. The danger from such confusion is that it may establish unrealistic goals for evolvability that prove unproductive in practice. An important issue separate from conceptual confusion is the common misalignment between selection and evolvability in evolutionary robotics. While more expressive encodings can represent higher-level adaptations (e.g. sexual reproduction or developmental systems that increase long-term evolutionary potential (i.e. evolvability, realizing such potential requires gradients of fitness and evolvability to align. In other words, selection is often a critical factor limiting increasing evolvability. Thus, drawing from a series of recent papers, this article seeks to both (1 clarify and focus the ways in which the term evolvability is used within artificial evolution, and (2 argue for the importance of one type of selection, i.e. divergent selection, for enabling evolvability. The main argument is that there is a fundamental connection between divergent selection and evolvability (on both the individual and population level that does not hold for typical goal-oriented selection. The conclusion is that selection pressure plays a critical role in realizing the potential for evolvability, and that divergent selection in particular provides a principled mechanism for encouraging evolvability in artificial evolution.

Theories and simulations of complex social systems

CERN Document Server

Mago, Vijay

2014-01-01

Research into social systems is challenging due to their complex nature. Traditional methods of analysis are often difficult to apply effectively as theories evolve over time. This can be due to a lack of appropriate data, or too much uncertainty. It can also be the result of problems which are not yet understood well enough in the general sense so that they can be classified, and an appropriate solution quickly identified. Simulation is one tool that deals well with these challenges, fits in well with the deductive process, and is useful for testing theory. This field is still relatively new, and much of the work is necessarily innovative, although it builds upon a rich and varied foundation. There are a number of existing modelling paradigms being applied to complex social systems research. Additionally, new methods and measures are being devised through the process of conducting research. We expect that readers will enjoy the collection of high quality research works from new and accomplished researchers. ...

The Similar Structures and Control Problems of Complex Systems

Institute of Scientific and Technical Information of China (English)

无

2002-01-01

In this paper, the naturally evolving complex systems, such as biotic and social ones, are considered. Focusing on their structures, a feature is noteworthy, i.e., the similarity in structures. The relations between the functions and behaviors of these systems and their similar structures will be studied. Owing to the management of social systems and the course of evolution of biotic systems may be regarded as control processes, the researches will be within the scope of control problems. Moreover, since it is difficult to model for biotic and social systems, it will start with the control problems of complex systems, possessing similar structures, in engineering.The obtained results show that for either linear or nonlinear systems and for a lot of control problemssimilar structures lead to a series of simplifications. In general, the original system may be decomposed into reduced amount of subsystems with lower dimensions and simpler structures. By virtue of such subsystems, the control problems of original system can be solved more simply.At last, it turns round to observe the biotic and social systems and some analyses are given.

The evolving definition of systemic arterial hypertension.

Science.gov (United States)

Ram, C Venkata S; Giles, Thomas D

2010-05-01

Systemic hypertension is an important risk factor for premature cardiovascular disease. Hypertension also contributes to excessive morbidity and mortality. Whereas excellent therapeutic options are available to treat hypertension, there is an unsettled issue about the very definition of hypertension. At what level of blood pressure should we treat hypertension? Does the definition of hypertension change in the presence of co-morbid conditions? This article covers in detail the evolving concepts in the diagnosis and management of hypertension.

基于区间不确定性水资源复杂系统的协调演化研究%Study on coordination evolvement of complex water resources system with interval uncertainty

Institute of Scientific and Technical Information of China (English)

韩雁; 黄跃飞; 王光谦; 王丽珍

2011-01-01

水资源系统是具有不确定性的复杂系统。本文通过分析水资源系统的复杂性与不确定性，构建了基于区间不确定条件下的水资源复杂系统协调演化分析方法。在利用主成分分析法得到子系统综合发展水平的基础上，采用系统的协调性指数模型来揭示系统间的相互关系，然后根据系统的信息熵得到其协调有序度，以此来反映水资源复杂系统的演化规律。以大连市为例的应用研究表明，观真实地揭示水资源复杂系统的演化区间及其发展趋势，指导意义。基于区间不确定性的水资源复杂系统协调演化，能够客对于实现区域水资源和社会经济的可持续发展具有重要指导意义。%Water resources system is a kind of complex system with great uncertainties. In this paper, a methodology for analyzing coordination degree of complex and uncertainty characteristics of water resources system is proposed. Based on interval uncertainty, a comprehensive development level of each subsystem in a water resources system with interval parameters could be obtained by using the Principal Component Analysis method. Then the mutual relationships between subsystems are obtained by using coordination exponent method. Finally, the order degree is determined by using information entropy to reveal the coordinated evolvement of complex water resources system. Such method has been applied to Dalian City and the resuits indicate that the coordinated evolvement of water resources system under uncertainty could objectively and factually reflect the evolutional interval and trend of a complex water resources system, which is important to decision-making for sustainable development of water resources and socio-economy.

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.

Biomimetic molecular design tools that learn, evolve, and adapt

Science.gov (United States)

2017-01-01

A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known “S curve”, with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine. PMID:28694872

Biomimetic molecular design tools that learn, evolve, and adapt

Directory of Open Access Journals (Sweden)

David A Winkler

2017-06-01

Full Text Available A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known “S curve”, with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine.

Complex Engineered Systems: A New Paradigm

Science.gov (United States)

Mina, Ali A.; Braha, Dan; Bar-Yam, Yaneer

Human history is often seen as an inexorable march towards greater complexity — in ideas, artifacts, social, political and economic systems, technology, and in the structure of life itself. While we do not have detailed knowledge of ancient times, it is reasonable to conclude that the average resident of New York City today faces a world of much greater complexity than the average denizen of Carthage or Tikal. A careful consideration of this change, however, suggests that most of it has occurred recently, and has been driven primarily by the emergence of technology as a force in human life. In the 4000 years separating the Indus Valley Civilization from 18th century Europe, human transportation evolved from the bullock cart to the hansom, and the methods of communication used by George Washington did not differ significantly from those used by Alexander or Rameses. The world has moved radically towards greater complexity in the last two centuries. We have moved from buggies and letter couriers to airplanes and the Internet — an increase in capacity, and through its diversity also in complexity, orders of magnitude greater than that accumulated through the rest of human history. In addition to creating iconic artifacts — the airplane, the car, the computer, the television, etc. — this change has had a profound effect on the scope of experience by creating massive, connected and multiultra- level systems — traffic networks, power grids, markets, multinational corporations — that defy analytical understanding and seem to have a life of their own. This is where complexity truly enters our lives.

Moving alcohol prevention research forward-Part I: introducing a complex systems paradigm.

Science.gov (United States)

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

2018-02-01

The drinking environment is a complex system consisting of a number of heterogeneous, evolving and interacting components, which exhibit circular causality and emergent properties. These characteristics reduce the efficacy of commonly used research approaches, which typically do not account for the underlying dynamic complexity of alcohol consumption and the interdependent nature of diverse factors influencing misuse over time. We use alcohol misuse among college students in the United States as an example for framing our argument for a complex systems paradigm. A complex systems paradigm, grounded in socio-ecological and complex systems theories and computational modeling and simulation, is introduced. Theoretical, conceptual, methodological and analytical underpinnings of this paradigm are described in the context of college drinking prevention research. The proposed complex systems paradigm can transcend limitations of traditional approaches, thereby fostering new directions in alcohol prevention research. By conceptualizing student alcohol misuse as a complex adaptive system, computational modeling and simulation methodologies and analytical techniques can be used. Moreover, use of participatory model-building approaches to generate simulation models can further increase stakeholder buy-in, understanding and policymaking. A complex systems paradigm for research into alcohol misuse can provide a holistic understanding of the underlying drinking environment and its long-term trajectory, which can elucidate high-leverage preventive interventions. © 2017 Society for the Study of Addiction.

Programming adaptive control to evolve increased metabolite production.

Science.gov (United States)

Chou, Howard H; Keasling, Jay D

2013-01-01

The complexity inherent in biological systems challenges efforts to rationally engineer novel phenotypes, especially those not amenable to high-throughput screens and selections. In nature, increased mutation rates generate diversity in a population that can lead to the evolution of new phenotypes. Here we construct an adaptive control system that increases the mutation rate in order to generate diversity in the population, and decreases the mutation rate as the concentration of a target metabolite increases. This system is called feedback-regulated evolution of phenotype (FREP), and is implemented with a sensor to gauge the concentration of a metabolite and an actuator to alter the mutation rate. To evolve certain novel traits that have no known natural sensors, we develop a framework to assemble synthetic transcription factors using metabolic enzymes and construct four different sensors that recognize isopentenyl diphosphate in bacteria and yeast. We verify FREP by evolving increased tyrosine and isoprenoid production.

Assessing the evolving fragility of the global food system

Science.gov (United States)

Puma, Michael J.; Bose, Satyajit; Chon, So Young; Cook, Benjamin I.

2015-02-01

The world food crisis in 2008 highlighted the susceptibility of the global food system to price shocks. Here we use annual staple food production and trade data from 1992-2009 to analyse the changing properties of the global food system. Over the 18 year study period, we show that the global food system is relatively homogeneous (85% of countries have low or marginal food self-sufficiency) and increases in complexity, with the number of global wheat and rice trade connections doubling and trade flows increasing by 42 and 90%, respectively. The increased connectivity and flows within these global trade networks suggest that the global food system is vulnerable to systemic disruptions, especially considering the tendency for exporting countries to switch to non-exporting states during times of food scarcity in the global markets. To test this hypothesis, we superimpose continental-scale disruptions on the wheat and rice trade networks. We find greater absolute reductions in global wheat and rice exports along with larger losses in network connectivity as the networks evolve due to disruptions in European wheat and Asian rice production. Importantly, our findings indicate that least developed countries suffer greater import losses in more connected networks through their increased dependence on imports for staple foods (due to these large-scale disturbances): mean (median) wheat losses as percentages of staple food supply are 8.9% (3.8%) for 1992-1996, increasing to 11% (5.7%) for 2005-2009. Over the same intervals, rice losses increase from 8.2% (2.2%) to 14% (5.2%). Our work indicates that policy efforts should focus on balancing the efficiency of international trade (and its associated specialization) with increased resilience of domestic production and global demand diversity.

Assessing the evolving fragility of the global food system

International Nuclear Information System (INIS)

Puma, Michael J; Bose, Satyajit; Chon, So Young; Cook, Benjamin I

2015-01-01

The world food crisis in 2008 highlighted the susceptibility of the global food system to price shocks. Here we use annual staple food production and trade data from 1992–2009 to analyse the changing properties of the global food system. Over the 18 year study period, we show that the global food system is relatively homogeneous (85% of countries have low or marginal food self-sufficiency) and increases in complexity, with the number of global wheat and rice trade connections doubling and trade flows increasing by 42 and 90%, respectively. The increased connectivity and flows within these global trade networks suggest that the global food system is vulnerable to systemic disruptions, especially considering the tendency for exporting countries to switch to non-exporting states during times of food scarcity in the global markets. To test this hypothesis, we superimpose continental-scale disruptions on the wheat and rice trade networks. We find greater absolute reductions in global wheat and rice exports along with larger losses in network connectivity as the networks evolve due to disruptions in European wheat and Asian rice production. Importantly, our findings indicate that least developed countries suffer greater import losses in more connected networks through their increased dependence on imports for staple foods (due to these large-scale disturbances): mean (median) wheat losses as percentages of staple food supply are 8.9% (3.8%) for 1992–1996, increasing to 11% (5.7%) for 2005–2009. Over the same intervals, rice losses increase from 8.2% (2.2%) to 14% (5.2%). Our work indicates that policy efforts should focus on balancing the efficiency of international trade (and its associated specialization) with increased resilience of domestic production and global demand diversity. (letter)

Assessing the Evolving Fragility of the Global Food System

Science.gov (United States)

Puma, Michael Joseph; Bose, Satyajit; Chon, So Young; Cook, Benjamin I.

2015-01-01

The world food crisis in 2008 highlighted the susceptibility of the global food system to price shocks. Here we use annual staple food production and trade data from 1992-2009 to analyse the changing properties of the global food system. Over the 18-year study period, we show that the global food system is relatively homogeneous (85 of countries have low or marginal food self-sufficiency) and increases in complexity, with the number of global wheat and rice trade connections doubling and trade flows increasing by 42 and 90, respectively. The increased connectivity and flows within these global trade networks suggest that the global food system is vulnerable to systemic disruptions, especially considering the tendency for exporting countries to switch to non-exporting states during times of food scarcity in the global markets. To test this hypothesis, we superimpose continental-scale disruptions on the wheat and rice trade networks. We find greater absolute reductions in global wheat and rice exports along with larger losses in network connectivity as the networks evolve due to disruptions in European wheat and Asian rice production. Importantly, our findings indicate that least developed countries suffer greater import losses in more connected networks through their increased dependence on imports for staple foods (due to these large-scale disturbances): mean (median) wheat losses as percentages of staple food supply are 8.9 (3.8) for 1992-1996, increasing to 11 (5.7) for 20052009. Over the same intervals, rice losses increase from 8.2 (2.2) to 14 (5.2). Our work indicates that policy efforts should focus on balancing the efficiency of international trade (and its associated specialization) with increased resilience of domestic production and global demand diversity.

Smart signal processing for an evolving electric grid

Science.gov (United States)

Silva, Leandro Rodrigues Manso; Duque, Calos Augusto; Ribeiro, Paulo F.

2015-12-01

Electric grids are interconnected complex systems consisting of generation, transmission, distribution, and active loads, recently called prosumers as they produce and consume electric energy. Additionally, these encompass a vast array of equipment such as machines, power transformers, capacitor banks, power electronic devices, motors, etc. that are continuously evolving in their demand characteristics. Given these conditions, signal processing is becoming an essential assessment tool to enable the engineer and researcher to understand, plan, design, and operate the complex and smart electronic grid of the future. This paper focuses on recent developments associated with signal processing applied to power system analysis in terms of characterization and diagnostics. The following techniques are reviewed and their characteristics and applications discussed: active power system monitoring, sparse representation of power system signal, real-time resampling, and time-frequency (i.e., wavelets) applied to power fluctuations.

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.

Evolving a Method to Capture Science Stakeholder Inputs to Optimize Instrument, Payload, and Program Design

Science.gov (United States)

Clark, P. E.; Rilee, M. L.; Curtis, S. A.; Bailin, S.

2012-03-01

We are developing Frontier, a highly adaptable, stably reconfigurable, web-accessible intelligent decision engine capable of optimizing design as well as the simulating operation of complex systems in response to evolving needs and environment.

Self-organization scenario acting as physical basis of intelligent complex systems created in laboratory

International Nuclear Information System (INIS)

Lozneanu, Erzilia; Sanduloviciu, Mircea

2006-01-01

The recognition of limits in the tendency to miniaturize the so-called self-organizing devices inspired scientists to seek inspiration from living organisms that operate with functional elements that employ thermal energy exploiting quantum phenomena. Here we show how such operations are performed by a complex space charge configuration emerged by self-organization in plasma. Endowed with a special kind of memory, the complexity is able to ensure its survival in a metastable state performing the operations 'learned' during its emergence by self-organization. Possessing memory, the complexity works as an intelligent system able to evolve under suitable environmental conditions

The interplay of evolved seawater and magmatic-hydrothermal fluids in the 3.24 Ga panorama volcanic-hosted massive sulfide hydrothermal system, North Pilbara Craton, Western Australia

Science.gov (United States)

Drieberg, Susan L.; Hagemann, Steffen G.; Huston, David L.; Landis, Gary; Ryan, Chris G.; Van Achterbergh, Esmé; Vennemann, Torsten

2013-01-01

The ~3240 Ma Panorama volcanic-hosted massive sulfide (VHMS) district is unusual for its high degree of exposure and low degree of postdepositional modification. In addition to typical seafloor VHMS deposits, this district contains greisen- and vein-hosted Mo-Cu-Zn-Sn mineral occurrences that are contemporaneous with VHMS orebodies and are hosted by the Strelley granite complex, which also drove VHMS circulation. Hence the Panorama district is a natural laboratory to investigate the role of magmatic-hydrothermal fluids in VHMS hydrothermal systems. Regional and proximal high-temperature alteration zones in volcanic rocks underlying the VHMS deposits are dominated by chlorite-quartz ± albite assemblages, with lesser low-temperature sericite-quartz ± K-feldspar assemblages. These assemblages are typical of VHMS hydrothermal systems. In contrast, the alteration assemblages associated with granite-hosted greisens and veins include quartz-topaz-muscovite-fluorite and quartz-muscovite (sericite)-chlorite-ankerite. These vein systems generally do not extend into the overlying volcanic pile. Fluid inclusion and stable isotope studies suggest that the greisens were produced by high-temperature (~590°C), high-salinity (38–56 wt % NaCl equiv) fluids with high densities (>1.3 g/cm3) and high δ18O (9.3 ± 0.6‰). These fluids are compatible with the measured characteristics of magmatic fluids evolved from the Strelley granite complex. In contrast, fluids in the volcanic pile (including the VHMS ore-forming fluids) were of lower temperature (90°–270°C), lower salinity (5.0–11.2 wt % NaCl equiv), with lower densities (0.88–1.01 g/cm3) and lower δ18O (−0.8 ± 2.6‰). These fluids are compatible with evolved Paleoarchean seawater. Fluids that formed the quartz-chalcopyrite-sphalerite-cassiterite veins, which are present within the granite complex near the contact with the volcanic pile, were intermediate in temperature and isotopic composition between the greisen

Building an evolvable prototype for a multiple GAAP accounting information system

NARCIS (Netherlands)

Vanhoof, E.; De Bruyn, P.; Aerts, Walter; Verelst, J.; Aveiro, D.; Pergl, R.; Gouveia, D.

In this paper we build a prototype of an evolvable Accounting Information System (AIS) that supports multiple Generally Accepted Accounting Standards (GAAP) reporting. Reporting in multiple GAAP can have different origins: differences in local and tax GAAP, belonging to an economic group or

MK classification of evolved blue stars in the halo

International Nuclear Information System (INIS)

Garrison, R.F.

1987-01-01

The problem of the masses and origin of the evolved blue stars is very complex. No single approach can give all the answers unambiguously; it would be naive to suppose otherwise. The MK process and the MK system give a perspective which complements photometric, kinematic, high dispersion and other quantitative data. It is useful to know which stars are similar (or not) in spectral morphology, so that interesting candidates can be selected for further study. In many cases, the gross physical characteristics can be fairly well determined by use of the MK System. 8 references

Empirical and theoretical analysis of complex systems

Science.gov (United States)

Zhao, Guannan

This thesis is an interdisciplinary work under the heading of complexity science which focuses on an arguably common "hard" problem across physics, finance and biology [1], to quantify and mimic the macroscopic "emergent phenomenon" in large-scale systems consisting of many interacting "particles" governed by microscopic rules. In contrast to traditional statistical physics, we are interested in systems whose dynamics are subject to feedback, evolution, adaption, openness, etc. Global financial markets, like the stock market and currency market, are ideal candidate systems for such a complexity study: there exists a vast amount of accurate data, which is the aggregate output of many autonomous agents continuously competing with each other. We started by examining the ultrafast "mini flash crash (MFC)" events in the US stock market. An abrupt system-wide composition transition from a mixed human machine phase to a new all-machine phase is uncovered, and a novel theory developed to explain this observation. Then in the study of FX market, we found an unexpected variation in the synchronicity of price changes in different market subsections as a function of the overall trading activity. Several survival models have been tested in analyzing the distribution of waiting times to the next price change. In the region of long waiting-times, the distribution for each currency pair exhibits a power law with exponent in the vicinity of 3.5. By contrast, for short waiting times only, the market activity can be mimicked by the fluctuations emerging from a finite resource competition model containing multiple agents with limited rationality (so called El Farol Model). Switching to the biomedical domain, we present a minimal mathematical model built around a co-evolving resource network and cell population, yielding good agreement with primary tumors in mice experiment and with clinical metastasis data. In the quest to understand contagion phenomena in systems where social group

A model for the emergence of cooperation, interdependence, and structure in evolving networks

Science.gov (United States)

Jain, Sanjay; Krishna, Sandeep

2001-01-01

Evolution produces complex and structured networks of interacting components in chemical, biological, and social systems. We describe a simple mathematical model for the evolution of an idealized chemical system to study how a network of cooperative molecular species arises and evolves to become more complex and structured. The network is modeled by a directed weighted graph whose positive and negative links represent "catalytic" and "inhibitory" interactions among the molecular species, and which evolves as the least populated species (typically those that go extinct) are replaced by new ones. A small autocatalytic set, appearing by chance, provides the seed for the spontaneous growth of connectivity and cooperation in the graph. A highly structured chemical organization arises inevitably as the autocatalytic set enlarges and percolates through the network in a short analytically determined timescale. This self organization does not require the presence of self-replicating species. The network also exhibits catastrophes over long timescales triggered by the chance elimination of "keystone" species, followed by recoveries.

Chemical Equilibrium Models for the S3 State of the Oxygen-Evolving Complex of Photosystem II.

Science.gov (United States)

Isobe, Hiroshi; Shoji, Mitsuo; Shen, Jian-Ren; Yamaguchi, Kizashi

2016-01-19

We have performed hybrid density functional theory (DFT) calculations to investigate how chemical equilibria can be described in the S3 state of the oxygen-evolving complex in photosystem II. For a chosen 340-atom model, 1 stable and 11 metastable intermediates have been identified within the range of 13 kcal mol(-1) that differ in protonation, charge, spin, and conformational states. The results imply that reversible interconversion of these intermediates gives rise to dynamic equilibria that involve processes with relocations of protons and electrons residing in the Mn4CaO5 cluster, as well as bound water ligands, with concomitant large changes in the cluster geometry. Such proton tautomerism and redox isomerism are responsible for reversible activation/deactivation processes of substrate oxygen species, through which Mn-O and O-O bonds are transiently ruptured and formed. These results may allow for a tentative interpretation of kinetic data on substrate water exchange on the order of seconds at room temperature, as measured by time-resolved mass spectrometry. The reliability of the hybrid DFT method for the multielectron redox reaction in such an intricate system is also addressed.

EVOLVE

CERN Document Server

Deutz, André; Schütze, Oliver; Legrand, Pierrick; Tantar, Emilia; Tantar, Alexandru-Adrian

2017-01-01

This book comprises nine selected works on numerical and computational methods for solving multiobjective optimization, game theory, and machine learning problems. It provides extended versions of selected papers from various fields of science such as computer science, mathematics and engineering that were presented at EVOLVE 2013 held in July 2013 at Leiden University in the Netherlands. The internationally peer-reviewed papers include original work on important topics in both theory and applications, such as the role of diversity in optimization, statistical approaches to combinatorial optimization, computational game theory, and cell mapping techniques for numerical landscape exploration. Applications focus on aspects including robustness, handling multiple objectives, and complex search spaces in engineering design and computational biology.

Modeling complexity in engineered infrastructure system: Water distribution network as an example

Science.gov (United States)

Zeng, Fang; Li, Xiang; Li, Ke

2017-02-01

The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.

The genotype-phenotype map of an evolving digital organism

OpenAIRE

Fortuna, Miguel A.; Zaman, Luis; Ofria, Charles; Wagner, Andreas

2017-01-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms fr...

ARC-VM: An architecture real options complexity-based valuation methodology for military systems-of-systems acquisitions

Science.gov (United States)

Domercant, Jean Charles

The combination of today's national security environment and mandated acquisition policies makes it necessary for military systems to interoperate with each other to greater degrees. This growing interdependency results in complex Systems-of-Systems (SoS) that only continue to grow in complexity to meet evolving capability needs. Thus, timely and affordable acquisition becomes more difficult, especially in the face of mounting budgetary pressures. To counter this, architecting principles must be applied to SoS design. The research objective is to develop an Architecture Real Options Complexity-Based Valuation Methodology (ARC-VM) suitable for acquisition-level decision making, where there is a stated desire for more informed tradeoffs between cost, schedule, and performance during the early phases of design. First, a framework is introduced to measure architecture complexity as it directly relates to military SoS. Development of the framework draws upon a diverse set of disciplines, including Complexity Science, software architecting, measurement theory, and utility theory. Next, a Real Options based valuation strategy is developed using techniques established for financial stock options that have recently been adapted for use in business and engineering decisions. The derived complexity measure provides architects with an objective measure of complexity that focuses on relevant complex system attributes. These attributes are related to the organization and distribution of SoS functionality and the sharing and processing of resources. The use of Real Options provides the necessary conceptual and visual framework to quantifiably and traceably combine measured architecture complexity, time-valued performance levels, as well as programmatic risks and uncertainties. An example suppression of enemy air defenses (SEAD) capability demonstrates the development and usefulness of the resulting architecture complexity & Real Options based valuation methodology. Different

Cumulative impacts of an evolving oil-field complex on the distribution of calving caribou

International Nuclear Information System (INIS)

Nellemann, C.; Cameron, R.D.

1998-01-01

A study was conducted to examine the relationship between caribou density and road density as one means of assessing the reaction of caribou to activities associated with the evolving Prudhoe Bay oil-field complex in Alaska. Aerial surveys from 1987 to 1992 have shown that caribou density is inversely related to road density. The effects of avoidance were most apparent in preferred rugged terrain which are important habitats for foraging during the calving period. Female calves were found to be much more sensitive to surface development than adult males and yearlings. The biggest disturbances were caused by initial road construction and related facilities. The recent displacement of some calving activity within the Kuparuk Development area may result in heightened competition for forage, increased risk of predation, and lower productivity of the herd. 43 refs., 3 tabs., 3 figs

Complexity science and leadership in healthcare.

Science.gov (United States)

Burns, J P

2001-10-01

The emerging field of complexity science offers an alternative leadership strategy for the chaotic, complex healthcare environment. A survey revealed that healthcare leaders intuitively support principles of complexity science. Leadership that uses complexity principles offers opportunities in the chaotic healthcare environment to focus less on prediction and control and more on fostering relationships and creating conditions in which complex adaptive systems can evolve to produce creative outcomes.

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.

Evolvability Is an Evolved Ability: The Coding Concept as the Arch-Unit of Natural Selection.

Science.gov (United States)

Janković, Srdja; Ćirković, Milan M

2016-03-01

Physical processes that characterize living matter are qualitatively distinct in that they involve encoding and transfer of specific types of information. Such information plays an active part in the control of events that are ultimately linked to the capacity of the system to persist and multiply. This algorithmicity of life is a key prerequisite for its Darwinian evolution, driven by natural selection acting upon stochastically arising variations of the encoded information. The concept of evolvability attempts to define the total capacity of a system to evolve new encoded traits under appropriate conditions, i.e., the accessible section of total morphological space. Since this is dependent on previously evolved regulatory networks that govern information flow in the system, evolvability itself may be regarded as an evolved ability. The way information is physically written, read and modified in living cells (the "coding concept") has not changed substantially during the whole history of the Earth's biosphere. This biosphere, be it alone or one of many, is, accordingly, itself a product of natural selection, since the overall evolvability conferred by its coding concept (nucleic acids as information carriers with the "rulebook of meanings" provided by codons, as well as all the subsystems that regulate various conditional information-reading modes) certainly played a key role in enabling this biosphere to survive up to the present, through alterations of planetary conditions, including at least five catastrophic events linked to major mass extinctions. We submit that, whatever the actual prebiotic physical and chemical processes may have been on our home planet, or may, in principle, occur at some time and place in the Universe, a particular coding concept, with its respective potential to give rise to a biosphere, or class of biospheres, of a certain evolvability, may itself be regarded as a unit (indeed the arch-unit) of natural selection.

Control of multidimensional systems on complex network

Science.gov (United States)

Bagnoli, Franco; Battistelli, Giorgio; Chisci, Luigi; Fanelli, Duccio

2017-01-01

Multidimensional systems coupled via complex networks are widespread in nature and thus frequently invoked for a large plethora of interesting applications. From ecology to physics, individual entities in mutual interactions are grouped in families, homogeneous in kind. These latter interact selectively, through a sequence of self-consistently regulated steps, whose deeply rooted architecture is stored in the assigned matrix of connections. The asymptotic equilibrium eventually attained by the system, and its associated stability, can be assessed by employing standard nonlinear dynamics tools. For many practical applications, it is however important to externally drive the system towards a desired equilibrium, which is resilient, hence stable, to external perturbations. To this end we here consider a system made up of N interacting populations which evolve according to general rate equations, bearing attributes of universality. One species is added to the pool of interacting families and used as a dynamical controller to induce novel stable equilibria. Use can be made of the root locus method to shape the needed control, in terms of intrinsic reactivity and adopted protocol of injection. The proposed method is tested on both synthetic and real data, thus enabling to demonstrate its robustness and versatility. PMID:28892493

Quality plan and configuration management in complex systems

International Nuclear Information System (INIS)

Gonzalez Junto, J.; Merchan Teyssiere

1993-01-01

Since the Second World War, the philosophy behind the quality systems of industries and service companies has evolved to embrace the whole life cycle of the product, system or service. In this evolution process, quality has become a strategic factor in the survival of entreprises. The first steps in trying to establish quality systems were taken for the armed forces, followed by space, aeronautical and nuclear projects, whose products were more and more complex and sophisticated. These systems were established by means of quality plans or programmes, and their basic objective was to guarantee a high safety level for the user and/or the general population. In later years, the main concern was to reach a determined quality level not only in one phase of the product life, but in the complete life cycle of the final product. Today a new goal is established and pursued: better quality of the product, service or system life cycle at a lower cost. Methods of improving the quality of systems and processes are the subject of numerous initiatives and studies, to better availability and maintainability of complex equipment or installations, with an extended useful life and greater requirements. Experience in the performance of complex projects shows that a higher quality may be obtained through designing a comprehensive quality plan which pays special attention to information management and modifications of the original design. Obtaining a high reliability level for an installation (equipment, systems, etc), increasing its availability and rationalizing its maintenance may be little less than fanciful without a deep knowledge of the installation, of its activities and its current status in day-to-day operation, which shows the importance of truthful information available to operators and corresponding exactly to their needs. In this frame of mind, a quality plan comprising a configuration management system of information and documents constitutes the basic support tool for

Natural selection promotes antigenic evolvability.

Science.gov (United States)

Graves, Christopher J; Ros, Vera I D; Stevenson, Brian; Sniegowski, Paul D; Brisson, Dustin

2013-01-01

The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed 'cassettes' that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios) and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish chronic infections.

Natural selection promotes antigenic evolvability.

Directory of Open Access Journals (Sweden)

Christopher J Graves

Full Text Available The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide an experimentally tractable system to test whether natural selection has favored mechanisms that increase evolvability. Many antigenic variation systems consist of paralogous unexpressed 'cassettes' that recombine into an expression site to rapidly alter the expressed protein. Importantly, the magnitude of antigenic change is a function of the genetic diversity among the unexpressed cassettes. Thus, evidence that selection favors among-cassette diversity is direct evidence that natural selection promotes antigenic evolvability. We used the Lyme disease bacterium, Borrelia burgdorferi, as a model to test the prediction that natural selection favors amino acid diversity among unexpressed vls cassettes and thereby promotes evolvability in a primary surface antigen, VlsE. The hypothesis that diversity among vls cassettes is favored by natural selection was supported in each B. burgdorferi strain analyzed using both classical (dN/dS ratios and Bayesian population genetic analyses of genetic sequence data. This hypothesis was also supported by the conservation of highly mutable tandem-repeat structures across B. burgdorferi strains despite a near complete absence of sequence conservation. Diversification among vls cassettes due to natural selection and mutable repeat structures promotes long-term antigenic evolvability of VlsE. These findings provide a direct demonstration that molecular mechanisms that enhance evolvability of surface antigens are an evolutionary adaptation. The molecular evolutionary processes identified here can serve as a model for the evolution of antigenic evolvability in many pathogens which utilize similar strategies to establish

On the Philosophy of Bitcoin/Blockchain Technology: Is it a Chaotic, Complex System?

OpenAIRE

Santos, Renato P. dos

2017-01-01

The philosophy of blockchain technology is concerned, among other things, with blockchain ontology, how it might be characterised, how it is being created, implemented, and adopted, how it operates in the world, and how it evolves over time. This paper concentrates on whether Bitcoin/blockchain can be considered a complex system and, if so, whether it is a chaotic one. Beyond mere academic curiosity, a positive response would raise concerns about the likelihood of Bitcoin/blockchain entering ...

The Systems Biology Research Tool: evolvable open-source software

Directory of Open Access Journals (Sweden)

Wright Jeremiah

2008-06-01

Full Text Available Abstract Background Research in the field of systems biology requires software for a variety of purposes. Software must be used to store, retrieve, analyze, and sometimes even to collect the data obtained from system-level (often high-throughput experiments. Software must also be used to implement mathematical models and algorithms required for simulation and theoretical predictions on the system-level. Results We introduce a free, easy-to-use, open-source, integrated software platform called the Systems Biology Research Tool (SBRT to facilitate the computational aspects of systems biology. The SBRT currently performs 35 methods for analyzing stoichiometric networks and 16 methods from fields such as graph theory, geometry, algebra, and combinatorics. New computational techniques can be added to the SBRT via process plug-ins, providing a high degree of evolvability and a unifying framework for software development in systems biology. Conclusion The Systems Biology Research Tool represents a technological advance for systems biology. This software can be used to make sophisticated computational techniques accessible to everyone (including those with no programming ability, to facilitate cooperation among researchers, and to expedite progress in the field of systems biology.

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

Science.gov (United States)

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

2008-01-01

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

A mysterious dust clump in a disk around an evolved binary star system.

Science.gov (United States)

Jura, M; Turner, J

1998-09-10

The discovery of planets in orbit around the pulsar PSR1257+12 shows that planets may form around post-main-sequence stars. Other evolved stars, such as HD44179 (an evolved star which is part of the binary system that has expelled the gas and dust that make the Red Rectangle nebula), possess gravitationally bound orbiting dust disks. It is possible that planets might form from gravitational collapse in such disks. Here we report high-angular-resolution observations at millimetre and submillimetre wavelengths of the dusk disk associated with the Red Rectangle. We find a dust clump with an estimated mass near that of Jupiter in the outer region of the disk. The clump is larger than our Solar System, and far beyond where planet formation would normally be expected, so its nature is at present unclear.

System Evolution Barriers and How to Overcome Them!

NARCIS (Netherlands)

Borches Juzgado, P.D.; Bonnema, Gerrit Maarten; Cloutier Sauser, B.; Gill, E.

2010-01-01

Creating complex systems from scratch is time consuming and costly, therefore a strategy often chosen by companies is to evolve existing systems. Yet evolving a system is also complicated. Complex systems are usually the result of multidisciplinary teams, therefore it is essential to understand

Dynamics of Large Systems of Nonlinearly Evolving Units

Science.gov (United States)

Lu, Zhixin

The dynamics of large systems of many nonlinearly evolving units is a general research area that has great importance for many areas in science and technology, including biology, computation by artificial neural networks, statistical mechanics, flocking in animal groups, the dynamics of coupled neurons in the brain, and many others. While universal principles and techniques are largely lacking in this broad area of research, there is still one particular phenomenon that seems to be broadly applicable. In particular, this is the idea of emergence, by which is meant macroscopic behaviors that "emerge" from a large system of many "smaller or simpler entities such that...large entities" [i.e., macroscopic behaviors] arise which "exhibit properties the smaller/simpler entities do not exhibit." In this thesis we investigate mechanisms and manifestations of emergence in four dynamical systems consisting many nonlinearly evolving units. These four systems are as follows. (a) We first study the motion of a large ensemble of many noninteracting particles in a slowly changing Hamiltonian system that undergoes a separatrix crossing. In such systems, we find that separatrix-crossing induces a counterintuitive effect. Specifically, numerical simulation of two sets of densely sprinkled initial conditions on two energy curves appears to suggest that the two energy curves, one originally enclosing the other, seemingly interchange their positions. This, however, is topologically forbidden. We resolve this paradox by introducing a numerical simulation method we call "robust" and study its consequences. (b) We next study the collective dynamics of oscillatory pacemaker neurons in Suprachiasmatic Nucleus (SCN), which, through synchrony, govern the circadian rhythm of mammals. We start from a high-dimensional description of the many coupled oscillatory neuronal units within the SCN. This description is based on a forced Kuramoto model. We then reduce the system dimensionality by using

EVOLVE 2014 International Conference

CERN Document Server

Tantar, Emilia; Sun, Jian-Qiao; Zhang, Wei; Ding, Qian; Schütze, Oliver; Emmerich, Michael; Legrand, Pierrick; Moral, Pierre; Coello, Carlos

2014-01-01

This volume encloses research articles that were presented at the EVOLVE 2014 International Conference in Beijing, China, July 1–4, 2014.The book gathers contributions that emerged from the conference tracks, ranging from probability to set oriented numerics and evolutionary computation; all complemented by the bridging purpose of the conference, e.g. Complex Networks and Landscape Analysis, or by the more application oriented perspective. The novelty of the volume, when considering the EVOLVE series, comes from targeting also the practitioner’s view. This is supported by the Machine Learning Applied to Networks and Practical Aspects of Evolutionary Algorithms tracks, providing surveys on new application areas, as in the networking area and useful insights in the development of evolutionary techniques, from a practitioner’s perspective. Complementary to these directions, the conference tracks supporting the volume, follow on the individual advancements of the subareas constituting the scope of the confe...

Revisiting Robustness and Evolvability: Evolution in Weighted Genotype Spaces

Science.gov (United States)

Partha, Raghavendran; Raman, Karthik

2014-01-01

Robustness and evolvability are highly intertwined properties of biological systems. The relationship between these properties determines how biological systems are able to withstand mutations and show variation in response to them. Computational studies have explored the relationship between these two properties using neutral networks of RNA sequences (genotype) and their secondary structures (phenotype) as a model system. However, these studies have assumed every mutation to a sequence to be equally likely; the differences in the likelihood of the occurrence of various mutations, and the consequence of probabilistic nature of the mutations in such a system have previously been ignored. Associating probabilities to mutations essentially results in the weighting of genotype space. We here perform a comparative analysis of weighted and unweighted neutral networks of RNA sequences, and subsequently explore the relationship between robustness and evolvability. We show that assuming an equal likelihood for all mutations (as in an unweighted network), underestimates robustness and overestimates evolvability of a system. In spite of discarding this assumption, we observe that a negative correlation between sequence (genotype) robustness and sequence evolvability persists, and also that structure (phenotype) robustness promotes structure evolvability, as observed in earlier studies using unweighted networks. We also study the effects of base composition bias on robustness and evolvability. Particularly, we explore the association between robustness and evolvability in a sequence space that is AU-rich – sequences with an AU content of 80% or higher, compared to a normal (unbiased) sequence space. We find that evolvability of both sequences and structures in an AU-rich space is lesser compared to the normal space, and robustness higher. We also observe that AU-rich populations evolving on neutral networks of phenotypes, can access less phenotypic variation compared to

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

A local-world evolving hypernetwork model

International Nuclear Information System (INIS)

Yang Guang-Yong; Liu Jian-Guo

2014-01-01

Complex hypernetworks are ubiquitous in the real system. It is very important to investigate the evolution mechanisms. In this paper, we present a local-world evolving hypernetwork model by taking into account the hyperedge growth and local-world hyperedge preferential attachment mechanisms. At each time step, a newly added hyperedge encircles a new coming node and a number of nodes from a randomly selected local world. The number of the selected nodes from the local world obeys the uniform distribution and its mean value is m. The analytical and simulation results show that the hyperdegree approximately obeys the power-law form and the exponent of hyperdegree distribution is γ = 2 + 1/m. Furthermore, we numerically investigate the node degree, hyperedge degree, clustering coefficient, as well as the average distance, and find that the hypernetwork model shares the scale-free and small-world properties, which shed some light for deeply understanding the evolution mechanism of the real systems. (interdisciplinary physics and related areas of science and technology)

Generalized Combination Complex Synchronization for Fractional-Order Chaotic Complex Systems

Directory of Open Access Journals (Sweden)

Cuimei Jiang

2015-07-01

Full Text Available Based on two fractional-order chaotic complex drive systems and one fractional-order chaotic complex response system with different dimensions, we propose generalized combination complex synchronization. In this new synchronization scheme, there are two complex scaling matrices that are non-square matrices. On the basis of the stability theory of fractional-order linear systems, we design a general controller via active control. Additionally, by virtue of two complex scaling matrices, generalized combination complex synchronization between fractional-order chaotic complex systems and real systems is investigated. Finally, three typical examples are given to demonstrate the effectiveness and feasibility of the schemes.

Nitrogen ligation to manganese in the photosynthetic oxygen-evolving complex: Continuous-wave and pulsed EPR studies of Photosystem II particles containing 14N or 15N

International Nuclear Information System (INIS)

DeRose, V.J.; Yachandra, V.K.; McDermott, A.E.; Britt, R.D.; Sauer, K.; Klein, M.P.

1991-01-01

The possibility of nitrogen ligation to the Mn in the oxygen-evolving complex from photosystem II was investigated with electron paramagnetic resonance (EPR) and electron spin echo envelope modulation (ESEEM) spectroscopies using 14 N- and 15 N-labeled preparations. Oxygen-evolving preparations were isolated from a thermophilic cyanobacterium, Synechococcus sp., grown on a medium containing either 14 NO 3 - or 15 NO - 3 as the sole source of nitrogen. The substructure on the multiline EPR signal, which arises from Mn in the S 2 state of the enzyme, was measured with continuous-wave EPR. No changes were detected in the substructure peak positions upon substitution of 15 N for 14 N, indicating that this substructure is not due to superhyperfine coupling from nitrogen ligands. To detect potential nitrogen ligands with superhyperfine couplings of lesser magnitude than could be observed with conventional EPR methods, electron spin-echo envelope modulation experiments were also performed on the multiline EPR signal. The Fourier transform of the light-minus-dark time domain ESEEM data shows a peak at 4.8 MHz in 14 N samples which is absent upon substitution with 15 N. This gives unambiguous evidence for weak hyperfine coupling of nitrogen to the Mn of the oxygen-evolving complex. Possible origins of this nitrogen interaction are discussed

Reframing the challenges to integrated care: a complex-adaptive systems perspective

Directory of Open Access Journals (Sweden)

Peter Tsasis

2012-09-01

Full Text Available Introduction: Despite over two decades of international experience and research on health systems integration, integrated care has not developed widely. We hypothesized that part of the problem may lie in how we conceptualize the integration process and the complex systems within which integrated care is enacted. This study aims to contribute to discourse regarding the relevance and utility of a complex-adaptive systems (CAS perspective on integrated care.Methods: In the Canadian province of Ontario, government mandated the development of fourteen Local Health Integration Networks in 2006. Against the backdrop of these efforts to integrate care, we collected focus group data from a diverse sample of healthcare professionals in the Greater Toronto Area using convenience and snowball sampling. A semi-structured interview guide was used to elicit participant views and experiences of health systems integration. We use a CAS framework to describe and analyze the data, and to assess the theoretical fit of a CAS perspective with the dominant themes in participant responses.Results: Our findings indicate that integration is challenged by system complexity, weak ties and poor alignment among professionals and organizations, a lack of funding incentives to support collaborative work, and a bureaucratic environment based on a command and control approach to management. Using a CAS framework, we identified several characteristics of CAS in our data, including diverse, interdependent and semi-autonomous actors; embedded co-evolutionary systems; emergent behaviours and non-linearity; and self-organizing capacity. Discussion and Conclusion: One possible explanation for the lack of systems change towards integration is that we have failed to treat the healthcare system as complex-adaptive. The data suggest that future integration initiatives must be anchored in a CAS perspective, and focus on building the system's capacity to self-organize. We conclude that

Reframing the challenges to integrated care: a complex-adaptive systems perspective

Directory of Open Access Journals (Sweden)

Peter Tsasis

2012-09-01

Full Text Available Introduction: Despite over two decades of international experience and research on health systems integration, integrated care has not developed widely. We hypothesized that part of the problem may lie in how we conceptualize the integration process and the complex systems within which integrated care is enacted. This study aims to contribute to discourse regarding the relevance and utility of a complex-adaptive systems (CAS perspective on integrated care. Methods: In the Canadian province of Ontario, government mandated the development of fourteen Local Health Integration Networks in 2006. Against the backdrop of these efforts to integrate care, we collected focus group data from a diverse sample of healthcare professionals in the Greater Toronto Area using convenience and snowball sampling. A semi-structured interview guide was used to elicit participant views and experiences of health systems integration. We use a CAS framework to describe and analyze the data, and to assess the theoretical fit of a CAS perspective with the dominant themes in participant responses. Results: Our findings indicate that integration is challenged by system complexity, weak ties and poor alignment among professionals and organizations, a lack of funding incentives to support collaborative work, and a bureaucratic environment based on a command and control approach to management. Using a CAS framework, we identified several characteristics of CAS in our data, including diverse, interdependent and semi-autonomous actors; embedded co-evolutionary systems; emergent behaviours and non-linearity; and self-organizing capacity.  Discussion and Conclusion: One possible explanation for the lack of systems change towards integration is that we have failed to treat the healthcare system as complex-adaptive. The data suggest that future integration initiatives must be anchored in a CAS perspective, and focus on building the system's capacity to self-organize. We conclude that

Trading Control Intelligence for Physical Intelligence: Muscle Drives in Evolved Virtual Creatures

DEFF Research Database (Denmark)

Lessin, Dan; Fussell, Don; Miikkulainen, Risto

2014-01-01

Traditional evolved virtual creatures [12] are actuated using unevolved, uniform, invisible drives at joints between rigid segments. In contrast, this paper shows how such conven- tional actuators can be replaced by evolvable muscle drives that are a part of the creature’s physical structure....... This design is important for two reasons: First, the con- trol intelligence is made visible in the purposeful develop- ment of muscle density, orientation, attachment points, and size. Second, the complexity that needs to be evolved for the brain to control the actuators is reduced, and in some cases can...... be essentially eliminated, thus freeing brain power for higher-level functions. Such designs may thus make it pos- sible to create more complex behavior than would otherwise be achievable....

A measurement system for large, complex software programs

Science.gov (United States)

Rone, Kyle Y.; Olson, Kitty M.; Davis, Nathan E.

1994-01-01

This paper describes measurement systems required to forecast, measure, and control activities for large, complex software development and support programs. Initial software cost and quality analysis provides the foundation for meaningful management decisions as a project evolves. In modeling the cost and quality of software systems, the relationship between the functionality, quality, cost, and schedule of the product must be considered. This explicit relationship is dictated by the criticality of the software being developed. This balance between cost and quality is a viable software engineering trade-off throughout the life cycle. Therefore, the ability to accurately estimate the cost and quality of software systems is essential to providing reliable software on time and within budget. Software cost models relate the product error rate to the percent of the project labor that is required for independent verification and validation. The criticality of the software determines which cost model is used to estimate the labor required to develop the software. Software quality models yield an expected error discovery rate based on the software size, criticality, software development environment, and the level of competence of the project and developers with respect to the processes being employed.

Ageing as a price of cooperation and complexity: self-organization of complex systems causes the gradual deterioration of constituent networks.

Science.gov (United States)

Kiss, Huba J M; Mihalik, Agoston; Nánási, Tibor; Ory, Bálint; Spiró, Zoltán; Soti, Csaba; Csermely, Peter

2009-06-01

The network concept is increasingly used for the description of complex systems. Here, we summarize key aspects of the evolvability and robustness of the hierarchical network set of macromolecules, cells, organisms and ecosystems. Listing the costs and benefits of cooperation as a necessary behaviour to build this network hierarchy, we outline the major hypothesis of the paper: the emergence of hierarchical complexity needs cooperation leading to the ageing (i.e. gradual deterioration) of the constituent networks. A stable environment develops cooperation leading to over-optimization, and forming an 'always-old' network, which accumulates damage, and dies in an apoptosis-like process. A rapidly changing environment develops competition forming a 'forever-young' network, which may suffer an occasional over-perturbation exhausting system resources, and causing death in a necrosis-like process. Giving a number of examples we demonstrate how cooperation evokes the gradual accumulation of damage typical to ageing. Finally, we show how various forms of cooperation and consequent ageing emerge as key elements in all major steps of evolution from the formation of protocells to the establishment of the globalized, modern human society.

EvoCommander: A Novel Game Based on Evolving and Switching Between Artificial Brains

DEFF Research Database (Denmark)

Jallov, D.; Risi, S.; Togelius, J.

2016-01-01

Neuroevolution (i.e. evolving artificial neural networks (ANNs) through evolutionary algorithms) has shown promise in evolving agents and robot controllers, which display complex behaviours and can adapt to their environments. These properties are also relevant to video games, since they can...

A Smart Mobile Lab-on-Chip-Based Medical Diagnostics System Architecture Designed For Evolvability

DEFF Research Database (Denmark)

Patou, François; Dimaki, Maria; Svendsen, Winnie Edith

2015-01-01

for this work. We introduce a smart-mobile and LoC-based system architecture designed for evolvability. By propagating LoC programmability, instrumentation, and control tools to the highlevel abstraction smart-mobile software layer, our architecture facilitates the realisation of new use...

Evolvability as a Quality Attribute of Software Architectures

NARCIS (Netherlands)

Ciraci, S.; van den Broek, P.M.; Duchien, Laurence; D'Hondt, Maja; Mens, Tom

We review the definition of evolvability as it appears on the literature. In particular, the concept of software evolvability is compared with other system quality attributes, such as adaptability, maintainability and modifiability.

Complex Adaptive Systems of Systems (CASOS) engineering environment.

Energy Technology Data Exchange (ETDEWEB)

Detry, Richard Joseph; Linebarger, John Michael; Finley, Patrick D.; Maffitt, S. Louise; Glass, Robert John, Jr.; Beyeler, Walter Eugene; Ames, Arlo Leroy

2012-02-01

Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.

Systemic Resilience of Complex Urban Systems

Directory of Open Access Journals (Sweden)

Serge Salat

2012-07-01

Full Text Available Two key paradigms emerge out of the variety of urban forms: certain cities resemble trees, others leaves. The structural difference between a tree and a leaf is huge: one is open, the other closed. Trees are entirely disconnected on a given scale: even if two twigs are spatially close, if they do not belong to the same branch, to go from one to the other implies moving down and then up all the hierarchy of branches.  Leaves on the contrary are entirely connected on intermediary scales. The veins of a leaf are disconnected on the two larger scales but entirely connected on the two or three following intermediary scales before presenting tiny tree-like structures on the finest capillary scales. Deltas are leaves not trees. Neither galaxies nor whirlpools are trees. We will see in this paper that historical cities, like leaves, deltas, galaxies, lungs, brains and vein systems are all fractal structures, multiply connected and complex on all scales. These structures display the same degree of complexity and connectivity, regardless of the magnification scale on which we observe them. We say that these structures are scale free. Mathematical fractal forms are often generated recursively by applying again and again the same generator to an initiator. The iteration creates an arborescence. But scale free structure is not synonymous with a recursive tree-like structure. The fractal structure of the leaf is much more complex than that of the tree by its multiconnectivity on three or more intermediary levels. In contrast, trees in the virgin forest, even when they seem to be entangled, horizontal, and rhizomic, have branches that are not interconnected to form a lattice. As we will see, the history of urban planning has evolved from leaf-like to tree-like patterns, with a consequent loss of efficiency and resilience. Indeed, in a closed foliar path structure, the formation of cycles enables internal complexification and flow fluctuations due to the

Measuring the Accuracy of Simple Evolving Connectionist System with Varying Distance Formulas

Science.gov (United States)

Al-Khowarizmi; Sitompul, O. S.; Suherman; Nababan, E. B.

2017-12-01

Simple Evolving Connectionist System (SECoS) is a minimal implementation of Evolving Connectionist Systems (ECoS) in artificial neural networks. The three-layer network architecture of the SECoS could be built based on the given input. In this study, the activation value for the SECoS learning process, which is commonly calculated using normalized Hamming distance, is also calculated using normalized Manhattan distance and normalized Euclidean distance in order to compare the smallest error value and best learning rate obtained. The accuracy of measurement resulted by the three distance formulas are calculated using mean absolute percentage error. In the training phase with several parameters, such as sensitivity threshold, error threshold, first learning rate, and second learning rate, it was found that normalized Euclidean distance is more accurate than both normalized Hamming distance and normalized Manhattan distance. In the case of beta fibrinogen gene -455 G/A polymorphism patients used as training data, the highest mean absolute percentage error value is obtained with normalized Manhattan distance compared to normalized Euclidean distance and normalized Hamming distance. However, the differences are very small that it can be concluded that the three distance formulas used in SECoS do not have a significant effect on the accuracy of the training results.

Evolvable Smartphone-Based Platforms for Point-of-Care In-Vitro Diagnostics Applications

Science.gov (United States)

Patou, François; AlZahra’a Alatraktchi, Fatima; Kjægaard, Claus; Dimaki, Maria; Madsen, Jan; Svendsen, Winnie E.

2016-01-01

The association of smart mobile devices and lab-on-chip technologies offers unprecedented opportunities for the emergence of direct-to-consumer in vitro medical diagnostics applications. Despite their clear transformative potential, obstacles remain to the large-scale disruption and long-lasting success of these systems in the consumer market. For instance, the increasing level of complexity of instrumented lab-on-chip devices, coupled to the sporadic nature of point-of-care testing, threatens the viability of a business model mainly relying on disposable/consumable lab-on-chips. We argued recently that system evolvability, defined as the design characteristic that facilitates more manageable transitions between system generations via the modification of an inherited design, can help remedy these limitations. In this paper, we discuss how platform-based design can constitute a formal entry point to the design and implementation of evolvable smart device/lab-on-chip systems. We present both a hardware/software design framework and the implementation details of a platform prototype enabling at this stage the interfacing of several lab-on-chip variants relying on current- or impedance-based biosensors. Our findings suggest that several change-enabling mechanisms implemented in the higher abstraction software layers of the system can promote evolvability, together with the design of change-absorbing hardware/software interfaces. Our platform architecture is based on a mobile software application programming interface coupled to a modular hardware accessory. It allows the specification of lab-on-chip operation and post-analytic functions at the mobile software layer. We demonstrate its potential by operating a simple lab-on-chip to carry out the detection of dopamine using various electroanalytical methods. PMID:27598208

Evolvable Smartphone-Based Platforms for Point-of-Care In-Vitro Diagnostics Applications.

Science.gov (United States)

Patou, François; AlZahra'a Alatraktchi, Fatima; Kjægaard, Claus; Dimaki, Maria; Madsen, Jan; Svendsen, Winnie E

2016-09-03

The association of smart mobile devices and lab-on-chip technologies offers unprecedented opportunities for the emergence of direct-to-consumer in vitro medical diagnostics applications. Despite their clear transformative potential, obstacles remain to the large-scale disruption and long-lasting success of these systems in the consumer market. For instance, the increasing level of complexity of instrumented lab-on-chip devices, coupled to the sporadic nature of point-of-care testing, threatens the viability of a business model mainly relying on disposable/consumable lab-on-chips. We argued recently that system evolvability, defined as the design characteristic that facilitates more manageable transitions between system generations via the modification of an inherited design, can help remedy these limitations. In this paper, we discuss how platform-based design can constitute a formal entry point to the design and implementation of evolvable smart device/lab-on-chip systems. We present both a hardware/software design framework and the implementation details of a platform prototype enabling at this stage the interfacing of several lab-on-chip variants relying on current- or impedance-based biosensors. Our findings suggest that several change-enabling mechanisms implemented in the higher abstraction software layers of the system can promote evolvability, together with the design of change-absorbing hardware/software interfaces. Our platform architecture is based on a mobile software application programming interface coupled to a modular hardware accessory. It allows the specification of lab-on-chip operation and post-analytic functions at the mobile software layer. We demonstrate its potential by operating a simple lab-on-chip to carry out the detection of dopamine using various electroanalytical methods.

Evolvable Smartphone-Based Platforms for Point-of-Care In-Vitro Diagnostics Applications

Directory of Open Access Journals (Sweden)

François Patou

2016-09-01

Full Text Available The association of smart mobile devices and lab-on-chip technologies offers unprecedented opportunities for the emergence of direct-to-consumer in vitro medical diagnostics applications. Despite their clear transformative potential, obstacles remain to the large-scale disruption and long-lasting success of these systems in the consumer market. For instance, the increasing level of complexity of instrumented lab-on-chip devices, coupled to the sporadic nature of point-of-care testing, threatens the viability of a business model mainly relying on disposable/consumable lab-on-chips. We argued recently that system evolvability, defined as the design characteristic that facilitates more manageable transitions between system generations via the modification of an inherited design, can help remedy these limitations. In this paper, we discuss how platform-based design can constitute a formal entry point to the design and implementation of evolvable smart device/lab-on-chip systems. We present both a hardware/software design framework and the implementation details of a platform prototype enabling at this stage the interfacing of several lab-on-chip variants relying on current- or impedance-based biosensors. Our findings suggest that several change-enabling mechanisms implemented in the higher abstraction software layers of the system can promote evolvability, together with the design of change-absorbing hardware/software interfaces. Our platform architecture is based on a mobile software application programming interface coupled to a modular hardware accessory. It allows the specification of lab-on-chip operation and post-analytic functions at the mobile software layer. We demonstrate its potential by operating a simple lab-on-chip to carry out the detection of dopamine using various electroanalytical methods.

Complex Adaptive Schools: Educational Leadership and School Change

Science.gov (United States)

Kershner, Brad; McQuillan, Patrick

2016-01-01

This paper utilizes the theoretical framework of complexity theory to compare and contrast leadership and educational change in two urban schools. Drawing on the notion of a complex adaptive system--an interdependent network of interacting elements that learns and evolves in adapting to an ever-shifting context--our case studies seek to reveal the…

High-resolution method for evolving complex interface networks

Science.gov (United States)

Pan, Shucheng; Hu, Xiangyu Y.; Adams, Nikolaus A.

2018-04-01

In this paper we describe a high-resolution transport formulation of the regional level-set approach for an improved prediction of the evolution of complex interface networks. The novelty of this method is twofold: (i) construction of local level sets and reconstruction of a global level set, (ii) local transport of the interface network by employing high-order spatial discretization schemes for improved representation of complex topologies. Various numerical test cases of multi-region flow problems, including triple-point advection, single vortex flow, mean curvature flow, normal driven flow, dry foam dynamics and shock-bubble interaction show that the method is accurate and suitable for a wide range of complex interface-network evolutions. Its overall computational cost is comparable to the Semi-Lagrangian regional level-set method while the prediction accuracy is significantly improved. The approach thus offers a viable alternative to previous interface-network level-set method.

Evolution of networks for body plan patterning; interplay of modularity, robustness and evolvability.

Directory of Open Access Journals (Sweden)

Kirsten H Ten Tusscher

2011-10-01

Full Text Available A major goal of evolutionary developmental biology (evo-devo is to understand how multicellular body plans of increasing complexity have evolved, and how the corresponding developmental programs are genetically encoded. It has been repeatedly argued that key to the evolution of increased body plan complexity is the modularity of the underlying developmental gene regulatory networks (GRNs. This modularity is considered essential for network robustness and evolvability. In our opinion, these ideas, appealing as they may sound, have not been sufficiently tested. Here we use computer simulations to study the evolution of GRNs' underlying body plan patterning. We select for body plan segmentation and differentiation, as these are considered to be major innovations in metazoan evolution. To allow modular networks to evolve, we independently select for segmentation and differentiation. We study both the occurrence and relation of robustness, evolvability and modularity of evolved networks. Interestingly, we observed two distinct evolutionary strategies to evolve a segmented, differentiated body plan. In the first strategy, first segments and then differentiation domains evolve (SF strategy. In the second scenario segments and domains evolve simultaneously (SS strategy. We demonstrate that under indirect selection for robustness the SF strategy becomes dominant. In addition, as a byproduct of this larger robustness, the SF strategy is also more evolvable. Finally, using a combined functional and architectural approach, we determine network modularity. We find that while SS networks generate segments and domains in an integrated manner, SF networks use largely independent modules to produce segments and domains. Surprisingly, we find that widely used, purely architectural methods for determining network modularity completely fail to establish this higher modularity of SF networks. Finally, we observe that, as a free side effect of evolving segmentation

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).

An evolving user-oriented model of Internet health information seeking.

Science.gov (United States)

Gaie, Martha J

2006-01-01

This paper presents an evolving user-oriented model of Internet health information seeking (IS) based on qualitative data collected from 22 lung cancer (LC) patients and caregivers. This evolving model represents information search behavior as more highly individualized, complex, and dynamic than previous models, including pre-search psychological activity, use of multiple heuristics throughout the process, and cost-benefit evaluation of search results. This study's findings suggest that IS occurs in four distinct phases: search initiation/continuation, selective exposure, message processing, and message evaluation. The identification of these phases and the heuristics used within them suggests a higher order of complexity in the decision-making processes that underlie IS, which could lead to the development of a conceptual framework that more closely reflects the complex nature of contextualized IS. It also illustrates the advantages of using qualitative methods to extract more subtle details of the IS process and fill in the gaps in existing models.

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

systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods

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

dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods

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

dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods

Extending Life Concepts to Complex Systems

Directory of Open Access Journals (Sweden)

Jean Le Fur

2013-01-01

Full Text Available There is still no consensus definition of complex systems. This article explores, as a heuristic approach, the possibility of using notions associated with life as transversal concepts for defining complex systems. This approach is developed within a general classification of systems, with complex systems considered as a general ‘living things’ category and living organisms as a specialised class within this category. Concepts associated with life are first explored in the context of complex systems: birth, death and lifetime, adaptation, ontogeny and growth, reproduction. Thereafter, a refutation approach is used to test the proposed classification against a set of diverse systems, including a reference case, edge cases and immaterial complex systems. The summary of this analysis is then used to generate a definition of complex systems, based on the proposal, and within the background of cybernetics, complex adaptive systems and biology. Using notions such as ‘birth’ or ‘lifespan’ as transversal concepts may be of heuristic value for the generic characterization of complex systems, opening up new lines of research for improving their definition.

Complex Systems Science for Subsurface Fate and Transport Report from the August 2009 Workshop

Energy Technology Data Exchange (ETDEWEB)

None

2010-03-01

The subsurface environment, which encompasses the vadose and saturated zones, is a heterogeneous, geologically complex domain. Believed to contain a large percentage of Earth's biomass in the form of microorganisms, the subsurface is a dynamic zone where important biogeochemical cycles work to sustain life. Actively linked to the atmosphere and biosphere through the hydrologic and carbon cycles, the subsurface serves as a storage location for much of Earth's fresh water. Coupled hydrological, microbiological, and geochemical processes occurring within the subsurface environment cause the local and regional natural chemical fluxes that govern water quality. These processes play a vital role in the formation of soil, economically important fossil fuels, mineral deposits, and other natural resources. Cleaning up Department of Energy (DOE) lands impacted by legacy wastes and using the subsurface for carbon sequestration or nuclear waste isolation require a firm understanding of these processes and the documented means to characterize the vertical and spatial distribution of subsurface properties directing water, nutrient, and contaminant flows. This information, along with credible, predictive models that integrate hydrological, microbiological, and geochemical knowledge over a range of scales, is needed to forecast the sustainability of subsurface water systems and to devise ways to manage and manipulate dynamic in situ processes for beneficial outcomes. Predictive models provide the context for knowledge integration. They are the primary tools for forecasting the evolving geochemistry or microbial ecology of groundwater under various scenarios and for assessing and optimizing the potential effectiveness of proposed approaches to carbon sequestration, waste isolation, or environmental remediation. An iterative approach of modeling and experimentation can reveal powerful insights into the behavior of subsurface systems. State-of-science understanding codified

Complex Systems Science for Subsurface Fate and Transport Report from the August 2009 Workshop

International Nuclear Information System (INIS)

2010-01-01

The subsurface environment, which encompasses the vadose and saturated zones, is a heterogeneous, geologically complex domain. Believed to contain a large percentage of Earth's biomass in the form of microorganisms, the subsurface is a dynamic zone where important biogeochemical cycles work to sustain life. Actively linked to the atmosphere and biosphere through the hydrologic and carbon cycles, the subsurface serves as a storage location for much of Earth's fresh water. Coupled hydrological, microbiological, and geochemical processes occurring within the subsurface environment cause the local and regional natural chemical fluxes that govern water quality. These processes play a vital role in the formation of soil, economically important fossil fuels, mineral deposits, and other natural resources. Cleaning up Department of Energy (DOE) lands impacted by legacy wastes and using the subsurface for carbon sequestration or nuclear waste isolation require a firm understanding of these processes and the documented means to characterize the vertical and spatial distribution of subsurface properties directing water, nutrient, and contaminant flows. This information, along with credible, predictive models that integrate hydrological, microbiological, and geochemical knowledge over a range of scales, is needed to forecast the sustainability of subsurface water systems and to devise ways to manage and manipulate dynamic in situ processes for beneficial outcomes. Predictive models provide the context for knowledge integration. They are the primary tools for forecasting the evolving geochemistry or microbial ecology of groundwater under various scenarios and for assessing and optimizing the potential effectiveness of proposed approaches to carbon sequestration, waste isolation, or environmental remediation. An iterative approach of modeling and experimentation can reveal powerful insights into the behavior of subsurface systems. State-of-science understanding codified in models

Applying a complex adaptive system's understanding of health to primary care [version 2; referees: 2 approved

Directory of Open Access Journals (Sweden)

Johannes Bircher

2016-09-01

Full Text Available This paper explores the diagnostic and therapeutic potential of a new concept of health. Investigations into the nature of health have led to a new definition that explains health as a complex adaptive system (CAS and is based on five components (a-e. Humans like all biological creatures must satisfactorily respond to (a the demands of life. For this purpose they need (b a biologically given potential (BGP and (c a personally acquired potential (PAP. These properties of individuals are embedded within (d social and (e environmental determinants of health. Between these five components of health there are 10 complex interactions that justify viewing health as a CAS. In each patient, the current state of health as a CAS evolved from the past, will move forward to a new future, and has to be analyzed and treated as an autonomous whole. A diagnostic procedure is suggested as follows: together with the patient, the five components and 10 complex interactions are assessed. This may help patients to better understand their situations and to recognize possible next steps that may be useful in order to evolve toward better health by themselves. In this process mutual trust in the patient-physician interaction is critical. The described approach offers new possibilities for helping patients improve their health prospects.

Governing Laws of Complex System Predictability under Co-evolving Uncertainty Sources: Theory and Nonlinear Geophysical Applications

Science.gov (United States)

Perdigão, R. A. P.

2017-12-01

Predictability assessments are traditionally made on a case-by-case basis, often by running the particular model of interest with randomly perturbed initial/boundary conditions and parameters, producing computationally expensive ensembles. These approaches provide a lumped statistical view of uncertainty evolution, without eliciting the fundamental processes and interactions at play in the uncertainty dynamics. In order to address these limitations, we introduce a systematic dynamical framework for predictability assessment and forecast, by analytically deriving governing equations of predictability in terms of the fundamental architecture of dynamical systems, independent of any particular problem under consideration. The framework further relates multiple uncertainty sources along with their coevolutionary interplay, enabling a comprehensive and explicit treatment of uncertainty dynamics along time, without requiring the actual model to be run. In doing so, computational resources are freed and a quick and effective a-priori systematic dynamic evaluation is made of predictability evolution and its challenges, including aspects in the model architecture and intervening variables that may require optimization ahead of initiating any model runs. It further brings out universal dynamic features in the error dynamics elusive to any case specific treatment, ultimately shedding fundamental light on the challenging issue of predictability. The formulated approach, framed with broad mathematical physics generality in mind, is then implemented in dynamic models of nonlinear geophysical systems with various degrees of complexity, in order to evaluate their limitations and provide informed assistance on how to optimize their design and improve their predictability in fundamental dynamical terms.

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 Systems: An Introduction

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 14; Issue 9. Complex Systems: An Introduction - Anthropic Principle, Terrestrial Complexity, Complex Materials. V K Wadhawan. General Article Volume 14 Issue 9 September 2009 pp 894-906 ...

Evolvability Search: Directly Selecting for Evolvability in order to Study and Produce It

DEFF Research Database (Denmark)

Mengistu, Henok; Lehman, Joel Anthony; Clune, Jeff

2016-01-01

of evolvable digital phenotypes. Although some types of selection in evolutionary computation indirectly encourage evolvability, one unexplored possibility is to directly select for evolvability. To do so, we estimate an individual's future potential for diversity by calculating the behavioral diversity of its...... immediate offspring, and select organisms with increased offspring variation. While the technique is computationally expensive, we hypothesized that direct selection would better encourage evolvability than indirect methods. Experiments in two evolutionary robotics domains confirm this hypothesis: in both...... domains, such Evolvability Search produces solutions with higher evolvability than those produced with Novelty Search or traditional objective-based search algorithms. Further experiments demonstrate that the higher evolvability produced by Evolvability Search in a training environment also generalizes...

Methods Evolved by Observation

Science.gov (United States)

Montessori, Maria

2016-01-01

Montessori's idea of the child's nature and the teacher's perceptiveness begins with amazing simplicity, and when she speaks of "methods evolved," she is unveiling a methodological system for observation. She begins with the early childhood explosion into writing, which is a familiar child phenomenon that Montessori has written about…

Complex Systems and Dependability

CERN Document Server

Zamojski, Wojciech; Sugier, Jaroslaw

2012-01-01

Typical contemporary complex system is a multifaceted amalgamation of technical, information, organization, software and human (users, administrators and management) resources. Complexity of such a system comes not only from its involved technical and organizational structure but mainly from complexity of information processes that must be implemented in the operational environment (data processing, monitoring, management, etc.). In such case traditional methods of reliability analysis focused mainly on technical level are usually insufficient in performance evaluation and more innovative meth

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...

Adaptive generalized combination complex synchronization of uncertain real and complex nonlinear systems

Energy Technology Data Exchange (ETDEWEB)

Wang, Shi-bing, E-mail: wang-shibing@dlut.edu.cn, E-mail: wangxy@dlut.edu.cn [School of Computer and Information Engineering, Fuyang Normal University, Fuyang 236041 (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xing-yuan, E-mail: wang-shibing@dlut.edu.cn, E-mail: wangxy@dlut.edu.cn [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xiu-you [School of Computer and Information Engineering, Fuyang Normal University, Fuyang 236041 (China); Zhou, Yu-fei [College of Electrical Engineering and Automation, Anhui University, Hefei 230601 (China)

2016-04-15

With comprehensive consideration of generalized synchronization, combination synchronization and adaptive control, this paper investigates a novel adaptive generalized combination complex synchronization (AGCCS) scheme for different real and complex nonlinear systems with unknown parameters. On the basis of Lyapunov stability theory and adaptive control, an AGCCS controller and parameter update laws are derived to achieve synchronization and parameter identification of two real drive systems and a complex response system, as well as two complex drive systems and a real response system. Two simulation examples, namely, ACGCS for chaotic real Lorenz and Chen systems driving a hyperchaotic complex Lü system, and hyperchaotic complex Lorenz and Chen systems driving a real chaotic Lü system, are presented to verify the feasibility and effectiveness of the proposed scheme.

Control of complex systems

CERN Document Server

Albertos, Pedro; Blanke, Mogens; Isidori, Alberto; Schaufelberger, Walter; Sanz, Ricardo

2001-01-01

The world of artificial systems is reaching complexity levels that es­ cape human understanding. Surface traffic, electricity distribution, air­ planes, mobile communications, etc. , are examples that demonstrate that we are running into problems that are beyond classical scientific or engi­ neering knowledge. There is an ongoing world-wide effort to understand these systems and develop models that can capture its behavior. The reason for this work is clear, if our lack of understanding deepens, we will lose our capability to control these systems and make they behave as we want. Researchers from many different fields are trying to understand and develop theories for complex man-made systems. This book presents re­ search from the perspective of control and systems theory. The book has grown out of activities in the research program Control of Complex Systems (COSY). The program has been sponsored by the Eu­ ropean Science Foundation (ESF) which for 25 years has been one of the leading players in stimula...

Synchronization in node of complex networks consist of complex chaotic system

Energy Technology Data Exchange (ETDEWEB)

Wei, Qiang, E-mail: qiangweibeihua@163.com [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024 (China); Xie, Cheng-jun [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Liu, Hong-jun [School of Information Engineering, Weifang Vocational College, Weifang, 261041 (China); Li, Yan-hui [The Library, Weifang Vocational College, Weifang, 261041 (China)

2014-07-15

A new synchronization method is investigated for node of complex networks consists of complex chaotic system. When complex networks realize synchronization, different component of complex state variable synchronize up to different scaling complex function by a designed complex feedback controller. This paper change synchronization scaling function from real field to complex field for synchronization in node of complex networks with complex chaotic system. Synchronization in constant delay and time-varying coupling delay complex networks are investigated, respectively. Numerical simulations are provided to show the effectiveness of the proposed method.

Multi-agent and complex systems

CERN Document Server

Ren, Fenghui; Fujita, Katsuhide; Zhang, Minjie; Ito, Takayuki

2017-01-01

This book provides a description of advanced multi-agent and artificial intelligence technologies for the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field. A complex system features a large number of interacting components, whose aggregate activities are nonlinear and self-organized. A multi-agent system is a group or society of agents which interact with others cooperatively and/or competitively in order to reach their individual or common goals. Multi-agent systems are suitable for modeling and simulation of complex systems, which is difficult to accomplish using traditional computational approaches.

European Conference on Complex Systems 2012

CERN Document Server

Kirkilionis, Markus; Nicolis, Gregoire

2013-01-01

The European Conference on Complex Systems, held under the patronage of the Complex Systems Society, is an annual event that has become the leading European conference devoted to complexity science. ECCS'12, its ninth edition, took place in Brussels, during the first week of September 2012. It gathered about 650 scholars representing a wide range of topics relating to complex systems research, with emphasis on interdisciplinary approaches. More specifically, the following tracks were covered:  1. Foundations of Complex Systems 2. Complexity, Information and Computation 3. Prediction, Policy and Planning, Environment 4. Biological Complexity 5. Interacting Populations, Collective Behavior 6. Social Systems, Economics and Finance This book contains a selection of the contributions presented at the conference and its satellite meetings. Its contents reflect the extent, diversity and richness of research areas in the field, both fundamental and applied.  

Intelligent systems engineering methodology

Science.gov (United States)

Fouse, Scott

1990-01-01

An added challenge for the designers of large scale systems such as Space Station Freedom is the appropriate incorporation of intelligent system technology (artificial intelligence, expert systems, knowledge-based systems, etc.) into their requirements and design. This presentation will describe a view of systems engineering which successfully addresses several aspects of this complex problem: design of large scale systems, design with requirements that are so complex they only completely unfold during the development of a baseline system and even then continue to evolve throughout the system's life cycle, design that involves the incorporation of new technologies, and design and development that takes place with many players in a distributed manner yet can be easily integrated to meet a single view of the requirements. The first generation of this methodology was developed and evolved jointly by ISX and the Lockheed Aeronautical Systems Company over the past five years on the Defense Advanced Research Projects Agency/Air Force Pilot's Associate Program, one of the largest, most complex, and most successful intelligent systems constructed to date. As the methodology has evolved it has also been applied successfully to a number of other projects. Some of the lessons learned from this experience may be applicable to Freedom.

Mathematical Creativity, Cohen Forcing, and Evolving Systems: Elements for a Case Study on Paul Cohen

Science.gov (United States)

Dickman, Benjamin

2013-01-01

The Evolving Systems approach to case studies due initially to Piaget-contemporary Howard Gruber, and complemented by subsequent work on sociocultural factors developed by Mihaly Csikszentmihalyi and others, provides an inroad for examining creative achievements in a variety of domains. This paper provides a proof of concept for how one might…

Reduction of Subjective and Objective System Complexity

Science.gov (United States)

Watson, Michael D.

2015-01-01

Occam's razor is often used in science to define the minimum criteria to establish a physical or philosophical idea or relationship. Albert Einstein is attributed the saying "everything should be made as simple as possible, but not simpler". These heuristic ideas are based on a belief that there is a minimum state or set of states for a given system or phenomena. In looking at system complexity, these heuristics point us to an idea that complexity can be reduced to a minimum. How then, do we approach a reduction in complexity? Complexity has been described as a subjective concept and an objective measure of a system. Subjective complexity is based on human cognitive comprehension of the functions and inter relationships of a system. Subjective complexity is defined by the ability to fully comprehend the system. Simplifying complexity, in a subjective sense, is thus gaining a deeper understanding of the system. As Apple's Jonathon Ive has stated," It's not just minimalism or the absence of clutter. It involves digging through the depth of complexity. To be truly simple, you have to go really deep". Simplicity is not the absence of complexity but a deeper understanding of complexity. Subjective complexity, based on this human comprehension, cannot then be discerned from the sociological concept of ignorance. The inability to comprehend a system can be either a lack of knowledge, an inability to understand the intricacies of a system, or both. Reduction in this sense is based purely on a cognitive ability to understand the system and no system then may be truly complex. From this view, education and experience seem to be the keys to reduction or eliminating complexity. Objective complexity, is the measure of the systems functions and interrelationships which exist independent of human comprehension. Jonathon Ive's statement does not say that complexity is removed, only that the complexity is understood. From this standpoint, reduction of complexity can be approached

On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach

Science.gov (United States)

Chen, Bor-Sen; Lin, Ying-Po

2011-01-01

In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563

Evolution and the complexity of bacteriophages.

Science.gov (United States)

Serwer, Philip

2007-03-13

The genomes of both long-genome (> 200 Kb) bacteriophages and long-genome eukaryotic viruses have cellular gene homologs whose selective advantage is not explained. These homologs add genomic and possibly biochemical complexity. Understanding their significance requires a definition of complexity that is more biochemically oriented than past empirically based definitions. Initially, I propose two biochemistry-oriented definitions of complexity: either decreased randomness or increased encoded information that does not serve immediate needs. Then, I make the assumption that these two definitions are equivalent. This assumption and recent data lead to the following four-part hypothesis that explains the presence of cellular gene homologs in long bacteriophage genomes and also provides a pathway for complexity increases in prokaryotic cells: (1) Prokaryotes underwent evolutionary increases in biochemical complexity after the eukaryote/prokaryote splits. (2) Some of the complexity increases occurred via multi-step, weak selection that was both protected from strong selection and accelerated by embedding evolving cellular genes in the genomes of bacteriophages and, presumably, also archaeal viruses (first tier selection). (3) The mechanisms for retaining cellular genes in viral genomes evolved under additional, longer-term selection that was stronger (second tier selection). (4) The second tier selection was based on increased access by prokaryotic cells to improved biochemical systems. This access was achieved when DNA transfer moved to prokaryotic cells both the more evolved genes and their more competitive and complex biochemical systems. I propose testing this hypothesis by controlled evolution in microbial communities to (1) determine the effects of deleting individual cellular gene homologs on the growth and evolution of long genome bacteriophages and hosts, (2) find the environmental conditions that select for the presence of cellular gene homologs, (3) determine

Evolution and the complexity of bacteriophages

Directory of Open Access Journals (Sweden)

Serwer Philip

2007-03-01

Full Text Available Abstract Background The genomes of both long-genome (> 200 Kb bacteriophages and long-genome eukaryotic viruses have cellular gene homologs whose selective advantage is not explained. These homologs add genomic and possibly biochemical complexity. Understanding their significance requires a definition of complexity that is more biochemically oriented than past empirically based definitions. Hypothesis Initially, I propose two biochemistry-oriented definitions of complexity: either decreased randomness or increased encoded information that does not serve immediate needs. Then, I make the assumption that these two definitions are equivalent. This assumption and recent data lead to the following four-part hypothesis that explains the presence of cellular gene homologs in long bacteriophage genomes and also provides a pathway for complexity increases in prokaryotic cells: (1 Prokaryotes underwent evolutionary increases in biochemical complexity after the eukaryote/prokaryote splits. (2 Some of the complexity increases occurred via multi-step, weak selection that was both protected from strong selection and accelerated by embedding evolving cellular genes in the genomes of bacteriophages and, presumably, also archaeal viruses (first tier selection. (3 The mechanisms for retaining cellular genes in viral genomes evolved under additional, longer-term selection that was stronger (second tier selection. (4 The second tier selection was based on increased access by prokaryotic cells to improved biochemical systems. This access was achieved when DNA transfer moved to prokaryotic cells both the more evolved genes and their more competitive and complex biochemical systems. Testing the hypothesis I propose testing this hypothesis by controlled evolution in microbial communities to (1 determine the effects of deleting individual cellular gene homologs on the growth and evolution of long genome bacteriophages and hosts, (2 find the environmental conditions that

XANES, EXAFS and Kbeta spectroscopic studies of the oxygen-evolving complex in Photosystem II

Energy Technology Data Exchange (ETDEWEB)

Robblee, John Henry [Univ. of California, Berkeley, CA (United States)

2000-12-01

A key question for the understanding of photosynthetic water oxidation is whether the four oxidizing equivalents necessary to oxidize water to dioxygen are accumulated on the four Mn ions of the oxygen evolving complex (OEC), or whether some ligand-centered oxidations take place before the formation and release of dioxygen during the S₃ → [S₄] → S₀ transition. Progress in instrumentation and flash sample preparation allowed us to apply Mn Kβ X-ray emission spectroscopy (Kb XES) to this problem for the first time. The Kβ XES results, in combination with Mn X-ray absorption near-edge structure (XANES) and electron paramagnetic resonance (EPR) data obtained from the same set of samples, show that the S₂ → S₃ transition, in contrast to the S₀ → S₁ and S₁ → S₂ transitions, does not involve a Mn-centered oxidation. This is rationalized by manganese μ-oxo bridge radical formation during the S₂ → S₃ transition. Using extended X-ray absorption fine structure (EXAFS) spectroscopy, the local environment of the Mn atoms in the S₀ state has been structurally characterized. These results show that the Mn-Mn distance in one of the di-μ-oxo-bridged Mn-Mn moieties increases from 2.7 Å in the S₁} state to 2.85 Å in the S₀ state. Furthermore, evidence is presented that shows three di-μ-oxo binuclear Mn₂ clusters may be present in the OEC, which is contrary to the widely held theory that two such clusters are present in the OEC. The EPR properties of the S₀ state have been investigated and a characteristic ''multiline'' signal in the S₀ state has been discovered in the presence of methanol. This provides the first direct confirmation that the native S₀ state is paramagnetic. In addition, this signal was simulated using parameters derived from three

Increase of Organization in Complex Systems

OpenAIRE

Georgiev, Georgi Yordanov; Daly, Michael; Gombos, Erin; Vinod, Amrit; Hoonjan, Gajinder

2013-01-01

Measures of complexity and entropy have not converged to a single quantitative description of levels of organization of complex systems. The need for such a measure is increasingly necessary in all disciplines studying complex systems. To address this problem, starting from the most fundamental principle in Physics, here a new measure for quantity of organization and rate of self-organization in complex systems based on the principle of least (stationary) action is applied to a model system -...

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 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.

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)

A complex systems approach to constructing better models for managing financial markets and the economy

Science.gov (United States)

Farmer, J. Doyne; Gallegati, M.; Hommes, C.; Kirman, A.; Ormerod, P.; Cincotti, S.; Sanchez, A.; Helbing, D.

2012-11-01

We outline a vision for an ambitious program to understand the economy and financial markets as a complex evolving system of coupled networks of interacting agents. This is a completely different vision from that currently used in most economic models. This view implies new challenges and opportunities for policy and managing economic crises. The dynamics of such models inherently involve sudden and sometimes dramatic changes of state. Further, the tools and approaches we use emphasize the analysis of crises rather than of calm periods. In this they respond directly to the calls of Governors Bernanke and Trichet for new approaches to macroeconomic modelling.

Life: Complexity and Diversity

Indian Academy of Sciences (India)

tinual increase in the diversity of life over evolutionary time. Ways of ... Centre for Ecological. Scienc'es .... plants evolved flowers to attract pollinators and reward them with .... with the evolving complexity of their interactions in communi- ties.

Integration of Life Cycle Assessment Into Agent-Based Modeling : Toward Informed Decisions on Evolving Infrastructure Systems

NARCIS (Netherlands)

Davis, C.B.; Nikoli?, I.; Dijkema, G.P.J.

2009-01-01

A method is presented that allows for a life cycle assessment (LCA) to provide environmental information on an energy infrastructure system while it evolves. Energy conversion facilities are represented in an agent-based model (ABM) as distinct instances of technologies with owners capable of making

A modeling process to understand complex system architectures

Science.gov (United States)

Robinson, Santiago Balestrini

2009-12-01

architectures is better more than 98% of the time. The second objective led to Hypothesis B, the second of the main hypotheses. This hypothesis stated that by studying the functional relations, the most critical entities composing the architecture could be identified. The critical entities are those that when their behavior varies slightly, the behavior of the overall architecture varies greatly. These are the entities that must be modeled more carefully and where modeling effort should be expended. This hypothesis was tested by simplifying agent-based models to the non-trivial minimum, and executing a large number of different simulations in order to obtain statistically significant results. The tests were conducted by evolving the complex model without any error induced, and then evolving the model once again for each ranking and assigning error to any of the nodes with a probability inversely proportional to the ranking. The results from this hypothesis test indicate that depending on the structural characteristics of the functional relations, it is useful to use one of two of the intelligent rankings tested, or it is best to expend effort equally amongst all the entities. Random ranking always performed worse than uniform ranking, indicating that if modeling effort is to be prioritized amongst the entities composing the large-scale system architecture, it should be prioritized intelligently. The benefit threshold between intelligent prioritization and no prioritization lays on the large-scale system's chaotic boundary. If the large-scale system behaves chaotically, small variations in any of the entities tends to have a great impact on the behavior of the entire system. Therefore, even low ranking entities can still affect the behavior of the model greatly, and error should not be concentrated in any one entity. It was discovered that the threshold can be identified from studying the structure of the networks, in particular the cyclicity, the Off-diagonal Complexity, and

Marshal: Maintaining Evolving Models, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — SIFT proposes to design and develop the Marshal system, a mixed-initiative tool for maintaining task models over the course of evolving missions. Marshal-enabled...

On the efficacy of cinema, or what the visual system did not evolve to do

Science.gov (United States)

Cutting, James E.

1989-01-01

Spatial displays, and a constraint that they do not place on the use of spatial instruments are discussed. Much of the work done in visual perception by psychologists and by computer scientists has concerned displays that show the motion of rigid objects. Typically, if one assumes that objects are rigid, one can then proceed to understand how the constant shape of the object can be perceived (or computed) as it moves through space. The author maintains that photographs and cinema are visual displays that are also powerful forms of art. Their efficacy, in part, stems from the fact that, although viewpoint is constrained when composing them, it is not nearly so constrained when viewing them. It is obvious, according to the author, that human visual systems did not evolve to watch movies or look at photographs. Thus, what photographs and movies present must be allowed in the rule-governed system under which vision evolved. Machine-vision algorithms, to be applicable to human vision, should show the same types of tolerance.

Complexity in Dynamical Systems

Science.gov (United States)

Moore, Cristopher David

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

Complex logistics audit system

Directory of Open Access Journals (Sweden)

Zuzana Marková

2010-02-01

Full Text Available Complex logistics audit system is a tool for realization of logistical audit in the company. The current methods for logistics auditare based on “ad hok” analysis of logisticsl system. This paper describes system for complex logistics audit. It is a global diagnosticsof logistics processes and functions of enterprise. The goal of logistics audit is to provide comparative documentation for managementabout state of logistics in company and to show the potential of logistics changes in order to achieve more effective companyperformance.

Snake venoms are integrated systems, but abundant venom proteins evolve more rapidly.

Science.gov (United States)

Aird, Steven D; Aggarwal, Shikha; Villar-Briones, Alejandro; Tin, Mandy Man-Ying; Terada, Kouki; Mikheyev, Alexander S

2015-08-28

While many studies have shown that extracellular proteins evolve rapidly, how selection acts on them remains poorly understood. We used snake venoms to understand the interaction between ecology, expression level, and evolutionary rate in secreted protein systems. Venomous snakes employ well-integrated systems of proteins and organic constituents to immobilize prey. Venoms are generally optimized to subdue preferred prey more effectively than non-prey, and many venom protein families manifest positive selection and rapid gene family diversification. Although previous studies have illuminated how individual venom protein families evolve, how selection acts on venoms as integrated systems, is unknown. Using next-generation transcriptome sequencing and mass spectrometry, we examined microevolution in two pitvipers, allopatrically separated for at least 1.6 million years, and their hybrids. Transcriptomes of parental species had generally similar compositions in regard to protein families, but for a given protein family, the homologs present and concentrations thereof sometimes differed dramatically. For instance, a phospholipase A2 transcript comprising 73.4 % of the Protobothrops elegans transcriptome, was barely present in the P. flavoviridis transcriptome (king cobra genome, suggesting that rapid evolution of abundant proteins may be generally true for snake venoms. Looking more broadly at Protobothrops, we show that rapid evolution of the most abundant components is due to positive selection, suggesting an interplay between abundance and adaptation. Given log-scale differences in toxin abundance, which are likely correlated with biosynthetic costs, we hypothesize that as a result of natural selection, snakes optimize return on energetic investment by producing more of venom proteins that increase their fitness. Natural selection then acts on the additive genetic variance of these components, in proportion to their contributions to overall fitness. Adaptive

Measuring Complexity of SAP Systems

Directory of Open Access Journals (Sweden)

Ilja Holub

2016-10-01

Full Text Available The paper discusses the reasons of complexity rise in ERP system SAP R/3. It proposes a method for measuring complexity of SAP. Based on this method, the computer program in ABAP for measuring complexity of particular SAP implementation is proposed as a tool for keeping ERP complexity under control. The main principle of the measurement method is counting the number of items or relations in the system. The proposed computer program is based on counting of records in organization tables in SAP.

European Conference on Complex Systems

CERN Document Server

Pellegrini, Francesco; Caldarelli, Guido; Merelli, Emanuela

2016-01-01

This work contains a stringent selection of extended contributions presented at the meeting of 2014 and its satellite meetings, reflecting scope, diversity and richness of research areas in the field, both fundamental and applied. The ECCS meeting, held under the patronage of the Complex Systems Society, is an annual event that has become the leading European conference devoted to complexity science. It offers cutting edge research and unique opportunities to study novel scientific approaches in a multitude of application areas. ECCS'14, its eleventh occurrence, took place in Lucca, Italy. It gathered some 650 scholars representing a wide range of topics relating to complex systems research, with emphasis on interdisciplinary approaches. The editors are among the best specialists in the area. The book is of great interest to scientists, researchers and graduate students in complexity, complex systems and networks.

Third International Conference on Complex Systems

CERN Document Server

Minai, Ali A; Unifying Themes in Complex Systems

2006-01-01

In recent years, scientists have applied the principles of complex systems science to increasingly diverse fields. The results have been nothing short of remarkable: their novel approaches have provided answers to long-standing questions in biology, ecology, physics, engineering, computer science, economics, psychology and sociology. The Third International Conference on Complex Systems attracted over 400 researchers from around the world. The conference aimed to encourage cross-fertilization between the many disciplines represented and to deepen our understanding of the properties common to all complex systems. This volume contains over 35 papers selected from those presented at the conference on topics including: self-organization in biology, ecological systems, language, economic modeling, ecological systems, artificial life, robotics, and complexity and art. ALI MINAI is an Affiliate of the New England Complex Systems Institute and an Associate Professor in the Department of Electrical and Computer Engine...

Why, when and where did honey bee dance communication evolve?

Directory of Open Access Journals (Sweden)

Robbie eI'Anson Price

2015-11-01

Full Text Available Honey bees (Apis sp. are the only known bee genus that uses nest-based communication to provide nest-mates with information about the location of resources, the so-called dance language. Successful foragers perform waggle dances for high quality food sources and suitable nest-sites during swarming. However, since many species of social insects do not communicate the location of resources to their nest-mates, the question of why the dance language evolved is of ongoing interest. We review recent theoretical and empirical research into the ecological circumstances that make dance communication beneficial in present day environments. This research suggests that the dance language is most beneficial when food sources differ greatly in quality and are hard to find. The dances of extant honey bee species differ in important ways, and phylogenetic studies suggest an increase in dance complexity over time: species with the least complex dance were the first to appear and species with the most complex dance are the most derived. We review the fossil record of honey bees and speculate about the time and context (foraging vs. swarming in which spatially referential dance communication might have evolved. We conclude that there are few certainties about when the dance language first appeared; dance communication could be older than 40 million years and, thus, predate the genus Apis, or it could be as recent as 20 million years when extant honey bee species diverged during the early Miocene. The most parsimonious scenario assumes it evolved in a sub-tropical to temperate climate, with patchy vegetation somewhere in Eurasia.

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.

Maintaining evolvability.

Science.gov (United States)

Crow, James F

2008-12-01

is yet to be determined. It is likely that only a case-by-case analysis will provide the answers. Despite the difficulties that complex interactions cause for evolution in Mendelian populations, such populations nevertheless evolve very well. Longlasting species must have evolved mechanisms for coping with such problems. Since such difficulties do not arise in asexual populations, a comparison of epistatic patterns in closely related sexual and asexual species might provide some important insights.

Use of the parameterised finite element method to robustly and efficiently evolve the edge of a moving cell.

Science.gov (United States)

Neilson, Matthew P; Mackenzie, John A; Webb, Steven D; Insall, Robert H

2010-11-01

In this paper we present a computational tool that enables the simulation of mathematical models of cell migration and chemotaxis on an evolving cell membrane. Recent models require the numerical solution of systems of reaction-diffusion equations on the evolving cell membrane and then the solution state is used to drive the evolution of the cell edge. Previous work involved moving the cell edge using a level set method (LSM). However, the LSM is computationally very expensive, which severely limits the practical usefulness of the algorithm. To address this issue, we have employed the parameterised finite element method (PFEM) as an alternative method for evolving a cell boundary. We show that the PFEM is far more efficient and robust than the LSM. We therefore suggest that the PFEM potentially has an essential role to play in computational modelling efforts towards the understanding of many of the complex issues related to chemotaxis.

Bose-Einstein Condensation in Complex Networks

International Nuclear Information System (INIS)

Bianconi, Ginestra; Barabasi, Albert-Laszlo

2001-01-01

The evolution of many complex systems, including the World Wide Web, business, and citation networks, is encoded in the dynamic web describing the interactions between the system's constituents. Despite their irreversible and nonequilibrium nature these networks follow Bose statistics and can undergo Bose-Einstein condensation. Addressing the dynamical properties of these nonequilibrium systems within the framework of equilibrium quantum gases predicts that the 'first-mover-advantage,' 'fit-get-rich,' and 'winner-takes-all' phenomena observed in competitive systems are thermodynamically distinct phases of the underlying evolving networks

Evolvable mathematical models: A new artificial Intelligence paradigm

Science.gov (United States)

Grouchy, Paul

We develop a novel Artificial Intelligence paradigm to generate autonomously artificial agents as mathematical models of behaviour. Agent/environment inputs are mapped to agent outputs via equation trees which are evolved in a manner similar to Symbolic Regression in Genetic Programming. Equations are comprised of only the four basic mathematical operators, addition, subtraction, multiplication and division, as well as input and output variables and constants. From these operations, equations can be constructed that approximate any analytic function. These Evolvable Mathematical Models (EMMs) are tested and compared to their Artificial Neural Network (ANN) counterparts on two benchmarking tasks: the double-pole balancing without velocity information benchmark and the challenging discrete Double-T Maze experiments with homing. The results from these experiments show that EMMs are capable of solving tasks typically solved by ANNs, and that they have the ability to produce agents that demonstrate learning behaviours. To further explore the capabilities of EMMs, as well as to investigate the evolutionary origins of communication, we develop NoiseWorld, an Artificial Life simulation in which interagent communication emerges and evolves from initially noncommunicating EMM-based agents. Agents develop the capability to transmit their x and y position information over a one-dimensional channel via a complex, dialogue-based communication scheme. These evolved communication schemes are analyzed and their evolutionary trajectories examined, yielding significant insight into the emergence and subsequent evolution of cooperative communication. Evolved agents from NoiseWorld are successfully transferred onto physical robots, demonstrating the transferability of EMM-based AIs from simulation into physical reality.

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...

Large-scale Complex IT Systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2011-01-01

This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that identifies the major challen...

Large-scale complex IT systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2012-01-01

12 pages, 2 figures This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that ident...

Polystochastic Models for Complexity

CERN Document Server

Iordache, Octavian

2010-01-01

This book is devoted to complexity understanding and management, considered as the main source of efficiency and prosperity for the next decades. Divided into six chapters, the book begins with a presentation of basic concepts as complexity, emergence and closure. The second chapter looks to methods and introduces polystochastic models, the wave equation, possibilities and entropy. The third chapter focusing on physical and chemical systems analyzes flow-sheet synthesis, cyclic operations of separation, drug delivery systems and entropy production. Biomimetic systems represent the main objective of the fourth chapter. Case studies refer to bio-inspired calculation methods, to the role of artificial genetic codes, neural networks and neural codes for evolutionary calculus and for evolvable circuits as biomimetic devices. The fifth chapter, taking its inspiration from systems sciences and cognitive sciences looks to engineering design, case base reasoning methods, failure analysis, and multi-agent manufacturing...

5th International Conference on Complex Systems

CERN Document Server

Braha, Dan; Bar-Yam, Yaneer

2011-01-01

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 common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.

7th International Conference on Complex Systems

CERN Document Server

Braha, Dan; Bar-Yam, Yaneer

2012-01-01

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 common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.

Evolved stars as complex chemical laboratories - the quest for gaseous chemistry

Science.gov (United States)

Katrien Els Decin, Leen

2015-08-01

At the end of their life, most stars lose a large fraction of their mass through a stellar wind. The stellar winds of evolved (super)giant stars are the dominant suppliers for the pristine building blocks of the interstellar medium (ISM). Crucial to the understanding of the chemical life cycle of the ISM is hence a profound insight in the chemical and physical structure governing these stellar winds.These winds are really unique chemical laboratories in which currently more than 70 different molecules and 15 different dust species are detected. Several chemical processes such as neutral-neutral and ion-molecule gas-phase reactions, dust nucleation and growth, and photo-processes determine the chemical content of these winds. However, gas-phase and dust-nucleation chemistry for astronomical environments still faces many challenges. One should realize that only ˜15% of the rate coefficients for gas-phase reactions considered to occur in (inter/circum)stellar regions at temperatures (T) below 300K have been subject to direct laboratory determinations and that the temperature dependence of the rate constants is often not known; only ˜2% have rate constants at Tgrant, we are now in the position to solve some riddles involved in understanding the gas-phase chemistry in evolved stars. In this presentation, I will demonstrate the need for accurate temperature-dependent gas-phase reaction rate constants and will present our new laboratory equipment built to measure the rate constants for species key in stellar wind chemistry. Specifically, we aim to obtain the rate constants of reactions involving silicon- and sulphur bearing species and HCCO for 30

Reliability of large and complex systems

CERN Document Server

Kolowrocki, Krzysztof

2014-01-01

Reliability of Large and Complex Systems, previously titled Reliability of Large Systems, is an innovative guide to the current state and reliability of large and complex systems. In addition to revised and updated content on the complexity and safety of large and complex mechanisms, this new edition looks at the reliability of nanosystems, a key research topic in nanotechnology science. The author discusses the importance of safety investigation of critical infrastructures that have aged or have been exposed to varying operational conditions. This reference provides an asympt

Geographical National Condition and Complex System

Directory of Open Access Journals (Sweden)

WANG Jiayao

2016-01-01

Full Text Available The significance of studying the complex system of geographical national conditions lies in rationally expressing the complex relationships of the “resources-environment-ecology-economy-society” system. Aiming to the problems faced by the statistical analysis of geographical national conditions, including the disunity of research contents, the inconsistency of range, the uncertainty of goals, etc.the present paper conducted a range of discussions from the perspectives of concept, theory and method, and designed some solutions based on the complex system theory and coordination degree analysis methods.By analyzing the concepts of geographical national conditions, geographical national conditions survey and geographical national conditions statistical analysis, as well as investigating the relationships between theirs, the statistical contents and the analytical range of geographical national conditions are clarified and defined. This investigation also clarifies the goals of the statistical analysis by analyzing the basic characteristics of the geographical national conditions and the complex system, and the consistency between the analysis of the degree of coordination and statistical analyses. It outlines their goals, proposes a concept for the complex system of geographical national conditions, and it describes the concept. The complex system theory provides new theoretical guidance for the statistical analysis of geographical national conditions. The degree of coordination offers new approaches on how to undertake the analysis based on the measurement method and decision-making analysis scheme upon which the complex system of geographical national conditions is based. It analyzes the overall trend via the degree of coordination of the complex system on a macro level, and it determines the direction of remediation on a micro level based on the degree of coordination among various subsystems and of single systems. These results establish

Characterization of the Sr(2+)- and Cd(2+)-Substituted Oxygen-Evolving Complex of Photosystem II by Quantum Mechanics/Molecular Mechanics Calculations.

Science.gov (United States)

Pitari, Fabio; Bovi, Daniele; Narzi, Daniele; Guidoni, Leonardo

2015-09-29

The Mn4CaO5 cluster in the oxygen-evolving complex is the catalytic core of the Photosystem II (PSII) enzyme, responsible for the water splitting reaction in oxygenic photosynthesis. The role of the redox-inactive ion in the cluster has not yet been fully clarified, although several experimental data are available on Ca2+-depleted and Ca2+-substituted PSII complexes, indicating Sr2+-substituted PSII as the only modification that preserves oxygen evolution. In this work, we investigated the structural and electronic properties of the PSII catalytic core with Ca2+ replaced with Sr2+ and Cd2+ in the S2 state of the Kok−Joliot cycle by means of density functional theory and ab initio molecular dynamics based on a quantum mechanics/ molecular mechanics approach. Our calculations do not reveal significant differences between the substituted and wild-type systems in terms of geometries, thermodynamics, and kinetics of two previously identified intermediate states along the S2 to S3 transition, namely, the open cubane S2 A and closed cubane S2 B conformers. Conversely, our calculations show different pKa values for the water molecule bound to the three investigated heterocations. Specifically, for Cd-substituted PSII, the pKa value is 5.3 units smaller than the respective value in wild type Ca-PSII. On the basis of our results, we conclude that, assuming all the cations sharing the same binding site, the induced difference in the acidity of the binding pocket might influence the hydrogen bonding network and the redox levels to prevent the further evolution of the cycle toward the S3 state.

Nonsynonymous substitution rate (Ka is a relatively consistent parameter for defining fast-evolving and slow-evolving protein-coding genes

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Wang Lei

2011-02-01

Full Text Available Abstract Background Mammalian genome sequence data are being acquired in large quantities and at enormous speeds. We now have a tremendous opportunity to better understand which genes are the most variable or conserved, and what their particular functions and evolutionary dynamics are, through comparative genomics. Results We chose human and eleven other high-coverage mammalian genome data–as well as an avian genome as an outgroup–to analyze orthologous protein-coding genes using nonsynonymous (Ka and synonymous (Ks substitution rates. After evaluating eight commonly-used methods of Ka and Ks calculation, we observed that these methods yielded a nearly uniform result when estimating Ka, but not Ks (or Ka/Ks. When sorting genes based on Ka, we noticed that fast-evolving and slow-evolving genes often belonged to different functional classes, with respect to species-specificity and lineage-specificity. In particular, we identified two functional classes of genes in the acquired immune system. Fast-evolving genes coded for signal-transducing proteins, such as receptors, ligands, cytokines, and CDs (cluster of differentiation, mostly surface proteins, whereas the slow-evolving genes were for function-modulating proteins, such as kinases and adaptor proteins. In addition, among slow-evolving genes that had functions related to the central nervous system, neurodegenerative disease-related pathways were enriched significantly in most mammalian species. We also confirmed that gene expression was negatively correlated with evolution rate, i.e. slow-evolving genes were expressed at higher levels than fast-evolving genes. Our results indicated that the functional specializations of the three major mammalian clades were: sensory perception and oncogenesis in primates, reproduction and hormone regulation in large mammals, and immunity and angiotensin in rodents. Conclusion Our study suggests that Ka calculation, which is less biased compared to Ks and Ka

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…

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...

Understanding Patterns for System-of-Systems Integration

DEFF Research Database (Denmark)

Kazman, Rick; Nielsen, Claus Ballegård; Schmid, Klaus

Creating a successful system of systems—one that meets the needs of its stakeholders today and can evolve and scale to sustain those stakeholders into the future—is a very complex engineering challenge. In a system of systems (SoS), one of the biggest challenges is in achieving cooperation and in...

Adoption of Geospatial Systems towards evolving Sustainable Himalayan Mountain Development

Science.gov (United States)

Murthy, M. S. R.; Bajracharya, B.; Pradhan, S.; Shestra, B.; Bajracharya, R.; Shakya, K.; Wesselmann, S.; Ali, M.; Bajracharya, S.; Pradhan, S.

2014-11-01

Natural resources dependence of mountain communities, rapid social and developmental changes, disaster proneness and climate change are conceived as the critical factors regulating sustainable Himalayan mountain development. The Himalayan region posed by typical geographic settings, diverse physical and cultural diversity present a formidable challenge to collect and manage data, information and understands varied socio-ecological settings. Recent advances in earth observation, near real-time data, in-situ measurements and in combination of information and communication technology have transformed the way we collect, process, and generate information and how we use such information for societal benefits. Glacier dynamics, land cover changes, disaster risk reduction systems, food security and ecosystem conservation are a few thematic areas where geospatial information and knowledge have significantly contributed to informed decision making systems over the region. The emergence and adoption of near-real time systems, unmanned aerial vehicles (UAV), board-scale citizen science (crowd-sourcing), mobile services and mapping, and cloud computing have paved the way towards developing automated environmental monitoring systems, enhanced scientific understanding of geophysical and biophysical processes, coupled management of socio-ecological systems and community based adaptation models tailored to mountain specific environment. There are differentiated capacities among the ICIMOD regional member countries with regard to utilization of earth observation and geospatial technologies. The region can greatly benefit from a coordinated and collaborative approach to capture the opportunities offered by earth observation and geospatial technologies. The regional level data sharing, knowledge exchange, and Himalayan GEO supporting geospatial platforms, spatial data infrastructure, unique region specific satellite systems to address trans-boundary challenges would go a long way in

Using ESB and BPEL for Evolving Healthcare Systems Towards Pervasive, Grid-Enabled SOA

Science.gov (United States)

Koufi, V.; Malamateniou, F.; Papakonstantinou, D.; Vassilacopoulos, G.

Healthcare organizations often face the challenge of integrating diverse and geographically disparate information technology systems to respond to changing requirements and to exploit the capabilities of modern technologies. Hence, systems evolution, through modification and extension of the existing information technology infrastructure, becomes a necessity. Moreover, the availability of these systems at the point of care when needed is a vital issue for the quality of healthcare provided to patients. This chapter takes a process perspective of healthcare delivery within and across organizational boundaries and presents a disciplined approach for evolving healthcare systems towards a pervasive, grid-enabled service-oriented architecture using the enterprise system bus middleware technology for resolving integration issues, the business process execution language for supporting collaboration requirements and grid middleware technology for both addressing common SOA scalability requirements and complementing existing system functionality. In such an environment, appropriate security mechanisms must ensure authorized access to integrated healthcare services and data. To this end, a security framework addressing security aspects such as authorization and access control is also presented.

Evolving approaches to the ethical management of genomic data.

Science.gov (United States)

McEwen, Jean E; Boyer, Joy T; Sun, Kathie Y

2013-06-01

The ethical landscape in the field of genomics is rapidly shifting. Plummeting sequencing costs, along with ongoing advances in bioinformatics, now make it possible to generate an enormous volume of genomic data about vast numbers of people. The informational richness, complexity, and frequently uncertain meaning of these data, coupled with evolving norms surrounding the sharing of data and samples and persistent privacy concerns, have generated a range of approaches to the ethical management of genomic information. As calls increase for the expanded use of broad or even open consent, and as controversy grows about how best to handle incidental genomic findings, these approaches, informed by normative analysis and empirical data, will continue to evolve alongside the science. Published by Elsevier Ltd.

Complexity and Health Coaching: Synergies in Nursing

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Gail J. Mitchell

2013-01-01

Full Text Available Health care professionals are increasingly aware that persons are complex and live in relation with other complex human communities and broader systems. Complex beings and systems are living and evolving in nonlinear ways through a process of mutual influence. Traditional standardized approaches in chronic disease management do not address these non-linear linkages and the meaning and changes that impact day-to-day life and caring for self and family. The RN health coach role described in this paper addresses the complexities and ambiguities for persons living with chronic illness in order to provide person-centered care and support that are unique and responsive to the context of persons’ lives. Informed by complexity thinking and relational inquiry, the RN health coach is an emergent innovation of creative action with community and groups that support persons as they shape their health and patterns of living.

AUTOMOTIVE APPLICATIONS OF EVOLVING TAKAGI-SUGENO-KANG FUZZY MODELS

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Radu-Emil Precup

2017-08-01

Full Text Available This paper presents theoretical and application results concerning the development of evolving Takagi-Sugeno-Kang fuzzy models for two dynamic systems, which will be viewed as controlled processes, in the field of automotive applications. The two dynamic systems models are nonlinear dynamics of the longitudinal slip in the Anti-lock Braking Systems (ABS and the vehicle speed in vehicles with the Continuously Variable Transmission (CVT systems. The evolving Takagi-Sugeno-Kang fuzzy models are obtained as discrete-time fuzzy models by incremental online identification algorithms. The fuzzy models are validated against experimental results in the case of the ABS and the first principles simulation results in the case of the vehicle with the CVT.

Advertising, product quality, and complex evolving marketing systems

NARCIS (Netherlands)

W.J.M.I. Verbeke (Willem)

1992-01-01

textabstractThe paper analyses the advertising as power vs. advertising as information controversy as well as its recent empirical testing. It is stressed that this distinction focuses too much on the interaction between consumer and manufacturer while ignoring the retailer as an important

Physical approach to complex systems

Science.gov (United States)

Kwapień, Jarosław; Drożdż, Stanisław

2012-06-01

Typically, complex systems are natural or social systems which consist of a large number of nonlinearly interacting elements. These systems are open, they interchange information or mass with environment and constantly modify their internal structure and patterns of activity in the process of self-organization. As a result, they are flexible and easily adapt to variable external conditions. However, the most striking property of such systems is the existence of emergent phenomena which cannot be simply derived or predicted solely from the knowledge of the systems’ structure and the interactions among their individual elements. This property points to the holistic approaches which require giving parallel descriptions of the same system on different levels of its organization. There is strong evidence-consolidated also in the present review-that different, even apparently disparate complex systems can have astonishingly similar characteristics both in their structure and in their behaviour. One can thus expect the existence of some common, universal laws that govern their properties. Physics methodology proves helpful in addressing many of the related issues. In this review, we advocate some of the computational methods which in our opinion are especially fruitful in extracting information on selected-but at the same time most representative-complex systems like human brain, financial markets and natural language, from the time series representing the observables associated with these systems. The properties we focus on comprise the collective effects and their coexistence with noise, long-range interactions, the interplay between determinism and flexibility in evolution, scale invariance, criticality, multifractality and hierarchical structure. The methods described either originate from “hard” physics-like the random matrix theory-and then were transmitted to other fields of science via the field of complex systems research, or they originated elsewhere but

System design in an evolving system-of-systems architecture and concept of operations

Science.gov (United States)

Rovekamp, Roger N., Jr.

Proposals for space exploration architectures have increased in complexity and scope. Constituent systems (e.g., rovers, habitats, in-situ resource utilization facilities, transfer vehicles, etc) must meet the needs of these architectures by performing in multiple operational environments and across multiple phases of the architecture's evolution. This thesis proposes an approach for using system-of-systems engineering principles in conjunction with system design methods (e.g., Multi-objective optimization, genetic algorithms, etc) to create system design options that perform effectively at both the system and system-of-systems levels, across multiple concepts of operations, and over multiple architectural phases. The framework is presented by way of an application problem that investigates the design of power systems within a power sharing architecture for use in a human Lunar Surface Exploration Campaign. A computer model has been developed that uses candidate power grid distribution solutions for a notional lunar base. The agent-based model utilizes virtual control agents to manage the interactions of various exploration and infrastructure agents. The philosophy behind the model is based both on lunar power supply strategies proposed in literature, as well as on the author's own approaches for power distribution strategies of future lunar bases. In addition to proposing a framework for system design, further implications of system-of-systems engineering principles are briefly explored, specifically as they relate to producing more robust cross-cultural system-of-systems architecture solutions.

How Heart Valves Evolve to Adapt to an Extreme-Pressure System

DEFF Research Database (Denmark)

Amstrup Funder, Jonas; Christian Danielsen, Carl; Baandrup, Ulrik

2017-01-01

BACKGROUND: Heart valves which exist naturally in an extreme-pressure system must have evolved in a way to resist the stresses of high pressure. Giraffes are interesting as they naturally have a blood pressure twice that of humans. Thus, knowledge regarding giraffe heart valves may aid...... in developing techniques to design improved pressure-resistant biological heart valves. METHODS: Heart valves from 12 giraffes and 10 calves were explanted and subjected to either biomechanical or morphological examinations. Strips from the heart valves were subjected to cyclic loading tests, followed...... in giraffes than in calves, which would make giraffe valves more resistant to the high-pressure forces. However, collagen also stiffens and thickens the valves. The mitral leaflets showed similar (but mostly insignificant) trends in strength, stiffness, and collagen content....

Synchronization and emergence in complex systems

Indian Academy of Sciences (India)

... complex systems. Fatihcan M Atay. Synchronization, Coupled Systems and Networks Volume 77 Issue 5 November 2011 pp 855-863 ... We show how novel behaviour can emerge in complex systems at the global level through synchronization of the activities of their constituent units. Two mechanisms are suggested for ...

Infinite Particle Systems: Complex Systems III

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Editorial Board

2008-06-01

Full Text Available In the years 2002-2005, a group of German and Polish mathematicians worked under a DFG research project No 436 POL 113/98/0-1 entitled "Methods of stochastic analysis in the theory of collective phenomena: Gibbs states and statistical hydrodynamics". The results of their study were summarized at the German-Polish conference, which took place in Poland in October 2005. The venue of the conference was Kazimierz Dolny upon Vistula - a lovely town and a popular place for various cultural, scientific, and even political events of an international significance. The conference was also attended by scientists from France, Italy, Portugal, UK, Ukraine, and USA, which predetermined its international character. Since that time, the conference, entitled "Infinite Particle Systems: Complex Systems" has become an annual international event, attended by leading scientists from Germany, Poland and many other countries. The present volume of the "Condensed Matter Physics" contains proceedings of the conference "Infinite Particle Systems: Complex Systems III", which took place in June 2007.

X-ray spectroscopy of the photosynthetic oxygen-evolving complex

Energy Technology Data Exchange (ETDEWEB)

Sauer, Ken; Yano, Junko; Yachandra, Vittal K

2007-04-05

Water oxidation to dioxygen in photosynthesis is catalyzed by a Mn4Ca cluster with O bridging in Photosystem II (PS II) of plants, algae and cyanobacteria. A variety of spectroscopic methods have been applied to analyzing the participation of the complex. X-ray spectroscopy is particularly useful because it is element-specific, and because it can reveal important structural features of the complex with high accuracy and identify the participation of Mn in the redox chemistry. Following a brief history of the application of X-ray spectroscopy to PS II, an overview of newer results will be presented and a description of the present state of our knowledge based on this approach.

Money Laundering Detection Framework to Link the Disparate and Evolving Schemes

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Murad Mehmet

2013-09-01

Full Text Available Money launderers hide traces of their transactions with the involvement of entities that participate in sophisticated schemes. Money laundering detection requires unraveling concealed connections among multiple but seemingly unrelated human money laundering networks, ties among actors of those schemes, and amounts of funds transferred among those entities. The link among small networks, either financial or social, is the primary factor that facilitates money laundering. Hence, the analysis of relations among money laundering networks is required to present the full structure of complex schemes. We propose a framework that uses sequence matching, case-based analysis, social network analysis, and complex event processing to detect money laundering. Our framework captures an ongoing single scheme as an event, and associations among such ongoing sequence of events to capture complex relationships among evolving money laundering schemes. The framework can detect associated multiple money laundering networks even in the absence of some evidence. We validated the accuracy of detecting evolving money laundering schemes using a multi-phases test methodology. Our test used data generated from real-life cases, and extrapolated to generate more data from real-life schemes generator that we implemented.

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.

Network Analysis of Earth's Co-Evolving Geosphere and Biosphere

Science.gov (United States)

Hazen, R. M.; Eleish, A.; Liu, C.; Morrison, S. M.; Meyer, M.; Consortium, K. D.

2017-12-01

A fundamental goal of Earth science is the deep understanding of Earth's dynamic, co-evolving geosphere and biosphere through deep time. Network analysis of geo- and bio- `big data' provides an interactive, quantitative, and predictive visualization framework to explore complex and otherwise hidden high-dimension features of diversity, distribution, and change in the evolution of Earth's geochemistry, mineralogy, paleobiology, and biochemistry [1]. Networks also facilitate quantitative comparison of different geological time periods, tectonic settings, and geographical regions, as well as different planets and moons, through network metrics, including density, centralization, diameter, and transitivity.We render networks by employing data related to geographical, paragenetic, environmental, or structural relationships among minerals, fossils, proteins, and microbial taxa. An important recent finding is that the topography of many networks reflects parameters not explicitly incorporated in constructing the network. For example, networks for minerals, fossils, and protein structures reveal embedded qualitative time axes, with additional network geometries possibly related to extinction and/or other punctuation events (see Figure). Other axes related to chemical activities and volatile fugacities, as well as pressure and/or depth of formation, may also emerge from network analysis. These patterns provide new insights into the way planets evolve, especially Earth's co-evolving geosphere and biosphere. 1. Morrison, S.M. et al. (2017) Network analysis of mineralogical systems. American Mineralogist 102, in press. Figure Caption: A network of Phanerozoic Era fossil animals from the past 540 million years includes blue, red, and black circles (nodes) representing family-level taxa and grey lines (links) between coexisting families. Age information was not used in the construction of this network; nevertheless an intrinsic timeline is embedded in the network topology. In

Complex Systems Design & Management : Proceedings of the Third International Conference on Complex Systems Design & Management

CERN Document Server

Caseau, Yves; Krob, Daniel; Rauzy, Antoine

2013-01-01

This book contains all refereed papers that were accepted to the third edition of the « Complex Systems Design & Management » (CSD&M 2012) international conference that took place in Paris (France) from December 12-14, 2012. (Website: http://www.csdm2012.csdm.fr)  These proceedings cover the most recent trends in the emerging field of complex systems sciences & practices from an industrial and academic perspective, including the main industrial domains (transport, defense & security, electronics, energy & environment, e-services), scientific & technical topics (systems fundamentals, systems architecture& engineering, systems metrics & quality, systemic  tools) and system types (transportation systems, embedded systems, software & information systems, systems of systems, artificial ecosystems). The CSD&M 2012 conference is organized under the guidance of the CESAMES non-profit organization (http://www.cesames.net).

The Meaning of System: Towards a Complexity Orientation in Systems Thinking

DEFF Research Database (Denmark)

Leleur, Steen

2014-01-01

for systems practice. It is argued that complexity theory and thinking with reference to Luhmann a.o. ought to be recognised and paid attention to by the systems community. Overall, it is found that a complexity orientation may contribute to extend and enrich the explanatory power of current systems theory......This article reviews the generic meaning of ‘system’ and complements more conventional system notions with a system perception based on recent complexity theory. With system as the core concept of systems theory, its actual meaning is not just of theoretical interest but is highly relevant also...... when used to complex real-world problems. As regards systems practice it is found that selective use and combination of five presented research approaches (functionalist, interpretive, emancipatory, postmodern and complexity) which function as different but complementing ‘epistemic lenses’ in a process...

Complex Adaptive Systems, soil degradation and land sensitivity to desertification: A multivariate assessment of Italian agro-forest landscape.

Science.gov (United States)

Salvati, Luca; Mavrakis, Anastasios; Colantoni, Andrea; Mancino, Giuseppe; Ferrara, Agostino

2015-07-15

Degradation of soils and sensitivity of land to desertification are intensified in last decades in the Mediterranean region producing heterogeneous spatial patterns determined by the interplay of factors such as climate, land-use changes, and human pressure. The present study hypothesizes that rising levels of soil degradation and land sensitivity to desertification are reflected into increasingly complex (and non-linear) relationships between environmental and socioeconomic variables. To verify this hypothesis, the Complex Adaptive Systems (CAS) framework was used to explore the spatiotemporal dynamics of eleven indicators derived from a standard assessment of soil degradation and land sensitivity to desertification in Italy. Indicators were made available on a detailed spatial scale (773 agricultural districts) for various years (1960, 1990, 2000 and 2010) and analyzed through a multi-dimensional exploratory data analysis. Our results indicate that the number of significant pair-wise correlations observed between indicators increased with the level of soil and land degradation, although with marked differences between northern and southern Italy. 'Fast' and 'slow' factors underlying soil and land degradation, and 'rapidly-evolving' or 'locked' agricultural districts were identified according to the rapidity of change estimated for each of the indicators studied. In southern Italy, 'rapidly-evolving' districts show a high level of soil degradation and land sensitivity to desertification during the whole period of investigation. On the contrary, those districts in northern Italy are those experiencing a moderate soil degradation and land sensitivity to desertification with the highest increase in the level of sensitivity over time. The study framework contributes to the assessment of complex local systems' dynamics in affluent but divided countries. Results may inform thematic strategies for the mitigation of land and soil degradation in the framework of action

The clinical educator and complexity: a review.

Science.gov (United States)

Schoo, Adrian; Kumar, Koshila

2018-02-08

Complexity science perspectives have helped in examining fundamental assumptions about learning and teaching in the health professions. The implications of complexity thinking for how we understand the role and development of the clinical educator is less well articulated. This review article outlines: the key principles of complexity science; a conceptual model that situates the clinical educator in a complex system; and the implications for the individual, organisation and the system. Our conceptual model situates the clinical educator at the centre of a complex and dynamic system spanning four domains and multiple levels. The four domains are: personal (encompassing personal/professional needs and expectations); health services (health agencies and their consumers); educational (educational institutions and their health students); and societal (local community/region and government). The system also comprises: micro or individual, meso or organisational, and macro or socio-political levels. Our model highlights that clinical educators are situated within a complex system comprising different agents and connections. It emphasises that individuals, teams and organisations need to recognise and be responsive to the unpredictability, interconnectedness and evolving nature of this system. Importantly, our article also calls for an epistemological shift from faculty development to capacity building in health professions education, aimed at developing individual, team, organisational and system capabilities to work with(in) complexity. Clinical educators are situated within a complex system comprising different agents and connections. © 2018 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Sandpile model for relaxation in complex systems

International Nuclear Information System (INIS)

Vazquez, A.; Sotolongo-Costa, O.; Brouers, F.

1997-10-01

The relaxation in complex systems is, in general, nonexponential. After an initial rapid decay the system relaxes slowly following a long time tail. In the present paper a sandpile moderation of the relaxation in complex systems is analysed. Complexity is introduced by a process of avalanches in the Bethe lattice and a feedback mechanism which leads to slower decay with increasing time. In this way, some features of relaxation in complex systems: long time tails relaxation, aging, and fractal distribution of characteristic times, are obtained by simple computer simulations. (author)

Evolving Metadata in NASA Earth Science Data Systems

Science.gov (United States)

Mitchell, A.; Cechini, M. F.; Walter, J.

2011-12-01

NASA's effort to continually evolve its data systems led ECHO to enhancing the method in which it receives inventory metadata from the data centers to allow for multiple metadata formats including ISO 19115. ECHO's metadata model will also be mapped to the NASA-specific convention for ingesting science metadata into the ECHO system. As NASA's new Earth Science missions and data centers are migrating to the ISO 19115 standards, EOSDIS is developing metadata management resources to assist in the reading, writing and parsing ISO 19115 compliant metadata. To foster interoperability with other agencies and international partners, NASA is working to ensure that a common ISO 19115 convention is developed, enhancing data sharing capabilities and other data analysis initiatives. NASA is also investigating the use of ISO 19115 standards to encode data quality, lineage and provenance with stored values. A common metadata standard across NASA's Earth Science data systems promotes interoperability, enhances data utilization and removes levels of uncertainty found in data products.

Complex Education Systems: From Steering Change to Governance

Science.gov (United States)

Michel, Alain

2016-01-01

The theories and approaches of steering/monitoring a process of change within education systems have evolved over the last 20 years or so as a result of many factors such as globalisation and decentralisation, a faster pace of change, increasing expectations and demands from various stakeholders (parents, employers, teacher unions, etc.) and the…

Embracing uncertainty, managing complexity: applying complexity thinking principles to transformation efforts in healthcare systems.

Science.gov (United States)

Khan, Sobia; Vandermorris, Ashley; Shepherd, John; Begun, James W; Lanham, Holly Jordan; Uhl-Bien, Mary; Berta, Whitney

2018-03-21

Complexity thinking is increasingly being embraced in healthcare, which is often described as a complex adaptive system (CAS). Applying CAS to healthcare as an explanatory model for understanding the nature of the system, and to stimulate changes and transformations within the system, is valuable. A seminar series on systems and complexity thinking hosted at the University of Toronto in 2016 offered a number of insights on applications of CAS perspectives to healthcare that we explore here. We synthesized topics from this series into a set of six insights on how complexity thinking fosters a deeper understanding of accepted ideas in healthcare, applications of CAS to actors within the system, and paradoxes in applications of complexity thinking that may require further debate: 1) a complexity lens helps us better understand the nebulous term "context"; 2) concepts of CAS may be applied differently when actors are cognizant of the system in which they operate; 3) actor responses to uncertainty within a CAS is a mechanism for emergent and intentional adaptation; 4) acknowledging complexity supports patient-centred intersectional approaches to patient care; 5) complexity perspectives can support ways that leaders manage change (and transformation) in healthcare; and 6) complexity demands different ways of implementing ideas and assessing the system. To enhance our exploration of key insights, we augmented the knowledge gleaned from the series with key articles on complexity in the literature. Ultimately, complexity thinking acknowledges the "messiness" that we seek to control in healthcare and encourages us to embrace it. This means seeing challenges as opportunities for adaptation, stimulating innovative solutions to ensure positive adaptation, leveraging the social system to enable ideas to emerge and spread across the system, and even more important, acknowledging that these adaptive actions are part of system behaviour just as much as periods of stability are. By

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.

Metasynthetic computing and engineering of complex systems

CERN Document Server

Cao, Longbing

2015-01-01

Provides a comprehensive overview and introduction to the concepts, methodologies, analysis, design and applications of metasynthetic computing and engineering. The author: Presents an overview of complex systems, especially open complex giant systems such as the Internet, complex behavioural and social problems, and actionable knowledge discovery and delivery in the big data era. Discusses ubiquitous intelligence in complex systems, including human intelligence, domain intelligence, social intelligence, network intelligence, data intelligence and machine intelligence, and their synergy thro

Complexity: Outline of the NWO strategic theme Dynamics of complex systems

NARCIS (Netherlands)

Burgers, G.; Doelman, A.; Frenken, K.; Hogeweg, P.; Hommes, C.; van der Maas, H.; Mulder, B.; Stam, K.; van Steen, M.; Zandee, L.

2008-01-01

Dynamics of complex systems is one of the program 5 themes in the NWO (Netherlands Organisation for Scientific Research) strategy for the years 2007-2011. The ambition of the current proposal is to initiate integrated activities in the field of complex systems within the Netherlands, to provide

Complexity : outline of the NWO strategic theme dynamics of complex systems

NARCIS (Netherlands)

Burgers, G.; Doelman, A.; Frenken, K.; Hogeweg, P.; Hommes, C.; Maas, van der H.; Mulder, B.; Stam, K.; Steen, van M.; Zandee, L.

2008-01-01

Dynamics of complex systems is one of the program 5 themes in the NWO (Netherlands Organisation for Scientific Research) strategy for the years 2007-2011. The ambition of the current proposal is to initiate integrated activities in the field of complex systems within the Netherlands, to provide

Robustness to Faults Promotes Evolvability: Insights from Evolving Digital Circuits.

Science.gov (United States)

Milano, Nicola; Nolfi, Stefano

2016-01-01

We demonstrate how the need to cope with operational faults enables evolving circuits to find more fit solutions. The analysis of the results obtained in different experimental conditions indicates that, in absence of faults, evolution tends to select circuits that are small and have low phenotypic variability and evolvability. The need to face operation faults, instead, drives evolution toward the selection of larger circuits that are truly robust with respect to genetic variations and that have a greater level of phenotypic variability and evolvability. Overall our results indicate that the need to cope with operation faults leads to the selection of circuits that have a greater probability to generate better circuits as a result of genetic variation with respect to a control condition in which circuits are not subjected to faults.

Theory for the Emergence of Modularity in Complex Systems

Science.gov (United States)

Deem, Michael; Park, Jeong-Man

2013-03-01

Biological systems are modular, and this modularity evolves over time and in different environments. A number of observations have been made of increased modularity in biological systems under increased environmental pressure. We here develop a theory for the dynamics of modularity in these systems. We find a principle of least action for the evolved modularity at long times. In addition, we find a fluctuation dissipation relation for the rate of change of modularity at short times. We discuss a number of biological and social systems that can be understood with this framework. The modularity of the protein-protein interaction network increases when yeast are exposed to heat shock, and the modularity of the protein-protein networks in both yeast and E. coli appears to have increased over evolutionary time. Food webs in low-energy, stressful environments are more modular than those in plentiful environments, arid ecologies are more modular during droughts, and foraging of sea otters is more modular when food is limiting. The modularity of social networks changes over time: stock brokers instant messaging networks are more modular under stressful market conditions, criminal networks are more modular under increased police pressure, and world trade network modularity has decreased

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.

Mining sensor data from complex systems

NARCIS (Netherlands)

Vespier, Ugo

2015-01-01

Today, virtually everything, from natural phenomena to complex artificial and physical systems, can be measured and the resulting information collected, stored and analyzed in order to gain new insight. This thesis shows how complex systems often exhibit diverse behavior at different temporal

Towards an evaluation framework for complex social systems

Science.gov (United States)

McDonald, Diane M.; Kay, Nigel

While there is growing realisation that the world in which we live in is highly complex with multiple interdependencies and irreducibly open to outside influence, how to make these 'systems' more manageable is still a significant outstanding issue. As (2004) suggests, applying the theoretical principles of Complex Systems may help solve complex problems in this complex world. While Bar-Yam provides examples of forward-thinking organisations which have begun to see the relevance of complex systems principles, for many organisations the language and concepts of complexity science such as self-organisation and unpredictability while they make theoretical sense offer no practical or acceptable method of implementation to those more familiar with definitive facts and classical hierarchical, deterministic approaches to control. Complexity Science explains why designed systems or interventions may not function as anticipated in differing environments, without providing a silver bullet which enables control or engineering of the system to ensure the desired results. One familiar process which might, if implemented with complex systems in mind, provide the basis of an accessible and understandable framework that enables policy makers and practitioners to better design and manage complex socio-technical systems is that of evaluation.

Preface: evolving rotifers, evolving science: Proceedings of the XIV International Rotifer Symposium

Czech Academy of Sciences Publication Activity Database

Devetter, Miloslav; Fontaneto, D.; Jersabek, Ch.D.; Welch, D.B.M.; May, L.; Walsh, E.J.

2017-01-01

Roč. 796, č. 1 (2017), s. 1-6 ISSN 0018-8158 Institutional support: RVO:60077344 Keywords : evolving rotifers * 14th International Rotifer Symposium * evolving science Subject RIV: EG - Zoology OBOR OECD: Zoology Impact factor: 2.056, year: 2016

Dental Infection and Pregnancy: the Lack of Treatment by the Dental Professional Evolving to a Complex Maxillofacial Infection.

Science.gov (United States)

Pereira, Rodrigo Dos Santos; Gomes-Ferreira, Pedro Henrique Silva; Bonardi, João Paulo; Silva, Jonathan Ribeiro da; Latini, Gustavo Lima; Hochuli-Vieira, Eduardo

2017-11-01

Infections of the maxillofacial complex caused by caries disease are common in dental practice. The professionals have to have technical knowledge to treat it at the onset of the condition and avoid the spread to deep anatomical spaces of face and neck, which can implicate in a risk of patients' life.In Brazil, current dental professionals usually denied oral surgical treatments in patients with some clinical conditions, not because of fear to resolve it but for lack of knowledge to treat it. An example of these conditionals is pregnancy. It is well known that during the pregnancy period, the patient can be treated in the correct period of gestation. Early diagnosis is crucial for effective therapy in serious infections. The treatment has to be crucial during pregnancy because of the potentially fatal situation that the disease can create to the pregnant woman and the fetus.The aim of this article is to demonstrate a case of dental caries in a pregnant patient, which was evaluated by other professionals and had the treatment denied, evolving to a serious maxillofacial infection.

A System for Complex Robotic Welding

DEFF Research Database (Denmark)

Madsen, Ole; Sørensen, Carsten Bro; Olsen, Birger

2002-01-01

This paper presents the architecture of a system for robotic welding of complex tasks. The system integrates off-line programming, control of redundant robots, collision-free motion planning and sensor-based control. An implementation for pipe structure welding made at Odense Steel Shipyard Ltd......., Denmark, demonstrates the system can be used for automatic welding of complex products in one-of-a-kind production....

Analysis and control of complex dynamical systems robust bifurcation, dynamic attractors, and network complexity

CERN Document Server

Imura, Jun-ichi; Ueta, Tetsushi

2015-01-01

This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.

Modeling Power Systems as Complex Adaptive Systems

Energy Technology Data Exchange (ETDEWEB)

Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.

2004-12-30

Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

Cosmic Biology How Life Could Evolve on Other Worlds

CERN Document Server

Irwin, Louis Neil

2011-01-01

It is very unlikely that little green humanoids are living on Mars. But what are the possible life forms that might exist in our Solar System and how might they have evolved? This uniquely authoritative and imaginative book on the possibilties for alien life addresses the intrinsic interest that we have about life on other worlds - reinforcing some of our assumptions and reshaping others. It introduces new possibilties that will enlarge our understanding of the issue overall, in particular the enormous range of environments and planetary conditions within which life might evolve. Cosmic Biology -discusses a broad range of possible environments where alien life might have evolved; -explains why carbon-based, water-borne life is more likely that its alternatives, but is not the only possiblity; -applies the principles of planetary science and modern biology to evolutionary scenarios on other worlds; -looks at the future fates of living systems, including those on Earth.

Modelling methodology for engineering of complex sociotechnical systems

CSIR Research Space (South Africa)

Oosthuizen, R

2014-10-01

Full Text Available Different systems engineering techniques and approaches are applied to design and develop complex sociotechnical systems for complex problems. In a complex sociotechnical system cognitive and social humans use information technology to make sense...

Stephen Jay Kline on systems, or physics, complex systems, and the gap between.

Energy Technology Data Exchange (ETDEWEB)

Campbell, Philip LaRoche

2011-06-01

At the end of his life, Stephen Jay Kline, longtime professor of mechanical engineering at Stanford University, completed a book on how to address complex systems. The title of the book is 'Conceptual Foundations of Multi-Disciplinary Thinking' (1995), but the topic of the book is systems. Kline first establishes certain limits that are characteristic of our conscious minds. Kline then establishes a complexity measure for systems and uses that complexity measure to develop a hierarchy of systems. Kline then argues that our minds, due to their characteristic limitations, are unable to model the complex systems in that hierarchy. Computers are of no help to us here. Our attempts at modeling these complex systems are based on the way we successfully model some simple systems, in particular, 'inert, naturally-occurring' objects and processes, such as what is the focus of physics. But complex systems overwhelm such attempts. As a result, the best we can do in working with these complex systems is to use a heuristic, what Kline calls the 'Guideline for Complex Systems.' Kline documents the problems that have developed due to 'oversimple' system models and from the inappropriate application of a system model from one domain to another. One prominent such problem is the Procrustean attempt to make the disciplines that deal with complex systems be 'physics-like.' Physics deals with simple systems, not complex ones, using Kline's complexity measure. The models that physics has developed are inappropriate for complex systems. Kline documents a number of the wasteful and dangerous fallacies of this type.

Complex engineering systems science meets technology

CERN Document Server

Minai, Ali A; Bar-Yam, Yaneer

2006-01-01

Every time that we take money out of an ATM, surf the internet or simply turn on a light switch, we enjoy the benefits of complex engineered systems. Systems like power grids and global communication networks are so ubiquitous in our daily lives that we usually take them for granted, only noticing them when they break down. But how do such amazing technologies and infrastructures come to be what they are? How are these systems designed? How do distributed networks work? How are they made to respond rapidly in 'real time'? And as the demands that we place on these systems become increasingly complex, are traditional systems-engineering practices still relevant? This volume examines the difficulties that arise in creating highly complex engineered systems and new approaches that are being adopted. Topics addressed range from the formal representation and classification of distributed networked systems to revolutionary engineering practices inspired by biological evolution. By bringing together the latest resear...

Decentralized control of complex systems

CERN Document Server

Siljak, Dragoslav D

2011-01-01

Complex systems require fast control action in response to local input, and perturbations dictate the use of decentralized information and control structures. This much-cited reference book explores the approaches to synthesizing control laws under decentralized information structure constraints.Starting with a graph-theoretic framework for structural modeling of complex systems, the text presents results related to robust stabilization via decentralized state feedback. Subsequent chapters explore optimization, output feedback, the manipulative power of graphs, overlapping decompositions and t

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.

Quantifying selection in evolving populations using time-resolved genetic data

Science.gov (United States)

Illingworth, Christopher J. R.; Mustonen, Ville

2013-01-01

Methods which uncover the molecular basis of the adaptive evolution of a population address some important biological questions. For example, the problem of identifying genetic variants which underlie drug resistance, a question of importance for the treatment of pathogens, and of cancer, can be understood as a matter of inferring selection. One difficulty in the inference of variants under positive selection is the potential complexity of the underlying evolutionary dynamics, which may involve an interplay between several contributing processes, including mutation, recombination and genetic drift. A source of progress may be found in modern sequencing technologies, which confer an increasing ability to gather information about evolving populations, granting a window into these complex processes. One particularly interesting development is the ability to follow evolution as it happens, by whole-genome sequencing of an evolving population at multiple time points. We here discuss how to use time-resolved sequence data to draw inferences about the evolutionary dynamics of a population under study. We begin by reviewing our earlier analysis of a yeast selection experiment, in which we used a deterministic evolutionary framework to identify alleles under selection for heat tolerance, and to quantify the selection acting upon them. Considering further the use of advanced intercross lines to measure selection, we here extend this framework to cover scenarios of simultaneous recombination and selection, and of two driver alleles with multiple linked neutral, or passenger, alleles, where the driver pair evolves under an epistatic fitness landscape. We conclude by discussing the limitations of the approach presented and outlining future challenges for such methodologies.

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

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...

Dynamic facial expressions of emotion transmit an evolving hierarchy of signals over time.

Science.gov (United States)

Jack, Rachael E; Garrod, Oliver G B; Schyns, Philippe G

2014-01-20

Designed by biological and social evolutionary pressures, facial expressions of emotion comprise specific facial movements to support a near-optimal system of signaling and decoding. Although highly dynamical, little is known about the form and function of facial expression temporal dynamics. Do facial expressions transmit diagnostic signals simultaneously to optimize categorization of the six classic emotions, or sequentially to support a more complex communication system of successive categorizations over time? Our data support the latter. Using a combination of perceptual expectation modeling, information theory, and Bayesian classifiers, we show that dynamic facial expressions of emotion transmit an evolving hierarchy of "biologically basic to socially specific" information over time. Early in the signaling dynamics, facial expressions systematically transmit few, biologically rooted face signals supporting the categorization of fewer elementary categories (e.g., approach/avoidance). Later transmissions comprise more complex signals that support categorization of a larger number of socially specific categories (i.e., the six classic emotions). Here, we show that dynamic facial expressions of emotion provide a sophisticated signaling system, questioning the widely accepted notion that emotion communication is comprised of six basic (i.e., psychologically irreducible) categories, and instead suggesting four. Copyright © 2014 Elsevier Ltd. All rights reserved.

An evolving network model with community structure

International Nuclear Information System (INIS)

Li Chunguang; Maini, Philip K

2005-01-01

Many social and biological networks consist of communities-groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties

Evolving controllers for a homogeneous system of physical robots: structured cooperation with minimal sensors.

Science.gov (United States)

Quinn, Matt; Smith, Lincoln; Mayley, Giles; Husbands, Phil

2003-10-15

We report on recent work in which we employed artificial evolution to design neural network controllers for small, homogeneous teams of mobile autonomous robots. The robots were evolved to perform a formation-movement task from random starting positions, equipped only with infrared sensors. The dual constraints of homogeneity and minimal sensors make this a non-trivial task. We describe the behaviour of a successful system in which robots adopt and maintain functionally distinct roles in order to achieve the task. We believe this to be the first example of the use of artificial evolution to design coordinated, cooperative behaviour for real robots.

Genetic programming for evolving due-date assignment models in job shop environments.

Science.gov (United States)

Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

2014-01-01

Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.

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

Directory of Open Access Journals (Sweden)

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.

The Meaning of System: Towards a Complexity Orientation in Systems Thinking

DEFF Research Database (Denmark)

Leleur, Steen

2017-01-01

when used to complex real-world problems. As regards systems practice it is found that selective use and combination of five presented research approaches (functionalist, interpretive, emancipatory, postmodern and complexity) which function as different but complementing ‘epistemic lenses’ in a process...... described as constructive circularity, may strengthen the exploration and learning efforts in systems-based intervention.......This article reviews the generic meaning of ‘system’ and complements more conventional system notions with a system perception based on recent complexity theory. With system as the core concept of systems theory, its actual meaning is not just of theoretical interest but is highly relevant also...

Autopoietic Automata: Complexity Issues in Offspring-Producing Evolving Processes

Czech Academy of Sciences Publication Activity Database

Wiedermann, Jiří

2007-01-01

Roč. 383, č. 2-3 (2007), s. 260-269 ISSN 0304-3975 R&D Projects: GA AV ČR 1ET100300517 Institutional research plan: CEZ:AV0Z10300504 Keywords : autopoietic automata * self-reproducing automata * interactive Turing machine * simulation * computational complexity Subject RIV: IN - Informatics, Computer Science Impact factor: 0.735, year: 2007

Managing complexity challenges for industrial engineering and operations management

CERN Document Server

López-Paredes, Adolfo; Pérez-Ríos, José

2014-01-01

This book presents papers by experts in the field of Industrial Engineering, covering topics in business strategy; modelling and simulation in operations research; logistics and production; service systems; innovation and knowledge; and project management. The focus of operations and production management has evolved from product and manufacturing to the capabilities of firms and collaborative management. Nowadays, Industrial Engineering is concerned with the study of how to design, modify, control and improve the performance of complex systems. It has extended its scope to any physical landscape populated by social agents. This raises a major challenge to Industrial Engineering:  managing complexity. This volume shows how experts are dealing with this challenge.

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.

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.

When Darwin meets Lorenz: Evolving new chaotic attractors through genetic programming

International Nuclear Information System (INIS)

Pan, Indranil; Das, Saptarshi

2015-01-01

Highlights: •New 3D continuous time chaotic systems with analytical expressions are obtained. •The multi-gene genetic programming (MGGP) paradigm is employed to achieve this. •Extends earlier works for evolving generalised family of Lorenz attractors. •Over one hundred of new chaotic attractors along with their parameters are reported. •The MGGP method have the potential for finding other similar chaotic attractors. -- Abstract: In this paper, we propose a novel methodology for automatically finding new chaotic attractors through a computational intelligence technique known as multi-gene genetic programming (MGGP). We apply this technique to the case of the Lorenz attractor and evolve several new chaotic attractors based on the basic Lorenz template. The MGGP algorithm automatically finds new nonlinear expressions for the different state variables starting from the original Lorenz system. The Lyapunov exponents of each of the attractors are calculated numerically based on the time series of the state variables using time delay embedding techniques. The MGGP algorithm tries to search the functional space of the attractors by aiming to maximise the largest Lyapunov exponent (LLE) of the evolved attractors. To demonstrate the potential of the proposed methodology, we report over one hundred new chaotic attractor structures along with their parameters, which are evolved from just the Lorenz system alone

CMIP6 Data Citation of Evolving Data

Directory of Open Access Journals (Sweden)

Martina Stockhause

2017-06-01

Full Text Available Data citations have become widely accepted. Technical infrastructures as well as principles and recommendations for data citation are in place but best practices or guidelines for their implementation are not yet available. On the other hand, the scientific climate community requests early citations on evolving data for credit, e.g. for CMIP6 (Coupled Model Intercomparison Project Phase 6. The data citation concept for CMIP6 is presented. The main challenges lie in limited resources, a strict project timeline and the dependency on changes of the data dissemination infrastructure ESGF (Earth System Grid Federation to meet the data citation requirements. Therefore a pragmatic, flexible and extendible approach for the CMIP6 data citation service was developed, consisting of a citation for the full evolving data superset and a data cart approach for citing the concrete used data subset. This two citation approach can be implemented according to the RDA recommendations for evolving data. Because of resource constraints and missing project policies, the implementation of the second part of the citation concept is postponed to CMIP7.

Functional and structural analysis of photosystem II core complexes from spinach with high oxygen evolution capacity

NARCIS (Netherlands)

Haag, Elisabeth; Irrgang, Klaus-D.; Boekema, Egbert J.; Renger, Gernot

1990-01-01

Oxygen-evolving photo system II core complexes were prepared from spinach by solubilizing photosystem II membrane fragments with dodecyl-β-D-maltoside. The core complexes consist of the intrinsic 47-kDa, 43-kDa, D1 and D2 polypeptides, the two subunits of cytochrome b559 and the extrinsic 33-kDa

The Capabilities of Chaos and Complexity

Directory of Open Access Journals (Sweden)

David L. Abel

2009-01-01

Full Text Available To what degree could chaos and complexity have organized a Peptide or RNA World of crude yet necessarily integrated protometabolism? How far could such protolife evolve in the absence of a heritable linear digital symbol system that could mutate, instruct, regulate, optimize and maintain metabolic homeostasis? To address these questions, chaos, complexity, self-ordered states, and organization must all be carefully defined and distinguished. In addition their cause-and-effect relationships and mechanisms of action must be delineated. Are there any formal (non physical, abstract, conceptual, algorithmic components to chaos, complexity, self-ordering and organization, or are they entirely physicodynamic (physical, mass/energy interaction alone? Chaos and complexity can produce some fascinating self-ordered phenomena. But can spontaneous chaos and complexity steer events and processes toward pragmatic benefit, select function over non function, optimize algorithms, integrate circuits, produce computational halting, organize processes into formal systems, control and regulate existing systems toward greater efficiency? The question is pursued of whether there might be some yet-to-be discovered new law of biology that will elucidate the derivation of prescriptive information and control. “System” will be rigorously defined. Can a low-informational rapid succession of Prigogine’s dissipative structures self-order into bona fide organization?

Managing Schools as Complex Adaptive Systems: A Strategic Perspective

Science.gov (United States)

Fidan, Tuncer; Balci, Ali

2017-01-01

This conceptual study examines the analogies between schools and complex adaptive systems and identifies strategies used to manage schools as complex adaptive systems. Complex adaptive systems approach, introduced by the complexity theory, requires school administrators to develop new skills and strategies to realize their agendas in an…

Evolving Neural Turing Machines for Reward-based Learning

DEFF Research Database (Denmark)

Greve, Rasmus Boll; Jacobsen, Emil Juul; Risi, Sebastian

2016-01-01

An unsolved problem in neuroevolution (NE) is to evolve artificial neural networks (ANN) that can store and use information to change their behavior online. While plastic neural networks have shown promise in this context, they have difficulties retaining information over longer periods of time...... version of the double T-Maze, a complex reinforcement-like learning problem. In the T-Maze learning task the agent uses the memory bank to display adaptive behavior that normally requires a plastic ANN, thereby suggesting a complementary and effective mechanism for adaptive behavior in NE....

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.

Complex Nonlinear Autonomic Nervous System Modulation Link Cardiac Autonomic Neuropathy and Peripheral Vascular Disease

Directory of Open Access Journals (Sweden)

Kinda eKhalaf

2015-03-01

Full Text Available Background: Physiological interactions are abundant within, and between, body systems. These interactions may evolve into discrete states during pathophysiological processes resulting from common mechanisms. An association between arterial stenosis, identified by low ankle-brachial pressure index (ABPI and cardiovascular disease (CVD as been reported. Whether an association between vascular calcification - characterized by high ABPI and a different pathophysiology - is similarly associated with CVD, has not been established. The current study aims to investigate the association between ABPI, and cardiac rhythm, as an indicator of cardiovascular health and functionality, utilising heart rate variability (HRV.Methods and Results: Two hundred and thirty six patients underwent ABPI assessment. Standard time and frequency domain, and non-linear HRV measures were determined from 5-minute electrocardiogram. ABPI data were divided into normal (n=101, low (n=67 and high (n=66 and compared to HRV measures.(DFAα1 and SampEn were significantly different between the low ABPI, high ABPI and control groups (p<0.05.Conclusion: A possible coupling between arterial stenosis and vascular calcification with decreased and increased HRV respectively was observed. Our results suggest a model for interpreting the relationship between vascular pathophysiology and cardiac rhythm. The cardiovascular system may be viewed as a complex system comprising a number of interacting subsystems. These cardiac and vascular subsystems/networks may be coupled and undergo transitions in response to internal or external perturbations. From a clinical perspective, the significantly increased sample entropy compared to the normal ABPI group and the decreased and increased complex correlation properties measured by DFA for the low and high ABPI groups respectively, may be useful indicators that a more holistic treatment approach in line with this more complex clinical picture is required.

Advances in complex societal, environmental and engineered systems

CERN Document Server

Essaaidi, Mohammad

2017-01-01

This book addresses recent technological progress that has led to an increased complexity in many natural and artificial systems. The resulting complexity research due to the emergence of new properties and spatio-temporal interactions among a large number of system elements - and between the system and its environment - is the primary focus of this text. This volume is divided into three parts: Part one focuses on societal and ecological systems, Part two deals with approaches for understanding, modeling, predicting and mastering socio-technical systems, and Part three includes real-life examples. Each chapter has its own special features; it is a self-contained contribution of distinguished experts working on different fields of science and technology relevant to the study of complex systems. Advances in Complex Systems of Contemporary Reality: Societal, Environmental and Engineered Systems will provide postgraduate students, researchers and managers with qualitative and quantitative methods for handling th...

Complexity Triggered by Economic Globalisation— The Issue of On-Line Betting-Related Match Fixing

OpenAIRE

Wladimir Andreff

2017-01-01

Complexity in mainstream economics consists in high intermediary consumption of mathematics. A new approach to complexity economics dwells upon path-dependent global systems; their emergence and evolving organisation. The focus here is on the complexity of the real economic world due to globalisation. On-line betting related match-fixing is a case in point about which the article presents non-exhaustive empirical evidence and shows how it is analysed with the standard model of the economics o...

Understanding complex urban systems multidisciplinary approaches to modeling

CERN Document Server

Gurr, Jens; Schmidt, J

2014-01-01

Understanding Complex Urban Systems takes as its point of departure the insight that the challenges of global urbanization and the complexity of urban systems cannot be understood – let alone ‘managed’ – by sectoral and disciplinary approaches alone. But while there has recently been significant progress in broadening and refining the methodologies for the quantitative modeling of complex urban systems, in deepening the theoretical understanding of cities as complex systems, or in illuminating the implications for urban planning, there is still a lack of well-founded conceptual thinking on the methodological foundations and the strategies of modeling urban complexity across the disciplines. Bringing together experts from the fields of urban and spatial planning, ecology, urban geography, real estate analysis, organizational cybernetics, stochastic optimization, and literary studies, as well as specialists in various systems approaches and in transdisciplinary methodologies of urban analysis, the volum...

Evolving RBF neural networks for adaptive soft-sensor design.

Science.gov (United States)

Alexandridis, Alex

2013-12-01

This work presents an adaptive framework for building soft-sensors based on radial basis function (RBF) neural network models. The adaptive fuzzy means algorithm is utilized in order to evolve an RBF network, which approximates the unknown system based on input-output data from it. The methodology gradually builds the RBF network model, based on two separate levels of adaptation: On the first level, the structure of the hidden layer is modified by adding or deleting RBF centers, while on the second level, the synaptic weights are adjusted with the recursive least squares with exponential forgetting algorithm. The proposed approach is tested on two different systems, namely a simulated nonlinear DC Motor and a real industrial reactor. The results show that the produced soft-sensors can be successfully applied to model the two nonlinear systems. A comparison with two different adaptive modeling techniques, namely a dynamic evolving neural-fuzzy inference system (DENFIS) and neural networks trained with online backpropagation, highlights the advantages of the proposed methodology.

Observation-Driven Configuration of Complex Software Systems

Science.gov (United States)

Sage, Aled

2010-06-01

The ever-increasing complexity of software systems makes them hard to comprehend, predict and tune due to emergent properties and non-deterministic behaviour. Complexity arises from the size of software systems and the wide variety of possible operating environments: the increasing choice of platforms and communication policies leads to ever more complex performance characteristics. In addition, software systems exhibit different behaviour under different workloads. Many software systems are designed to be configurable so that policies can be chosen to meet the needs of various stakeholders. For complex software systems it can be difficult to accurately predict the effects of a change and to know which configuration is most appropriate. This thesis demonstrates that it is useful to run automated experiments that measure a selection of system configurations. Experiments can find configurations that meet the stakeholders' needs, find interesting behavioural characteristics, and help produce predictive models of the system's behaviour. The design and use of ACT (Automated Configuration Tool) for running such experiments is described, in combination a number of search strategies for deciding on the configurations to measure. Design Of Experiments (DOE) is discussed, with emphasis on Taguchi Methods. These statistical methods have been used extensively in manufacturing, but have not previously been used for configuring software systems. The novel contribution here is an industrial case study, applying the combination of ACT and Taguchi Methods to DC-Directory, a product from Data Connection Ltd (DCL). The case study investigated the applicability of Taguchi Methods for configuring complex software systems. Taguchi Methods were found to be useful for modelling and configuring DC- Directory, making them a valuable addition to the techniques available to system administrators and developers.

Design of the tool for periodic not evolvent profiles

Directory of Open Access Journals (Sweden)

Anisimov Roman

2017-01-01

Full Text Available The new approach to profiling of the tool for processing of parts with periodic not evolvent profiles are considered in the article The discriminatory analysis of periodic profiles including repetition of profile both in the plane of perpendicular axis of part, and in the plane of passing along part of axis is offered. In the basis of the offered profiling method the idea of space shaping by rated surface of product of tool surface lies. The big advantage of the offered approach in profiling is its combination with the analysis of parameters of process of engineering work. It allows to predict the accuracy and surface quality of product with not evolvent periodic profile. While using the offered approach the pinion cutter for processing of wheels with internal triangular teeths and mill for processing of the screw of the counter of consumption of liquid, complex profile of which consists of several formings, have been received

Design tools for complex dynamic security systems.

Energy Technology Data Exchange (ETDEWEB)

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

2007-01-01

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

Complexity in practice: understanding primary care as a complex adaptive system

Directory of Open Access Journals (Sweden)

Beverley Ellis

2010-06-01

Conclusions The results are real-world exemplars of the emergent properties of complex adaptive systems. Improving clinical governance in primary care requires both complex social interactions and underpinning informatics. The socio-technical lessons learned from this research should inform future management approaches.

Methodology for Measuring the Complexity of Enterprise Information Systems

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Ilja Holub

2016-07-01

Full Text Available The complexity of enterprise information systems is currently a challenge faced not only by IT professionals and project managers, but also by the users of such systems. Current methodologies and frameworks used to design and implement information systems do not specifically deal with the issue of their complexity and, apart from few exceptions, do not at all attempt to simplify the complexity. This article presents the author's own methodology for managing complexity, which can be used to complement any other methodology and which helps limit the growth of complexity. It introduces its own definition and metric of complexity, which it defines as the sum of entities of the individual UML models of the given system, which are selected according to the MMDIS methodology so as to consistently describe all relevant content dimensions of the system. The main objective is to propose a methodology to manage information system complexity and to verify it in practice on a real-life SAP implementation project.

Risk Modeling of Interdependent Complex Systems of Systems: Theory and Practice.

Science.gov (United States)

Haimes, Yacov Y

2018-01-01

The emergence of the complexity characterizing our systems of systems (SoS) requires a reevaluation of the way we model, assess, manage, communicate, and analyze the risk thereto. Current models for risk analysis of emergent complex SoS are insufficient because too often they rely on the same risk functions and models used for single systems. These models commonly fail to incorporate the complexity derived from the networks of interdependencies and interconnectedness (I-I) characterizing SoS. There is a need to reevaluate currently practiced risk analysis to respond to this reality by examining, and thus comprehending, what makes emergent SoS complex. The key to evaluating the risk to SoS lies in understanding the genesis of characterizing I-I of systems manifested through shared states and other essential entities within and among the systems that constitute SoS. The term "essential entities" includes shared decisions, resources, functions, policies, decisionmakers, stakeholders, organizational setups, and others. This undertaking can be accomplished by building on state-space theory, which is fundamental to systems engineering and process control. This article presents a theoretical and analytical framework for modeling the risk to SoS with two case studies performed with the MITRE Corporation and demonstrates the pivotal contributions made by shared states and other essential entities to modeling and analysis of the risk to complex SoS. A third case study highlights the multifarious representations of SoS, which require harmonizing the risk analysis process currently applied to single systems when applied to complex SoS. © 2017 Society for Risk Analysis.

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.

Third International Conference on Complex Systems

CERN Document Server

Minai, Ali A; Unifying Themes in Complex Systems

2006-01-01

In recent years, scientists have applied the principles of complex systems science to increasingly diverse fields. The results have been nothing short of remarkable: their novel approaches have provided answers to long-standing questions in biology, ecology, physics, engineering, computer science, economics, psychology and sociology. The Third International Conference on Complex Systems attracted over 400 researchers from around the world. The conference aimed to encourage cross-fertilization between the many disciplines represented and to deepen our understanding of the properties common to all complex systems. This volume contains selected transcripts from presentations given at the conference. Speakers include: Chris Adami, Kenneth Arrow, Michel Baranger, Dan Braha, Timothy Buchman, Michael Caramanis, Kathleen Carley, Greg Chaitin, David Clark, Jack Cohen, Jim Collins, George Cowan, Clay Easterly, Steven Eppinger, Irving Epstein, Dan Frey, Ary Goldberger, Helen Harte, Leroy Hood, Don Ingber, Atlee Jackson,...

"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...

Test-driven modeling and development of cloud-enabled cyber-physical smart systems

DEFF Research Database (Denmark)

Munck, Allan; Madsen, Jan

2017-01-01

Embedded products currently tend to evolve into large and complex smart systems where products are enriched with services through clouds and other web technologies. The complex characteristics of smart systems make it very difficult to guarantee functionality, safety, security and performance...

Systems engineering for very large systems

Science.gov (United States)

Lewkowicz, Paul E.

Very large integrated systems have always posed special problems for engineers. Whether they are power generation systems, computer networks or space vehicles, whenever there are multiple interfaces, complex technologies or just demanding customers, the challenges are unique. 'Systems engineering' has evolved as a discipline in order to meet these challenges by providing a structured, top-down design and development methodology for the engineer. This paper attempts to define the general class of problems requiring the complete systems engineering treatment and to show how systems engineering can be utilized to improve customer satisfaction and profit ability. Specifically, this work will focus on a design methodology for the largest of systems, not necessarily in terms of physical size, but in terms of complexity and interconnectivity.

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.

Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System.

Directory of Open Access Journals (Sweden)

Jinjun Tang

Full Text Available Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed collected from loop detectors located at points both upstream and downstream of a given link, and the output variable is the link travel time. A first order Takagi-Sugeno fuzzy rule set is used to complete the inference. For training the evolving fuzzy neural network (EFNN, two learning processes are proposed: (1 a K-means method is employed to partition input samples into different clusters, and a Gaussian fuzzy membership function is designed for each cluster to measure the membership degree of samples to the cluster centers. As the number of input samples increases, the cluster centers are modified and membership functions are also updated; (2 a weighted recursive least squares estimator is used to optimize the parameters of the linear functions in the Takagi-Sugeno type fuzzy rules. Testing datasets consisting of actual and simulated data are used to test the proposed method. Three common criteria including mean absolute error (MAE, root mean square error (RMSE, and mean absolute relative error (MARE are utilized to evaluate the estimation performance. Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR, instantaneous model (IM, linear model (LM, neural network (NN, and cumulative plots (CP.

Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System.

Science.gov (United States)

Tang, Jinjun; Zou, Yajie; Ash, John; Zhang, Shen; Liu, Fang; Wang, Yinhai

2016-01-01

Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed) collected from loop detectors located at points both upstream and downstream of a given link, and the output variable is the link travel time. A first order Takagi-Sugeno fuzzy rule set is used to complete the inference. For training the evolving fuzzy neural network (EFNN), two learning processes are proposed: (1) a K-means method is employed to partition input samples into different clusters, and a Gaussian fuzzy membership function is designed for each cluster to measure the membership degree of samples to the cluster centers. As the number of input samples increases, the cluster centers are modified and membership functions are also updated; (2) a weighted recursive least squares estimator is used to optimize the parameters of the linear functions in the Takagi-Sugeno type fuzzy rules. Testing datasets consisting of actual and simulated data are used to test the proposed method. Three common criteria including mean absolute error (MAE), root mean square error (RMSE), and mean absolute relative error (MARE) are utilized to evaluate the estimation performance. Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR), instantaneous model (IM), linear model (LM), neural network (NN), and cumulative plots (CP).

Improving evolvability of morphologies and controllers of developmental soft-bodied robots with novelty search

Directory of Open Access Journals (Sweden)

Michał eJoachimczak

2015-12-01

Full Text Available Novelty search is an evolutionary search algorithm based on the superficially contradictory idea that abandoning goal focused fitness function altogether can lead to the discovery of higher fitness solutions. In the course of our work, we have created a biologically inspired artificial development system with the purpose of automatically designing complex morphologies and controllers of multicellular, soft-bodied robots. Our goal is to harness the creative potential of in silico evolution so that it can provide us with novel and efficient designs that are free of any preconceived notions a human designer would have. In order to do so, we strive to allow for the evolution of arbitrary morphologies. Using a fitness-driven search algorithm, the system has been shown to be capable of evolving complex multicellular solutions consisting of hundreds of cells that can walk, run and swim, yet the large space of possible designs makes the search expensive and prone to getting stuck in local minima. In this work, we investigate how a developmental approach to the evolution of robotic designs benefits from abandoning objective fitness function. We discover that novelty search produced significantly better performing solutions. We then discuss the key factors of the success in terms of the phenotypic representation for the novelty search, the deceptive landscape for co-designing morphology/brain, and the complex development-based phenotypic encoding.

Blood-brain barrier-on-a-chip: Microphysiological systems that capture the complexity of the blood-central nervous system interface.

Science.gov (United States)

Phan, Duc Tt; Bender, R Hugh F; Andrejecsk, Jillian W; Sobrino, Agua; Hachey, Stephanie J; George, Steven C; Hughes, Christopher Cw

2017-11-01

The blood-brain barrier is a dynamic and highly organized structure that strictly regulates the molecules allowed to cross the brain vasculature into the central nervous system. The blood-brain barrier pathology has been associated with a number of central nervous system diseases, including vascular malformations, stroke/vascular dementia, Alzheimer's disease, multiple sclerosis, and various neurological tumors including glioblastoma multiforme. There is a compelling need for representative models of this critical interface. Current research relies heavily on animal models (mostly mice) or on two-dimensional (2D) in vitro models, neither of which fully capture the complexities of the human blood-brain barrier. Physiological differences between humans and mice make translation to the clinic problematic, while monolayer cultures cannot capture the inherently three-dimensional (3D) nature of the blood-brain barrier, which includes close association of the abluminal side of the endothelium with astrocyte foot-processes and pericytes. Here we discuss the central nervous system diseases associated with blood-brain barrier pathology, recent advances in the development of novel 3D blood-brain barrier -on-a-chip systems that better mimic the physiological complexity and structure of human blood-brain barrier, and provide an outlook on how these blood-brain barrier-on-a-chip systems can be used for central nervous system disease modeling. Impact statement The field of microphysiological systems is rapidly evolving as new technologies are introduced and our understanding of organ physiology develops. In this review, we focus on Blood-Brain Barrier (BBB) models, with a particular emphasis on how they relate to neurological disorders such as Alzheimer's disease, multiple sclerosis, stroke, cancer, and vascular malformations. We emphasize the importance of capturing the three-dimensional nature of the brain and the unique architecture of the BBB - something that until recently

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...

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.

A Cognition-based View of Decision Processes in Complex Social-Ecological Systems

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Kathi K. Beratan

2007-06-01

Full Text Available This synthesis paper is intended to provide an overview of individual and collective decision-making processes that might serve as a theoretical foundation for a complexity-based approach to environmental policy design and natural resource management planning. Human activities are the primary drivers of change in the Earth's biosphere today, so efforts to shift the trajectory of social-ecological systems must focus on changes in individual and collective human behavior. Recent advances in understanding the biological basis of thought and memory offer insights of use in designing management and planning processes. The human brain has evolved ways of dealing with complexity and uncertainty, and is particularly attuned to social information. Changes in an individual's schemas, reflecting changes in the patterns of neural connections that are activated by particular stimuli, occur primarily through nonconsious processes in response to experiential learning during repeated exposure to novel situations, ideas, and relationships. Discourse is an important mechanism for schema modification, and thus for behavior change. Through discourse, groups of people construct a shared story - a collective model - that is useful for predicting likely outcomes of actions and events. In effect, good stories are models that filter and organize distributed knowledge about complex situations and relationships in ways that are readily absorbed by human cognitive processes. The importance of discourse supports the view that collaborative approaches are needed to effectively deal with environmental problems and natural resource management challenges. Methods derived from the field of mediation and dispute resolution can help us take advantage of the distinctly human ability to deal with complexity and uncertainty. This cognitive view of decision making supports fundamental elements of resilience management and adaptive co-management, including fostering social learning

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...

A Weighted Evolving Network with Community Size Preferential Attachment

International Nuclear Information System (INIS)

Zhuo Zhiwei; Shan Erfang

2010-01-01

Community structure is an important characteristic in real complex network. It is a network consists of groups of nodes within which links are dense but among which links are sparse. In this paper, the evolving network include node, link and community growth and we apply the community size preferential attachment and strength preferential attachment to a growing weighted network model and utilize weight assigning mechanism from BBV model. The resulting network reflects the intrinsic community structure with generalized power-law distributions of nodes' degrees and strengths.

Semiotics of constructed complex systems

Energy Technology Data Exchange (ETDEWEB)

Landauer, C.; Bellman, K.L.

1996-12-31

The scope of this paper is limited to software and other constructed complex systems mediated or integrated by software. Our research program studies foundational issues that we believe will help us develop a theoretically sound approach to constructing complex systems. There have really been only two theoretical approaches that have helped us understand and develop computational systems: mathematics and linguistics. We show how semiotics can also play a role, whether we think of it as part of these other theories or as subsuming one or both of them. We describe our notion of {open_quotes}computational semiotics{close_quotes}, which we define to be the study of computational methods of dealing with symbols, show how such a theory might be formed, and describe what we might get from it in terms of more interesting use of symbols by computing systems. This research was supported in part by the Federal Highway Administration`s Office of Advanced Research and by the Advanced Research Projects Agency`s Software and Intelligent Systems Technology Office.

Complex energy system management using optimization techniques

Energy Technology Data Exchange (ETDEWEB)

Bridgeman, Stuart; Hurdowar-Castro, Diana; Allen, Rick; Olason, Tryggvi; Welt, Francois

2010-09-15

Modern energy systems are often very complex with respect to the mix of generation sources, energy storage, transmission, and avenues to market. Historically, power was provided by government organizations to load centers, and pricing was provided in a regulatory manner. In recent years, this process has been displaced by the independent system operator (ISO). This complexity makes the operation of these systems very difficult, since the components of the system are interdependent. Consequently, computer-based large-scale simulation and optimization methods like Decision Support Systems are now being used. This paper discusses the application of a DSS to operations and planning systems.

Complex systems and networks dynamics, controls and applications

CERN Document Server

Yu, Xinghuo; Chen, Guanrong; Yu, Wenwu

2016-01-01

This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of ...

Exploring the application of an evolutionary educational complex systems framework to teaching and learning about issues in the science and technology classroom

Science.gov (United States)

Yoon, Susan Anne

Understanding the world through a complex systems lens has recently garnered a great deal of interest in many knowledge disciplines. In the educational arena, interactional studies, through their focus on understanding patterns of system behaviour including the dynamical processes and trajectories of learning, lend support for investigating how a complex systems approach can inform educational research. This study uses previously existing literature and tools for complex systems applications and seeks to extend this research base by exploring learning outcomes of a complex systems framework when applied to curriculum and instruction. It is argued that by applying the evolutionary dynamics of variation, interaction and selection, complexity may be harnessed to achieve growth in both the social and cognitive systems of the classroom. Furthermore, if the goal of education, i.e., the social system under investigation, is to teach for understanding, conceptual knowledge of the kind described in Popper's (1972; 1976) World 3, needs to evolve. Both the study of memetic processes and knowledge building pioneered by Bereiter (cf. Bereiter, 2002) draw on the World 3 notion of ideas existing as conceptual artifacts that can be investigated as products outside of the individual mind providing an educational lens from which to proceed. The curricular topic addressed is the development of an ethical understanding of the scientific and technological issues of genetic engineering. 11 grade 8 students are studied as they proceed through 40 hours of curricular instruction based on the complex systems evolutionary framework. Results demonstrate growth in both complex systems thinking and content knowledge of the topic of genetic engineering. Several memetic processes are hypothesized to have influenced how and why ideas change. Categorized by factors influencing either reflective or non-reflective selection, these processes appear to have exerted differential effects on students

Biosphere 2: a prototype project for a permanent and evolving life system for Mars base.

Science.gov (United States)

Nelson, M; Allen, J P; Dempster, W F

1992-01-01

As part of the ground-based preparation for creating long-term life systems needed for space habitation and settlement, Space Biospheres Ventures (SBV) is undertaking the Biosphere 2 project near Oracle, Arizona. Biosphere 2, currently under construction, is scheduled to commence its operations in 1991 with a two-year closure period with a crew of eight people. Biosphere 2 is a facility which will be essentialy materially-closed to exchange with the outside environment. It is open to information and energy flow. Biosphere 2 is designed to achieve a complex life-support system by the integration of seven areas or "biomes"--rainforest, savannah, desert, marsh, ocean, intensive agriculture and human habitat. Unique bioregenerative technologies, such as soil bed reactors for air purification, aquatic waste processing systems, real-time analytic systems and complex computer monitoring and control systems are being developed for the Biosphere 2 project. Its operation should afford valuable insight into the functioning of complex life systems necessary for long-term habitation in space. It will serve as an experimental ground-based prototype and testbed for the stable, permanent life systems needed for human exploration of Mars.

Biosphere 2: A prototype project for a permanent and evolving life system for Mars base

Science.gov (United States)

Nelson, Mark; Allen, John P.; Dempster, William F.

As part of the ground-based preparation for creating long-term life systems needed for space habitation and settlement, Space Biopsheres Ventures (SBV) is undertaking the Biosphere 2 project near Oracle, Arizona. Biosphere 2, currently under construction, is scheduled to commence its operations in 1991 with a two-year closure period with a crew of eight people. Biosphere 2 is a facility which will be essentially materially-closed to exchange with the outside environment. It is open to information and energy flow. Biosphere 2 is designed to achieve a complex life-support system by the integration of seven areas or ``biomes'' - rainforest, savannah, desert, marsh, ocean, intensive agriculture and human habitat. Unique bioregenerative technologies, such as soil bed reactors for air purification, aquatic waste processing systems, real-time analytic systems and complex computer monitoring and control systems are being developed for the Biosphere 2 project. Its operation should afford valuable insight into the functioning of complex life systems necessary for long-term habitation in space. It will serve as an experimental ground-based prototype and testbed for the stable, permanent life systems needed for human exploration of Mars.

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.

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...

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...

Evolving cellular automata for diversity generation and pattern recognition: deterministic versus random strategy

International Nuclear Information System (INIS)

De Menezes, Marcio Argollo; Brigatti, Edgardo; Schwämmle, Veit

2013-01-01

Microbiological systems evolve to fulfil their tasks with maximal efficiency. The immune system is a remarkable example, where the distinction between self and non-self is made by means of molecular interaction between self-proteins and antigens, triggering affinity-dependent systemic actions. Specificity of this binding and the infinitude of potential antigenic patterns call for novel mechanisms to generate antibody diversity. Inspired by this problem, we develop a genetic algorithm where agents evolve their strings in the presence of random antigenic strings and reproduce with affinity-dependent rates. We ask what is the best strategy to generate diversity if agents can rearrange their strings a finite number of times. We find that endowing each agent with an inheritable cellular automaton rule for performing rearrangements makes the system more efficient in pattern-matching than if transformations are totally random. In the former implementation, the population evolves to a stationary state where agents with different automata rules coexist. (paper)

Energy Flows in Low-Entropy Complex Systems

Directory of Open Access Journals (Sweden)

Eric J. Chaisson

2015-12-01

Full Text Available Nature’s many complex systems—physical, biological, and cultural—are islands of low-entropy order within increasingly disordered seas of surrounding, high-entropy chaos. Energy is a principal facilitator of the rising complexity of all such systems in the expanding Universe, including galaxies, stars, planets, life, society, and machines. A large amount of empirical evidence—relating neither entropy nor information, rather energy—suggests that an underlying simplicity guides the emergence and growth of complexity among many known, highly varied systems in the 14-billion-year-old Universe, from big bang to humankind. Energy flows are as centrally important to life and society as they are to stars and galaxies. In particular, the quantity energy rate density—the rate of energy flow per unit mass—can be used to explicate in a consistent, uniform, and unifying way a huge collection of diverse complex systems observed throughout Nature. Operationally, those systems able to utilize optimal amounts of energy tend to survive and those that cannot are non-randomly eliminated.

Macroscopic Theory for Evolving Biological Systems Akin to Thermodynamics.

Science.gov (United States)

Kaneko, Kunihiko; Furusawa, Chikara

2018-05-20

We present a macroscopic theory to characterize the plasticity, robustness, and evolvability of biological responses and their fluctuations. First, linear approximation in intracellular reaction dynamics is used to demonstrate proportional changes in the expression of all cellular components in response to a given environmental stress, with the proportion coefficient determined by the change in growth rate as a consequence of the steady growth of cells. We further demonstrate that this relationship is supported through adaptation experiments of bacteria, perhaps too well as this proportionality is held even across cultures of different types of conditions. On the basis of simulations of cell models, we further show that this global proportionality is a consequence of evolution in which expression changes in response to environmental or genetic perturbations are constrained along a unique one-dimensional curve, which is a result of evolutionary robustness. It then follows that the expression changes induced by environmental changes are proportionally reduced across different components of a cell by evolution, which is akin to the Le Chatelier thermodynamics principle. Finally, with the aid of a fluctuation-response relationship, this proportionality is shown to hold between fluctuations caused by genetic changes and those caused by noise. Overall, these results and support from the theoretical and experimental literature suggest a formulation of cellular systems akin to thermodynamics, in which a macroscopic potential is given by the growth rate (or fitness) represented as a function of environmental and evolutionary changes.

Signs, Systems and Complexity of Transmedia Storytelling

Directory of Open Access Journals (Sweden)

Renira Rampazzo Gambarato

2012-12-01

Full Text Available This article addresses key concepts such as sign, system and complexity in order to approach transmedia storytelling and better understand its intricate nature. The theoretical framework chosen to investigate transmedia storytelling meanders is Semiotics by Charles Sanders Peirce (1839-1914 and General Systems Theory by Mario Bunge (1919-. The complexity of transmedia storytelling is not simply the one of the signs of the works included in a transmedia franchise. It also includes the complexity of the dispositions of users/consumers/players as interpreters of semiotic elements (e.g. characters, themes, environments, events and outcomes presented by transmedia products. It extends further to the complexity of social, cultural, economical and political constructs. The German transmedia narrative The Ultimate SuperHero-Blog by Stefan Gieren and Sofia’s Diary, a Portuguese multiplatform production by BeActive, are presented as examples of closed and open system transmedia storytelling respectively.

Language Networks as Complex Systems

Science.gov (United States)

Lee, Max Kueiming; Ou, Sheue-Jen

2008-01-01

Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…

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...

Catastrophic failure in complex socio-technical systems

International Nuclear Information System (INIS)

Weir, D.

2004-01-01

This paper reviews the sequences leading to catastrophic failures in complex socio-technical systems. It traces some of the elements of an analytic framework to that proposed by Beer in Decision and Control, first published in 1966, and argues that these ideas are centrally relevant to a topic on which research interest has developed subsequently, the study of crises, catastrophes and disasters in complex socio-technical systems in high technology sectors. But while the system perspective is central, it is not by itself entirely adequate. The problems discussed cannot be discussed simply in terms of system parameters like variety, redundancy and complexity. Much empirical research supports the view that these systems typically operate in degraded mode. The degradations may be primarily initiated within the social components of the socio-technical system. Such variables as hierarchical position, actors' motivations and intentions are relevant to explain the ways in which communication systems typically operate to filter out messages from lower participants and to ignore the 'soft signals' issuing from small-scale and intermittent malfunctions. (author)

Dissipative quantum trajectories in complex space: Damped harmonic oscillator

Energy Technology Data Exchange (ETDEWEB)

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

2016-10-15

Dissipative quantum trajectories in complex space are investigated in the framework of the logarithmic nonlinear Schrödinger equation. The logarithmic nonlinear Schrödinger equation provides a phenomenological description for dissipative quantum systems. Substituting the wave function expressed in terms of the complex action into the complex-extended logarithmic nonlinear Schrödinger equation, we derive the complex quantum Hamilton–Jacobi equation including the dissipative potential. It is shown that dissipative quantum trajectories satisfy a quantum Newtonian equation of motion in complex space with a friction force. Exact dissipative complex quantum trajectories are analyzed for the wave and solitonlike solutions to the logarithmic nonlinear Schrödinger equation for the damped harmonic oscillator. These trajectories converge to the equilibrium position as time evolves. It is indicated that dissipative complex quantum trajectories for the wave and solitonlike solutions are identical to dissipative complex classical trajectories for the damped harmonic oscillator. This study develops a theoretical framework for dissipative quantum trajectories in complex space.

Dissipative quantum trajectories in complex space: Damped harmonic oscillator

International Nuclear Information System (INIS)

Chou, Chia-Chun

2016-01-01

Dissipative quantum trajectories in complex space are investigated in the framework of the logarithmic nonlinear Schrödinger equation. The logarithmic nonlinear Schrödinger equation provides a phenomenological description for dissipative quantum systems. Substituting the wave function expressed in terms of the complex action into the complex-extended logarithmic nonlinear Schrödinger equation, we derive the complex quantum Hamilton–Jacobi equation including the dissipative potential. It is shown that dissipative quantum trajectories satisfy a quantum Newtonian equation of motion in complex space with a friction force. Exact dissipative complex quantum trajectories are analyzed for the wave and solitonlike solutions to the logarithmic nonlinear Schrödinger equation for the damped harmonic oscillator. These trajectories converge to the equilibrium position as time evolves. It is indicated that dissipative complex quantum trajectories for the wave and solitonlike solutions are identical to dissipative complex classical trajectories for the damped harmonic oscillator. This study develops a theoretical framework for dissipative quantum trajectories in complex space.

Membrane tethering complexes in the endosomal system

Directory of Open Access Journals (Sweden)

Anne eSpang

2016-05-01

Full Text Available Vesicles that are generated by endocytic events at the plasma membrane are destined to early endosomes. A prerequisite for proper fusion is the tethering of two membrane entities. Tethering of vesicles to early endosomes is mediated by the CORVET complex, while fusion of late endosomes with lysosomes depends on the HOPS complex. Recycling through the TGN and to the plasma membrane is facilitated by the GARP and EARP complexes, respectively. However, there are other tethering functions in the endosomal system as there are multiple pathways through which proteins can be delivered from endosomes to either the TGN or the plasma membrane. Furthermore, complexes that may be part of novel tethering complexes have been recently identified. Thus it is likely that more tethering factors exist. In this review, I will provide an overview of different tethering complexes of the endosomal system and discuss how they may provide specificity in membrane traffic.

Toxic and nontoxic components of botulinum neurotoxin complex are evolved from a common ancestral zinc protein

International Nuclear Information System (INIS)

Inui, Ken; Sagane, Yoshimasa; Miyata, Keita; Miyashita, Shin-Ichiro; Suzuki, Tomonori; Shikamori, Yasuyuki; Ohyama, Tohru; Niwa, Koichi; Watanabe, Toshihiro

2012-01-01

Highlights: ► BoNT and NTNHA proteins share a similar protein architecture. ► NTNHA and BoNT were both identified as zinc-binding proteins. ► NTNHA does not have a classical HEXXH zinc-coordinating motif similar to that found in all serotypes of BoNT. ► Homology modeling implied probable key residues involved in zinc coordination. -- Abstract: Zinc atoms play an essential role in a number of enzymes. Botulinum neurotoxin (BoNT), the most potent toxin known in nature, is a zinc-dependent endopeptidase. Here we identify the nontoxic nonhemagglutinin (NTNHA), one of the BoNT-complex constituents, as a zinc-binding protein, along with BoNT. A protein structure classification database search indicated that BoNT and NTNHA share a similar domain architecture, comprising a zinc-dependent metalloproteinase-like, BoNT coiled-coil motif and concanavalin A-like domains. Inductively coupled plasma-mass spectrometry analysis demonstrated that every single NTNHA molecule contains a single zinc atom. This is the first demonstration of a zinc atom in this protein, as far as we know. However, the NTNHA molecule does not possess any known zinc-coordinating motif, whereas all BoNT serotypes possess the classical HEXXH motif. Homology modeling of the NTNHA structure implied that a consensus K-C-L-I-K-X 35 -D sequence common among all NTNHA serotype molecules appears to coordinate a single zinc atom. These findings lead us to propose that NTNHA and BoNT may have evolved distinct functional specializations following their branching out from a common ancestral zinc protein.

Evolving colon injury management: a review.

Science.gov (United States)

Greer, Lauren T; Gillern, Suzanne M; Vertrees, Amy E

2013-02-01

The colon is the second most commonly injured intra-abdominal organ in penetrating trauma. Management of traumatic colon injuries has evolved significantly over the past 200 years. Traumatic colon injuries can have a wide spectrum of severity, presentation, and management options. There is strong evidence that most non-destructive colon injuries can be successfully managed with primary repair or primary anastomosis. The management of destructive colon injuries remains controversial with most favoring resection with primary anastomosis and others favor colonic diversion in specific circumstances. The historical management of traumatic colon injuries, common mechanisms of injury, demographics, presentation, assessment, diagnosis, management, and complications of traumatic colon injuries both in civilian and military practice are reviewed. The damage control revolution has added another layer of complexity to management with continued controversy.

Natural selection promotes antigenic evolvability

NARCIS (Netherlands)

Graves, C.J.; Ros, V.I.D.; Stevenson, B.; Sniegowski, P.D.; Brisson, D.

2013-01-01

The hypothesis that evolvability - the capacity to evolve by natural selection - is itself the object of natural selection is highly intriguing but remains controversial due in large part to a paucity of direct experimental evidence. The antigenic variation mechanisms of microbial pathogens provide

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.

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.

Developing Leadership for Increasing Complexity: A Review of Online Graduate Leadership Programs

Science.gov (United States)

Winton, Steven L.; Palmer, Sarah; Hughes, Patrick J.

2018-01-01

Leadership education must evolve to keep pace with the growing recognition that effective leadership happens in a complex environment and is as much a systemic variable as a personal one. As part of a program review process, a graduate leadership program at a private Midwestern university conducted a qualitative review of 18 online graduate…

The Evolving Role of Physicians - Don’t Forget the Generalist Primary Care Providers; Comment on “Non-physician Clinicians in Sub-Saharan Africa and the Evolving Role of Physicians”

Directory of Open Access Journals (Sweden)

Vincent Kalumire Cubaka

2016-10-01

Full Text Available The editorial “Non-physician Clinicians in Sub-Saharan Africa and the Evolving Role of Physicians” by Eyal et al describes non-physician clinicians’ (NPC need for mentorship and support from physicians. We emphasise the same need of support for front line generalist primary healthcare providers who carry out complex tasks yet may have an inadequate skill mix.

The Evolving Role of Physicians - Don't Forget the Generalist Primary Care Providers Comment on "Non-physician Clinicians in Sub-Saharan Africa and the Evolving Role of Physicians".

Science.gov (United States)

Cubaka, Vincent Kalumire; Schriver, Michael; Flinkenflögel, Maaike; Cotton, Philip

2016-06-12

The editorial "Non-physician Clinicians in Sub-Saharan Africa and the Evolving Role of Physicians" by Eyal et al describes non-physician clinicians' (NPC) need for mentorship and support from physicians. We emphasise the same need of support for front line generalist primary healthcare providers who carry out complex tasks yet may have an inadequate skill mix. © 2016 by Kerman University of Medical Sciences.

On synchronisation of a class of complex chaotic systems with complex unknown parameters via integral sliding mode control

Science.gov (United States)

Tirandaz, Hamed; Karami-Mollaee, Ali

2018-06-01

Chaotic systems demonstrate complex behaviour in their state variables and their parameters, which generate some challenges and consequences. This paper presents a new synchronisation scheme based on integral sliding mode control (ISMC) method on a class of complex chaotic systems with complex unknown parameters. Synchronisation between corresponding states of a class of complex chaotic systems and also convergence of the errors of the system parameters to zero point are studied. The designed feedback control vector and complex unknown parameter vector are analytically achieved based on the Lyapunov stability theory. Moreover, the effectiveness of the proposed methodology is verified by synchronisation of the Chen complex system and the Lorenz complex systems as the leader and the follower chaotic systems, respectively. In conclusion, some numerical simulations related to the synchronisation methodology is given to illustrate the effectiveness of the theoretical discussions.

Complex and Adaptive Dynamical Systems A Primer

CERN Document Server

Gros, Claudius

2011-01-01

We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

Complex and adaptive dynamical systems a primer

CERN Document Server

Gros, Claudius

2007-01-01

We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

Synchronization in Complex Networks of Nonlinear Dynamical Systems

CERN Document Server

Wu, Chai Wah

2007-01-01

This book brings together two emerging research areas: synchronization in coupled nonlinear systems and complex networks, and study conditions under which a complex network of dynamical systems synchronizes. While there are many texts that study synchronization in chaotic systems or properties of complex networks, there are few texts that consider the intersection of these two very active and interdisciplinary research areas. The main theme of this book is that synchronization conditions can be related to graph theoretical properties of the underlying coupling topology. The book introduces ide

Large-scale computing techniques for complex system simulations

CERN Document Server

Dubitzky, Werner; Schott, Bernard

2012-01-01

Complex systems modeling and simulation approaches are being adopted in a growing number of sectors, including finance, economics, biology, astronomy, and many more. Technologies ranging from distributed computing to specialized hardware are explored and developed to address the computational requirements arising in complex systems simulations. The aim of this book is to present a representative overview of contemporary large-scale computing technologies in the context of complex systems simulations applications. The intention is to identify new research directions in this field and

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...

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.

Complexity, adaptations and variations in the secondary insemination system of female Dermanyssina mites (Acari: Anactinothrichida: Gamasida): the case of Afrocypholaelaps africana.

Science.gov (United States)

Di Palma, A; Seeman, O D; Alberti, G

2017-07-01

Gamasine mites, mainly of the taxon Dermanyssina, possess a secondarily evolved insemination system (sperm access system), of which there are two, generally recognized, structurally different types, the laelapid- and the phytoseiid-type. The ultrastructure of the female sperm access system in Afrocypholaelaps africana is described. It consists of paired insemination pores, opening between the bases of legs three and four, and paired cuticle-lined tubules that converge into a large, sack-like spermatheca, remarkably cuticle-lined as well. The entire spermatheca and part of the tubules are embedded in a peculiar syncytial tissue where numerous sperm cells are present. The general organization of this insemination system is of the laelapid-type. However, it presents striking structural differences, compared with the systems described in Varroa destructor and Hattena cometis, the other gamasine mites having a laelapid-type system studied ultrastructurally until now. The functional morphology, complexity and variations of the sperm access system in Dermanyssina are discussed and correlated with the evolutionary biology of the group.

A new decision sciences for complex systems.

Science.gov (United States)

Lempert, Robert J

2002-05-14

Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an approach to decision-making under conditions of deep uncertainty that is ideally suited to applying complex systems to policy analysis. The article demonstrates the approach on the policy problem of global climate change, with a particular focus on the role of technology policies in a robust, adaptive strategy for greenhouse gas abatement.

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.

Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.

Science.gov (United States)

Steinacher, Arno; Bates, Declan G; Akman, Ozgur E; Soyer, Orkun S

2016-01-01

Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for

Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.

Directory of Open Access Journals (Sweden)

Arno Steinacher

Full Text Available Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest

Systems thinking and complexity: considerations for health promoting schools.

Science.gov (United States)

Rosas, Scott R

2017-04-01

The health promoting schools concept reflects a comprehensive and integrated philosophy to improving student and personnel health and well-being. Conceptualized as a configuration of interacting, interdependent parts connected through a web of relationships that form a whole greater than the sum of its parts, school health promotion initiatives often target several levels (e.g. individual, professional, procedural and policy) simultaneously. Health promoting initiatives, such as those operationalized under the whole school approach, include several interconnected components that are coordinated to improve health outcomes in complex settings. These complex systems interventions are embedded in intricate arrangements of physical, biological, ecological, social, political and organizational relationships. Systems thinking and characteristics of complex adaptive systems are introduced in this article to provide a perspective that emphasizes the patterns of inter-relationships associated with the nonlinear, dynamic and adaptive nature of complex hierarchical systems. Four systems thinking areas: knowledge, networks, models and organizing are explored as a means to further manage the complex nature of the development and sustainability of health promoting schools. Applying systems thinking and insights about complex adaptive systems can illuminate how to address challenges found in settings with both complicated (i.e. multi-level and multisite) and complex aspects (i.e. synergistic processes and emergent outcomes). © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Anomaly Detection for Complex Systems

Data.gov (United States)

National Aeronautics and Space Administration — In performance maintenance in large, complex systems, sensor information from sub-components tends to be readily available, and can be used to make predictions about...

Disgust: Evolved function and structure

NARCIS (Netherlands)

Tybur, J.M.; Lieberman, D.; Kurzban, R.; DeScioli, P.

2013-01-01

Interest in and research on disgust has surged over the past few decades. The field, however, still lacks a coherent theoretical framework for understanding the evolved function or functions of disgust. Here we present such a framework, emphasizing 2 levels of analysis: that of evolved function and

New and Old Aspects of Complexity in Modern Research

CERN Document Server

Musaev, Djamaladdin

2012-01-01

Complexity occurs in biological and synthetic systems alike.  This general phenomenon has been addressed in recent publications by investigators in disciplines ranging from chemistry and biology to psychology and philosophy.  Studies of complexity for molecular scientists have focussed on breaking symmetry, dissipative processes, and emergence.  Investigators in the social and medical sciences have focused on neurophenomenology, cognitive approaches and self-consciousness.  Complexity in both structure and function is inherent in many scientific disciplines of current significance and also in technologies of current importance that are rapidly evolving to address global societal needs.  Several of these multifaceted scientific disciplines are addressed in this book including complexity from the general and philosophical perspective, magnetic phenomena, control of self assembly and function in large multicomponent clusters, application of theory to probe structure and mechanism in highly complex molecular...

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.

Evolving dynamics of trading behavior based on coordination game in complex networks

Science.gov (United States)

Bian, Yue-tang; Xu, Lu; Li, Jin-sheng

2016-05-01

This work concerns the modeling of evolvement of trading behavior in stock markets. Based on the assumption of the investors' limited rationality, the evolution mechanism of trading behavior is modeled according to the investment strategy of coordination game in network, that investors are prone to imitate their neighbors' activity through comprehensive analysis on the risk dominance degree of certain investment behavior, the network topology of their relationship and its heterogeneity. We investigate by mean-field analysis and extensive simulations the evolution of investors' trading behavior in various typical networks under different risk dominance degree of investment behavior. Our results indicate that the evolution of investors' behavior is affected by the network structure of stock market and the effect of risk dominance degree of investment behavior; the stability of equilibrium states of investors' behavior dynamics is directly related with the risk dominance degree of some behavior; connectivity and heterogeneity of the network plays an important role in the evolution of the investment behavior in stock market.

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.

The evolving network structure of US airline system during 1990-2010

Science.gov (United States)

Lin, Jingyi; Ban, Yifang

2014-09-01

This paper analyzes the growth and evolution of topological features of the US airline network over a 20-year period. It captures the change in the network system from different dimensions of complex networks such as centrality distribution and various structural properties of the network over time. We first illustrate the results of a set of measures, including degree, strength, betweenness centrality, and clustering structure. The geographic features of airport systems, spatial distance and network efficiency are also discussed in this section. In order to further capture the dynamics of the system, this paper also explores the correlation between different measures, and investigates various interactions inside the network. Overall this study offers a novel approach to understanding the growth and evolution of real physical networks.

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 Systems Analysis of Cell Cycling Models in Carcinogenesis:II. Cell Genome and Interactome, Neoplastic Non-random Transformation Models in Topoi with Lukasiewicz-Logic and MV Algebras

CERN Document Server

Baianu, I C

2004-01-01

Quantitative Biology, abstract q-bio.OT/0406045 From: I.C. Baianu Dr. [view email] Date (v1): Thu, 24 Jun 2004 02:45:13 GMT (164kb) Date (revised v2): Fri, 2 Jul 2004 00:58:06 GMT (160kb) Complex Systems Analysis of Cell Cycling Models in Carcinogenesis: II. Authors: I.C. Baianu Comments: 23 pages, 1 Figure Report-no: CC04 Subj-class: Other Carcinogenesis is a complex process that involves dynamically inter-connected modular sub-networks that evolve under the influence of micro-environmentally induced perturbations, in non-random, pseudo-Markov chain processes. An appropriate n-stage model of carcinogenesis involves therefore n-valued Logic treatments of nonlinear dynamic transformations of complex functional genomes and cell interactomes. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous, Boolean or "fuzzy", logic models of genetic activities in vivo....

Development of TIGER code for radionuclide transport in a geochemically evolving region

International Nuclear Information System (INIS)

Mihara, Morihiro; Ooi, Takao

2004-01-01

In a transuranic (TRU) waste geological disposal facility, using cementitious materials is being considered. Cementitious materials will gradually dissolve in groundwater over the long-term. In the performance assessment report of a TRU waste repository in Japan already published, the most conservative radionuclide migration parameter set was selected considering the evolving cementitious material. Therefore, a tool to perform the calculation of radionuclide transport considering long-term geochemically evolving cementitious materials, named the TIGER code, Transport In Geochemically Evolving Region was developed to calculate a more realistic performance assessment. It can calculate radionuclide transport in engineered and natural barrier systems. In this report, mathematical equations of this code are described and validated with analytical solutions and results of other codes for radionuclide transport. The more realistic calculation of radionuclide transport for a TRU waste geological disposal system using the TIGER code could be performed. (author)

Morphogenetic Engineering Toward Programmable Complex Systems

CERN Document Server

Sayama, Hiroki; Michel, Olivier

2012-01-01

Generally, spontaneous pattern formation phenomena are random and repetitive, whereas elaborate devices are the deterministic product of human design. Yet, biological organisms and collective insect constructions are exceptional examples of complex systems that are both self-organized and architectural.   This book is the first initiative of its kind toward establishing a new field of research, Morphogenetic Engineering, to explore the modeling and implementation of “self-architecturing” systems. Particular emphasis is placed on the programmability and computational abilities of self-organization, properties that are often underappreciated in complex systems science—while, conversely, the benefits of self-organization are often underappreciated in engineering methodologies.   Altogether, the aim of this work is to provide a framework for and examples of a larger class of “self-architecturing” systems, while addressing fundamental questions such as   > How do biological organisms carry out morphog...

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 ...

Krylov Subspace Methods for Complex Non-Hermitian Linear Systems. Thesis

Science.gov (United States)

Freund, Roland W.

1991-01-01

We consider Krylov subspace methods for the solution of large sparse linear systems Ax = b with complex non-Hermitian coefficient matrices. Such linear systems arise in important applications, such as inverse scattering, numerical solution of time-dependent Schrodinger equations, underwater acoustics, eddy current computations, numerical computations in quantum chromodynamics, and numerical conformal mapping. Typically, the resulting coefficient matrices A exhibit special structures, such as complex symmetry, or they are shifted Hermitian matrices. In this paper, we first describe a Krylov subspace approach with iterates defined by a quasi-minimal residual property, the QMR method, for solving general complex non-Hermitian linear systems. Then, we study special Krylov subspace methods designed for the two families of complex symmetric respectively shifted Hermitian linear systems. We also include some results concerning the obvious approach to general complex linear systems by solving equivalent real linear systems for the real and imaginary parts of x. Finally, numerical experiments for linear systems arising from the complex Helmholtz equation are reported.

An evolving research agenda for human-coastal systems

Science.gov (United States)

Lazarus, Eli D.; Ellis, Michael A.; Brad Murray, A.; Hall, Damon M.

2016-03-01

morphodynamics and practitioners of coastal management. Future research into human-coastal systems can benefit from decades of interdisciplinary work on the complex dynamics of common-pool resources, from computational efficiency and new techniques in numerical modeling, and from the growing catalog of high-resolution geospatial data for natural and developed coastlines around the world.

A new decision sciences for complex systems

OpenAIRE

Lempert, Robert J.

2002-01-01

Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an...

Promoting evaluation capacity building in a complex adaptive system.

Science.gov (United States)

Lawrenz, Frances; Kollmann, Elizabeth Kunz; King, Jean A; Bequette, Marjorie; Pattison, Scott; Nelson, Amy Grack; Cohn, Sarah; Cardiel, Christopher L B; Iacovelli, Stephanie; Eliou, Gayra Ostgaard; Goss, Juli; Causey, Lauren; Sinkey, Anne; Beyer, Marta; Francisco, Melanie

2018-04-10

This study provides results from an NSF funded, four year, case study about evaluation capacity building in a complex adaptive system, the Nanoscale Informal Science Education Network (NISE Net). The results of the Complex Adaptive Systems as a Model for Network Evaluations (CASNET) project indicate that complex adaptive system concepts help to explain evaluation capacity building in a network. The NISE Network was found to be a complex learning system that was supportive of evaluation capacity building through feedback loops that provided for information sharing and interaction. Participants in the system had different levels of and sources of evaluation knowledge. To be successful at building capacity, the system needed to have a balance between both centralized and decentralized control, coherence, redundancy, and diversity. Embeddedness of individuals within the system also provided support and moved the capacity of the system forward. Finally, success depended on attention being paid to the control of resources. Implications of these findings are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Lie and Noether symmetries of systems of complex ordinary ...

Indian Academy of Sciences (India)

2014-07-02

Jul 2, 2014 ... Abstract. The Lie and Noether point symmetry analyses of a kth-order system of m complex ordi- nary differential equations (ODEs) with m dependent variables are performed. The decomposition of complex symmetries of the given system of complex ODEs yields Lie- and Noether-like opera- tors.

A multi-objective approach to evolving platooning strategies in intelligent transportation systems

NARCIS (Netherlands)

Illigen, W. van; Haasdijk, E.; Kester, L.J.H.M.

2013-01-01

The research in this paper is inspired by a vision of intelligent vehicles that autonomously move along motorways: they join and leave trains of vehicles (platoons), overtake other vehicles, etc. We propose a multi-objective evolutionary algorithm based on NEAT and SPEA2 that evolves highlevel

A Multi-Objective Approach to Evolving Platooning Strategies in Intelligent Transportation Systems

NARCIS (Netherlands)

van Willigen, W; Haasdijk, E; Kester, Leon

2013-01-01

The research in this paper is inspired by a vision of intelligent vehicles that autonomously move along motorways: they join and leave trains of vehicles (platoons), overtake other vehicles, etc. We propose a multi-objective evolutionary algorithm based on NEAT and SPEA2 that evolves high-level

Managing Programmatic Risk for Complex Space System Developments

Science.gov (United States)

Panetta, Peter V.; Hastings, Daniel; Brumfield, Mark (Technical Monitor)

2001-01-01

Risk management strategies have become a recent important research topic to many aerospace organizations as they prepare to develop the revolutionary complex space systems of the future. Future multi-disciplinary complex space systems will make it absolutely essential for organizations to practice a rigorous, comprehensive risk management process, emphasizing thorough systems engineering principles to succeed. Project managers must possess strong leadership skills to direct high quality, cross-disciplinary teams for successfully developing revolutionary space systems that are ever increasing in complexity. Proactive efforts to reduce or eliminate risk throughout a project's lifecycle ideally must be practiced by all technical members in the organization. This paper discusses some of the risk management perspectives that were collected from senior managers and project managers of aerospace and aeronautical organizations by the use of interviews and surveys. Some of the programmatic risks which drive the success or failure of projects are revealed. Key findings lead to a number of insights for organizations to consider for proactively approaching the risks which face current and future complex space systems projects.

Automated design of complex dynamic systems.

Directory of Open Access Journals (Sweden)

Michiel Hermans

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

Diagnostics of the vibrations of complex rotor systems

Science.gov (United States)

Yugraytis, I. Y.; Ragulskis, K. M.; Ionushas, R. A.; Karuzhene, I. P.

1973-01-01

The parameters of the imbalance of a complex rotor system, having n parallel rotors and having six degrees of freedom, can be determined from the parameters of the vibrations of two appropriate degrees of freedom. This considerably simplifies diagnostics of the vibrations of complex rotor systems.

Applications of Nonlinear Dynamics Model and Design of Complex Systems

CERN Document Server

In, Visarath; Palacios, Antonio

2009-01-01

This edited book is aimed at interdisciplinary, device-oriented, applications of nonlinear science theory and methods in complex systems. In particular, applications directed to nonlinear phenomena with space and time characteristics. Examples include: complex networks of magnetic sensor systems, coupled nano-mechanical oscillators, nano-detectors, microscale devices, stochastic resonance in multi-dimensional chaotic systems, biosensors, and stochastic signal quantization. "applications of nonlinear dynamics: model and design of complex systems" brings together the work of scientists and engineers that are applying ideas and methods from nonlinear dynamics to design and fabricate complex systems.

Toxic and nontoxic components of botulinum neurotoxin complex are evolved from a common ancestral zinc protein

Energy Technology Data Exchange (ETDEWEB)

Inui, Ken [Department of Food and Cosmetic Science, Faculty of Bioindustry, Tokyo University of Agriculture, 196 Yasaka, Abashiri 099-2493 (Japan); Japan Society for the Promotion of Science, 1-8 Chiyoda-ku, Tokyo 102-8472 (Japan); Sagane, Yoshimasa [Department of Food and Cosmetic Science, Faculty of Bioindustry, Tokyo University of Agriculture, 196 Yasaka, Abashiri 099-2493 (Japan); Miyata, Keita [Department of Food and Cosmetic Science, Faculty of Bioindustry, Tokyo University of Agriculture, 196 Yasaka, Abashiri 099-2493 (Japan); Japan Society for the Promotion of Science, 1-8 Chiyoda-ku, Tokyo 102-8472 (Japan); Miyashita, Shin-Ichiro [Department of Food and Cosmetic Science, Faculty of Bioindustry, Tokyo University of Agriculture, 196 Yasaka, Abashiri 099-2493 (Japan); Suzuki, Tomonori [Department of Bacteriology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, 2-5-1 Shikata-cho, Kita-ku, Okayama 700-8558 (Japan); Shikamori, Yasuyuki [Agilent Technologies International Japan, Ltd. Takaura-cho 9-1, Hachioji-shi, Tokyo 192-0033 (Japan); Ohyama, Tohru; Niwa, Koichi [Department of Food and Cosmetic Science, Faculty of Bioindustry, Tokyo University of Agriculture, 196 Yasaka, Abashiri 099-2493 (Japan); Watanabe, Toshihiro, E-mail: t-watana@bioindustry.nodai.ac.jp [Department of Food and Cosmetic Science, Faculty of Bioindustry, Tokyo University of Agriculture, 196 Yasaka, Abashiri 099-2493 (Japan)

2012-03-16

Highlights: Black-Right-Pointing-Pointer BoNT and NTNHA proteins share a similar protein architecture. Black-Right-Pointing-Pointer NTNHA and BoNT were both identified as zinc-binding proteins. Black-Right-Pointing-Pointer NTNHA does not have a classical HEXXH zinc-coordinating motif similar to that found in all serotypes of BoNT. Black-Right-Pointing-Pointer Homology modeling implied probable key residues involved in zinc coordination. -- Abstract: Zinc atoms play an essential role in a number of enzymes. Botulinum neurotoxin (BoNT), the most potent toxin known in nature, is a zinc-dependent endopeptidase. Here we identify the nontoxic nonhemagglutinin (NTNHA), one of the BoNT-complex constituents, as a zinc-binding protein, along with BoNT. A protein structure classification database search indicated that BoNT and NTNHA share a similar domain architecture, comprising a zinc-dependent metalloproteinase-like, BoNT coiled-coil motif and concanavalin A-like domains. Inductively coupled plasma-mass spectrometry analysis demonstrated that every single NTNHA molecule contains a single zinc atom. This is the first demonstration of a zinc atom in this protein, as far as we know. However, the NTNHA molecule does not possess any known zinc-coordinating motif, whereas all BoNT serotypes possess the classical HEXXH motif. Homology modeling of the NTNHA structure implied that a consensus K-C-L-I-K-X{sub 35}-D sequence common among all NTNHA serotype molecules appears to coordinate a single zinc atom. These findings lead us to propose that NTNHA and BoNT may have evolved distinct functional specializations following their branching out from a common ancestral zinc protein.

Partially satisfied to fully satisfied transitions in co-evolving inverse voter model and possible scaling behavior

International Nuclear Information System (INIS)

Choi, C.W.; Xu, C.; Hui, P.M.

2015-01-01

Understanding co-evolving networks characterized by the mutual influence of agents' actions and network structure remains a challenge. We study a co-evolving inverse voter model in which agents adapt to achieve a preferred environment with more opposite-opinion neighbors by rewiring their connections and switching opinion. Numerical studies reveal a transition from a dynamic partially satisfied phase to a frozen fully satisfied phase as the rewiring probability is varied. A simple mean field theory is shown to capture the behavior only qualitatively. An improved mean field theory carrying a longer spatial correlation gives better results. Motivated by numerical results in networks of different degrees and mean field results, we propose a scaling variable that combines the rewiring probability and mean degree in a special form. The scaling variable is shown to work well in analyzing data corresponding to different networks and different rewiring probabilities. An application is to predict the results for networks of different degrees based solely on results obtained from networks of one degree. Studying scaling behavior provides an alternative path for understanding co-evolving agent-based dynamical systems, especially in light of the trade-off between complexity of a theory and its accuracy. - Highlights: • Identified key features and phase transitions in coevolving inverse voter model. • Constructed a better theory incorporating longer spatial correlation. • Proposed scaling variable and illustrated possible scaling behavior. • Used scaling behavior to predict results of IVM in a different network.

Some overdetermined systems of complex partial differential equations

International Nuclear Information System (INIS)

Le Hung Son.

1990-01-01

In this paper we extend some properties of analytic functions on several complex variables to solutions of overdetermined systems of complex partial differential equations. It is proved that many global properties of analytic functions are true for solutions of the Vekua system in special cases. The relation between analytic functions and solutions of quasi-linear systems is discussed in the paper. (author). 8 refs

Fourth International Conference on Complex Systems Design & Management

CERN Document Server

Boulanger, Frédéric; Krob, Daniel; Marchal, Clotilde

2014-01-01

This book contains all refereed papers that were accepted to the fourth edition of the « Complex Systems Design & Management » (CSD&M 2013) international conference which took place in Paris (France) from December 4-6, 2013. These proceedings cover the most recent trends in the emerging field of complex systems sciences & practices from an industrial and academic perspective, including the main industrial domains (transport, defense & security, electronics, energy & environment, e-services), scientific & technical topics (systems fundamentals, systems architecture & engineering, systems metrics & quality, systemic tools) and system types (transportation systems, embedded systems, software & information systems, systems of systems, artificial ecosystems). The CSD&M 2013 conference is organized under the guidance of the CESAMES non-profit organization

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.

Complex Systems: Science for the 21st Century

Energy Technology Data Exchange (ETDEWEB)

Shank, Charles V. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Awschalom, David [Univ. of California, Santa Barbara, CA (United States); Bawendi, Moungi [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Frechet, Jean [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Murphy, Donald [Lucent Technologies (United States); Stupp, Sam [Northwestern Univ., Evanston, IL (United States); Wolynes, Peter [Univ. of Illinois, Urbana, IL (United States)

1999-03-06

The workshop was designed to help define new scientific directions related to complex systems in order to create new understanding about the nano world and complicated, multicomponent structures. Five emerging themes regarding complexity were covered: Collective Phenomena; Materials by Design; Functional Systems; Nature's Mastery; and New Tools.

Project risk management in complex petrochemical system

Directory of Open Access Journals (Sweden)

Kirin Snežana

2012-01-01

Full Text Available Investigation of risk in complex industrial systems, as well as evaluation of main factors influencing decision making and implementation process using large petrochemical company as an example, has proved the importance of successful project risk management. This is even more emphasized when analyzing systems with complex structure, i.e. with several organizational units. It has been shown that successful risk management requires modern methods, based on adequate application of statistical analysis methods.

What is complex in the complex world? Niklas Luhmann and the theory of social systems

Directory of Open Access Journals (Sweden)

Clarissa Eckert Baeta Neves

Full Text Available This paper discusses Niklas Luhmann's understanding of complexity, its function in the theory and the different ways of its use. It starts with the paradigmatic change that occurred in the field of general Science, with the rupture of the Newtonian model. In the 20th century, the paradigm of order, symmetry, regularity, regulation of the intellect to things, collapses.Based on new formulations of Physics, Chemistry, etc., a new universe is built on bases radically opposed to those of modern Science.Chaos, the procedural irreversibility, indeterminism, the observer and the complexity are rehabilitated.This new conceptual context served as substratum to Niklas Luhmann's theoretical reflection.With his Theory of Social Systems, he proposes the reduction of the world's complexity.Social systems have the function of reducing complexity because of their difference in relation to the environment.On the other hand, the reduction of complexity also creates its own complexity. Luhmann defines complexity as the moment when it is not possible anymore for each element to relate at any moment with all the others. Complexity forces the selection, what means contingency and risk. Luhmann expands the concept of complexity when he introduces the figure of the observer and the distinction of complexity as a unit of a multiplicity. He also deals with the limit of relations in connection, the time factor, the self-reference of operations and the representation of complexity in the form of sense. To conclude, the paper discusses the complexity in the system of science, the way it reduces internal and external complexity, in accordance in its own operative basis.

The cultural evolution of human communication systems in different sized populations: usability trumps learnability.

Science.gov (United States)

Fay, Nicolas; Ellison, T Mark

2013-01-01

This study examines the intergenerational transfer of human communication systems. It tests if human communication systems evolve to be easy to learn or easy to use (or both), and how population size affects learnability and usability. Using an experimental-semiotic task, we find that human communication systems evolve to be easier to use (production efficiency and reproduction fidelity), but harder to learn (identification accuracy) for a second generation of naïve participants. Thus, usability trumps learnability. In addition, the communication systems that evolve in larger populations exhibit distinct advantages over those that evolve in smaller populations: the learnability loss (from the Initial signs) is more muted and the usability benefits are more pronounced. The usability benefits for human communication systems that evolve in a small and large population is explained through guided variation reducing sign complexity. The enhanced performance of the communication systems that evolve in larger populations is explained by the operation of a content bias acting on the larger pool of competing signs. The content bias selects for information-efficient iconic signs that aid learnability and enhance usability.

Information, complexity and efficiency: The automobile model

Energy Technology Data Exchange (ETDEWEB)

Allenby, B. [Lucent Technologies (United States)]|[Lawrence Livermore National Lab., CA (United States)

1996-08-08

The new, rapidly evolving field of industrial ecology - the objective, multidisciplinary study of industrial and economic systems and their linkages with fundamental natural systems - provides strong ground for believing that a more environmentally and economically efficient economy will be more information intensive and complex. Information and intellectual capital will be substituted for the more traditional inputs of materials and energy in producing a desirable, yet sustainable, quality of life. While at this point this remains a strong hypothesis, the evolution of the automobile industry can be used to illustrate how such substitution may, in fact, already be occurring in an environmentally and economically critical sector.

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.

Application of Complex Adaptive Systems in Portfolio Management

Science.gov (United States)

Su, Zheyuan

2017-01-01

Simulation-based methods are becoming a promising research tool in financial markets. A general Complex Adaptive System can be tailored to different application scenarios. Based on the current research, we built two models that would benefit portfolio management by utilizing Complex Adaptive Systems (CAS) in Agent-based Modeling (ABM) approach.…

Dependency visualization for complex system understanding

Energy Technology Data Exchange (ETDEWEB)

Smart, J. Allison Cory [Univ. of California, Davis, CA (United States)

1994-09-01

With the volume of software in production use dramatically increasing, the importance of software maintenance has become strikingly apparent. Techniques now sought and developed for reverse engineering and design extraction and recovery. At present, numerous commercial products and research tools exist which are capable of visualizing a variety of programming languages and software constructs. The list of new tools and services continues to grow rapidly. Although the scope of the existing commercial and academic product set is quite broad, these tools still share a common underlying problem. The ability of each tool to visually organize object representations is increasingly impaired as the number of components and component dependencies within systems increases. Regardless of how objects are defined, complex ``spaghetti`` networks result in nearly all large system cases. While this problem is immediately apparent in modem systems analysis involving large software implementations, it is not new. As will be discussed in Chapter 2, related problems involving the theory of graphs were identified long ago. This important theoretical foundation provides a useful vehicle for representing and analyzing complex system structures. While the utility of directed graph based concepts in software tool design has been demonstrated in literature, these tools still lack the capabilities necessary for large system comprehension. This foundation must therefore be expanded with new organizational and visualization constructs necessary to meet this challenge. This dissertation addresses this need by constructing a conceptual model and a set of methods for interactively exploring, organizing, and understanding the structure of complex software systems.

Symmetry pattern transition in cellular automata with complex behavior

International Nuclear Information System (INIS)

Sanchez, Juan R.; Lopez-Ruiz, Ricardo

2008-01-01

A transition from asymmetric to symmetric patterns in time-dependent extended systems is described. It is shown that one dimensional cellular automata, started from fully random initial conditions, can be forced to evolve into complex symmetrical patterns by stochastically coupling a proportion p of pairs of sites located at equal distance from the center of the lattice. A nontrivial critical value of p must be surpassed in order to obtain symmetrical patterns during the evolution. This strategy is able to classify the cellular automata rules - with complex behavior - between those that support time-dependent symmetric patterns and those which do not support such kind of patterns

Distributed redundancy and robustness in complex systems

KAUST Repository

Randles, Martin

2011-03-01

The uptake and increasing prevalence of Web 2.0 applications, promoting new large-scale and complex systems such as Cloud computing and the emerging Internet of Services/Things, requires tools and techniques to analyse and model methods to ensure the robustness of these new systems. This paper reports on assessing and improving complex system resilience using distributed redundancy, termed degeneracy in biological systems, to endow large-scale complicated computer systems with the same robustness that emerges in complex biological and natural systems. However, in order to promote an evolutionary approach, through emergent self-organisation, it is necessary to specify the systems in an \\'open-ended\\' manner where not all states of the system are prescribed at design-time. In particular an observer system is used to select robust topologies, within system components, based on a measurement of the first non-zero Eigen value in the Laplacian spectrum of the components\\' network graphs; also known as the algebraic connectivity. It is shown, through experimentation on a simulation, that increasing the average algebraic connectivity across the components, in a network, leads to an increase in the variety of individual components termed distributed redundancy; the capacity for structurally distinct components to perform an identical function in a particular context. The results are applied to a specific application where active clustering of like services is used to aid load balancing in a highly distributed network. Using the described procedure is shown to improve performance and distribute redundancy. © 2010 Elsevier Inc.

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....

Mechanisms and dynamics of cooperation and competition emergence in complex networked systems

Science.gov (United States)

Gianetto, David A.

Cooperative behavior is a pervasive phenomenon in human interactions and yet how it can evolve and become established, through the selfish process of natural selection, is an enduring puzzle. These behaviors emerge when agents interact in a structured manner; even so, the key structural factors that affect cooperation are not well understood. Moreover, the literature often considers cooperation a single attribute of primitive agents who do not react to environmental changes but real-world actors are more perceptive. The present work moves beyond these assumptions by evolving more realistic game participants, with memories of the past, on complex networks. Agents play repeated games with a three-part Markovian strategy that allows us to separate the cooperation phenomenon into trust, reciprocity, and forgiveness characteristics. Our results show that networks matter most when agents gain the most by acting in a selfish manner, irrespective of how much they may lose by cooperating; since the context provided by neighborhoods inhibits greedy impulses that agents otherwise succumb to in isolation. Network modularity is the most important driver of cooperation emergence in these high-stakes games. However, modularity fails to tell the complete story. Modular scale-free graphs impede cooperation when close coordination is required, partially due to the acyclic nature of scale-free network models. To achieve the highest cooperation in diverse social conditions, both high modularity, low connectivity within modules, and a rich network of long cycles become important. With these findings in hand, we study the influence of networks on coordination and competition within the federal health care insurance exchange. In this applied study, we show that systemic health care coordination is encouraged by the emergent insurance network. The network helps underpin the viability of the exchange and provides an environment of stronger competition once a critical-mass of insurers have

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

Knowledge extraction from evolving spiking neural networks with rank order population coding.

Science.gov (United States)

Soltic, Snjezana; Kasabov, Nikola

2010-12-01

This paper demonstrates how knowledge can be extracted from evolving spiking neural networks with rank order population coding. Knowledge discovery is a very important feature of intelligent systems. Yet, a disproportionally small amount of research is centered on the issue of knowledge extraction from spiking neural networks which are considered to be the third generation of artificial neural networks. The lack of knowledge representation compatibility is becoming a major detriment to end users of these networks. We show that a high-level knowledge can be obtained from evolving spiking neural networks. More specifically, we propose a method for fuzzy rule extraction from an evolving spiking network with rank order population coding. The proposed method was used for knowledge discovery on two benchmark taste recognition problems where the knowledge learnt by an evolving spiking neural network was extracted in the form of zero-order Takagi-Sugeno fuzzy IF-THEN rules.

Strategies of complexity leadership in governance systems

NARCIS (Netherlands)

Nooteboom, S.G.; Termeer, C.J.A.M.

2013-01-01

In complex governance systems, innovations may emerge, not controlled by a single leader, but enabled by many. We discuss how these leaders are embedded in networks and which strategies they use. The theoretical framework is based on Complexity Leadership Theory. We conducted participatory

Efficient physical embedding of topologically complex information processing networks in brains and computer circuits.

Directory of Open Access Journals (Sweden)

Danielle S Bassett

2010-04-01

Full Text Available Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent's rule, which is related to the dimensionality of the circuit's interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent's rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks.

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 ...

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...

Understanding Complex Construction Systems Through Modularity

DEFF Research Database (Denmark)

Jensen, Tor Clarke; Bekdik, Baris; Thuesen, Christian

2014-01-01

This paper develops a framework for understanding complexity in construction projects by combining theories of complexity management and modularization. The framework incorporates three dimensions of product, process, and organizational modularity with the case of gypsum wall elements. The analysis...... system, rather than a modular, although the industry forces modular organizational structures. This creates a high complexity degree caused by the non-alignment of building parts and organizations and the frequent swapping of modules....... finds that the main driver of complexity is the fragmentation of the design and production, which causes the production modules to construct and install new product types and variants for each project as the designers are swapped for every project. The many interfaces are characteristics of an integral...

Symmetric and Asymmetric Tendencies in Stable Complex Systems.

Science.gov (United States)

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.

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...

Multistage Spectral Relaxation Method for Solving the Hyperchaotic Complex Systems

Directory of Open Access Journals (Sweden)

Hassan Saberi Nik

2014-01-01

Full Text Available We present a pseudospectral method application for solving the hyperchaotic complex systems. The proposed method, called the multistage spectral relaxation method (MSRM is based on a technique of extending Gauss-Seidel type relaxation ideas to systems of nonlinear differential equations and using the Chebyshev pseudospectral methods to solve the resulting system on a sequence of multiple intervals. In this new application, the MSRM is used to solve famous hyperchaotic complex systems such as hyperchaotic complex Lorenz system and the complex permanent magnet synchronous motor. We compare this approach to the Runge-Kutta based ode45 solver to show that the MSRM gives accurate results.

Galactic encounters our majestic and evolving star-system, from the big bang to time's end

CERN Document Server

Sheehan, William

2015-01-01

Written by William Sheehan, a noted historian of astronomy, and Christopher J. Conselice, a professional astronomer specializing in galaxies in the early universe, this book tells the story of how astronomers have pieced together what is known about the vast and complicated systems of stars and dust known as galaxies. The first galaxies appeared as violently disturbed exotic objects when the Universe was only a few 100 million years old.  From that tortured beginning, they have evolved though processes of accretion, merging and star formation into the majestic spirals and massive ellipticals that dominate our local part of the Universe. This of course includes the Milky Way, to which the Sun and Solar System belong; it is our galactic home, and the only galaxy we will ever know from the inside.  Sheehan and Conselice show how astronomers’ understanding has grown from the early catalogs of Charles Messier and William Herschel; developed through the pioneering efforts of astronomers like E.E. Barnard, V.M. ...

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

Science.gov (United States)

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"…

Engineering Complex Embedded Systems with State Analysis and the Mission Data System

Science.gov (United States)

Ingham, Michel D.; Rasmussen, Robert D.; Bennett, Matthew B.; Moncada, Alex C.

2004-01-01

It has become clear that spacecraft system complexity is reaching a threshold where customary methods of control are no longer affordable or sufficiently reliable. At the heart of this problem are the conventional approaches to systems and software engineering based on subsystem-level functional decomposition, which fail to scale in the tangled web of interactions typically encountered in complex spacecraft designs. Furthermore, there is a fundamental gap between the requirements on software specified by systems engineers and the implementation of these requirements by software engineers. Software engineers must perform the translation of requirements into software code, hoping to accurately capture the systems engineer's understanding of the system behavior, which is not always explicitly specified. This gap opens up the possibility for misinterpretation of the systems engineer s intent, potentially leading to software errors. This problem is addressed by a systems engineering methodology called State Analysis, which provides a process for capturing system and software requirements in the form of explicit models. This paper describes how requirements for complex aerospace systems can be developed using State Analysis and how these requirements inform the design of the system software, using representative spacecraft examples.

Evolving energy systems

Energy Technology Data Exchange (ETDEWEB)

Mills, E.

1991-04-01

This thesis presents scenarios of future energy systems, a cost-benefit analysis of measures to avoid greenhouse-gas emissions, an analysis of the effect of energy prices on end-use efficiencies and fuel choices, and an evaluation of financial-incentive programs designed to induce investments in efficient energy use. Twelve integrated energy supply/demand scenarios for the Swedish heat-and-power sector are presented to illustrate the potential for improvements in end-use efficiency and increased utilization of renewable energy sources. The results show that greenhouse-gas emissions could be reduced by 35 per cent from 1987 levels by 2010, with a net economic benefit compared to a business-as-usual scenario. A generalized methodology for calculating the net costs of reducing greenhouse-gas emissions is applied to a variety of fuel choices and energy end-use technologies. A key finding is that a combination of increased end-use efficiencies and use of renewable energy systems is required to achieve maximum cost-effective emissions reductions. End-use efficiencies and inter-fuel competition in Denmark and Sweden are compared during a time period in which real electricity prices were declining in Sweden and increasing in Denmark. Despite these different price environments, efficiencies and choices of heating fuels did not generally develop as expected according to economic theory. The influences of counter-price and non-price factors are important in understanding this outcome. Relying on prices alone injects considerable uncertainty into the energy planning process, and precludes efficiency improvements and fuel choices attainable with other mechanisms. Incentive programs can be used to promote energy-efficient technologies. Utilities in Europe have recently offered financial incentives intended to stimulate the adoption of compact-fluorescent lamps. These programs have been cost-effective in comparison to new electric supply. (au).

Simulating evolution of protein complexes through gene duplication and co-option.

Science.gov (United States)

Haarsma, Loren; Nelesen, Serita; VanAndel, Ethan; Lamine, James; VandeHaar, Peter

2016-06-21

We present a model of the evolution of protein complexes with novel functions through gene duplication, mutation, and co-option. Under a wide variety of input parameters, digital organisms evolve complexes of 2-5 bound proteins which have novel functions but whose component proteins are not independently functional. Evolution of complexes with novel functions happens more quickly as gene duplication rates increase, point mutation rates increase, protein complex functional probability increases, protein complex functional strength increases, and protein family size decreases. Evolution of complexity is inhibited when the metabolic costs of making proteins exceeds the fitness gain of having functional proteins, or when point mutation rates get so large the functional proteins undergo deleterious mutations faster than new functional complexes can evolve. Copyright © 2016 Elsevier Ltd. All rights reserved.

Interacting complex systems: Theory and application to real-world situations

Science.gov (United States)

Piccinini, Nicola

The interest in complex systems has increased exponentially during the past years because it was found helpful in addressing many of today's challenges. The study of the brain, biology, earthquakes, markets and social sciences are only a few examples of the fields that have benefited from the investigation of complex systems. Internet, the increased mobility of people and the raising energy demand are among the factors that brought in contact complex systems that were isolated till a few years ago. A theory for the interaction between complex systems is becoming more and more urgent to help mankind in this transition. The present work builds upon the most recent results in this field by solving a theoretical problem that prevented previous work to be applied to important complex systems, like the brain. It also shows preliminary laboratory results of perturbation of in vitro neural networks that were done to test the theory. Finally, it gives a preview of the studies that are being done to create a theory that is even closer to the interaction between real complex systems.

Exploring the morphospace of communication efficiency in complex networks.

Directory of Open Access Journals (Sweden)

Joaquín Goñi

Full Text Available Graph theoretical analysis has played a key role in characterizing global features of the topology of complex networks, describing diverse systems such as protein interactions, food webs, social relations and brain connectivity. How system elements communicate with each other depends not only on the structure of the network, but also on the nature of the system's dynamics which are constrained by the amount of knowledge and resources available for communication processes. Complementing widely used measures that capture efficiency under the assumption that communication preferentially follows shortest paths across the network ("routing", we define analytic measures directed at characterizing network communication when signals flow in a random walk process ("diffusion". The two dimensions of routing and diffusion efficiency define a morphospace for complex networks, with different network topologies characterized by different combinations of efficiency measures and thus occupying different regions of this space. We explore the relation of network topologies and efficiency measures by examining canonical network models, by evolving networks using a multi-objective optimization strategy, and by investigating real-world network data sets. Within the efficiency morphospace, specific aspects of network topology that differentially favor efficient communication for routing and diffusion processes are identified. Charting regions of the morphospace that are occupied by canonical, evolved or real networks allows inferences about the limits of communication efficiency imposed by connectivity and dynamics, as well as the underlying selection pressures that have shaped network topology.

Space-time complexity in solid state models

International Nuclear Information System (INIS)

Bishop, A.R.

1985-01-01

In this Workshop on symmetry-breaking it is appropriate to include the evolving fields of nonlinear-nonequilibrium systems in which transitions to and between various degrees of ''complexity'' (including ''chaos'') occur in time or space or both. These notions naturally bring together phenomena of pattern formation and chaos and therefore have ramifications for a huge array of natural sciences - astrophysics, plasmas and lasers, hydrodynamics, field theory, materials and solid state theory, optics and electronics, biology, pattern recognition and evolution, etc. Our particular concerns here are with examples from solid state and condensed matter

Evolved H II regions

International Nuclear Information System (INIS)

Churchwell, E.

1975-01-01

A probable evolutionary sequence of H II regions based on six distinct types of observed objects is suggested. Two examples which may deviate from this idealized sequence, are discussed. Even though a size-mean density relation of H II regions can be used as a rough indication of whether a nebula is very young or evolved, it is argued that such a relation is not likely to be useful for the quantitative assignment of ages to H II regions. Evolved H II regions appear to fit into one of four structural types: rings, core-halos, smooth structures, and irregular or filamentary structures. Examples of each type are given with their derived physical parameters. The energy balance in these nebulae is considered. The mass of ionized gas in evolved H II regions is in general too large to trace the nebula back to single compact H II regions. Finally, the morphological type of the Galaxy is considered from its H II region content. 2 tables, 2 figs., 29 refs

Generating functional analysis of complex formation and dissociation in large protein interaction networks

International Nuclear Information System (INIS)

Coolen, A C C; Rabello, S

2009-01-01

We analyze large systems of interacting proteins, using techniques from the non-equilibrium statistical mechanics of disordered many-particle systems. Apart from protein production and removal, the most relevant microscopic processes in the proteome are complex formation and dissociation, and the microscopic degrees of freedom are the evolving concentrations of unbound proteins (in multiple post-translational states) and of protein complexes. Here we only include dimer-complexes, for mathematical simplicity, and we draw the network that describes which proteins are reaction partners from an ensemble of random graphs with an arbitrary degree distribution. We show how generating functional analysis methods can be used successfully to derive closed equations for dynamical order parameters, representing an exact macroscopic description of the complex formation and dissociation dynamics in the infinite system limit. We end this paper with a discussion of the possible routes towards solving the nontrivial order parameter equations, either exactly (in specific limits) or approximately.

Distributed redundancy and robustness in complex systems

KAUST Repository

Randles, Martin; Lamb, David J.; Odat, Enas M.; Taleb-Bendiab, Azzelarabe

2011-01-01

that emerges in complex biological and natural systems. However, in order to promote an evolutionary approach, through emergent self-organisation, it is necessary to specify the systems in an 'open-ended' manner where not all states of the system are prescribed

System complexity and (im)possible sound changes

NARCIS (Netherlands)

Seinhorst, K.T.

2016-01-01

In the acquisition of phonological patterns, learners tend to considerably reduce the complexity of their input. This learning bias may also constrain the set of possible sound changes, which might be expected to contain only those changes that do not increase the complexity of the system. However,

Armada, an Evolving Database System

NARCIS (Netherlands)

F.E. Groffen (Fabian)

2009-01-01

htmlabstractIn a world where data usage becomes more and more widespread, single system solutions are no longer adequate to meet the data requirements of today. No longer one monolithic system, but instead a group of smaller and cheaper ones have to manage the workload of the system, preferably

Collaborative Management of Risks and Complexity in Banking Systems

Directory of Open Access Journals (Sweden)

Ion IVAN

2012-01-01

Full Text Available This paper describes types of risks encountered in banking systems and ways to prevent and eliminate them. Banking systems are presented in order to have a view on banking activities and processes that generates risks. The risks in banking processes are analyzed and the collaborative character of risk management is highlighted. A way to control the risk in banking systems through information security is described. Risks arise from system complexity, thus evaluation and comparison of different configurations are bases for improvements. The Halstead relative complexity function synthesizes system complexity from the point of view of the size of the variables analyzed and the heterogeneity between the variables. Section four was realized by Catalin SBORA.

Strategic optimisation of microgrid by evolving a unitised regenerative fuel cell system operational criterion

Science.gov (United States)

Bhansali, Gaurav; Singh, Bhanu Pratap; Kumar, Rajesh

2016-09-01

In this paper, the problem of microgrid optimisation with storage has been addressed in an unaccounted way rather than confining it to loss minimisation. Unitised regenerative fuel cell (URFC) systems have been studied and employed in microgrids to store energy and feed it back into the system when required. A value function-dependent on line losses, URFC system operational cost and stored energy at the end of the day are defined here. The function is highly complex, nonlinear and multi dimensional in nature. Therefore, heuristic optimisation techniques in combination with load flow analysis are used here to resolve the network and time domain complexity related with the problem. Particle swarm optimisation with the forward/backward sweep algorithm ensures optimal operation of microgrid thereby minimising the operational cost of the microgrid. Results are shown and are found to be consistently improving with evolution of the solution strategy.

Managing interoperability and complexity in health systems.

Science.gov (United States)

Bouamrane, M-M; Tao, C; Sarkar, I N

2015-01-01

In recent years, we have witnessed substantial progress in the use of clinical informatics systems to support clinicians during episodes of care, manage specialised domain knowledge, perform complex clinical data analysis and improve the management of health organisations' resources. However, the vision of fully integrated health information eco-systems, which provide relevant information and useful knowledge at the point-of-care, remains elusive. This journal Focus Theme reviews some of the enduring challenges of interoperability and complexity in clinical informatics systems. Furthermore, a range of approaches are proposed in order to address, harness and resolve some of the many remaining issues towards a greater integration of health information systems and extraction of useful or new knowledge from heterogeneous electronic data repositories.

Classical and quantum mechanics of complex Hamiltonian systems ...

Indian Academy of Sciences (India)

Vol. 73, No. 2. — journal of. August 2009 physics pp. 287–297. Classical and quantum mechanics of complex. Hamiltonian systems: An extended complex phase space ... 1Department of Physics, Ramjas College (University Enclave), University of Delhi,. Delhi 110 ... 1.1 Motivation behind the study of complex Hamiltonians.

EVOLVE : International Conference

CERN Document Server

Deutz, Andre; Schuetze, Oliver; Bäck, Thomas; Tantar, Emilia; Tantar, Alexandru-Adrian; Moral, Pierre; Legrand, Pierrick; Bouvry, Pascal; Coello, Carlos

2013-01-01

Numerical and computational methods are nowadays used in a wide range of contexts in complex systems research, biology, physics, and engineering.  Over the last decades different methodological schools have emerged with emphasis on different aspects of computation, such as nature-inspired algorithms, set oriented numerics, probabilistic systems and Monte Carlo methods. Due to the use of different terminologies and emphasis on different aspects of algorithmic performance there is a strong need for a more integrated view and opportunities for cross-fertilization across particular disciplines. These proceedings feature 20 original publications from distinguished authors in the cross-section of computational sciences, such as machine learning algorithms and probabilistic models, complex networks and fitness landscape analysis, set oriented numerics and cell mapping, evolutionary multiobjective optimization, diversity-oriented search, and the foundations of genetic programming algorithms. By presenting cutting ed...

Leadership and transitions: maintaining the science in complexity and complex systems.

Science.gov (United States)

Sturmberg, Joachim P; Martin, Carmel M

2012-02-01

It is the 'moral compass', however subtle, that underpins leadership. Leadership, meaning showing the way, demands as much conviction as gentile diplomacy in the discourse with supporters and detractors. In particular, leadership defends the goal by safeguarding its principles from its detractors. The authors writing in the Forum on Complexity in Medicine and Healthcare since its inception are leaders in an intellectual transition to complex systems thinking in medicine and health. © 2012 Blackwell Publishing Ltd.

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.

Challenges in data science: a complex systems perspective

International Nuclear Information System (INIS)

Carbone, Anna; Jensen, Meiko; Sato, Aki-Hiro

2016-01-01

The ability to process and manage large data volumes has been proven to be not enough to tackle the current challenges presented by “Big Data”. Deep insight is required for understanding interactions among connected systems, space- and time- dependent heterogeneous data structures. Emergence of global properties from locally interacting data entities and clustering phenomena demand suitable approaches and methodologies recently developed in the foundational area of Data Science by taking a Complex Systems standpoint. Here, we deal with challenges that can be summarized by the question: “What can Complex Systems Science contribute to Big Data? ”. Such question can be reversed and brought to a superior level of abstraction by asking “What Knowledge can be drawn from Big Data?” These aspects constitute the main motivation behind this article to introduce a volume containing a collection of papers presenting interdisciplinary advances in the Big Data area by methodologies and approaches typical of the Complex Systems Science, Nonlinear Systems Science and Statistical Physics.

Complex chloroplast RNA metabolism: just debugging the genetic programme?

Directory of Open Access Journals (Sweden)

Schmitz-Linneweber Christian

2008-08-01

Full Text Available Abstract Background The gene expression system of chloroplasts is far more complex than that of their cyanobacterial progenitor. This gain in complexity affects in particular RNA metabolism, specifically the transcription and maturation of RNA. Mature chloroplast RNA is generated by a plethora of nuclear-encoded proteins acquired or recruited during plant evolution, comprising additional RNA polymerases and sigma factors, and sequence-specific RNA maturation factors promoting RNA splicing, editing, end formation and translatability. Despite years of intensive research, we still lack a comprehensive explanation for this complexity. Results We inspected the available literature and genome databases for information on components of RNA metabolism in land plant chloroplasts. In particular, new inventions of chloroplast-specific mechanisms and the expansion of some gene/protein families detected in land plants lead us to suggest that the primary function of the additional nuclear-encoded components found in chloroplasts is the transgenomic suppression of point mutations, fixation of which occurred due to an enhanced genetic drift exhibited by chloroplast genomes. We further speculate that a fast evolution of transgenomic suppressors occurred after the water-to-land transition of plants. Conclusion Our inspections indicate that several chloroplast-specific mechanisms evolved in land plants to remedy point mutations that occurred after the water-to-land transition. Thus, the complexity of chloroplast gene expression evolved to guarantee the functionality of chloroplast genetic information and may not, with some exceptions, be involved in regulatory functions.

FY1995 evolvable hardware chip; 1995 nendo shinkasuru hardware chip

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

This project aims at the development of 'Evolvable Hardware' (EHW) which can adapt its hardware structure to the environment to attain better hardware performance, under the control of genetic algorithms. EHW is a key technology to explore the new application area requiring real-time performance and on-line adaptation. 1. Development of EHW-LSI for function level hardware evolution, which includes 15 DSPs in one chip. 2. Application of the EHW to the practical industrial applications such as data compression, ATM control, digital mobile communication. 3. Two patents : (1) the architecture and the processing method for programmable EHW-LSI. (2) The method of data compression for loss-less data, using EHW. 4. The first international conference for evolvable hardware was held by authors: Intl. Conf. on Evolvable Systems (ICES96). It was determined at ICES96 that ICES will be held every two years between Japan and Europe. So the new society has been established by us. (NEDO)

FY1995 evolvable hardware chip; 1995 nendo shinkasuru hardware chip

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

This project aims at the development of 'Evolvable Hardware' (EHW) which can adapt its hardware structure to the environment to attain better hardware performance, under the control of genetic algorithms. EHW is a key technology to explore the new application area requiring real-time performance and on-line adaptation. 1. Development of EHW-LSI for function level hardware evolution, which includes 15 DSPs in one chip. 2. Application of the EHW to the practical industrial applications such as data compression, ATM control, digital mobile communication. 3. Two patents : (1) the architecture and the processing method for programmable EHW-LSI. (2) The method of data compression for loss-less data, using EHW. 4. The first international conference for evolvable hardware was held by authors: Intl. Conf. on Evolvable Systems (ICES96). It was determined at ICES96 that ICES will be held every two years between Japan and Europe. So the new society has been established by us. (NEDO)

Documentation Driven Development for Complex Real-Time Systems

Science.gov (United States)

2004-12-01

This paper presents a novel approach for development of complex real - time systems , called the documentation-driven development (DDD) approach. This... time systems . DDD will also support automated software generation based on a computational model and some relevant techniques. DDD includes two main...stakeholders to be easily involved in development processes and, therefore, significantly improve the agility of software development for complex real

Common cause failure analysis methodology for complex systems

International Nuclear Information System (INIS)

Wagner, D.P.; Cate, C.L.; Fussell, J.B.

1977-01-01

Common cause failure analysis, also called common mode failure analysis, is an integral part of a complex system reliability analysis. This paper extends existing methods of computer aided common cause failure analysis by allowing analysis of the complex systems often encountered in practice. The methods presented here aid in identifying potential common cause failures and also address quantitative common cause failure analysis

Strategies and Rubrics for Teaching Complex Systems Theory to Novices (Invited)

Science.gov (United States)

Fichter, L. S.

2010-12-01

Bifurcation. Self-similarity. Fractal. Sensitive dependent. Agents. Self-organized criticality. Avalanche behavior. Power laws. Strange attractors. Emergence. The language of complexity is fundamentally different from the language of equilibrium. If students do not know these phenomena, and what they tell us about the pulse of dynamic systems, complex systems will be opaque. A complex system is a group of agents. (individual interacting units, like birds in a flock, sand grains in a ripple, or individual friction units along a fault zone), existing far from equilibrium, interacting through positive and negative feedbacks, following simple rules, forming interdependent, dynamic, evolutionary networks. Complex systems produce behaviors that cannot be predicted deductively from knowledge of the behaviors of the individual components themselves; they must be experienced. What complexity theory demonstrates is that, by following simple rules, all the agents end up coordinating their behavior—self organizing—so that what emerges is not chaos, but meaningful patterns. How can we introduce Freshman, non-science, general education students to complex systems theories, in 3 to 5 classes; in a way they really get it, and can use the principles to understand real systems? Complex systems theories are not a series of unconnected or disconnected equations or models; they are developed as narratives that makes sense of how all the pieces and properties are interrelated. The principles of complex systems must be taught as deliberately and systematically as the equilibrium principles normally taught; as, say, the systematic training from pre-algebra and geometry to algebra. We have developed a sequence of logically connected narratives (strategies and rubrics) that introduce complex systems principles using models that can be simulated in a computer, in class, in real time. The learning progression has a series of 12 models (e.g. logistic system, bifurcation diagrams, genetic

Achieving control and interoperability through unified model-based systems and software engineering

Science.gov (United States)

Rasmussen, Robert; Ingham, Michel; Dvorak, Daniel

2005-01-01

Control and interoperation of complex systems is one of the most difficult challenges facing NASA's Exploration Systems Mission Directorate. An integrated but diverse array of vehicles, habitats, and supporting facilities, evolving over the long course of the enterprise, must perform ever more complex tasks while moving steadily away from the sphere of ground support and intervention.

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

Science.gov (United States)

Cohen, Alan A

2016-02-01

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

Platform strategy for complex products and systems

NARCIS (Netherlands)

Alblas, A.A.

2011-01-01

The thesis of Alex Alblas presents a design reuse strategy for firms producing complex products and systems (CoPS). Examples of CoPS include industrial machinery, oil-rigs, electrical power distribution systems, integrated mail processing systems and printing press machinery. CoPS firms are

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.

Interdisciplinary Symposium on Complex Systems

CERN Document Server

Zelinka, Ivan; Rössler, Otto

2014-01-01

The book you hold in your hands is the outcome of the "ISCS 2013: Interdisciplinary Symposium on Complex Systems" held at the historical capital of Bohemia as a continuation of our series of symposia in the science of complex systems. Prague, one of the most beautiful European cities, has its own beautiful genius loci. Here, a great number of important discoveries were made and many important scientists spent fruitful and creative years to leave unforgettable traces. The perhaps most significant period was the time of Rudolf II who was a great supporter of the art and the science and attracted a great number of prominent minds to Prague. This trend would continue. Tycho Brahe, Niels Henrik Abel, Johannes Kepler, Bernard Bolzano, August Cauchy Christian Doppler, Ernst Mach, Albert Einstein and many others followed developing fundamental mathematical and physical theories or expanding them. Thus in the beginning of the 17th century, Kepler formulated here the first two of his three laws of planetary motion on ...

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...

Evolvable Smartphone-Based Platforms for Point-Of-Care In-Vitro Diagnostics Applications

DEFF Research Database (Denmark)

Patou, François; Al Atraktchi, Fatima Al-Zahraa; Kjærgaard, Claus

2016-01-01

recently that system evolvability, defined as the design characteristic that facilitates more manageable transitions between system generations via the modification of an inherited design, can help remedy these limitations. In this paper, we discuss how platform-based design can constitute a formal entry...

The Self as a Complex Dynamic System

Science.gov (United States)

Mercer, Sarah

2011-01-01

This article explores the potential offered by complexity theories for understanding language learners' sense of self and attempts to show how the self might usefully be conceived of as a complex dynamic system. Rather than presenting empirical findings, the article discusses existent research on the self and aims at outlining a conceptual…

Defining "The Weakest Link" Comparative Security in Complex Systems of Systems

NARCIS (Netherlands)

Pieters, Wolter

2013-01-01

Cloud architectures are complex socio-technical systems of systems, consisting not only of technological components and their connections, but also of physical premises and employees. When analysing security of such systems and considering countermeasures, the notion of "weakest link" often appears.

The cultural evolution of human communication systems in different sized populations: usability trumps learnability.

Directory of Open Access Journals (Sweden)

Nicolas Fay

Full Text Available This study examines the intergenerational transfer of human communication systems. It tests if human communication systems evolve to be easy to learn or easy to use (or both, and how population size affects learnability and usability. Using an experimental-semiotic task, we find that human communication systems evolve to be easier to use (production efficiency and reproduction fidelity, but harder to learn (identification accuracy for a second generation of naïve participants. Thus, usability trumps learnability. In addition, the communication systems that evolve in larger populations exhibit distinct advantages over those that evolve in smaller populations: the learnability loss (from the Initial signs is more muted and the usability benefits are more pronounced. The usability benefits for human communication systems that evolve in a small and large population is explained through guided variation reducing sign complexity. The enhanced performance of the communication systems that evolve in larger populations is explained by the operation of a content bias acting on the larger pool of competing signs. The content bias selects for information-efficient iconic signs that aid learnability and enhance usability.

Analysis of complex systems using neural networks

International Nuclear Information System (INIS)

Uhrig, R.E.

1992-01-01

The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems

An evolving model for the lodging-service network in a tourism destination

Science.gov (United States)

Hernández, Juan M.; González-Martel, Christian

2017-09-01

Tourism is a complex dynamic system including multiple actors which are related each other composing an evolving social network. This paper presents a growing model that explains how part of the supply components in a tourism system forms a social network. Specifically, the lodgings and services in a destination are the network nodes and a link between them appears if a representative tourist hosted in the lodging visits/consumes the service during his/her stay. The specific link between both categories are determined by a random and preferential attachment rule. The analytic results show that the long-term degree distribution of services follows a shifted power-law distribution. The numerical simulations show slight disagreements with the theoretical results in the case of the one-mode degree distribution of services, due to the low order of convergence to zero of X-motifs. The model predictions are compared with real data coming from a popular tourist destination in Gran Canaria, Spain, showing a good agreement between analytical and empirical data for the degree distribution of services. The theoretical model was validated assuming four type of perturbations in the real data.

Evaluating Complex Healthcare Systems: A Critique of Four Approaches

Directory of Open Access Journals (Sweden)

Heather Boon

2007-01-01

Full Text Available The purpose of this paper is to bring clarity to the emerging conceptual and methodological literature that focuses on understanding and evaluating complex or ‘whole’ systems of healthcare. An international working group reviewed literature from interdisciplinary or interprofessional groups describing approaches to the evaluation of complex systems of healthcare. The following four key approaches were identified: a framework from the MRC (UK, whole systems research, whole medical systems research described by NCCAM (USA and a model from NAFKAM (Norway. Main areas of congruence include acknowledgment of the inherent complexity of many healthcare interventions and the need to find new ways to evaluate these; the need to describe and understand the components of complex interventions in context (as they are actually practiced; the necessity of using mixed methods including randomized clinical trials (RCTs (explanatory and pragmatic and qualitative approaches; the perceived benefits of a multidisciplinary team approach to research; and the understanding that methodological developments in this field can be applied to both complementary and alternative medicine (CAM as well as conventional therapies. In contrast, the approaches differ in the following ways: terminology used, the extent to which the approach attempts to be applicable to both CAM and conventional medical interventions; the prioritization of research questions (in order of what should be done first especially with respect to how the ‘definitive’ RCT fits into the process of assessing complex healthcare systems; and the need for a staged approach. There appears to be a growing international understanding of the need for a new perspective on assessing complex healthcare systems.

Evolving Technologies: A View to Tomorrow

Science.gov (United States)