Complex systems as lenses on learning and teaching

NASA Astrophysics Data System (ADS)

Hurford, Andrew C.

From metaphors to mathematized models, the complexity sciences are changing the ways disciplines view their worlds, and ideas borrowed from complexity are increasingly being used to structure conversations and guide research on teaching and learning. The purpose of this corpus of research is to further those conversations and to extend complex systems ideas, theories, and modeling to curricula and to research on learning and teaching. A review of the literatures of learning and of complexity science and a discussion of the intersections between those disciplines are provided. The work reported represents an evolving model of learning qua complex system and that evolution is the result of iterative cycles of design research. One of the signatures of complex systems is the presence of scale invariance and this line of research furnishes empirical evidence of scale invariant behaviors in the activity of learners engaged in participatory simulations. The offered discussion of possible causes for these behaviors and chaotic phase transitions in human learning favors real-time optimization of decision-making as the means for producing such behaviors. Beyond theoretical development and modeling, this work includes the development of teaching activities intended to introduce pre-service mathematics and science teachers to complex systems. While some of the learning goals for this activity focused on the introduction of complex systems as a content area, we also used complex systems to frame perspectives on learning. Results of scoring rubrics and interview responses from students illustrate attributes of the proposed model of complex systems learning and also how these pre-service teachers made sense of the ideas. Correlations between established theories of learning and a complex adaptive systems model of learning are established and made explicit, and a means for using complex systems ideas for designing instruction is offered. It is a fundamental assumption of this research and researcher that complex systems ideas and understandings can be appropriated from more complexity-developed disciplines and put to use modeling and building increasingly productive understandings of learning and teaching.

Information driven self-organization of complex robotic behaviors.

PubMed

Martius, Georg; Der, Ralf; Ay, Nihat

2013-01-01

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

Disorder in Complex Human System

NASA Astrophysics Data System (ADS)

Akdeniz, K. Gediz

2011-11-01

Since the world of human and whose life becomes more and more complex every day because of the digital technology and under the storm of knowledge (media, internet, governmental and non-governmental organizations, etc...) the simulation is rapidly growing in the social systems and in human behaviors. The formation of the body and mutual interactions are left to digital technological, communication mechanisms and coding the techno genetics of the body. Deconstruction begins everywhere. The linear simulation mechanism with modern realities are replaced by the disorder simulation of human behaviors with awareness realities. In this paper I would like to introduce simulation theory of "Disorder Sensitive Human Behaviors". I recently proposed this theory to critique the role of disorder human behaviors in social systems. In this theory the principle of realty is the chaotic awareness of the complexity of human systems inside of principle of modern thinking in Baudrillard's simulation theory. Proper examples will be also considered to investigate the theory.

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

NASA Astrophysics Data System (ADS)

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 algorithms, etc.) leading to 19 learning outcomes that encompass most of the universality properties that characterize complex systems. They are developed in a specific order to achieve specific ends of understanding. We use these models in various depths and formats in courses ranging from gened courses, to evolutionary systems and environmental systems, to upper level geology courses. Depending on the goals of a course, the learning outcomes can be applied to understanding many other complex systems; e.g. oscillating chemical reactions (reaction-diffusion and activator-inhibitor systems), autocatalytic networks, hysteresis (bistable) systems, networks, and the rise/collapse of complex societies. We use these and other complex systems concepts in various classes to talk about the origin of life, ecosystem organization, game theory, extinction events, and environmental system behaviors. The applications are almost endless. The complete learning progression with models, computer programs, experiments, and learning outcomes is available at: www.jmu.edu/geology/ComplexEvolutionarySystems/

Creating virtual humans for simulation-based training and planning

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

Stansfield, S.; Sobel, A.

1998-05-12

Sandia National Laboratories has developed a distributed, high fidelity simulation system for training and planning small team Operations. The system provides an immersive environment populated by virtual objects and humans capable of displaying complex behaviors. The work has focused on developing the behaviors required to carry out complex tasks and decision making under stress. Central to this work are techniques for creating behaviors for virtual humans and for dynamically assigning behaviors to CGF to allow scenarios without fixed outcomes. Two prototype systems have been developed that illustrate these capabilities: MediSim, a trainer for battlefield medics and VRaptor, a system formore » planning, rehearsing and training assault operations.« less

ESCAPE: Eco-Behavioral System for Complex Assessments of Preschool Environments. Research Draft.

ERIC Educational Resources Information Center

Carta, Judith J.; And Others

The manual details an observational code designed to track a child during an entire day in a preschool setting. The Eco-Behavioral System for Complex Assessments of Preschool Environments (ESCAPE) encompasses assessment of the following three major categories of variables with their respective subcategories: (1) ecological variables (designated…

Self-organization and complexity in historical landscape patterns

Treesearch

Janine Bolliger; Julien C. Sprott; David J. Mladenoff

2003-01-01

Self-organization describes the evolution process of complex structures where systems emerge spontaneously, driven internally by variations of the system itself. Self-organization to the critical state is manifested by scale-free behavior across many orders of magnitude (Bak et al. 1987, Bak 1996, Sole et a1. 1999). Spatial scale-free behavior implies fractal...

Modeling Complex Cross-Systems Software Interfaces Using SysML

NASA Technical Reports Server (NTRS)

Mandutianu, Sanda; Morillo, Ron; Simpson, Kim; Liepack, Otfrid; Bonanne, Kevin

2013-01-01

The complex flight and ground systems for NASA human space exploration are designed, built, operated and managed as separate programs and projects. However, each system relies on one or more of the other systems in order to accomplish specific mission objectives, creating a complex, tightly coupled architecture. Thus, there is a fundamental need to understand how each system interacts with the other. To determine if a model-based system engineering approach could be utilized to assist with understanding the complex system interactions, the NASA Engineering and Safety Center (NESC) sponsored a task to develop an approach for performing cross-system behavior modeling. This paper presents the results of applying Model Based Systems Engineering (MBSE) principles using the System Modeling Language (SysML) to define cross-system behaviors and how they map to crosssystem software interfaces documented in system-level Interface Control Documents (ICDs).

Saving Human Lives: What Complexity Science and Information Systems can Contribute

NASA Astrophysics Data System (ADS)

Helbing, Dirk; Brockmann, Dirk; Chadefaux, Thomas; Donnay, Karsten; Blanke, Ulf; Woolley-Meza, Olivia; Moussaid, Mehdi; Johansson, Anders; Krause, Jens; Schutte, Sebastian; Perc, Matjaž

2015-02-01

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.

Saving Human Lives: What Complexity Science and Information Systems can Contribute.

PubMed

Helbing, Dirk; Brockmann, Dirk; Chadefaux, Thomas; Donnay, Karsten; Blanke, Ulf; Woolley-Meza, Olivia; Moussaid, Mehdi; Johansson, Anders; Krause, Jens; Schutte, Sebastian; Perc, Matjaž

We discuss models and data of crowd disasters, crime, terrorism, war and disease spreading to show that conventional recipes, such as deterrence strategies, are often not effective and sufficient to contain them. Many common approaches do not provide a good picture of the actual system behavior, because they neglect feedback loops, instabilities and cascade effects. The complex and often counter-intuitive behavior of social systems and their macro-level collective dynamics can be better understood by means of complexity science. We highlight that a suitable system design and management can help to stop undesirable cascade effects and to enable favorable kinds of self-organization in the system. In such a way, complexity science can help to save human lives.

Complexity Theory

USGS Publications Warehouse

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.

Design tools for complex dynamic security systems.

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

Byrne, Raymond Harry; Rigdon, James Brian; Rohrer, Brandon Robinson

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 systemsmore » are described: a 100 node wireless sensor network, unmanned ground vehicle and unmanned aerial vehicle.« less

Teaching Methodology of Flexible Pavement Materials and Pavement Systems

ERIC Educational Resources Information Center

Mehta, Yusuf; Najafi, Fazil

2004-01-01

Flexible pavement materials exhibit complex mechanical behavior, in the sense, that they not only show stress and temperature dependency but also are sensitive to moisture conditions. This complex behavior presents a great challenge to the faculty in bringing across the level of complexity and providing the concepts needed to understand them. The…

Effector peptides of the renin-angiotensin system in the central mechanisms of acquired and innate behavior in thirst in rats.

PubMed

Vlasenko, R Ya; Kotov, A V

2007-03-01

We report here a comparative analysis of the involvement of a number of components of the renin-angiotensin system in the performance of simple and complex forms of drinking behavior and thirst-associated non-drinking types of behavior. On central (intracerebroventricular) microinjection, [des-Asp1]-angiotensin I at doses equieffective to those of angiotensins II and III was found to be involved only in the performance of simple (taking water from the bowl) and linked forms of activity (comfort behavior, stress grooming, orientational-investigative, and feeding behavior). Angiotensin II was involved in the central mechanisms of complex acquired drinking behavior, selectively modulating its key stages (initial, final), while angiotensin III was involved only in the mechanisms of reproduction of the complex skill. All three substances induced "innate patterns of behavior" specific for each compound, these occurring at fixed periods of time after intracerebral microinjection. The effects of these substances were selectively suppressed by the AT1 receptor blocker losartan potassium.

Structural Behavioral Study on the General Aviation Network Based on Complex Network

NASA Astrophysics Data System (ADS)

Zhang, Liang; Lu, Na

2017-12-01

The general aviation system is an open and dissipative system with complex structures and behavioral features. This paper has established the system model and network model for general aviation. We have analyzed integral attributes and individual attributes by applying the complex network theory and concluded that the general aviation network has influential enterprise factors and node relations. We have checked whether the network has small world effect, scale-free property and network centrality property which a complex network should have by applying degree distribution of functions and proved that the general aviation network system is a complex network. Therefore, we propose to achieve the evolution process of the general aviation industrial chain to collaborative innovation cluster of advanced-form industries by strengthening network multiplication effect, stimulating innovation performance and spanning the structural hole path.

Developing custom fire behavior fuel models from ecologically complex fuel structures for upper Atlantic Coastal Plain forests

Treesearch

Bernard R. Parresol; Joe H. Scott; Anne Andreu; Susan Prichard; Laurie Kurth

2012-01-01

Currently geospatial fire behavior analyses are performed with an array of fire behavior modeling systems such as FARSITE, FlamMap, and the Large Fire Simulation System. These systems currently require standard or customized surface fire behavior fuel models as inputs that are often assigned through remote sensing information. The ability to handle hundreds or...

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

PubMed

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

2017-01-02

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

Teaching Complex Organizations: A Survey Essay.

ERIC Educational Resources Information Center

Dobratz, Betty

1988-01-01

Briefly reviews six textbooks for teaching about complex organizations: ORGANIZATIONS: STRUCTURES, PROCESSES, AND OUTCOMES (Hall, 1987); ORGANIZATIONS: RATIONAL, NATURAL, AND OPEN SYSTEMS (Scott, 1987); ORGANIZATIONS IN SOCIETY (Etzioni, 1985); ORGANIZATIONAL BEHAVIOR (Hellriegel et al, 1986); ORGANIZATIONAL BEHAVIOR: EXPERIENCES AND CASES (Hai,…

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

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

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

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

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

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

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

Levels of behavioral organization and the evolution of division of labor

NASA Astrophysics Data System (ADS)

Page, Robert E.; Erber, Joachim

2002-03-01

The major features of insect societies that fascinate biologists are the self-sacrificing altruism expressed by colony members, the complex division of labor, and the tremendous plasticity demonstrated in the face of changing environments. The social behavior of insects is a result of complex interactions at different levels of biological organization. Genes give rise to proteins and peptides that build the nervous and muscular systems, regulate their own synthesis, interact with each other, and affect the behavior of individuals. Social behavior emerges from the complex interactions of individuals that are themselves far removed from the direct effects of the genes. In order to understand how social organization evolves, we must understand the mechanisms that link the different levels of organization. In this review, we discuss how behavior is influenced by genes and the neural system and how social behavior emerges from the behavioral activities of individuals. We show how different levels of organization share common features and are linked through common mechanisms. We focus on the behavior of the honey bee, the best studied of all social insects.

Integrating Wraparound into a Schoolwide System of Positive Behavior Supports

ERIC Educational Resources Information Center

Eber, Lucille; Hyde, Kelly; Suter, Jesse C.

2011-01-01

We describe the structure for implementation of the wraparound process within a multi-tiered system of school wide positive behavior support (SWPBS) to address the needs of the 1-5% of students with complex emotional/behavioral challenges. The installation of prerequisite system features that, based on a 3 year demonstration process, we consider…

Probing Teachers' Lesson Planning: Promoting Metacognition

ERIC Educational Resources Information Center

Eilam, Billie

2017-01-01

Classrooms are complex systems, with dynamic interactions of different kinds among their composing varied elements. Such complex interactions lead to the system's unpredictable emergent learning behaviors. To support teachers' lesson planning and monitoring in the complex environment of classrooms, the present article examines the core…

Micro-Macro Compatibility: When Does a Complex Systems Approach Strongly Benefit Science Learning?

ERIC Educational Resources Information Center

Samon, Sigal; Levy, Sharona T.

2017-01-01

The study explores how a complexity approach empowers science learning. A complexity approach represents systems as many interacting entities. The construct of micro-macro compatibility is introduced, the degree of similarity between behaviors at the micro- and macro-levels of the system. Seventh-grade students' learning about gases was studied…

New approaches in agent-based modeling of complex financial systems

NASA Astrophysics Data System (ADS)

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

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

Time-spatial model on the dynamics of the proliferation of Aedes aegypti

NASA Astrophysics Data System (ADS)

Gouvêa, Maury Meirelles, Jr.

2017-03-01

Some complex physical systems, such as cellular regulation, ecosystems, and societies, can be represented by local interactions between agents. Then, complex behaviors may emerge. A cellular automaton is a discrete dynamic system with these features. Among the several complex systems, epidemic diseases are given special attention by researchers with respect to their dynamics. Understanding the behavior of an epidemic may well benefit a society. For instance, different proliferation scenarios may be produced and a prevention policy set. This paper presents a new simulation method of the time-spatial spread of the Dengue mosquito with a cellular automaton. Thus, it will be possible to create different dissemination scenarios and preventive policies for these in several regions. Simulations were performed with different initial conditions and parameters as a result of which the behavior of the proposed method was characterized.

System-level musings about system-level science (Invited)

NASA Astrophysics Data System (ADS)

Liu, W.

2009-12-01

In teleology, a system has a purpose. In physics, a system has a tendency. For example, a mechanical system has a tendency to lower its potential energy. A thermodynamic system has a tendency to increase its entropy. Therefore, if geospace is seen as a system, what is its tendency? Surprisingly or not, there is no simple answer to this question. Or, to flip the statement, the answer is complex, or complexity. We can understand generally why complexity arises, as the geospace boundary is open to influences from the solar wind and Earth’s atmosphere and components of the system couple to each other in a myriad of ways to make the systemic behavior highly nonlinear. But this still begs the question: What is the system-level approach to geospace science? A reductionist view might assert that as our understanding of a component or subsystem progresses to a certain point, we can couple some together to understand the system on a higher level. However, in practice, a subsystem can almost never been observed in isolation with others. Even if such is possible, there is no guarantee that the subsystem behavior will not change when coupled to others. Hence, there is no guarantee that a subsystem, such as the ring current, has an innate and intrinsic behavior like a hydrogen atom. An absolutist conclusion from this logic can be sobering, as one would have to trace a flash of aurora to the nucleosynthesis in the solar core. The practical answer, however, is more promising; it is a mix of the common sense we call reductionism and awareness that, especially when strongly coupled, subsystems can experience behavioral changes, breakdowns, and catastrophes. If the stock answer to the systemic tendency of geospace is complexity, the objective of the system-level approach to geospace science is to define, measure, and understand this complexity. I will use the example of magnetotail dynamics to illuminate some key points in this talk.

Finding equilibrium in the spatiotemporal chaos of the complex Ginzburg-Landau equation

NASA Astrophysics Data System (ADS)

Ballard, Christopher C.; Esty, C. Clark; Egolf, David A.

2016-11-01

Equilibrium statistical mechanics allows the prediction of collective behaviors of large numbers of interacting objects from just a few system-wide properties; however, a similar theory does not exist for far-from-equilibrium systems exhibiting complex spatial and temporal behavior. We propose a method for predicting behaviors in a broad class of such systems and apply these ideas to an archetypal example, the spatiotemporal chaotic 1D complex Ginzburg-Landau equation in the defect chaos regime. Building on the ideas of Ruelle and of Cross and Hohenberg that a spatiotemporal chaotic system can be considered a collection of weakly interacting dynamical units of a characteristic size, the chaotic length scale, we identify underlying, mesoscale, chaotic units and effective interaction potentials between them. We find that the resulting equilibrium Takahashi model accurately predicts distributions of particle numbers. These results suggest the intriguing possibility that a class of far-from-equilibrium systems may be well described at coarse-grained scales by the well-established theory of equilibrium statistical mechanics.

Finding equilibrium in the spatiotemporal chaos of the complex Ginzburg-Landau equation.

PubMed

Ballard, Christopher C; Esty, C Clark; Egolf, David A

2016-11-01

Equilibrium statistical mechanics allows the prediction of collective behaviors of large numbers of interacting objects from just a few system-wide properties; however, a similar theory does not exist for far-from-equilibrium systems exhibiting complex spatial and temporal behavior. We propose a method for predicting behaviors in a broad class of such systems and apply these ideas to an archetypal example, the spatiotemporal chaotic 1D complex Ginzburg-Landau equation in the defect chaos regime. Building on the ideas of Ruelle and of Cross and Hohenberg that a spatiotemporal chaotic system can be considered a collection of weakly interacting dynamical units of a characteristic size, the chaotic length scale, we identify underlying, mesoscale, chaotic units and effective interaction potentials between them. We find that the resulting equilibrium Takahashi model accurately predicts distributions of particle numbers. These results suggest the intriguing possibility that a class of far-from-equilibrium systems may be well described at coarse-grained scales by the well-established theory of equilibrium statistical mechanics.

Computational Models of Consumer Confidence from Large-Scale Online Attention Data: Crowd-Sourcing Econometrics

PubMed Central

2015-01-01

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation's citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting. PMID:25826692

Computational models of consumer confidence from large-scale online attention data: crowd-sourcing econometrics.

PubMed

Dong, Xianlei; Bollen, Johan

2015-01-01

Economies are instances of complex socio-technical systems that are shaped by the interactions of large numbers of individuals. The individual behavior and decision-making of consumer agents is determined by complex psychological dynamics that include their own assessment of present and future economic conditions as well as those of others, potentially leading to feedback loops that affect the macroscopic state of the economic system. We propose that the large-scale interactions of a nation's citizens with its online resources can reveal the complex dynamics of their collective psychology, including their assessment of future system states. Here we introduce a behavioral index of Chinese Consumer Confidence (C3I) that computationally relates large-scale online search behavior recorded by Google Trends data to the macroscopic variable of consumer confidence. Our results indicate that such computational indices may reveal the components and complex dynamics of consumer psychology as a collective socio-economic phenomenon, potentially leading to improved and more refined economic forecasting.

Embracing chaos and complexity: a quantum change for public health.

PubMed

Resnicow, Kenneth; Page, Scott E

2008-08-01

Public health research and practice have been guided by a cognitive, rational paradigm where inputs produce linear, predictable changes in outputs. However, the conceptual and statistical assumptions underlying this paradigm may be flawed. In particular, this perspective does not adequately account for nonlinear and quantum influences on human behavior. We propose that health behavior change is better understood through the lens of chaos theory and complex adaptive systems. Key relevant principles include that behavior change (1) is often a quantum event; (2) can resemble a chaotic process that is sensitive to initial conditions, highly variable, and difficult to predict; and (3) occurs within a complex adaptive system with multiple components, where results are often greater than the sum of their parts.

A chaotic view of behavior change: a quantum leap for health promotion.

PubMed

Resnicow, Ken; Vaughan, Roger

2006-09-12

The study of health behavior change, including nutrition and physical activity behaviors, has been rooted in a cognitive-rational paradigm. Change is conceptualized as a linear, deterministic process where individuals weigh pros and cons, and at the point at which the benefits outweigh the cost change occurs. Consistent with this paradigm, the associated statistical models have almost exclusively assumed a linear relationship between psychosocial predictors and behavior. Such a perspective however, fails to account for non-linear, quantum influences on human thought and action. Consider why after years of false starts and failed attempts, a person succeeds at increasing their physical activity, eating healthier or losing weight. Or, why after years of success a person relapses. This paper discusses a competing view of health behavior change that was presented at the 2006 annual ISBNPA meeting in Boston. Rather than viewing behavior change from a linear perspective it can be viewed as a quantum event that can be understood through the lens of Chaos Theory and Complex Dynamic Systems. Key principles of Chaos Theory and Complex Dynamic Systems relevant to understanding health behavior change include: 1) Chaotic systems can be mathematically modeled but are nearly impossible to predict; 2) Chaotic systems are sensitive to initial conditions; 3) Complex Systems involve multiple component parts that interact in a nonlinear fashion; and 4) The results of Complex Systems are often greater than the sum of their parts. Accordingly, small changes in knowledge, attitude, efficacy, etc may dramatically alter motivation and behavioral outcomes. And the interaction of such variables can yield almost infinite potential patterns of motivation and behavior change. In the linear paradigm unaccounted for variance is generally relegated to the catch all "error" term, when in fact such "error" may represent the chaotic component of the process. The linear and chaotic paradigms are however, not mutually exclusive, as behavior change may include both chaotic and cognitive processes. Studies of addiction suggest that many decisions to change are quantum rather than planned events; motivation arrives as opposed to being planned. Moreover, changes made through quantum processes appear more enduring than those that involve more rational, planned processes. How such processes may apply to nutrition and physical activity behavior and related interventions merits examination.

Review Article: Shallow Draughts--Larsen-Freeman and Cameron on Complexity

ERIC Educational Resources Information Center

Gregg, Kevin R.

2010-01-01

Complexity theory is a field of physics that studies the nature and behavior of complex systems, systems whose elements interact in complex and unpredictable ways. Recent years have seen a number of attempts to extend its scope to the biological and social sciences, and now Larsen-Freeman and Cameron offer a view of applied linguistics from a…

The phase behavior of cationic lipid-DNA complexes.

PubMed Central

May, S; Harries, D; Ben-Shaul, A

2000-01-01

We present a theoretical analysis of the phase behavior of solutions containing DNA, cationic lipids, and nonionic (helper) lipids. Our model allows for five possible structures, treated as incompressible macroscopic phases: two lipid-DNA composite (lipoplex) phases, namely, the lamellar (L(alpha)(C)) and hexagonal (H(II)(C)) complexes; two binary (cationic/neutral) lipid phases, that is, the bilayer (L(alpha)) and inverse-hexagonal (H(II)) structures, and uncomplexed DNA. The free energy of the four lipid-containing phases is expressed as a sum of composition-dependent electrostatic, elastic, and mixing terms. The electrostatic free energies of all phases are calculated based on Poisson-Boltzmann theory. The phase diagram of the system is evaluated by minimizing the total free energy of the three-component mixture with respect to all the compositional degrees of freedom. We show that the phase behavior, in particular the preferred lipid-DNA complex geometry, is governed by a subtle interplay between the electrostatic, elastic, and mixing terms, which depend, in turn, on the lipid composition and lipid/DNA ratio. Detailed calculations are presented for three prototypical systems, exhibiting markedly different phase behaviors. The simplest mixture corresponds to a rigid planar membrane as the lipid source, in which case, only lamellar complexes appear in solution. When the membranes are "soft" (i.e., low bending modulus) the system exhibits the formation of both lamellar and hexagonal complexes, sometimes coexisting with each other, and with pure lipid or DNA phases. The last system corresponds to a lipid mixture involving helper lipids with strong propensity toward the inverse-hexagonal phase. Here, again, the phase diagram is rather complex, revealing a multitude of phase transitions and coexistences. Lamellar and hexagonal complexes appear, sometimes together, in different regions of the phase diagram. PMID:10733951

Dynamic control and information processing in chemical reaction systems by tuning self-organization behavior

NASA Astrophysics Data System (ADS)

Lebiedz, Dirk; Brandt-Pollmann, Ulrich

2004-09-01

Specific external control of chemical reaction systems and both dynamic control and signal processing as central functions in biochemical reaction systems are important issues of modern nonlinear science. For example nonlinear input-output behavior and its regulation are crucial for the maintainance of the life process that requires extensive communication between cells and their environment. An important question is how the dynamical behavior of biochemical systems is controlled and how they process information transmitted by incoming signals. But also from a general point of view external forcing of complex chemical reaction processes is important in many application areas ranging from chemical engineering to biomedicine. In order to study such control issues numerically, here, we choose a well characterized chemical system, the CO oxidation on Pt(110), which is interesting per se as an externally forced chemical oscillator model. We show numerically that tuning of temporal self-organization by input signals in this simple nonlinear chemical reaction exhibiting oscillatory behavior can in principle be exploited for both specific external control of dynamical system behavior and processing of complex information.

Hybrid estimation of complex systems.

PubMed

Hofbaur, Michael W; Williams, Brian C

2004-10-01

Modern automated systems evolve both continuously and discretely, and hence require estimation techniques that go well beyond the capability of a typical Kalman Filter. Multiple model (MM) estimation schemes track these system evolutions by applying a bank of filters, one for each discrete system mode. Modern systems, however, are often composed of many interconnected components that exhibit rich behaviors, due to complex, system-wide interactions. Modeling these systems leads to complex stochastic hybrid models that capture the large number of operational and failure modes. This large number of modes makes a typical MM estimation approach infeasible for online estimation. This paper analyzes the shortcomings of MM estimation, and then introduces an alternative hybrid estimation scheme that can efficiently estimate complex systems with large number of modes. It utilizes search techniques from the toolkit of model-based reasoning in order to focus the estimation on the set of most likely modes, without missing symptoms that might be hidden amongst the system noise. In addition, we present a novel approach to hybrid estimation in the presence of unknown behavioral modes. This leads to an overall hybrid estimation scheme for complex systems that robustly copes with unforeseen situations in a degraded, but fail-safe manner.

Complex Adaptive Systems: The Theater Air Control System in Desert Storm

DTIC Science & Technology

2014-05-22

insight into leverage points of effective and ineffective adaptation of the TACS. Successful adaptation indicates that increased variety or diversity of...encourages innovation and diversity of ideas. 15. SUBJECT TERMS Theater Air Control System, TACS, Complex Adaptive Systems, Adaptation, Desert Storm...increased variety or diversity of agents and purposeful behaviors are beneficial to overcoming complexity. Leaders play a key role in creating an

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

PubMed

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.

Resource Recovery-based Sustainable Water Systems - the City of Tomorrow

EPA Science Inventory

Urban water systems are an example of complex, dynamic human-environment coupled systems which exhibit emergent behaviors that transcends individual scientific disciplines. To address the complexities associated with municipal water issues there is a need to shift from our tradi...

Contrarian behavior in a complex adaptive system

NASA Astrophysics Data System (ADS)

Liang, Y.; An, K. N.; Yang, G.; Huang, J. P.

2013-01-01

Contrarian behavior is a kind of self-organization in complex adaptive systems (CASs). Here we report the existence of a transition point in a model resource-allocation CAS with contrarian behavior by using human experiments, computer simulations, and theoretical analysis. The resource ratio and system predictability serve as the tuning parameter and order parameter, respectively. The transition point helps to reveal the positive or negative role of contrarian behavior. This finding is in contrast to the common belief that contrarian behavior always has a positive role in resource allocation, say, stabilizing resource allocation by shrinking the redundancy or the lack of resources. It is further shown that resource allocation can be optimized at the transition point by adding an appropriate size of contrarians. This work is also expected to be of value to some other fields ranging from management and social science to ecology and evolution.

Automatic Fault Characterization via Abnormality-Enhanced Classification

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

Bronevetsky, G; Laguna, I; de Supinski, B R

Enterprise and high-performance computing systems are growing extremely large and complex, employing hundreds to hundreds of thousands of processors and software/hardware stacks built by many people across many organizations. As the growing scale of these machines increases the frequency of faults, system complexity makes these faults difficult to detect and to diagnose. Current system management techniques, which focus primarily on efficient data access and query mechanisms, require system administrators to examine the behavior of various system services manually. Growing system complexity is making this manual process unmanageable: administrators require more effective management tools that can detect faults and help tomore » identify their root causes. System administrators need timely notification when a fault is manifested that includes the type of fault, the time period in which it occurred and the processor on which it originated. Statistical modeling approaches can accurately characterize system behavior. However, the complex effects of system faults make these tools difficult to apply effectively. This paper investigates the application of classification and clustering algorithms to fault detection and characterization. We show experimentally that naively applying these methods achieves poor accuracy. Further, we design novel techniques that combine classification algorithms with information on the abnormality of application behavior to improve detection and characterization accuracy. Our experiments demonstrate that these techniques can detect and characterize faults with 65% accuracy, compared to just 5% accuracy for naive approaches.« less

Supporting Space Systems Design via Systems Dependency Analysis Methodology

NASA Astrophysics Data System (ADS)

Guariniello, Cesare

The increasing size and complexity of space systems and space missions pose severe challenges to space systems engineers. When complex systems and Systems-of-Systems are involved, the behavior of the whole entity is not only due to that of the individual systems involved but also to the interactions and dependencies between the systems. Dependencies can be varied and complex, and designers usually do not perform analysis of the impact of dependencies at the level of complex systems, or this analysis involves excessive computational cost, or occurs at a later stage of the design process, after designers have already set detailed requirements, following a bottom-up approach. While classical systems engineering attempts to integrate the perspectives involved across the variety of engineering disciplines and the objectives of multiple stakeholders, there is still a need for more effective tools and methods capable to identify, analyze and quantify properties of the complex system as a whole and to model explicitly the effect of some of the features that characterize complex systems. This research describes the development and usage of Systems Operational Dependency Analysis and Systems Developmental Dependency Analysis, two methods based on parametric models of the behavior of complex systems, one in the operational domain and one in the developmental domain. The parameters of the developed models have intuitive meaning, are usable with subjective and quantitative data alike, and give direct insight into the causes of observed, and possibly emergent, behavior. The approach proposed in this dissertation combines models of one-to-one dependencies among systems and between systems and capabilities, to analyze and evaluate the impact of failures or delays on the outcome of the whole complex system. The analysis accounts for cascading effects, partial operational failures, multiple failures or delays, and partial developmental dependencies. The user of these methods can assess the behavior of each system based on its internal status and on the topology of its dependencies on systems connected to it. Designers and decision makers can therefore quickly analyze and explore the behavior of complex systems and evaluate different architectures under various working conditions. The methods support educated decision making both in the design and in the update process of systems architecture, reducing the need to execute extensive simulations. In particular, in the phase of concept generation and selection, the information given by the methods can be used to identify promising architectures to be further tested and improved, while discarding architectures that do not show the required level of global features. The methods, when used in conjunction with appropriate metrics, also allow for improved reliability and risk analysis, as well as for automatic scheduling and re-scheduling based on the features of the dependencies and on the accepted level of risk. This dissertation illustrates the use of the two methods in sample aerospace applications, both in the operational and in the developmental domain. The applications show how to use the developed methodology to evaluate the impact of failures, assess the criticality of systems, quantify metrics of interest, quantify the impact of delays, support informed decision making when scheduling the development of systems and evaluate the achievement of partial capabilities. A larger, well-framed case study illustrates how the Systems Operational Dependency Analysis method and the Systems Developmental Dependency Analysis method can support analysis and decision making, at the mid and high level, in the design process of architectures for the exploration of Mars. The case study also shows how the methods do not replace the classical systems engineering methodologies, but support and improve them.

COREBA (cognition-oriented emergent behavior architecture)

NASA Astrophysics Data System (ADS)

Kwak, S. David

2000-06-01

Currently, many behavior implementation technologies are available for modeling human behaviors in Department of Defense (DOD) computerized systems. However, it is commonly known that any single currently adopted behavior implementation technology is not so capable of fully representing complex and dynamic human decision-making and cognition behaviors. The author views that the current situation can be greatly improved if multiple technologies are integrated within a well designed overarching architecture that amplifies the merits of each of the participating technologies while suppressing the limitations that are inherent with each of the technologies. COREBA uses an overarching behavior integration architecture that makes the multiple implementation technologies cooperate in a homogeneous environment while collectively transcending the limitations associated with the individual implementation technologies. Specifically, COREBA synergistically integrates Artificial Intelligence and Complex Adaptive System under Rational Behavior Model multi-level multi- paradigm behavior architecture. This paper will describe applicability of COREBA in DOD domain, behavioral capabilities and characteristics of COREBA and how the COREBA architectural integrates various behavior implementation technologies.

Selective predation and productivity jointly drive complex behavior in host-parasite systems.

PubMed

Hall, Spencer R; Duffy, Meghan A; Cáceres, Carla E

2005-01-01

Successful invasion of a parasite into a host population and resulting host-parasite dynamics can depend crucially on other members of a host's community such as predators. We do not fully understand how predation intensity and selectivity shape host-parasite dynamics because the interplay between predator density, predator foraging behavior, and ecosystem productivity remains incompletely explored. By modifying a standard susceptible-infected model, we show how productivity can modulate complex behavior induced by saturating and selective foraging behavior of predators in an otherwise stable host-parasite system. When predators strongly prefer parasitized hosts, the host-parasite system can oscillate, but predators can also create alternative stable states, Allee effects, and catastrophic extinction of parasites. In the latter three cases, parasites have difficulty invading and/or persisting in ecosystems. When predators are intermediately selective, these more complex behaviors become less important, but the host-parasite system can switch from stable to oscillating and then back to stable states along a gradient of predator control. Surprisingly, at higher productivity, predators that neutrally select or avoid parasitized hosts can catalyze extinction of both hosts and parasites. Thus, synergy between two enemies can end disastrously for the host. Such diverse outcomes underscore the crucial importance of the community and ecosystem context in which host-parasite interactions occur.

Mathematical concepts for modeling human behavior in complex man-machine systems

NASA Technical Reports Server (NTRS)

Johannsen, G.; Rouse, W. B.

1979-01-01

Many human behavior (e.g., manual control) models have been found to be inadequate for describing processes in certain real complex man-machine systems. An attempt is made to find a way to overcome this problem by examining the range of applicability of existing mathematical models with respect to the hierarchy of human activities in real complex tasks. Automobile driving is chosen as a baseline scenario, and a hierarchy of human activities is derived by analyzing this task in general terms. A structural description leads to a block diagram and a time-sharing computer analogy.

Mathematical Models to Determine Stable Behavior of Complex Systems

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Biologically-inspired approaches for self-organization, adaptation, and collaboration of heterogeneous autonomous systems

NASA Astrophysics Data System (ADS)

Steinberg, Marc

2011-06-01

This paper presents a selective survey of theoretical and experimental progress in the development of biologicallyinspired approaches for complex surveillance and reconnaissance problems with multiple, heterogeneous autonomous systems. The focus is on approaches that may address ISR problems that can quickly become mathematically intractable or otherwise impractical to implement using traditional optimization techniques as the size and complexity of the problem is increased. These problems require dealing with complex spatiotemporal objectives and constraints at a variety of levels from motion planning to task allocation. There is also a need to ensure solutions are reliable and robust to uncertainty and communications limitations. First, the paper will provide a short introduction to the current state of relevant biological research as relates to collective animal behavior. Second, the paper will describe research on largely decentralized, reactive, or swarm approaches that have been inspired by biological phenomena such as schools of fish, flocks of birds, ant colonies, and insect swarms. Next, the paper will discuss approaches towards more complex organizational and cooperative mechanisms in team and coalition behaviors in order to provide mission coverage of large, complex areas. Relevant team behavior may be derived from recent advances in understanding of the social and cooperative behaviors used for collaboration by tens of animals with higher-level cognitive abilities such as mammals and birds. Finally, the paper will briefly discuss challenges involved in user interaction with these types of systems.

Complexity, Robustness, and Network Thermodynamics in Large-Scale and Multiagent Systems: A Hybrid Control Approach

DTIC Science & Technology

2012-01-11

dynamic behavior , wherein a dissipative dynamical system can deliver only a fraction of its energy to its surroundings and can store only a fraction of the...collection of interacting subsystems. The behavior and properties of the aggregate large-scale system can then be deduced from the behaviors of the...uniqueness is established. This state space formalism of thermodynamics shows that the behavior of heat, as described by the conservation equations of

Managing Complexity

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

Chassin, David P.; Posse, Christian; Malard, Joel M.

2004-08-01

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 paper explores the state of the art in the use physical analogs for understanding the behavior of some econophysical systems and to deriving stable and robust controlmore » strategies for them. In particular we review and discussion applications of some analytic methods based on the 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.« less

New approach of financial volatility duration dynamics by stochastic finite-range interacting voter system.

PubMed

Wang, Guochao; Wang, Jun

2017-01-01

We make an approach on investigating the fluctuation behaviors of financial volatility duration dynamics. A new concept of volatility two-component range intensity (VTRI) is developed, which constitutes the maximal variation range of volatility intensity and shortest passage time of duration, and can quantify the investment risk in financial markets. In an attempt to study and describe the nonlinear complex properties of VTRI, a random agent-based financial price model is developed by the finite-range interacting biased voter system. The autocorrelation behaviors and the power-law scaling behaviors of return time series and VTRI series are investigated. Then, the complexity of VTRI series of the real markets and the proposed model is analyzed by Fuzzy entropy (FuzzyEn) and Lempel-Ziv complexity. In this process, we apply the cross-Fuzzy entropy (C-FuzzyEn) to study the asynchrony of pairs of VTRI series. The empirical results reveal that the proposed model has the similar complex behaviors with the actual markets and indicate that the proposed stock VTRI series analysis and the financial model are meaningful and feasible to some extent.

New approach of financial volatility duration dynamics by stochastic finite-range interacting voter system

NASA Astrophysics Data System (ADS)

Wang, Guochao; Wang, Jun

2017-01-01

We make an approach on investigating the fluctuation behaviors of financial volatility duration dynamics. A new concept of volatility two-component range intensity (VTRI) is developed, which constitutes the maximal variation range of volatility intensity and shortest passage time of duration, and can quantify the investment risk in financial markets. In an attempt to study and describe the nonlinear complex properties of VTRI, a random agent-based financial price model is developed by the finite-range interacting biased voter system. The autocorrelation behaviors and the power-law scaling behaviors of return time series and VTRI series are investigated. Then, the complexity of VTRI series of the real markets and the proposed model is analyzed by Fuzzy entropy (FuzzyEn) and Lempel-Ziv complexity. In this process, we apply the cross-Fuzzy entropy (C-FuzzyEn) to study the asynchrony of pairs of VTRI series. The empirical results reveal that the proposed model has the similar complex behaviors with the actual markets and indicate that the proposed stock VTRI series analysis and the financial model are meaningful and feasible to some extent.

Vocal repertoire of the social giant otter.

PubMed

Leuchtenberger, Caroline; Sousa-Lima, Renata; Duplaix, Nicole; Magnusson, William E; Mourão, Guilherme

2014-11-01

According to the "social intelligence hypothesis," species with complex social interactions have more sophisticated communication systems. Giant otters (Pteronura brasiliensis) live in groups with complex social interactions. It is likely that the vocal communication of giant otters is more sophisticated than previous studies suggest. The objectives of the current study were to describe the airborne vocal repertoire of giant otters in the Pantanal area of Brazil, to analyze call types within different behavioral contexts, and to correlate vocal complexity with level of sociability of mustelids to verify whether or not the result supports the social intelligence hypothesis. The behavior of nine giant otters groups was observed. Vocalizations recorded were acoustically and statistically analyzed to describe the species' repertoire. The repertoire was comprised by 15 sound types emitted in different behavioral contexts. The main behavioral contexts of each sound type were significantly associated with the acoustic variable ordination of different sound types. A strong correlation between vocal complexity and sociability was found for different species, suggesting that the communication systems observed in the family mustelidae support the social intelligence hypothesis.

Snowflakes, Living Systems, and the Mystery of Giftedness

ERIC Educational Resources Information Center

Dai, David Yun; Renzulli, Joseph S.

2008-01-01

The main argument of this article is that human living systems are open, dynamic, intentional systems and, therefore, are capable of building ever more complex behaviors through self-organization and self-direction. This principle underlying general human development is also applicable to the development of gifted and talented behaviors. These…

A PDA-based system for online recording and analysis of concurrent events in complex behavioral processes.

PubMed

Held, Jürgen; Manser, Tanja

2005-02-01

This article outlines how a Palm- or Newton-based PDA (personal digital assistant) system for online event recording was used to record and analyze concurrent events. We describe the features of this PDA-based system, called the FIT-System (flexible interface technique), and its application to the analysis of concurrent events in complex behavioral processes--in this case, anesthesia work processes. The patented FIT-System has a unique user interface design allowing the user to design an interface template with a pencil and paper or using a transparency film. The template usually consists of a drawing or sketch that includes icons or symbols that depict the observer's representation of the situation to be observed. In this study, the FIT-System allowed us to create a design for fast, intuitive online recording of concurrent events using a set of 41 observation codes. An analysis of concurrent events leads to a description of action density, and our results revealed a characteristic distribution of action density during the administration of anesthesia in the operating room. This distribution indicated the central role of the overlapping operations in the action sequences of medical professionals as they deal with the varying requirements of this complex task. We believe that the FIT-System for online recording of concurrent events in complex behavioral processes has the potential to be useful across a broad spectrum of research areas.

Impact of delayed information in sub-second complex systems

NASA Astrophysics Data System (ADS)

Manrique, Pedro D.; Zheng, Minzhang; Johnson Restrepo, D. Dylan; Hui, Pak Ming; Johnson, Neil F.

What happens when you slow down the delivery of information in large-scale complex systems that operate faster than the blink of an eye? This question just adopted immediate commercial, legal and political importance following U.S. regulators' decision to allow an intentional 350 microsecond delay to be added in the ultrafast network of financial exchanges. However there is still no scientific understanding available to policymakers of the potential system-wide impact of such delays. Here we take a first step in addressing this question using a minimal model of a population of competing, heterogeneous, adaptive agents which has previously been shown to produce similar statistical features to real markets. We find that while certain extreme system-level behaviors can be prevented by such delays, the duration of others is increased. This leads to a highly non-trivial relationship between delays and system-wide instabilities which warrants deeper empirical investigation. The generic nature of our model suggests there should be a fairly wide class of complex systems where such delay-driven extreme behaviors can arise, e.g. sub-second delays in brain function possibly impacting individuals' behavior, and sub-second delays in navigational systems potentially impacting the safety of driverless vehicles.

Is a Universal Science of Complexity Conceivable?

NASA Astrophysics Data System (ADS)

West, Geoffrey B.

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

Origins of Aminergic Regulation of Behavior in Complex Insect Social Systems

PubMed Central

Kamhi, J. Frances; Arganda, Sara; Moreau, Corrie S.; Traniello, James F. A.

2017-01-01

Neuromodulators are conserved across insect taxa, but how biogenic amines and their receptors in ancestral solitary forms have been co-opted to control behaviors in derived socially complex species is largely unknown. Here we explore patterns associated with the functions of octopamine (OA), serotonin (5-HT) and dopamine (DA) in solitary ancestral insects and their derived functions in eusocial ants, bees, wasps and termites. Synthesizing current findings that reveal potential ancestral roles of monoamines in insects, we identify physiological processes and conserved behaviors under aminergic control, consider how biogenic amines may have evolved to modulate complex social behavior, and present focal research areas that warrant further study. PMID:29066958

Complex behavior in chains of nonlinear oscillators.

PubMed

Alonso, Leandro M

2017-06-01

This article outlines sufficient conditions under which a one-dimensional chain of identical nonlinear oscillators can display complex spatio-temporal behavior. The units are described by phase equations and consist of excitable oscillators. The interactions are local and the network is poised to a critical state by balancing excitation and inhibition locally. The results presented here suggest that in networks composed of many oscillatory units with local interactions, excitability together with balanced interactions is sufficient to give rise to complex emergent features. For values of the parameters where complex behavior occurs, the system also displays a high-dimensional bifurcation where an exponentially large number of equilibria are borne in pairs out of multiple saddle-node bifurcations.

Prospect Theory and Interval-Valued Hesitant Set for Safety Evacuation Model

NASA Astrophysics Data System (ADS)

Kou, Meng; Lu, Na

2018-01-01

The study applies the research results of prospect theory and multi attribute decision making theory, combined with the complexity, uncertainty and multifactor influence of the underground mine fire system and takes the decision makers’ psychological behavior of emotion and intuition into full account to establish the intuitionistic fuzzy multiple attribute decision making method that is based on the prospect theory. The model established by this method can explain the decision maker’s safety evacuation decision behavior in the complex system of underground mine fire due to the uncertainty of the environment, imperfection of the information and human psychological behavior and other factors.

QMU as an approach to strengthening the predictive capabilities of complex models.

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

Gray, Genetha Anne.; Boggs, Paul T.; Grace, Matthew D.

2010-09-01

Complex systems are made up of multiple interdependent parts, and the behavior of the entire system cannot always be directly inferred from the behavior of the individual parts. They are nonlinear and system responses are not necessarily additive. Examples of complex systems include energy, cyber and telecommunication infrastructures, human and animal social structures, and biological structures such as cells. To meet the goals of infrastructure development, maintenance, and protection for cyber-related complex systems, novel modeling and simulation technology is needed. Sandia has shown success using M&S in the nuclear weapons (NW) program. However, complex systems represent a significant challenge andmore » relative departure from the classical M&S exercises, and many of the scientific and mathematical M&S processes must be re-envisioned. Specifically, in the NW program, requirements and acceptable margins for performance, resilience, and security are well-defined and given quantitatively from the start. The Quantification of Margins and Uncertainties (QMU) process helps to assess whether or not these safety, reliability and performance requirements have been met after a system has been developed. In this sense, QMU is used as a sort of check that requirements have been met once the development process is completed. In contrast, performance requirements and margins may not have been defined a priori for many complex systems, (i.e. the Internet, electrical distribution grids, etc.), particularly not in quantitative terms. This project addresses this fundamental difference by investigating the use of QMU at the start of the design process for complex systems. Three major tasks were completed. First, the characteristics of the cyber infrastructure problem were collected and considered in the context of QMU-based tools. Second, UQ methodologies for the quantification of model discrepancies were considered in the context of statistical models of cyber activity. Third, Bayesian methods for optimal testing in the QMU framework were developed. This completion of this project represent an increased understanding of how to apply and use the QMU process as a means for improving model predictions of the behavior of complex systems. 4« less

Modeling Power Systems as Complex Adaptive Systems

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

Chassin, David P.; Malard, Joel M.; Posse, Christian

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 reviewmore » 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.« less

The Internet As a Large-Scale Complex System

NASA Astrophysics Data System (ADS)

Park, Kihong; Willinger, Walter

2005-06-01

The Internet may be viewed as a "complex system" with diverse features and many components that can give rise to unexpected emergent phenomena, revealing much about its own engineering. This book brings together chapter contributions from a workshop held at the Santa Fe Institute in March 2001. This volume captures a snapshot of some features of the Internet that may be fruitfully approached using a complex systems perspective, meaning using interdisciplinary tools and methods to tackle the subject area. The Internet penetrates the socioeconomic fabric of everyday life; a broader and deeper grasp of the Internet may be needed to meet the challenges facing the future. The resulting empirical data have already proven to be invaluable for gaining novel insights into the network's spatio-temporal dynamics, and can be expected to become even more important when tryin to explain the Internet's complex and emergent behavior in terms of elementary networking-based mechanisms. The discoveries of fractal or self-similar network traffic traces, power-law behavior in network topology and World Wide Web connectivity are instances of unsuspected, emergent system traits. Another important factor at the heart of fair, efficient, and stable sharing of network resources is user behavior. Network systems, when habited by selfish or greedy users, take on the traits of a noncooperative multi-party game, and their stability and efficiency are integral to understanding the overall system and its dynamics. Lastly, fault-tolerance and robustness of large-scale network systems can exhibit spatial and temporal correlations whose effective analysis and management may benefit from rescaling techniques applied in certain physical and biological systems. The present book will bring together several of the leading workers involved in the analysis of complex systems with the future development of the Internet.

Acquisition Program Teamwork and Performance Seen Anew: Exposing the Interplay of Architecture and Behaviors in Complex Defense Programs

DTIC Science & Technology

2016-04-30

fåÑçêãÉÇ=`Ü~åÖÉ= - 194 - Panel 16. Improving Governance of Complex Systems Acquisition Thursday, May 5, 2016 11:15 a.m. – 12:45 p.m. Chair: Rear...Admiral David Gale, USN, Program Executive Officer, SHIPS Complex System Governance for Acquisition Joseph Bradley, President, Leading Change, LLC...Bryan Moser, Lecturer, MIT John Dickmann, Vice President, Sonalysts Inc. A Complex Systems Perspective of Risk Mitigation and Modeling in

Medicaid's Complex Goals: Challenges for Managed Care and Behavioral Health

PubMed Central

Gold, Marsha; Mittler, Jessica

2000-01-01

The Medicaid program has become increasingly complex as policymakers use it to address various policy objectives, leading to structural tensions that surface with Medicaid managed care. In this article, we illustrate this complexity by focusing on the experience of three States with behavioral health carveouts—Maryland, Oregon, and Tennessee. Converting to Medicaid managed care forces policymakers to confront Medicaid's competing policy objectives, multiplicity of stakeholders, and diverse patients, many with complex needs. Emerging Medicaid managed care systems typically represent compromises in which existing inequities and fragmentation are reconfigured rather than eliminated. PMID:12500322

Chronic systemic pesticide exposure reproduces features of Parkinson's disease.

PubMed

Betarbet, R; Sherer, T B; MacKenzie, G; Garcia-Osuna, M; Panov, A V; Greenamyre, J T

2000-12-01

The cause of Parkinson's disease (PD) is unknown, but epidemiological studies suggest an association with pesticides and other environmental toxins, and biochemical studies implicate a systemic defect in mitochondrial complex I. We report that chronic, systemic inhibition of complex I by the lipophilic pesticide, rotenone, causes highly selective nigrostriatal dopaminergic degeneration that is associated behaviorally with hypokinesia and rigidity. Nigral neurons in rotenone-treated rats accumulate fibrillar cytoplasmic inclusions that contain ubiquitin and alpha-synuclein. These results indicate that chronic exposure to a common pesticide can reproduce the anatomical, neurochemical, behavioral and neuropathological features of PD.

Predicting the behavior of techno-social systems.

PubMed

Vespignani, Alessandro

2009-07-24

We live in an increasingly interconnected world of techno-social systems, in which infrastructures composed of different technological layers are interoperating within the social component that drives their use and development. Examples are provided by the Internet, the World Wide Web, WiFi communication technologies, and transportation and mobility infrastructures. The multiscale nature and complexity of these networks are crucial features in understanding and managing the networks. The accessibility of new data and the advances in the theory and modeling of complex networks are providing an integrated framework that brings us closer to achieving true predictive power of the behavior of techno-social systems.

Tio2-dopamine complex implanted unilaterally in the caudate nucleus improves motor activity and behavior function of rats with induced hemiparkinsonism.

PubMed

Vergara-Aragón, Patricia; Domínguez-Marrufo, Leonardo Eduardo; Ibarra-Guerrero, Patricia; Hernandez-Ramírez, Heidi; Hernández-Téllez, Beatriz; López-Martínez, Irma Elena; Sánchez-Cervantes, Ivonne; Santiago-Jacinto, Patricia; García-Macedo, Jorge Alberto; Valverde-Aguilar, Guadalupe; Santiago, Julio

2011-01-01

Parkinson's disease (PD) is characterized by malfunction of dopaminergic systems, and the current symptomatic treatment is to replace lost dopamine. For investigating mechanisms of pathogenesis and alternative treatments to compensate lack of dopamine (DA) activity in PD, the 6-hydroxydopamine (6-OHDA)-lesioned rat model of PD has been useful, these animals display apomorphine-induced contralateral rotational behavior, when they are examined after lesion. The purpose of this study was to assess Titania-dopamine (TiO2-DA) complexes implanted on the caudate nucleus for diminishing motor behavior alterations of the 6-OHDA rat model. Rats with 6-OHDA unilateral lesions received TiO2 alone or TiO2-DA implants, and were tested for open field (OF) gross motor crossing and rearing behaviors, and apomorphine-induced rotation (G) behavior. TiO2 complex have no effects on rearing OF and G behaviors, and a significant reducing effect on crossing motor behavior of normal rats compared to control non-treated rats throughout 56 days of observation. Interestingly, TiO2-DA treatment significant recovered motor crossing and rearing behaviors in 6-OHDA-lesioned rats, and diminished the G behaviors during 56 days of examination. Additionally, in the 6-OHDA-lesioned rats TiO2 treatment had a moderate recovering effect only on crossing behavior compared to lesioned non treated rats. Our results suggest that continuous release of dopamine in the caudate nucleus from TiO2-DA complex is capable of reversing gross motor deficits observed in the 6-OHDA-lesioned rat model of PD. Thistype of delivery system of DA represents a promising therapy for PD in humans.

Fire danger and fire behavior modeling systems in Australia, Europe, and North America

Treesearch

Francis M. Fujioka; A. Malcolm Gill; Domingos X. Viegas; B. Mike Wotton

2009-01-01

Wildland fire occurrence and behavior are complex phenomena involving essentially fuel (vegetation), topography, and weather. Fire managers around the world use a variety of systems to track and predict fire danger and fire behavior, at spatial scales that span from local to global extents, and temporal scales ranging from minutes to seasons. The fire management...

Toward a Common Structure in Demographic Educational Modeling and Simulation: A Complex Systems Approach

ERIC Educational Resources Information Center

Guevara, Porfirio

2014-01-01

This article identifies elements and connections that seem to be relevant to explain persistent aggregate behavioral patterns in educational systems when using complex dynamical systems modeling and simulation approaches. Several studies have shown what factors are at play in educational fields, but confusion still remains about the underlying…

Complexation behavior of oppositely charged polyelectrolytes: Effect of charge distribution

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

Zhao, Mingtian; Li, Baohui, E-mail: dliang@pku.edu.cn, E-mail: baohui@nankai.edu.cn; Zhou, Jihan

Complexation behavior of oppositely charged polyelectrolytes in a solution is investigated using a combination of computer simulations and experiments, focusing on the influence of polyelectrolyte charge distributions along the chains on the structure of the polyelectrolyte complexes. The simulations are performed using Monte Carlo with the replica-exchange algorithm for three model systems where each system is composed of a mixture of two types of oppositely charged model polyelectrolyte chains (EGEG){sub 5}/(KGKG){sub 5}, (EEGG){sub 5}/(KKGG){sub 5}, and (EEGG){sub 5}/(KGKG){sub 5}, in a solution including explicit solvent molecules. Among the three model systems, only the charge distributions along the chains are notmore » identical. Thermodynamic quantities are calculated as a function of temperature (or ionic strength), and the microscopic structures of complexes are examined. It is found that the three systems have different transition temperatures, and form complexes with different sizes, structures, and densities at a given temperature. Complex microscopic structures with an alternating arrangement of one monolayer of E/K monomers and one monolayer of G monomers, with one bilayer of E and K monomers and one bilayer of G monomers, and with a mixture of monolayer and bilayer of E/K monomers in a box shape and a trilayer of G monomers inside the box are obtained for the three mixture systems, respectively. The experiments are carried out for three systems where each is composed of a mixture of two types of oppositely charged peptide chains. Each peptide chain is composed of Lysine (K) and glycine (G) or glutamate (E) and G, in solution, and the chain length and amino acid sequences, and hence the charge distribution, are precisely controlled, and all of them are identical with those for the corresponding model chain. The complexation behavior and complex structures are characterized through laser light scattering and atomic force microscopy measurements. The order of the apparent weight-averaged molar mass and the order of density of complexes observed from the three experimental systems are qualitatively in agreement with those predicted from the simulations.« less

A neural learning classifier system with self-adaptive constructivism for mobile robot control.

PubMed

Hurst, Jacob; Bull, Larry

2006-01-01

For artificial entities to achieve true autonomy and display complex lifelike behavior, they will need to exploit appropriate adaptable learning algorithms. In this context adaptability implies flexibility guided by the environment at any given time and an open-ended ability to learn appropriate behaviors. This article examines the use of constructivism-inspired mechanisms within a neural learning classifier system architecture that exploits parameter self-adaptation as an approach to realize such behavior. The system uses a rule structure in which each rule is represented by an artificial neural network. It is shown that appropriate internal rule complexity emerges during learning at a rate controlled by the learner and that the structure indicates underlying features of the task. Results are presented in simulated mazes before moving to a mobile robot platform.

Robust mechanobiological behavior emerges in heterogeneous myosin systems.

PubMed

Egan, Paul F; Moore, Jeffrey R; Ehrlicher, Allen J; Weitz, David A; Schunn, Christian; Cagan, Jonathan; LeDuc, Philip

2017-09-26

Biological complexity presents challenges for understanding natural phenomenon and engineering new technologies, particularly in systems with molecular heterogeneity. Such complexity is present in myosin motor protein systems, and computational modeling is essential for determining how collective myosin interactions produce emergent system behavior. We develop a computational approach for altering myosin isoform parameters and their collective organization, and support predictions with in vitro experiments of motility assays with α-actinins as molecular force sensors. The computational approach models variations in single myosin molecular structure, system organization, and force stimuli to predict system behavior for filament velocity, energy consumption, and robustness. Robustness is the range of forces where a filament is expected to have continuous velocity and depends on used myosin system energy. Myosin systems are shown to have highly nonlinear behavior across force conditions that may be exploited at a systems level by combining slow and fast myosin isoforms heterogeneously. Results suggest some heterogeneous systems have lower energy use near stall conditions and greater energy consumption when unloaded, therefore promoting robustness. These heterogeneous system capabilities are unique in comparison with homogenous systems and potentially advantageous for high performance bionanotechnologies. Findings open doors at the intersections of mechanics and biology, particularly for understanding and treating myosin-related diseases and developing approaches for motor molecule-based technologies.

Robust mechanobiological behavior emerges in heterogeneous myosin systems

NASA Astrophysics Data System (ADS)

Egan, Paul F.; Moore, Jeffrey R.; Ehrlicher, Allen J.; Weitz, David A.; Schunn, Christian; Cagan, Jonathan; LeDuc, Philip

2017-09-01

Biological complexity presents challenges for understanding natural phenomenon and engineering new technologies, particularly in systems with molecular heterogeneity. Such complexity is present in myosin motor protein systems, and computational modeling is essential for determining how collective myosin interactions produce emergent system behavior. We develop a computational approach for altering myosin isoform parameters and their collective organization, and support predictions with in vitro experiments of motility assays with α-actinins as molecular force sensors. The computational approach models variations in single myosin molecular structure, system organization, and force stimuli to predict system behavior for filament velocity, energy consumption, and robustness. Robustness is the range of forces where a filament is expected to have continuous velocity and depends on used myosin system energy. Myosin systems are shown to have highly nonlinear behavior across force conditions that may be exploited at a systems level by combining slow and fast myosin isoforms heterogeneously. Results suggest some heterogeneous systems have lower energy use near stall conditions and greater energy consumption when unloaded, therefore promoting robustness. These heterogeneous system capabilities are unique in comparison with homogenous systems and potentially advantageous for high performance bionanotechnologies. Findings open doors at the intersections of mechanics and biology, particularly for understanding and treating myosin-related diseases and developing approaches for motor molecule-based technologies.

Construction of Polynuclear Lanthanide (Ln = Dy(III), Tb(III), and Nd(III)) Cage Complexes Using Pyridine-Pyrazole-Based Ligands: Versatile Molecular Topologies and SMM Behavior.

PubMed

Bala, Sukhen; Sen Bishwas, Mousumi; Pramanik, Bhaskar; Khanra, Sumit; Fromm, Katharina M; Poddar, Pankaj; Mondal, Raju

2015-09-08

Employment of two different pyridyl-pyrazolyl-based ligands afforded three octanuclear lanthanide(III) (Ln = Dy, Tb) cage compounds and one hexanuclear neodymium(III) coordination cage, exhibiting versatile molecular architectures including a butterfly core. Relatively less common semirigid pyridyl-pyrazolyl-based asymmetric ligand systems show an interesting trend of forming polynuclear lanthanide cage complexes with different coordination environments around the metal centers. It is noteworthy here that construction of lanthanide complex itself is a challenging task in a ligand system as soft N-donor rich as pyridyl-pyrazol. We report herein some lanthanide complexes using ligand containing only one or two O-donors compare to five N-coordinating sites. The resultant multinuclear lanthanide complexes show interesting magnetic and spectroscopic features originating from different spatial arrangements of the metal ions. Alternating current (ac) susceptibility measurements of the two dysprosium complexes display frequency- and temperature-dependent out-of-phase signals in zero and 0.5 T direct current field, a typical characteristic feature of single-molecule magnet (SMM) behavior, indicating different energy reversal barriers due to different molecular topologies. Another aspect of this work is the occurrence of the not-so-common SMM behavior of the terbium complex, further confirmed by ac susceptibility measurement.

Network Theory: A Primer and Questions for Air Transportation Systems Applications

NASA Technical Reports Server (NTRS)

Holmes, Bruce J.

2004-01-01

A new understanding (with potential applications to air transportation systems) has emerged in the past five years in the scientific field of networks. This development emerges in large part because we now have a new laboratory for developing theories about complex networks: The Internet. The premise of this new understanding is that most complex networks of interest, both of nature and of human contrivance, exhibit a fundamentally different behavior than thought for over two hundred years under classical graph theory. Classical theory held that networks exhibited random behavior, characterized by normal, (e.g., Gaussian or Poisson) degree distributions of the connectivity between nodes by links. The new understanding turns this idea on its head: networks of interest exhibit scale-free (or small world) degree distributions of connectivity, characterized by power law distributions. The implications of scale-free behavior for air transportation systems include the potential that some behaviors of complex system architectures might be analyzed through relatively simple approximations of local elements of the system. For air transportation applications, this presentation proposes a framework for constructing topologies (architectures) that represent the relationships between mobility, flight operations, aircraft requirements, and airspace capacity, and the related externalities in airspace procedures and architectures. The proposed architectures or topologies may serve as a framework for posing comparative and combinative analyses of performance, cost, security, environmental, and related metrics.

Short-Range Temporal Interactions in Sleep; Hippocampal Spike Avalanches Support a Large Milieu of Sequential Activity Including Replay

PubMed Central

Mahoney, J. Matthew; Titiz, Ali S.; Hernan, Amanda E.; Scott, Rod C.

2016-01-01

Hippocampal neural systems consolidate multiple complex behaviors into memory. However, the temporal structure of neural firing supporting complex memory consolidation is unknown. Replay of hippocampal place cells during sleep supports the view that a simple repetitive behavior modifies sleep firing dynamics, but does not explain how multiple episodes could be integrated into associative networks for recollection during future cognition. Here we decode sequential firing structure within spike avalanches of all pyramidal cells recorded in sleeping rats after running in a circular track. We find that short sequences that combine into multiple long sequences capture the majority of the sequential structure during sleep, including replay of hippocampal place cells. The ensemble, however, is not optimized for maximally producing the behavior-enriched episode. Thus behavioral programming of sequential correlations occurs at the level of short-range interactions, not whole behavioral sequences and these short sequences are assembled into a large and complex milieu that could support complex memory consolidation. PMID:26866597

Designing To Learn about Complex Systems.

ERIC Educational Resources Information Center

Hmelo, Cindy E.; Holton, Douglas L.; Kolodner, Janet L.

2000-01-01

Indicates the presence of complex structural, behavioral, and functional relations to understanding. Reports on a design experiment in which 6th grade children learned about the human respiratory system by designing artificial lungs and building partial working models. Makes suggestions for successful learning from design activities. (Contains 44…

Special Educators as Intervention Specialists: Dynamic Systems and the Complexity of Intensifying Intervention for Students With Emotional and Behavioral Disorders

ERIC Educational Resources Information Center

Farmer, Thomas W.; Sutherland, Kevin S.; Talbott, Elizabeth; Brooks, Debbie S.; Norwalk, Kate; Huneke, Michelle

2016-01-01

We present a dynamic systems perspective for the intensification of interventions for students with emotional and behavioral disorders (EBD). With this framework, we suggest behavior involves the contributions of multiple factors and reflects the interplay between the characteristics of the student and the ecologies in which he or she is embedded.…

Power-rate-distortion analysis for wireless video communication under energy constraint

NASA Astrophysics Data System (ADS)

He, Zhihai; Liang, Yongfang; Ahmad, Ishfaq

2004-01-01

In video coding and streaming over wireless communication network, the power-demanding video encoding operates on the mobile devices with limited energy supply. To analyze, control, and optimize the rate-distortion (R-D) behavior of the wireless video communication system under the energy constraint, we need to develop a power-rate-distortion (P-R-D) analysis framework, which extends the traditional R-D analysis by including another dimension, the power consumption. Specifically, in this paper, we analyze the encoding mechanism of typical video encoding systems and develop a parametric video encoding architecture which is fully scalable in computational complexity. Using dynamic voltage scaling (DVS), a hardware technology recently developed in CMOS circuits design, the complexity scalability can be translated into the power consumption scalability of the video encoder. We investigate the rate-distortion behaviors of the complexity control parameters and establish an analytic framework to explore the P-R-D behavior of the video encoding system. Both theoretically and experimentally, we show that, using this P-R-D model, the encoding system is able to automatically adjust its complexity control parameters to match the available energy supply of the mobile device while maximizing the picture quality. The P-R-D model provides a theoretical guideline for system design and performance optimization in wireless video communication under energy constraint, especially over the wireless video sensor network.

Effect on Ammonium Bromide in dielectric behavior based Alginate Solid Biopolymer electrolytes

NASA Astrophysics Data System (ADS)

Fuzlin, A. F.; Rasali, N. M. J.; Samsudin, A. S.

2018-04-01

This paper present the development of solid biopolymer electrolytes (SBEs) system which has been accomplished by incorporating various composition of ionic dopant namely ammonium bromide (NH4Br) with alginate solution casting method. The prepared sample of SBEs has been analyzed via electrical impedance spectroscopy (EIS) showed that the ionic conductivity at room temperature was increased from 4.67 x 10-7 S cm-1 for un-doped sample to optimum value at 4.41 x 10-5 S cm-1 for composition of 20 wt. % NH4Br. The SBEs system was found to obey the Arrhenius characteristics with R2~1where all sample is thermally activated when increasing temperature. The dielectric behavior of the alginate-NH4Br SBEs system were measured using complex permittivity (ε*) and complex electrical modulus (M*) and shown the non-debye behavior where no single relaxation was found for present SBEs system.

Critical behavior in graphene with Coulomb interactions.

PubMed

Wang, Jianhui; Fertig, H A; Murthy, Ganpathy

2010-05-07

We demonstrate that, in the presence of Coulomb interactions, electrons in graphene behave like a critical system, supporting power law correlations with interaction-dependent exponents. An asymptotic analysis shows that the origin of this behavior lies in particle-hole scattering, for which the Coulomb interaction induces anomalously close approaches. With increasing interaction strength the relevant power law changes from real to complex, leading to an unusual instability characterized by a complex-valued susceptibility in the thermodynamic limit. Measurable quantities, as well as the connection to classical two-dimensional systems, are discussed.

An integration architecture for the automation of a continuous production complex.

PubMed

Chacón, Edgar; Besembel, Isabel; Narciso, Flor; Montilva, Jonás; Colina, Eliezer

2002-01-01

The development of integrated automation systems for continuous production plants is a very complicated process. A variety of factors must be taken into account, such as their different components (e.g., production units control systems, planning systems, financial systems, etc.), the interaction among them, and their different behavior (continuous or discrete). Moreover, the difficulty of this process is increased by the fact that each component can be viewed in a different way depending on the kind of decisions to be made, and its specific behavior. Modeling continuous production complexes as a composition of components, where, in turn, each component may also be a composite, appears to be the simplest and safest way to develop integrated automation systems. In order to provide the most versatile way to develop this kind of system, this work proposes a new approach for designing and building them, where process behavior, operation conditions and equipment conditions are integrated into a hierarchical automation architecture.

Developing Students' Understanding of Complex Systems in the Geosciences (Invited)

NASA Astrophysics Data System (ADS)

Manduca, C. A.; Mogk, D. W.; Bice, D. M.; Pyle, E.; Slotta, J.

2010-12-01

Developing a systems perspective is a commonly cited goal for geosciences courses and programs. This perspective is a powerful tool for critical thinking, problem solving and integrative thinking across and beyond the sciences. In April 2010, a NSF funded ‘On the Cutting Edge’ workshop brought together 45 geoscience faculty, education and cognitive science researchers, and faculty from other STEM and social science disciplines that make use of a complex systems approach. The workshop participants focused on understanding the challenges inherent in developing an understanding of complex systems and the teaching strategies currently in use across the disciplines. These include using models and visualizations to allow students to experiment with complex systems, using projects and problems to give students experience with data and observations derived from a complex system, and using illustrated lectures and discussions and analogies to illuminate the salient aspects of complex systems. The workshop website contains a collection of teaching activities, instructional resources and courses that demonstrate these approaches. The workshop participants concluded that research leading to a clear articulation of what constitutes understanding complex system behavior is needed, as are instruments and performance measures that could be used to assess this understanding. Developing the ability to recognize complex systems and understand their behavior is a significant learning task that cannot be achieved in a single course. Rather it is a type of literacy that should be taught in a progression extending from elementary school to college and across the disciplines. Research defining this progression and its endpoints is needed. Full information about the workshop, its discussions, and resulting collections of courses, activities, references and ideas are available on the workshop website.

Coupled disease-behavior dynamics on complex networks: A review

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

A case for human systems neuroscience.

PubMed

Gardner, J L

2015-06-18

Can the human brain itself serve as a model for a systems neuroscience approach to understanding the human brain? After all, how the brain is able to create the richness and complexity of human behavior is still largely mysterious. What better choice to study that complexity than to study it in humans? However, measurements of brain activity typically need to be made non-invasively which puts severe constraints on what can be learned about the internal workings of the brain. Our approach has been to use a combination of psychophysics in which we can use human behavioral flexibility to make quantitative measurements of behavior and link those through computational models to measurements of cortical activity through magnetic resonance imaging. In particular, we have tested various computational hypotheses about what neural mechanisms could account for behavioral enhancement with spatial attention (Pestilli et al., 2011). Resting both on quantitative measurements and considerations of what is known through animal models, we concluded that weighting of sensory signals by the magnitude of their response is a neural mechanism for efficient selection of sensory signals and consequent improvements in behavioral performance with attention. While animal models have many technical advantages over studying the brain in humans, we believe that human systems neuroscience should endeavor to validate, replicate and extend basic knowledge learned from animal model systems and thus form a bridge to understanding how the brain creates the complex and rich cognitive capacities of humans. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Interesting examples of supervised continuous variable systems

NASA Technical Reports Server (NTRS)

Chase, Christopher; Serrano, Joe; Ramadge, Peter

1990-01-01

The authors analyze two simple deterministic flow models for multiple buffer servers which are examples of the supervision of continuous variable systems by a discrete controller. These systems exhibit what may be regarded as the two extremes of complexity of the closed loop behavior: one is eventually periodic, the other is chaotic. The first example exhibits chaotic behavior that could be characterized statistically. The dual system, the switched server system, exhibits very predictable behavior, which is modeled by a finite state automaton. This research has application to multimodal discrete time systems where the controller can choose from a set of transition maps to implement.

A Synergistic Transcriptional Regulation of Olfactory Genes Drives Blood-Feeding Associated Complex Behavioral Responses in the Mosquito Anopheles culicifacies.

PubMed

Das De, Tanwee; Thomas, Tina; Verma, Sonia; Singla, Deepak; Chauhan, Charu; Srivastava, Vartika; Sharma, Punita; Kumari, Seena; Tevatiya, Sanjay; Rani, Jyoti; Hasija, Yasha; Pandey, Kailash C; Dixit, Rajnikant

2018-01-01

Decoding the molecular basis of host seeking and blood feeding behavioral evolution/adaptation in the adult female mosquitoes may provide an opportunity to design new molecular strategy to disrupt human-mosquito interactions. Although there is a great progress in the field of mosquito olfaction and chemo-detection, little is known about the sex-specific evolution of the specialized olfactory system of adult female mosquitoes that enables them to drive and manage the complex blood-feeding associated behavioral responses. A comprehensive RNA-Seq analysis of prior and post blood meal olfactory system of An. culicifacies mosquito revealed a minor but unique change in the nature and regulation of key olfactory genes that may play a pivotal role in managing diverse behavioral responses. Based on age-dependent transcriptional profiling, we further demonstrated that adult female mosquito's chemosensory system gradually learned and matured to drive the host-seeking and blood feeding behavior at the age of 5-6 days. A time scale expression analysis of Odorant Binding Proteins (OBPs) unravels unique association with a late evening to midnight peak biting time. Blood meal-induced switching of unique sets of OBP genes and Odorant Receptors (Ors) expression coincides with the change in the innate physiological status of the mosquitoes. Blood meal follows up experiments further provide enough evidence that how a synergistic and concurrent action of OBPs-Ors may drive "prior and post blood meal" associated complex behavioral events. A dominant expression of two sensory appendages proteins (SAP-1 & SAP2) in the legs of An. culicifacies suggests that this mosquito species may draw an extra advantage of having more sensitive appendages than An. stephensi , an urban malarial vector in the Indian subcontinents. Finally, our molecular modeling analysis predicts crucial amino acid residues for future functional characterization of the sensory appendages proteins which may play a central role in regulating multiple behaviors of An. culicifacies mosquito. SIGNIFICANCE   Evolution and adaptation of blood feeding behavior not only favored the reproductive success of adult female mosquitoes but also make them important disease-transmitting vectors. An environmental exposure after emergence may favor the broadly tuned olfactory system of mosquitoes to drive complex behavioral responses. But, how these olfactory derived genetic factors manage female specific "pre and post" blood meal associated complex behavioral responses are not well known. Our findings suggest that a synergistic action of olfactory factors may govern an innate to prime learning strategy to facilitate rapid blood meal acquisition and downstream behavioral activities. A species-specific transcriptional profiling and an in-silico analysis predict that "sensory appendages protein" may be a unique target to design disorientation strategy against the mosquito Anopheles culicifacies .

Patterns of Negotiation

NASA Astrophysics Data System (ADS)

Sood, Suresh; Pattinson, Hugh

Traditionally, face-to-face negotiations in the real world have not been looked at as a complex systems interaction of actors resulting in a dynamic and potentially emergent system. If indeed negotiations are an outcome of a dynamic interaction of simpler behavior just as with a complex system, we should be able to see the patterns contributing to the complexities of a negotiation under study. This paper and the supporting research sets out to show B2B (business-to-business) negotiations as complex systems of interacting actors exhibiting dynamic and emergent behavior. This paper discusses the exploratory research based on negotiation simulations in which a large number of business students participate as buyers and sellers. The student interactions are captured on video and a purpose built research method attempts to look for patterns of interactions between actors using visualization techniques traditionally reserved to observe the algorithmic complexity of complex systems. Students are videoed negotiating with partners. Each video is tagged according to a recognized classification and coding scheme for negotiations. The classification relates to the phases through which any particular negotiation might pass, such as laughter, aggression, compromise, and so forth — through some 30 possible categories. Were negotiations more or less successful if they progressed through the categories in different ways? Furthermore, does the data depict emergent pathway segments considered to be more or less successful? This focus on emergence within the data provides further strong support for face-to-face (F2F) negotiations to be construed as complex systems.

Basal ganglia systems in ritualistic social displays: reptiles and humans; function and illness.

PubMed

Baxter, Lewis R

2003-08-01

Complex, situation-specific territorial maintenance routines are similar across living terrestrial vertebrates (=amniotes). Decades ago, Paul MacLean et al., at the Laboratory of Brain Evolution and Behavior of the National Institute of Mental Health, postulated that these are evolutionarily conserved behaviors whose expression is mediated by the similarly conserved amniote basal ganglia and related brain systems (BG systems). Therefore, they undertook studies in nonhuman primates and in small social lizards (the common green anole, Anolis carolinensis) to examine this idea. MacLean et al. also postulated that when BG systems misfunction in humans, behavioral abnormalities result, some of them under the rubric of psychiatric illnesses. Obsessive-compulsive disorder (OCD) was singled out as one likely candidate. In the last dozen years, functional brain imaging studies of OCD patients have validated the contention that this is, in fact, a condition involving dysfunctioning BG systems. Inspired by the MacLean group's original investigations, my colleagues and I have now applied related functional imaging techniques in naturalistic experiments using Anolis to better understand BG systems' roles in the mediation of complex behavioral routines in healthy amniotes. Here, I will review this functional imaging work in primates (man, and a little in monkey) and in lizards. I believe the literature not only supports MacLean et al.'s contentions about BG systems and behavior in general, but also validates Paul MacLean's life-long contention that human behavioral medicine can profit from a broad comparative approach.

Activity Diagrams for DEVS Models: A Case Study Modeling Health Care Behavior

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

Ozmen, Ozgur; Nutaro, James J

Discrete Event Systems Specification (DEVS) is a widely used formalism for modeling and simulation of discrete and continuous systems. While DEVS provides a sound mathematical representation of discrete systems, its practical use can suffer when models become complex. Five main functions, which construct the core of atomic modules in DEVS, can realize the behaviors that modelers want to represent. The integration of these functions is handled by the simulation routine, however modelers can implement each function in various ways. Therefore, there is a need for graphical representations of complex models to simplify their implementation and facilitate their reproduction. In thismore » work, we illustrate the use of activity diagrams for this purpose in the context of a health care behavior model, which is developed with an agent-based modeling paradigm.« less

Polynomiography and Chaos

NASA Astrophysics Data System (ADS)

Kalantari, Bahman

Polynomiography is the algorithmic visualization of iterative systems for computing roots of a complex polynomial. It is well known that iterations of a rational function in the complex plane result in chaotic behavior near its Julia set. In one scheme of computing polynomiography for a given polynomial p(z), we select an individual member from the Basic Family, an infinite fundamental family of rational iteration functions that in particular include Newton's. Polynomiography is an excellent means for observing, understanding, and comparing chaotic behavior for variety of iterative systems. Other iterative schemes in polynomiography are possible and result in chaotic behavior of different kinds. In another scheme, the Basic Family is collectively applied to p(z) and the iterates for any seed in the Voronoi cell of a root converge to that root. Polynomiography reveals chaotic behavior of another kind near the boundary of the Voronoi diagram of the roots. We also describe a novel Newton-Ellipsoid iterative system with its own chaos and exhibit images demonstrating polynomiographies of chaotic behavior of different kinds. Finally, we consider chaos for the more general case of polynomiography of complex analytic functions. On the one hand polynomiography is a powerful medium capable of demonstrating chaos in different forms, it is educationally instructive to students and researchers, also it gives rise to numerous research problems. On the other hand, it is a medium resulting in images with enormous aesthetic appeal to general audiences.

Disentangling the stochastic behavior of complex time series

NASA Astrophysics Data System (ADS)

Anvari, Mehrnaz; Tabar, M. Reza Rahimi; Peinke, Joachim; Lehnertz, Klaus

2016-10-01

Complex systems involving a large number of degrees of freedom, generally exhibit non-stationary dynamics, which can result in either continuous or discontinuous sample paths of the corresponding time series. The latter sample paths may be caused by discontinuous events - or jumps - with some distributed amplitudes, and disentangling effects caused by such jumps from effects caused by normal diffusion processes is a main problem for a detailed understanding of stochastic dynamics of complex systems. Here we introduce a non-parametric method to address this general problem. By means of a stochastic dynamical jump-diffusion modelling, we separate deterministic drift terms from different stochastic behaviors, namely diffusive and jumpy ones, and show that all of the unknown functions and coefficients of this modelling can be derived directly from measured time series. We demonstrate appli- cability of our method to empirical observations by a data-driven inference of the deterministic drift term and of the diffusive and jumpy behavior in brain dynamics from ten epilepsy patients. Particularly these different stochastic behaviors provide extra information that can be regarded valuable for diagnostic purposes.

Emergent 1d Ising Behavior in AN Elementary Cellular Automaton Model

NASA Astrophysics Data System (ADS)

Kassebaum, Paul G.; Iannacchione, Germano S.

The fundamental nature of an evolving one-dimensional (1D) Ising model is investigated with an elementary cellular automaton (CA) simulation. The emergent CA simulation employs an ensemble of cells in one spatial dimension, each cell capable of two microstates interacting with simple nearest-neighbor rules and incorporating an external field. The behavior of the CA model provides insight into the dynamics of coupled two-state systems not expressible by exact analytical solutions. For instance, state progression graphs show the causal dynamics of a system through time in relation to the system's entropy. Unique graphical analysis techniques are introduced through difference patterns, diffusion patterns, and state progression graphs of the 1D ensemble visualizing the evolution. All analyses are consistent with the known behavior of the 1D Ising system. The CA simulation and new pattern recognition techniques are scalable (in both dimension, complexity, and size) and have many potential applications such as complex design of materials, control of agent systems, and evolutionary mechanism design.

Simulating the Interactions Among Land Use, Transportation ...

EPA Pesticide Factsheets

In most transportation studies, computer models that forecast travel behavior statistics for a future year use static projections of the spatial distribution of future population and employment growth as inputs. As a result, they are unable to account for the temporally dynamic and non-linear interactions among transportation, land use, and socioeconomic systems. System dynamics (SD) provides a common framework for modeling the complex interactions among transportation and other related systems. This study uses a SD model to simulate the cascading impacts of a proposed light rail transit (LRT) system in central North Carolina, USA. The Durham-Orange Light Rail Project (D-O LRP) SD model incorporates relationships among the land use, transportation, and economy sectors to simulate the complex feedbacks that give rise to the travel behavior changes forecasted by the region’s transportation model. This paper demonstrates the sensitivity of changes in travel behavior to the proposed LRT system and the assumptions that went into the transportation modeling, and compares those results to the impacts of an alternative fare-free transit system. SD models such as the D-O LRP SD model can complement transportation studies by providing valuable insight into the interdependent community systems that collectively contribute to travel behavior changes. Presented at the 35th International Conference of the System Dynamics Society in Cambridge, MA, July 18th, 2017

Cyclic Game Dynamics Driven by Iterated Reasoning

PubMed Central

Frey, Seth; Goldstone, Robert L.

2013-01-01

Recent theories from complexity science argue that complex dynamics are ubiquitous in social and economic systems. These claims emerge from the analysis of individually simple agents whose collective behavior is surprisingly complicated. However, economists have argued that iterated reasoning–what you think I think you think–will suppress complex dynamics by stabilizing or accelerating convergence to Nash equilibrium. We report stable and efficient periodic behavior in human groups playing the Mod Game, a multi-player game similar to Rock-Paper-Scissors. The game rewards subjects for thinking exactly one step ahead of others in their group. Groups that play this game exhibit cycles that are inconsistent with any fixed-point solution concept. These cycles are driven by a “hopping” behavior that is consistent with other accounts of iterated reasoning: agents are constrained to about two steps of iterated reasoning and learn an additional one-half step with each session. If higher-order reasoning can be complicit in complex emergent dynamics, then cyclic and chaotic patterns may be endogenous features of real-world social and economic systems. PMID:23441191

Molecular Origins of Thermal Transitions in Polyelectrolyte Assemblies

NASA Astrophysics Data System (ADS)

Yildirim, Erol; Zhang, Yanpu; Antila, Hanne S.; Lutkenhaus, Jodie L.; Sammalkorpi, Maria; Aalto Team; Texas A&M Team

2015-03-01

Polyelectrolyte (PE) multilayers and complexes formed from oppositely charged polymers can exhibit extraordinary superhydrophobicity, mechanical strength and responsiveness resulting in applications ranging functional membranes, optics, sensors and drug delivery. Depending on the assembly conditions, PE assemblies may undergo a thermal transition from glassy to soft behavior under heating. Our earlier work using thermal analysis measurements shows a distinct thermal transition for PE layer-by-layer (LbL) systems assembled with added salt but no analogous transition in films assembled without added salt or dry systems. These findings raise interesting questions on the nature of the thermal transition; here, we explore its molecular origins through characterization of the PE aggregates by temperature-controlled all-atom molecular dynamics simulations. We show via molecular simulations the thermal transition results from the existence of an LCST (lower critical solution temperature) in the PE systems: the diffusion behavior, hydrogen bond formation, and bridging capacity of water molecules plasticizing the complex changes at the transition temperature. We quantify the behavior, map its chemistry specificity through comparison of strongly and weakly charged PE complexes, and connect the findings to our interrelated QCM-D experiments.

Mixture and odorant processing in the olfactory systems of insects: a comparative perspective.

PubMed

Clifford, Marie R; Riffell, Jeffrey A

2013-11-01

Natural olfactory stimuli are often complex mixtures of volatiles, of which the identities and ratios of constituents are important for odor-mediated behaviors. Despite this importance, the mechanism by which the olfactory system processes this complex information remains an area of active study. In this review, we describe recent progress in how odorants and mixtures are processed in the brain of insects. We use a comparative approach toward contrasting olfactory coding and the behavioral efficacy of mixtures in different insect species, and organize these topics around four sections: (1) Examples of the behavioral efficacy of odor mixtures and the olfactory environment; (2) mixture processing in the periphery; (3) mixture coding in the antennal lobe; and (4) evolutionary implications and adaptations for olfactory processing. We also include pertinent background information about the processing of individual odorants and comparative differences in wiring and anatomy, as these topics have been richly investigated and inform the processing of mixtures in the insect olfactory system. Finally, we describe exciting studies that have begun to elucidate the role of the processing of complex olfactory information in evolution and speciation.

Serious Gaming for Test & Evaluation of Clean-Slate (Ab Initio) National Airspace System (NAS) Designs

NASA Technical Reports Server (NTRS)

Allen, B. Danette; Alexandrov, Natalia

2016-01-01

Incremental approaches to air transportation system development inherit current architectural constraints, which, in turn, place hard bounds on system capacity, efficiency of performance, and complexity. To enable airspace operations of the future, a clean-slate (ab initio) airspace design(s) must be considered. This ab initio National Airspace System (NAS) must be capable of accommodating increased traffic density, a broader diversity of aircraft, and on-demand mobility. System and subsystem designs should scale to accommodate the inevitable demand for airspace services that include large numbers of autonomous Unmanned Aerial Vehicles and a paradigm shift in general aviation (e.g., personal air vehicles) in addition to more traditional aerial vehicles such as commercial jetliners and weather balloons. The complex and adaptive nature of ab initio designs for the future NAS requires new approaches to validation, adding a significant physical experimentation component to analytical and simulation tools. In addition to software modeling and simulation, the ability to exercise system solutions in a flight environment will be an essential aspect of validation. The NASA Langley Research Center (LaRC) Autonomy Incubator seeks to develop a flight simulation infrastructure for ab initio modeling and simulation that assumes no specific NAS architecture and models vehicle-to-vehicle behavior to examine interactions and emergent behaviors among hundreds of intelligent aerial agents exhibiting collaborative, cooperative, coordinative, selfish, and malicious behaviors. The air transportation system of the future will be a complex adaptive system (CAS) characterized by complex and sometimes unpredictable (or unpredicted) behaviors that result from temporal and spatial interactions among large numbers of participants. A CAS not only evolves with a changing environment and adapts to it, it is closely coupled to all systems that constitute the environment. Thus, the ecosystem that contains the system and other systems evolves with the CAS as well. The effects of the emerging adaptation and co-evolution are difficult to capture with only combined mathematical and computational experimentation. Therefore, an ab initio flight simulation environment must accommodate individual vehicles, groups of self-organizing vehicles, and large-scale infrastructure behavior. Inspired by Massively Multiplayer Online Role Playing Games (MMORPG) and Serious Gaming, the proposed ab initio simulation environment is similar to online gaming environments in which player participants interact with each other, affect their environment, and expect the simulation to persist and change regardless of any individual player's active participation.

Wormlike micelle formation by acylglutamic acid with alkylamines.

PubMed

Sakai, Kenichi; Nomura, Kazuyuki; Shrestha, Rekha Goswami; Endo, Takeshi; Sakamoto, Kazutami; Sakai, Hideki; Abe, Masahiko

2012-12-21

Rheological properties of alkyl dicarboxylic acid-alkylamine complex systems have been characterized. The complex materials employed in this study consist of an amino acid-based surfactant (dodecanoylglutamic acid, C12Glu) and a tertiary alkylamine (dodecyldimethylamine, C12DMA) or a secondary alkylamine (dodecylmethylamine, C12MA). (1)H NMR and mass spectroscopic data have suggested that C12Glu forms a stoichiometric 1:1 complex with C12DMA and C12MA. Rheological measurements have suggested that the complex systems yield viscoelastic wormlike micellar solutions and the rheological behavior is strongly dependent on the aqueous solution pH. This pH-dependent behavior results from the structural transformation of the wormlike micelles to occur in the narrow pH range 5.5-6.2 (in the case of C12Glu-C12DMA system); i.e., positive curved aggregates such as spherical or rodlike micelles tend to be formed at high pH values. Our current study offers a unique way to obtain viscoelastic wormlike micellar solutions by means of alkyl dicarboxylic acid-alkylamine complex as gemini-like amphiphiles.

Complexity and dynamics of topological and community structure in complex networks

NASA Astrophysics Data System (ADS)

Berec, Vesna

2017-07-01

Complexity is highly susceptible to variations in the network dynamics, reflected on its underlying architecture where topological organization of cohesive subsets into clusters, system's modular structure and resulting hierarchical patterns, are cross-linked with functional dynamics of the system. Here we study connection between hierarchical topological scales of the simplicial complexes and the organization of functional clusters - communities in complex networks. The analysis reveals the full dynamics of different combinatorial structures of q-th-dimensional simplicial complexes and their Laplacian spectra, presenting spectral properties of resulting symmetric and positive semidefinite matrices. The emergence of system's collective behavior from inhomogeneous statistical distribution is induced by hierarchically ordered topological structure, which is mapped to simplicial complex where local interactions between the nodes clustered into subcomplexes generate flow of information that characterizes complexity and dynamics of the full system.

Model Based Autonomy for Robust Mars Operations

NASA Technical Reports Server (NTRS)

Kurien, James A.; Nayak, P. Pandurang; Williams, Brian C.; Lau, Sonie (Technical Monitor)

1998-01-01

Space missions have historically relied upon a large ground staff, numbering in the hundreds for complex missions, to maintain routine operations. When an anomaly occurs, this small army of engineers attempts to identify and work around the problem. A piloted Mars mission, with its multiyear duration, cost pressures, half-hour communication delays and two-week blackouts cannot be closely controlled by a battalion of engineers on Earth. Flight crew involvement in routine system operations must also be minimized to maximize science return. It also may be unrealistic to require the crew have the expertise in each mission subsystem needed to diagnose a system failure and effect a timely repair, as engineers did for Apollo 13. Enter model-based autonomy, which allows complex systems to autonomously maintain operation despite failures or anomalous conditions, contributing to safe, robust, and minimally supervised operation of spacecraft, life support, In Situ Resource Utilization (ISRU) and power systems. Autonomous reasoning is central to the approach. A reasoning algorithm uses a logical or mathematical model of a system to infer how to operate the system, diagnose failures and generate appropriate behavior to repair or reconfigure the system in response. The 'plug and play' nature of the models enables low cost development of autonomy for multiple platforms. Declarative, reusable models capture relevant aspects of the behavior of simple devices (e.g. valves or thrusters). Reasoning algorithms combine device models to create a model of the system-wide interactions and behavior of a complex, unique artifact such as a spacecraft. Rather than requiring engineers to all possible interactions and failures at design time or perform analysis during the mission, the reasoning engine generates the appropriate response to the current situation, taking into account its system-wide knowledge, the current state, and even sensor failures or unexpected behavior.

Speech as a breakthrough signaling resource in the cognitive evolution of biological complex adaptive systems.

PubMed

Mattei, Tobias A

2014-12-01

In self-adapting dynamical systems, a significant improvement in the signaling flow among agents constitutes one of the most powerful triggering events for the emergence of new complex behaviors. Ackermann and colleagues' comprehensive phylogenetic analysis of the brain structures involved in acoustic communication provides further evidence of the essential role which speech, as a breakthrough signaling resource, has played in the evolutionary development of human cognition viewed from the standpoint of complex adaptive system analysis.

Use and perception of the environment: cultural and developmental processes

Treesearch

Martin M. Chemers; Irwin Altman

1977-01-01

This paper presents a "social systems" orientation for integrating the diverse aspects of environment, culture, and individual behavior. It suggests that a wide range of variables, including the physical environment, cultural and social processes, environmental perceptions and cognitions, behavior, and products of behavior, are connected in a complex,...

A Complex Systems Framework for Research on Leadership and Organizational Dynamics in Academic Libraries

ERIC Educational Resources Information Center

Gilstrap, Donald L.

2009-01-01

This article provides a historiographical analysis of major leadership and organizational development theories that have shaped our thinking about how we lead and administrate academic libraries. Drawing from behavioral, cognitive, systems, and complexity theories, this article discusses major theorists and research studies appearing over the past…

Reliable High Performance Peta- and Exa-Scale Computing

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

Bronevetsky, G

2012-04-02

As supercomputers become larger and more powerful, they are growing increasingly complex. This is reflected both in the exponentially increasing numbers of components in HPC systems (LLNL is currently installing the 1.6 million core Sequoia system) as well as the wide variety of software and hardware components that a typical system includes. At this scale it becomes infeasible to make each component sufficiently reliable to prevent regular faults somewhere in the system or to account for all possible cross-component interactions. The resulting faults and instability cause HPC applications to crash, perform sub-optimally or even produce erroneous results. As supercomputers continuemore » to approach Exascale performance and full system reliability becomes prohibitively expensive, we will require novel techniques to bridge the gap between the lower reliability provided by hardware systems and users unchanging need for consistent performance and reliable results. Previous research on HPC system reliability has developed various techniques for tolerating and detecting various types of faults. However, these techniques have seen very limited real applicability because of our poor understanding of how real systems are affected by complex faults such as soft fault-induced bit flips or performance degradations. Prior work on such techniques has had very limited practical utility because it has generally focused on analyzing the behavior of entire software/hardware systems both during normal operation and in the face of faults. Because such behaviors are extremely complex, such studies have only produced coarse behavioral models of limited sets of software/hardware system stacks. Since this provides little insight into the many different system stacks and applications used in practice, this work has had little real-world impact. My project addresses this problem by developing a modular methodology to analyze the behavior of applications and systems during both normal and faulty operation. By synthesizing models of individual components into a whole-system behavior models my work is making it possible to automatically understand the behavior of arbitrary real-world systems to enable them to tolerate a wide range of system faults. My project is following a multi-pronged research strategy. Section II discusses my work on modeling the behavior of existing applications and systems. Section II.A discusses resilience in the face of soft faults and Section II.B looks at techniques to tolerate performance faults. Finally Section III presents an alternative approach that studies how a system should be designed from the ground up to make resilience natural and easy.« less

Archetypes for Organisational Safety

NASA Technical Reports Server (NTRS)

Marais, Karen; Leveson, Nancy G.

2003-01-01

We propose a framework using system dynamics to model the dynamic behavior of organizations in accident analysis. Most current accident analysis techniques are event-based and do not adequately capture the dynamic complexity and non-linear interactions that characterize accidents in complex systems. In this paper we propose a set of system safety archetypes that model common safety culture flaws in organizations, i.e., the dynamic behaviour of organizations that often leads to accidents. As accident analysis and investigation tools, the archetypes can be used to develop dynamic models that describe the systemic and organizational factors contributing to the accident. The archetypes help clarify why safety-related decisions do not always result in the desired behavior, and how independent decisions in different parts of the organization can combine to impact safety.

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

NASA Astrophysics Data System (ADS)

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

2008-08-01

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

Geometric state space uncertainty as a new type of uncertainty addressing disparity in ';emergent properties' between real and modeled systems

NASA Astrophysics Data System (ADS)

Montero, J. T.; Lintz, H. E.; Sharp, D.

2013-12-01

Do emergent properties that result from models of complex systems match emergent properties from real systems? This question targets a type of uncertainty that we argue requires more attention in system modeling and validation efforts. We define an ';emergent property' to be an attribute or behavior of a modeled or real system that can be surprising or unpredictable and result from complex interactions among the components of a system. For example, thresholds are common across diverse systems and scales and can represent emergent system behavior that is difficult to predict. Thresholds or other types of emergent system behavior can be characterized by their geometry in state space (where state space is the space containing the set of all states of a dynamic system). One way to expedite our growing mechanistic understanding of how emergent properties emerge from complex systems is to compare the geometry of surfaces in state space between real and modeled systems. Here, we present an index (threshold strength) that can quantify a geometric attribute of a surface in state space. We operationally define threshold strength as how strongly a surface in state space resembles a step or an abrupt transition between two system states. First, we validated the index for application in greater than three dimensions of state space using simulated data. Then, we demonstrated application of the index in measuring geometric state space uncertainty between a real system and a deterministic, modeled system. In particular, we looked at geometric space uncertainty between climate behavior in 20th century and modeled climate behavior simulated by global climate models (GCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5). Surfaces from the climate models came from running the models over the same domain as the real data. We also created response surfaces from a real, climate data based on an empirical model that produces a geometric surface of predicted values in state space. We used a kernel regression method designed to capture the geometry of real data pattern without imposing shape assumptions a priori on the data; this kernel regression method is known as Non-parametric Multiplicative Regression (NPMR). We found that quantifying and comparing a geometric attribute in more than three dimensions of state space can discern whether the emergent nature of complex interactions in modeled systems matches that of real systems. Further, this method has potentially wider application in contexts where searching for abrupt change or ';action' in any hyperspace is desired.

Polysaccharide/Surfactant complexes at the air-water interface - effect of the charge density on interfacial and foaming behaviors.

PubMed

Ropers, M H; Novales, B; Boué, F; Axelos, M A V

2008-11-18

The binding of a cationic surfactant (hexadecyltrimethylammonium bromide, CTAB) to a negatively charged natural polysaccharide (pectin) at air-solution interfaces was investigated on single interfaces and in foams, versus the linear charge densities of the polysaccharide. Besides classical methods to investigate polymer/surfactant systems, we applied, for the first time concerning these systems, the analogy between the small angle neutron scattering by foams and the neutron reflectivity of films to measure in situ film thicknesses of foams. CTAB/pectin foam films are much thicker than the pure surfactant foam film but similar for high- and low-charged pectin/CTAB systems despite the difference in structure of complexes at interfaces. The improvement of the foam properties of CTAB bound to pectin is shown to be directly related to the formation of pectin-CTAB complexes at the air-water interface. However, in opposition to surface activity, there is no specific behavior for the highly charged pectin: foam properties depend mainly upon the bulk charge concentration, while the interfacial behavior is mainly governed by the charge density of pectin. For the highly charged pectin, specific cooperative effects between neighboring charged sites along the chain are thought to be involved in the higher surface activity of pectin/CTAB complexes. A more general behavior can be obtained at lower charge density either by using a low-charged pectin or by neutralizing the highly charged pectin in decreasing pH.

Criticality as a Set-Point for Adaptive Behavior in Neuromorphic Hardware

PubMed Central

Srinivasa, Narayan; Stepp, Nigel D.; Cruz-Albrecht, Jose

2015-01-01

Neuromorphic hardware are designed by drawing inspiration from biology to overcome limitations of current computer architectures while forging the development of a new class of autonomous systems that can exhibit adaptive behaviors. Several designs in the recent past are capable of emulating large scale networks but avoid complexity in network dynamics by minimizing the number of dynamic variables that are supported and tunable in hardware. We believe that this is due to the lack of a clear understanding of how to design self-tuning complex systems. It has been widely demonstrated that criticality appears to be the default state of the brain and manifests in the form of spontaneous scale-invariant cascades of neural activity. Experiment, theory and recent models have shown that neuronal networks at criticality demonstrate optimal information transfer, learning and information processing capabilities that affect behavior. In this perspective article, we argue that understanding how large scale neuromorphic electronics can be designed to enable emergent adaptive behavior will require an understanding of how networks emulated by such hardware can self-tune local parameters to maintain criticality as a set-point. We believe that such capability will enable the design of truly scalable intelligent systems using neuromorphic hardware that embrace complexity in network dynamics rather than avoiding it. PMID:26648839

Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

USGS Publications Warehouse

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-01-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology

NASA Astrophysics Data System (ADS)

Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

2005-11-01

Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

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

PubMed

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

2015-12-01

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

Origins of heterogeneity in Streptococcus mutans competence: interpreting an environment-sensitive signaling pathway

NASA Astrophysics Data System (ADS)

Hagen, Stephen J.; Son, Minjun

2017-02-01

Bacterial pathogens rely on chemical signaling and environmental cues to regulate disease-causing behavior in complex microenvironments. The human pathogen Streptococcus mutans employs a particularly complex signaling and sensing scheme to regulate genetic competence and other virulence behaviors in the oral biofilms it inhabits. Individual S. mutans cells make the decision to enter the competent state by integrating chemical and physical cues received from their microenvironment along with endogenously produced peptide signals. Studies at the single-cell level, using microfluidics to control the extracellular environment, provide physical insight into how the cells process these inputs to generate complex and often heterogeneous outputs. Fine changes in environmental stimuli can dramatically alter the behavior of the competence circuit. Small shifts in pH can switch the quorum sensing response on or off, while peptide-rich media appear to switch the output from a unimodal to a bimodal behavior. Therefore, depending on environmental cues, the quorum sensing circuitry can either synchronize virulence across the population, or initiate and amplify heterogeneity in that behavior. Much of this complex behavior can be understood within the framework of a quorum sensing system that can operate both as an intercellular signaling mechanism and intracellularly as a noisy bimodal switch.

Complexity analysis of dual-channel game model with different managers' business objectives

NASA Astrophysics Data System (ADS)

Li, Ting; Ma, Junhai

2015-01-01

This paper considers dual-channel game model with bounded rationality, using the theory of bifurcations of dynamical system. The business objectives of retailers are assumed to be different, which is closer to reality than previous studies. We study the local stable region of Nash equilibrium point and find that business objectives can expand the stable region and play an important role in price strategy. One interesting finding is that a fiercer competition tends to stabilize the Nash equilibrium. Simulation shows the complex behavior of two dimensional dynamic system, we find period doubling bifurcation and chaos phenomenon. We measure performances of the model in different period by using the index of average profit. The results show that unstable behavior in economic system is often an unfavorable outcome. So this paper discusses the application of adaptive adjustment mechanism when the model exhibits chaotic behavior and then allows the retailers to eliminate the negative effects.

Behavior of the gypsy moth life system model and development of synoptic model formulations

Treesearch

J. J. Colbert; Xu Rumei

1991-01-01

Aims of the research: The gypsy moth life system model (GMLSM) is a complex model which incorporates numerous components (both biotic and abiotic) and ecological processes. It is a detailed simulation model which has much biological reality. However, it has not yet been tested with life system data. For such complex models, evaluation and testing cannot be adequately...

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

NASA Technical Reports Server (NTRS)

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 Red-Light Running Prevention System Based on Artificial Neural Network and Vehicle Trajectory Data

PubMed Central

Li, Pengfei; Li, Yan; Guo, Xiucheng

2014-01-01

The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs) to approximate the complex driver behaviors during yellow and all-red clearance and serve as the basis of an innovative red-light running prevention system. The artificial neural network and vehicle trajectory are applied to identify the potential red-light runners. The ANN training time was also acceptable and its predicting accurate rate was over 80%. Lastly, a prototype red-light running prevention system with the trained ANN model was described. This new system can be directly retrofitted into the existing traffic signal systems. PMID:25435870

A red-light running prevention system based on artificial neural network and vehicle trajectory data.

PubMed

Li, Pengfei; Li, Yan; Guo, Xiucheng

2014-01-01

The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs) to approximate the complex driver behaviors during yellow and all-red clearance and serve as the basis of an innovative red-light running prevention system. The artificial neural network and vehicle trajectory are applied to identify the potential red-light runners. The ANN training time was also acceptable and its predicting accurate rate was over 80%. Lastly, a prototype red-light running prevention system with the trained ANN model was described. This new system can be directly retrofitted into the existing traffic signal systems.

Sensory integration regulating male courtship behavior in Drosophila.

PubMed

Krstic, Dimitrije; Boll, Werner; Noll, Markus

2009-01-01

The courtship behavior of Drosophila melanogaster serves as an excellent model system to study how complex innate behaviors are controlled by the nervous system. To understand how the underlying neural network controls this behavior, it is not sufficient to unravel its architecture, but also crucial to decipher its logic. By systematic analysis of how variations in sensory inputs alter the courtship behavior of a naïve male in the single-choice courtship paradigm, we derive a model describing the logic of the network that integrates the various sensory stimuli and elicits this complex innate behavior. This approach and the model derived from it distinguish (i) between initiation and maintenance of courtship, (ii) between courtship in daylight and in the dark, where the male uses a scanning strategy to retrieve the decamping female, and (iii) between courtship towards receptive virgin females and mature males. The last distinction demonstrates that sexual orientation of the courting male, in the absence of discriminatory visual cues, depends on the integration of gustatory and behavioral feedback inputs, but not on olfactory signals from the courted animal. The model will complement studies on the connectivity and intrinsic properties of the neurons forming the circuitry that regulates male courtship behavior.

Sociopathic behavior and dementia.

PubMed

Cipriani, Gabriele; Borin, Gemma; Vedovello, Marcella; Di Fiorino, Andrea; Nuti, Angelo

2013-06-01

The maintenance of appropriate social behavior is a very complex process with many contributing factors. Social and moral judgments rely on the proper functioning of neural circuits concerned with complex cognitive and emotional processes. Damage to these systems may lead to distinct social behavior abnormalities. When patients present with dysmoral behavior for the first time, as a change from a prior pervasive pattern of behavior, clinicians need to consider a possible, causative brain disorder. The aim is to explore sociopathy as a manifestation of dementia. We searched electronic databases and key journals for original research and review articles on sociopathy in demented patients using the search terms "sociopathy, acquired sociopathy, sociopathic behavior, dementia, and personality". In conclusion, dementia onset may be heralded by changes in personality including alteration in social interpersonal behavior, personal regulation, and empathy. The sociopathy of dementia differs from antisocial/psychopathic personality disorders.

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

ERIC Educational Resources Information Center

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

2012-01-01

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

Complex adaptive systems and game theory: An unlikely union

USGS Publications Warehouse

Hadzikadic, M.; Carmichael, T.; Curtin, C.

2010-01-01

A Complex Adaptive System is a collection of autonomous, heterogeneous agents, whose behavior is defined with a limited number of rules. A Game Theory is a mathematical construct that assumes a small number of rational players who have a limited number of actions or strategies available to them. The CAS method has the potential to alleviate some of the shortcomings of GT. On the other hand, CAS researchers are always looking for a realistic way to define interactions among agents. GT offers an attractive option for defining the rules of such interactions in a way that is both potentially consistent with observed real-world behavior and subject to mathematical interpretation. This article reports on the results of an effort to build a CAS system that utilizes GT for determining the actions of individual agents. ?? 2009 Wiley Periodicals, Inc. Complexity, 16,24-42, 2010.

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

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

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

2014-03-15

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

Translations on USSR Science and Technology, Biomedical and Behavioral Sciences, Number 15

DTIC Science & Technology

1977-11-16

processed. By applying systems theory to synthesis of complex man-machine systems we form ergatic organisms which not only have external and internal...without exception (and this is extremely important to emphasize) as a complex , integral formation, which through various traditions has acquired a...and outputs of the whole, which has a complex internal organization and structure, which we can no longer ignore in our analysis. Thus analysis and

Ideal gas behavior of a strongly coupled complex (dusty) plasma.

PubMed

Oxtoby, Neil P; Griffith, Elias J; Durniak, Céline; Ralph, Jason F; Samsonov, Dmitry

2013-07-05

In a laboratory, a two-dimensional complex (dusty) plasma consists of a low-density ionized gas containing a confined suspension of Yukawa-coupled plastic microspheres. For an initial crystal-like form, we report ideal gas behavior in this strongly coupled system during shock-wave experiments. This evidence supports the use of the ideal gas law as the equation of state for soft crystals such as those formed by dusty plasmas.

Lifestyle and Clinical Health Behaviors and PSA Tests

ERIC Educational Resources Information Center

Norris, Cynthia; McFall, Stephanie

2006-01-01

This study assessed the association of lifestyle and clinical health behaviors with prostate specific antigen (PSA) tests. The study used cross-sectional data from the 2002 Behavioral Risk Factor Surveillance System (BRFSS). We used Stata 8.0 to take into account the complex sample design in analyses. Both lifestyle and clinical health behaviors…

Evaluating Water Demand Using Agent-Based Modeling

NASA Astrophysics Data System (ADS)

Lowry, T. S.

2004-12-01

The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage based on its own condition and the condition of the world around it. For example, residential agents can make decisions to convert to or from xeriscaping and/or low-flow appliances based on policy implementation, economic status, weather, and climatic conditions. Agricultural agents may vary their usage by making decisions on crop distribution and irrigation design. Preliminary results show that water usage can be highly irrational under certain conditions. Results also identify sub-sectors within each group that have the highest influence on ensemble group behavior, providing a means for policy makers to target their efforts. Finally, the model is able to predict the impact of low-probability, high-impact events such as catastrophic denial of service due to natural and/or man-made events.

Simulating Fire Disturbance and Plant Mortality Using Antecedent Eco-hydrological Conditions to Inform a Physically Based Combustion Model

NASA Astrophysics Data System (ADS)

Atchley, A. L.; Linn, R.; Middleton, R. S.; Runde, I.; Coon, E.; Michaletz, S. T.

2016-12-01

Wildfire is a complex agent of change that both affects and depends on eco-hydrological systems, thereby constituting a tightly linked system of disturbances and eco-hydrological conditions. For example, structure, build-up, and moisture content of fuel are dependent on eco-hydrological regimes, which impacts fire spread and intensity. Fire behavior, on the other hand, determines the severity and extent of eco-hydrological disturbance, often resulting in a mosaic of untouched, stressed, damaged, or completely destroyed vegetation within the fire perimeter. This in turn drives new eco-hydrological system behavior. The cycles of disturbance and recovery present a complex evolving system with many unknowns especially in the face of climate change that has implications for fire risk, water supply, and forest composition. Physically-based numerical experiments that attempt to capture the complex linkages between eco-hydrological regimes that affect fire behavior and the echo-hydrological response from those fire disturbances help build the understanding required to project how fire disturbance and eco-hydrological conditions coevolve over time. Here we explore the use of FIRETEC—a physically-based 3D combustion model that solves conservation of mass, momentum, energy, and chemical species—to resolve fire spread over complex terrain and fuel structures. Uniquely, we couple a physically-based plant mortality model with FIRETEC and examine the resultant hydrologic impact. In this proof of concept demonstration we spatially distribute fuel structure and moisture content based on the eco-hydrological condition to use as input for FIRETEC. The fire behavior simulation then produces localized burn severity and heat injures which are used as input to a spatially-informed plant mortality model. Ultimately we demonstrate the applicability of physically-based models to explore integrated disturbance and eco-hydrologic response to wildfire behavior and specifically map how fire spread and intensity is affect by the antecedent eco-hydrological condition, which then affects the resulting tree mortality patterns.

Consequences of nonclassical measurement for the algorithmic description of continuous dynamical systems

NASA Technical Reports Server (NTRS)

Fields, Chris

1989-01-01

Continuous dynamical systems intuitively seem capable of more complex behavior than discrete systems. If analyzed in the framework of the traditional theory of computation, a continuous dynamical system with countably many quasistable states has at least the computational power of a universal Turing machine. Such an analysis assumes, however, the classical notion of measurement. If measurement is viewed nonclassically, a continuous dynamical system cannot, even in principle, exhibit behavior that cannot be simulated by a universal Turing machine.

Consequences of nonclassical measurement for the algorithmic description of continuous dynamical systems

NASA Technical Reports Server (NTRS)

Fields, Chris

1989-01-01

Continuous dynamical systems intuitively seem capable of more complex behavior than discrete systems. If analyzed in the framework of the traditional theory of computation, a continuous dynamical system with countablely many quasistable states has at least the computational power of a universal Turing machine. Such an analyses assumes, however, the classical notion of measurement. If measurement is viewed nonclassically, a continuous dynamical system cannot, even in principle, exhibit behavior that cannot be simulated by a universal Turing machine.

Emerging role for corticotropin releasing factor signaling in the bed nucleus of the stria terminalis at the intersection of stress and reward.

PubMed

Silberman, Yuval; Winder, Danny G

2013-01-01

Stress and anxiety play an important role in the development and maintenance of drug and alcohol addiction. The bed nucleus of the stria terminalis (BNST), a brain region involved in the production of long-term stress-related behaviors, plays an important role in animal models of relapse, such as reinstatement to previously extinguished drug-seeking behaviors. While a number of neurotransmitter systems have been suggested to play a role in these behaviors, recent evidence points to the neuropeptide corticotropin releasing factor (CRF) as being critically important in BNST-mediated reinstatement behaviors. Although numerous studies indicate that the BNST is a complex brain region with multiple afferent and efferent systems and a variety of cell types, there has only been limited work to determine how CRF modulates this complex neuronal system at the circuit level. Recent work from our lab and others have begun to unravel these BNST neurocircuits and explore their roles in CRF-related reinstatement behaviors. This review will examine the role of CRF signaling in drug addiction and reinstatement with an emphasis on critical neurocircuitry within the BNST that may offer new insights into treatments for addiction.

1998 Complex Systems Summer School

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

NONE

1998-12-15

For the past eleven years a group of institutes, centers, and universities throughout the country have sponsored a summer school in Santa Fe, New Mexico as part of an interdisciplinary effort to promote the understanding of complex systems. The goal of these summer schools is to provide graduate students, postdoctoral fellows and active research scientists with an introduction to the study of complex behavior in mathematical, physical, and living systems. The Center for Nonlinear Studies supported the eleventh in this series of highly successful schools in Santa Fe in June, 1998.

Directed clustering coefficient as a measure of systemic risk in complex banking networks

NASA Astrophysics Data System (ADS)

Tabak, Benjamin M.; Takami, Marcelo; Rocha, Jadson M. C.; Cajueiro, Daniel O.; Souza, Sergio R. S.

2014-01-01

Recent literature has focused on the study of systemic risk in complex networks. It is clear now, after the crisis of 2008, that the aggregate behavior of the interaction among agents is not straightforward and it is very difficult to predict. Contributing to this debate, this paper shows that the directed clustering coefficient may be used as a measure of systemic risk in complex networks. Furthermore, using data from the Brazilian interbank network, we show that the directed clustering coefficient is negatively correlated with domestic interest rates.

[The evolution of human cultural behavior: notes on Darwinism and complexity].

PubMed

Peric, Mikael; Murrieta, Rui Sérgio Sereni

2015-12-01

The article analyzes three schools that can be understood as central in studies of the evolution of human behavior within the paradigm of evolution by natural selection: human behavioral ecology (HBE), evolutionary psychology, and dual inheritance. These three streams of thought are used to depict the Darwinist landscape and pinpoint its strong suits and limitations. Theoretical gaps were identified that seem to reduce these schools' ability to account for the diversity of human evolutionary behavior. Their weak points include issues related to the concept of reproductive success, types of adaptation, and targets of selection. An interdisciplinary approach is proposed as the solution to this dilemma, where complex adaptive systems would serve as a source.

ASSIST user manual

NASA Technical Reports Server (NTRS)

Johnson, Sally C.; Boerschlein, David P.

1995-01-01

Semi-Markov models can be used to analyze the reliability of virtually any fault-tolerant system. However, the process of delineating all the states and transitions in a complex system model can be devastatingly tedious and error prone. The Abstract Semi-Markov Specification Interface to the SURE Tool (ASSIST) computer program allows the user to describe the semi-Markov model in a high-level language. Instead of listing the individual model states, the user specifies the rules governing the behavior of the system, and these are used to generate the model automatically. A few statements in the abstract language can describe a very large, complex model. Because no assumptions are made about the system being modeled, ASSIST can be used to generate models describing the behavior of any system. The ASSIST program and its input language are described and illustrated by examples.

Prior activity of olfactory receptor neurons is required for proper sensory processing and behavior in Drosophila larvae.

PubMed

Utashiro, Nao; Williams, Claire R; Parrish, Jay Z; Emoto, Kazuo

2018-06-05

Animal responses to their environment rely on activation of sensory neurons by external stimuli. In many sensory systems, however, neurons display basal activity prior to the external stimuli. This prior activity is thought to modulate neural functions, yet its impact on animal behavior remains elusive. Here, we reveal a potential role for prior activity in olfactory receptor neurons (ORNs) in shaping larval olfactory behavior. We show that prior activity in larval ORNs is mediated by the olfactory receptor complex (OR complex). Mutations of Orco, an odorant co-receptor required for OR complex function, cause reduced attractive behavior in response to optogenetic activation of ORNs. Calcium imaging reveals that Orco mutant ORNs fully respond to optogenetic stimulation but exhibit altered temporal patterns of neural responses. These findings together suggest a critical role for prior activity in information processing upon ORN activation in Drosophila larvae, which in turn contributes to olfactory behavior control.

Exsolution as an Example of Complex-System Behavior

NASA Astrophysics Data System (ADS)

Mogk, D. W.; Dutrow, B. L.

2010-12-01

Exsolution in minerals is an important process that occurs in a wide range of mineral groups (e.g. alkali feldspars, pyroxenes, amphiboles, carbonates, oxides, sulfides) in response to changing physical conditions. Exsolution describes a physical process in which a mineral with an initially homogeneous solid solution separates into at least two distinct derivative minerals of disparate composition and is typically interpreted as the product of unmixing in response to lattice strain during slow cooling. Such a process is typically taught in introductory mineralogy and petrology courses, in part because exsolution textures can be readily observed in hand sample or thin section. Exsolution is typically represented on equilibrium binary phase diagrams (T-X), and compositions of the unmixed products can be used in geothermobarometry to calculate temperatures and pressures of initial equilibration or compositions of the unmixed products. Although central to course content, traditional approaches to teaching exsolution are largely descriptive, and do not address the underlying principles that drive this phenomenon: that is, dissipation of energy results in segregating and self-organizing behavior of the system. This process exemplifies complex-system behavior. We use perthite formation (i.e. exsolution in the alkali feldspar system) in a series of scaffolded exercises to teach and more completely demonstrate complex-system behavior. These exercises include the use of: 1) hand samples and a series of optical and TEM photomicrographs to display the scale invariance of perthite textures; 2) a puzzle activity in which a chessboard is used as an analog model of atomic positions and nickels and pennies are used to represent individual atoms (Na and K respectively); sequential moves to optimize contacts with similar coins approximates minimization of lattice energies and reveals a power-law relationship as the system becomes increasingly segregated as a function of time to create exsolution textures; 3) the NetLogo computer modeling program to demonstrate segregating behavior; 4) visualizations based on the binary alkali feldspar phase diagram to demonstrate changes to the state of the system over a range of temperatures, and 5) a series of follow-on thought questions. An interesting apparent paradox that our students should consider concerns the flow of mass and energy in natural systems. Commonly, we simply note that mass and energy typically flow down natural gradients (thermal, chemical potential) to attain a homogeneous equilibrium state; however, exsolution produces a segregated state of the system in the lowest energy configuration. Why? Complex-system behavior can be discovered in a wide range of geological phenomena such as exsolution, and could be explicitly identified throughout the geoscience curriculum as a mechanism to teach about interacting systems.

Stochastic model simulation using Kronecker product analysis and Zassenhaus formula approximation.

PubMed

Caglar, Mehmet Umut; Pal, Ranadip

2013-01-01

Probabilistic Models are regularly applied in Genetic Regulatory Network modeling to capture the stochastic behavior observed in the generation of biological entities such as mRNA or proteins. Several approaches including Stochastic Master Equations and Probabilistic Boolean Networks have been proposed to model the stochastic behavior in genetic regulatory networks. It is generally accepted that Stochastic Master Equation is a fundamental model that can describe the system being investigated in fine detail, but the application of this model is computationally enormously expensive. On the other hand, Probabilistic Boolean Network captures only the coarse-scale stochastic properties of the system without modeling the detailed interactions. We propose a new approximation of the stochastic master equation model that is able to capture the finer details of the modeled system including bistabilities and oscillatory behavior, and yet has a significantly lower computational complexity. In this new method, we represent the system using tensors and derive an identity to exploit the sparse connectivity of regulatory targets for complexity reduction. The algorithm involves an approximation based on Zassenhaus formula to represent the exponential of a sum of matrices as product of matrices. We derive upper bounds on the expected error of the proposed model distribution as compared to the stochastic master equation model distribution. Simulation results of the application of the model to four different biological benchmark systems illustrate performance comparable to detailed stochastic master equation models but with considerably lower computational complexity. The results also demonstrate the reduced complexity of the new approach as compared to commonly used Stochastic Simulation Algorithm for equivalent accuracy.

The application of sensitivity analysis to models of large scale physiological systems

NASA Technical Reports Server (NTRS)

Leonard, J. I.

1974-01-01

A survey of the literature of sensitivity analysis as it applies to biological systems is reported as well as a brief development of sensitivity theory. A simple population model and a more complex thermoregulatory model illustrate the investigatory techniques and interpretation of parameter sensitivity analysis. The role of sensitivity analysis in validating and verifying models, and in identifying relative parameter influence in estimating errors in model behavior due to uncertainty in input data is presented. This analysis is valuable to the simulationist and the experimentalist in allocating resources for data collection. A method for reducing highly complex, nonlinear models to simple linear algebraic models that could be useful for making rapid, first order calculations of system behavior is presented.

VBOT: Motivating computational and complex systems fluencies with constructionist virtual/physical robotics

NASA Astrophysics Data System (ADS)

Berland, Matthew W.

As scientists use the tools of computational and complex systems theory to broaden science perspectives (e.g., Bar-Yam, 1997; Holland, 1995; Wolfram, 2002), so can middle-school students broaden their perspectives using appropriate tools. The goals of this dissertation project are to build, study, evaluate, and compare activities designed to foster both computational and complex systems fluencies through collaborative constructionist virtual and physical robotics. In these activities, each student builds an agent (e.g., a robot-bird) that must interact with fellow students' agents to generate a complex aggregate (e.g., a flock of robot-birds) in a participatory simulation environment (Wilensky & Stroup, 1999a). In a participatory simulation, students collaborate by acting in a common space, teaching each other, and discussing content with one another. As a result, the students improve both their computational fluency and their complex systems fluency, where fluency is defined as the ability to both consume and produce relevant content (DiSessa, 2000). To date, several systems have been designed to foster computational and complex systems fluencies through computer programming and collaborative play (e.g., Hancock, 2003; Wilensky & Stroup, 1999b); this study suggests that, by supporting the relevant fluencies through collaborative play, they become mutually reinforcing. In this work, I will present both the design of the VBOT virtual/physical constructionist robotics learning environment and a comparative study of student interaction with the virtual and physical environments across four middle-school classrooms, focusing on the contrast in systems perspectives differently afforded by the two environments. In particular, I found that while performance gains were similar overall, the physical environment supported agent perspectives on aggregate behavior, and the virtual environment supported aggregate perspectives on agent behavior. The primary research questions are: (1) What are the relative affordances of virtual and physical constructionist robotics systems towards computational and complex systems fluencies? (2) What can middle school students learn using computational/complex systems learning environments in a collaborative setting? (3) In what ways are these environments and activities effective in teaching students computational and complex systems fluencies?

Observe, simplify, titrate, model, and synthesize: A paradigm for analyzing behavior

PubMed Central

Alberts, Jeffrey R.

2013-01-01

Phenomena in behavior and their underlying neural mechanisms are exquisitely complex problems. Infrequently do we reflect on our basic strategies of investigation and analysis, or formally confront the actual challenges of achieving an understanding of the phenomena that inspire research. Philip Teitelbaum is distinct in his elegant approaches to understanding behavioral phenomena and their associated neural processes. He also articulated his views on effective approaches to scientific analyses of brain and behavior, his vision of how behavior and the nervous system are patterned, and what constitutes basic understanding. His rubrics involve careful observation and description of behavior, simplification of the complexity, analysis of elements, and re-integration through different forms of synthesis. Research on the development of huddling behavior by individual and groups of rats is reviewed in a context of Teitelbaum’s rubrics of research, with the goal of appreciating his broad and positive influence on the scientific community. PMID:22481081

Interaction of mathematical modeling and social and behavioral HIV/AIDS research.

PubMed

Cassels, Susan; Goodreau, Steven M

2011-03-01

HIV is transmitted within complex biobehavioral systems. Mathematical modeling can provide insight to complex population-level outcomes of various behaviors measured at an individual level. HIV models in the social and behavioral sciences can be categorized in a number of ways; here, we consider two classes of applications common in the field generally, and in the past year in particular: those models that explore significant behavioral determinants of HIV disparities within and between populations; and those models that seek to evaluate the potential impact of specific social and behavioral interventions. We discuss two overarching issues we see in the field: the need to further systematize effectiveness models of behavioral interventions, and the need for increasing investigation of the use of behavioral data in epidemic models. We believe that a recent initiative by the National Institutes of Health will qualitatively change the relationships between epidemic modeling and sociobehavioral prevention research in the coming years.

Towards representing human behavior and decision making in Earth system models - an overview of techniques and approaches

NASA Astrophysics Data System (ADS)

Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, Jobst

2017-11-01

Today, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales.

Variations of trends of indicators describing complex systems: Change of scaling precursory to extreme events

NASA Astrophysics Data System (ADS)

Keilis-Borok, V. I.; Soloviev, A. A.

2010-09-01

Socioeconomic and natural complex systems persistently generate extreme events also known as disasters, crises, or critical transitions. Here we analyze patterns of background activity preceding extreme events in four complex systems: economic recessions, surges in homicides in a megacity, magnetic storms, and strong earthquakes. We use as a starting point the indicators describing the system's behavior and identify changes in an indicator's trend. Those changes constitute our background events (BEs). We demonstrate a premonitory pattern common to all four systems considered: relatively large magnitude BEs become more frequent before extreme event. A premonitory change of scaling has been found in various models and observations. Here we demonstrate this change in scaling of uniformly defined BEs in four real complex systems, their enormous differences notwithstanding.

Stochastic simulation of multiscale complex systems with PISKaS: A rule-based approach.

PubMed

Perez-Acle, Tomas; Fuenzalida, Ignacio; Martin, Alberto J M; Santibañez, Rodrigo; Avaria, Rodrigo; Bernardin, Alejandro; Bustos, Alvaro M; Garrido, Daniel; Dushoff, Jonathan; Liu, James H

2018-03-29

Computational simulation is a widely employed methodology to study the dynamic behavior of complex systems. Although common approaches are based either on ordinary differential equations or stochastic differential equations, these techniques make several assumptions which, when it comes to biological processes, could often lead to unrealistic models. Among others, model approaches based on differential equations entangle kinetics and causality, failing when complexity increases, separating knowledge from models, and assuming that the average behavior of the population encompasses any individual deviation. To overcome these limitations, simulations based on the Stochastic Simulation Algorithm (SSA) appear as a suitable approach to model complex biological systems. In this work, we review three different models executed in PISKaS: a rule-based framework to produce multiscale stochastic simulations of complex systems. These models span multiple time and spatial scales ranging from gene regulation up to Game Theory. In the first example, we describe a model of the core regulatory network of gene expression in Escherichia coli highlighting the continuous model improvement capacities of PISKaS. The second example describes a hypothetical outbreak of the Ebola virus occurring in a compartmentalized environment resembling cities and highways. Finally, in the last example, we illustrate a stochastic model for the prisoner's dilemma; a common approach from social sciences describing complex interactions involving trust within human populations. As whole, these models demonstrate the capabilities of PISKaS providing fertile scenarios where to explore the dynamics of complex systems. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2016-01-01

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

You Can't Get There From Here! Problems and Potential Solutions in Developing New Classes of Complex Systems

NASA Technical Reports Server (NTRS)

Hinchey, Michael G.; Rash, James L.; Truszkowski, Walter F.; Rouff, Christopher A.; Sterritt, Roy

2005-01-01

The explosion of capabilities and new products within the sphere of Information Technology (IT) has fostered widespread, overly optimistic opinions regarding the industry, based on common but unjustified assumptions of quality and correctness of software. These assumptions are encouraged by software producers and vendors, who at this late date have not succeeded in finding a way to overcome the lack of an automated, mathematically sound way to develop correct systems from requirements. NASA faces this dilemma as it envisages advanced mission concepts that involve large swarms of small spacecraft that will engage cooperatively to acheve science goals. Such missions entail levels of complexity that beg for new methods for system development far beyond today's methods, which are inadequate for ensuring correct behavior of large numbers of interacting intelligent mission elements. New system development techniques recently devised through NASA-led research will offer some innovative approaches to achieving correctness in complex system development, including autonomous swarm missions that exhibit emergent behavior, as well as general software products created by the computing industry.

A review of tin oxide-based catalytic systems: Preparation, characterization and catalytic behavior

NASA Technical Reports Server (NTRS)

Hoflund, Gar B.

1987-01-01

This paper reviews the important aspects of the preparation, characterization and catalytic behavior of tin oxide-based catalytic systems including doped tin oxide, mixed oxides which contain tin oxide, Pt supported on tin oxide and Pt/Sn supported on alumina. These systems have a broad range of applications and are continually increasing in importance. However, due to their complex nature, much remains to be understood concerning how they function catalytically.

Statistical inference of empirical constituents in partitioned analysis from integral-effect experiments: An application in thermo-mechanical coupling

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

Stevens, Garrison N.; Atamturktur, Sez; Brown, D. Andrew

Rapid advancements in parallel computing over the last two decades have enabled simulations of complex, coupled systems through partitioning. In partitioned analysis, independently developed constituent models communicate, representing dependencies between multiple physical phenomena that occur in the full system. Figure 1 schematically demonstrates a coupled system with two constituent models, each resolving different physical behavior. In this figure, the constituent model, denoted as the “consumer,” relies upon some input parameter that is being provided by the constituent model acting as a “feeder”. The role of the feeder model is to map operating conditions (i.e. those that are stimulating the process)more » to consumer inputs, thus providing functional inputs to the consumer model*. Problems arise if the feeder model cannot be built–a challenge that is prevalent for highly complex systems in extreme operational conditions that push the limits of our understanding of underlying physical behavior. Often, these are also the situations where separate-effect experiments isolating the physical phenomena are not available; meaning that experimentally determining the unknown constituent behavior is not possible (Bauer and Holland, 1995; Unal et al., 2013), and that integral-effect experiments that reflect the behavior of the complete system tend to be the only available observations. In this paper, the authors advocate for the usefulness of integral-effect experiments in furthering a model developer’s knowledge of the physics principles governing the system behavior of interest.« less

Statistical inference of empirical constituents in partitioned analysis from integral-effect experiments: An application in thermo-mechanical coupling

DOE PAGES

Stevens, Garrison N.; Atamturktur, Sez; Brown, D. Andrew; ...

2018-04-16

Rapid advancements in parallel computing over the last two decades have enabled simulations of complex, coupled systems through partitioning. In partitioned analysis, independently developed constituent models communicate, representing dependencies between multiple physical phenomena that occur in the full system. Figure 1 schematically demonstrates a coupled system with two constituent models, each resolving different physical behavior. In this figure, the constituent model, denoted as the “consumer,” relies upon some input parameter that is being provided by the constituent model acting as a “feeder”. The role of the feeder model is to map operating conditions (i.e. those that are stimulating the process)more » to consumer inputs, thus providing functional inputs to the consumer model*. Problems arise if the feeder model cannot be built–a challenge that is prevalent for highly complex systems in extreme operational conditions that push the limits of our understanding of underlying physical behavior. Often, these are also the situations where separate-effect experiments isolating the physical phenomena are not available; meaning that experimentally determining the unknown constituent behavior is not possible (Bauer and Holland, 1995; Unal et al., 2013), and that integral-effect experiments that reflect the behavior of the complete system tend to be the only available observations. In this paper, the authors advocate for the usefulness of integral-effect experiments in furthering a model developer’s knowledge of the physics principles governing the system behavior of interest.« less

Aeropropulsion 1987. Session 2: Aeropropulsion Structures Research

NASA Technical Reports Server (NTRS)

1987-01-01

Aeropropulsion systems present unique problems to the structural engineer. The extremes in operating temperatures, rotational effects, and behaviors of advanced material systems combine into complexities that require advances in many scientific disciplines involved in structural analysis and design procedures. This session provides an overview of the complexities of aeropropulsion structures and the theoretical, computational, and experimental research conducted to achieve the needed advances.

Dynamical singularities for complex initial conditions and the motion at a real separatrix.

PubMed

Shnerb, Tamar; Kay, K G

2006-04-01

This work investigates singularities occurring at finite real times in the classical dynamics of one-dimensional double-well systems with complex initial conditions. The objective is to understand the relationship between these singularities and the behavior of the systems for real initial conditions. An analytical treatment establishes that the dynamics of a quartic double well system possesses a doubly infinite sequence of singularities. These are associated with initial conditions that converge to those for the real separatrix as the singularity time becomes infinite. This confluence of singularities is shown to lead to the unstable behavior that characterizes the real motion at the separatrix. Numerical calculations confirm the existence of a large number of singularities converging to the separatrix for this and two additional double-well systems. The approach of singularities to the real axis is of particular interest since such behavior has been related to the formation of chaos in nonintegrable systems. The properties of the singular trajectories which cause this convergence to the separatrix are identified. The hyperbolic fixed point corresponding to the potential energy maximum, responsible for the characteristic motion at a separatrix, also plays a critical role in the formation of the complex singularities by delaying trajectories and then deflecting them into asymptotic regions of space from where they are directly repelled to infinity in a finite time.

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

PubMed

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

2013-01-01

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

On Chaotic and Hyperchaotic Complex Nonlinear Dynamical Systems

NASA Astrophysics Data System (ADS)

Mahmoud, Gamal M.

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

Applications of complex systems theory in nursing education, research, and practice.

PubMed

Clancy, Thomas R; Effken, Judith A; Pesut, Daniel

2008-01-01

The clinical and administrative processes in today's healthcare environment are becoming increasingly complex. Multiple providers, new technology, competition, and the growing ubiquity of information all contribute to the notion of health care as a complex system. A complex system (CS) is characterized by a highly connected network of entities (e.g., physical objects, people or groups of people) from which higher order behavior emerges. Research in the transdisciplinary field of CS has focused on the use of computational modeling and simulation as a methodology for analyzing CS behavior. The creation of virtual worlds through computer simulation allows researchers to analyze multiple variables simultaneously and begin to understand behaviors that are common regardless of the discipline. The application of CS principles, mediated through computer simulation, informs nursing practice of the benefits and drawbacks of new procedures, protocols and practices before having to actually implement them. The inclusion of new computational tools and their applications in nursing education is also gaining attention. For example, education in CSs and applied computational applications has been endorsed by The Institute of Medicine, the American Organization of Nurse Executives and the American Association of Colleges of Nursing as essential training of nurse leaders. The purpose of this article is to review current research literature regarding CS science within the context of expert practice and implications for the education of nurse leadership roles. The article focuses on 3 broad areas: CS defined, literature review and exemplars from CS research and applications of CS theory in nursing leadership education. The article also highlights the key role nursing informaticists play in integrating emerging computational tools in the analysis of complex nursing systems.

Looking for complexity in quantitative semiology of frontal and temporal lobe seizures using neuroethology and graph theory.

PubMed

Bertti, Poliana; Tejada, Julian; Martins, Ana Paula Pinheiro; Dal-Cól, Maria Luiza Cleto; Terra, Vera Cristina; de Oliveira, José Antônio Cortes; Velasco, Tonicarlo Rodrigues; Sakamoto, Américo Ceiki; Garcia-Cairasco, Norberto

2014-09-01

Epileptic syndromes and seizures are the expression of complex brain systems. Because no analysis of complexity has been applied to epileptic seizure semiology, our goal was to apply neuroethology and graph analysis to the study of the complexity of behavioral manifestations of epileptic seizures in human frontal lobe epilepsy (FLE) and temporal lobe epilepsy (TLE). We analyzed the video recordings of 120 seizures of 18 patients with FLE and 28 seizures of 28 patients with TLE. All patients were seizure-free >1 year after surgery (Engel Class I). All patients' behavioral sequences were analyzed by means of a glossary containing all behaviors and analyzed for neuroethology (Ethomatic software). The same series were used for graph analysis (CYTOSCAPE). Behaviors, displayed as nodes, were connected by edges to other nodes according to their temporal sequence of appearance. Using neuroethology analysis, we confirmed data in the literature such as in FLE: brief/frequent seizures, complex motor behaviors, head and eye version, unilateral/bilateral tonic posturing, speech arrest, vocalization, and rapid postictal recovery and in the case of TLE: presence of epigastric aura, lateralized dystonias, impairment of consciousness/speech during ictal and postictal periods, and development of secondary generalization. Using graph analysis metrics of FLE and TLE confirmed data from flowcharts. However, because of the algorithms we used, they highlighted more powerfully the connectivity and complex associations among behaviors in a quite selective manner, depending on the origin of the seizures. The algorithms we used are commonly employed to track brain connectivity from EEG and MRI sources, which makes our study very promising for future studies of complexity in this field. Copyright © 2014 Elsevier Inc. All rights reserved.

Searching for simplicity in the analysis of neurons and behavior

PubMed Central

Stephens, Greg J.; Osborne, Leslie C.; Bialek, William

2011-01-01

What fascinates us about animal behavior is its richness and complexity, but understanding behavior and its neural basis requires a simpler description. Traditionally, simplification has been imposed by training animals to engage in a limited set of behaviors, by hand scoring behaviors into discrete classes, or by limiting the sensory experience of the organism. An alternative is to ask whether we can search through the dynamics of natural behaviors to find explicit evidence that these behaviors are simpler than they might have been. We review two mathematical approaches to simplification, dimensionality reduction and the maximum entropy method, and we draw on examples from different levels of biological organization, from the crawling behavior of Caenorhabditis elegans to the control of smooth pursuit eye movements in primates, and from the coding of natural scenes by networks of neurons in the retina to the rules of English spelling. In each case, we argue that the explicit search for simplicity uncovers new and unexpected features of the biological system and that the evidence for simplification gives us a language with which to phrase new questions for the next generation of experiments. The fact that similar mathematical structures succeed in taming the complexity of very different biological systems hints that there is something more general to be discovered. PMID:21383186

Bioreactivity: Studies on a Simple Brain Stem Reflex in Behaving Animals

DTIC Science & Technology

1990-08-10

problem in attempting to understand complex physiological processes, such as brain neuromodulation , or complex behavioral processes, such as arousal...containing only one synapse in brain, and receives dense inputs from two neurochemical systems important in neuromodulation and arousal. Initial

Bioreactivity: Studies on a Simple Brain Stem Reflex in Behaving Animals

DTIC Science & Technology

1990-01-04

attempting to understand complex physiological processes, such as brain neuromodulation , or complex behavioral processes, such as arousal, is finding a...one synapse in brain, and receives dense inputs from two neurochemical systems important in neuromodulation and arousal. Initial pharmacologic studies

A cellular automation model accounting for bicycle's group behavior

NASA Astrophysics Data System (ADS)

Tang, Tie-Qiao; Rui, Ying-Xu; Zhang, Jian; Shang, Hua-Yan

2018-02-01

Recently, bicycle has become an important traffic tool in China, again. Due to the merits of bicycle, the group behavior widely exists in urban traffic system. However, little effort has been made to explore the impacts of the group behavior on bicycle flow. In this paper, we propose a CA (cellular automaton) model with group behavior to explore the complex traffic phenomena caused by shoulder group behavior and following group behavior on an open road. The numerical results illustrate that the proposed model can qualitatively describe the impacts of the two kinds of group behaviors on bicycle flow and that the effects are related to the mode and size of group behaviors. The results can help us to better understand the impacts of the bicycle's group behaviors on urban traffic system and effectively control the bicycle's group behavior.

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

PubMed

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

2016-03-01

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

State-Based Network Intrusion Detection Systems for SCADA Protocols: A Proof of Concept

NASA Astrophysics Data System (ADS)

Carcano, Andrea; Fovino, Igor Nai; Masera, Marcelo; Trombetta, Alberto

We present a novel Intrusion Detection System able to detect complex attacks to SCADA systems. By complex attack, we mean a set of commands (carried in Modbus packets) that, while licit when considered in isolation on a single-packet basis, interfere with the correct behavior of the system. The proposed IDS detects such attacks thanks to an internal representation of the controlled SCADA system and a corresponding rule language, powerful enough to express the system's critical states. Furthermore, we detail the implementation and provide experimental comparative results.

Education and Training in the Social, Behavioral, and Economic Sciences: A Plan of Action. A Report to the National Science Foundation.

ERIC Educational Resources Information Center

Levine, Felice J.; Abler, Ronald F.; Rosich, Katherine J.

2004-01-01

Over the last quarter of a century, the world has undergone rapid change. Almost every aspect of human life is more complex and interdependent, requiring knowledge of human and social systems as well as physical and biological systems. The social, behavioral, and economic (SBE) sciences contribute penetrating insights on such issues as the causes…

UAV Swarm Mission Planning Development Using Evolutionary Algorithms - Part I

DTIC Science & Technology

2008-05-01

desired behaviors in autonomous vehicles is a difficult problem at best and in general prob- ably impossible to completely resolve in complex dynamic...associated behaviors. Various techniques inspired by biological self-organized systems as found in forging insects and flocking birds, revolve around...swarms of heterogeneous vehicles in a distributed simulation system with animated graphics. Statistical measurements and observations indicate that bio

Electromagnetic game modeling through Tensor Analysis of Networks and Game Theory

NASA Astrophysics Data System (ADS)

Maurice, Olivier; Reineix, Alain; Lalléchère, Sébastien

2014-10-01

A complex system involves events coming from natural behaviors. Whatever is the complicated face of machines, they are still far from the complexity of natural systems. Currently, economy is one of the rare science trying to find out some ways to model human behavior. These attempts involve game theory and psychology. Our purpose is to develop a formalism able to take in charge both game and hardware modeling. We first present the Tensorial Analysis of Networks, used for the material part of the system. Then, we detail the mathematical objects defined in order to describe the evolution of the system and its gaming side. To illustrate the discussion we consider the case of a drone whose electronic can be disturbed by a radar field, but this drone must fly as near as possible close to this radar.

Occupational safety and health as an element of a complex compensation system evaluation within an organization.

PubMed

Beck-Krala, Ewa; Klimkiewicz, Katarzyna

2016-12-01

Occupational safety and health (OSH) plays a significant role in today's organizations, because it helps in attracting and retaining employees as well as molding their attitudes and behaviors at work. This is why the issue of OSH is stressed in a comprehensive approach to employee rewards: the total reward concept. This article explains how OSH may be included in a complex evaluation process of the compensation system. Although the literature on the effectiveness of employee compensation refers mainly to financial and non-financial components, there is a need for inclusion of working conditions in such analyses. An evaluation of the compensation system that incorporates OSH can drive many benefits for both the organization and employees. Obtaining such benefits, however, requires systematic evaluation of the reward system, including OSH. Incorporation of OSH issue within the comprehensive analysis of compensation systems promotes responsible behavior of all stakeholders.

Can Multilayer Networks Advance Animal Behavior Research?

PubMed

Silk, Matthew J; Finn, Kelly R; Porter, Mason A; Pinter-Wollman, Noa

2018-06-01

Interactions among individual animals - and between these individuals and their environment - yield complex, multifaceted systems. The development of multilayer network analysis offers a promising new approach for studying animal social behavior and its relation to eco-evolutionary dynamics. Copyright © 2018 Elsevier Ltd. All rights reserved.

Microbial endocrinology: Host-microbiota neuroendocrine interactions influencing brain and behavior.

PubMed

Lyte, Mark

2014-01-01

The ability of microorganisms, whether present as commensals within the microbiota or introduced as part of a therapeutic regimen, to influence behavior has been demonstrated by numerous laboratories over the last few years. Our understanding of the mechanisms that are responsible for microbiota-gut-brain interactions is, however, lacking. The complexity of the microbiota is, of course, a contributing factor. Nonetheless, while microbiologists approaching the issue of microbiota-gut-brain interactions in the behavior well recognize such complexity, what is often overlooked is the equal complexity of the host neurophysiological system, especially within the gut which is differentially innervated by the enteric nervous system. As such, in the search for common mechanisms by which the microbiota may influence behavior one may look for mechanisms which are shared by both host and microbiota. Such interkingdom signaling can be found in the shared production of neurochemical mediators that are found in both eukaryotes and prokaryotes. The study of the production and recognition of neurochemicals that are exactly the same in structure to those produced in the vertebrate organisms is known as microbial endocrinology. The examination of the microbiota from the vantage point of host-microbiota neuroendocrine interactions cannot only identify new microbial endocrinology-based mechanisms by which the microbiota can influence host behavior, but also lead to the design of interventions in which the composition of the microbiota may be modulated in order to achieve a specific microbial endocrinology-based profile beneficial to overall host behavior.

Neural systems analysis of decision making during goal-directed navigation.

PubMed

Penner, Marsha R; Mizumori, Sheri J Y

2012-01-01

The ability to make adaptive decisions during goal-directed navigation is a fundamental and highly evolved behavior that requires continual coordination of perceptions, learning and memory processes, and the planning of behaviors. Here, a neurobiological account for such coordination is provided by integrating current literatures on spatial context analysis and decision-making. This integration includes discussions of our current understanding of the role of the hippocampal system in experience-dependent navigation, how hippocampal information comes to impact midbrain and striatal decision making systems, and finally the role of the striatum in the implementation of behaviors based on recent decisions. These discussions extend across cellular to neural systems levels of analysis. Not only are key findings described, but also fundamental organizing principles within and across neural systems, as well as between neural systems functions and behavior, are emphasized. It is suggested that studying decision making during goal-directed navigation is a powerful model for studying interactive brain systems and their mediation of complex behaviors. Copyright © 2011. Published by Elsevier Ltd.

Numerical Study of the Complex Temporal Pattern of Spontaneous Oscillation in Bullfrog Saccular Hair Cells

NASA Astrophysics Data System (ADS)

Roongthumskul, Yuttana; Fredrickson-Hemsing, Lea; Kao, Albert; Bozovic, Dolores

2011-11-01

Hair bundles of the bullfrog sacculus display spontaneous oscillations that show complex temporal profiles. Quiescent intervals are typically interspersed with oscillations, analogous to bursting behavior observed in neural systems. By introducing slow calcium dynamics into the theoretical model of bundle mechanics, we reproduce numerically the multi-mode oscillations and explore the effects of internal parameters on the temporal profiles and the frequency tuning of their linear response functions. We also study the effects of mechanical overstimulation on the oscillatory behavior.

Optogenetic interrogation of neural circuits: technology for probing mammalian brain structures

PubMed Central

Zhang, Feng; Gradinaru, Viviana; Adamantidis, Antoine R; Durand, Remy; Airan, Raag D; de Lecea, Luis; Deisseroth, Karl

2015-01-01

Elucidation of the neural substrates underlying complex animal behaviors depends on precise activity control tools, as well as compatible readout methods. Recent developments in optogenetics have addressed this need, opening up new possibilities for systems neuroscience. Interrogation of even deep neural circuits can be conducted by directly probing the necessity and sufficiency of defined circuit elements with millisecond-scale, cell type-specific optical perturbations, coupled with suitable readouts such as electrophysiology, optical circuit dynamics measures and freely moving behavior in mammals. Here we collect in detail our strategies for delivering microbial opsin genes to deep mammalian brain structures in vivo, along with protocols for integrating the resulting optical control with compatible readouts (electrophysiological, optical and behavioral). The procedures described here, from initial virus preparation to systems-level functional readout, can be completed within 4–5 weeks. Together, these methods may help in providing circuit-level insight into the dynamics underlying complex mammalian behaviors in health and disease. PMID:20203662

Progesterone Response Element Variation in the OXTR Promoter Region and Paternal Care in New World Monkeys.

PubMed

Vargas-Pinilla, Pedro; Babb, Paul; Nunes, Leandro; Paré, Pâmela; Rosa, Gabrielle; Felkl, Aline; Longo, Dânae; Salzano, Francisco M; Paixão-Côrtes, Vanessa R; Gonçalves, Gislene Lopes; Bortolini, Maria Cátira

2017-01-01

Paternal care is a complex social behavior common in primate species with socially monogamous mating systems and twin births. Evolutionary causes and consequences of such behavior are not well understood, nor are their neuroendocrine and genetic bases. However, the neuropeptide oxytocin (OXT) and its receptor (OXTR) are associated with parental care in mammalian lineages. Here we investigated the interspecific variation in the number of progesterone response elements (PREs) in the OXTR promoter region of 32 primate species, correlating genetic data with behavior, social systems, and ecological/life-history parameters, while controlling for phylogeny. We verified that PREs are only present in New World monkeys and that PRE number is significantly correlated with the presence of paternal care in this branch. We suggest that PRE number could be an essential part of the genetic repertoire that allowed the emergence of taxon-specific complex social behaviors, such as paternal care in marmosets and tamarins.

A cognitive information processing framework for distributed sensor networks

NASA Astrophysics Data System (ADS)

Wang, Feiyi; Qi, Hairong

2004-09-01

In this paper, we present a cognitive agent framework (CAF) based on swarm intelligence and self-organization principles, and demonstrate it through collaborative processing for target classification in sensor networks. The framework involves integrated designs to provide both cognitive behavior at the organization level to conquer complexity and reactive behavior at the individual agent level to retain simplicity. The design tackles various problems in the current information processing systems, including overly complex systems, maintenance difficulties, increasing vulnerability to attack, lack of capability to tolerate faults, and inability to identify and cope with low-frequency patterns. An important and distinguishing point of the presented work from classical AI research is that the acquired intelligence does not pertain to distinct individuals but to groups. It also deviates from multi-agent systems (MAS) due to sheer quantity of extremely simple agents we are able to accommodate, to the degree that some loss of coordination messages and behavior of faulty/compromised agents will not affect the collective decision made by the group.

Sleeping of a Complex Brain Networks with Hierarchical Organization

NASA Astrophysics Data System (ADS)

Zhang, Ying-Yue; Yang, Qiu-Ying; Chen, Tian-Lun

2009-01-01

The dynamical behavior in the cortical brain network of macaque is studied by modeling each cortical area with a subnetwork of interacting excitable neurons. We characterize the system by studying how to perform the transition, which is now topology-dependent, from the active state to that with no activity. This could be a naive model for the wakening and sleeping of a brain-like system, i.e., a multi-component system with two different dynamical behavior.

Complex Dynamics of the Power Transmission Grid (and other Critical Infrastructures)

NASA Astrophysics Data System (ADS)

Newman, David

2015-03-01

Our modern societies depend crucially on a web of complex critical infrastructures such as power transmission networks, communication systems, transportation networks and many others. These infrastructure systems display a great number of the characteristic properties of complex systems. Important among these characteristics, they exhibit infrequent large cascading failures that often obey a power law distribution in their probability versus size. This power law behavior suggests that conventional risk analysis does not apply to these systems. It is thought that much of this behavior comes from the dynamical evolution of the system as it ages, is repaired, upgraded, and as the operational rules evolve with human decision making playing an important role in the dynamics. In this talk, infrastructure systems as complex dynamical systems will be introduced and some of their properties explored. The majority of the talk will then be focused on the electric power transmission grid though many of the results can be easily applied to other infrastructures. General properties of the grid will be discussed and results from a dynamical complex systems power transmission model will be compared with real world data. Then we will look at a variety of uses of this type of model. As examples, we will discuss the impact of size and network homogeneity on the grid robustness, the change in risk of failure as generation mix (more distributed vs centralized for example) changes, as well as the effect of operational changes such as the changing the operational risk aversion or grid upgrade strategies. One of the important outcomes from this work is the realization that ``improvements'' in the system components and operational efficiency do not always improve the system robustness, and can in fact greatly increase the risk, when measured as a risk of large failure.

Sustainable Water Systems for the City of Tomorrow—A Conceptual Framework

EPA Science Inventory

Urban water systems are an example of complex, dynamic human-environment coupled systems, which exhibit emergent behaviors that transcends individual scientific disciplines. While previous siloed approaches to water services (i.e., water resources, drinking water, wastewater, and...

Robot-assisted surgery: an emerging platform for human neuroscience research

PubMed Central

Jarc, Anthony M.; Nisky, Ilana

2015-01-01

Classic studies in human sensorimotor control use simplified tasks to uncover fundamental control strategies employed by the nervous system. Such simple tasks are critical for isolating specific features of motor, sensory, or cognitive processes, and for inferring causality between these features and observed behavioral changes. However, it remains unclear how these theories translate to complex sensorimotor tasks or to natural behaviors. Part of the difficulty in performing such experiments has been the lack of appropriate tools for measuring complex motor skills in real-world contexts. Robot-assisted surgery (RAS) provides an opportunity to overcome these challenges by enabling unobtrusive measurements of user behavior. In addition, a continuum of tasks with varying complexity—from simple tasks such as those in classic studies to highly complex tasks such as a surgical procedure—can be studied using RAS platforms. Finally, RAS includes a diverse participant population of inexperienced users all the way to expert surgeons. In this perspective, we illustrate how the characteristics of RAS systems make them compelling platforms to extend many theories in human neuroscience, as well as, to develop new theories altogether. PMID:26089785

Complexity and robustness

PubMed Central

Carlson, J. M.; Doyle, John

2002-01-01

Highly optimized tolerance (HOT) was recently introduced as a conceptual framework to study fundamental aspects of complexity. HOT is motivated primarily by systems from biology and engineering and emphasizes, (i) highly structured, nongeneric, self-dissimilar internal configurations, and (ii) robust yet fragile external behavior. HOT claims these are the most important features of complexity and not accidents of evolution or artifices of engineering design but are inevitably intertwined and mutually reinforcing. In the spirit of this collection, our paper contrasts HOT with alternative perspectives on complexity, drawing on real-world examples and also model systems, particularly those from self-organized criticality. PMID:11875207

Linear control theory for gene network modeling.

PubMed

Shin, Yong-Jun; Bleris, Leonidas

2010-09-16

Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

End-Directedness and Context in Nonliving Dissipative Systems

NASA Astrophysics Data System (ADS)

Dixon, James A.; Kay, Bruce A.; Davis, Tehran J.; Kondepudi, Dilip

Biological organisms are distinguished from non-living systems, in part, by their ability to choose and strive towards particular ends. This end-directed behavior is seen across all five biological kingdoms, from single-celled organisms to the most advanced primates. The ubiquitous nature of end-directedness, across such a wide variety of biological entities, suggests that a deeper principle may be at work. We propose that end-directedness, rather than being a special ability of living systems, is actually a fundamental property of a larger class of physical systems, called dissipative structures, which are formed and maintained by the flow of energy and matter. Our work shows that dissipative structures "behave so as to persist", seeking states that increase their rate of entropy production, and thus facilitate their own persistence. In addition, we suggest that biological entities create their exquisite sensitivity to context by interweaving this fundamental end-directedness with the contextual and physical constraints of their environments. The result is a repertoire of complex behavior. We provide an example of such complex behavior emerging from contextual and physical constraints coupled with end-directedness.

Applying User Input to the Design and Testing of an Electronic Behavioral Health Information System for Wraparound Care Coordination

PubMed Central

Bruns, Eric J.; Hyde, Kelly L.; Sather, April; Hook, Alyssa; Lyon, Aaron R.

2015-01-01

Health information technology (HIT) and care coordination for individuals with complex needs are high priorities for quality improvement in health care. However, there is little empirical guidance about how best to design electronic health record systems and related technologies to facilitate implementation of care coordination models in behavioral health, or how best to apply user input to the design and testing process. In this paper, we describe an iterative development process that incorporated user/stakeholder perspectives at multiple points and resulted in an electronic behavioral health information system (EBHIS) specific to the wraparound care coordination model for youth with serious emotional and behavioral disorders. First, we review foundational HIT research on how EBHIS can enhance efficiency and outcomes of wraparound that was used to inform development. After describing the rationale for and functions of a prototype EBHIS for wraparound, we describe methods and results for a series of six small studies that informed system development across four phases of effort – predevelopment, development, initial user testing, and commercialization – and discuss how these results informed system design and refinement. Finally, we present next steps, challenges to dissemination, and guidance for others aiming to develop specialized behavioral health HIT. The research team's experiences reinforce the opportunity presented by EBHIS to improve care coordination for populations with complex needs, while also pointing to a litany of barriers and challenges to be overcome to implement such technologies. PMID:26060099

Embracing Complexity beyond Systems Medicine: A New Approach to Chronic Immune Disorders

PubMed Central

te Velde, Anje A.; Bezema, Tjitske; van Kampen, Antoine H. C.; Kraneveld, Aletta D.; 't Hart, Bert A.; van Middendorp, Henriët; Hack, Erik C.; van Montfrans, Joris M.; Belzer, Clara; Jans-Beken, Lilian; Pieters, Raymond H.; Knipping, Karen; Huber, Machteld; Boots, Annemieke M. H.; Garssen, Johan; Radstake, Tim R.; Evers, Andrea W. M.; Prakken, Berent J.; Joosten, Irma

2016-01-01

In order to combat chronic immune disorders (CIDs), it is an absolute necessity to understand the bigger picture, one that goes beyond insights at a one-disease, molecular, cellular, and static level. To unravel this bigger picture we advocate an integral, cross-disciplinary approach capable of embracing the complexity of the field. This paper discusses the current knowledge on common pathways in CIDs including general psychosocial and lifestyle factors associated with immune functioning. We demonstrate the lack of more in-depth psychosocial and lifestyle factors in current research cohorts and most importantly the need for an all-encompassing analysis of these factors. The second part of the paper discusses the challenges of understanding immune system dynamics and effectively integrating all key perspectives on immune functioning, including the patient’s perspective itself. This paper suggests the use of techniques from complex systems science in describing and simulating healthy or deviating behavior of the immune system in its biopsychosocial surroundings. The patient’s perspective data are suggested to be generated by using specific narrative techniques. We conclude that to gain more insight into the behavior of the whole system and to acquire new ways of combatting CIDs, we need to construct and apply new techniques in the field of computational and complexity science, to an even wider variety of dynamic data than used in today’s systems medicine. PMID:28018353

Identifying behavioral circuits in Drosophila melanogaster: moving targets in a flying insect.

PubMed

Griffith, Leslie C

2012-08-01

Drosophila melanogaster has historically been the premier model system for understanding the molecular and genetic bases of complex behaviors. In the last decade technical advances, in the form of new genetic tools and electrophysiological and optical methods, have allowed investigators to begin to dissect the neuronal circuits that generate behavior in the adult. The blossoming of circuit analysis in this organism has also reinforced our appreciation of the inadequacy of wiring diagrams for specifying complex behavior. Neuromodulation and neuronal plasticity act to reconfigure circuits on both short and long time scales. These processes act on the connectome, providing context by integrating external and internal cues that are relevant for behavioral choices. New approaches in the fly are providing insight into these basic principles of circuit function. Copyright © 2012 Elsevier Ltd. All rights reserved.

Stress, Anxiety, and Immunomodulation: A Pharmacological Analysis.

PubMed

Ray, A; Gulati, K; Rai, N

2017-01-01

Stress and stressful events are common occurrences in our daily lives and such aversive situations bring about complex changes in the biological system. Such stress responses influence the brain and behavior, neuroendocrine and immune systems, and these responses orchestrate to increase or decrease the ability of the organism to cope with such stressors. The brain via expression of complex behavioral paradigms controls peripheral responses to stress and a bidirectional link exists in the modulation of stress effects. Anxiety is a common neurobehavioral correlate of a variety of stressors, and both acute and chronic stress exposure could precipitate anxiety disorders. Psychoneuroimmunology involves interactions between the brain and the immune system, and it is now being increasingly recognized that the immune system could contribute to the neurobehavioral responses to stress. Studies have shown that the brain and its complex neurotransmitter networks could influence immune function, and there could be a possible link between anxiogenesis and immunomodulation during stress. Physiological and pharmacological data have highlighted this concept, and the present review gives an overview of the relationship between stress, anxiety, and immune responsiveness. © 2017 Elsevier Inc. All rights reserved.

Young Investigator Program (8.5): Preventing Complex Failures of Human Interactive Systems with Erroneous Behavior Generation and Robust Human Task Behavior Patterns

DTIC Science & Technology

2017-11-13

behavior . The International Journal of Human-Computer Studies , 108, 105-121. https://doi.org/10.1016/j.ijhcs.2017.06.006 A second journal article...documenting the erroneous behavior generation approach and the case study analyses is currently being written. Planned submission is Spring 2017. RPPR...Belvoir, 2010. [3] A task-based taxonomy of erroneous human behavior . International Journal of Human-Computer Studies , 108:105–121, 2017. [4] M. L

Financing results and value in behavioral health services.

PubMed

2003-11-01

Current changes require that behavioral health care leaders understand how public and private financing mechanisms interact and how, now more than ever, behavioral health care leadership must span multiple systems and financing streams. Understanding how financing mechanisms work, what they create, and what they cause is essential if we are to make the most of increasingly limited and increasingly complex resource streams in today's health care market. This article explores a different paradigm of what adds value to publicly funded behavioral health care systems, and provides the framework for the American College of Mental Health Administration's call to behavioral health care administrators to take a new approach to the considerations behind funding decisions and payment mechanisms.

Liquid crystalline phase behavior of protein fibers in water: experiments versus theory.

PubMed

Jung, Jin-Mi; Mezzenga, Raffaele

2010-01-05

We have developed a new method allowing the study of the thermodynamic phase behavior of mesoscopic colloidal systems consisting of amyloid protein fibers in water, obtained by heat denaturation and aggregation of beta-lactoglobulin, a dairy protein. The fibers have a cross section of about 5.2 nm and two groups of polydisperse contour lengths: (i) long fibers of 1-20 microm, showing semiflexible behavior, and (ii) short rods of 100-200 nm long, obtained by cutting the long fibers via high-pressure homogenization. At pH 2 without salt, these fibers are highly charged and stable in water. We have studied the isotropic-nematic phase transition for both systems and compared our results with the theoretical values predicted by Onsager's theory. The experimentally measured isotropic-nematic phase transition was found to occur at 0.4% and at 3% for the long and short fibers, respectively. For both systems, this phase transition occurs at concentrations more than 1 order of magnitude lower than what is expected based on Onsager's theory. Moreover, at low enough pH, no intermediate biphasic region was observed between the isotropic phase and the nematic phase. The phase diagrams of both systems (pH vs concentration) showed similar, yet complex and rich, phase behavior. We discuss the possible physical fundamentals ruling the phase diagram as well as the discrepancy we observe for the isotropic-nematic phase transition between our experimental results and the predicted theoretical results. Our work highlights that systems formed by water-amyloid protein fibers are way too complex to be understood based solely on Onsager's theories. Experimental results are revisited in terms of the Flory's theory (1956) for suspensions of rods, which allows accounting for rod-solvent hydrophobic interactions. This theoretical approach allows explaining, on a semiquantitative basis, most of the discrepancies observed between the experimental results and Onsager's predictions. The sources of protein fibers complex colloidal behavior are analyzed and discussed at length.

A Pedagogical Software for the Analysis of Loudspeaker Systems

ERIC Educational Resources Information Center

Pueo, B.; Roma, M.; Escolano, J.; Lopez, J. J.

2009-01-01

In this paper, a pedagogical software for the design and analysis of loudspeaker systems is presented, with emphasis on training students in the interaction between system parameters. Loudspeakers are complex electromechanical system, whose behavior is neither intuitive nor easy to understand by inexperienced students. Although commercial…

[The dimension of the paradigm of complexity in health systems].

PubMed

Fajardo-Ortiz, Guillermo; Fernández-Ortega, Miguel Ángel; Ortiz-Montalvo, Armando; Olivares-Santos, Roberto Antonio

2015-01-01

This article presents elements to better understand health systems from the complety paradigm, innovative perspective that offers other ways in the conception of the scientific knowledge prevalent away from linear, characterized by the arise of emerging dissociative and behaviors, based on the intra and trans-disciplinarity concepts such knowledges explain and understand in a different way what happens in the health systems with a view to efficiency and effectiveness. The complexity paradigm means another way of conceptualizing the knowledge, is different from the prevalent epistemology, is still under construction does not separate, not isolated, is not reductionist, or fixed, does not solve the problems, but gives other bases to know them and study them, is a different strategy, a perspective that has basis in the systems theory, informatics and cybernetics beyond traditional knowledge, the positive logics, the newtonian physics and symmetric mathematics, in which everything is centered and balanced, joint the "soft sciences and hard sciences", it has present the Social Determinants of Health and organizational culture. Under the complexity paradigm the health systems are identified with the following concepts: entropy, neguentropy, the thermodynamic second law, attractors, chaos theory, fractals, selfmanagement and self-organization, emerging behaviors, percolation, uncertainty, networks and robusteness; such expressions open new possibilities to improve the management and better understanding of the health systems, giving rise to consider health systems as complex adaptive systems. Copyright © 2015. Published by Masson Doyma México S.A.

Modeling acclimatization by hybrid systems: condition changes alter biological system behavior models.

PubMed

Assar, Rodrigo; Montecino, Martín A; Maass, Alejandro; Sherman, David J

2014-07-01

In order to describe the dynamic behavior of a complex biological system, it is useful to combine models integrating processes at different levels and with temporal dependencies. Such combinations are necessary for modeling acclimatization, a phenomenon where changes in environmental conditions can induce drastic changes in the behavior of a biological system. In this article we formalize the use of hybrid systems as a tool to model this kind of biological behavior. A modeling scheme called strong switches is proposed. It allows one to take into account both minor adjustments to the coefficients of a continuous model, and, more interestingly, large-scale changes to the structure of the model. We illustrate the proposed methodology with two applications: acclimatization in wine fermentation kinetics, and acclimatization of osteo-adipo differentiation system linking stimulus signals to bone mass. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

The Importance of Protons in Reactive Transport Modeling

NASA Astrophysics Data System (ADS)

McNeece, C. J.; Hesse, M. A.

2014-12-01

The importance of pH in aqueous chemistry is evident; yet, its role in reactive transport is complex. Consider a column flow experiment through silica glass beads. Take the column to be saturated and flowing with solution of a distinct pH. An instantaneous change in the influent solution pH can yield a breakthrough curve with both a rarefaction and shock component (composite wave). This behavior is unique among aqueous ions in transport and is more complex than intuition would tell. Analysis of the hyperbolic limit of this physical system can explain these first order transport phenomenon. This analysis shows that transport behavior is heavily dependent on the shape of the adsorption isotherm. Hence it is clear that accurate surface chemistry models are important in reactive transport. The proton adsorption isotherm has nonconstant concavity due to the proton's ability to partition into hydroxide. An eigenvalue analysis shows that an inflection point in the adsorption isotherm allows the development of composite waves. We use electrostatic surface complexation models to calculate realistic proton adsorption isotherms. Surface characteristics such as specific surface area, and surface site density were determined experimentally. We validate the model by comparison against silica glass bead flow through experiments. When coupled to surface complexation models, the transport equation captures the timing and behavior of breakthrough curves markedly better than with commonly used Langmuir assumptions. Furthermore, we use the adsorption isotherm to predict, a priori, the transport behavior of protons across pH composition space. Expansion of the model to multicomponent systems shows that proton adsorption can force composite waves to develop in the breakthrough curves of ions that would not otherwise exhibit such behavior. Given the abundance of reactive surfaces in nature and the nonlinearity of chemical systems, we conclude that building a greater understanding of proton adsorption is of utmost importance to reactive transport modeling.

Agent-Based Models in Social Physics

NASA Astrophysics Data System (ADS)

Quang, Le Anh; Jung, Nam; Cho, Eun Sung; Choi, Jae Han; Lee, Jae Woo

2018-06-01

We review the agent-based models (ABM) on social physics including econophysics. The ABM consists of agent, system space, and external environment. The agent is autonomous and decides his/her behavior by interacting with the neighbors or the external environment with the rules of behavior. Agents are irrational because they have only limited information when they make decisions. They adapt using learning from past memories. Agents have various attributes and are heterogeneous. ABM is a non-equilibrium complex system that exhibits various emergence phenomena. The social complexity ABM describes human behavioral characteristics. In ABMs of econophysics, we introduce the Sugarscape model and the artificial market models. We review minority games and majority games in ABMs of game theory. Social flow ABM introduces crowding, evacuation, traffic congestion, and pedestrian dynamics. We also review ABM for opinion dynamics and voter model. We discuss features and advantages and disadvantages of Netlogo, Repast, Swarm, and Mason, which are representative platforms for implementing ABM.

Patterns of Performance

ERIC Educational Resources Information Center

Eoyang, Glenda H.

2007-01-01

Complex human interactions involve more than just performance toward pre-determined goals. For this reason, systems that measure and seek to improve performance must adapt to a wide range of ever-changing patterns of individual and group behavior. Historically, HPT professionals have recognized these complexities and responded in a variety of…

Sensor Abstractions to Support Many-Robot Systems

DTIC Science & Technology

1993-04-01

the behaviors of the social insects: ants, bees, and termites ; the observed aggregate behaviors exhibit a greater complexity, while the individual...applicability -’f" togies from biology (hjrdirg, ec!"x’-oig, iiununc system and pheromone mechanisms) and physics (entropy, temperature, pressure...in [17-19]. Pheromones provide an important example of animals arranging their environment to, for example, help moths find mates, or to help a colony

A Second-Generation Device for Automated Training and Quantitative Behavior Analyses of Molecularly-Tractable Model Organisms

PubMed Central

Blackiston, Douglas; Shomrat, Tal; Nicolas, Cindy L.; Granata, Christopher; Levin, Michael

2010-01-01

A deep understanding of cognitive processes requires functional, quantitative analyses of the steps leading from genetics and the development of nervous system structure to behavior. Molecularly-tractable model systems such as Xenopus laevis and planaria offer an unprecedented opportunity to dissect the mechanisms determining the complex structure of the brain and CNS. A standardized platform that facilitated quantitative analysis of behavior would make a significant impact on evolutionary ethology, neuropharmacology, and cognitive science. While some animal tracking systems exist, the available systems do not allow automated training (feedback to individual subjects in real time, which is necessary for operant conditioning assays). The lack of standardization in the field, and the numerous technical challenges that face the development of a versatile system with the necessary capabilities, comprise a significant barrier keeping molecular developmental biology labs from integrating behavior analysis endpoints into their pharmacological and genetic perturbations. Here we report the development of a second-generation system that is a highly flexible, powerful machine vision and environmental control platform. In order to enable multidisciplinary studies aimed at understanding the roles of genes in brain function and behavior, and aid other laboratories that do not have the facilities to undergo complex engineering development, we describe the device and the problems that it overcomes. We also present sample data using frog tadpoles and flatworms to illustrate its use. Having solved significant engineering challenges in its construction, the resulting design is a relatively inexpensive instrument of wide relevance for several fields, and will accelerate interdisciplinary discovery in pharmacology, neurobiology, regenerative medicine, and cognitive science. PMID:21179424

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

PubMed Central

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

2013-01-01

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

Tendency towards maximum complexity in a nonequilibrium isolated system

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

Calbet, Xavier; Lopez-Ruiz, Ricardo

2001-06-01

The time evolution equations of a simplified isolated ideal gas, the {open_quotes}tetrahedral{close_quotes} gas, are derived. The dynamical behavior of the Lopez-Ruiz{endash}Mancini{endash}Calbet complexity [R. Lopez-Ruiz, H. L. Mancini, and X. Calbet, Phys. Lett. A >209, 321 (1995)] is studied in this system. In general, it is shown that the complexity remains within the bounds of minimum and maximum complexity. We find that there are certain restrictions when the isolated {open_quotes}tetrahedral{close_quotes} gas evolves towards equilibrium. In addition to the well-known increase in entropy, the quantity called disequilibrium decreases monotonically with time. Furthermore, the trajectories of the system in phase space approach themore » maximum complexity path as it evolves toward equilibrium.« less

Review-Physicochemical hydrodynamics of gas bubbles in two phase electrochemical systems.

PubMed

Taqieddin, Amir; Nazari, Roya; Rajic, Ljiljana; Alshawabkeh, Akram

2017-01-01

Electrochemical systems suffer from poor management of evolving gas bubbles. Improved understanding of bubbles behavior helps to reduce overpotential, save energy and enhance the mass transfer during chemical reactions. This work investigates and reviews the gas bubbles hydrodynamics, behavior, and management in electrochemical cells. Although the rate of bubble growth over the electrode surface is well understood, there is no reliable prediction of bubbles break-off diameter from the electrode surface because of the complexity of bubbles motion near the electrode surface. Particle Image Velocimetry (PIV) and Laser Doppler Anemometry (LDA) are the most common experimental techniques to measure bubble dynamics. Although the PIV is faster than LDA, both techniques are considered expensive and time-consuming. This encourages adapting Computational Fluid Dynamics (CFD) methods as an alternative to study bubbles behavior. However, further development of CFD methods is required to include coalescence and break-up of bubbles for better understanding and accuracy. The disadvantages of CFD methods can be overcome by using hybrid methods. The behavior of bubbles in electrochemical systems is still a complex challenging topic which requires a better understanding of the gas bubbles hydrodynamics and their interactions with the electrode surface and bulk liquid, as well as between the bubbles itself.

Dynamical singularities of glassy systems in a quantum quench.

PubMed

Obuchi, Tomoyuki; Takahashi, Kazutaka

2012-11-01

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

Logical Interactions in AN Expanded Space

NASA Astrophysics Data System (ADS)

Tadić, Bosiljka

Understanding the emergent behavior in many complex systems in the physical world and society requires a detailed study of dynamical phenomena occurring and mutually coupled at different scales. The brain processes underlying the social conduct of each, and the emergent social behavior of interacting individuals on a larger scale, represent striking examples of the multiscale complexity. Studies of the human brain, a paradigm of a complex functional system, are enabled by a wealth of brain imaging data that provide clues of how we comprehend space, time, languages, numbers, and differentiate normal from diseased individuals, for example. The social brain, a neural basis for social cognition, represents a dynamically organized part of the brain which is involved in the inference of thoughts, feelings, and intentions going on in the brains of others. Research in this currently unexplored area opens a new perspective on the genesis of the societal organization at different levels and the associated social values...

Modeling fluctuations in default-mode brain network using a spiking neural network.

PubMed

Yamanishi, Teruya; Liu, Jian-Qin; Nishimura, Haruhiko

2012-08-01

Recently, numerous attempts have been made to understand the dynamic behavior of complex brain systems using neural network models. The fluctuations in blood-oxygen-level-dependent (BOLD) brain signals at less than 0.1 Hz have been observed by functional magnetic resonance imaging (fMRI) for subjects in a resting state. This phenomenon is referred to as a "default-mode brain network." In this study, we model the default-mode brain network by functionally connecting neural communities composed of spiking neurons in a complex network. Through computational simulations of the model, including transmission delays and complex connectivity, the network dynamics of the neural system and its behavior are discussed. The results show that the power spectrum of the modeled fluctuations in the neuron firing patterns is consistent with the default-mode brain network's BOLD signals when transmission delays, a characteristic property of the brain, have finite values in a given range.

Chemical induced behavioral responses in anopheles minimus and Anopheles harrisoni in Thailand

USDA-ARS?s Scientific Manuscript database

Behavioral responses of female mosquitoes representing two species in the Minimus Complex exposed to an operational field dose of bifenthrin or DEET (N,N-diethyl-m-toluamide) were described using an excito-repellency test system. Two test populations of An. minimus, one from the field (Tak Provinc...

How to analytically characterize the epidemic threshold within the coupled disease-behavior systems?. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Xia, Cheng-Yi; Ding, Shuai; Sun, Shi-Wen; Wang, Li; Gao, Zhong-Ke; Wang, Juan

2015-12-01

As is well known, outbreak of epidemics may drive the human population to take some necessary measures to protect themselves from not being infected by infective ones, these precautions in turn will also keep from the further spreading of infectious diseases among the population. Thus, to fully comprehend the epidemic spreading behavior within real-world systems, the interplay between disease dynamics and human behavioral and social dynamics needs to be considered simultaneously, such that some effective containment-measures can be successfully developed [1-3].

Flash crashes, bursts, and black swans: parallels between financial markets and healthcare systems.

PubMed

West, Bruce J; Clancy, Thomas R

2010-11-01

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 management in social organizations such as hospitals. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. This is the 16th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, Dr Clancy, the editor of this column, and co-author, Dr West, discuss how the collapse of global financial markets in 2008 may provide valuable insight into mechanisms of complex system behavior in healthcare. Dr West, a physicist and expert in the field of complex systems and network science, is author of a chapter in the book, On the Edge: Nursing in the Age of Complexity (Lindberg C, Nash S, Linberg C. Bordertown, NJ: Plexus Press; 2008) and his most recent book, Disrupted Networks: From Physics to Climate Change (West BJ, Scafetta N. Singapore: Disrupted Networks, World Scientific Publishing; 2010).

Periodicity and chaos from switched flow systems - Contrasting examples of discretely controlled continuous systems

NASA Technical Reports Server (NTRS)

Chase, Christopher; Serrano, Joseph; Ramadge, Peter J.

1993-01-01

We analyze two examples of the discrete control of a continuous variable system. These examples exhibit what may be regarded as the two extremes of complexity of the closed-loop behavior: one is eventually periodic, the other is chaotic. Our examples are derived from sampled deterministic flow models. These are of interest in their own right but have also been used as models for certain aspects of manufacturing systems. In each case, we give a precise characterization of the closed-loop behavior.

Diamond and diamond-like carbon MEMS

NASA Astrophysics Data System (ADS)

Luo, J. K.; Fu, Y. Q.; Le, H. R.; Williams, J. A.; Spearing, S. M.; Milne, W. I.

2007-07-01

To generate complex cartilage/bone tissues, scaffolds must possess several structural features that are difficult to create using conventional scaffold design/fabrication technologies. Successful cartilage/bone regeneration depends on the ability to assemble chondrocytes/osteoblasts into three-dimensional (3D) scaffolds. Therefore, we developed a 3D scaffold fabrication system that applies the axiomatic approach to our microstereolithography system. The new system offers a reduced machine size by minimizing the optical components, and shows that the design matrix is decoupled. This analysis identified the key factors affecting microstructure fabrication and an improved scaffold fabrication system was constructed. The results demonstrate that precise, predesigned 3D structures can be fabricated. Using this 3D scaffold, cell adhesion behavior was observed. The use of 3D scaffolds might help determine key factors in the study of cell behavior in complex environments and could eventually lead to the optimal design of scaffolds for the regeneration of various tissues, such as cartilage and bone.

Self-affinity in the dengue fever time series

NASA Astrophysics Data System (ADS)

Azevedo, S. M.; Saba, H.; Miranda, J. G. V.; Filho, A. S. Nascimento; Moret, M. A.

2016-06-01

Dengue is a complex public health problem that is common in tropical and subtropical regions. This disease has risen substantially in the last three decades, and the physical symptoms depict the self-affine behavior of the occurrences of reported dengue cases in Bahia, Brazil. This study uses detrended fluctuation analysis (DFA) to verify the scale behavior in a time series of dengue cases and to evaluate the long-range correlations that are characterized by the power law α exponent for different cities in Bahia, Brazil. The scaling exponent (α) presents different long-range correlations, i.e. uncorrelated, anti-persistent, persistent and diffusive behaviors. The long-range correlations highlight the complex behavior of the time series of this disease. The findings show that there are two distinct types of scale behavior. In the first behavior, the time series presents a persistent α exponent for a one-month period. For large periods, the time series signal approaches subdiffusive behavior. The hypothesis of the long-range correlations in the time series of the occurrences of reported dengue cases was validated. The observed self-affinity is useful as a forecasting tool for future periods through extrapolation of the α exponent behavior. This complex system has a higher predictability in a relatively short time (approximately one month), and it suggests a new tool in epidemiological control strategies. However, predictions for large periods using DFA are hidden by the subdiffusive behavior.

Human Error In Complex Systems

NASA Technical Reports Server (NTRS)

Morris, Nancy M.; Rouse, William B.

1991-01-01

Report presents results of research aimed at understanding causes of human error in such complex systems as aircraft, nuclear powerplants, and chemical processing plants. Research considered both slips (errors of action) and mistakes (errors of intention), and influence of workload on them. Results indicated that: humans respond to conditions in which errors expected by attempting to reduce incidence of errors; and adaptation to conditions potent influence on human behavior in discretionary situations.

A Novel Approach to Primary Cell Culture for Octopus vulgaris Neurons

PubMed Central

Maselli, Valeria; Xu, Fenglian; Syed, Naweed I.; Polese, Gianluca; Di Cosmo, Anna

2018-01-01

Octopus vulgaris is a unique model system for studying complex behaviors in animals. It has a large and centralized nervous system made up of lobes that are involved in controlling various sophisticated behaviors. As such, it may be considered as a model organism for untangling the neuronal mechanisms underlying behaviors—including learning and memory. However, despite considerable efforts, Octopus lags behind its other counterparts vis-à-vis its utility in deciphering the cellular, molecular and synaptic mechanisms underlying various behaviors. This study represents a novel approach designed to establish a neuronal cell culture protocol that makes this species amenable to further exploitation as a model system. Here we developed a protocol that enables dissociation of neurons from two specific Octopus' brain regions, the vertical-superior frontal system and the optic lobes, which are involved in memory, learning, sensory integration and adult neurogenesis. In particular, cells dissociated with enzyme papain and cultured on Poly-D-Lysine-coated dishes with L15-medium and fetal bovine serum yielded high neuronal survival, axon growth, and re-growth after injury. This model was also explored to define optimal culture conditions and to demonstrate the regenerative capabilities of adult Octopus neurons after axotomy. This study thus further underscores the importance of Octopus neurons as a model system for deciphering fundamental molecular and cellular mechanism of complex brain function and underlying behaviors. PMID:29666582

The Sea Slug, Pleurobranchaea californica: A Signpost Species in the Evolution of Complex Nervous Systems and Behavior.

PubMed

Gillette, Rhanor; Brown, Jeffrey W

2015-12-01

How and why did complex brain and behavior evolve? Clues emerge from comparative studies of animals with simpler morphology, nervous system, and behavioral economics. The brains of vertebrates, arthropods, and some annelids have highly derived executive structures and function that control downstream, central pattern generators (CPGs) for locomotion, behavioral choice, and reproduction. For the vertebrates, these structures-cortex, basal ganglia, and hypothalamus-integrate topographically mapped sensory inputs with motivation and memory to transmit complex motor commands to relay stations controlling CPG outputs. Similar computations occur in the central complex and mushroom bodies of the arthropods, and in mammals these interactions structure subjective thought and socially based valuations. The simplest model systems available for comparison are opisthobranch molluscs, which have avoided selective pressure for complex bodies, brain, and behavior through potent chemical defenses. In particular, in the sea-slug Pleurobranchaea californica the functions of vertebrates' olfactory bulb and pallium are performed in the peripheral nervous system (PNS) of the chemotactile oral veil. Functions of hypothalamus and basal ganglia are combined in Pleurobranchaea's feeding motor network. The actions of basal ganglia on downstream locomotor regions and spinal CPGs are analogous to Pleurobranchaea's feeding network actions on CPGs for agonist and antagonist behaviors. The nervous systems of opisthobranch and pulmonate gastropods may conserve or reflect relations of the ancestral urbilaterian. Parallels and contrasts in neuronal circuits for action selection in Pleurobranchaea and vertebrates suggest how a basic set of decision circuitry was built upon in evolving segmentation, articulated skeletons, sociality, and highly invested reproductive strategies. They suggest (1) an origin of olfactory bulb and pallium from head-region PNS; (2) modularization of an ancestral feeding network into discrete but interacting executive modules for incentive comparison and decision (basal ganglia), and homeostatic functions (hypothalamus); (3) modification of a multifunctional premotor network for turns and locomotion, and its downstream targets for mid-brain and hind-brain motor areas and spinal CPGs; (4) condensation of a distributed serotonergic network for arousal into the raphe nuclei, with superimposed control by a peptidergic hypothalamic network mediating appetite and arousal; (5) centralization and condensation of the dopaminergic sensory afferents of the PNS, and/or the disperse dopaminergic elements of central CPGs, into the brain nuclei mediating valuation, reward, and motor arousal; and (6) the urbilaterian possessed the basic circuit relations integrating sensation, internal state, and learning for cost-benefit approach-avoidance decisions. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Protein Folding and Self-Organized Criticality

NASA Astrophysics Data System (ADS)

Bajracharya, Arun; Murray, Joelle

Proteins are known to fold into tertiary structures that determine their functionality in living organisms. However, the complex dynamics of protein folding and the way they consistently fold into the same structures is not fully understood. Self-organized criticality (SOC) has provided a framework for understanding complex systems in various systems (earthquakes, forest fires, financial markets, and epidemics) through scale invariance and the associated power law behavior. In this research, we use a simple hydrophobic-polar lattice-bound computational model to investigate self-organized criticality as a possible mechanism for generating complexity in protein folding.

Solve the Dilemma of Over-Simplification

NASA Astrophysics Data System (ADS)

Schmitt, Gerhard

Complexity science can help to understand the functioning and the interaction of the components of a city. In 1965, Christopher Alexander gave in his book A city is not a tree a description of the complex nature of urban organization. At this time, neither high-speed computers nor urban big data existed. Today, Luis Bettencourt et al. use complexity science to analyze data for countries, regions, or cities. The results can be used globally in other cities. Objectives of complexity science with regard to future cities are the observation and identification of tendencies and regularities in behavioral patterns, and to find correlations between them and spatial configurations. Complex urban systems cannot be understood in total yet. But research focuses on describing the system by finding some simple, preferably general and emerging patterns and rules that can be used for urban planning. It is important that the influencing factors are not just geo-spatial patterns but also consider variables which are important for the design quality. Complexity science is a way to solve the dilemma of oversimplification of insights from existing cities and their applications to new cities. An example: The effects of streets, public places and city structures on citizens and their behavior depend on how they are perceived. To describe this perception, it is not sufficient to consider only particular characteristics of the urban environment. Different aspects play a role and influence each other. Complexity science could take this fact into consideration and handle the non-linearity of the system...

Complex Systems

PubMed Central

Goldberger, Ary L.

2006-01-01

Physiologic systems in health and disease display an extraordinary range of temporal behaviors and structural patterns that defy understanding based on linear constructs, reductionist strategies, and classical homeostasis. Application of concepts and computational tools derived from the contemporary study of complex systems, including nonlinear dynamics, fractals and “chaos theory,” is having an increasing impact on biology and medicine. This presentation provides a brief overview of an emerging area of biomedical research, including recent applications to cardiopulmonary medicine and chronic obstructive lung disease. PMID:16921107

INTERCOMPARISON OF DPASV AND ISE FOR THE MEASUREMENT OF CU COMPLEXATION CHARACTERISTICS OF NOM IN FRESHWATER. (R825395)

EPA Science Inventory

Complexation by dissolved humic substances has an important influence on
trace metal behavior in natural systems. Unfortunately, few analytical
techniques are available with adequate sensitivity and selectivity to measure
free metal ions reliably at the low concent...

Networking at the Protein Society symposium.

PubMed

McKnight, C James; Cordes, Matthew H J

2005-10-01

From the complex behavior of multicomponent signaling networks to the structures of large protein complexes and aggregates, questions once viewed as daunting are now being tackled fearlessly by protein scientists. The 19th Annual Symposium of the Protein Society in Boston highlighted the maturation of systems biology as applied to proteins.

The Speech Community in Evolutionary Language Dynamics

ERIC Educational Resources Information Center

Blythe, Richard A.; Croft, William A.

2009-01-01

Language is a complex adaptive system: Speakers are agents who interact with each other, and their past and current interactions feed into speakers' future behavior in complex ways. In this article, we describe the social cognitive linguistic basis for this analysis of language and a mathematical model developed in collaboration between…

Sorption and speciation of iodine in groundwater system: The roles of organic matter and organic-mineral complexes.

PubMed

Li, Junxia; Zhou, Hailing; Wang, Yanxin; Xie, Xianjun; Qian, Kun

2017-06-01

Characterizing the properties of main host of iodine in soil/sediment and the geochemical behaviors of iodine species are critical to understand the mechanisms of iodine mobilization in groundwater systems. Four surface soil and six subsurface sediment samples were collected from the iodine-affected area of Datong basin in northern China to conduct batch experiments and to evaluate the effects of NOM and/or organic-mineral complexes on iodide/iodate geochemical behaviors. The results showed that both iodine contents and k f -iodate values had positive correlations with solid TOC contents, implying the potential host of NOM for iodine in soil/sediment samples. The results of chemical removal of easily extracted NOM indicated that the NOM of surface soils is mainly composed of surface embedded organic matter, while sediment NOM mainly occurs in the form of organic-mineral complexes. After the removal of surface sorbed NOM, the decrease in k f -iodate value of treated surface soils indicates that surface sorbed NOM enhances iodate adsorption onto surface soil. By contrast, k f -iodate value increases in several H 2 O 2 -treated sediment samples, which was considered to result from exposed rod-like minerals rich in Fe/Al oxyhydroxide/oxides. After chemical removal of organic-mineral complexes, the lowest k f -iodate value for both treated surface soils and sediments suggests the dominant role of organic-mineral complexes on controlling the iodate geochemical behavior. In comparison with iodate, iodide exhibited lower affinities on all (un)treated soil/sediment samples. The understanding of different geochemical behaviors of iodine species helps to explain the occurrence of high iodine groundwater with iodate and iodide as the main species in shallow (oxidizing conditions) and deep (reducing conditions) groundwater. Copyright © 2017 Elsevier B.V. All rights reserved.

Sorption and speciation of iodine in groundwater system: The roles of organic matter and organic-mineral complexes

NASA Astrophysics Data System (ADS)

Li, Junxia; Zhou, Hailing; Wang, Yanxin; Xie, Xianjun; Qian, Kun

2017-06-01

Characterizing the properties of main host of iodine in soil/sediment and the geochemical behaviors of iodine species are critical to understand the mechanisms of iodine mobilization in groundwater systems. Four surface soil and six subsurface sediment samples were collected from the iodine-affected area of Datong basin in northern China to conduct batch experiments and to evaluate the effects of NOM and/or organic-mineral complexes on iodide/iodate geochemical behaviors. The results showed that both iodine contents and kf-iodate values had positive correlations with solid TOC contents, implying the potential host of NOM for iodine in soil/sediment samples. The results of chemical removal of easily extracted NOM indicated that the NOM of surface soils is mainly composed of surface embedded organic matter, while sediment NOM mainly occurs in the form of organic-mineral complexes. After the removal of surface sorbed NOM, the decrease in kf-iodate value of treated surface soils indicates that surface sorbed NOM enhances iodate adsorption onto surface soil. By contrast, kf-iodate value increases in several H2O2-treated sediment samples, which was considered to result from exposed rod-like minerals rich in Fe/Al oxyhydroxide/oxides. After chemical removal of organic-mineral complexes, the lowest kf-iodate value for both treated surface soils and sediments suggests the dominant role of organic-mineral complexes on controlling the iodate geochemical behavior. In comparison with iodate, iodide exhibited lower affinities on all (un)treated soil/sediment samples. The understanding of different geochemical behaviors of iodine species helps to explain the occurrence of high iodine groundwater with iodate and iodide as the main species in shallow (oxidizing conditions) and deep (reducing conditions) groundwater.

Towards a unified study of extreme events using universality concepts and transdisciplinary analysis methods

NASA Astrophysics Data System (ADS)

Balasis, George; Donner, Reik V.; Donges, Jonathan F.; Radebach, Alexander; Eftaxias, Konstantinos; Kurths, Jürgen

2013-04-01

The dynamics of many complex systems is characterized by the same universal principles. In particular, systems which are otherwise quite different in nature show striking similarities in their behavior near tipping points (bifurcations, phase transitions, sudden regime shifts) and associated extreme events. Such critical phenomena are frequently found in diverse fields such as climate, seismology, or financial markets. Notably, the observed similarities include a high degree of organization, persistent behavior, and accelerated energy release, which are common to (among others) phenomena related to geomagnetic variability of the terrestrial magnetosphere (intense magnetic storms), seismic activity (electromagnetic emissions prior to earthquakes), solar-terrestrial physics (solar flares), neurophysiology (epileptic seizures), and socioeconomic systems (stock market crashes). It is an open question whether the spatial and temporal complexity associated with extreme events arises from the system's structural organization (geometry) or from the chaotic behavior inherent to the nonlinear equations governing the dynamics of these phenomena. On the one hand, the presence of scaling laws associated with earthquakes and geomagnetic disturbances suggests understanding these events as generalized phase transitions similar to nucleation and critical phenomena in thermal and magnetic systems. On the other hand, because of the structural organization of the systems (e.g., as complex networks) the associated spatial geometry and/or topology of interactions plays a fundamental role in the emergence of extreme events. Here, a few aspects of the interplay between geometry and dynamics (critical phase transitions) that could result in the emergence of extreme events, which is an open problem, will be discussed.

Characteristics of pattern formation and evolution in approximations of Physarum transport networks.

PubMed

Jones, Jeff

2010-01-01

Most studies of pattern formation place particular emphasis on its role in the development of complex multicellular body plans. In simpler organisms, however, pattern formation is intrinsic to growth and behavior. Inspired by one such organism, the true slime mold Physarum polycephalum, we present examples of complex emergent pattern formation and evolution formed by a population of simple particle-like agents. Using simple local behaviors based on chemotaxis, the mobile agent population spontaneously forms complex and dynamic transport networks. By adjusting simple model parameters, maps of characteristic patterning are obtained. Certain areas of the parameter mapping yield particularly complex long term behaviors, including the circular contraction of network lacunae and bifurcation of network paths to maintain network connectivity. We demonstrate the formation of irregular spots and labyrinthine and reticulated patterns by chemoattraction. Other Turing-like patterning schemes were obtained by using chemorepulsion behaviors, including the self-organization of regular periodic arrays of spots, and striped patterns. We show that complex pattern types can be produced without resorting to the hierarchical coupling of reaction-diffusion mechanisms. We also present network behaviors arising from simple pre-patterning cues, giving simple examples of how the emergent pattern formation processes evolve into networks with functional and quasi-physical properties including tensionlike effects, network minimization behavior, and repair to network damage. The results are interpreted in relation to classical theories of biological pattern formation in natural systems, and we suggest mechanisms by which emergent pattern formation processes may be used as a method for spatially represented unconventional computation.

Preparation and luminescence properties of organogel doped with Eu(TTA)3phen complex

NASA Astrophysics Data System (ADS)

Cocca, M.; Di Lorenzo, M. L.; Avella, M.; Gentile, G.; Aubouy, L.; Della Pirreira, M.; Gutiérrez-Tauste, D.; Kennedy, M.; Doran, J.; Norton, B.

2012-07-01

In this contribution we report the preparation and the luminescence property of Eu(TTA)3phen complex doped toluene gels. Gels were prepared by using either a low molecular weight gelator, 12-hydroxystearic acid (HSA), or a macromolecular gelator, syndiotactic polymethylmethacrylate (s-PMMA). The gelation properties and their reversible behavior from solid-like to liquid systems have been investigated. In addition, photophysical investigations, as well as morphology, thermal properties and ageing behavior of the gels were analyzed as a function of composition of the gels.

Robot, computer problem solving system

NASA Technical Reports Server (NTRS)

Becker, J. D.

1972-01-01

The development of a computer problem solving system is reported that considers physical problems faced by an artificial robot moving around in a complex environment. Fundamental interaction constraints with a real environment are simulated for the robot by visual scan and creation of an internal environmental model. The programming system used in constructing the problem solving system for the simulated robot and its simulated world environment is outlined together with the task that the system is capable of performing. A very general framework for understanding the relationship between an observed behavior and an adequate description of that behavior is included.

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

NASA Astrophysics Data System (ADS)

Zhang, Yali; Wang, Jun

2017-09-01

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

Folding Behaviors of Protein (Lysozyme) Confined in Polyelectrolyte Complex Micelle.

PubMed

Wu, Fu-Gen; Jiang, Yao-Wen; Chen, Zhan; Yu, Zhi-Wu

2016-04-19

The folding/unfolding behavior of proteins (enzymes) in confined space is important for their properties and functions, but such a behavior remains largely unexplored. In this article, we reported our finding that lysozyme and a double hydrophilic block copolymer, methoxypoly(ethylene glycol)5K-block-poly(l-aspartic acid sodium salt)10 (mPEG(5K)-b-PLD10), can form a polyelectrolyte complex micelle with a particle size of ∼30 nm, as verified by dynamic light scattering and transmission electron microscopy. The unfolding and refolding behaviors of lysozyme molecules in the presence of the copolymer were studied by microcalorimetry and circular dichroism spectroscopy. Upon complex formation with mPEG(5K)-b-PLD10, lysozyme changed from its initial native state to a new partially unfolded state. Compared with its native state, this copolymer-complexed new folding state of lysozyme has different secondary and tertiary structures, a decreased thermostability, and significantly altered unfolding/refolding behaviors. It was found that the native lysozyme exhibited reversible unfolding and refolding upon heating and subsequent cooling, while lysozyme in the new folding state (complexed with the oppositely charged PLD segments of the polymer) could unfold upon heating but could not refold upon subsequent cooling. By employing the heating-cooling-reheating procedure, the prevention of complex formation between lysozyme and polymer due to the salt screening effect was observed, and the resulting uncomplexed lysozyme regained its proper unfolding and refolding abilities upon heating and subsequent cooling. Besides, we also pointed out the important role the length of the PLD segment played during the formation of micelles and the monodispersity of the formed micelles. Furthermore, the lysozyme-mPEG(5K)-b-PLD10 mixtures prepared in this work were all transparent, without the formation of large aggregates or precipitates in solution as frequently observed in other protein-polyelectrolyte systems. Hence, the present protein-PEGylated poly(amino acid) mixture provides an ideal water-soluble model system to study the important role of electrostatic interaction in the complexation between proteins and polymers, leading to important new knowledge on the protein-polymer interactions. Moreover, the polyelectrolyte complex micelle formed between protein and PEGylated polymer may provide a good drug delivery vehicle for therapeutic proteins.

Robustness of critical points in a complex adaptive system: Effects of hedge behavior

NASA Astrophysics Data System (ADS)

Liang, Yuan; Huang, Ji-Ping

2013-08-01

In our recent papers, we have identified a class of phase transitions in the market-directed resource-allocation game, and found that there exists a critical point at which the phase transitions occur. The critical point is given by a certain resource ratio. Here, by performing computer simulations and theoretical analysis, we report that the critical point is robust against various kinds of human hedge behavior where the numbers of herds and contrarians can be varied widely. This means that the critical point can be independent of the total number of participants composed of normal agents, herds and contrarians, under some conditions. This finding means that the critical points we identified in this complex adaptive system (with adaptive agents) may also be an intensive quantity, similar to those revealed in traditional physical systems (with non-adaptive units).

High-performance execution of psychophysical tasks with complex visual stimuli in MATLAB

PubMed Central

Asaad, Wael F.; Santhanam, Navaneethan; McClellan, Steven

2013-01-01

Behavioral, psychological, and physiological experiments often require the ability to present sensory stimuli, monitor and record subjects' responses, interface with a wide range of devices, and precisely control the timing of events within a behavioral task. Here, we describe our recent progress developing an accessible and full-featured software system for controlling such studies using the MATLAB environment. Compared with earlier reports on this software, key new features have been implemented to allow the presentation of more complex visual stimuli, increase temporal precision, and enhance user interaction. These features greatly improve the performance of the system and broaden its applicability to a wider range of possible experiments. This report describes these new features and improvements, current limitations, and quantifies the performance of the system in a real-world experimental setting. PMID:23034363

Effects of Task Complexity on L2 Writing Behaviors and Linguistic Complexity

ERIC Educational Resources Information Center

Révész, Andrea; Kourtali, Nektaria-Efstathia; Mazgutova, Diana

2017-01-01

This study investigated whether task complexity influences second language (L2) writers' fluency, pausing, and revision behaviors and the cognitive processes underlying these behaviors; whether task complexity affects linguistic complexity of written output; and whether relationships between writing behaviors and linguistic complexity are…

Automating Network Node Behavior Characterization by Mining Communication Patterns

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

Carroll, Thomas E.; Chikkagoudar, Satish; Arthur-Durett, Kristine M.

Enterprise networks of scale are complex, dynamic computing environments that respond to evolv- ing business objectives and requirements. Characteriz- ing system behaviors in these environments is essential for network management and cyber security operations. Characterization of system’s communication is typical and is supported using network flow information (NetFlow). Related work has characterized behavior using theoretical graph metrics; results are often difficult to interpret by enterprise staff. We propose a different approach, where flow information is mapped to sets of tags that contextualize the data in terms of network principals and enterprise concepts. Frequent patterns are then extracted and are expressedmore » as behaviors. Behaviors can be com- pared, identifying systems expressing similar behaviors. We evaluate the approach using flow information collected by a third party.« less

Dopamine signaling in reward-related behaviors.

PubMed

Baik, Ja-Hyun

2013-01-01

Dopamine (DA) regulates emotional and motivational behavior through the mesolimbic dopaminergic pathway. Changes in DA mesolimbic neurotransmission have been found to modify behavioral responses to various environmental stimuli associated with reward behaviors. Psychostimulants, drugs of abuse, and natural reward such as food can cause substantial synaptic modifications to the mesolimbic DA system. Recent studies using optogenetics and DREADDs, together with neuron-specific or circuit-specific genetic manipulations have improved our understanding of DA signaling in the reward circuit, and provided a means to identify the neural substrates of complex behaviors such as drug addiction and eating disorders. This review focuses on the role of the DA system in drug addiction and food motivation, with an overview of the role of D1 and D2 receptors in the control of reward-associated behaviors.

LOGAM (Logistic Analysis Model). Volume 2. Users Manual.

DTIC Science & Technology

1982-08-01

as opposed to simulation models which represent a system’s behavior as a function of time. These latter classes of models are often complex. They...includes the cost of ammunition and missiles comsumed by the system being costed during unit training. Excluded is the cost of ammunition consumed during...data. The results obtained from sensitivity testing may be used to construct graphs which display the behavior of the maintenance concept over the range

Structure, Behavior, Function as a Framework For Teaching and Learning about Complexity In Ecosystems: Lessons from Middle School Classrooms (Invited)

NASA Astrophysics Data System (ADS)

Hmelo-Silver, C.; Gray, S.; Jordan, R.

2010-12-01

Complex systems surround us, and as Sabelli (2006) has argued, understanding complex systems is a critical component of science literacy. Understanding natural and designed systems are also prominent in the new draft science standards (NRC, 2010) and therefore of growing importance in the science classroom. Our work has focused on promoting an understanding of one complex natural system, aquatic ecosystems, which given current events, is fast becoming a requisite for informed decision-making as citizens (Jordan et al. 2008). Learners have difficulty understanding many concepts related to complex natural systems (e.g., Hmelo-Silver, Marathe, & Liu, 2007; Jordan, Gray, Liu, Demeter, & Hmelo-Silver, 2009). Studies of how students think about complex ecological systems (e.g; Hmelo-Silver, Marathe, & Liu, 2007; Hogan, 2000, Hogan & Fisherkeller, 1996: Covitt & Gunkel, 2008) have revealed difficulties in thinking beyond linear flow, single causality, and visible structure. Helping students to learn about ecosystems is a complex task that requires providing opportunities for students to not only engage directly with ecosystems but also with resources that provide relevant background knowledge and opportunities for learners to make their thinking visible. Both tasks can be difficult given the large spatial and temporal scales on which ecosystems operate. Additionally, visible components interact with often invisible components which can obscure ecosystem processes for students. Working in the context of aquatic ecosystems, we sought to provide learners with representations and simulations that make salient the relationship between system components. In particular, we provided learners with opportunities to experience both the micro-level and macro-level phenomena that are key to understanding ecosystems (Hmelo-Silver, Liu, Gray, & Jordan, submitted; Liu & Hmelo-Silver, 2008; Jacobson & Wilensky, 2006). To accomplish this, we needed to help learners make connections across the levels of ecosystems. A big part of this is making phenomena accessible to their experience. We accomplished through the use of physical models and computers simulations at different scale. In an effort to promote a coherent understanding in our learners, we sought to develop tools that can provide dynamic feedback that will enable them to modify, enrich, and repair their mental models as needed (e.g., Roschelle, 1996). Additionally, we also wanted to develop a conceptual representation that can be used across multiple ecosystems to prepare students to learn about new systems in the future (Bransford & Schwartz, 1999). Our approach to this has been to use the structure-behavior-function (SBF) conceptual representation (Liu & Hmelo-Silver, 2009; Vattam et al., in press). Often, learning life science is about learning the names of structures. One of our design principles is to ensure instruction emphasizes the behaviors (or mechanisms) of systems as well as the functions (the system outputs) in addition to the structures. We have used simulations to help make behaviors and functions visible and a modeling tool that supports students in thinking about the SBF conceptual representation. In this presentation, we will report on the results of classroom interventions and the lessons learned.

Metaphors to Drive By: Exploring New Ways to Guide Human-Robot Interaction

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

David J. Bruemmer; David I. Gertman; Curtis W. Nielsen

2007-08-01

Autonomous behaviors created by the research and development community are not being extensively utilized within energy, defense, security, or industrial contexts. This paper provides evidence that the interaction methods used alongside these behaviors may not provide a mental model that can be easily adopted or used by operators. Although autonomy has the potential to reduce overall workload, the use of robot behaviors often increased the complexity of the underlying interaction metaphor. This paper reports our development of new metaphors that support increased robot complexity without passing the complexity of the interaction onto the operator. Furthermore, we illustrate how recognition ofmore » problems in human-robot interactions can drive the creation of new metaphors for design and how human factors lessons in usability, human performance, and our social contract with technology have the potential for enormous payoff in terms of establishing effective, user-friendly robot systems when appropriate metaphors are used.« less

Behavioral Mapless Navigation Using Rings

NASA Technical Reports Server (NTRS)

Monroe, Randall P.; Miller, Samuel A.; Bradley, Arthur T.

2012-01-01

This paper presents work on the development and implementation of a novel approach to robotic navigation. In this system, map-building and localization for obstacle avoidance are discarded in favor of moment-by-moment behavioral processing of the sonar sensor data. To accomplish this, we developed a network of behaviors that communicate through the passing of rings, data structures that are similar in form to the sonar data itself and express the decisions of each behavior. Through the use of these rings, behaviors can moderate each other, conflicting impulses can be mediated, and designers can easily connect modules to create complex emergent navigational techniques. We discuss the development of a number of these modules and their successful use as a navigation system in the Trinity omnidirectional robot.

Four Single-Page Learning Models.

ERIC Educational Resources Information Center

Hlynka, Denis

1979-01-01

Identifies four models of single-page learning systems that can streamline lengthy, complex prose: Information Mapping, Focal Press Model, Behavioral Objectives Model, and School Mathematics Model. (CMV)

Thermodynamics aspects of noise-induced phase synchronization

NASA Astrophysics Data System (ADS)

Pinto, Pedro D.; Oliveira, Fernando A.; Penna, André L. A.

2016-05-01

In this article, we present an approach for the thermodynamics of phase oscillators induced by an internal multiplicative noise. We analytically derive the free energy, entropy, internal energy, and specific heat. In this framework, the formulation of the first law of thermodynamics requires the definition of a synchronization field acting on the phase oscillators. By introducing the synchronization field, we have consistently obtained the susceptibility and analyzed its behavior. This allows us to characterize distinct phases in the system, which we have denoted as synchronized and parasynchronized phases, in analogy with magnetism. The system also shows a rich complex behavior, exhibiting ideal gas characteristics for low temperatures and susceptibility anomalies that are similar to those present in complex fluids such as water.

Thermodynamics aspects of noise-induced phase synchronization.

PubMed

Pinto, Pedro D; Oliveira, Fernando A; Penna, André L A

2016-05-01

In this article, we present an approach for the thermodynamics of phase oscillators induced by an internal multiplicative noise. We analytically derive the free energy, entropy, internal energy, and specific heat. In this framework, the formulation of the first law of thermodynamics requires the definition of a synchronization field acting on the phase oscillators. By introducing the synchronization field, we have consistently obtained the susceptibility and analyzed its behavior. This allows us to characterize distinct phases in the system, which we have denoted as synchronized and parasynchronized phases, in analogy with magnetism. The system also shows a rich complex behavior, exhibiting ideal gas characteristics for low temperatures and susceptibility anomalies that are similar to those present in complex fluids such as water.

Computation of the spectrum of spatial Lyapunov exponents for the spatially extended beam-plasma systems and electron-wave devices

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

Hramov, Alexander E.; Saratov State Technical University, Politechnicheskaja str., 77, Saratov 410054; Koronovskii, Alexey A.

2012-08-15

The spectrum of Lyapunov exponents is powerful tool for the analysis of the complex system dynamics. In the general framework of nonlinear dynamics, a number of the numerical techniques have been developed to obtain the spectrum of Lyapunov exponents for the complex temporal behavior of the systems with a few degree of freedom. Unfortunately, these methods cannot be applied directly to analysis of complex spatio-temporal dynamics of plasma devices which are characterized by the infinite phase space, since they are the spatially extended active media. In the present paper, we propose the method for the calculation of the spectrum ofmore » the spatial Lyapunov exponents (SLEs) for the spatially extended beam-plasma systems. The calculation technique is applied to the analysis of chaotic spatio-temporal oscillations in three different beam-plasma model: (1) simple plasma Pierce diode, (2) coupled Pierce diodes, and (3) electron-wave system with backward electromagnetic wave. We find an excellent agreement between the system dynamics and the behavior of the spectrum of the spatial Lyapunov exponents. Along with the proposed method, the possible problems of SLEs calculation are also discussed. It is shown that for the wide class of the spatially extended systems, the set of quantities included in the system state for SLEs calculation can be reduced using the appropriate feature of the plasma systems.« less

Ethanol-Induced Effects on Sting Extension Response and Punishment Learning in the Western Honey Bee (Apis mellifera)

PubMed Central

Giannoni-Guzmán, Manuel A.; Giray, Tugrul; Agosto-Rivera, Jose Luis; Stevison, Blake K.; Freeman, Brett; Ricci, Paige; Brown, Erika A.; Abramson, Charles I.

2014-01-01

Acute ethanol administration is associated with sedation and analgesia as well as behavioral disinhibition and memory loss but the mechanisms underlying these effects remain to be elucidated. During the past decade, insects have emerged as important model systems to understand the neural and genetic bases of alcohol effects. However, novel assays to assess ethanol's effects on complex behaviors in social or isolated contexts are necessary. Here we used the honey bee as an especially relevant model system since bees are typically exposed to ethanol in nature when collecting standing nectar crop of flowers, and there is recent evidence for independent biological significance of this exposure for social behavior. Bee's inhibitory control of the sting extension response (SER) and a conditioned-place aversion assay were used to study ethanol effects on analgesia, behavioral disinhibition, and associative learning. Our findings indicate that although ethanol, in a dose-dependent manner, increases SER thresholds (analgesic effects), it disrupts the ability of honey bees to inhibit SER and to associate aversive stimuli with their environment. These results suggest that ethanol's effects on analgesia, behavioral disinhibition and associative learning are common across vertebrates and invertebrates. These results add to the use of honey bees as an ethanol model to understand ethanol's effects on complex, socially relevant behaviors. PMID:24988309

Internest food sharing within wood ant colonies: resource redistribution behavior in a complex system

PubMed Central

Robinson, Elva J.H.

2016-01-01

Resource sharing is an important cooperative behavior in many animals. Sharing resources is particularly important in social insect societies, as division of labor often results in most individuals including, importantly, the reproductives, relying on other members of the colony to provide resources. Sharing resources between individuals is therefore fundamental to the success of social insects. Resource sharing is complicated if a colony inhabits several spatially separated nests, a nesting strategy common in many ant species. Resources must be shared not only between individuals in a single nest but also between nests. We investigated the behaviors facilitating resource redistribution between nests in a dispersed-nesting population of wood ant Formica lugubris. We marked ants, in the field, as they transported resources along the trails between nests of a colony, to investigate how the behavior of individual workers relates to colony-level resource exchange. We found that workers from a particular nest “forage” to other nests in the colony, treating them as food sources. Workers treating other nests as food sources means that simple, pre-existing foraging behaviors are used to move resources through a distributed system. It may be that this simple behavioral mechanism facilitates the evolution of this complex life-history strategy. PMID:27004016

The game-theoretic national interstate economic model : an integrated framework to quantify the economic impacts of cyber-terrorist behavior.

DOT National Transportation Integrated Search

2014-12-01

This study suggests an integrated framework to quantify cyber attack impacts on the U.S. airport security system. A cyber attack by terrorists on the U.S. involves complex : strategic behavior by the terrorists because they could plan to invade an ai...

Assessment of electrical conductivity as a surrogate measurement for water samples in a tracer injection experiment

USDA-ARS?s Scientific Manuscript database

The transport behavior of solutes in streams depends on chemical, physical, biological, and hydrodynamic processes. Although it is a very complex system, it is known that this behavior is greatly influenced by surface and subsurface flows. For this reason, tracer injection in the water flows is one ...

Nonlinear dynamics behavior analysis of the spatial configuration of a tendril-bearing plant

NASA Astrophysics Data System (ADS)

Feng, Jingjing; Zhang, Qichang; Wang, Wei; Hao, Shuying

2017-03-01

Tendril-bearing plants appear to have a spiraling shape when tendrils climb along a support during growth. The growth characteristics of a tendril-bearer can be simplified to a model of a thin elastic rod with a cylindrical constraint. In this paper, the connection between some typical configuration characteristics of tendrils and complex nonlinear dynamic behavior are qualitatively analyzed. The space configuration problem of tendrils can be explained through the study of the nonlinear dynamic behavior of the thin elastic rod system equation. In this study, the complex non-Z2 symmetric critical orbits in the system equation under critical parameters were presented. A new function transformation method that can effectively maintain the critical orbit properties was proposed, and a new nonlinear differential equations system containing complex nonlinear terms can been obtained to describe the cross section position and direction of a rod during climbing. Numerical simulation revealed that the new system can describe the configuration of a rod with reasonable accuracy. To adequately explain the growing regulation of the rod shape, the critical orbit and configuration of rod are connected in a direct way. The high precision analytical expressions of these complex non-Z2 symmetric critical orbits are obtained by introducing a suitable analytical method, and then these expressions are used to draw the corresponding three-dimensional configuration figures of an elastic thin rod. Combined with actual tendrils on a live plant, the space configuration of the winding knots of tendril is explained by the concept of heteroclinic orbit from the perspective of nonlinear dynamics, and correctness of the theoretical analysis was verified. This theoretical analysis method could also be effectively applied to other similar slender structures.

Micro-Macro Analysis of Complex Networks

PubMed Central

Marchiori, Massimo; Possamai, Lino

2015-01-01

Complex systems have attracted considerable interest because of their wide range of applications, and are often studied via a “classic” approach: study a specific system, find a complex network behind it, and analyze the corresponding properties. This simple methodology has produced a great deal of interesting results, but relies on an often implicit underlying assumption: the level of detail on which the system is observed. However, in many situations, physical or abstract, the level of detail can be one out of many, and might also depend on intrinsic limitations in viewing the data with a different level of abstraction or precision. So, a fundamental question arises: do properties of a network depend on its level of observability, or are they invariant? If there is a dependence, then an apparently correct network modeling could in fact just be a bad approximation of the true behavior of a complex system. In order to answer this question, we propose a novel micro-macro analysis of complex systems that quantitatively describes how the structure of complex networks varies as a function of the detail level. To this extent, we have developed a new telescopic algorithm that abstracts from the local properties of a system and reconstructs the original structure according to a fuzziness level. This way we can study what happens when passing from a fine level of detail (“micro”) to a different scale level (“macro”), and analyze the corresponding behavior in this transition, obtaining a deeper spectrum analysis. The obtained results show that many important properties are not universally invariant with respect to the level of detail, but instead strongly depend on the specific level on which a network is observed. Therefore, caution should be taken in every situation where a complex network is considered, if its context allows for different levels of observability. PMID:25635812

Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

DOE PAGES

Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

2015-02-14

Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equationsmore » at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.« less

A comparison of thermoelectric phenomena in diverse alloy systems

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

Cook, Bruce

1999-01-01

The study of thermoelectric phenomena in solids provides a wealth of opportunity for exploration of the complex interrelationships between structure, processing, and properties of materials. As thermoelectricity implies some type of coupled thermal and electrical behavior, it is expected that a basic understanding of transport behavior in materials is the goal of such a study. However, transport properties such as electrical resistivity and thermal diffusivity cannot be fully understood and interpreted without first developing an understanding of the material's preparation and its underlying structure. It is the objective of this dissertation to critically examine a number of diverse systems inmore » order to develop a broad perspective on how structure-processing-property relationships differ from system to system, and to discover the common parameters upon which any good thermoelectric material is based. The alloy systems examined in this work include silicon-germanium, zinc oxide, complex intermetallic compounds such as the half-Heusler MNiSn, where M = Ti, Zr, or Hf, and rare earth chalcogenides.« less

Diet and Energy-Sensing Inputs Affect TorC1-Mediated Axon Misrouting but Not TorC2-Directed Synapse Growth in a Drosophila Model of Tuberous Sclerosis

PubMed Central

Dimitroff, Brian; Lee, Hyun-Gwan; Zhao, Na; O'Connor, Michael B.; Neufeld, Thomas P.; Selleck, Scott B.

2012-01-01

The Target of Rapamycin (TOR) growth regulatory system is influenced by a number of different inputs, including growth factor signaling, nutrient availability, and cellular energy levels. While the effects of TOR on cell and organismal growth have been well characterized, this pathway also has profound effects on neural development and behavior. Hyperactivation of the TOR pathway by mutations in the upstream TOR inhibitors TSC1 (tuberous sclerosis complex 1) or TSC2 promotes benign tumors and neurological and behavioral deficits, a syndrome known as tuberous sclerosis (TS). In Drosophila, neuron-specific overexpression of Rheb, the direct downstream target inhibited by Tsc1/Tsc2, produced significant synapse overgrowth, axon misrouting, and phototaxis deficits. To understand how misregulation of Tor signaling affects neural and behavioral development, we examined the influence of growth factor, nutrient, and energy sensing inputs on these neurodevelopmental phenotypes. Neural expression of Pi3K, a principal mediator of growth factor inputs to Tor, caused synapse overgrowth similar to Rheb, but did not disrupt axon guidance or phototaxis. Dietary restriction rescued Rheb-mediated behavioral and axon guidance deficits, as did overexpression of AMPK, a component of the cellular energy sensing pathway, but neither was able to rescue synapse overgrowth. While axon guidance and behavioral phenotypes were affected by altering the function of a Tor complex 1 (TorC1) component, Raptor, or a TORC1 downstream element (S6k), synapse overgrowth was only suppressed by reducing the function of Tor complex 2 (TorC2) components (Rictor, Sin1). These findings demonstrate that different inputs to Tor signaling have distinct activities in nervous system development, and that Tor provides an important connection between nutrient-energy sensing systems and patterning of the nervous system. PMID:22319582

The Results of Complex Research of GSS "SBIRS-Geo 2" Behavior in the Orbit

NASA Astrophysics Data System (ADS)

Sukhov, P. P.; Epishev, V. P.; Sukhov, K. P.; Karpenko, G. F.; Motrunich, I. I.

2017-04-01

The new generation of geosynchronous satellites SBIRS of US Air Force early warning system series (Satellite Early Warning System) replaced the previous DSP-satellite series (Defense Support Program). Currently from the territory of Ukraine, several GSS of DSP series and one "SBIRS-Geo 2" are available to observation. During two years of observations, we have received and analyzed for two satellites more than 30 light curves in B, V, R photometric system. As a result of complex research, we propose a model of "SBIRS-Geo" 2 orbital behavior compared with the same one of the DSP-satellite. To control the entire surface of the Earth with 15-16 sec interval, including the polar regions, 4 SBIRS satellites located every 90 deg. along the equator are enough in GEO orbit. Since DSP-satellites provide the coverage of the Earth's surface to 83 deg. latitudes with a period of 50 sec, DSP-satellites should be 8. All the conclusions were made based on an analysis of photometric and coordinate observations using the simulation of the dynamics of their orbital behavior.

A Qualitative Model of Human Interaction with Complex Dynamic Systems

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1987-01-01

A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.

A qualitative model of human interaction with complex dynamic systems

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1987-01-01

A qualitative model describing human interaction with complex dynamic systems is developed. The model is hierarchical in nature and consists of three parts: a behavior generator, an internal model, and a sensory information processor. The behavior generator is responsible for action decomposition, turning higher level goals or missions into physical action at the human-machine interface. The internal model is an internal representation of the environment which the human is assumed to possess and is divided into four submodel categories. The sensory information processor is responsible for sensory composition. All three parts of the model act in consort to allow anticipatory behavior on the part of the human in goal-directed interaction with dynamic systems. Human workload and error are interpreted in this framework, and the familiar example of an automobile commute is used to illustrate the nature of the activity in the three model elements. Finally, with the qualitative model as a guide, verbal protocols from a manned simulation study of a helicopter instrument landing task are analyzed with particular emphasis on the effect of automation on human-machine performance.

Complexity and multifractal behaviors of multiscale-continuum percolation financial system for Chinese stock markets

NASA Astrophysics Data System (ADS)

Zeng, Yayun; Wang, Jun; Xu, Kaixuan

2017-04-01

A new financial agent-based time series model is developed and investigated by multiscale-continuum percolation system, which can be viewed as an extended version of continuum percolation system. In this financial model, for different parameters of proportion and density, two Poisson point processes (where the radii of points represent the ability of receiving or transmitting information among investors) are applied to model a random stock price process, in an attempt to investigate the fluctuation dynamics of the financial market. To validate its effectiveness and rationality, we compare the statistical behaviors and the multifractal behaviors of the simulated data derived from the proposed model with those of the real stock markets. Further, the multiscale sample entropy analysis is employed to study the complexity of the returns, and the cross-sample entropy analysis is applied to measure the degree of asynchrony of return autocorrelation time series. The empirical results indicate that the proposed financial model can simulate and reproduce some significant characteristics of the real stock markets to a certain extent.

Serendipitous Offline Learning in a Neuromorphic Robot.

PubMed

Stewart, Terrence C; Kleinhans, Ashley; Mundy, Andrew; Conradt, Jörg

2016-01-01

We demonstrate a hybrid neuromorphic learning paradigm that learns complex sensorimotor mappings based on a small set of hard-coded reflex behaviors. A mobile robot is first controlled by a basic set of reflexive hand-designed behaviors. All sensor data is provided via a spike-based silicon retina camera (eDVS), and all control is implemented via spiking neurons simulated on neuromorphic hardware (SpiNNaker). Given this control system, the robot is capable of simple obstacle avoidance and random exploration. To train the robot to perform more complex tasks, we observe the robot and find instances where the robot accidentally performs the desired action. Data recorded from the robot during these times is then used to update the neural control system, increasing the likelihood of the robot performing that task in the future, given a similar sensor state. As an example application of this general-purpose method of training, we demonstrate the robot learning to respond to novel sensory stimuli (a mirror) by turning right if it is present at an intersection, and otherwise turning left. In general, this system can learn arbitrary relations between sensory input and motor behavior.

Bioreactivity: Studies on a Simple Brain Stem Reflex in Behaving Animals

DTIC Science & Technology

1988-07-22

neuromodulation , or complex behavioral processes, such as arousal, is finding a simple system that will permit such analyses. The brain stem...systems important in neuromodulation and arousal. Initial pharmacologic studies showed that locally applied norepinephrine facilitated the reflex

Normal people working in normal organizations with normal equipment: system safety and cognition in a mid-air collision.

PubMed

de Carvalho, Paulo Victor Rodrigues; Gomes, José Orlando; Huber, Gilbert Jacob; Vidal, Mario Cesar

2009-05-01

A fundamental challenge in improving the safety of complex systems is to understand how accidents emerge in normal working situations, with equipment functioning normally in normally structured organizations. We present a field study of the en route mid-air collision between a commercial carrier and an executive jet, in the clear afternoon Amazon sky in which 154 people lost their lives, that illustrates one response to this challenge. Our focus was on how and why the several safety barriers of a well structured air traffic system melted down enabling the occurrence of this tragedy, without any catastrophic component failure, and in a situation where everything was functioning normally. We identify strong consistencies and feedbacks regarding factors of system day-to-day functioning that made monitoring and awareness difficult, and the cognitive strategies that operators have developed to deal with overall system behavior. These findings emphasize the active problem-solving behavior needed in air traffic control work, and highlight how the day-to-day functioning of the system can jeopardize such behavior. An immediate consequence is that safety managers and engineers should review their traditional safety approach and accident models based on equipment failure probability, linear combinations of failures, rules and procedures, and human errors, to deal with complex patterns of coincidence possibilities, unexpected links, resonance among system functions and activities, and system cognition.

Interactive specification acquisition via scenarios: A proposal

NASA Technical Reports Server (NTRS)

Hall, Robert J.

1992-01-01

Some reactive systems are most naturally specified by giving large collections of behavior scenarios. These collections not only specify the behavior of the system, but also provide good test suites for validating the implemented system. Due to the complexity of the systems and the number of scenarios, however, it appears that automated assistance is necessary to make this software development process workable. Interactive Specification Acquisition Tool (ISAT) is a proposed interactive system for supporting the acquisition and maintenance of a formal system specification from scenarios, as well as automatic synthesis of control code and automated test generation. This paper discusses the background, motivation, proposed functions, and implementation status of ISAT.

Informing Biological Design by Integration of Systems and Synthetic Biology

PubMed Central

Smolke, Christina D.; Silver, Pamela A.

2011-01-01

Synthetic biology aims to make the engineering of biology faster and more predictable. In contrast, systems biology focuses on the interaction of myriad components and how these give rise to the dynamic and complex behavior of biological systems. Here, we examine the synergies between these two fields. PMID:21414477

Deterministic chaos and fractal complexity in the dynamics of cardiovascular behavior: perspectives on a new frontier.

PubMed

Sharma, Vijay

2009-09-10

Physiological systems such as the cardiovascular system are capable of five kinds of behavior: equilibrium, periodicity, quasi-periodicity, deterministic chaos and random behavior. Systems adopt one or more these behaviors depending on the function they have evolved to perform. The emerging mathematical concepts of fractal mathematics and chaos theory are extending our ability to study physiological behavior. Fractal geometry is observed in the physical structure of pathways, networks and macroscopic structures such the vasculature and the His-Purkinje network of the heart. Fractal structure is also observed in processes in time, such as heart rate variability. Chaos theory describes the underlying dynamics of the system, and chaotic behavior is also observed at many levels, from effector molecules in the cell to heart function and blood pressure. This review discusses the role of fractal structure and chaos in the cardiovascular system at the level of the heart and blood vessels, and at the cellular level. Key functional consequences of these phenomena are highlighted, and a perspective provided on the possible evolutionary origins of chaotic behavior and fractal structure. The discussion is non-mathematical with an emphasis on the key underlying concepts.

Deterministic Chaos and Fractal Complexity in the Dynamics of Cardiovascular Behavior: Perspectives on a New Frontier

PubMed Central

Sharma, Vijay

2009-01-01

Physiological systems such as the cardiovascular system are capable of five kinds of behavior: equilibrium, periodicity, quasi-periodicity, deterministic chaos and random behavior. Systems adopt one or more these behaviors depending on the function they have evolved to perform. The emerging mathematical concepts of fractal mathematics and chaos theory are extending our ability to study physiological behavior. Fractal geometry is observed in the physical structure of pathways, networks and macroscopic structures such the vasculature and the His-Purkinje network of the heart. Fractal structure is also observed in processes in time, such as heart rate variability. Chaos theory describes the underlying dynamics of the system, and chaotic behavior is also observed at many levels, from effector molecules in the cell to heart function and blood pressure. This review discusses the role of fractal structure and chaos in the cardiovascular system at the level of the heart and blood vessels, and at the cellular level. Key functional consequences of these phenomena are highlighted, and a perspective provided on the possible evolutionary origins of chaotic behavior and fractal structure. The discussion is non-mathematical with an emphasis on the key underlying concepts. PMID:19812706

Further Understanding of Complex Information Processing in Verbal Adolescents and Adults with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Williams, Diane L.; Minshew, Nancy J.; Goldstein, Gerald

2015-01-01

More than 20?years ago, Minshew and colleagues proposed the Complex Information Processing model of autism in which the impairment is characterized as a generalized deficit involving multiple modalities and cognitive domains that depend on distributed cortical systems responsible for higher order abilities. Subsequent behavioral work revealed a…

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

PubMed

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

2016-01-01

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

How to identify the most effective control measures based on disease-behavior coupled mechanisms?. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Sun, Gui-Quan; Jin, Zhen

2015-12-01

Modelling infectious diseases on complex networks is a significant tool to understand the transmission of epidemics in human society, and consequently it has commanded increasing attention in the community of mathematicians, physicists, epidemiologists, public health policy-makers and so on [1-4]. Human behavior responses are associated with the emergence of infectious disease, for instance, wearing masks [5], staying away from a thick crowd [6], cutting contacts with infected individuals [7] and receiving a vaccination [8]. However, infectious diseases and human behavior were often modeled as independent systems in the literature, despite the fact that in the real world they are often mutually influential on each other, and hence their coupling exerts significant impacts on disease spread [9,10].

Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems

NASA Technical Reports Server (NTRS)

Terrile, Richard J.; Guillaume, Alexandre

2009-01-01

Over the past several years the Center for Evolutionary Computation and Automated Design at the Jet Propulsion Laboratory has developed a technique based on Evolutionary Computational Methods (ECM) that allows for the automated optimization of complex computationally modeled systems. An important application of this technique is for the identification of emergent behaviors in autonomous systems. Mobility platforms such as rovers or airborne vehicles are now being designed with autonomous mission controllers that can find trajectories over a solution space that is larger than can reasonably be tested. It is critical to identify control behaviors that are not predicted and can have surprising results (both good and bad). These emergent behaviors need to be identified, characterized and either incorporated into or isolated from the acceptable range of control characteristics. We use cluster analysis of automatically retrieved solutions to identify isolated populations of solutions with divergent behaviors.

Quantifying Pilot Visual Attention in Low Visibility Terminal Operations

NASA Technical Reports Server (NTRS)

Ellis, Kyle K.; Arthur, J. J.; Latorella, Kara A.; Kramer, Lynda J.; Shelton, Kevin J.; Norman, Robert M.; Prinzel, Lawrence J.

2012-01-01

Quantifying pilot visual behavior allows researchers to determine not only where a pilot is looking and when, but holds implications for specific behavioral tracking when these data are coupled with flight technical performance. Remote eye tracking systems have been integrated into simulators at NASA Langley with effectively no impact on the pilot environment. This paper discusses the installation and use of a remote eye tracking system. The data collection techniques from a complex human-in-the-loop (HITL) research experiment are discussed; especially, the data reduction algorithms and logic to transform raw eye tracking data into quantified visual behavior metrics, and analysis methods to interpret visual behavior. The findings suggest superior performance for Head-Up Display (HUD) and improved attentional behavior for Head-Down Display (HDD) implementations of Synthetic Vision System (SVS) technologies for low visibility terminal area operations. Keywords: eye tracking, flight deck, NextGen, human machine interface, aviation

POD Model Reconstruction for Gray-Box Fault Detection

NASA Technical Reports Server (NTRS)

Park, Han; Zak, Michail

2007-01-01

Proper orthogonal decomposition (POD) is the mathematical basis of a method of constructing low-order mathematical models for the "gray-box" fault-detection algorithm that is a component of a diagnostic system known as beacon-based exception analysis for multi-missions (BEAM). POD has been successfully applied in reducing computational complexity by generating simple models that can be used for control and simulation for complex systems such as fluid flows. In the present application to BEAM, POD brings the same benefits to automated diagnosis. BEAM is a method of real-time or offline, automated diagnosis of a complex dynamic system.The gray-box approach makes it possible to utilize incomplete or approximate knowledge of the dynamics of the system that one seeks to diagnose. In the gray-box approach, a deterministic model of the system is used to filter a time series of system sensor data to remove the deterministic components of the time series from further examination. What is left after the filtering operation is a time series of residual quantities that represent the unknown (or at least unmodeled) aspects of the behavior of the system. Stochastic modeling techniques are then applied to the residual time series. The procedure for detecting abnormal behavior of the system then becomes one of looking for statistical differences between the residual time series and the predictions of the stochastic model.

Adsorption of Nucleic Acid/Protein Supramolecular Complexes on Goethite: The Influence of Solution Interactions on Behavior at the Solution-Mineral Interface

NASA Astrophysics Data System (ADS)

Schmidt, M.; Martinez, C. E.

2017-12-01

Adsorption of biomolecule rich supramolecular complexes onto mineral surfaces plays an important role in the development of organo-mineral associations in soils. In this study, a series of supramolecular complexes of a model nucleic acid (deoxyribonucleic acid (DNA)) and protein (bovine serum albumin (BSA)) are synthesized, characterized and exposed to goethite to probe their adsorption behavior. To synthesize DNA/BSA complexes, a fixed DNA concentration (0.1 mg/mL) was mixed with a range of BSA concentrations (0.025-0.5 mg/mL) in 5 mM KCl at pH=5.0. Circular dichroism spectroscopy demonstrates strong, cooperative, Hill-type binding between DNA and BSA (Ka= 4.74 x 105 M-1) with DNA saturation achieved when BSA concentration reaches 0.4 mg/mL. Dynamic light scattering measurements of DNA/BSA complexes suggest binding accompanies disruption of DNA-DNA intermolecular electrostatic repulsion, resulting in a decrease of the DNA slow relaxation mode with increasing amount of BSA. Zeta potential measurements show increasing amounts of BSA lead to a reduction of negative charge on DNA/BSA complexes, in line with light scattering results. In situ attenuated total reflectance Fourier transform infrared spectroscopic studies of adsorption of DNA/BSA complexes onto goethite show that complexation of BSA with DNA appears to hinder direct coordination of DNA backbone phosphodiester groups with goethite, relative to DNA by itself. Furthermore, increasing amount of BSA (up to 0.4 mg/mL) in DNA/BSA complexes enhances DNA adsorption, possibly as a result of reduced repulsion between adsorbed DNA helices. When BSA concentration exceeds 0.4 mg/mL, a decrease in adsorbed DNA is observed. We hypothesize that this discrepancy in behavior between systems with BSA concentrations below and above saturation of DNA is caused by initial fast adsorption of loosely associated BSA on goethite, restricting access to goethite surface sites. Overall, these results highlight the impact of solution interaction between biomolecules on subsequent behavior at mineral surfaces. This work represents a bridge between model experiments with individual biomolecules and more complex natural systems, yielding a fundamental viewpoint of the formation of organo-mineral associations in soils.

Variation in mating systems of salamanders: mate guarding or territoriality?

PubMed

Deitloff, Jennifer; Alcorn, Michael A; Graham, Sean P

2014-07-01

Two of the most common mating tactics in vertebrates are mate guarding and territoriality, yet much of the research on these strategies has focused on mating systems in birds, despite novel insights gained from studying less traditional systems. North American stream salamanders that comprise the Eurycea bislineata complex represent an excellent nontraditional system for comparing mating strategies because these species exhibit a continuum of male morphologies, diverse habitat associations, and various potential mating strategies. We studied two species within this complex that exhibit the extremes of this continuum, Eurycea aquatica (robust morph) and Eurycea cirrigera (slender morph). The larger head in males of E. aquatica is due to larger musculature around the jaw and may be associated with aggressive behavior. Therefore, we hypothesized that the robust morphology exhibited by males of E. aquatica provides benefits during either territorial defense or mate defense and that males of E. cirrigera would not exhibit aggression in either scenario. We found that neither species exhibited aggressive behavior to defend a territory. However, in the presence of a female, males of E. aquatica were significantly more aggressive toward intruding males than were males of E. cirrigera. Therefore, mate-guarding behavior occurs in E. aquatica, and the enlarged head of males likely aids in deterring rivals. This is the first demonstration of mate-guarding behavior in a plethodontid, the most speciose family of salamanders. Copyright © 2014 Elsevier B.V. All rights reserved.

Influence of Hydrophobicity on Polyelectrolyte Complexation

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

Sadman, Kazi; Wang, Qifeng; Chen, Yaoyao

Polyelectrolyte complexes are a fascinating class of soft materials that can span the full spectrum of mechanical properties from low viscosity fluids to glassy solids. This spectrum can be accessed by modulating the extent of electrostatic association in these complexes. However, to realize the full potential of polyelectrolyte complexes as functional materials their molecular level details need to be clearly correlated with their mechanical response. The present work demonstrates that by making simple amendments to the chain architecture it is possible to affect the salt responsiveness of polyelectrolyte complexes in a systematic manner. This is achieved by quaternizing poly(4-vinylpyridine) (QVP)more » with methyl, ethyl and propyl substituents– thereby increasing the hydrophobicity with increasing side chain length– and complexing them with a common anionic polyelectrolyte, poly(styrene sulfonate). The mechanical 1 ACS Paragon Plus Environment behavior of these complexes is compared to the more hydrophilic system of poly(styrene sulfonate) and poly(diallyldimethylammonium) by quantifying the swelling behavior in response to salt stimuli. More hydrophobic complexes are found to be more resistant to doping by salt, yet the mechanical properties of the complex remain contingent on the overall swelling ratio of the complex itself, following near universal swelling-modulus master curves that are quantified in this work. The rheological behavior of QVP complex coacervates are found to be approximately the same, only requiring higher salt concentrations to overcome strong hydrophobic interactions, demonstrating that hydrophobicity can be used as an important parameter for tuning the stability of polyelectrolyte complexes in general, while still preserving the ability to be processed “saloplastically”.« less

Influence of Hydrophobicity on Polyelectrolyte Complexation

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

Sadman, Kazi; Wang, Qifeng; Chen, Yaoyao

Polyelectrolyte complexes are a fascinating class of soft materials that can span the full spectrum of mechanical properties from low-viscosity fluids to glassy solids. This spectrum can be accessed by modulating the extent of electrostatic association in these complexes. However, to realize the full potential of polyelectrolyte complexes as functional materials, their molecular level details need to be clearly correlated with their mechanical response. The present work demonstrates that by making simple amendments to the chain architecture, it is possible to affect the salt responsiveness of polyelectrolyte complexes in a systematic manner. This is achieved by quaternizing poly(4-vinylpyridine) (QVP) withmore » methyl, ethyl, and propyl substituents—thereby increasing the hydrophobicity with increasing side chain length—and complexing them with a common anionic polyelectrolyte, poly(styrenesulfonate). The mechanical behavior of these complexes is compared to the more hydrophilic system of poly(styrenesulfonate) and poly(diallyldimethylammonium) by quantifying the swelling behavior in response to salt stimuli. More hydrophobic complexes are found to be more resistant to doping by salt, yet the mechanical properties of the complex remain contingent on the overall swelling ratio of the complex itself, following near universal swelling–modulus master curves that are quantified in this work. Furthermore, the rheological behaviors of QVP complex coacervates are found to be approximately the same, only requiring higher salt concentrations to overcome strong hydrophobic interactions, demonstrating that hydrophobicity can be used as an important parameter for tuning the stability of polyelectrolyte complexes in general, while still preserving the ability to be processed “saloplastically”.« less

Influence of Hydrophobicity on Polyelectrolyte Complexation

DOE PAGES

Sadman, Kazi; Wang, Qifeng; Chen, Yaoyao; ...

2017-11-16

Polyelectrolyte complexes are a fascinating class of soft materials that can span the full spectrum of mechanical properties from low-viscosity fluids to glassy solids. This spectrum can be accessed by modulating the extent of electrostatic association in these complexes. However, to realize the full potential of polyelectrolyte complexes as functional materials, their molecular level details need to be clearly correlated with their mechanical response. The present work demonstrates that by making simple amendments to the chain architecture, it is possible to affect the salt responsiveness of polyelectrolyte complexes in a systematic manner. This is achieved by quaternizing poly(4-vinylpyridine) (QVP) withmore » methyl, ethyl, and propyl substituents—thereby increasing the hydrophobicity with increasing side chain length—and complexing them with a common anionic polyelectrolyte, poly(styrenesulfonate). The mechanical behavior of these complexes is compared to the more hydrophilic system of poly(styrenesulfonate) and poly(diallyldimethylammonium) by quantifying the swelling behavior in response to salt stimuli. More hydrophobic complexes are found to be more resistant to doping by salt, yet the mechanical properties of the complex remain contingent on the overall swelling ratio of the complex itself, following near universal swelling–modulus master curves that are quantified in this work. Furthermore, the rheological behaviors of QVP complex coacervates are found to be approximately the same, only requiring higher salt concentrations to overcome strong hydrophobic interactions, demonstrating that hydrophobicity can be used as an important parameter for tuning the stability of polyelectrolyte complexes in general, while still preserving the ability to be processed “saloplastically”.« less

Size does Matter

NASA Astrophysics Data System (ADS)

Vespignani, Alessandro

From schools of fish and flocks of birds, to digital networks and self-organizing biopolymers, our understanding of spontaneously emergent phenomena, self-organization, and critical behavior is in large part due to complex systems science. The complex systems approach is indeed a very powerful conceptual framework to shed light on the link between the microscopic dynamical evolution of the basic elements of the system and the emergence of oscopic phenomena; often providing evidence for mathematical principles that go beyond the particulars of the individual system, thus hinting to general modeling principles. By killing the myth of the ant queen and shifting the focus on the dynamical interaction across the elements of the systems, complex systems science has ushered our way into the conceptual understanding of many phenomena at the core of major scientific and social challenges such as the emergence of consensus, social opinion dynamics, conflicts and cooperation, contagion phenomena. For many years though, these complex systems approaches to real-world problems were often suffering from being oversimplified and not grounded on actual data...

Profilin2 contributes to synaptic vesicle exocytosis, neuronal excitability, and novelty-seeking behavior

PubMed Central

Pilo Boyl, Pietro; Di Nardo, Alessia; Mulle, Christophe; Sassoè-Pognetto, Marco; Panzanelli, Patrizia; Mele, Andrea; Kneussel, Matthias; Costantini, Vivian; Perlas, Emerald; Massimi, Marzia; Vara, Hugo; Giustetto, Maurizio; Witke, Walter

2007-01-01

Profilins are actin binding proteins essential for regulating cytoskeletal dynamics, however, their function in the mammalian nervous system is unknown. Here, we provide evidence that in mouse brain profilin1 and profilin2 have distinct roles in regulating synaptic actin polymerization with profilin2 preferring a WAVE-complex-mediated pathway. Mice lacking profilin2 show a block in synaptic actin polymerization in response to depolarization, which is accompanied by increased synaptic excitability of glutamatergic neurons due to higher vesicle exocytosis. These alterations in neurotransmitter release correlate with a hyperactivation of the striatum and enhanced novelty-seeking behavior in profilin2 mutant mice. Our results highlight a novel, profilin2-dependent pathway, regulating synaptic physiology, neuronal excitability, and complex behavior. PMID:17541406

Understanding magnetotransport signatures in networks of connected permalloy nanowires

NASA Astrophysics Data System (ADS)

Le, B. L.; Park, J.; Sklenar, J.; Chern, G.-W.; Nisoli, C.; Watts, J. D.; Manno, M.; Rench, D. W.; Samarth, N.; Leighton, C.; Schiffer, P.

2017-02-01

The change in electrical resistance associated with the application of an external magnetic field is known as the magnetoresistance (MR). The measured MR is quite complex in the class of connected networks of single-domain ferromagnetic nanowires, known as "artificial spin ice," due to the geometrically induced collective behavior of the nanowire moments. We have conducted a thorough experimental study of the MR of a connected honeycomb artificial spin ice, and we present a simulation methodology for understanding the detailed behavior of this complex correlated magnetic system. Our results demonstrate that the behavior, even at low magnetic fields, can be well described only by including significant contributions from the vertices at which the legs meet, opening the door to new geometrically induced MR phenomena.

Review—Physicochemical hydrodynamics of gas bubbles in two phase electrochemical systems

PubMed Central

Taqieddin, Amir; Nazari, Roya; Rajic, Ljiljana; Alshawabkeh, Akram

2018-01-01

Electrochemical systems suffer from poor management of evolving gas bubbles. Improved understanding of bubbles behavior helps to reduce overpotential, save energy and enhance the mass transfer during chemical reactions. This work investigates and reviews the gas bubbles hydrodynamics, behavior, and management in electrochemical cells. Although the rate of bubble growth over the electrode surface is well understood, there is no reliable prediction of bubbles break-off diameter from the electrode surface because of the complexity of bubbles motion near the electrode surface. Particle Image Velocimetry (PIV) and Laser Doppler Anemometry (LDA) are the most common experimental techniques to measure bubble dynamics. Although the PIV is faster than LDA, both techniques are considered expensive and time-consuming. This encourages adapting Computational Fluid Dynamics (CFD) methods as an alternative to study bubbles behavior. However, further development of CFD methods is required to include coalescence and break-up of bubbles for better understanding and accuracy. The disadvantages of CFD methods can be overcome by using hybrid methods. The behavior of bubbles in electrochemical systems is still a complex challenging topic which requires a better understanding of the gas bubbles hydrodynamics and their interactions with the electrode surface and bulk liquid, as well as between the bubbles itself. PMID:29731515

What can fish brains tell us about visual perception?

PubMed Central

Rosa Salva, Orsola; Sovrano, Valeria Anna; Vallortigara, Giorgio

2014-01-01

Fish are a complex taxonomic group, whose diversity and distance from other vertebrates well suits the comparative investigation of brain and behavior: in fish species we observe substantial differences with respect to the telencephalic organization of other vertebrates and an astonishing variety in the development and complexity of pallial structures. We will concentrate on the contribution of research on fish behavioral biology for the understanding of the evolution of the visual system. We shall review evidence concerning perceptual effects that reflect fundamental principles of the visual system functioning, highlighting the similarities and differences between distant fish groups and with other vertebrates. We will focus on perceptual effects reflecting some of the main tasks that the visual system must attain. In particular, we will deal with subjective contours and optical illusions, invariance effects, second order motion and biological motion and, finally, perceptual binding of object properties in a unified higher level representation. PMID:25324728

Neonatal Feeding Behavior as a Complex Dynamical System.

PubMed

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

2017-04-01

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

Dynamics and Collapse in a Power System Model with Voltage Variation: The Damping Effect.

PubMed

Ma, Jinpeng; Sun, Yong; Yuan, Xiaoming; Kurths, Jürgen; Zhan, Meng

2016-01-01

Complex nonlinear phenomena are investigated in a basic power system model of the single-machine-infinite-bus (SMIB) with a synchronous generator modeled by a classical third-order differential equation including both angle dynamics and voltage dynamics, the so-called flux decay equation. In contrast, for the second-order differential equation considering the angle dynamics only, it is the classical swing equation. Similarities and differences of the dynamics generated between the third-order model and the second-order one are studied. We mainly find that, for positive damping, these two models show quite similar behavior, namely, stable fixed point, stable limit cycle, and their coexistence for different parameters. However, for negative damping, the second-order system can only collapse, whereas for the third-order model, more complicated behavior may happen, such as stable fixed point, limit cycle, quasi-periodicity, and chaos. Interesting partial collapse phenomena for angle instability only and not for voltage instability are also found here, including collapse from quasi-periodicity and from chaos etc. These findings not only provide a basic physical picture for power system dynamics in the third-order model incorporating voltage dynamics, but also enable us a deeper understanding of the complex dynamical behavior and even leading to a design of oscillation damping in electric power systems.

Dynamics of Complex Systems Built as Coupled Physical, Communication and Decision Layers

PubMed Central

Kühnlenz, Florian; Nardelli, Pedro H. J.

2016-01-01

This paper proposes a simple model to capture the complexity of multilayer systems where their constituent layers affect, and are affected by, each other. The physical layer is a circuit composed by a power source and resistors in parallel. Every individual agent aims at maximizing its own delivered power by adding, removing or keeping the resistors it has; the delivered power is in turn a non-linear function that depends on the other agents’ behavior, its own internal state, its global state perception, the information received from its neighbors via the communication network and a randomized selfishness. We develop an agent-based simulation to analyze the effects of number of agents (system size), communication network topology, communication errors and the minimum power gain that triggers a behavioral change on the system dynamic. Our results show that a wave-like behavior at macro-level (caused by individual changes in the decision layer) can only emerge for a specific system size. The ratio between cooperators and defectors depends on the minimum gain assumed—lower minimal gains lead to less cooperation, and vice-versa. Different communication network topologies imply different levels of power utilization and fairness at the physical layer, and a certain level of error in the communication layer induces more cooperation. PMID:26730590

Complexity and chaos control in a discrete-time prey-predator model

NASA Astrophysics Data System (ADS)

Din, Qamar

2017-08-01

We investigate the complex behavior and chaos control in a discrete-time prey-predator model. Taking into account the Leslie-Gower prey-predator model, we propose a discrete-time prey-predator system with predator partially dependent on prey and investigate the boundedness, existence and uniqueness of positive equilibrium and bifurcation analysis of the system by using center manifold theorem and bifurcation theory. Various feedback control strategies are implemented for controlling the bifurcation and chaos in the system. Numerical simulations are provided to illustrate theoretical discussion.

Towards a framework of human factors certification of complex human-machine systems

NASA Technical Reports Server (NTRS)

Bukasa, Birgit

1994-01-01

As far as total automation is not realized, the combination of technical and social components in man-machine systems demands not only contributions from engineers but at least to an equal extent from behavioral scientists. This has been neglected far too long. The psychological, social and cultural aspects of technological innovations were almost totally overlooked. Yet, along with expected safety improvements the institutionalization of human factors is on the way. The introduction of human factors certification of complex man-machine systems will be a milestone in this process.

A Bayes network approach to uncertainty quantification in hierarchically developed computational models

DOE PAGES

Urbina, Angel; Mahadevan, Sankaran; Paez, Thomas L.

2012-03-01

Here, performance assessment of complex systems is ideally accomplished through system-level testing, but because they are expensive, such tests are seldom performed. On the other hand, for economic reasons, data from tests on individual components that are parts of complex systems are more readily available. The lack of system-level data leads to a need to build computational models of systems and use them for performance prediction in lieu of experiments. Because their complexity, models are sometimes built in a hierarchical manner, starting with simple components, progressing to collections of components, and finally, to the full system. Quantification of uncertainty inmore » the predicted response of a system model is required in order to establish confidence in the representation of actual system behavior. This paper proposes a framework for the complex, but very practical problem of quantification of uncertainty in system-level model predictions. It is based on Bayes networks and uses the available data at multiple levels of complexity (i.e., components, subsystem, etc.). Because epistemic sources of uncertainty were shown to be secondary, in this application, aleatoric only uncertainty is included in the present uncertainty quantification. An example showing application of the techniques to uncertainty quantification of measures of response of a real, complex aerospace system is included.« less

Fluid Intelligence Predicts Novel Rule Implementation in a Distributed Frontoparietal Control Network.

PubMed

Tschentscher, Nadja; Mitchell, Daniel; Duncan, John

2017-05-03

Fluid intelligence has been associated with a distributed cognitive control or multiple-demand (MD) network, comprising regions of lateral frontal, insular, dorsomedial frontal, and parietal cortex. Human fluid intelligence is also intimately linked to task complexity, and the process of solving complex problems in a sequence of simpler, more focused parts. Here, a complex target detection task included multiple independent rules, applied one at a time in successive task epochs. Although only one rule was applied at a time, increasing task complexity (i.e., the number of rules) impaired performance in participants of lower fluid intelligence. Accompanying this loss of performance was reduced response to rule-critical events across the distributed MD network. The results link fluid intelligence and MD function to a process of attentional focus on the successive parts of complex behavior. SIGNIFICANCE STATEMENT Fluid intelligence is intimately linked to the ability to structure complex problems in a sequence of simpler, more focused parts. We examine the basis for this link in the functions of a distributed frontoparietal or multiple-demand (MD) network. With increased task complexity, participants of lower fluid intelligence showed reduced responses to task-critical events. Reduced responses in the MD system were accompanied by impaired behavioral performance. Low fluid intelligence is linked to poor foregrounding of task-critical information across a distributed MD system. Copyright © 2017 Tschentscher et al.

Complex systems and health behavior change: insights from cognitive science.

PubMed

Orr, Mark G; Plaut, David C

2014-05-01

To provide proof-of-concept that quantum health behavior can be instantiated as a computational model that is informed by cognitive science, the Theory of Reasoned Action, and quantum health behavior theory. We conducted a synthetic review of the intersection of quantum health behavior change and cognitive science. We conducted simulations, using a computational model of quantum health behavior (a constraint satisfaction artificial neural network) and tested whether the model exhibited quantum-like behavior. The model exhibited clear signs of quantum-like behavior. Quantum health behavior can be conceptualized as constraint satisfaction: a mitigation between current behavioral state and the social contexts in which it operates. We outlined implications for moving forward with computational models of both quantum health behavior and health behavior in general.

Behavior of complex mixtures in aquatic environments: a synthesis of PNL ecological research

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

Fickeisen, D.H.; Vaughan, B.E.

1984-06-01

The term complex mixture has been recently applied to energy-related process streams, products and wastes that typically contain hundreds or thousands of individual organic compounds, like petroleum or synthetic fuel oils; but it is more generally applicable. A six-year program of ecological research has focused on four areas important to understanding the environmental behavior of complex mixtures: physicochemical variables, individual organism responses, ecosystems-level determinations, and metabolism. Of these areas, physicochemical variables and organism responses were intensively studied; system-level determinations and metabolism represent more recent directions. Chemical characterization was integrated throughout all areas of the program, and state-of-the-art methods were applied.more » 155 references, 35 figures, 4 tables.« less

Agent-based models of cellular systems.

PubMed

Cannata, Nicola; Corradini, Flavio; Merelli, Emanuela; Tesei, Luca

2013-01-01

Software agents are particularly suitable for engineering models and simulations of cellular systems. In a very natural and intuitive manner, individual software components are therein delegated to reproduce "in silico" the behavior of individual components of alive systems at a given level of resolution. Individuals' actions and interactions among individuals allow complex collective behavior to emerge. In this chapter we first introduce the readers to software agents and multi-agent systems, reviewing the evolution of agent-based modeling of biomolecular systems in the last decade. We then describe the main tools, platforms, and methodologies available for programming societies of agents, possibly profiting also of toolkits that do not require advanced programming skills.

Locus coeruleus to basolateral amygdala noradrenergic projections promote anxiety-like behavior.

PubMed

McCall, Jordan G; Siuda, Edward R; Bhatti, Dionnet L; Lawson, Lamley A; McElligott, Zoe A; Stuber, Garret D; Bruchas, Michael R

2017-07-14

Increased tonic activity of locus coeruleus noradrenergic (LC-NE) neurons induces anxiety-like and aversive behavior. While some information is known about the afferent circuitry that endogenously drives this neural activity and behavior, the downstream receptors and anatomical projections that mediate these acute risk aversive behavioral states via the LC-NE system remain unresolved. Here we use a combination of retrograde tracing, fast-scan cyclic voltammetry, electrophysiology, and in vivo optogenetics with localized pharmacology to identify neural substrates downstream of increased tonic LC-NE activity in mice. We demonstrate that photostimulation of LC-NE fibers in the BLA evokes norepinephrine release in the basolateral amygdala (BLA), alters BLA neuronal activity, conditions aversion, and increases anxiety-like behavior. Additionally, we report that β-adrenergic receptors mediate the anxiety-like phenotype of increased NE release in the BLA. These studies begin to illustrate how the complex efferent system of the LC-NE system selectively mediates behavior through distinct receptor and projection-selective mechanisms.

Development of the Next Generation of Biogeochemistry Simulations Using EMSL's NWChem Molecular Modeling Software

NASA Astrophysics Data System (ADS)

Bylaska, E. J.; Kowalski, K.; Apra, E.; Govind, N.; Valiev, M.

2017-12-01

Methods of directly simulating the behavior of complex strongly interacting atomic systems (molecular dynamics, Monte Carlo) have provided important insight into the behavior of nanoparticles, biogeochemical systems, mineral/fluid systems, nanoparticles, actinide systems and geofluids. The limitation of these methods to even wider applications is the difficulty of developing accurate potential interactions in these systems at the molecular level that capture their complex chemistry. The well-developed tools of quantum chemistry and physics have been shown to approach the accuracy required. However, despite the continuous effort being put into improving their accuracy and efficiency, these tools will be of little value to condensed matter problems without continued improvements in techniques to traverse and sample the high-dimensional phase space needed to span the ˜10^12 time scale differences between molecular simulation and chemical events. In recent years, we have made considerable progress in developing electronic structure and AIMD methods tailored to treat biochemical and geochemical problems, including very efficient implementations of many-body methods, fast exact exchange methods, electron-transfer methods, excited state methods, QM/MM, and new parallel algorithms that scale to +100,000 cores. The poster will focus on the fundamentals of these methods and the realities in terms of system size, computational requirements and simulation times that are required for their application to complex biogeochemical systems.

Monitoring a Complex Physical System using a Hybrid Dynamic Bayes Net

NASA Technical Reports Server (NTRS)

Lerner, Uri; Moses, Brooks; Scott, Maricia; McIlraith, Sheila; Keller, Daphne

2005-01-01

The Reverse Water Gas Shift system (RWGS) is a complex physical system designed to produce oxygen from the carbon dioxide atmosphere on Mars. If sent to Mars, it would operate without human supervision, thus requiring a reliable automated system for monitoring and control. The RWGS presents many challenges typical of real-world systems, including: noisy and biased sensors, nonlinear behavior, effects that are manifested over different time granularities, and unobservability of many important quantities. In this paper we model the RWGS using a hybrid (discrete/continuous) Dynamic Bayesian Network (DBN), where the state at each time slice contains 33 discrete and 184 continuous variables. We show how the system state can be tracked using probabilistic inference over the model. We discuss how to deal with the various challenges presented by the RWGS, providing a suite of techniques that are likely to be useful in a wide range of applications. In particular, we describe a general framework for dealing with nonlinear behavior using numerical integration techniques, extending the successful Unscented Filter. We also show how to use a fixed-point computation to deal with effects that develop at different time scales, specifically rapid changes occuring during slowly changing processes. We test our model using real data collected from the RWGS, demonstrating the feasibility of hybrid DBNs for monitoring complex real-world physical systems.

Technology Entrepreneurship: A Deliberation on Success and Failure in Technology Venturing toward a Grounded Theory of Dystechnia

ERIC Educational Resources Information Center

Stewart, McDonald R.

2011-01-01

In the realm of social sciences, the greater body of business and economic theory constructs frameworks of complex organizational systems: the firm, the industry, the institution. Underlying these interdependent and concentric layers are individuals whose behaviors exist first; behaviors must give rise to institutions before institutions can mold…

Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.

PubMed

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

2015-01-01

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

SIM_EXPLORE: Software for Directed Exploration of Complex Systems

NASA Technical Reports Server (NTRS)

Burl, Michael; Wang, Esther; Enke, Brian; Merline, William J.

2013-01-01

Physics-based numerical simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. While such codes may provide the highest- fidelity representation of system behavior, they are often so slow to run that insight into the system is limited. Trying to understand the effects of inputs on outputs by conducting an exhaustive grid-based sweep over the input parameter space is simply too time-consuming. An alternative approach called "directed exploration" has been developed to harvest information from numerical simulators more efficiently. The basic idea is to employ active learning and supervised machine learning to choose cleverly at each step which simulation trials to run next based on the results of previous trials. SIM_EXPLORE is a new computer program that uses directed exploration to explore efficiently complex systems represented by numerical simulations. The software sequentially identifies and runs simulation trials that it believes will be most informative given the results of previous trials. The results of new trials are incorporated into the software's model of the system behavior. The updated model is then used to pick the next round of new trials. This process, implemented as a closed-loop system wrapped around existing simulation code, provides a means to improve the speed and efficiency with which a set of simulations can yield scientifically useful results. The software focuses on the case in which the feedback from the simulation trials is binary-valued, i.e., the learner is only informed of the success or failure of the simulation trial to produce a desired output. The software offers a number of choices for the supervised learning algorithm (the method used to model the system behavior given the results so far) and a number of choices for the active learning strategy (the method used to choose which new simulation trials to run given the current behavior model). The software also makes use of the LEGION distributed computing framework to leverage the power of a set of compute nodes. The approach has been demonstrated on a planetary science application in which numerical simulations are used to study the formation of asteroid families.

The neuroscience of investing: fMRI of the reward system.

PubMed

Peterson, Richard L

2005-11-15

Functional magnetic resonance imaging (fMRI) has proven a useful tool for observing neural BOLD signal changes during complex cognitive and emotional tasks. Yet the meaning and applicability of the fMRI data being gathered is still largely unknown. The brain's reward system underlies the fundamental neural processes of goal evaluation, preference formation, positive motivation, and choice behavior. fMRI technology allows researchers to dynamically visualize reward system processes. Experimenters can then correlate reward system BOLD activations with experimental behavior from carefully controlled experiments. In the SPAN lab at Stanford University, directed by Brian Knutson Ph.D., researchers have been using financial tasks during fMRI scanning to correlate emotion, behavior, and cognition with the reward system's fundamental neural activations. One goal of the SPAN lab is the development of predictive models of behavior. In this paper we extrapolate our fMRI results toward understanding and predicting individual behavior in the uncertain and high-risk environment of the financial markets. The financial market price anomalies of "value versus glamour" and "momentum" may be real-world examples of reward system activation biasing collective behavior. On the individual level, the investor's bias of overconfidence may similarly be related to reward system activation. We attempt to understand selected "irrational" investor behaviors and anomalous financial market price patterns through correlations with findings from fMRI research of the reward system.

Contribution to the meaning and understanding of anticipatory systems

NASA Astrophysics Data System (ADS)

Kljajić, Miroljub

2001-06-01

The present article discusses the cybernetic method in the modelling and understanding of complex systems from the epistemological, semantic as well as psychological point of view. Biological and organisational systems are the most important among complex systems. According to Rosen [1] anticipatory systems is another name for complex systems because, in a way, they function to anticipate the future state in order to preserve its structure and functioning. This paper demonstrates a strong analogy between Rosen's modified definition of anticipatory systems [2] and decision-making through simulation in organisational systems. The possible meaning of several models modified in the anticipatory mode will also be discussed as for example: a) The modified Verhaulst Model and its anticipatory modification in the case of the description of human behavior, b) The Prey-Predator Model, and c) The Evans Market Model under different conditions of the demand and supply function.

Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Niebur, Dagmar

1995-01-01

Electric power systems represent complex systems involving many electrical components whoseoperation has to be planned, analyzed, monitored and controlled. The time-scale of tasks in electricpower systems extends from long term planning years ahead to milliseconds in the area of control. The behavior of power systems is highly non-linear. Monitoring and control involves several hundred variables which are only partly available by measurements.

The Limitations of Model-Based Experimental Design and Parameter Estimation in Sloppy Systems.

PubMed

White, Andrew; Tolman, Malachi; Thames, Howard D; Withers, Hubert Rodney; Mason, Kathy A; Transtrum, Mark K

2016-12-01

We explore the relationship among experimental design, parameter estimation, and systematic error in sloppy models. We show that the approximate nature of mathematical models poses challenges for experimental design in sloppy models. In many models of complex biological processes it is unknown what are the relevant physical mechanisms that must be included to explain system behaviors. As a consequence, models are often overly complex, with many practically unidentifiable parameters. Furthermore, which mechanisms are relevant/irrelevant vary among experiments. By selecting complementary experiments, experimental design may inadvertently make details that were ommitted from the model become relevant. When this occurs, the model will have a large systematic error and fail to give a good fit to the data. We use a simple hyper-model of model error to quantify a model's discrepancy and apply it to two models of complex biological processes (EGFR signaling and DNA repair) with optimally selected experiments. We find that although parameters may be accurately estimated, the discrepancy in the model renders it less predictive than it was in the sloppy regime where systematic error is small. We introduce the concept of a sloppy system-a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. We explore the limits of accurate parameter estimation in sloppy systems and argue that identifying underlying mechanisms controlling system behavior is better approached by considering a hierarchy of models of varying detail rather than focusing on parameter estimation in a single model.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

NASA Astrophysics Data System (ADS)

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

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

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

PubMed

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

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

Collective Behavior of Camphor Floats Migrating on the Water Surface

NASA Astrophysics Data System (ADS)

Nishimori, Hiraku; Suematsu, Nobuhiko J.; Nakata, Satoshi

2017-10-01

As simple and easily controllable objects among various self-propelled particles, camphor floats on the water surface have been widely recognized. In this paper, we introduce characteristic behaviors and discuss the background mechanism of camphor floats on water, both in isolated and non-isolated conditions. In particular, we focus on: (i) the transition of dynamical characters through bifurcations exhibited by systems with small number of camphor floats and (ii) the emergence of a rich variety of complex dynamics observed in systems with large number camphor floats, and attempt to elucidate these phenomena through mathematical modeling as well as experimental analysis. Finally, we discuss the connection of the dynamics of camphor floats to that of a wider class of complex and sophisticated dynamics exhibited by various types of self-propelled particles.

Thermo-mechanical behavior of power electronic packaging assemblies: From characterization to predictive simulation of lifetimes

NASA Astrophysics Data System (ADS)

Dalverny, O.; Alexis, J.

2018-02-01

This article deals with thermo-mechanical behavior of power electronic modules used in several transportation applications as railway, aeronautic or automotive systems. Due to a multi-layered structures, involving different materials with a large variation of coefficient of thermal expansion, temperature variations originated from active or passive cycling (respectively from die dissipation or environmental constraint) induces strain and stresses field variations, giving fatigue phenomenon of the system. The analysis of the behavior of these systems and their dimensioning require the implementation of complex modeling strategies by both the multi-physical and the multi-scale character of the power modules. In this paper we present some solutions for studying the thermomechanical behavior of brazed assemblies as well as taking into account the interfaces represented by the numerous metallizations involved in the process assembly.

Mechanisms of cooperation in cancer nanomedicine: towards systems nanotechnology.

PubMed

Hauert, Sabine; Bhatia, Sangeeta N

2014-09-01

Nanoparticles are designed to deliver therapeutics and diagnostics selectively to tumors. Their size, shape, charge, material, coating, and cargo determine their individual functionalities. A systems approach could help predict the behavior of trillions of nanoparticles interacting in complex tumor environments. Engineering these nanosystems may lead to biomimetic strategies where interactions between nanoparticles and their environment give rise to cooperative behaviors typically seen in natural self-organized systems. Examples include nanoparticles that communicate the location of a tumor to amplify tumor homing or self-assemble and disassemble to optimize nanoparticle transport. The challenge is to discover which nanoparticle designs lead to a desired system behavior. To this end, novel nanomaterials, deep understanding of biology, and computational tools are emerging as the next frontier. Copyright © 2014 Elsevier Ltd. All rights reserved.

State analysis requirements database for engineering complex embedded systems

NASA Technical Reports Server (NTRS)

Bennett, Matthew B.; Rasmussen, Robert D.; Ingham, Michel D.

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 tool called the State Analysis Database, which provides a tool 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 the State Analysis Database.

Characteristics of Behavior of Robots with Emotion Model

NASA Astrophysics Data System (ADS)

Sato, Shigehiko; Nozawa, Akio; Ide, Hideto

Cooperated multi robots system has much dominance in comparison with single robot system. It is able to adapt to various circumstances and has a flexibility for variation of tasks. However it has still problems to control each robot, though methods for control multi robots system have been studied. Recently, the robots have been coming into real scene. And emotion and sensitivity of the robots have been widely studied. In this study, human emotion model based on psychological interaction was adapt to multi robots system to achieve methods for organization of multi robots. The characteristics of behavior of multi robots system achieved through computer simulation were analyzed. As a result, very complexed and interesting behavior was emerged even though it has rather simple configuration. And it has flexiblity in various circumstances. Additional experiment with actual robots will be conducted based on the emotion model.

Radiation Chemistry in Organized Assemblies.

ERIC Educational Resources Information Center

Thomas, J. K.; Chen, T. S.

1981-01-01

Expands the basic concepts regarding the radiation chemistry of simple aqueous systems to more complex, but well defined, organized assemblies. Discusses the differences in behavior in comparison to simple systems. Reviews these techniques: pulse radiolysis, laser flash, photolysis, and steady state irradiation by gamma rays or light. (CS)

Approaches for scalable modeling and emulation of cyber systems : LDRD final report.

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

Mayo, Jackson R.; Minnich, Ronald G.; Armstrong, Robert C.

2009-09-01

The goal of this research was to combine theoretical and computational approaches to better understand the potential emergent behaviors of large-scale cyber systems, such as networks of {approx} 10{sup 6} computers. The scale and sophistication of modern computer software, hardware, and deployed networked systems have significantly exceeded the computational research community's ability to understand, model, and predict current and future behaviors. This predictive understanding, however, is critical to the development of new approaches for proactively designing new systems or enhancing existing systems with robustness to current and future cyber threats, including distributed malware such as botnets. We have developed preliminarymore » theoretical and modeling capabilities that can ultimately answer questions such as: How would we reboot the Internet if it were taken down? Can we change network protocols to make them more secure without disrupting existing Internet connectivity and traffic flow? We have begun to address these issues by developing new capabilities for understanding and modeling Internet systems at scale. Specifically, we have addressed the need for scalable network simulation by carrying out emulations of a network with {approx} 10{sup 6} virtualized operating system instances on a high-performance computing cluster - a 'virtual Internet'. We have also explored mappings between previously studied emergent behaviors of complex systems and their potential cyber counterparts. Our results provide foundational capabilities for further research toward understanding the effects of complexity in cyber systems, to allow anticipating and thwarting hackers.« less

Predicting Pilot Behavior in Medium Scale Scenarios Using Game Theory and Reinforcement Learning

NASA Technical Reports Server (NTRS)

Yildiz, Yildiray; Agogino, Adrian; Brat, Guillaume

2013-01-01

Effective automation is critical in achieving the capacity and safety goals of the Next Generation Air Traffic System. Unfortunately creating integration and validation tools for such automation is difficult as the interactions between automation and their human counterparts is complex and unpredictable. This validation becomes even more difficult as we integrate wide-reaching technologies that affect the behavior of different decision makers in the system such as pilots, controllers and airlines. While overt short-term behavior changes can be explicitly modeled with traditional agent modeling systems, subtle behavior changes caused by the integration of new technologies may snowball into larger problems and be very hard to detect. To overcome these obstacles, we show how integration of new technologies can be validated by learning behavior models based on goals. In this framework, human participants are not modeled explicitly. Instead, their goals are modeled and through reinforcement learning their actions are predicted. The main advantage to this approach is that modeling is done within the context of the entire system allowing for accurate modeling of all participants as they interact as a whole. In addition such an approach allows for efficient trade studies and feasibility testing on a wide range of automation scenarios. The goal of this paper is to test that such an approach is feasible. To do this we implement this approach using a simple discrete-state learning system on a scenario where 50 aircraft need to self-navigate using Automatic Dependent Surveillance-Broadcast (ADS-B) information. In this scenario, we show how the approach can be used to predict the ability of pilots to adequately balance aircraft separation and fly efficient paths. We present results with several levels of complexity and airspace congestion.

Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology?

PubMed

Jedlicka, Peter

2017-01-01

The nervous system is a non-linear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of non-linear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system's behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in non-neuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a non-trivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics.

Accommodating complexity and human behaviors in decision analysis.

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

Backus, George A.; Siirola, John Daniel; Schoenwald, David Alan

2007-11-01

This is the final report for a LDRD effort to address human behavior in decision support systems. One sister LDRD effort reports the extension of this work to include actual human choices and additional simulation analyses. Another provides the background for this effort and the programmatic directions for future work. This specific effort considered the feasibility of five aspects of model development required for analysis viability. To avoid the use of classified information, healthcare decisions and the system embedding them became the illustrative example for assessment.

Visualizing Parallel Computer System Performance

NASA Technical Reports Server (NTRS)

Malony, Allen D.; Reed, Daniel A.

1988-01-01

Parallel computer systems are among the most complex of man's creations, making satisfactory performance characterization difficult. Despite this complexity, there are strong, indeed, almost irresistible, incentives to quantify parallel system performance using a single metric. The fallacy lies in succumbing to such temptations. A complete performance characterization requires not only an analysis of the system's constituent levels, it also requires both static and dynamic characterizations. Static or average behavior analysis may mask transients that dramatically alter system performance. Although the human visual system is remarkedly adept at interpreting and identifying anomalies in false color data, the importance of dynamic, visual scientific data presentation has only recently been recognized Large, complex parallel system pose equally vexing performance interpretation problems. Data from hardware and software performance monitors must be presented in ways that emphasize important events while eluding irrelevant details. Design approaches and tools for performance visualization are the subject of this paper.

Understanding System of Systems Development Using an Agent-Based Wave Model

DTIC Science & Technology

2012-01-01

Procedia Computer Science Procedia Computer Science 00 (2012) 000–000 www.elsevier.com/locate/ procedia Complex Adaptive Systems...integration of technical systems as well as cognitive and social processes, which alter system behavior [6]. As mentioned before * Corresponding...Prescribed by ANSI Std Z39-18 Acheson/ Procedia Computer Science 00 (2012) 000–000 most system architects assume that SoS participants exhibit

Phase transitions in the first-passage time of scale-invariant correlated processes

PubMed Central

Carretero-Campos, Concepción; Bernaola-Galván, Pedro; Ch. Ivanov, Plamen

2012-01-01

A key quantity describing the dynamics of complex systems is the first-passage time (FPT). The statistical properties of FPT depend on the specifics of the underlying system dynamics. We present a unified approach to account for the diversity of statistical behaviors of FPT observed in real-world systems. We find three distinct regimes, separated by two transition points, with fundamentally different behavior for FPT as a function of increasing strength of the correlations in the system dynamics: stretched exponential, power-law, and saturation regimes. In the saturation regime, the average length of FPT diverges proportionally to the system size, with important implications for understanding electronic delocalization in one-dimensional correlated-disordered systems. PMID:22400544

Network representations of immune system complexity

PubMed Central

Subramanian, Naeha; Torabi-Parizi, Parizad; Gottschalk, Rachel A.; Germain, Ronald N.; Dutta, Bhaskar

2015-01-01

The mammalian immune system is a dynamic multi-scale system composed of a hierarchically organized set of molecular, cellular and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein-protein interactions underlying intracellular signaling pathways and single cell responses to increasingly complex networks of in vivo cellular interaction, positioning and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather non-linear behaviors arising from dynamic, feedback-regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multi-scale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular and organism-level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks. PMID:25625853

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

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

The Tangled Tale of Genes and Environment: Moore's The Dependent Gene: The Fallacy of “nature VS. Nurture”

PubMed Central

Schneider, Susan M

2007-01-01

Nature–nurture views that smack of genetic determinism remain prevalent. Yet, the increasing knowledge base shows ever more clearly that environmental factors and genes form a fully interactional system at all levels. Moore's book covers the major topics of discovery and dispute, including behavior genetics and the twin studies, developmental psychobiology, and developmental systems theory. Knowledge of this larger life-sciences context for behavior principles will become increasingly important as the full complexity of gene–environment relations is revealed. Behavior analysis both contributes to and gains from the larger battle for the recognition of how nature and nurture really work.

A computational framework for modeling targets as complex adaptive systems

NASA Astrophysics Data System (ADS)

Santos, Eugene; Santos, Eunice E.; Korah, John; Murugappan, Vairavan; Subramanian, Suresh

2017-05-01

Modeling large military targets is a challenge as they can be complex systems encompassing myriad combinations of human, technological, and social elements that interact, leading to complex behaviors. Moreover, such targets have multiple components and structures, extending across multiple spatial and temporal scales, and are in a state of change, either in response to events in the environment or changes within the system. Complex adaptive system (CAS) theory can help in capturing the dynamism, interactions, and more importantly various emergent behaviors, displayed by the targets. However, a key stumbling block is incorporating information from various intelligence, surveillance and reconnaissance (ISR) sources, while dealing with the inherent uncertainty, incompleteness and time criticality of real world information. To overcome these challenges, we present a probabilistic reasoning network based framework called complex adaptive Bayesian Knowledge Base (caBKB). caBKB is a rigorous, overarching and axiomatic framework that models two key processes, namely information aggregation and information composition. While information aggregation deals with the union, merger and concatenation of information and takes into account issues such as source reliability and information inconsistencies, information composition focuses on combining information components where such components may have well defined operations. Since caBKBs can explicitly model the relationships between information pieces at various scales, it provides unique capabilities such as the ability to de-aggregate and de-compose information for detailed analysis. Using a scenario from the Network Centric Operations (NCO) domain, we will describe how our framework can be used for modeling targets with a focus on methodologies for quantifying NCO performance metrics.

Phase locking route behind complex periodic windows in a forced oscillator

NASA Astrophysics Data System (ADS)

Jan, Hengtai; Tsai, Kuo-Ting; Kuo, Li-wei

2013-09-01

Chaotic systems have complex reactions against an external driving force; even in cases with low-dimension oscillators, the routes to synchronization are diverse. We proposed a stroboscope-based method for analyzing driven chaotic systems in their phase space. According to two statistic quantities generated from time series, we could realize the system state and the driving behavior simultaneously. We demonstrated our method in a driven bi-stable system, which showed complex period windows under a proper driving force. With increasing periodic driving force, a route from interior periodic oscillation to phase synchronization through the chaos state could be found. Periodic windows could also be identified and the circumstances under which they occurred distinguished. Statistical results were supported by conditional Lyapunov exponent analysis to show the power in analyzing the unknown time series.

A method for multiprotein assembly in cells reveals independent action of kinesins in complex

PubMed Central

Norris, Stephen R.; Soppina, Virupakshi; Dizaji, Aslan S.; Schimert, Kristin I.; Sept, David; Cai, Dawen; Sivaramakrishnan, Sivaraj

2014-01-01

Teams of processive molecular motors are critical for intracellular transport and organization, yet coordination between motors remains poorly understood. Here, we develop a system using protein components to generate assemblies of defined spacing and composition inside cells. This system is applicable to studying macromolecular complexes in the context of cell signaling, motility, and intracellular trafficking. We use the system to study the emergent behavior of kinesin motors in teams. We find that two kinesin motors in complex act independently (do not help or hinder each other) and can alternate their activities. For complexes containing a slow kinesin-1 and fast kinesin-3 motor, the slow motor dominates motility in vitro but the fast motor can dominate on certain subpopulations of microtubules in cells. Both motors showed dynamic interactions with the complex, suggesting that motor–cargo linkages are sensitive to forces applied by the motors. We conclude that kinesin motors in complex act independently in a manner regulated by the microtubule track. PMID:25365993

Physical Behavior in Older Persons during Daily Life: Insights from Instrumented Shoes.

PubMed

Moufawad El Achkar, Christopher; Lenoble-Hoskovec, Constanze; Paraschiv-Ionescu, Anisoara; Major, Kristof; Büla, Christophe; Aminian, Kamiar

2016-08-03

Activity level and gait parameters during daily life are important indicators for clinicians because they can provide critical insights into modifications of mobility and function over time. Wearable activity monitoring has been gaining momentum in daily life health assessment. Consequently, this study seeks to validate an algorithm for the classification of daily life activities and to provide a detailed gait analysis in older adults. A system consisting of an inertial sensor combined with a pressure sensing insole has been developed. Using an algorithm that we previously validated during a semi structured protocol, activities in 10 healthy elderly participants were recorded and compared to a wearable reference system over a 4 h recording period at home. Detailed gait parameters were calculated from inertial sensors. Dynamics of physical behavior were characterized using barcodes that express the measure of behavioral complexity. Activity classification based on the algorithm led to a 93% accuracy in classifying basic activities of daily life, i.e., sitting, standing, and walking. Gait analysis emphasizes the importance of metrics such as foot clearance in daily life assessment. Results also underline that measures of physical behavior and gait performance are complementary, especially since gait parameters were not correlated to complexity. Participants gave positive feedback regarding the use of the instrumented shoes. These results extend previous observations in showing the concurrent validity of the instrumented shoes compared to a body-worn reference system for daily-life physical behavior monitoring in older adults.

Emergent complexity of the cytoskeleton: from single filaments to tissue

PubMed Central

Huber, F.; Schnauß, J.; Rönicke, S.; Rauch, P.; Müller, K.; Fütterer, C.; Käs, J.

2013-01-01

Despite their overwhelming complexity, living cells display a high degree of internal mechanical and functional organization which can largely be attributed to the intracellular biopolymer scaffold, the cytoskeleton. Being a very complex system far from thermodynamic equilibrium, the cytoskeleton's ability to organize is at the same time challenging and fascinating. The extensive amounts of frequently interacting cellular building blocks and their inherent multifunctionality permits highly adaptive behavior and obstructs a purely reductionist approach. Nevertheless (and despite the field's relative novelty), the physics approach has already proved to be extremely successful in revealing very fundamental concepts of cytoskeleton organization and behavior. This review aims at introducing the physics of the cytoskeleton ranging from single biopolymer filaments to multicellular organisms. Throughout this wide range of phenomena, the focus is set on the intertwined nature of the different physical scales (levels of complexity) that give rise to numerous emergent properties by means of self-organization or self-assembly. PMID:24748680

Artificial intelligence exploration of unstable protocells leads to predictable properties and discovery of collective behavior.

PubMed

Points, Laurie J; Taylor, James Ward; Grizou, Jonathan; Donkers, Kevin; Cronin, Leroy

2018-01-30

Protocell models are used to investigate how cells might have first assembled on Earth. Some, like oil-in-water droplets, can be seemingly simple models, while able to exhibit complex and unpredictable behaviors. How such simple oil-in-water systems can come together to yield complex and life-like behaviors remains a key question. Herein, we illustrate how the combination of automated experimentation and image processing, physicochemical analysis, and machine learning allows significant advances to be made in understanding the driving forces behind oil-in-water droplet behaviors. Utilizing >7,000 experiments collected using an autonomous robotic platform, we illustrate how smart automation cannot only help with exploration, optimization, and discovery of new behaviors, but can also be core to developing fundamental understanding of such systems. Using this process, we were able to relate droplet formulation to behavior via predicted physical properties, and to identify and predict more occurrences of a rare collective droplet behavior, droplet swarming. Proton NMR spectroscopic and qualitative pH methods enabled us to better understand oil dissolution, chemical change, phase transitions, and droplet and aqueous phase flows, illustrating the utility of the combination of smart-automation and traditional analytical chemistry techniques. We further extended our study for the simultaneous exploration of both the oil and aqueous phases using a robotic platform. Overall, this work shows that the combination of chemistry, robotics, and artificial intelligence enables discovery, prediction, and mechanistic understanding in ways that no one approach could achieve alone.

Tools for Detecting Causality in Space Systems

NASA Astrophysics Data System (ADS)

Johnson, J.; Wing, S.

2017-12-01

Complex systems such as the solar and magnetospheric envivonment often exhibit patterns of behavior that suggest underlying organizing principles. Causality is a key organizing principle that is particularly difficult to establish in strongly coupled nonlinear systems, but essential for understanding and modeling the behavior of systems. While traditional methods of time-series analysis can identify linear correlations, they do not adequately quantify the distinction between causal and coincidental dependence. We discuss tools for detecting causality including: granger causality, transfer entropy, conditional redundancy, and convergent cross maps. The tools are illustrated by applications to magnetospheric and solar physics including radiation belt, Dst (a magnetospheric state variable), substorm, and solar cycle dynamics.

Autonomic nervous system function, child behavior, and maternal sensitivity in three-year-old children with surgically corrected transposition.

PubMed

Harrison, Tondi M

2013-01-01

Explore relationships among autonomic nervous system (ANS) function, child behavior, and maternal sensitivity in three-year-old children with surgically corrected transposition of the great arteries (TGA) and in children healthy at birth. Children surviving complex congenital heart defects are at risk for behavior problems. ANS function is associated with behavior and with maternal sensitivity. Child ANS function (heart rate variability) and maternal sensitivity (Parent-Child Early Relational Assessment) were measured during a challenging task. Mother completed the Child Behavior Checklist. Data were analyzed descriptively and graphically. Children with TGA had less responsive autonomic function and more behavior problems than healthy children. Autonomic function improved with more maternal sensitivity. Alterations in ANS function may continue years after surgical correction in children with TGA, potentially impacting behavioral regulation. Maternal sensitivity may be associated with ANS function in this population. Continued research on relationships among ANS function, child behavior, and maternal sensitivity is warranted. Copyright © 2013 Elsevier Inc. All rights reserved.

ABLEPathPlanner library for Umbra

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

Oppel III, Fred J; Xavier, Patrick G.; Gottlieb, Eric Joseph

Umbra contains a flexible, modular path planner that is used to simulate complex entity behaviors moving within 3D terrain environments that include buildings, barriers, roads, bridges, fences, and a variety of other terrain features (water, vegetation, slope, etc…). The path planning algorithm is a critical component required to execute these tactical behaviors to provide realistic entity movement and provide efficient system computing performance.

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

NASA Astrophysics Data System (ADS)

Takagi, Kazushi; Gotoda, Hiroshi

2016-11-01

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

Crew workload-management strategies - A critical factor in system performance

NASA Technical Reports Server (NTRS)

Hart, Sandra G.

1989-01-01

This paper reviews the philosophy and goals of the NASA/USAF Strategic Behavior/Workload Management Program. The philosophical foundation of the program is based on the assumption that an improved understanding of pilot strategies will clarify the complex and inconsistent relationships observed among objective task demands and measures of system performance and pilot workload. The goals are to: (1) develop operationally relevant figures of merit for performance, (2) quantify the effects of strategic behaviors on system performance and pilot workload, (3) identify evaluation criteria for workload measures, and (4) develop methods of improving pilots' abilities to manage workload extremes.

Molecular investigation on the binding of Cd(II) by the binary mixtures of montmorillonite with two bacterial species

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

Du, Huihui; Qu, ChenChen; Liu, Jing

Bacteria and phyllosilicate commonly coexist in the natural environment, producing various bacteria–clay complexes that are capable of immobilizing heavy metals, such as cadmium, via adsorption. However, the molecular binding mechanisms of heavy metals on these complex aggregates still remain poorly understood. This study investigated Cd adsorption on Gram-positive B. subtilis, Gram-negative P. putida and their binary mixtures with montmorillonite (Mont) using the Cd K-edge x-ray absorption spectroscopy (XAS) and isothermal titration calorimetry (ITC). We observed a lower adsorptive capacity for P. putida than B. subtilis, whereas P. putida–Mont and B. subtilis–Mont mixtures showed nearly identical Cd adsorption behaviors. EXAFS fitsmore » and ITC measurements demonstrated more phosphoryl binding of Cd in P. putida. The decreased coordination of C atoms around Cd and the reduced adsorption enthalpies and entropies for the binary mixtures compared to that for individual bacteria suggested that the bidentate Cd-carboxyl complexes in pure bacteria systems were probably transformed into monodentate complexes that acted as ionic bridging structure between bacteria and motmorillonite. This study clarified the binding mechanism of Cd at the bacteria–phyllosilicate interfaces from a molecular and thermodynamic view, which has an environmental significance for predicting the chemical behavior of trace elements in complex mineral–organic systems.« less

An Efficient Model-based Diagnosis Engine for Hybrid Systems Using Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Bregon, Anibal; Narasimhan, Sriram; Roychoudhury, Indranil; Daigle, Matthew; Pulido, Belarmino

2013-01-01

Complex hybrid systems are present in a large range of engineering applications, like mechanical systems, electrical circuits, or embedded computation systems. The behavior of these systems is made up of continuous and discrete event dynamics that increase the difficulties for accurate and timely online fault diagnosis. The Hybrid Diagnosis Engine (HyDE) offers flexibility to the diagnosis application designer to choose the modeling paradigm and the reasoning algorithms. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. However, HyDE faces some problems regarding performance in terms of complexity and time. Our focus in this paper is on developing efficient model-based methodologies for online fault diagnosis in complex hybrid systems. To do this, we propose a diagnosis framework where structural model decomposition is integrated within the HyDE diagnosis framework to reduce the computational complexity associated with the fault diagnosis of hybrid systems. As a case study, we apply our approach to a diagnostic testbed, the Advanced Diagnostics and Prognostics Testbed (ADAPT), using real data.

Effects of task and age on the magnitude and structure of force fluctuations: insights into underlying neuro-behavioral processes.

PubMed

Vieluf, Solveig; Temprado, Jean-Jacques; Berton, Eric; Jirsa, Viktor K; Sleimen-Malkoun, Rita

2015-03-13

The present study aimed at characterizing the effects of increasing (relative) force level and aging on isometric force control. To achieve this objective and to infer changes in the underlying control mechanisms, measures of information transmission, as well as magnitude and time-frequency structure of behavioral variability were applied to force-time-series. Older adults were found to be weaker, more variable, and less efficient than young participants. As a function of force level, efficiency followed an inverted-U shape in both groups, suggesting a similar organization of the force control system. The time-frequency structure of force output fluctuations was only significantly affected by task conditions. Specifically, a narrower spectral distribution with more long-range correlations and an inverted-U pattern of complexity changes were observed with increasing force level. Although not significant older participants displayed on average a less complex behavior for low and intermediate force levels. The changes in force signal's regularity presented a strong dependence on time-scales, which significantly interacted with age and condition. An inverted-U profile was only observed for the time-scale relevant to the sensorimotor control process. However, in both groups the peak was not aligned with the optimum of efficiency. Our results support the view that behavioral variability, in terms of magnitude and structure, has a functional meaning and affords non-invasive markers of the adaptations of the sensorimotor control system to various constraints. The measures of efficiency and variability ought to be considered as complementary since they convey specific information on the organization of control processes. The reported weak age effect on variability and complexity measures suggests that the behavioral expression of the loss of complexity hypothesis is not as straightforward as conventionally admitted. However, group differences did not completely vanish, which suggests that age differences can be more or less apparent depending on task properties and whether difficulty is scaled in relative or absolute terms.

Applying Behavior-Based Robotics Concepts to Telerobotic Use of Power Tooling

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

Noakes, Mark W; Hamel, Dr. William R.

While it has long been recognized that telerobotics has potential advantages to reduce operator fatigue, to permit lower skilled operators to function as if they had higher skill levels, and to protect tools and manipulators from excessive forces during operation, relatively little laboratory research in telerobotics has actually been implemented in fielded systems. Much of this has to do with the complexity of the implementation and its lack of ability to operate in complex unstructured remote systems environments. One possible solution is to approach the tooling task using an adaptation of behavior-based techniques to facilitate task decomposition to a simplermore » perspective and to provide sensor registration to the task target object in the field. An approach derived from behavior-based concepts has been implemented to provide automated tool operation for a teleoperated manipulator system. The generic approach is adaptable to a wide range of typical remote tools used in hot-cell and decontamination and dismantlement-type operations. Two tasks are used in this work to test the validity of the concept. First, a reciprocating saw is used to cut a pipe. The second task is bolt removal from mockup process equipment. This paper explains the technique, its implementation, and covers experimental data, analysis of results, and suggestions for implementation on fielded systems.« less

Getting what they need when they need it. Identifying barriers to information needs of family caregivers to manage dementia-related behavioral symptoms.

PubMed

Werner, Nicole E; Stanislawski, Barbara; Marx, Katherine A; Watkins, Daphne C; Kobayashi, Marissa; Kales, Helen; Gitlin, Laura N

2017-02-22

Consumer health informatics (CHI) such as web-based applications may provide the platform for enabling the over 15 million family caregivers of patients with Alzheimer's Disease or related dementias the information they need when they need it to support behavioral symptom management. However, for CHI to be successful, it is necessary that it be designed to meet the specific information needs of family caregivers in the context in which caregiving occurs. A sociotechnical systems approach to CHI design can help to understand the contextual complexities of family caregiving and account for those complexities in the design of CHI for family caregivers. This study used a sociotechnical systems approach to identify barriers to meeting caregivers' information needs related to the management of dementia-related behavioral symptoms, and to derive design implications that overcome barriers for caregiver-focused web-based platforms. We have subsequently used these design implications to inform the development of a web-based platform, WeCareAdvisor,TM which provides caregivers with information and an algorithm by which to identify and manage behavioral symptoms for which they seek management strategies. We conducted 4 focus groups with family caregivers (N=26) in a Midwestern state. Qualitative content analysis of the data was guided by a sociotechnical systems framework. We identified nine categories of barriers that family caregivers confront in obtaining needed information about behavioral symptom management from which we extrapolated design implications for a web-based platform. Based on interactions within the sociotechnical system, three critical information needs were identified: 1) timely access to information, 2) access to information that is tailored or specific to caregiver's needs and contexts, and 3) usable information that can directly inform how caregivers' manage behaviors. The sociotechnical system framework is a useful approach for identifying information needs of family caregivers to inform design of web-based platforms that are user-centered.

Modeling driver behavior in a cognitive architecture.

PubMed

Salvucci, Dario D

2006-01-01

This paper explores the development of a rigorous computational model of driver behavior in a cognitive architecture--a computational framework with underlying psychological theories that incorporate basic properties and limitations of the human system. Computational modeling has emerged as a powerful tool for studying the complex task of driving, allowing researchers to simulate driver behavior and explore the parameters and constraints of this behavior. An integrated driver model developed in the ACT-R (Adaptive Control of Thought-Rational) cognitive architecture is described that focuses on the component processes of control, monitoring, and decision making in a multilane highway environment. This model accounts for the steering profiles, lateral position profiles, and gaze distributions of human drivers during lane keeping, curve negotiation, and lane changing. The model demonstrates how cognitive architectures facilitate understanding of driver behavior in the context of general human abilities and constraints and how the driving domain benefits cognitive architectures by pushing model development toward more complex, realistic tasks. The model can also serve as a core computational engine for practical applications that predict and recognize driver behavior and distraction.

Agent-based modeling of the immune system: NetLogo, a promising framework.

PubMed

Chiacchio, Ferdinando; Pennisi, Marzio; Russo, Giulia; Motta, Santo; Pappalardo, Francesco

2014-01-01

Several components that interact with each other to evolve a complex, and, in some cases, unexpected behavior, represents one of the main and fascinating features of the mammalian immune system. Agent-based modeling and cellular automata belong to a class of discrete mathematical approaches in which entities (agents) sense local information and undertake actions over time according to predefined rules. The strength of this approach is characterized by the appearance of a global behavior that emerges from interactions among agents. This behavior is unpredictable, as it does not follow linear rules. There are a lot of works that investigates the immune system with agent-based modeling and cellular automata. They have shown the ability to see clearly and intuitively into the nature of immunological processes. NetLogo is a multiagent programming language and modeling environment for simulating complex phenomena. It is designed for both research and education and is used across a wide range of disciplines and education levels. In this paper, we summarize NetLogo applications to immunology and, particularly, how this framework can help in the development and formulation of hypotheses that might drive further experimental investigations of disease mechanisms.

Nonlinear analysis of dynamic signature

NASA Astrophysics Data System (ADS)

Rashidi, S.; Fallah, A.; Towhidkhah, F.

2013-12-01

Signature is a long trained motor skill resulting in well combination of segments like strokes and loops. It is a physical manifestation of complex motor processes. The problem, generally stated, is that how relative simplicity in behavior emerges from considerable complexity of perception-action system that produces behavior within an infinitely variable biomechanical and environmental context. To solve this problem, we present evidences which indicate that motor control dynamic in signing process is a chaotic process. This chaotic dynamic may explain a richer array of time series behavior in motor skill of signature. Nonlinear analysis is a powerful approach and suitable tool which seeks for characterizing dynamical systems through concepts such as fractal dimension and Lyapunov exponent. As a result, they can be analyzed in both horizontal and vertical for time series of position and velocity. We observed from the results that noninteger values for the correlation dimension indicates low dimensional deterministic dynamics. This result could be confirmed by using surrogate data tests. We have also used time series to calculate the largest Lyapunov exponent and obtain a positive value. These results constitute significant evidence that signature data are outcome of chaos in a nonlinear dynamical system of motor control.

Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology?

PubMed Central

Jedlicka, Peter

2017-01-01

The nervous system is a non-linear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of non-linear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system’s behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in non-neuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a non-trivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics. PMID:29163041

Synchronization of networked chaotic oscillators under external periodic driving.

PubMed

Yang, Wenchao; Lin, Weijie; Wang, Xingang; Huang, Liang

2015-03-01

The dynamical responses of a complex system to external perturbations are of both fundamental interest and practical significance. Here, by the model of networked chaotic oscillators, we investigate how the synchronization behavior of a complex network is influenced by an externally added periodic driving. Interestingly, it is found that by a slight change of the properties of the external driving, e.g., the frequency or phase lag between its intrinsic oscillation and external driving, the network synchronizability could be significantly modified. We demonstrate this phenomenon by different network models and, based on the method of master stability function, give an analysis on the underlying mechanisms. Our studies highlight the importance of external perturbations on the collective behaviors of complex networks, and also provide an alternate approach for controlling network synchronization.

Active Learning for Directed Exploration of Complex Systems

NASA Technical Reports Server (NTRS)

Burl, Michael C.; Wang, Esther

2009-01-01

Physics-based simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. Such codes provide the highest-fidelity representation of system behavior, but are often so slow to run that insight into the system is limited. For example, conducting an exhaustive sweep over a d-dimensional input parameter space with k-steps along each dimension requires k(sup d) simulation trials (translating into k(sup d) CPU-days for one of our current simulations). An alternative is directed exploration in which the next simulation trials are cleverly chosen at each step. Given the results of previous trials, supervised learning techniques (SVM, KDE, GP) are applied to build up simplified predictive models of system behavior. These models are then used within an active learning framework to identify the most valuable trials to run next. Several active learning strategies are examined including a recently-proposed information-theoretic approach. Performance is evaluated on a set of thirteen synthetic oracles, which serve as surrogates for the more expensive simulations and enable the experiments to be replicated by other researchers.

Experimentation in machine discovery

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Simon, Herbert A.

1990-01-01

KEKADA, a system that is capable of carrying out a complex series of experiments on problems from the history of science, is described. The system incorporates a set of experimentation strategies that were extracted from the traces of the scientists' behavior. It focuses on surprises to constrain its search, and uses its strategies to generate hypotheses and to carry out experiments. Some strategies are domain independent, whereas others incorporate knowledge of a specific domain. The domain independent strategies include magnification, determining scope, divide and conquer, factor analysis, and relating different anomalous phenomena. KEKADA represents an experiment as a set of independent and dependent entities, with apparatus variables and a goal. It represents a theory either as a sequence of processes or as abstract hypotheses. KEKADA's response is described to a particular problem in biochemistry. On this and other problems, the system is capable of carrying out a complex series of experiments to refine domain theories. Analysis of the system and its behavior on a number of different problems has established its generality, but it has also revealed the reasons why the system would not be a good experimental scientist.

Molecular gearing systems

DOE PAGES

Gakh, Andrei A.; Sachleben, Richard A.; Bryan, Jeff C.

1997-11-01

The race to create smaller devices is fueling much of the research in electronics. The competition has intensified with the advent of microelectromechanical systems (MEMS), in which miniaturization is already reaching the dimensional limits imposed by physics of current lithographic techniques. Also, in the realm of biochemistry, evidence is accumulating that certain enzyme complexes are capable of very sophisticated modes of motion. Complex synergistic biochemical complexes driven by sophisticated biomechanical processes are quite common. Their biochemical functions are based on the interplay of mechanical and chemical processes, including allosteric effects. In addition, the complexity of this interplay far exceeds thatmore » of typical chemical reactions. Understanding the behavior of artificial molecular devices as well as complex natural molecular biomechanical systems is difficult. Fortunately, the problem can be successfully resolved by direct molecular engineering of simple molecular systems that can mimic desired mechanical or electronic devices. These molecular systems are called technomimetics (the name is derived, by analogy, from biomimetics). Several classes of molecular systems that can mimic mechanical, electronic, or other features of macroscopic devices have been successfully synthesized by conventional chemical methods during the past two decades. In this article we discuss only one class of such model devices: molecular gearing systems.« less

Towards Behavioral Reflexion Models

NASA Technical Reports Server (NTRS)

Ackermann, Christopher; Lindvall, Mikael; Cleaveland, Rance

2009-01-01

Software architecture has become essential in the struggle to manage today s increasingly large and complex systems. Software architecture views are created to capture important system characteristics on an abstract and, thus, comprehensible level. As the system is implemented and later maintained, it often deviates from the original design specification. Such deviations can have implication for the quality of the system, such as reliability, security, and maintainability. Software architecture compliance checking approaches, such as the reflexion model technique, have been proposed to address this issue by comparing the implementation to a model of the systems architecture design. However, architecture compliance checking approaches focus solely on structural characteristics and ignore behavioral conformance. This is especially an issue in Systems-of- Systems. Systems-of-Systems (SoS) are decompositions of large systems, into smaller systems for the sake of flexibility. Deviations of the implementation to its behavioral design often reduce the reliability of the entire SoS. An approach is needed that supports the reasoning about behavioral conformance on architecture level. In order to address this issue, we have developed an approach for comparing the implementation of a SoS to an architecture model of its behavioral design. The approach follows the idea of reflexion models and adopts it to support the compliance checking of behaviors. In this paper, we focus on sequencing properties as they play an important role in many SoS. Sequencing deviations potentially have a severe impact on the SoS correctness and qualities. The desired behavioral specification is defined in UML sequence diagram notation and behaviors are extracted from the SoS implementation. The behaviors are then mapped to the model of the desired behavior and the two are compared. Finally, a reflexion model is constructed that shows the deviations between behavioral design and implementation. This paper discusses the approach and shows how it can be applied to investigate reliability issues in SoS.

Examining fire-prone forest landscapes as coupled human and natural systems

Treesearch

Thomas A. Spies; Eric M. White; Jeffrey D. Kline; A. Paige Fisher; Alan Ager; John Bailey; John Bolte; Jennifer Koch; Emily Platt; Christine S. Olsen; Derric Jacobs; Bruce Shindler; Michelle M. Steen-Adams; Roger Hammer

2014-01-01

Fire-prone landscapes are not well studied as coupled human and natural systems (CHANS) and present many challenges for understanding and promoting adaptive behaviors and institutions. Here, we explore how heterogeneity, feedbacks, and external drivers in this type of natural hazard system can lead to complexity and can limit the development of more adaptive approaches...

A Behavioral Study of Regularity, Irregularity and Rules in the English Past Tense

ERIC Educational Resources Information Center

Magen, Harriet S.

2014-01-01

Opposing views of storage and processing of morphologically complex words (e.g., past tense) have been suggested: the dual system, whereby regular forms are not in the lexicon but are generated by rule, while irregular forms are explicitly represented; the single system, whereby regular and irregular forms are computed by a single system, using…

Video Views and Reviews: Neurulation and the Fashioning of the Vertebrate Central Nervous System

ERIC Educational Resources Information Center

Watters, Christopher

2006-01-01

The central nervous system (CNS) is the first adult organ system to appear during vertebrate development, and the process of its emergence is commonly called neurulation. Such biological "urgency" is perhaps not surprising given the structural and functional complexity of the CNS and the importance of neural function to adaptive behavior and…

Informing biological design by integration of systems and synthetic biology.

PubMed

Smolke, Christina D; Silver, Pamela A

2011-03-18

Synthetic biology aims to make the engineering of biology faster and more predictable. In contrast, systems biology focuses on the interaction of myriad components and how these give rise to the dynamic and complex behavior of biological systems. Here, we examine the synergies between these two fields. Copyright © 2011 Elsevier Inc. All rights reserved.

Observing Consistency in Online Communication Patterns for User Re-Identification

PubMed Central

Venter, Hein S.

2016-01-01

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

Thermodynamic Insight into the Solvation and Complexation Behavior of U(VI) in Ionic Liquid: Binding of CMPO with U(VI) Studied by Optical Spectroscopy and Calorimetry.

PubMed

Wu, Qi; Sun, Taoxiang; Meng, Xianghai; Chen, Jing; Xu, Chao

2017-03-06

The complexation of U(VI) with octylphenyl-N,N-diisobutylcarbamoylmethylphosphine oxide (CMPO, denoted as L) in ionic liquid (IL) C 4 mimNTf 2 was investigated by UV-vis absorption spectrophotometry and isothermal titration calorimetry. Spectro-photometric titration suggests that three successive complexes, UO 2 L j 2+ (j = 1-3), formed both in "dry" (water content < 250 ppm) and "wet" (water content ≈ 12 500 ppm) ionic liquid. However, the thermodynamic parameters are distinctly different in the two ILs. In dry IL, the complexation strength between CMPO and U(VI) is much stronger, with stability constants of the respective complexes more than 1 order of magnitude higher than that in wet IL. Energetically, the complexation of U(VI) with CMPO in dry IL is mainly driven by negative enthalpies. In contrast, the complexation in wet IL is overwhelmingly driven by highly positive entropies as a result of the release of a large amount of water molecules from the solvation sphere of U(VI). Moreover, comparisons between the fitted absorption spectra of complexes in wet IL and that of extractive samples from solvent extraction have identified the speciation involved in the extraction of U(VI) by CMPO in ionic liquid. The results from this study not only offer a thermodynamic insight into the complexation behavior of U(VI) with CMPO in IL but also provide valuable information for understanding the extraction behavior in the corresponding solvent extraction system.

The Use of Behavior Models for Predicting Complex Operations

NASA Technical Reports Server (NTRS)

Gore, Brian F.

2010-01-01

Modeling and simulation (M&S) plays an important role when complex human-system notions are being proposed, developed and tested within the system design process. National Aeronautics and Space Administration (NASA) as an agency uses many different types of M&S approaches for predicting human-system interactions, especially when it is early in the development phase of a conceptual design. NASA Ames Research Center possesses a number of M&S capabilities ranging from airflow, flight path models, aircraft models, scheduling models, human performance models (HPMs), and bioinformatics models among a host of other kinds of M&S capabilities that are used for predicting whether the proposed designs will benefit the specific mission criteria. The Man-Machine Integration Design and Analysis System (MIDAS) is a NASA ARC HPM software tool that integrates many models of human behavior with environment models, equipment models, and procedural / task models. The challenge to model comprehensibility is heightened as the number of models that are integrated and the requisite fidelity of the procedural sets are increased. Model transparency is needed for some of the more complex HPMs to maintain comprehensibility of the integrated model performance. This will be exemplified in a recent MIDAS v5 application model and plans for future model refinements will be presented.

Deep Metastable Eutectic Nanometer-Scale Particles in the MgO-Al2O3-SiO2 System

NASA Technical Reports Server (NTRS)

Reitmeijer, Frans J. M.; Nash, J. A., III

2011-01-01

Laboratory vapor phase condensation experiments systematically yield amorphous, homogeneous, nanoparticles with unique deep metastable eutectic compositions. They formed during the nucleation stage in rapidly cooling vapor systems. These nanoparticles evidence the complexity of the nucleation stage. Similar complex behavior may occur during the nucleation stage in quenched-melt laboratory experiments. Because of the bulk size of the quenched system many of such deep metastable eutectic nanodomains will anneal and adjust to local equilibrium but some will persist metastably depending on the time-temperature regime and melt/glass transformation.

Simulations of Instabilities in Complex Valve and Feed Systems

NASA Technical Reports Server (NTRS)

Ahuja, Vineet; Hosangadi, Ashvin; Shipman, Jeremy; Cavallo, Peter A.

2006-01-01

CFD analyses are playing an increasingly important role in identifying and characterizing flow induced instabilities in rocket engine test facilities and flight systems. In this paper, we analyze instability mechanisms that range from turbulent pressure fluctuations due to vortex shedding in structurally complex valve systems to flow resonance in plug cavities to large scale pressure fluctuations due to collapse of cavitation induced vapor clouds. Furthermore, we discuss simulations of transient behavior related to valve motion that can serve as guidelines for valve scheduling. Such predictions of valve response to varying flow conditions is of crucial importance to engine operation and testing.

System Models and Aging: A Driving Example.

ERIC Educational Resources Information Center

Melichar, Joseph F.

Chronological age is a marker in time but it fails to measure accurately the performance or behavioral characteristics of individuals. This paper models the complexity of aging by using a system model and a human function paradigm. These models help facilitate representation of older adults, integrate research agendas, and enhance remediative…

Neurogenic Communication Disorders and Paralleling Agraphic Disturbances: Implications for Concerns in Basic Writing.

ERIC Educational Resources Information Center

De Jarnette, Glenda

Vertical and lateral integration are two important nervous system integrations that affect the development of oral behaviors. There are three progressions in the vertical integration process for speech nervous system development: R-complex speech (ritualistic, memorized expressions), limbic speech (emotional expressions), and cortical speech…

Public Relations Roles and Systems Theory: Functional and Historicist Causal Models.

ERIC Educational Resources Information Center

Broom, Glen M.

The effectiveness of an organizations's adaptive behavior depends on the extent to which public relations concerns are considered in goal setting and program planning. The following five open systems propositions, based on a "functional" paradigm, address the complex relationship between public relations and organizational intelligence and do not…

New gelling systems to fabricate complex-shaped transparent ceramics

NASA Astrophysics Data System (ADS)

Yang, Yan; Wu, Yiquan

2013-06-01

The aim of this work was to prepare transparent ceramics with large size and complex-shapes by a new water-soluble gelling agent poly(isobutylene-alt-maleic anhydride). Alumina was used as an example of the application of the new gelling system. A stable suspension with 38vol% was prepared by ball milling. Trapped bubbles were removed before casting to obtain homogenous green bodies. The microstructure and particle distribution of alumina raw material were tested. The thermal behavior of the alumina green body was investigated, which exhibited low weight loss when compared with other gelling processes. The influence of solid loading and gelling agent addition were studied on the basis of rheological behavior of the suspension. The microstructures of alumina powders, green bodies before and after de-bindering process, were compared to understand the gelling condition between alumina particles and gelling agent.

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

NASA Technical Reports Server (NTRS)

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.

Interactions of platinum metals and their complexes in biological systems.

PubMed Central

LeRoy, A F

1975-01-01

Platinum-metal oxidation catalysts are to be introduced in exhaust systems of many 1975 model-year automobiles in the U.S. to meet Clean Air Act standards. Small quantities of finely divided catalyst have been found issuing from prototype systems; platinum and palladium compounds may be found also. Although platinum exhibits a remarkable resistance to oxidation and chemical attack, it reacts chemically under some conditions producing coordination complex compounds. Palladium reacts more readily than platinum. Some platinum-metal complexes interact with biological systems as bacteriostatic, bacteriocidal, viricidal, and immunosuppressive agents. Workers chronically exposed to platinum complexes often develop asthma-like respiratory distress and skin reactions called platinosis. Platinum complexes used alone and in combination therapy with other drugs have recently emerged as effective agents in cancer chemotherapy. Understanding toxic and favorable interactions of metal species with living organisms requires basic information on quantities and chemical characteristics of complexes at trace concentrations in biological materials. Some basic chemical kinetic and thermodynamic data are presented to characterize the chemical behavior of the complex cis-[Pt(NH3)2Cl2] used therapeutically. A brief discussion of platinum at manogram levels in biological tissue is discussed. PMID:50943

The Limitations of Model-Based Experimental Design and Parameter Estimation in Sloppy Systems

PubMed Central

Tolman, Malachi; Thames, Howard D.; Mason, Kathy A.

2016-01-01

We explore the relationship among experimental design, parameter estimation, and systematic error in sloppy models. We show that the approximate nature of mathematical models poses challenges for experimental design in sloppy models. In many models of complex biological processes it is unknown what are the relevant physical mechanisms that must be included to explain system behaviors. As a consequence, models are often overly complex, with many practically unidentifiable parameters. Furthermore, which mechanisms are relevant/irrelevant vary among experiments. By selecting complementary experiments, experimental design may inadvertently make details that were ommitted from the model become relevant. When this occurs, the model will have a large systematic error and fail to give a good fit to the data. We use a simple hyper-model of model error to quantify a model’s discrepancy and apply it to two models of complex biological processes (EGFR signaling and DNA repair) with optimally selected experiments. We find that although parameters may be accurately estimated, the discrepancy in the model renders it less predictive than it was in the sloppy regime where systematic error is small. We introduce the concept of a sloppy system–a sequence of models of increasing complexity that become sloppy in the limit of microscopic accuracy. We explore the limits of accurate parameter estimation in sloppy systems and argue that identifying underlying mechanisms controlling system behavior is better approached by considering a hierarchy of models of varying detail rather than focusing on parameter estimation in a single model. PMID:27923060

Spatiotemporal Detection of Unusual Human Population Behavior Using Mobile Phone Data

PubMed Central

Dobra, Adrian; Williams, Nathalie E.; Eagle, Nathan

2015-01-01

With the aim to contribute to humanitarian response to disasters and violent events, scientists have proposed the development of analytical tools that could identify emergency events in real-time, using mobile phone data. The assumption is that dramatic and discrete changes in behavior, measured with mobile phone data, will indicate extreme events. In this study, we propose an efficient system for spatiotemporal detection of behavioral anomalies from mobile phone data and compare sites with behavioral anomalies to an extensive database of emergency and non-emergency events in Rwanda. Our methodology successfully captures anomalous behavioral patterns associated with a broad range of events, from religious and official holidays to earthquakes, floods, violence against civilians and protests. Our results suggest that human behavioral responses to extreme events are complex and multi-dimensional, including extreme increases and decreases in both calling and movement behaviors. We also find significant temporal and spatial variance in responses to extreme events. Our behavioral anomaly detection system and extensive discussion of results are a significant contribution to the long-term project of creating an effective real-time event detection system with mobile phone data and we discuss the implications of our findings for future research to this end. PMID:25806954

Creative strategies of businesses with the holistic eigensolution in manufacturing industries

NASA Astrophysics Data System (ADS)

Zeichen, Gerfried; Huray, Paul G.

1998-10-01

It is a mission of this contribution to recognize and synthesize all the efforts in industry and in management science to strengthen our techniques and tools for successfully solving increasingly complex leadership problems in manufacturing industries. With the high standard of the work sharing method--the so called Taylorism principle--for cost efficient and mass production, invented at the beginning of the 20th century and the opening of the world market for global sales of goods and services a gigantic progress in living standards was reached. But at the beginning of the 21st century we are needing new ideas and methods for the guidance of overcoming increasing complexity. The holistic eigensolution presents a new operational framework for viewing and controlling the behavior of businesses. In contrast to the traditional process for viewing complex business systems through the intricate analysis of every part of that system, the authors have employed a technique used by physicists to understand the characteristic of `eigen' behaviors of complex physical systems. This method of systems analysis is achieved by observing interactions between the parts in a whole. This kind of analysis has a rigorous mathematical foundation in the physical world and it can be employed to understand most natural phenomena. Within a holistic framework, the observer is challenged to view the system form just the right perspective so that characteristic eigenmodes reveal themselves. The conclusion of the article describes why exactly the intelligent manufacturing science--especially in a broader sense--has the responsibility and chance to develop the holistic eigensolution framework as a Taylorism II-principle for the 21st century.

Complexity in Soil Systems: What Does It Mean and How Should We Proceed?

NASA Astrophysics Data System (ADS)

Faybishenko, B.; Molz, F. J.; Brodie, E.; Hubbard, S. S.

2015-12-01

The complex soil systems approach is needed fundamentally for the development of integrated, interdisciplinary methods to measure and quantify the physical, chemical and biological processes taking place in soil, and to determine the role of fine-scale heterogeneities. This presentation is aimed at a review of the concepts and observations concerning complexity and complex systems theory, including terminology, emergent complexity and simplicity, self-organization and a general approach to the study of complex systems using the Weaver (1948) concept of "organized complexity." These concepts are used to provide understanding of complex soil systems, and to develop experimental and mathematical approaches to soil microbiological processes. The results of numerical simulations, observations and experiments are presented that indicate the presence of deterministic chaotic dynamics in soil microbial systems. So what are the implications for the scientists who wish to develop mathematical models in the area of organized complexity or to perform experiments to help clarify an aspect of an organized complex system? The modelers have to deal with coupled systems having at least three dependent variables, and they have to forgo making linear approximations to nonlinear phenomena. The analogous rule for experimentalists is that they need to perform experiments that involve measurement of at least three interacting entities (variables depending on time, space, and each other). These entities could be microbes in soil penetrated by roots. If a process being studied in a soil affects the soil properties, like biofilm formation, then this effect has to be measured and included. The mathematical implications of this viewpoint are examined, and results of numerical solutions to a system of equations demonstrating deterministic chaotic behavior are also discussed using time series and the 3D strange attractors.

Growth condition dependency is the major cause of non-responsiveness upon genetic perturbation

PubMed Central

Amini, Saman; Holstege, Frank C. P.

2017-01-01

Investigating the role and interplay between individual proteins in biological processes is often performed by assessing the functional consequences of gene inactivation or removal. Depending on the sensitivity of the assay used for determining phenotype, between 66% (growth) and 53% (gene expression) of Saccharomyces cerevisiae gene deletion strains show no defect when analyzed under a single condition. Although it is well known that this non-responsive behavior is caused by different types of redundancy mechanisms or by growth condition/cell type dependency, it is not known what the relative contribution of these different causes is. Understanding the underlying causes of and their relative contribution to non-responsive behavior upon genetic perturbation is extremely important for designing efficient strategies aimed at elucidating gene function and unraveling complex cellular systems. Here, we provide a systematic classification of the underlying causes of and their relative contribution to non-responsive behavior upon gene deletion. The overall contribution of redundancy to non-responsive behavior is estimated at 29%, of which approximately 17% is due to homology-based redundancy and 12% is due to pathway-based redundancy. The major determinant of non-responsiveness is condition dependency (71%). For approximately 14% of protein complexes, just-in-time assembly can be put forward as a potential mechanistic explanation for how proteins can be regulated in a condition dependent manner. Taken together, the results underscore the large contribution of growth condition requirement to non-responsive behavior, which needs to be taken into account for strategies aimed at determining gene function. The classification provided here, can also be further harnessed in systematic analyses of complex cellular systems. PMID:28257504

Simple models for studying complex spatiotemporal patterns of animal behavior

NASA Astrophysics Data System (ADS)

Tyutyunov, Yuri V.; Titova, Lyudmila I.

2017-06-01

Minimal mathematical models able to explain complex patterns of animal behavior are essential parts of simulation systems describing large-scale spatiotemporal dynamics of trophic communities, particularly those with wide-ranging species, such as occur in pelagic environments. We present results obtained with three different modelling approaches: (i) an individual-based model of animal spatial behavior; (ii) a continuous taxis-diffusion-reaction system of partial-difference equations; (iii) a 'hybrid' approach combining the individual-based algorithm of organism movements with explicit description of decay and diffusion of the movement stimuli. Though the models are based on extremely simple rules, they all allow description of spatial movements of animals in a predator-prey system within a closed habitat, reproducing some typical patterns of the pursuit-evasion behavior observed in natural populations. In all three models, at each spatial position the animal movements are determined by local conditions only, so the pattern of collective behavior emerges due to self-organization. The movement velocities of animals are proportional to the density gradients of specific cues emitted by individuals of the antagonistic species (pheromones, exometabolites or mechanical waves of the media, e.g., sound). These cues play a role of taxis stimuli: prey attract predators, while predators repel prey. Depending on the nature and the properties of the movement stimulus we propose using either a simplified individual-based model, a continuous taxis pursuit-evasion system, or a little more detailed 'hybrid' approach that combines simulation of the individual movements with the continuous model describing diffusion and decay of the stimuli in an explicit way. These can be used to improve movement models for many species, including large marine predators.

Dynamic Modeling of ALS Systems

NASA Technical Reports Server (NTRS)

Jones, Harry

2002-01-01

The purpose of dynamic modeling and simulation of Advanced Life Support (ALS) systems is to help design them. Static steady state systems analysis provides basic information and is necessary to guide dynamic modeling, but static analysis is not sufficient to design and compare systems. ALS systems must respond to external input variations and internal off-nominal behavior. Buffer sizing, resupply scheduling, failure response, and control system design are aspects of dynamic system design. We develop two dynamic mass flow models and use them in simulations to evaluate systems issues, optimize designs, and make system design trades. One model is of nitrogen leakage in the space station, the other is of a waste processor failure in a regenerative life support system. Most systems analyses are concerned with optimizing the cost/benefit of a system at its nominal steady-state operating point. ALS analysis must go beyond the static steady state to include dynamic system design. All life support systems exhibit behavior that varies over time. ALS systems must respond to equipment operating cycles, repair schedules, and occasional off-nominal behavior or malfunctions. Biological components, such as bioreactors, composters, and food plant growth chambers, usually have operating cycles or other complex time behavior. Buffer sizes, material stocks, and resupply rates determine dynamic system behavior and directly affect system mass and cost. Dynamic simulation is needed to avoid the extremes of costly over-design of buffers and material reserves or system failure due to insufficient buffers and lack of stored material.

Theory of reliable systems. [systems analysis and design

NASA Technical Reports Server (NTRS)

Meyer, J. F.

1973-01-01

The analysis and design of reliable systems are discussed. The attributes of system reliability studied are fault tolerance, diagnosability, and reconfigurability. Objectives of the study include: to determine properties of system structure that are conducive to a particular attribute; to determine methods for obtaining reliable realizations of a given system; and to determine how properties of system behavior relate to the complexity of fault tolerant realizations. A list of 34 references is included.

Locus coeruleus to basolateral amygdala noradrenergic projections promote anxiety-like behavior

PubMed Central

McCall, Jordan G; Siuda, Edward R; Bhatti, Dionnet L; Lawson, Lamley A; McElligott, Zoe A; Stuber, Garret D; Bruchas, Michael R

2017-01-01

Increased tonic activity of locus coeruleus noradrenergic (LC-NE) neurons induces anxiety-like and aversive behavior. While some information is known about the afferent circuitry that endogenously drives this neural activity and behavior, the downstream receptors and anatomical projections that mediate these acute risk aversive behavioral states via the LC-NE system remain unresolved. Here we use a combination of retrograde tracing, fast-scan cyclic voltammetry, electrophysiology, and in vivo optogenetics with localized pharmacology to identify neural substrates downstream of increased tonic LC-NE activity in mice. We demonstrate that photostimulation of LC-NE fibers in the BLA evokes norepinephrine release in the basolateral amygdala (BLA), alters BLA neuronal activity, conditions aversion, and increases anxiety-like behavior. Additionally, we report that β-adrenergic receptors mediate the anxiety-like phenotype of increased NE release in the BLA. These studies begin to illustrate how the complex efferent system of the LC-NE system selectively mediates behavior through distinct receptor and projection-selective mechanisms. DOI: http://dx.doi.org/10.7554/eLife.18247.001 PMID:28708061

Disordered models of acquired dyslexia

NASA Astrophysics Data System (ADS)

Virasoro, M. A.

We show that certain specific correlations in the probability of errors observed in dyslexic patients that are normally explained by introducing additional complexity in the model for the reading process are typical of any Neural Network system that has learned to deal with a quasiregular environment. On the other hand we show that in Neural Networks the more regular behavior does not become naturally the default behavior.

Empirical modeling for intelligent, real-time manufacture control

NASA Technical Reports Server (NTRS)

Xu, Xiaoshu

1994-01-01

Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper.

Experimentally modeling stochastic processes with less memory by the use of a quantum processor

PubMed Central

Palsson, Matthew S.; Gu, Mile; Ho, Joseph; Wiseman, Howard M.; Pryde, Geoff J.

2017-01-01

Computer simulation of observable phenomena is an indispensable tool for engineering new technology, understanding the natural world, and studying human society. However, the most interesting systems are often so complex that simulating their future behavior demands storing immense amounts of information regarding how they have behaved in the past. For increasingly complex systems, simulation becomes increasingly difficult and is ultimately constrained by resources such as computer memory. Recent theoretical work shows that quantum theory can reduce this memory requirement beyond ultimate classical limits, as measured by a process’ statistical complexity, C. We experimentally demonstrate this quantum advantage in simulating stochastic processes. Our quantum implementation observes a memory requirement of Cq = 0.05 ± 0.01, far below the ultimate classical limit of C = 1. Scaling up this technique would substantially reduce the memory required in simulations of more complex systems. PMID:28168218

Transport behaviors of locally fractional coupled Brownian motors with fluctuating interactions

NASA Astrophysics Data System (ADS)

Wang, Huiqi; Ni, Feixiang; Lin, Lifeng; Lv, Wangyong; Zhu, Hongqiang

2018-09-01

In some complex viscoelastic mediums, it is ubiquitous that absorbing and desorbing surrounding Brownian particles randomly occur in coupled systems. The conventional method is to model a variable-mass system driven by both multiplicative and additive noises. In this paper, an improved mathematical model is created based on generalized Langevin equations (GLE) to characterize the random interaction with locally fluctuating number of coupled particles in the elastically coupled factional Brownian motors (FBM). By the numerical simulations, the effect of fluctuating interactions on collective transport behaviors is investigated, and some abnormal phenomena, such as cooperative behaviors, stochastic resonance (SR) and anomalous transport, are observed in the regime of sub-diffusion.

Scale Invariance in Lateral Head Scans During Spatial Exploration.

PubMed

Yadav, Chetan K; Doreswamy, Yoganarasimha

2017-04-14

Universality connects various natural phenomena through physical principles governing their dynamics, and has provided broadly accepted answers to many complex questions, including information processing in neuronal systems. However, its significance in behavioral systems is still elusive. Lateral head scanning (LHS) behavior in rodents might contribute to spatial navigation by actively managing (optimizing) the available sensory information. Our findings of scale invariant distributions in LHS lifetimes, interevent intervals and event magnitudes, provide evidence for the first time that the optimization takes place at a critical point in LHS dynamics. We propose that the LHS behavior is responsible for preprocessing of the spatial information content, critical for subsequent foolproof encoding by the respective downstream neural networks.

Scale Invariance in Lateral Head Scans During Spatial Exploration

NASA Astrophysics Data System (ADS)

Yadav, Chetan K.; Doreswamy, Yoganarasimha

2017-04-01

Universality connects various natural phenomena through physical principles governing their dynamics, and has provided broadly accepted answers to many complex questions, including information processing in neuronal systems. However, its significance in behavioral systems is still elusive. Lateral head scanning (LHS) behavior in rodents might contribute to spatial navigation by actively managing (optimizing) the available sensory information. Our findings of scale invariant distributions in LHS lifetimes, interevent intervals and event magnitudes, provide evidence for the first time that the optimization takes place at a critical point in LHS dynamics. We propose that the LHS behavior is responsible for preprocessing of the spatial information content, critical for subsequent foolproof encoding by the respective downstream neural networks.

Traffic flow theory and chaotic behavior

DOT National Transportation Integrated Search

1989-03-01

Many commonly occurring natural systems are modeled with mathematical experessions and exhibit a certain stability. The inherent stability of these equations allows them to serve as the basis for engineering predictions. More complex models, such as ...

Implementation of behavioral health interventions in real world scenarios: Managing complex change.

PubMed

Clark, Khaya D; Miller, Benjamin F; Green, Larry A; de Gruy, Frank V; Davis, Melinda; Cohen, Deborah J

2017-03-01

A practice embarks on a radical reformulation of how care is designed and delivered when it decides to integrate medical and behavioral health care for its patients and success depends on managing complex change in a complex system. We examined the ways change is managed when integrating behavioral health and medical care. Observational cross-case comparative study of 19 primary care and community mental health practices. We collected mixed methods data through practice surveys, observation, and semistructured interviews. We analyzed data using a data-driven, emergent approach. The change management strategies that leadership employed to manage the changes of integrating behavioral health and medical care included: (a) advocating for a mission and vision focused on integrated care; (b) fostering collaboration, with a focus on population care and a team-based approaches; (c) attending to learning, which includes viewing the change process as continuous, and creating a culture that promoted reflection and continual improvement; (d) using data to manage change, and (e) developing approaches to finance integration. This paper reports the change management strategies employed by practice leaders making changes to integrate care, as observed by independent investigators. We offer an empirically based set of actionable recommendations that are relevant to a range of leaders (policymakers, medical directors) and practice members who wish to effectively manage the complex changes associated with integrated primary care. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Enriched Environment Increases PCNA and PARP1 Levels in Octopus vulgaris Central Nervous System: First Evidence of Adult Neurogenesis in Lophotrochozoa.

PubMed

Bertapelle, Carla; Polese, Gianluca; Di Cosmo, Anna

2017-06-01

Organisms showing a complex and centralized nervous system, such as teleosts, amphibians, reptiles, birds and mammals, and among invertebrates, crustaceans and insects, can adjust their behavior according to the environmental challenges. Proliferation, differentiation, migration, and axonal and dendritic development of newborn neurons take place in brain areas where structural plasticity, involved in learning, memory, and sensory stimuli integration, occurs. Octopus vulgaris has a complex and centralized nervous system, located between the eyes, with a hierarchical organization. It is considered the most "intelligent" invertebrate for its advanced cognitive capabilities, as learning and memory, and its sophisticated behaviors. The experimental data obtained by immunohistochemistry and western blot assay using proliferating cell nuclear antigen and poli (ADP-ribose) polymerase 1 as marker of cell proliferation and synaptogenesis, respectively, reviled cell proliferation in areas of brain involved in learning, memory, and sensory stimuli integration. Furthermore, we showed how enriched environmental conditions affect adult neurogenesis. © 2017 Wiley Periodicals, Inc.

Emergence of Life-Like Properties from Dissipative Self-Assembly of Nanoparticles

NASA Astrophysics Data System (ADS)

Ilday, Serim; Makey, Ghaith; Akguc, Gursoy B.; Yavuz, Ozgun; Tokel, Onur; Pavlov, Ihor; Gulseren, Oguz; Ilday, F. Omer

A profoundly fundamental question at the interface between physics and biology remains open: What are the minimum requirements for emergence of life-like properties from non-living systems? Here, we address this question and report emergent complex behavior of tens to thousands of colloidal nanoparticles in a system designed to be as plain as possible: The system is driven far from equilibrium by ultrafast laser pulses, which create spatiotemporal temperature gradients, inducing Marangoni-type flow that drags the particles towards aggregation; strong Brownian motion, used as source of fluctuations, opposes aggregation. Nonlinear feedback mechanisms naturally arise between the flow, the aggregate, and Brownian motion, allowing fast external control with minimal intervention. Consequently, complex behavior, analogous to those commonly seen in living organisms, emerges, whereby the aggregates can self-sustain, self-regulate, self-replicate, self-heal and can be transferred from one location to another, all within seconds. Aggregates can comprise of only one pattern or bifurcated patterns can co-exist, compete, survive or die.

Antecedents of the People and Organizational Aspects of Medical Informatics

PubMed Central

Lorenzi, Nancy M.; Riley, Robert T.; Blyth, Andrew J. C.; Southon, Gray; Dixon, Bradley J.

1997-01-01

Abstract People and organizational issues are critical in both implementing medical informatics systems and in dealing with the altered organizations that new systems often create. The people and organizational issues area—like medical informatics itself—is a blend of many disciplines. The academic disciplines of psychology, sociology, social psychology, social anthropology, organizational behavior and organizational development, management, and cognitive sciences are rich with research with significant potential to ease the introduction and on-going use of information technology in today's complex health systems. These academic areas contribute research data and core information for better understanding of such issues as the importance of and processes for creating future direction; managing a complex change process; effective strategies for involving individuals and groups in the informatics effort; and effectively managing the altered organization. This article reviews the behavioral and business referent disciplines that can potentially contribute to improved implementations and on-going management of change in the medical informatics arena. PMID:9067874

The CRF system and social behavior: a review

PubMed Central

Hostetler, Caroline M.; Ryabinin, Andrey E.

2013-01-01

The corticotropin-releasing factor (CRF) system plays a key role in a diversity of behaviors accompanying stress, anxiety and depression. There is also substantial research on relationships between social behaviors and the CRF system in a variety of taxa including fish, birds, rodents, and primates. Some of these relationships are due to the broad role of CRF and urocortins in stress and anxiety, but these peptides also modulate social behavior specifically. For example, the social interaction (SI) test is often used to measure anxiety-like behavior. Many components of the CRF system including CRF, urocortin1, and the R1 receptor have been implicated in SI, via general effects on anxiety as well as specific effects depending on the brain region. The CRF system is also highly responsive to chronic social stressors such as social defeat and isolation. Animals exposed to these stressors display a number of anxiety- and stress-related behaviors, accompanied by changes in specific components the CRF system. Although the primary focus of CRF research on social behavior has been on the deleterious effects of social stress, there are also insights on a role for CRF and urocortins in prosocial and affiliative behaviors. The CRF system has been implicated in parental care, maternal defense, sexual behavior, and pair bonding. Species differences in the ligands and CRF receptors have been observed in vole and bird species differing in social behavior. Exogenous administration of CRF facilitates partner preference formation in monogamous male prairie voles, and these effects are dependent on both the CRF R1 and R2 receptors. These findings are particularly interesting as studies have also implicated the CRF and urocortins in social memory. With the rapid progress of social neuroscience and in understanding the complex structure of the CRF system, the next challenge is in parsing the exact contribution of individual components of this system to specific social behaviors. PMID:23754975

The CRF system and social behavior: a review.

PubMed

Hostetler, Caroline M; Ryabinin, Andrey E

2013-01-01

The corticotropin-releasing factor (CRF) system plays a key role in a diversity of behaviors accompanying stress, anxiety and depression. There is also substantial research on relationships between social behaviors and the CRF system in a variety of taxa including fish, birds, rodents, and primates. Some of these relationships are due to the broad role of CRF and urocortins in stress and anxiety, but these peptides also modulate social behavior specifically. For example, the social interaction (SI) test is often used to measure anxiety-like behavior. Many components of the CRF system including CRF, urocortin1, and the R1 receptor have been implicated in SI, via general effects on anxiety as well as specific effects depending on the brain region. The CRF system is also highly responsive to chronic social stressors such as social defeat and isolation. Animals exposed to these stressors display a number of anxiety- and stress-related behaviors, accompanied by changes in specific components the CRF system. Although the primary focus of CRF research on social behavior has been on the deleterious effects of social stress, there are also insights on a role for CRF and urocortins in prosocial and affiliative behaviors. The CRF system has been implicated in parental care, maternal defense, sexual behavior, and pair bonding. Species differences in the ligands and CRF receptors have been observed in vole and bird species differing in social behavior. Exogenous administration of CRF facilitates partner preference formation in monogamous male prairie voles, and these effects are dependent on both the CRF R1 and R2 receptors. These findings are particularly interesting as studies have also implicated the CRF and urocortins in social memory. With the rapid progress of social neuroscience and in understanding the complex structure of the CRF system, the next challenge is in parsing the exact contribution of individual components of this system to specific social behaviors.

Swarms, phase transitions, and collective intelligence

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

Millonas, M.M.

1992-01-01

A model of the collective behavior of a large number of locally acting organisms is proposed. The model is intended to be realistic, but turns out to fit naturally into the category of connectionist models, Like all connectionist models, its properties can be divided into the categories of structure, dynamics, and learning. The space in which the organisms move is discretized, and is modeled by a lattice of nodes, or cells. Each cell hag a specified volume, and is connected to other cells in the space in a definite way. Organisms move probabilistically between local cells in this space, butmore » with weights dependent on local morphogenic substances, or morphogens. The morphogens are in turn are effected by the passage of an organism. The evolution of the morphogens, and the corresponding constitutes of the organisms constitutes the collective behavior of the group. The generic properties of such systems are analyzed, and a number of results are obtained. The model has various types of phase transitions and self-organizing properties controlled both by the level of the noise, and other parameters. It is hoped that the present mode; might serve as a paradigmatic example of a complex cooperative system in nature. In particular this model can be used to explore the relation of phase transitions to at least three important issues encountered in artificial life. Firstly, that of emergence as complex adaptive behavior. Secondly, as an exploration of second order phase transitions in biological systems. Lastly, to derive behavioral criteria for the evolution of collective behavior in social organisms. The model is then applied to the specific case of ants moving on a lattice. The local behavior of the ants is inspired by the actual behavior observed in the laboratory, and analytic results for the collective behavior are compared to the corresponding laboratory results. Monte carlo simulations are used as illustrations.« less

Swarms, phase transitions, and collective intelligence

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

Millonas, M.M.

1992-12-31

A model of the collective behavior of a large number of locally acting organisms is proposed. The model is intended to be realistic, but turns out to fit naturally into the category of connectionist models, Like all connectionist models, its properties can be divided into the categories of structure, dynamics, and learning. The space in which the organisms move is discretized, and is modeled by a lattice of nodes, or cells. Each cell hag a specified volume, and is connected to other cells in the space in a definite way. Organisms move probabilistically between local cells in this space, butmore » with weights dependent on local morphogenic substances, or morphogens. The morphogens are in turn are effected by the passage of an organism. The evolution of the morphogens, and the corresponding constitutes of the organisms constitutes the collective behavior of the group. The generic properties of such systems are analyzed, and a number of results are obtained. The model has various types of phase transitions and self-organizing properties controlled both by the level of the noise, and other parameters. It is hoped that the present mode; might serve as a paradigmatic example of a complex cooperative system in nature. In particular this model can be used to explore the relation of phase transitions to at least three important issues encountered in artificial life. Firstly, that of emergence as complex adaptive behavior. Secondly, as an exploration of second order phase transitions in biological systems. Lastly, to derive behavioral criteria for the evolution of collective behavior in social organisms. The model is then applied to the specific case of ants moving on a lattice. The local behavior of the ants is inspired by the actual behavior observed in the laboratory, and analytic results for the collective behavior are compared to the corresponding laboratory results. Monte carlo simulations are used as illustrations.« less

Supramolecular structure, phase behavior and thermo-rheological properties of a poly (L-lactide-co-ε-caprolactone) statistical copolymer.

PubMed

Ugartemendia, Jone M; Muñoz, M E; Santamaria, A; Sarasua, J R

2015-08-01

PLAcoCL samples, both unaged, termed PLAcoCLu, and aged over time, PLAcoCLa, were prepared and analyzed to study the phase structure, morphology, and their evolution under non-quiescent conditions. X- ray diffraction, Differential Scanning Calorimetry and Atomic Force Microscopy were complemented with thermo-rheological measurements to reveal that PLAcoCL evolves over time from a single amorphous metastable state to a 3 phase system, made up of two compositionally different amorphous phases and a crystalline phase. The supramolecular arrangements developed during aging lead to a rheological complex behavior in the PLAcoCLa copolymer: Around Tt=131 °C thermo-rheological complexity and a peculiar chain mobility reduction were observed, but at T>Tt the thermo-rheological response of a homogeneous system was recorded. In comparison with the latter, the PLLA/PCL 70:30 physical blend counterpart showed double amorphous phase behavior at all temperatures, supporting the hypothesis that phase separation in the PLAcoCLa copolymer is caused by the crystallization of polylactide segment blocks during aging. Copyright © 2015 Elsevier Ltd. All rights reserved.

Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems

PubMed Central

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

2015-01-01

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

Re-187-Os-187, Pt-190-Os-186 Isotopic and Highly Siderophile Element Systematics of Group IVA Irons

NASA Technical Reports Server (NTRS)

Walker, R. J.; McCoy, T. J.; Schulte, R. F.; McDonough, W. F.; Ash, R. D.

2005-01-01

We have recently completed Re-187-Os-187 and Pt-190-Os-186 isotopic and elemental studies of the two largest magmatic iron meteorite groups, IIAB and IIIAB [1]. These studies revealed closed-system behavior of both isotopic systems, but complex trace element behavior for Re, Pt and Os in group IIIAB. Here we examine isotopic and trace elemental systematics of group IVA irons. The IVA irons are not as extensively fractionated as IIAB and IIIAB and their apparently less complex crystallization history may make for more robust interpretation of the relative partitioning behavior of Re, Pt and Os, as well as the other highly siderophile elements (HSE) measured here; Pd, Ru and Ir [e.g. 2]. An additional goal of our continuing research plan for iron meteorites is to assess the possibility of relating certain ungrouped irons with major groups via trace element modeling. Here, the isotopic and trace element systematics of the ungrouped irons Nedagolla and EET 83230 are compared with the IVA irons.

Adaptive System Modeling for Spacecraft Simulation

NASA Technical Reports Server (NTRS)

Thomas, Justin

2011-01-01

This invention introduces a methodology and associated software tools for automatically learning spacecraft system models without any assumptions regarding system behavior. Data stream mining techniques were used to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). Evaluation on historical ISS telemetry data shows that adaptive system modeling reduces simulation error anywhere from 50 to 90 percent over existing approaches. The purpose of the methodology is to outline how someone can create accurate system models from sensor (telemetry) data. The purpose of the software is to support the methodology. The software provides analysis tools to design the adaptive models. The software also provides the algorithms to initially build system models and continuously update them from the latest streaming sensor data. The main strengths are as follows: Creates accurate spacecraft system models without in-depth system knowledge or any assumptions about system behavior. Automatically updates/calibrates system models using the latest streaming sensor data. Creates device specific models that capture the exact behavior of devices of the same type. Adapts to evolving systems. Can reduce computational complexity (faster simulations).

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

NASA Astrophysics Data System (ADS)

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.

Complex collective dynamics of active torque-driven colloids at interfaces

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

Snezhko, Alexey

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

A fluid-filled soft robot that exhibits spontaneous switching among versatile spatiotemporal oscillatory patterns inspired by the true slime mold.

PubMed

Umedachi, Takuya; Idei, Ryo; Ito, Kentaro; Ishiguro, Akio

2013-01-01

Behavioral diversity is an essential feature of living systems, enabling them to exhibit adaptive behavior in hostile and dynamically changing environments. However, traditional engineering approaches strive to avoid, or suppress, the behavioral diversity in artificial systems to achieve high performance in specific environments for given tasks. The goals of this research include understanding how living systems exhibit behavioral diversity and using these findings to build lifelike robots that exhibit truly adaptive behaviors. To this end, we have focused on one of the most primitive forms of intelligence concerning behavioral diversity, namely, a plasmodium of true slime mold. The plasmodium is a large amoeba-like unicellular organism that does not possess any nervous system or specialized organs. However, it exhibits versatile spatiotemporal oscillatory patterns and switches spontaneously between these. Inspired by the plasmodium, we built a mathematical model that exhibits versatile oscillatory patterns and spontaneously transitions between these patterns. This model demonstrates that, in contrast to coupled nonlinear oscillators with a well-designed complex diffusion network, physically interacting mechanosensory oscillators are capable of generating versatile oscillatory patterns without changing any parameters. Thus, the results are expected to shed new light on the design scheme for lifelike robots that exhibit amazingly versatile and adaptive behaviors.

Aviation Safety: Modeling and Analyzing Complex Interactions between Humans and Automated Systems

NASA Technical Reports Server (NTRS)

Rungta, Neha; Brat, Guillaume; Clancey, William J.; Linde, Charlotte; Raimondi, Franco; Seah, Chin; Shafto, Michael

2013-01-01

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Ueberligen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.

Topics in Complexity: From Physical to Life Science Systems

NASA Astrophysics Data System (ADS)

Charry, Pedro David Manrique

Complexity seeks to unwrap the mechanisms responsible for collective phenomena across the physical, biological, chemical, economic and social sciences. This thesis investigates real-world complex dynamical systems ranging from the quantum/natural domain to the social domain. The following novel understandings are developed concerning these systems' out-of-equilibrium and nonlinear behavior. Standard quantum techniques show divergent outcomes when a quantum system comprising more than one subunit is far from thermodynamic equilibrium. Abnormal photon inter-arrival times help fulfill the metabolic needs of a terrestrial photosynthetic bacterium. Spatial correlations within incident light can act as a driving mechanism for an organism's adaptation toward more ordered structures. The group dynamics of non-identical objects, whose assembly rules depend on mutual heterogeneity, yield rich transition dynamics between isolation and cohesion, with the cohesion regime reproducing a particular universal pattern commonly found in many real-world systems. Analyses of covert networks reveal collective gender superiority in the connectivity that provides benefits for system robustness and survival. Nodal migration in a network generates complex contagion profiles that lie beyond traditional approaches and yet resemble many modern-day outbreaks.

Properties of a Formal Method for Prediction of Emergent Behaviors in Swarm-based Systems

NASA Technical Reports Server (NTRS)

Rouff, Christopher; Vanderbilt, Amy; Hinchey, Mike; Truszkowski, Walt; Rash, James

2004-01-01

Autonomous intelligent swarms of satellites are being proposed for NASA missions that have complex behaviors and interactions. The emergent properties of swarms make these missions powerful, but at the same time more difficult to design and assure that proper behaviors will emerge. This paper gives the results of research into formal methods techniques for verification and validation of NASA swarm-based missions. Multiple formal methods were evaluated to determine their effectiveness in modeling and assuring the behavior of swarms of spacecraft. The NASA ANTS mission was used as an example of swarm intelligence for which to apply the formal methods. This paper will give the evaluation of these formal methods and give partial specifications of the ANTS mission using four selected methods. We then give an evaluation of the methods and the needed properties of a formal method for effective specification and prediction of emergent behavior in swarm-based systems.

A Neurobehavioral Model of Flexible Spatial Language Behaviors

PubMed Central

Lipinski, John; Schneegans, Sebastian; Sandamirskaya, Yulia; Spencer, John P.; Schöner, Gregor

2012-01-01

We propose a neural dynamic model that specifies how low-level visual processes can be integrated with higher level cognition to achieve flexible spatial language behaviors. This model uses real-word visual input that is linked to relational spatial descriptions through a neural mechanism for reference frame transformations. We demonstrate that the system can extract spatial relations from visual scenes, select items based on relational spatial descriptions, and perform reference object selection in a single unified architecture. We further show that the performance of the system is consistent with behavioral data in humans by simulating results from 2 independent empirical studies, 1 spatial term rating task and 1 study of reference object selection behavior. The architecture we present thereby achieves a high degree of task flexibility under realistic stimulus conditions. At the same time, it also provides a detailed neural grounding for complex behavioral and cognitive processes. PMID:21517224

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

ERIC Educational Resources Information Center

Pennings, Helena J. M.

2017-01-01

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

X-ray radiographic measurements of falling beads in thermally heated Comp B

NASA Astrophysics Data System (ADS)

Suvorova, Natalya; Remelius, Dennis; Oschwald, David; Smilowitz, Laura; Henson, Bryan; Davis, Stephen; Zerkle, David

2017-06-01

We have studied the behavior of Composition B under thermal heating conditions. Comp B formulation has complex thermal behavior due to the combination of 40% low melting point TNT and 60% RDX. At temperatures above the TNT melt, the mechanical behavior of Comp B is complex and sensitive to handling conditions (for instance, stirred versus stationary). In this presentation, we will discuss our experiments studying the motion of embedded beads of various densities different from Comp B density as the system is heated above the TNT melt temperature and before the onset of significant gas generation in the Comp B which acts to mix the RDX and molten TNT. X-ray radiography was used to directly observe the motion of the embedded bead in the Comp B as it is slowly and uniformly heated.

Coexisting multiple attractors and riddled basins of a memristive system.

PubMed

Wang, Guangyi; Yuan, Fang; Chen, Guanrong; Zhang, Yu

2018-01-01

In this paper, a new memristor-based chaotic system is designed, analyzed, and implemented. Multistability, multiple attractors, and complex riddled basins are observed from the system, which are investigated along with other dynamical behaviors such as equilibrium points and their stabilities, symmetrical bifurcation diagrams, and sustained chaotic states. With different sets of system parameters, the system can also generate various multi-scroll attractors. Finally, the system is realized by experimental circuits.

Scaling the Pyramid Model across Complex Systems Providing Early Care for Preschoolers: Exploring How Models for Decision Making May Enhance Implementation Science

ERIC Educational Resources Information Center

Johnson, LeAnne D.

2017-01-01

Bringing effective practices to scale across large systems requires attending to how information and belief systems come together in decisions to adopt, implement, and sustain those practices. Statewide scaling of the Pyramid Model, a framework for positive behavior intervention and support, across different types of early childhood programs…

Evolutionary fields can explain patterns of high-dimensional complexity in ecology

NASA Astrophysics Data System (ADS)

Wilsenach, James; Landi, Pietro; Hui, Cang

2017-04-01

One of the properties that make ecological systems so unique is the range of complex behavioral patterns that can be exhibited by even the simplest communities with only a few species. Much of this complexity is commonly attributed to stochastic factors that have very high-degrees of freedom. Orthodox study of the evolution of these simple networks has generally been limited in its ability to explain complexity, since it restricts evolutionary adaptation to an inertia-free process with few degrees of freedom in which only gradual, moderately complex behaviors are possible. We propose a model inspired by particle-mediated field phenomena in classical physics in combination with fundamental concepts in adaptation, which suggests that small but high-dimensional chaotic dynamics near to the adaptive trait optimum could help explain complex properties shared by most ecological datasets, such as aperiodicity and pink, fractal noise spectra. By examining a simple predator-prey model and appealing to real ecological data, we show that this type of complexity could be easily confused for or confounded by stochasticity, especially when spurred on or amplified by stochastic factors that share variational and spectral properties with the underlying dynamics.

Model authoring system for fail safe analysis

NASA Technical Reports Server (NTRS)

Sikora, Scott E.

1990-01-01

The Model Authoring System is a prototype software application for generating fault tree analyses and failure mode and effects analyses for circuit designs. Utilizing established artificial intelligence and expert system techniques, the circuits are modeled as a frame-based knowledge base in an expert system shell, which allows the use of object oriented programming and an inference engine. The behavior of the circuit is then captured through IF-THEN rules, which then are searched to generate either a graphical fault tree analysis or failure modes and effects analysis. Sophisticated authoring techniques allow the circuit to be easily modeled, permit its behavior to be quickly defined, and provide abstraction features to deal with complexity.

Behavior systems and reinforcement: an integrative approach.

PubMed Central

Timberlake, W

1993-01-01

Most traditional conceptions of reinforcement are based on a simple causal model in which responding is strengthened by the presentation of a reinforcer. I argue that reinforcement is better viewed as the outcome of constraint of a functioning causal system comprised of multiple interrelated causal sequences, complex linkages between causes and effects, and a set of initial conditions. Using a simplified system conception of the reinforcement situation, I review the similarities and drawbacks of traditional reinforcement models and analyze the recent contributions of cognitive, regulatory, and ecological approaches. Finally, I show how the concept of behavior systems can begin to incorporate both traditional and recent conceptions of reinforcement in an integrative approach. PMID:8354963

The utility of vignettes to stimulate reflection on professionalism: theory and practice.

PubMed

Bernabeo, E C; Holmboe, E S; Ross, K; Chesluk, B; Ginsburg, S

2013-08-01

Professionalism remains a substantive theme in medical literature. There is an emerging emphasis on sociological and complex adaptive systems perspectives that refocuses attention from just the individual role to working within one's system to enact professionalism in practice. Reflecting on responses to professional dilemmas may be one method to help practicing physicians identify both internal and external factors contributing to (un) professional behavior. We present a rationale and theoretical framework that supports and guides a reflective approach to the self assessment of professionalism. Guided by principles grounded in this theoretical framework, we developed and piloted a set of vignettes on professionally challenging situations, designed to stimulate reflection in practicing physicians. Findings show that participants found the vignettes to be authentic and typical, and reported the group experience as facilitative around discussions of professional ambiguity. Providing an opportunity for physicians to reflect on professional behavior in an open and safe forum may be a practical way to guide physicians to assess themselves on professional behavior and engage with the complexities of their work. The finding that the focus groups led to reflection at a group level suggests that effective reflection on professional behavior may require a socially interactive process. Emphasizing both the behaviors and the internal and external context in which they occur can thus be viewed as critically important for understanding professionalism in practicing physicians.

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

NASA Astrophysics Data System (ADS)

Liu, Feng; Li, Yaguang

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

Research on the Complexity of Dual-Channel Supply Chain Model in Competitive Retailing Service Market

NASA Astrophysics Data System (ADS)

Ma, Junhai; Li, Ting; Ren, Wenbo

2017-06-01

This paper examines the optimal decisions of dual-channel game model considering the inputs of retailing service. We analyze how adjustment speed of service inputs affect the system complexity and market performance, and explore the stability of the equilibrium points by parameter basin diagrams. And chaos control is realized by variable feedback method. The numerical simulation shows that complex behavior would trigger the system to become unstable, such as double period bifurcation and chaos. We measure the performances of the model in different periods by analyzing the variation of average profit index. The theoretical results show that the percentage share of the demand and cross-service coefficients have important influence on the stability of the system and its feasible basin of attraction.

Nemesis Autonomous Test System

NASA Technical Reports Server (NTRS)

Barltrop, Kevin J.; Lee, Cin-Young; Horvath, Gregory A,; Clement, Bradley J.

2012-01-01

A generalized framework has been developed for systems validation that can be applied to both traditional and autonomous systems. The framework consists of an automated test case generation and execution system called Nemesis that rapidly and thoroughly identifies flaws or vulnerabilities within a system. By applying genetic optimization and goal-seeking algorithms on the test equipment side, a "war game" is conducted between a system and its complementary nemesis. The end result of the war games is a collection of scenarios that reveals any undesirable behaviors of the system under test. The software provides a reusable framework to evolve test scenarios using genetic algorithms using an operation model of the system under test. It can automatically generate and execute test cases that reveal flaws in behaviorally complex systems. Genetic algorithms focus the exploration of tests on the set of test cases that most effectively reveals the flaws and vulnerabilities of the system under test. It leverages advances in state- and model-based engineering, which are essential in defining the behavior of autonomous systems. It also uses goal networks to describe test scenarios.

Evolution of Cooperation in Social Dilemmas on Complex Networks

PubMed Central

Iyer, Swami; Killingback, Timothy

2016-01-01

Cooperation in social dilemmas is essential for the functioning of systems at multiple levels of complexity, from the simplest biological organisms to the most sophisticated human societies. Cooperation, although widespread, is fundamentally challenging to explain evolutionarily, since natural selection typically favors selfish behavior which is not socially optimal. Here we study the evolution of cooperation in three exemplars of key social dilemmas, representing the prisoner’s dilemma, hawk-dove and coordination classes of games, in structured populations defined by complex networks. Using individual-based simulations of the games on model and empirical networks, we give a detailed comparative study of the effects of the structural properties of a network, such as its average degree, variance in degree distribution, clustering coefficient, and assortativity coefficient, on the promotion of cooperative behavior in all three classes of games. PMID:26928428

Preface

NASA Astrophysics Data System (ADS)

Gidea, Marian; Sieber, Jan; Silber, Mary; Wieczorek, Sebastian

2015-05-01

This special issue on "Tipping Points: Fundamentals and Applications" is an offspring of the workshop with the same title held at the International Centre for Mathematical Sciences (ICMS), Edinburgh, between September 09-13, 2013. The theme of the meeting was the study of threshold behavior in complex environmental systems, such as Earth's climate, or ecological, sociological or economic systems.

The Effect of Functional Flow Diagrams on Apprentice Aircraft Mechanics' Technical System Understanding.

ERIC Educational Resources Information Center

Johnson, Scott D.; Satchwell, Richard E.

1993-01-01

Describes an experimental study that tested the impact of a conceptual illustration on college students' understanding of the structure, function, and behavior of complex technical systems. The use of functional flow diagrams in aircraft mechanics' training is explained, a concept map analysis is discussed, and implications for technical training…

Modeling Off-Nominal Behavior in SysML

NASA Technical Reports Server (NTRS)

Day, John; Donahue, Kenny; Ingham, Mitch; Kadesch, Alex; Kennedy, Kit; Post, Ethan

2012-01-01

Fault Management is an essential part of the system engineering process that is limited in its effectiveness by the ad hoc nature of the applied approaches and methods. Providing a rigorous way to develop and describe off-nominal behavior is a necessary step in the improvement of fault management, and as a result, will enable safe, reliable and available systems even as system complexity increases... The basic concepts described in this paper provide a foundation to build a larger set of necessary concepts and relationships for precise modeling of off-nominal behavior, and a basis for incorporating these ideas into the overall systems engineering process.. The simple FMEA example provided applies the modeling patterns we have developed and illustrates how the information in the model can be used to reason about the system and derive typical fault management artifacts.. A key insight from the FMEA work was the utility of defining failure modes as the "inverse of intent", and deriving this from the behavior models.. Additional work is planned to extend these ideas and capabilities to other types of relevant information and additional products.

The fractal geometry of Hartree-Fock

NASA Astrophysics Data System (ADS)

Theel, Friethjof; Karamatskou, Antonia; Santra, Robin

2017-12-01

The Hartree-Fock method is an important approximation for the ground-state electronic wave function of atoms and molecules so that its usage is widespread in computational chemistry and physics. The Hartree-Fock method is an iterative procedure in which the electronic wave functions of the occupied orbitals are determined. The set of functions found in one step builds the basis for the next iteration step. In this work, we interpret the Hartree-Fock method as a dynamical system since dynamical systems are iterations where iteration steps represent the time development of the system, as encountered in the theory of fractals. The focus is put on the convergence behavior of the dynamical system as a function of a suitable control parameter. In our case, a complex parameter λ controls the strength of the electron-electron interaction. An investigation of the convergence behavior depending on the parameter λ is performed for helium, neon, and argon. We observe fractal structures in the complex λ-plane, which resemble the well-known Mandelbrot set, determine their fractal dimension, and find that with increasing nuclear charge, the fragmentation increases as well.

Multi-Node Thermal System Model for Lithium-Ion Battery Packs: Preprint

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

Shi, Ying; Smith, Kandler; Wood, Eric

Temperature is one of the main factors that controls the degradation in lithium ion batteries. Accurate knowledge and control of cell temperatures in a pack helps the battery management system (BMS) to maximize cell utilization and ensure pack safety and service life. In a pack with arrays of cells, a cells temperature is not only affected by its own thermal characteristics but also by its neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model,more » which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs. neighbors, the cooling system and pack configuration, which increase the noise level and the complexity of cell temperatures prediction. This work proposes to model lithium ion packs thermal behavior using a multi-node thermal network model, which predicts the cell temperatures by zones. The model was parametrized and validated using commercial lithium-ion battery packs.« less

Macroscopic behavior and fluctuation-dissipation response of stochastic ecohydrological systems

NASA Astrophysics Data System (ADS)

Porporato, A. M.

2017-12-01

The coupled dynamics of water, carbon and nutrient cycles in ecohydrological systems is forced by unpredictable and intermittent hydroclimatic fluctuations at different time scales. While modeling and long-term prediction of these complex interactions often requires a probabilistic approach, the resulting stochastic equations however are only solvable in special cases. To obtain information on the behavior of the system one typically has to resort to approximation methods. Here we discuss macroscopic equations for the averages and fluctuation-dissipation estimates for the general correlations between the forcing and the ecohydrological response for the soil moisture-plant biomass interaction and the problem of primary salinization and nitrogen retention in soils.

Frontogenesis driven by horizontally quadratic distributions of density

NASA Technical Reports Server (NTRS)

Jacqmin, David

1991-01-01

Attention is given to the quadratic density distribution in a channel, which has been established by Simpson and Linden to be the simplest case of the horizontally nonlinear distribution of fluid density required for the production of frontogenesis. The porous-media and Boussinesq flow models are examined, and their evolution equations are reduced to one-dimensional systems. While both the porous-media and the inviscid/nondiffusive Boussinesq systems exhibit classic frontogenesis behavior, the viscous Boussinesq system exhibits a more complex behavior: boundary-layer effects force frontogenesis away from the lower boundary, and at late times the steepest density gradients are close to mid-channel.

Tour time in a two-route traffic system controlled by signals

NASA Astrophysics Data System (ADS)

Nagatani, Takashi; Naito, Yuichi

2011-11-01

We study the dynamic behavior of vehicular traffic in a two-route system with a series of signals (traffic lights) at low density where the number of signals on route A is different from that on route B. We investigate the dependence of the tour time on the route for some strategies of signal control. The nonlinear dynamic model of a two-route traffic system controlled by signals is presented by nonlinear maps. The vehicular traffic exhibits a very complex behavior, depending on the cycle time, the phase difference, and the irregularity. The dependence of the tour time on the route choice is clarified for the signal strategies.

Rule-Based Simulation of Multi-Cellular Biological Systems—A Review of Modeling Techniques

PubMed Central

Hwang, Minki; Garbey, Marc; Berceli, Scott A.; Tran-Son-Tay, Roger

2011-01-01

Emergent behaviors of multi-cellular biological systems (MCBS) result from the behaviors of each individual cells and their interactions with other cells and with the environment. Modeling MCBS requires incorporating these complex interactions among the individual cells and the environment. Modeling approaches for MCBS can be grouped into two categories: continuum models and cell-based models. Continuum models usually take the form of partial differential equations, and the model equations provide insight into the relationship among the components in the system. Cell-based models simulate each individual cell behavior and interactions among them enabling the observation of the emergent system behavior. This review focuses on the cell-based models of MCBS, and especially, the technical aspect of the rule-based simulation method for MCBS is reviewed. How to implement the cell behaviors and the interactions with other cells and with the environment into the computational domain is discussed. The cell behaviors reviewed in this paper are division, migration, apoptosis/necrosis, and differentiation. The environmental factors such as extracellular matrix, chemicals, microvasculature, and forces are also discussed. Application examples of these cell behaviors and interactions are presented. PMID:21369345

Inductive System Health Monitoring

NASA Technical Reports Server (NTRS)

Iverson, David L.

2004-01-01

The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS uses nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. IMS is able to monitor the system by comparing real time operational data with these classes. We present a description of learning and monitoring method used by IMS and summarize some recent IMS results.

Ground state atoms confined in a real Rydberg and complex Rydberg-Scarf II potential

NASA Astrophysics Data System (ADS)

Mansoori Kermani, Maryam

2017-12-01

In this work, a system of two ground state atoms confined in a one-dimensional real Rydberg potential was modeled. The atom-atom interaction was considered as a nonlocal separable potential (NLSP) of rank one. This potential was assumed because it leads to an analytical solution of the Lippmann-Schwinger equation. The NLSPs are useful in the few body problems that the many-body potential at each point is replaced by a projective two-body nonlocal potential operator. Analytical expressions for the confined particle resolvent were calculated as a key function in this study. The contributions of the bound and virtual states in the complex energy plane were obtained via the derived transition matrix. Since the low energy quantum scattering problems scattering length is an important quantity, the behavior of this parameter was described versus the reduced energy considering various values of potential parameters. In a one-dimensional model, the total cross section in units of the area is not a meaningful property; however, the reflectance coefficient has a similar role. Therefore the reflectance probability and its behavior were investigated. Then a new confined potential via combining the complex absorbing Scarf II potential with the real Rydberg potential, called the Rydberg-Scarf II potential, was introduced to construct a non-Hermitian Hamiltonian. In order to investigate the effect of the complex potential, the scattering length and reflectance coefficient were calculated. It was concluded that in addition to the competition between the repulsive and attractive parts of both potentials, the imaginary part of the complex potential has an important effect on the properties of the system. The complex potential also reduces the reflectance probability via increasing the absorption probability. For all numerical computations, the parameters of a system including argon gas confined in graphite were considered.

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

PubMed

Rajagopalan, Ramesh; Litvan, Irene; Jung, Tzyy-Ping

2017-11-01

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems.

Modeling the data management system of Space Station Freedom with DEPEND

NASA Technical Reports Server (NTRS)

Olson, Daniel P.; Iyer, Ravishankar K.; Boyd, Mark A.

1993-01-01

Some of the features and capabilities of the DEPEND simulation-based modeling tool are described. A study of a 1553B local bus subsystem of the Space Station Freedom Data Management System (SSF DMS) is used to illustrate some types of system behavior that can be important to reliability and performance evaluations of this type of spacecraft. A DEPEND model of the subsystem is used to illustrate how these types of system behavior can be modeled, and shows what kinds of engineering and design questions can be answered through the use of these modeling techniques. DEPEND's process-based simulation environment is shown to provide a flexible method for modeling complex interactions between hardware and software elements of a fault-tolerant computing system.

Generating Phenotypical Erroneous Human Behavior to Evaluate Human-automation Interaction Using Model Checking

PubMed Central

Bolton, Matthew L.; Bass, Ellen J.; Siminiceanu, Radu I.

2012-01-01

Breakdowns in complex systems often occur as a result of system elements interacting in unanticipated ways. In systems with human operators, human-automation interaction associated with both normative and erroneous human behavior can contribute to such failures. Model-driven design and analysis techniques provide engineers with formal methods tools and techniques capable of evaluating how human behavior can contribute to system failures. This paper presents a novel method for automatically generating task analytic models encompassing both normative and erroneous human behavior from normative task models. The generated erroneous behavior is capable of replicating Hollnagel’s zero-order phenotypes of erroneous action for omissions, jumps, repetitions, and intrusions. Multiple phenotypical acts can occur in sequence, thus allowing for the generation of higher order phenotypes. The task behavior model pattern capable of generating erroneous behavior can be integrated into a formal system model so that system safety properties can be formally verified with a model checker. This allows analysts to prove that a human-automation interactive system (as represented by the model) will or will not satisfy safety properties with both normative and generated erroneous human behavior. We present benchmarks related to the size of the statespace and verification time of models to show how the erroneous human behavior generation process scales. We demonstrate the method with a case study: the operation of a radiation therapy machine. A potential problem resulting from a generated erroneous human action is discovered. A design intervention is presented which prevents this problem from occurring. We discuss how our method could be used to evaluate larger applications and recommend future paths of development. PMID:23105914

A Complex Systems Approach to More Resilient Multi-Layered Security Systems

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

Brown, Nathanael J. K.; Jones, Katherine A.; Bandlow, Alisa

In July 2012, protestors cut through security fences and gained access to the Y-12 National Security Complex. This was believed to be a highly reliable, multi-layered security system. This report documents the results of a Laboratory Directed Research and Development (LDRD) project that created a consistent, robust mathematical framework using complex systems analysis algorithms and techniques to better understand the emergent behavior, vulnerabilities and resiliency of multi-layered security systems subject to budget constraints and competing security priorities. Because there are several dimensions to security system performance and a range of attacks that might occur, the framework is multi-objective for amore » performance frontier to be estimated. This research explicitly uses probability of intruder interruption given detection (P I) as the primary resilience metric. We demonstrate the utility of this framework with both notional as well as real-world examples of Physical Protection Systems (PPSs) and validate using a well-established force-on-force simulation tool, Umbra.« less

CHEMICAL PROCESSES AND MODELING IN ECOSYSTEMS

EPA Science Inventory

Trends in regulatory strategies require EPA to understand better chemical behavior in natural and impacted ecosystems and in biological systems to carry out the increasingly complex array of exposure and risk assessments needed to develop scientifically defensible regulations (GP...

Insensitivity of synchronization to network structure in chaotic pendulum systems with time-delay coupling.

PubMed

Yao, Chenggui; Zhan, Meng; Shuai, Jianwei; Ma, Jun; Kurths, Jürgen

2017-12-01

It has been generally believed that both time delay and network structure could play a crucial role in determining collective dynamical behaviors in complex systems. In this work, we study the influence of coupling strength, time delay, and network topology on synchronization behavior in delay-coupled networks of chaotic pendulums. Interestingly, we find that the threshold value of the coupling strength for complete synchronization in such networks strongly depends on the time delay in the coupling, but appears to be insensitive to the network structure. This lack of sensitivity was numerically tested in several typical regular networks, such as different locally and globally coupled ones as well as in several complex networks, such as small-world and scale-free networks. Furthermore, we find that the emergence of a synchronous periodic state induced by time delay is of key importance for the complete synchronization.

Modulating the single-molecule magnet behaviour in phenoxo-O bridged Dy2 systems via subtle structural variations

NASA Astrophysics Data System (ADS)

Wang, Wen-Min; Zhao, Xiao-Yu; Qiao, Hui; Bai, Li; Han, Hong-Fei; Fang, Ming; Wu, Zhi-Lei; Zou, Ji-Yong

2017-09-01

In search of simple approaches to rationally modulate the single-molecule magnet behaviour in polynuclear lanthanide compound, a new system containing two structurally closely related dinuclear dysprosium complexes, namely [Dy2(hfac)4L2] (1) and [Dy2(hfac)4L‧2] (2) (hfac = hexafluoroacetylacetonate, HL = 2-[4-methylaniline-imino]methyl]-8-hydroxyquinoline and HL' = 2-[(3,4-dimethylaniline)-imino]methyl]-8-hydroxyquinoline), are successfully synthesized and the structure-dependent magnetic properties are investigated. The two Dy2 compounds display only slight variations in the coordination geometries of the center Dy(III) ion but display remarkably different single-molecule magnet behaviors with the anisotropic barriers (ΔE/kB) of 9.91 K for 1 and 20.57 K for 2. The different magnetic relaxation behaviors of the two Dy2 complexes mainly originate from the different chemical environments of the central DyIII ions.

Selective attention determines emotional responses to novel visual stimuli.

PubMed

Raymond, Jane E; Fenske, Mark J; Tavassoli, Nader T

2003-11-01

Distinct complex brain systems support selective attention and emotion, but connections between them suggest that human behavior should reflect reciprocal interactions of these systems. Although there is ample evidence that emotional stimuli modulate attentional processes, it is not known whether attention influences emotional behavior. Here we show that evaluation of the emotional tone (cheery/dreary) of complex but meaningless visual patterns can be modulated by the prior attentional state (attending vs. ignoring) used to process each pattern in a visual selection task. Previously ignored patterns were evaluated more negatively than either previously attended or novel patterns. Furthermore, this emotional devaluation of distracting stimuli was robust across different emotional contexts and response scales. Finding that negative affective responses are specifically generated for ignored stimuli points to a new functional role for attention and elaborates the link between attention and emotion. This finding also casts doubt on the conventional marketing wisdom that any exposure is good exposure.

Development of Design Rules for Reliable Antisense RNA Behavior in E. coli.

PubMed

Hoynes-O'Connor, Allison; Moon, Tae Seok

2016-12-16

A key driver of synthetic biology is the development of designable genetic parts with predictable behaviors that can be quickly implemented in complex genetic systems. However, the intrinsic complexity of gene regulation can make the rational design of genetic parts challenging. This challenge is apparent in the design of antisense RNA (asRNA) regulators. Though asRNAs are well-known regulators, the literature governing their design is conflicting and leaves the synthetic biology community without clear asRNA design rules. The goal of this study is to perform a comprehensive experimental characterization and statistical analysis of 121 unique asRNA regulators in order to resolve the conflicts that currently exist in the literature. asRNAs usually consist of two regions, the Hfq binding site and the target binding region (TBR). First, the behaviors of several high-performing Hfq binding sites were compared, in terms of their ability to improve repression efficiencies and their orthogonality. Next, a large-scale analysis of TBR design parameters identified asRNA length, the thermodynamics of asRNA-mRNA complex formation, and the percent of target mismatch as key parameters for TBR design. These parameters were used to develop simple asRNA design rules. Finally, these design rules were applied to construct both a simple and a complex genetic circuit containing different asRNAs, and predictable behavior was observed in both circuits. The results presented in this study will drive synthetic biology forward by providing useful design guidelines for the construction of asRNA regulators with predictable behaviors.

Dissecting genetic architecture of startle response in Drosophila melanogaster using multi-omics information.

PubMed

Xue, Angli; Wang, Hongcheng; Zhu, Jun

2017-09-28

Startle behavior is important for survival, and abnormal startle responses are related to several neurological diseases. Drosophila melanogaster provides a powerful system to investigate the genetic underpinnings of variation in startle behavior. Since mechanically induced, startle responses and environmental conditions can be readily quantified and precisely controlled. The 156 wild-derived fully sequenced lines of the Drosophila Genetic Reference Panel (DGRP) were used to identify SNPs and transcripts associated with variation in startle behavior. The results validated highly significant effects of 33 quantitative trait SNPs (QTSs) and 81 quantitative trait transcripts (QTTs) directly associated with phenotypic variation of startle response. We also detected QTT variation controlled by 20 QTSs (tQTSs) and 73 transcripts (tQTTs). Association mapping based on genomic and transcriptomic data enabled us to construct a complex genetic network that underlies variation in startle behavior. Based on principles of evolutionary conservation, human orthologous genes could be superimposed on this network. This study provided both genetic and biological insights into the variation of startle response behavior of Drosophila melanogaster, and highlighted the importance of genetic network to understand the genetic architecture of complex traits.

Neuron hemilineages provide the functional ground plan for the Drosophila ventral nervous system

PubMed Central

Harris, Robin M; Pfeiffer, Barret D; Rubin, Gerald M; Truman, James W

2015-01-01

Drosophila central neurons arise from neuroblasts that generate neurons in a pair-wise fashion, with the two daughters providing the basis for distinct A and B hemilineage groups. 33 postembryonically-born hemilineages contribute over 90% of the neurons in each thoracic hemisegment. We devised genetic approaches to define the anatomy of most of these hemilineages and to assessed their functional roles using the heat-sensitive channel dTRPA1. The simplest hemilineages contained local interneurons and their activation caused tonic or phasic leg movements lacking interlimb coordination. The next level was hemilineages of similar projection cells that drove intersegmentally coordinated behaviors such as walking. The highest level involved hemilineages whose activation elicited complex behaviors such as takeoff. These activation phenotypes indicate that the hemilineages vary in their behavioral roles with some contributing to local networks for sensorimotor processing and others having higher order functions of coordinating these local networks into complex behavior. DOI: http://dx.doi.org/10.7554/eLife.04493.001 PMID:26193122

Development of the Neurochemical Architecture of the Central Complex

PubMed Central

Boyan, George S.; Liu, Yu

2016-01-01

The central complex represents one of the most conspicuous neuroarchitectures to be found in the insect brain and regulates a wide repertoire of behaviors including locomotion, stridulation, spatial orientation and spatial memory. In this review article, we show that in the grasshopper, a model insect system, the intricate wiring of the fan-shaped body (FB) begins early in embryogenesis when axons from the first progeny of four protocerebral stem cells (called W, X, Y, Z, respectively) in each brain hemisphere establish a set of tracts to the primary commissural system. Decussation of subsets of commissural neurons at stereotypic locations across the brain midline then establishes a columnar neuroarchitecture in the FB which is completed during embryogenesis. Examination of the expression patterns of various neurochemicals in the central complex including neuropeptides, a neurotransmitter and the gas nitric oxide (NO), show that these appear progressively and in a substance-specific manner during embryogenesis. Each neuroactive substance is expressed by neurons located at stereotypic locations in a given central complex lineage, confirming that the stem cells are biochemically multipotent. The organization of axons expressing the various neurochemicals within the central complex is topologically related to the location, and hence birthdate, of the neurons within the lineages. The neurochemical expression patterns within the FB are layered, and so reflect the temporal topology present in the lineages. This principle relates the neuroanatomical to the neurochemical architecture of the central complex and so may provide insights into the development of adaptive behaviors. PMID:27630548

Hemispheric asymmetry in stress processing in rat prefrontal cortex and the role of mesocortical dopamine.

PubMed

Sullivan, R M

2004-06-01

The prefrontal cortex (PFC) is known to play an important role not only in the regulation of emotion, but in the integration of affective states with appropriate modulation of autonomic and neuroendocrine stress regulatory systems. The present review highlights findings in the rat which helps to elucidate the complex nature of prefrontal involvement in emotion and stress regulation. The medial PFC is particularly important in this regard and while dorsomedial regions appear to play a suppressive role in such regulation, the ventromedial (particularly infralimbic) region appears to activate behavioral, neuroendocrine and sympathetic autonomic systems in response to stressful situations. This may be especially true of spontaneous stress-related behavior or physiological responses to relatively acute stressors. The role of the medial PFC is somewhat more complex in conditions involving learned adjustments to stressful situations, such as the extinction of conditioned fear responses, but it is clear that the medial PFC is important in incorporating stressful experience for future adaptive behavior. It is also suggested that mesocortical dopamine plays an important adaptive role in this region by preventing excessive behavioral and physiological stress reactivity. The rat brain shows substantial hemispheric specialization in many respects, and while the right PFC is normally dominant in the activation of stress-related systems, the left may play a role in countering this activation through processes of interhemispheric inhibition. This proposed basic template for the lateralization of stress regulatory systems is suggested to be associated with efficient stress and emotional self-regulation, and also to be shaped by both early postnatal experience and gender differences.

Human performance cognitive-behavioral modeling: a benefit for occupational safety.

PubMed

Gore, Brian F

2002-01-01

Human Performance Modeling (HPM) is a computer-aided job analysis software methodology used to generate predictions of complex human-automation integration and system flow patterns with the goal of improving operator and system safety. The use of HPM tools has recently been increasing due to reductions in computational cost, augmentations in the tools' fidelity, and usefulness in the generated output. An examination of an Air Man-machine Integration Design and Analysis System (Air MIDAS) model evaluating complex human-automation integration currently underway at NASA Ames Research Center will highlight the importance to occupational safety of considering both cognitive and physical aspects of performance when researching human error.

Human performance cognitive-behavioral modeling: a benefit for occupational safety

NASA Technical Reports Server (NTRS)

Gore, Brian F.

2002-01-01

Human Performance Modeling (HPM) is a computer-aided job analysis software methodology used to generate predictions of complex human-automation integration and system flow patterns with the goal of improving operator and system safety. The use of HPM tools has recently been increasing due to reductions in computational cost, augmentations in the tools' fidelity, and usefulness in the generated output. An examination of an Air Man-machine Integration Design and Analysis System (Air MIDAS) model evaluating complex human-automation integration currently underway at NASA Ames Research Center will highlight the importance to occupational safety of considering both cognitive and physical aspects of performance when researching human error.

A scale-free systems theory of motivation and addiction.

PubMed

Chambers, R Andrew; Bickel, Warren K; Potenza, Marc N

2007-01-01

Scale-free organizations, characterized by uneven distributions of linkages between nodal elements, describe the structure and function of many life-based complex systems developing under evolutionary pressures. We explore motivated behavior as a scale-free map toward a comprehensive translational theory of addiction. Motivational and behavioral repertoires are reframed as link and nodal element sets, respectively, comprising a scale-free structure. These sets are generated by semi-independent information-processing streams within cortical-striatal circuits that cooperatively provide decision-making and sequential processing functions necessary for traversing maps of motivational links connecting behavioral nodes. Dopamine modulation of cortical-striatal plasticity serves a central-hierarchical mechanism for survival-adaptive sculpting and development of motivational-behavioral repertoires by guiding a scale-free design. Drug-induced dopamine activity promotes drug taking as a highly connected behavioral hub at the expense of natural-adaptive motivational links and behavioral nodes. Conceptualizing addiction as pathological alteration of scale-free motivational-behavioral repertoires unifies neurobiological, neurocomputational and behavioral research while addressing addiction vulnerability in adolescence and psychiatric illness. This model may inform integrative research in defining more effective prevention and treatment strategies for addiction.

A Scale-Free Systems Theory of Motivation and Addiction

PubMed Central

Bickel, Warren K.; Potenza, Marc N.

2007-01-01

Scale-free organizations, characterized by uneven distributions of linkages between nodal elements, describe the structure and function of many life-based complex systems developing under evolutionary pressures. We explore motivated behavior as a scale-free map toward a comprehensive translational theory of addiction. Motivational and behavioral repertoires are reframed as link and nodal element sets, respectively, comprising a scale-free structure. These sets are generated by semi-independent information-processing streams within cortical-striatal circuits that cooperatively provide decision-making and sequential processing functions necessary for traversing maps of motivational links connecting behavioral nodes. Dopamine modulation of cortical-striatal plasticity serves a central-hierarchical mechanism for survival-adaptive sculpting and development of motivational-behavioral repertoires by guiding a scale-free design. Drug-induced dopamine activity promotes drug-taking as a highly connected behavioral hub at the expense of natural-adaptive motivational links and behavioral nodes. Conceptualizing addiction as pathological alteration of scale-free motivational-behavioral repertoires unifies neurobiological, neurocomputational and behavioral research while addressing addiction vulnerability in adolescence and psychiatric illness. This model may inform integrative research in defining more effective prevention and treatment strategies for addiction. PMID:17574673

Complexity for Survival of Living Systems

NASA Technical Reports Server (NTRS)

Zak, Michail

2009-01-01

A logical connection between the survivability of living systems and the complexity of their behavior (equivalently, mental complexity) has been established. This connection is an important intermediate result of continuing research on mathematical models that could constitute a unified representation of the evolution of both living and non-living systems. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the two most relevant being Characteristics of Dynamics of Intelligent Systems (NPO- 21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; and Self-Supervised Dynamical Systems (NPO- 30634) NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72. As used here, living systems is synonymous with active systems and intelligent systems. The quoted terms can signify artificial agents (e.g., suitably programmed computers) or natural biological systems ranging from single-cell organisms at one extreme to the whole of human society at the other extreme. One of the requirements that must be satisfied in mathematical modeling of living systems is reconciliation of evolution of life with the second law of thermodynamics. In the approach followed in this research, this reconciliation is effected by means of a model, inspired partly by quantum mechanics, in which the quantum potential is replaced with an information potential. The model captures the most fundamental property of life - the ability to evolve from disorder to order without any external interference. The model incorporates the equations of classical dynamics, including Newton s equations of motion and equations for random components caused by uncertainties in initial conditions and by Langevin forces. The equations of classical dynamics are coupled with corresponding Liouville or Fokker-Planck equations that describe the evolutions of probability densities that represent the uncertainties. The coupling is effected by fictitious information-based forces that are gradients of the information potential, which, in turn, is a function of the probability densities. The probability densities are associated with mental images both self-image and nonself images (images of external objects that can include other agents). The evolution of the probability densities represents mental dynamics. Then the interaction between the physical and metal aspects of behavior is implemented by feedback from mental to motor dynamics, as represented by the aforementioned fictitious forces. The interaction of a system with its self and nonself images affords unlimited capacity for increase of complexity. There is a biological basis for this model of mental dynamics in the discovery of mirror neurons that learn by imitation. The levels of complexity attained by use of this model match those observed in living systems. To establish a mechanism for increasing the complexity of dynamics of an active system, the model enables exploitation of a chain of reflections exemplified by questions of the form, "What do you think that I think that you think...?" Mathematically, each level of reflection is represented in the form of an attractor performing the corresponding level of abstraction with more details removed from higher levels. The model can be used to describe the behaviors, not only of biological systems, but also of ecological, social, and economics ones.

Understanding Systems Theory for U.S. Marines

DTIC Science & Technology

2007-01-01

Combat Development Command Quantico, Virginia 22134-5068 FUTURE WAR Understanding Systems Theory for U.S. Marines SUBMITTED IN...Systems Theory for U.S. Marines 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR( S ) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f...attached as Appendix C). Developing solutions requires understanding the problem( s ). In complex situations, some behavior of the target system

Complex and unexpected dynamics in simple genetic regulatory networks

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Achieving realistic performance and decison-making capabilities in computer-generated air forces

NASA Astrophysics Data System (ADS)

Banks, Sheila B.; Stytz, Martin R.; Santos, Eugene, Jr.; Zurita, Vincent B.; Benslay, James L., Jr.

1997-07-01

For a computer-generated force (CGF) system to be useful in training environments, it must be able to operate at multiple skill levels, exhibit competency at assigned missions, and comply with current doctrine. Because of the rapid rate of change in distributed interactive simulation (DIS) and the expanding set of performance objectives for any computer- generated force, the system must also be modifiable at reasonable cost and incorporate mechanisms for learning. Therefore, CGF applications must have adaptable decision mechanisms and behaviors and perform automated incorporation of past reasoning and experience into its decision process. The CGF must also possess multiple skill levels for classes of entities, gracefully degrade its reasoning capability in response to system stress, possess an expandable modular knowledge structure, and perform adaptive mission planning. Furthermore, correctly performing individual entity behaviors is not sufficient. Issues related to complex inter-entity behavioral interactions, such as the need to maintain formation and share information, must also be considered. The CGF must also be able to acceptably respond to unforeseen circumstances and be able to make decisions in spite of uncertain information. Because of the need for increased complexity in the virtual battlespace, the CGF should exhibit complex, realistic behavior patterns within the battlespace. To achieve these necessary capabilities, an extensible software architecture, an expandable knowledge base, and an adaptable decision making mechanism are required. Our lab has addressed these issues in detail. The resulting DIS-compliant system is called the automated wingman (AW). The AW is based on fuzzy logic, the common object database (CODB) software architecture, and a hierarchical knowledge structure. We describe the techniques we used to enable us to make progress toward a CGF entity that satisfies the requirements presented above. We present our design and implementation of an adaptable decision making mechanism that uses multi-layered, fuzzy logic controlled situational analysis. Because our research indicates that fuzzy logic can perform poorly under certain circumstances, we combine fuzzy logic inferencing with adversarial game tree techniques for decision making in strategic and tactical engagements. We describe the approach we employed to achieve this fusion. We also describe the automated wingman's system architecture and knowledge base architecture.

Complex Dynamical Behavior in Hybrid Systems

DTIC Science & Technology

2012-09-29

stability for a class of hybrid dynamical systems via averaging”, Mathematics of Control , Signals, and Systems , vol. 23, no. 4, pp...no. 7, pp. 1636-1649, 2011. J9. A.R. Teel and L. Marconi, `` Stabilization for a class of minimum phase hybrid systems under an average dwell- time ...functions for L2 and input-to-state stability in a class of quantized control systems ”, 50th IEEE Conference on Decision and Control , Dec.

Zebrafish model systems for developmental neurobehavioral toxicology.

PubMed

Bailey, Jordan; Oliveri, Anthony; Levin, Edward D

2013-03-01

Zebrafish offer many advantages that complement classic mammalian models for the study of normal development as well as for the teratogenic effects of exposure to hazardous compounds. The clear chorion and embryo of the zebrafish allow for continuous visualization of the anatomical changes associated with development, which, along with short maturation times and the capability of complex behavior, makes this model particularly useful for measuring changes to the developing nervous system. Moreover, the rich array of developmental, behavioral, and molecular benefits offered by the zebrafish have contributed to an increasing demand for the use of zebrafish in behavioral teratology. Essential for this endeavor has been the development of a battery of tests to evaluate a spectrum of behavior in zebrafish. Measures of sensorimotor plasticity, emotional function, cognition and social interaction have been used to characterize the persisting adverse effects of developmental exposure to a variety of chemicals including therapeutic drugs, drugs of abuse and environmental toxicants. In this review, we present and discuss such tests and data from a range of developmental neurobehavioral toxicology studies using zebrafish as a model. Zebrafish provide a key intermediate model between high throughput in vitro screens and the classic mammalian models as they have the accessibility of in vitro models and the complex functional capabilities of mammalian models. Copyright © 2013 Wiley Periodicals, Inc.

Zebrafish Model Systems for Developmental Neurobehavioral Toxicology

PubMed Central

Bailey, Jordan; Oliveri, Anthony; Levin, Edward D.

2014-01-01

Zebrafish offer many advantages that complement classic mammalian models for the study of normal development as well as for the teratogenic effects of exposure to hazardous compounds. The clear chorion and embryo of the zebrafish allow for continuous visualization of the anatomical changes associated with development, which, along with short maturation times and the capability of complex behavior, makes this model particularly useful for measuring changes to the developing nervous system. Moreover, the rich array of developmental, behavioral, and molecular benefits offered by the zebrafish have contributed to an increasing demand for the use of zebrafish in behavioral teratology. Essential for this endeavor has been the development of a battery of tests to evaluate a spectrum of behavior in zebrafish. Measures of sensorimotor plasticity, emotional function, cognition and social interaction have been used to characterize the persisting adverse effects of developmental exposure to a variety of chemicals including therapeutic drugs, drugs of abuse and environmental toxicants. In this review, we present and discuss such tests and data from a range of developmental neurobehavioral toxicology studies using zebrafish as a model. Zebrafish provide a key intermediate model between high throughput in vitro screens and the classic mammalian models as they have the accessibility of in vitro models and the complex functional capabilities of mammalian models. PMID:23723169

Generalized sample entropy analysis for traffic signals based on similarity measure

NASA Astrophysics Data System (ADS)

Shang, Du; Xu, Mengjia; Shang, Pengjian

2017-05-01

Sample entropy is a prevailing method used to quantify the complexity of a time series. In this paper a modified method of generalized sample entropy and surrogate data analysis is proposed as a new measure to assess the complexity of a complex dynamical system such as traffic signals. The method based on similarity distance presents a different way of signals patterns match showing distinct behaviors of complexity. Simulations are conducted over synthetic data and traffic signals for providing the comparative study, which is provided to show the power of the new method. Compared with previous sample entropy and surrogate data analysis, the new method has two main advantages. The first one is that it overcomes the limitation about the relationship between the dimension parameter and the length of series. The second one is that the modified sample entropy functions can be used to quantitatively distinguish time series from different complex systems by the similar measure.

ADAPT: The Agent Development and Prototyping Testbed.

PubMed

Shoulson, Alexander; Marshak, Nathan; Kapadia, Mubbasir; Badler, Norman I

2014-07-01

We present ADAPT, a flexible platform for designing and authoring functional, purposeful human characters in a rich virtual environment. Our framework incorporates character animation, navigation, and behavior with modular interchangeable components to produce narrative scenes. The animation system provides locomotion, reaching, gaze tracking, gesturing, sitting, and reactions to external physical forces, and can easily be extended with more functionality due to a decoupled, modular structure. The navigation component allows characters to maneuver through a complex environment with predictive steering for dynamic obstacle avoidance. Finally, our behavior framework allows a user to fully leverage a character's animation and navigation capabilities when authoring both individual decision-making and complex interactions between actors using a centralized, event-driven model.

Advances in molecular labeling, high throughput imaging and machine intelligence portend powerful functional cellular biochemistry tools.

PubMed

Price, Jeffrey H; Goodacre, Angela; Hahn, Klaus; Hodgson, Louis; Hunter, Edward A; Krajewski, Stanislaw; Murphy, Robert F; Rabinovich, Andrew; Reed, John C; Heynen, Susanne

2002-01-01

Cellular behavior is complex. Successfully understanding systems at ever-increasing complexity is fundamental to advances in modern science and unraveling the functional details of cellular behavior is no exception. We present a collection of prospectives to provide a glimpse of the techniques that will aid in collecting, managing and utilizing information on complex cellular processes via molecular imaging tools. These include: 1) visualizing intracellular protein activity with fluorescent markers, 2) high throughput (and automated) imaging of multilabeled cells in statistically significant numbers, and 3) machine intelligence to analyze subcellular image localization and pattern. Although not addressed here, the importance of combining cell-image-based information with detailed molecular structure and ligand-receptor binding models cannot be overlooked. Advanced molecular imaging techniques have the potential to impact cellular diagnostics for cancer screening, clinical correlations of tissue molecular patterns for cancer biology, and cellular molecular interactions for accelerating drug discovery. The goal of finally understanding all cellular components and behaviors will be achieved by advances in both instrumentation engineering (software and hardware) and molecular biochemistry. Copyright 2002 Wiley-Liss, Inc.

Phase Transitions in Model Active Systems

NASA Astrophysics Data System (ADS)

Redner, Gabriel S.

The amazing collective behaviors of active systems such as bird flocks, schools of fish, and colonies of microorganisms have long amazed scientists and laypeople alike. Understanding the physics of such systems is challenging due to their far-from-equilibrium dynamics, as well as the extreme diversity in their ingredients, relevant time- and length-scales, and emergent phenomenology. To make progress, one can categorize active systems by the symmetries of their constituent particles, as well as how activity is expressed. In this work, we examine two categories of active systems, and explore their phase behavior in detail. First, we study systems of self-propelled spherical particles moving in two dimensions. Despite the absence of an aligning interaction, this system displays complex emergent dynamics, including phase separation into a dense active solid and dilute gas. Using simulations and analytic modeling, we quantify the phase diagram and separation kinetics. We show that this nonequilibrium phase transition is analogous to an equilibrium vapor-liquid system, with binodal and spinodal curves and a critical point. We also characterize the dense active solid phase, a unique material which exhibits the structural signatures of a crystalline solid near the crystal-hexatic transition point, as well as anomalous dynamics including superdiffusive motion on intermediate timescales. We also explore the role of interparticle attraction in this system. We demonstrate that attraction drastically changes the phase diagram, which contains two distinct phase-separated regions and is reentrant as a function of propulsion speed. We interpret this complex situation with a simple kinetic model, which builds from the observed microdynamics of individual particles to a full description of the macroscopic phase behavior. We also study active nematics, liquid crystals driven out of equilibrium by energy-dissipating active stresses. The equilibrium nematic state is unstable in these materials, leading to beautiful and surprising behaviors including the spontaneous generation of topological defect pairs which stream through the system and later annihilate, yielding a complex, seemingly chaotic dynamical steady-state. Here, we describe the emergence of order from this chaos in the form of previously unknown broken-symmetry phases in which the topological defects themselves undergo orientational ordering. We have identified these defect-ordered phases in two realizations of an active nematic: first, a suspension of extensile bundles of microtubules and molecular motor proteins, and second, a computational model of extending hard rods. We will describe the defect-stabilized phases that manifest in these systems, our current understanding of their origins, and discuss whether such phases may be a general feature of extensile active nematics.

Studies on Cu(II) ternary complexes involving an aminopenicillin drug and imidazole containing ligands

NASA Astrophysics Data System (ADS)

Regupathy, Sthanumoorthy; Nair, Madhavan Sivasankaran

2010-02-01

Equilibrium studies on the ternary complex systems involving ampicillin (amp) as ligand (A) and imidazole containing ligands viz., imidazole (Him), benzimidazole (Hbim), histamine (Hist) and histidine (His) as ligands (B) at 37 °C and I = 0.15 mol dm -3 (NaClO 4) show the presence of CuABH, CuAB and CuAB 2. The proton in the CuABH species is attached to ligand A. In the ternary complexes the ligand, amp(A) binds the metal ion via amino nitrogen and carbonyl oxygen atom. The CuAB (B = Hist/His)/CuAB 2 (B = Him/Hbim) species have also been isolated and the analytical data confirmed its formation. Non-electrolytic behavior and monomeric type of chelates have been assessed from their low conductance and magnetic susceptibility values. The electronic and vibrational spectral results were interpreted to find the mode of binding of ligands to metal and geometry of the complexes. This is also supported by the g tensor values calculated from ESR spectra. The thermal behaviour of complexes were studied by TGA/DTA. The redox behavior of the complexes has been studied by cyclic voltammetry. The antimicrobial activity and CT DNA cleavage study of the complexes show higher activity for ternary complexes.

Managing change: an overview.

PubMed

Lorenzi, N M; Riley, R T

2000-01-01

As increasingly powerful informatics systems are designed, developed, and implemented, they inevitably affect larger, more heterogeneous groups of people and more organizational areas. In turn, the major challenges to system success are often more behavioral than technical. Successfully introducing such systems into complex health care organizations requires an effective blend of good technical and good organizational skills. People who have low psychological ownership in a system and who vigorously resist its implementation can bring a "technically best" system to its knees. However, effective leadership can sharply reduce the behavioral resistance to change-including to new technologies-to achieve a more rapid and productive introduction of informatics technology. This paper looks at four major areas-why information system failures occur, the core theories supporting change management, the practical applications of change management, and the change management efforts in informatics.

Self-Organization, Resilience and Robustness of Complex Systems Through an Application to Financial Market from an Agent-Based Approach

NASA Astrophysics Data System (ADS)

Lucas, Iris; Cotsaftis, Michel; Bertelle, Cyrille

This paper introduces the implementation of a computational agent-based financial market model in which the system is described on both microscopic and macroscopic levels. This artificial financial market model is used to study the system response when a shock occurs. Indeed, when a market experiences perturbations, financial systems behavior can exhibit two different properties: resilience and robustness. Through simulations and different scenarios of market shocks, these system properties are studied. The results notably show that the emergence of collective herding behavior when market shock occurs leads to a temporary disruption of the system self-organization. Numerical simulations highlight that the market can absorb strong mono-shocks but can also be led to rupture by low but repeated perturbations.

Monitoring and decision making by people in man machine systems

NASA Technical Reports Server (NTRS)

Johannsen, G.

1979-01-01

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

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

PubMed

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

2018-01-01

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

Recent advances in mathematical criminology. Comment on "Statistical physics of crime: A review" by M.R. D'Orsogna and M. Perc

NASA Astrophysics Data System (ADS)

Rodríguez, Nancy

2015-03-01

The use of mathematical tools has long proved to be useful in gaining understanding of complex systems in physics [1]. Recently, many researchers have realized that there is an analogy between emerging phenomena in complex social systems and complex physical or biological systems [4,5,12]. This realization has particularly benefited the modeling and understanding of crime, a ubiquitous phenomena that is far from being understood. In fact, when one is interested in the bulk behavior of patterns that emerge from small and seemingly unrelated interactions as well as decisions that occur at the individual level, the mathematical tools that have been developed in statistical physics, game theory, network theory, dynamical systems, and partial differential equations can be useful in shedding light into the dynamics of these patterns [2-4,6,12].

Brief history of intermolecular and intersurface forces in complex fluid systems.

PubMed

Israelachvili, Jacob; Ruths, Marina

2013-08-06

We review the developments of ideas, concepts, and theories of intermolecular and intersurface forces and how these were influenced (or ignored) by observations of nature and, later, systematic experimentation. The emphasis of this review is on the way things gradually changed: experimentation replaced rhetoric, measurement and quantification replaced hand waving, energy replaced force in calculations, discrete atoms replaced the (continuum) aether, thermodynamics replaced mechanistic models, randomness and probability replaced certainty, and delicate experiments on the subnanoscale revealed fascinating self-assembling structures and complex behavior of even the simplest systems. We conclude by discussing today's unresolved challenges: how complex "dynamic" multicomponent--especially living biological--systems that receive a continuous supply of energy can be far from equilibrium and not even in any steady state. Such systems, never static but evolving in both space and time, are still far from being understood both experimentally and theoretically.

Transition Manifolds of Complex Metastable Systems

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

A numerical study of coarsening in the two-dimensional complex Ginzburg-Landau equation

NASA Astrophysics Data System (ADS)

Liu, Weigang; Tauber, Uwe

The complex Ginzburg-Landau equation with additive noise is a stochastic partial differential equation that describes a remarkably wide range of physical systems: coupled non-linear oscillators subject to external noise near a Hopf bifurcation instability; spontaneous structure formation in non-equilibrium systems, e.g., in cyclically competing populations; and driven-dissipative Bose-Einstein condensation, realized in open systems on the interface of quantum optics and many-body physics. We employ a finite-difference method to numerically solve the noisy complex Ginzburg-Landau equation on a two-dimensional domain with the goal to investigate the coarsening dynamics following a quench from a strongly fluctuating defect turbulence phase to a long-range ordered phase. We start from a simplified amplitude equation, solve it numerically, and then study the spatio-temporal behavior characterized by the spontaneous creation and annihilation of topological defects (spiral waves). We check our simulation results against the known dynamical phase diagram in this non-equilibrium system, tentatively analyze the coarsening kinetics following sudden quenches, and characterize the ensuing aging scaling behavior. In addition, we aim to use Voronoi triangulation to study the cellular structure in the phase turbulence and frozen states. This research is supported by the U. S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Science and Engineering under Award DE-FG02-09ER46613.

Alcoholism: a systems approach from molecular physiology to addictive behavior.

PubMed

Spanagel, Rainer

2009-04-01

Alcohol consumption is an integral part of daily life in many societies. The benefits associated with the production, sale, and use of alcoholic beverages come at an enormous cost to these societies. The World Health Organization ranks alcohol as one of the primary causes of the global burden of disease in industrialized countries. Alcohol-related diseases, especially alcoholism, are the result of cumulative responses to alcohol exposure, the genetic make-up of an individual, and the environmental perturbations over time. This complex gene x environment interaction, which has to be seen in a life-span perspective, leads to a large heterogeneity among alcohol-dependent patients, in terms of both the symptom dimensions and the severity of this disorder. Therefore, a reductionistic approach is not very practical if a better understanding of the pathological processes leading to an addictive behavior is to be achieved. Instead, a systems-oriented perspective in which the interactions and dynamics of all endogenous and environmental factors involved are centrally integrated, will lead to further progress in alcohol research. This review adheres to a systems biology perspective such that the interaction of alcohol with primary and secondary targets within the brain is described in relation to the behavioral consequences. As a result of the interaction of alcohol with these targets, alterations in gene expression and synaptic plasticity take place that lead to long-lasting alteration in neuronal network activity. As a subsequent consequence, alcohol-seeking responses ensue that can finally lead via complex environmental interactions to an addictive behavior.

Behavioral Priming 2.0: Enter a Dynamical Systems Perspective

PubMed Central

Krpan, Dario

2017-01-01

On a daily basis, people are exposed to numerous stimuli, ranging from colors and smells to sounds and words, that could potentially activate different cognitive constructs and influence their actions. This type of influence on human behavior is referred to as priming. Roughly two decades ago, behavioral priming was hailed as one of the core forces that shape automatic behavior. However, failures to replicate some of the representative findings in this domain soon followed, which posed the following question: “How robust are behavioral priming effects, and to what extent are they actually important in shaping people's actions?” To shed a new light on this question, I revisit behavioral priming through the prism of a dynamical systems perspective (DSP). The DSP is a scientific paradigm that has been developed through a combined effort of many different academic disciplines, ranging from mathematics and physics to biology, economics, psychology, etc., and it deals with behavior of simple and complex systems over time. In the present paper, I use conceptual and methodological tools stemming from the DSP to propose circumstances under which behavioral priming effects are likely to occur. More precisely, I outline three possible types of the influence of priming on human behavior, to which I refer as emergence, readjustment, and attractor switch, and propose experimental designs to examine them. Finally, I discuss relevant implications for behavioral priming effects and their replications. PMID:28769846

Chaos as a psychological construct: historical roots, principal findings, and current growth directions.

PubMed

Guastello, Stephen J

2009-07-01

The landmarks in the use of chaos and related constructs in psychology were entwined with the growing use of other nonlinear dynamical constructs, especially catastrophes and self-organization. The growth in substantive applications of chaos in psychology is partially related to the development of methodologies that work within the constraints of psychological data. The psychological literature includes rigorous theory with testable propositions, lighter-weight metaphorical uses of the construct, and colloquial uses of "chaos" with no particular theoretical intent. The current state of the chaos construct and supporting empirical research in psychological theory is summarized in neuroscience, psychophysics, psychomotor skill and other learning phenomena, clinical and abnormal psychology, and group dynamics and organizational behavior. Trends indicate that human systems do not remain chaotic indefinitely; they eventually self-organize, and the concept of the complex adaptive system has become prominent. Chaotic turbulence is generally higher in healthy systems compared to unhealthy systems, although opposite appears true in mood disorders. Group dynamics research shows trends consistent with the complex adaptive system, whereas organizational behavior lags behind in empirical studies relative to the quantity of its theory. Future directions for research involving the chaos construct and other nonlinear dynamics are outlined.

Psychological safety: The key to high performance in high stress, potentially traumatic environments

Treesearch

James Saveland

2011-01-01

Safety is typically talked about in a context of the absence of injury. The field of resilience engineering has been advocating that we think about safety differently, by taking a systems view and begin to see how people create safety in unsafe systems by managing risk. There is growing recognition that safety is an emergent behavior of our complex system of human...

Behavior Models for Software Architecture

DTIC Science & Technology

2014-11-01

MP. Existing process modeling frameworks (BPEL, BPMN [Grosskopf et al. 2009], IDEF) usually follow the “single flowchart” paradigm. MP separates...Process: Business Process Modeling using BPMN , Meghan Kiffer Press. HAREL, D., 1987, A Visual Formalism for Complex Systems. Science of Computer

Genetic basis of male sexual behavior.

PubMed

Emmons, Scott W; Lipton, Jonathan

2003-01-01

Male sexual behavior is increasingly the focus of genetic study in a variety of animals. Genetic analysis in the soil roundworm Caenorhabditis elegans and the fruit fly Drosophila melanogaster has lead to identification of genes and circuits that govern behaviors ranging from motivation and mate-searching to courtship and copulation. Some worm and fly genes have counterparts with related functions in higher animals and many more such correspondences can be expected. Analysis of mutations in mammals can potentially lead to insights into such issues as monogamous versus promiscuous sexual behavior and sexual orientation. Genetic analysis of sexual behavior has implications for understanding how the nervous system generates and controls a complex behavior. It can also help us to gain an appreciation of how behavior is encoded by genes and their regulatory sequences. Copyright 2003 Wiley Periodicals, Inc.

Behavioral barcoding in the cloud: embracing data-intensive digital phenotyping in neuropharmacology.

PubMed

Kokel, David; Rennekamp, Andrew J; Shah, Asmi H; Liebel, Urban; Peterson, Randall T

2012-08-01

For decades, studying the behavioral effects of individual drugs and genetic mutations has been at the heart of efforts to understand and treat nervous system disorders. High-throughput technologies adapted from other disciplines (e.g., high-throughput chemical screening, genomics) are changing the scale of data acquisition in behavioral neuroscience. Massive behavioral datasets are beginning to emerge, particularly from zebrafish labs, where behavioral assays can be performed rapidly and reproducibly in 96-well, high-throughput format. Mining these datasets and making comparisons across different assays are major challenges for the field. Here, we review behavioral barcoding, a process by which complex behavioral assays are reduced to a string of numeric features, facilitating analysis and comparison within and across datasets. Copyright © 2012 Elsevier Ltd. All rights reserved.

Scale-invariant cascades in turbulence and evolution

NASA Astrophysics Data System (ADS)

Guttenberg, Nicholas Ryan

In this dissertation, I present work addressing three systems which are traditionally considered to be unrelated: turbulence, evolution, and social organization. The commonality between these systems is that in each case, microscopic interaction rules give rise to an emergent behavior that in some way makes contact with the macroscopic scale of the problem. The open-ended evolution of complexity in evolving systems is analogous to the scale-free structure established in turbulent flows through local transportation of energy. In both cases, an invariance is required for the cascading behavior to occur, and in both cases the scale-free structure is built up from some initial scale from which the behavior is fed. In turbulence, I examine the case of two-dimensional turbulence in order to support the hypothesis that the friction factor and velocity profile of turbulent pipe flows depend on the turbulent energy spectrum in a way unpredicted by the classic Prandtl theory. By simulating two-dimensional flows in controlled geometries, either an inverse energy cascade or forward enstrophy cascade can be produced. The friction factor scaling of the flow changes depending on which cascade is present, in a way consistent with momentum transfer theory and roughness-induced criticality. In the problem of evolution, I show that open-ended growth of complexity can be obtained by ensuring that the evolutionary dynamics are invariant with respect to changes in complexity. Finite system size, finite point mutation rate, and fixed points in the fitness landscape can all interrupt this cascade behavior, producing an analogue to the integral scale of turbulence. This complexity cascade can exist both for competing and for symbiotic sets of organisms. Extending this picture to the qualitatively-different levels of organization of real lifeforms (viruses, unicellular, biofilms, multicellular) requires an understanding of how the processes of evolution themselves evolve. I show that a separation of spatial or temporal scales can enhance selection pressure on parameters that only matter several generations down the line. Because of this, I conclude that the prime candidates for the emergence of novel evolutionary mechanisms are biofilms and things living in oscillating environments. Finally, in the problem of social organization, I show that different types of control hierarchies - leaders or communal decision making - can emerge depending on the relationship between the environment in which members of the social group act and the development and exchange of information.

Automated Discovery and Modeling of Sequential Patterns Preceding Events of Interest

NASA Technical Reports Server (NTRS)

Rohloff, Kurt

2010-01-01

The integration of emerging data manipulation technologies has enabled a paradigm shift in practitioners' abilities to understand and anticipate events of interest in complex systems. Example events of interest include outbreaks of socio-political violence in nation-states. Rather than relying on human-centric modeling efforts that are limited by the availability of SMEs, automated data processing technologies has enabled the development of innovative automated complex system modeling and predictive analysis technologies. We introduce one such emerging modeling technology - the sequential pattern methodology. We have applied the sequential pattern methodology to automatically identify patterns of observed behavior that precede outbreaks of socio-political violence such as riots, rebellions and coups in nation-states. The sequential pattern methodology is a groundbreaking approach to automated complex system model discovery because it generates easily interpretable patterns based on direct observations of sampled factor data for a deeper understanding of societal behaviors that is tolerant of observation noise and missing data. The discovered patterns are simple to interpret and mimic human's identifications of observed trends in temporal data. Discovered patterns also provide an automated forecasting ability: we discuss an example of using discovered patterns coupled with a rich data environment to forecast various types of socio-political violence in nation-states.

Discrepancies in Autonomy and Relatedness Promoting Behaviors of Substance Using Mothers and Their Children: The Effects of a Family Systems Intervention.

PubMed

Zhang, Jing; Slesnick, Natasha

2017-03-01

Parents' and children's autonomy and relatedness behaviors are associated with a wide range of child outcomes. Yet, little is known about how parents and children's autonomy and relatedness behaviors jointly influence child outcomes. The current study captured this joint influence by exploring the longitudinal trajectory of mother-child discrepancies in autonomy and relatedness behaviors and its association with child problem behaviors. The effects of a family systems intervention on the trajectory of mother-child discrepancies were also examined. The sample included 183 substance using mothers and their children (M age = 11.54 years, SD = 2.55, range 8-16; 48 % females). Both the mother and child completed an assessment at baseline, 6- and 18-month post-baseline. A person-centered analysis identified subgroups varying in mother-child discrepancy patterns in their autonomy and relatedness behaviors. The results also showed that participation in the family systems therapy was associated with decreased mother-child discrepancies, and also a synchronous increase in mother's and child's autonomy and relatedness. Additionally, increased mother-child discrepancies and mother-child dyads showing no change in autonomy and relatedness was associated with higher levels of children's problem behaviors. The findings reveal a dynamic process of mother-child discrepancies in autonomy and relatedness behaviors related to child outcomes. The findings also support the effectiveness of the family systems therapy, and highlight the importance of understanding the complexities in family interactions when explaining children's problem behaviors.

Continuous monitoring the vehicle dynamics and driver behavior using navigation systems

NASA Astrophysics Data System (ADS)

Ene, George

2017-10-01

In all fields cost is very important and the increasing amount of data that are needed for active safety systems, like ADAS, lead to implementation of some complex and powerful unit for processing raw data. In this manner is necessary a cost-effective method to estimate the maximum available tire road friction during acceleration and braking by continuous monitoring the vehicle dynamics and driver behavior. The method is based on the hypothesis that short acceleration and braking periods can indicate vehicle dynamics, and thus the available tire road friction coefficient, and also human behavior and his limits. Support for this hypothesis is found in the literature and is supported by the result of experiments conducted under different conditions and seasons.

Renormalization Group Tutorial

NASA Technical Reports Server (NTRS)

Bell, Thomas L.

2004-01-01

Complex physical systems sometimes have statistical behavior characterized by power- law dependence on the parameters of the system and spatial variability with no particular characteristic scale as the parameters approach critical values. The renormalization group (RG) approach was developed in the fields of statistical mechanics and quantum field theory to derive quantitative predictions of such behavior in cases where conventional methods of analysis fail. Techniques based on these ideas have since been extended to treat problems in many different fields, and in particular, the behavior of turbulent fluids. This lecture will describe a relatively simple but nontrivial example of the RG approach applied to the diffusion of photons out of a stellar medium when the photons have wavelengths near that of an emission line of atoms in the medium.

Recurrence quantity analysis based on matrix eigenvalues

NASA Astrophysics Data System (ADS)

Yang, Pengbo; Shang, Pengjian

2018-06-01

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

Role of Graph Architecture in Controlling Dynamical Networks with Applications to Neural Systems.

PubMed

Kim, Jason Z; Soffer, Jonathan M; Kahn, Ari E; Vettel, Jean M; Pasqualetti, Fabio; Bassett, Danielle S

2018-01-01

Networked systems display complex patterns of interactions between components. In physical networks, these interactions often occur along structural connections that link components in a hard-wired connection topology, supporting a variety of system-wide dynamical behaviors such as synchronization. While descriptions of these behaviors are important, they are only a first step towards understanding and harnessing the relationship between network topology and system behavior. Here, we use linear network control theory to derive accurate closed-form expressions that relate the connectivity of a subset of structural connections (those linking driver nodes to non-driver nodes) to the minimum energy required to control networked systems. To illustrate the utility of the mathematics, we apply this approach to high-resolution connectomes recently reconstructed from Drosophila, mouse, and human brains. We use these principles to suggest an advantage of the human brain in supporting diverse network dynamics with small energetic costs while remaining robust to perturbations, and to perform clinically accessible targeted manipulation of the brain's control performance by removing single edges in the network. Generally, our results ground the expectation of a control system's behavior in its network architecture, and directly inspire new directions in network analysis and design via distributed control.

Distributed recurrent neural forward models with synaptic adaptation and CPG-based control for complex behaviors of walking robots

PubMed Central

Dasgupta, Sakyasingha; Goldschmidt, Dennis; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like stick insects, cockroaches or ants, demonstrate a fascinating range of locomotive abilities and complex behaviors. The locomotive behaviors can consist of a variety of walking patterns along with adaptation that allow the animals to deal with changes in environmental conditions, like uneven terrains, gaps, obstacles etc. Biological study has revealed that such complex behaviors are a result of a combination of biomechanics and neural mechanism thus representing the true nature of embodied interactions. While the biomechanics helps maintain flexibility and sustain a variety of movements, the neural mechanisms generate movements while making appropriate predictions crucial for achieving adaptation. Such predictions or planning ahead can be achieved by way of internal models that are grounded in the overall behavior of the animal. Inspired by these findings, we present here, an artificial bio-inspired walking system which effectively combines biomechanics (in terms of the body and leg structures) with the underlying neural mechanisms. The neural mechanisms consist of (1) central pattern generator based control for generating basic rhythmic patterns and coordinated movements, (2) distributed (at each leg) recurrent neural network based adaptive forward models with efference copies as internal models for sensory predictions and instantaneous state estimations, and (3) searching and elevation control for adapting the movement of an individual leg to deal with different environmental conditions. Using simulations we show that this bio-inspired approach with adaptive internal models allows the walking robot to perform complex locomotive behaviors as observed in insects, including walking on undulated terrains, crossing large gaps, leg damage adaptations, as well as climbing over high obstacles. Furthermore, we demonstrate that the newly developed recurrent network based approach to online forward models outperforms the adaptive neuron forward models, which have hitherto been the state of the art, to model a subset of similar walking behaviors in walking robots. PMID:26441629

Sensory response system of social behavior tied to female reproductive traits.

PubMed

Tsuruda, Jennifer M; Amdam, Gro V; Page, Robert E

2008-01-01

Honey bees display a complex set of anatomical, physiological, and behavioral traits that correlate with the colony storage of surplus pollen (pollen hoarding). We hypothesize that the association of these traits is a result of pleiotropy in a gene signaling network that was co-opted by natural selection to function in worker division of labor and foraging specialization. By acting on the gene network, selection can change a suite of traits, including stimulus/response relationships that affect individual foraging behavior and alter the colony level trait of pollen hoarding. The 'pollen-hoarding syndrome' of honey bees is the best documented syndrome of insect social organization. It can be exemplified as a link between reproductive anatomy (ovary size), physiology (yolk protein level), and foraging behavior in honey bee strains selected for pollen hoarding, a colony level trait. The syndrome gave rise to the forager-Reproductive Ground Plan Hypothesis (RGPH), which proposes that the regulatory control of foraging onset and foraging preference toward nectar or pollen was derived from a reproductive signaling network. This view was recently challenged. To resolve the controversy, we tested the associations between reproductive anatomy, physiology, and stimulus/response relationships of behavior in wild-type honey bees. Central to the stimulus/response relationships of honey bee foraging behavior and pollen hoarding is the behavioral trait of sensory sensitivity to sucrose (an important sugar in nectar). To test the linkage of reproductive traits and sensory response systems of social behavior, we measured sucrose responsiveness with the proboscis extension response (PER) assay and quantified ovary size and vitellogenin (yolk precursor) gene expression in 6-7-day-old bees by counting ovarioles (ovary filaments) and by using semiquantitative real time RT-PCR. We show that bees with larger ovaries (more ovarioles) are characterized by higher levels of vitellogenin mRNA expression and are more responsive to sucrose solutions, a trait that is central to division of labor and foraging specialization. Our results establish that in wild-type honey bees, ovary size and vitellogenin mRNA level covary with the sucrose sensory response system, an important component of foraging behavior. This finding validates links between reproductive physiology and behavioral-trait associations of the pollen-hoarding syndrome of honey bees, and supports the forager-RGPH. Our data address a current evolutionary debate, and represent the first direct demonstration of the links between reproductive anatomy, physiology, and behavioral response systems that are central to the control of complex social behavior in insects.

Fast parametric relationships for the large-scale reservoir simulation of mixed CH 4-CO 2 gas hydrate systems

DOE PAGES

Reagan, Matthew T.; Moridis, George J.; Seim, Katie S.

2017-03-27

A recent Department of Energy field test on the Alaska North Slope has increased interest in the ability to simulate systems of mixed CO 2-CH 4 hydrates. However, the physically realistic simulation of mixed-hydrate simulation is not yet a fully solved problem. Limited quantitative laboratory data leads to the use of various ab initio, statistical mechanical, or other mathematic representations of mixed-hydrate phase behavior. Few of these methods are suitable for inclusion in reservoir simulations, particularly for systems with large number of grid elements, 3D systems, or systems with complex geometric configurations. In this paper, we present a set ofmore » fast parametric relationships describing the thermodynamic properties and phase behavior of a mixed methane-carbon dioxide hydrate system. We use well-known, off-the-shelf hydrate physical properties packages to generate a sufficiently large dataset, select the most convenient and efficient mathematical forms, and fit the data to those forms to create a physical properties package suitable for inclusion in the TOUGH+ family of codes. Finally, the mapping of the phase and thermodynamic space reveals the complexity of the mixed-hydrate system and allows understanding of the thermodynamics at a level beyond what much of the existing laboratory data and literature currently offer.« less

Fast parametric relationships for the large-scale reservoir simulation of mixed CH4-CO2 gas hydrate systems

NASA Astrophysics Data System (ADS)

Reagan, Matthew T.; Moridis, George J.; Seim, Katie S.

2017-06-01

A recent Department of Energy field test on the Alaska North Slope has increased interest in the ability to simulate systems of mixed CO2-CH4 hydrates. However, the physically realistic simulation of mixed-hydrate simulation is not yet a fully solved problem. Limited quantitative laboratory data leads to the use of various ab initio, statistical mechanical, or other mathematic representations of mixed-hydrate phase behavior. Few of these methods are suitable for inclusion in reservoir simulations, particularly for systems with large number of grid elements, 3D systems, or systems with complex geometric configurations. In this work, we present a set of fast parametric relationships describing the thermodynamic properties and phase behavior of a mixed methane-carbon dioxide hydrate system. We use well-known, off-the-shelf hydrate physical properties packages to generate a sufficiently large dataset, select the most convenient and efficient mathematical forms, and fit the data to those forms to create a physical properties package suitable for inclusion in the TOUGH+ family of codes. The mapping of the phase and thermodynamic space reveals the complexity of the mixed-hydrate system and allows understanding of the thermodynamics at a level beyond what much of the existing laboratory data and literature currently offer.

Fast parametric relationships for the large-scale reservoir simulation of mixed CH 4-CO 2 gas hydrate systems

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

Reagan, Matthew T.; Moridis, George J.; Seim, Katie S.

A recent Department of Energy field test on the Alaska North Slope has increased interest in the ability to simulate systems of mixed CO 2-CH 4 hydrates. However, the physically realistic simulation of mixed-hydrate simulation is not yet a fully solved problem. Limited quantitative laboratory data leads to the use of various ab initio, statistical mechanical, or other mathematic representations of mixed-hydrate phase behavior. Few of these methods are suitable for inclusion in reservoir simulations, particularly for systems with large number of grid elements, 3D systems, or systems with complex geometric configurations. In this paper, we present a set ofmore » fast parametric relationships describing the thermodynamic properties and phase behavior of a mixed methane-carbon dioxide hydrate system. We use well-known, off-the-shelf hydrate physical properties packages to generate a sufficiently large dataset, select the most convenient and efficient mathematical forms, and fit the data to those forms to create a physical properties package suitable for inclusion in the TOUGH+ family of codes. Finally, the mapping of the phase and thermodynamic space reveals the complexity of the mixed-hydrate system and allows understanding of the thermodynamics at a level beyond what much of the existing laboratory data and literature currently offer.« less

Teaching complex verbal operants to children with autism and establishing generalization using the peak curriculum.

PubMed

Dixon, Mark R; Peach, Jacqueline; Daar, Jacob H; Penrod, Cindy

2017-04-01

The present study evaluated the feasibility of the PEAK Relational Training System's Generalization Module (Dixon, 2014b) to teach and establish generalization of autoclitic mands, distorted tacts, and creative path finding in three children diagnosed with autism spectrum disorder. Using a multiple-baseline design across behaviors, each participant was provided with differential reinforcement and a least-to-most prompting hierarchy for correct responses to a subset of stimuli, and responses to other similar stimulus sets were probed for emergent generalization. Following training, each participant successfully acquired the directly trained behaviors and demonstrated generalization to the nonreinforced test exemplars. These data support the utility of Skinner's (1957) analysis to teach complex forms of verbal operants, and suggest that a manualized curriculum such as PEAK may have utility for promoting skill development and generalization for front line staff and caregivers of children with autism. © 2017 Society for the Experimental Analysis of Behavior.

Genetics on the Fly: A Primer on the Drosophila Model System

PubMed Central

Hales, Karen G.; Korey, Christopher A.; Larracuente, Amanda M.; Roberts, David M.

2015-01-01

Fruit flies of the genus Drosophila have been an attractive and effective genetic model organism since Thomas Hunt Morgan and colleagues made seminal discoveries with them a century ago. Work with Drosophila has enabled dramatic advances in cell and developmental biology, neurobiology and behavior, molecular biology, evolutionary and population genetics, and other fields. With more tissue types and observable behaviors than in other short-generation model organisms, and with vast genome data available for many species within the genus, the fly’s tractable complexity will continue to enable exciting opportunities to explore mechanisms of complex developmental programs, behaviors, and broader evolutionary questions. This primer describes the organism’s natural history, the features of sequenced genomes within the genus, the wide range of available genetic tools and online resources, the types of biological questions Drosophila can help address, and historical milestones. PMID:26564900

Dynamics of Charged Species in Ionic-Neutral Block Copolymer and Surfactant Complexes [Structural Relaxation and Dynamics of Ionic-Neutral Block Copolymer Surfactant Complexes

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

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

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

Neural basis of processing threatening voices in a crowded auditory world

PubMed Central

Mothes-Lasch, Martin; Becker, Michael P. I.; Miltner, Wolfgang H. R.

2016-01-01

In real world situations, we typically listen to voice prosody against a background crowded with auditory stimuli. Voices and background can both contain behaviorally relevant features and both can be selectively in the focus of attention. Adequate responses to threat-related voices under such conditions require that the brain unmixes reciprocally masked features depending on variable cognitive resources. It is unknown which brain systems instantiate the extraction of behaviorally relevant prosodic features under varying combinations of prosody valence, auditory background complexity and attentional focus. Here, we used event-related functional magnetic resonance imaging to investigate the effects of high background sound complexity and attentional focus on brain activation to angry and neutral prosody in humans. Results show that prosody effects in mid superior temporal cortex were gated by background complexity but not attention, while prosody effects in the amygdala and anterior superior temporal cortex were gated by attention but not background complexity, suggesting distinct emotional prosody processing limitations in different regions. Crucially, if attention was focused on the highly complex background, the differential processing of emotional prosody was prevented in all brain regions, suggesting that in a distracting, complex auditory world even threatening voices may go unnoticed. PMID:26884543

Dynamics of Charged Species in Ionic-Neutral Block Copolymer and Surfactant Complexes [Structural Relaxation and Dynamics of Ionic-Neutral Block Copolymer Surfactant Complexes

DOE PAGES

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

2017-06-21

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

Self-organized criticality in a cold plasma

NASA Astrophysics Data System (ADS)

Alex, Prince; Carreras, Benjamin Andres; Arumugam, Saravanan; Sinha, Suraj Kumar

2017-12-01

We present direct evidence for the existence of self-organized critical behavior in cold plasma. A multiple anodic double layer structure generated in a double discharge plasma setup shows critical behavior for the anode bias above a threshold value. Analysis of the floating potential fluctuations reveals the existence of long-range time correlations and power law behavior in the tail of the probability distribution function of the fluctuations. The measured Hurst exponent and the power law tail in the rank function are strong indication of the self-organized critical behavior of the system and hence provide a condition under which complexities arise in cold plasma.

Space and time in ecology: Noise or fundamental driver? [chapter 2

Treesearch

Samuel A. Cushman

2010-01-01

In this chapter I frame the central issue of the book, namely is spatial and temporal complexity in ecological systems merely noise around the predictions of non-spatial, equilibrium processes? Or, alternatively, do spatial and temporal variability in the environment and autogenic space­time processes in populations fundamentally alter system behavior such that ideal...

Real-Time Visualization of Network Behaviors for Situational Awareness

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

Best, Daniel M.; Bohn, Shawn J.; Love, Douglas V.

Plentiful, complex, and dynamic data make understanding the state of an enterprise network difficult. Although visualization can help analysts understand baseline behaviors in network traffic and identify off-normal events, visual analysis systems often do not scale well to operational data volumes (in the hundreds of millions to billions of transactions per day) nor to analysis of emergent trends in real-time data. We present a system that combines multiple, complementary visualization techniques coupled with in-stream analytics, behavioral modeling of network actors, and a high-throughput processing platform called MeDICi. This system provides situational understanding of real-time network activity to help analysts takemore » proactive response steps. We have developed these techniques using requirements gathered from the government users for which the tools are being developed. By linking multiple visualization tools to a streaming analytic pipeline, and designing each tool to support a particular kind of analysis (from high-level awareness to detailed investigation), analysts can understand the behavior of a network across multiple levels of abstraction.« less

Endocrine and neuroendocrine regulation of fathering behavior in birds.

PubMed

Lynn, Sharon E

2016-01-01

This article is part of a Special Issue "Parental Care". Although paternal care is generally rare among vertebrates, care of eggs and young by male birds is extremely common and may take on a variety of forms across species. Thus, birds provide ample opportunities for investigating both the evolution of and the proximate mechanisms underpinning diverse aspects of fathering behavior. However, significant gaps remain in our understanding of the endocrine and neuroendocrine influences on paternal care in this vertebrate group. In this review, I focus on proximate mechanisms of paternal care in birds. I place an emphasis on specific hormones that vary predictably and/or unpredictably during the parental phase in both captive and wild birds: prolactin and progesterone are generally assumed to enhance paternal care, whereas testosterone and corticosterone are commonly-though not always correctly-assumed to inhibit paternal care. In addition, because endocrine secretions are not the sole mechanistic influence on paternal behavior, I also explore potential roles for certain neuropeptide systems (specifically the oxytocin-vasopressin nonapeptides and gonadotropin inhibitory hormone) and social and experiential factors in influencing paternal behavior in birds. Ultimately, mechanistic control of fathering behavior in birds is complex, and I suggest specific avenues for future research with the goal of narrowing gaps in our understanding of this complexity. Such avenues include (1) experimental studies that carefully consider not only endocrine and neuroendocrine mechanisms of paternal behavior, but also the ecology, phylogenetic history, and social context of focal species; (2) investigations that focus on individual variation in both hormonal and behavioral responses during the parental phase; (3) studies that investigate mechanisms of maternal and paternal care independently, rather than assuming that the mechanistic foundations of care are similar between the sexes; (4) expansion of work on interactions of the neuroendocrine system and fathering behavior to a wider array of paternal behaviors and taxa (e.g., currently, studies of the interactions of testosterone and paternal care largely focus on songbirds, whereas studies of the interactions of corticosterone, prolactin, and paternal care in times of stress focus primarily on seabirds); and (5) more deliberate study of exceptions to commonly held assumptions about hormone-paternal behavior interactions (such as the prevailing assumptions that elevations in androgens and glucocorticoids are universally disruptive to paternal care). Ultimately, investigations that take an intentionally integrative approach to understanding the social, evolutionary, and physiological influences on fathering behavior will make great strides toward refining our understanding of the complex nature by which paternal behavior in birds is regulated. Copyright © 2015 Elsevier Inc. All rights reserved.

Complexity reduction of rate-equations models for two-choice decision-making.

PubMed

Carrillo, José Antonio; Cordier, Stéphane; Deco, Gustavo; Mancini, Simona

2013-01-01

We are concerned with the complexity reduction of a stochastic system of differential equations governing the dynamics of a neuronal circuit describing a decision-making task. This reduction is based on the slow-fast behavior of the problem and holds on the whole phase space and not only locally around the spontaneous state. Macroscopic quantities, such as performance and reaction times, computed applying this reduction are in agreement with previous works in which the complexity reduction is locally performed at the spontaneous point by means of a Taylor expansion.

A new universality class in corpus of texts; A statistical physics study

NASA Astrophysics Data System (ADS)

Najafi, Elham; Darooneh, Amir H.

2018-05-01

Text can be regarded as a complex system. There are some methods in statistical physics which can be used to study this system. In this work, by means of statistical physics methods, we reveal new universal behaviors of texts associating with the fractality values of words in a text. The fractality measure indicates the importance of words in a text by considering distribution pattern of words throughout the text. We observed a power law relation between fractality of text and vocabulary size for texts and corpora. We also observed this behavior in studying biological data.

Growth and Decay in Life-Like Cellular Automata

NASA Astrophysics Data System (ADS)

Eppstein, David

Since the study of life began, many have asked: is it unique in the universe, or are there other interesting forms of life elsewhere? Before we can answer that question, we should ask others: What makes life special? If we happen across another system with life-like behavior, how would we be able to recognize it? We are speaking, of course, of the mathematical systems of cellular automata, of the fascinating patterns that have been discovered and engineered in Conway's Game of Life, and of the possible existence of other cellular automaton rules with equally complex behavior to that of Life.

“Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases

PubMed Central

Gutierrez Najera, Nora A.; Resendis-Antonio, Osbaldo; Nicolini, Humberto

2017-01-01

The integration of different sources of biological information about what defines a behavioral phenotype is difficult to unify in an entity that reflects the arithmetic sum of its individual parts. In this sense, the challenge of Systems Biology for understanding the “psychiatric phenotype” is to provide an improved vision of the shape of the phenotype as it is visualized by “Gestalt” psychology, whose fundamental axiom is that the observed phenotype (behavior or mental disorder) will be the result of the integrative composition of every part. Therefore, we propose the term “Gestaltomics” as a term from Systems Biology to integrate data coming from different sources of information (such as the genome, transcriptome, proteome, epigenome, metabolome, phenome, and microbiome). In addition to this biological complexity, the mind is integrated through multiple brain functions that receive and process complex information through channels and perception networks (i.e., sight, ear, smell, memory, and attention) that in turn are programmed by genes and influenced by environmental processes (epigenetic). Today, the approach of medical research in human diseases is to isolate one disease for study; however, the presence of an additional disease (co-morbidity) or more than one disease (multimorbidity) adds complexity to the study of these conditions. This review will present the challenge of integrating psychiatric disorders at different levels of information (Gestaltomics). The implications of increasing the level of complexity, for example, studying the co-morbidity with another disease such as cancer, will also be discussed. PMID:28536537