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

PubMed

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

2017-11-22

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

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

PubMed

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

2018-03-21

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

Linking Complexity with Cultural Historical Activity Theory

ERIC Educational Resources Information Center

McMurtry, Angus

2006-01-01

This paper explores the similarities and differences between complexity science's and cultural-historical activity theory's understandings of human learning. Notable similarities include their emphasis on the importance of social systems or collectives in understanding human knowledge and practices, as well as their characterization of systems'…

Collaborative Modelling of the Vascular System--Designing and Evaluating a New Learning Method for Secondary Students

ERIC Educational Resources Information Center

Haugwitz, Marion; Sandmann, Angela

2010-01-01

Understanding biological structures and functions is often difficult because of their complexity and micro-structure. For example, the vascular system is a complex and only partly visible system. Constructing models to better understand biological functions is seen as a suitable learning method. Models function as simplified versions of real…

Schools as social complex adaptive systems: a new way to understand the challenges of introducing the health promoting schools concept.

PubMed

Keshavarz, Nastaran; Nutbeam, Don; Rowling, Louise; Khavarpour, Freidoon

2010-05-01

Achieving system-wide implementation of health promotion programs in schools and sustaining both the program and its health related benefits have proved challenging. This paper reports on a qualitative study examining the implementation of health promoting schools programs in primary schools in Sydney, Australia. It draw upon insights from systems science to examine the relevance and usefulness of the concept of "complex adaptive systems" as a framework to better understand ways in which health promoting school interventions could be introduced and sustained. The primary data for the study were collected by semi-structured interviews with 26 school principals and teachers. Additional information was extracted from publicly available school management plans and annual reports. We examined the data from these sources to determine whether schools exhibit characteristics of complex adaptive systems. The results confirmed that schools do exhibit most, but not all of the characteristics of social complex adaptive systems, and exhibit significant differences with artificial and natural systems. Understanding schools as social complex adaptive systems may help to explain some of the challenges of introducing and sustaining change in schools. These insights may, in turn, lead us to adopt more sophisticated approaches to the diffusion of new programs in school systems that account for the diverse, complex and context specific nature of individual school systems. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Understanding Complex Adaptive Systems by Playing Games

ERIC Educational Resources Information Center

van Bilsen, Arthur; Bekebrede, Geertje; Mayer, Igor

2010-01-01

While educators teach their students about decision making in complex environments, managers have to deal with the complexity of large projects on a daily basis. To make better decisions it is assumed, that the latter would benefit from better understanding of complex phenomena, as do students as the professionals of the future. The goal of this…

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).

General description and understanding of the nonlinear dynamics of mode-locked fiber lasers.

PubMed

Wei, Huai; Li, Bin; Shi, Wei; Zhu, Xiushan; Norwood, Robert A; Peyghambarian, Nasser; Jian, Shuisheng

2017-05-02

As a type of nonlinear system with complexity, mode-locked fiber lasers are known for their complex behaviour. It is a challenging task to understand the fundamental physics behind such complex behaviour, and a unified description for the nonlinear behaviour and the systematic and quantitative analysis of the underlying mechanisms of these lasers have not been developed. Here, we present a complexity science-based theoretical framework for understanding the behaviour of mode-locked fiber lasers by going beyond reductionism. This hierarchically structured framework provides a model with variable dimensionality, resulting in a simple view that can be used to systematically describe complex states. Moreover, research into the attractors' basins reveals the origin of stochasticity, hysteresis and multistability in these systems and presents a new method for quantitative analysis of these nonlinear phenomena. These findings pave the way for dynamics analysis and system designs of mode-locked fiber lasers. We expect that this paradigm will also enable potential applications in diverse research fields related to complex nonlinear phenomena.

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

NASA Astrophysics Data System (ADS)

Yoon, Susan Anne

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

Dissecting innate immune responses with the tools of systems biology.

PubMed

Smith, Kelly D; Bolouri, Hamid

2005-02-01

Systems biology strives to derive accurate predictive descriptions of complex systems such as innate immunity. The innate immune system is essential for host defense, yet the resulting inflammatory response must be tightly regulated. Current understanding indicates that this system is controlled by complex regulatory networks, which maintain homoeostasis while accurately distinguishing pathogenic infections from harmless exposures. Recent studies have used high throughput technologies and computational techniques that presage predictive models and will be the foundation of a systems level understanding of innate immunity.

[Health: an adaptive complex system].

PubMed

Toro-Palacio, Luis Fernando; Ochoa-Jaramillo, Francisco Luis

2012-02-01

This article points out the enormous gap that exists between complex thinking of an intellectual nature currently present in our environment, and complex experimental thinking that has facilitated the scientific and technological advances that have radically changed the world. The article suggests that life, human beings, global society, and all that constitutes health be considered as adaptive complex systems. This idea, in turn, prioritizes the adoption of a different approach that seeks to expand understanding. When this rationale is recognized, the principal characteristics and emerging properties of health as an adaptive complex system are sustained, following a care and services delivery model. Finally, some pertinent questions from this perspective are put forward in terms of research, and a series of appraisals are expressed that will hopefully serve to help us understand all that we have become as individuals and as a species. The article proposes that the delivery of health care services be regarded as an adaptive complex system.

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

ERIC Educational Resources Information Center

Storey, Brian; Butler, Joy

2013-01-01

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

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

PubMed

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

2018-02-01

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

Hypothesis: the chaos and complexity theory may help our understanding of fibromyalgia and similar maladies.

PubMed

Martinez-Lavin, Manuel; Infante, Oscar; Lerma, Claudia

2008-02-01

Modern clinicians are often frustrated by their inability to understand fibromyalgia and similar maladies since these illnesses cannot be explained by the prevailing linear-reductionist medical paradigm. This article proposes that new concepts derived from the Complexity Theory may help understand the pathogenesis of fibromyalgia, chronic fatigue syndrome, and Gulf War syndrome. This hypothesis is based on the recent recognition of chaos fractals and complex systems in human physiology. These nonlinear dynamics concepts offer a different perspective to the notion of homeostasis and disease. They propose that the essence of disease is dysfunction and not structural damage. Studies using novel nonlinear instruments have shown that fibromyalgia and similar maladies may be caused by the degraded performance of our main complex adaptive system. This dysfunction explains the multifaceted manifestations of these entities. To understand and alleviate the suffering associated with these complex illnesses, a paradigm shift from reductionism to holism based on the Complexity Theory is suggested. This shift perceives health as resilient adaptation and some chronic illnesses as rigid dysfunction.

Mathematical and Computational Modeling in Complex Biological Systems

PubMed Central

Li, Wenyang; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology. PMID:28386558

Mathematical and Computational Modeling in Complex Biological Systems.

PubMed

Ji, Zhiwei; Yan, Ke; Li, Wenyang; Hu, Haigen; Zhu, Xiaoliang

2017-01-01

The biological process and molecular functions involved in the cancer progression remain difficult to understand for biologists and clinical doctors. Recent developments in high-throughput technologies urge the systems biology to achieve more precise models for complex diseases. Computational and mathematical models are gradually being used to help us understand the omics data produced by high-throughput experimental techniques. The use of computational models in systems biology allows us to explore the pathogenesis of complex diseases, improve our understanding of the latent molecular mechanisms, and promote treatment strategy optimization and new drug discovery. Currently, it is urgent to bridge the gap between the developments of high-throughput technologies and systemic modeling of the biological process in cancer research. In this review, we firstly studied several typical mathematical modeling approaches of biological systems in different scales and deeply analyzed their characteristics, advantages, applications, and limitations. Next, three potential research directions in systems modeling were summarized. To conclude, this review provides an update of important solutions using computational modeling approaches in systems biology.

Promoting Complex Systems Learning through the Use of Conceptual Representations in Hypermedia

ERIC Educational Resources Information Center

Liu, Lei; Hmelo-Silver, Cindy E.

2009-01-01

Studying complex systems is increasingly important in many science domains. Many features of complex systems make it difficult for students to develop deep understanding. Our previous research indicated that a function-centered conceptual representation is part of the disciplinary toolbox of biologists, suggesting that it is an appropriate…

1991 Annual report on scientific programs: A broad research program on the sciences of complexity

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

Not Available

1991-01-01

1991 was continued rapid growth for the Santa Fe Institute (SFI) as it broadened its interdisciplinary research into the organization, evolution and operation of complex systems and sought deeply the principles underlying their dynamic behavior. Research on complex systems--the focus of work at SFI--involves an extraordinary range of topics normally studied in seemingly disparate fields. Natural systems displaying complex behavior range upwards from proteins and DNA through cells and evolutionary systems to human societies. Research models exhibiting complexity include nonlinear equations, spin glasses, cellular automata, genetic algorithms, classifier systems, and an array of other computational models. Some of the majormore » questions facing complex systems researchers are: (1) explaining how complexity arises from the nonlinear interaction of simples components, (2) describing the mechanisms underlying high-level aggregate behavior of complex systems (such as the overt behavior of an organism, the flow of energy in an ecology, the GNP of an economy), and (3) creating a theoretical framework to enable predictions about the likely behavior of such systems in various conditions. The importance of understanding such systems in enormous: many of the most serious challenges facing humanity--e.g., environmental sustainability, economic stability, the control of disease--as well as many of the hardest scientific questions--e.g., protein folding, the distinction between self and non-self in the immune system, the nature of intelligence, the origin of life--require deep understanding of complex systems.« less

1991 Annual report on scientific programs: A broad research program on the sciences of complexity

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

Not Available

1991-12-31

1991 was continued rapid growth for the Santa Fe Institute (SFI) as it broadened its interdisciplinary research into the organization, evolution and operation of complex systems and sought deeply the principles underlying their dynamic behavior. Research on complex systems--the focus of work at SFI--involves an extraordinary range of topics normally studied in seemingly disparate fields. Natural systems displaying complex behavior range upwards from proteins and DNA through cells and evolutionary systems to human societies. Research models exhibiting complexity include nonlinear equations, spin glasses, cellular automata, genetic algorithms, classifier systems, and an array of other computational models. Some of the majormore » questions facing complex systems researchers are: (1) explaining how complexity arises from the nonlinear interaction of simples components, (2) describing the mechanisms underlying high-level aggregate behavior of complex systems (such as the overt behavior of an organism, the flow of energy in an ecology, the GNP of an economy), and (3) creating a theoretical framework to enable predictions about the likely behavior of such systems in various conditions. The importance of understanding such systems in enormous: many of the most serious challenges facing humanity--e.g., environmental sustainability, economic stability, the control of disease--as well as many of the hardest scientific questions--e.g., protein folding, the distinction between self and non-self in the immune system, the nature of intelligence, the origin of life--require deep understanding of complex systems.« less

Taxonomy for complexity theory in the context of maternity care.

PubMed

Nieuwenhuijze, Marianne; Downe, Soo; Gottfreðsdóttir, Helga; Rijnders, Marlies; du Preez, Antoinette; Vaz Rebelo, Piedade

2015-09-01

The linear focus of 'normal science' is unable to adequately take account of the complex interactions that direct health care systems. There is a turn towards complexity theory as a more appropriate framework for understanding system behaviour. However, a comprehensive taxonomy for complexity theory in the context of health care is lacking. This paper aims to build a taxonomy based on the key complexity theory components that have been used in publications on complexity theory and health care, and to explore their explanatory power for health care system behaviour, specifically for maternity care. A search strategy was devised in PubMed and 31 papers were identified as relevant for the taxonomy. The final taxonomy for complexity theory included and defined 11 components. The use of waterbirth and the impact of the Term Breech trial showed that each of the components of our taxonomy has utility in helping to understand how these techniques became widely adopted. It is not just the components themselves that characterise a complex system but also the dynamics between them. Copyright © 2015 Elsevier Ltd. All rights reserved.

Characterising the Development of the Understanding of Human Body Systems in High-School Biology Students--A Longitudinal Study

ERIC Educational Resources Information Center

Snapir, Zohar; Eberbach, Catherine; Ben-Zvi-Assaraf, Orit; Hmelo-Silver, Cindy; Tripto, Jaklin

2017-01-01

Science education today has become increasingly focused on research into complex natural, social and technological systems. In this study, we examined the development of high-school biology students' systems understanding of the human body, in a three-year longitudinal study. The development of the students' system understanding was evaluated…

The dynamics of health care reform--learning from a complex adaptive systems theoretical perspective.

PubMed

Sturmberg, Joachim P; Martin, Carmel M

2010-10-01

Health services demonstrate key features of complex adaptive systems (CAS), they are dynamic and unfold in unpredictable ways, and unfolding events are often unique. To better understand the complex adaptive nature of health systems around a core attractor we propose the metaphor of the health care vortex. We also suggest that in an ideal health care system the core attractor would be personal health attainment. Health care reforms around the world offer an opportunity to analyse health system change from a complex adaptive perspective. At large health care reforms have been pursued disregarding the complex adaptive nature of the health system. The paper details some recent reforms and outlines how to understand their strategies and outcomes, and what could be learnt for future efforts, utilising CAS principles. Current health systems show the inherent properties of a CAS driven by a core attractor of disease and cost containment. We content that more meaningful health systems reform requires the delicate task of shifting the core attractor from disease and cost containment towards health attainment.

Video Analysis and Remote Digital Ethnography: Approaches to understanding user perspectives and processes involving healthcare information technology.

PubMed

Kushniruk, Andre W; Borycki, Elizabeth M

2015-01-01

Innovations in healthcare information systems promise to revolutionize and streamline healthcare processes worldwide. However, the complexity of these systems and the need to better understand issues related to human-computer interaction have slowed progress in this area. In this chapter the authors describe their work in using methods adapted from usability engineering, video ethnography and analysis of digital log files for improving our understanding of complex real-world healthcare interactions between humans and technology. The approaches taken are cost-effective and practical and can provide detailed ethnographic data on issues health professionals and consumers encounter while using systems as well as potential safety problems. The work is important in that it can be used in techno-anthropology to characterize complex user interactions with technologies and also to provide feedback into redesign and optimization of improved healthcare information systems.

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/

Identifying behaviour patterns of construction safety using system archetypes.

PubMed

Guo, Brian H W; Yiu, Tak Wing; González, Vicente A

2015-07-01

Construction safety management involves complex issues (e.g., different trades, multi-organizational project structure, constantly changing work environment, and transient workforce). Systems thinking is widely considered as an effective approach to understanding and managing the complexity. This paper aims to better understand dynamic complexity of construction safety management by exploring archetypes of construction safety. To achieve this, this paper adopted the ground theory method (GTM) and 22 interviews were conducted with participants in various positions (government safety inspector, client, health and safety manager, safety consultant, safety auditor, and safety researcher). Eight archetypes were emerged from the collected data: (1) safety regulations, (2) incentive programs, (3) procurement and safety, (4) safety management in small businesses (5) production and safety, (6) workers' conflicting goals, (7) blame on workers, and (8) reactive and proactive learning. These archetypes capture the interactions between a wide range of factors within various hierarchical levels and subsystems. As a free-standing tool, they advance the understanding of dynamic complexity of construction safety management and provide systemic insights into dealing with the complexity. They also can facilitate system dynamics modelling of construction safety process. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mathematical modeling of physiological systems: an essential tool for discovery.

PubMed

Glynn, Patric; Unudurthi, Sathya D; Hund, Thomas J

2014-08-28

Mathematical models are invaluable tools for understanding the relationships between components of a complex system. In the biological context, mathematical models help us understand the complex web of interrelations between various components (DNA, proteins, enzymes, signaling molecules etc.) in a biological system, gain better understanding of the system as a whole, and in turn predict its behavior in an altered state (e.g. disease). Mathematical modeling has enhanced our understanding of multiple complex biological processes like enzyme kinetics, metabolic networks, signal transduction pathways, gene regulatory networks, and electrophysiology. With recent advances in high throughput data generation methods, computational techniques and mathematical modeling have become even more central to the study of biological systems. In this review, we provide a brief history and highlight some of the important applications of modeling in biological systems with an emphasis on the study of excitable cells. We conclude with a discussion about opportunities and challenges for mathematical modeling going forward. In a larger sense, the review is designed to help answer a simple but important question that theoreticians frequently face from interested but skeptical colleagues on the experimental side: "What is the value of a model?" Copyright © 2014 Elsevier Inc. All rights reserved.

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.

The Good, the Bad and the Ugly? The Dynamic Interplay between Educational Practice, Policy and Research

ERIC Educational Resources Information Center

Van Geert, Paul; Steenbeek, Henderien

2014-01-01

The notion of complexity--as in "education is a complex system"--has two different meanings. On the one hand, there is the epistemic connotation, with "Complex" meaning "difficult to understand, hard to control". On the other hand, complex has a technical meaning, referring to systems composed of many interacting…

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...

Understanding health system reform - a complex adaptive systems perspective.

PubMed

Sturmberg, Joachim P; O'Halloran, Di M; Martin, Carmel M

2012-02-01

Everyone wants a sustainable well-functioning health system. However, this notion has different meaning to policy makers and funders compared to clinicians and patients. The former perceive public policy and economic constraints, the latter clinical or patient-centred strategies as the means to achieving a desired outcome. Theoretical development and critical analysis of a complex health system model. We introduce the concept of the health care vortex as a metaphor by which to understand the complex adaptive nature of health systems, and the degree to which their behaviour is predetermined by their 'shared values' or attractors. We contrast the likely functions and outcomes of a health system with a people-centred attractor and one with a financial attractor. This analysis suggests a shift in the system's attractor is fundamental to progress health reform thinking. © 2012 Blackwell Publishing Ltd.

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.

The Self as a Complex Dynamic System

ERIC Educational Resources Information Center

Mercer, Sarah

2011-01-01

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

Systems Integration Challenges for a National Space Launch System

NASA Technical Reports Server (NTRS)

May, Todd A.

2011-01-01

System Integration was refined through the complexity and early failures experienced in rocket flight. System Integration encompasses many different viewpoints of the system development. System Integration must ensure consistency in development and operations activities. Human Space Flight tends toward large, complex systems. Understanding the system fs operational and use context is the guiding principle for System Integration: (1) Sizeable costs can be driven into systems by not fully understanding context (2). Adhering to the system context throughout the system fs life cycle is essential to maintaining efficient System Integration. System Integration exists within the System Architecture. Beautiful systems are simple in use and operation -- Block upgrades facilitate manageable steps in functionality evolution. Effective System Integration requires a stable system concept. Communication is essential to system simplicity

The trajectory of life. Decreasing physiological network complexity through changing fractal patterns

PubMed Central

Sturmberg, Joachim P.; Bennett, Jeanette M.; Picard, Martin; Seely, Andrew J. E.

2015-01-01

In this position paper, we submit a synthesis of theoretical models based on physiology, non-equilibrium thermodynamics, and non-linear time-series analysis. Based on an understanding of the human organism as a system of interconnected complex adaptive systems, we seek to examine the relationship between health, complexity, variability, and entropy production, as it might be useful to help understand aging, and improve care for patients. We observe the trajectory of life is characterized by the growth, plateauing and subsequent loss of adaptive function of organ systems, associated with loss of functioning and coordination of systems. Understanding development and aging requires the examination of interdependence among these organ systems. Increasing evidence suggests network interconnectedness and complexity can be captured/measured/associated with the degree and complexity of healthy biologic rhythm variability (e.g., heart and respiratory rate variability). We review physiological mechanisms linking the omics, arousal/stress systems, immune function, and mitochondrial bioenergetics; highlighting their interdependence in normal physiological function and aging. We argue that aging, known to be characterized by a loss of variability, is manifested at multiple scales, within functional units at the small scale, and reflected by diagnostic features at the larger scale. While still controversial and under investigation, it appears conceivable that the integrity of whole body complexity may be, at least partially, reflected in the degree and variability of intrinsic biologic rhythms, which we believe are related to overall system complexity that may be a defining feature of health and it's loss through aging. Harnessing this information for the development of therapeutic and preventative strategies may hold an opportunity to significantly improve the health of our patients across the trajectory of life. PMID:26082722

Systems and complexity thinking in general practice: part 1 - clinical application.

PubMed

Sturmberg, Joachim P

2007-03-01

Many problems encountered in general practice cannot be sufficiently explained within the Newtonian reductionist paradigm. Systems and complexity thinking - already widely adopted in most nonmedical disciplines - describes and explores the contextual nature of questions posed in medicine, and in general practice in particular. This article briefly describes the framework underpinning systems and complexity sciences. A case study illustrates how systems and complexity thinking can help to better understand the contextual nature of patient presentations, and how different approaches will lead to different outcomes.

Characterising the development of the understanding of human body systems in high-school biology students - a longitudinal study

NASA Astrophysics Data System (ADS)

Snapir, Zohar; Eberbach, Catherine; Ben-Zvi-Assaraf, Orit; Hmelo-Silver, Cindy; Tripto, Jaklin

2017-10-01

Science education today has become increasingly focused on research into complex natural, social and technological systems. In this study, we examined the development of high-school biology students' systems understanding of the human body, in a three-year longitudinal study. The development of the students' system understanding was evaluated using the Components Mechanisms Phenomena (CMP) framework for conceptual representation. We coded and analysed the repertory grid personal constructs of 67 high-school biology students at 4 points throughout the study. Our data analysis builds on the assumption that systems understanding entails a perception of all the system categories, including structures within the system (its Components), specific processes and interactions at the macro and micro levels (Mechanisms), and the Phenomena that present the macro scale of processes and patterns within a system. Our findings suggest that as the learning process progressed, the systems understanding of our students became more advanced, moving forward within each of the major CMP categories. Moreover, there was an increase in the mechanism complexity presented by the students, manifested by more students describing mechanisms at the molecular level. Thus, the 'mechanism' category and the micro level are critical components that enable students to understand system-level phenomena such as homeostasis.

Concept Mapping to Assess Learning and Understanding of Complexity in Courses on Global Climate Change

NASA Astrophysics Data System (ADS)

Rebich-Hespanha, S.; Gautier, C.

2010-12-01

The complex nature of climate change science poses special challenges for educators wishing to broaden and deepen student understanding of the climate system and its sensitivity to and impacts upon human activity. Learners have prior knowledge that may limit their perception and processing of the multiple relationships between processes (e.g., feedbacks) that arise in global change science, and these existing mental models serve as the scaffold for all future learning. Because adoption of complex scientific concepts is not likely if instruction includes presentation of information or concepts that are not compatible with the learners’ prior knowledge, providing effective instruction on this complex topic requires learning opportunities that are anchored upon an evaluation of the limitations and inaccuracies of the learners’ existing understandings of the climate system. The formative evaluation that serves as the basis for planning such instruction can also be useful as a baseline against which to evaluate subsequent learning. We will present concept-mapping activities that we have used to assess students’ knowledge and understanding about global climate change in courses that utilized multiple assessment methods including presentations, writings, discussions, and concept maps. The courses in which these activities were completed use a variety of instructional approaches (including standard lectures and lab assignments and a mock summit) to help students understand the inherently interdisciplinary topic of global climate change, its interwoven human and natural causes, and the connections it has with society through a complex range of political, social, technological and economic factors. Two instances of concept map assessment will be presented: one focused on evaluating student understanding of the major components of the climate system and their interconnections, and the other focused on student understanding of the connections between climate change and the global food system. We will discuss how concept mapping can be used to demonstrate evidence of learning and conceptual change, and also how it can be used to provide information about gaps in knowledge and misconceptions students have about the topic.

The genotype-phenotype map of an evolving digital organism.

PubMed

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

2017-02-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

The genotype-phenotype map of an evolving digital organism

PubMed Central

Zaman, Luis; Wagner, Andreas

2017-01-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable. PMID:28241039

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.

Social networks as embedded complex adaptive systems.

PubMed

Benham-Hutchins, Marge; Clancy, Thomas R

2010-09-01

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 15th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, the authors discuss healthcare social networks as a hierarchy of embedded complex adaptive systems. The authors further examine the use of social network analysis tools as a means to understand complex communication patterns and reduce medical errors.

How Information Visualization Systems Change Users' Understandings of Complex Data

ERIC Educational Resources Information Center

Allendoerfer, Kenneth Robert

2009-01-01

User-centered evaluations of information systems often focus on the usability of the system rather its usefulness. This study examined how a using an interactive knowledge-domain visualization (KDV) system affected users' understanding of a domain. Interactive KDVs allow users to create graphical representations of domains that depict important…

Concept Mapping: A Graphical System for Understanding the Relationship between Concepts. ERIC Digest.

ERIC Educational Resources Information Center

Plotnick, Eric

This ERIC Digest discusses concept mapping, a technique for representing the structure of information visually. Concept mapping can be used to brainstorm, design complex structures, communicate complex ideas, aid learning by explicitly integrating new and old knowledge, and assess understanding or diagnose misunderstanding. Visual representation…

Teaching Complex Concepts in the Geosciences by Integrating Analytical Reasoning with GIS

ERIC Educational Resources Information Center

Houser, Chris; Bishop, Michael P.; Lemmons, Kelly

2017-01-01

Conceptual models have long served as a means for physical geographers to organize their understanding of feedback mechanisms and complex systems. Analytical reasoning provides undergraduate students with an opportunity to develop conceptual models based upon their understanding of surface processes and environmental conditions. This study…

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

Dynamical systems in economics

NASA Astrophysics Data System (ADS)

Stanojević, Jelena; Kukić, Katarina

2018-01-01

In last few decades much attention is given to explain complex behaviour of very large systems, such as weather, economy, biology and demography. In this paper we give short overview of basic notions in the field of dynamical systems which are relevant for understanding complex nature of some economic models.

Toward a multiscale modeling framework for understanding serotonergic function

PubMed Central

Wong-Lin, KongFatt; Wang, Da-Hui; Moustafa, Ahmed A; Cohen, Jeremiah Y; Nakamura, Kae

2017-01-01

Despite its importance in regulating emotion and mental wellbeing, the complex structure and function of the serotonergic system present formidable challenges toward understanding its mechanisms. In this paper, we review studies investigating the interactions between serotonergic and related brain systems and their behavior at multiple scales, with a focus on biologically-based computational modeling. We first discuss serotonergic intracellular signaling and neuronal excitability, followed by neuronal circuit and systems levels. At each level of organization, we will discuss the experimental work accompanied by related computational modeling work. We then suggest that a multiscale modeling approach that integrates the various levels of neurobiological organization could potentially transform the way we understand the complex functions associated with serotonin. PMID:28417684

Mathematics and complex systems.

PubMed

Foote, Richard

2007-10-19

Contemporary researchers strive to understand complex physical phenomena that involve many constituents, may be influenced by numerous forces, and may exhibit unexpected or emergent behavior. Often such "complex systems" are macroscopic manifestations of other systems that exhibit their own complex behavior and obey more elemental laws. This article proposes that areas of mathematics, even ones based on simple axiomatic foundations, have discernible layers, entirely unexpected "macroscopic" outcomes, and both mathematical and physical ramifications profoundly beyond their historical beginnings. In a larger sense, the study of mathematics itself, which is increasingly surpassing the capacity of researchers to verify "by hand," may be the ultimate complex system.

Confluence and convergence: team effectiveness in complex systems.

PubMed

Porter-OʼGrady, Tim

2015-01-01

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

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 adaptive systems: A new approach for understanding health practices.

PubMed

Gomersall, Tim

2018-06-22

This article explores the potential of complex adaptive systems theory to inform behaviour change research. A complex adaptive system describes a collection of heterogeneous agents interacting within a particular context, adapting to each other's actions. In practical terms, this implies that behaviour change is 1) socially and culturally situated; 2) highly sensitive to small baseline differences in individuals, groups, and intervention components; and 3) determined by multiple components interacting "chaotically". Two approaches to studying complex adaptive systems are briefly reviewed. Agent-based modelling is a computer simulation technique that allows researchers to investigate "what if" questions in a virtual environment. Applied qualitative research techniques, on the other hand, offer a way to examine what happens when an intervention is pursued in real-time, and to identify the sorts of rules and assumptions governing social action. Although these represent very different approaches to complexity, there may be scope for mixing these methods - for example, by grounding models in insights derived from qualitative fieldwork. Finally, I will argue that the concept of complex adaptive systems offers one opportunity to gain a deepened understanding of health-related practices, and to examine the social psychological processes that produce health-promoting or damaging actions.

FuturICT: Participatory computing to understand and manage our complex world in a more sustainable and resilient way

NASA Astrophysics Data System (ADS)

Helbing, D.; Bishop, S.; Conte, R.; Lukowicz, P.; McCarthy, J. B.

2012-11-01

We have built particle accelerators to understand the forces that make up our physical world. Yet, we do not understand the principles underlying our strongly connected, techno-socio-economic systems. We have enabled ubiquitous Internet connectivity and instant, global information access. Yet we do not understand how it impacts our behavior and the evolution of society. To fill the knowledge gaps and keep up with the fast pace at which our world is changing, a Knowledge Accelerator must urgently be created. The financial crisis, international wars, global terror, the spreading of diseases and cyber-crime as well as demographic, technological and environmental change demonstrate that humanity is facing serious challenges. These problems cannot be solved within the traditional paradigms. Moving our attention from a component-oriented view of the world to an interaction-oriented view will allow us to understand the complex systems we have created and the emergent collective phenomena characterising them. This paradigm shift will enable new solutions to long-standing problems, very much as the shift from a geocentric to a heliocentric worldview has facilitated modern physics and the ability to launch satellites. The FuturICT flagship project will develop new science and technology to manage our future in a complex, strongly connected world. For this, it will combine the power of information and communication technology (ICT) with knowledge from the social and complexity sciences. ICT will provide the data to boost the social sciences into a new era. Complexity science will shed new light on the emergent phenomena in socially interactive systems, and the social sciences will provide a better understanding of the opportunities and risks of strongly networked systems, in particular future ICT systems. Hence, the envisaged FuturICT flagship will create new methods and instruments to tackle the challenges of the 21st century. FuturICT could indeed become one of the most important scientific endeavours ever, by revealing the principles that make socially interactive systems work well, by inspiring the creation of new platforms to explore our possible futures, and by initiating an era of social and socio-inspired innovations.

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

NASA Astrophysics Data System (ADS)

Box, Paul W.

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

The Affordable Care Act: a case study for understanding and applying complexity concepts to health care reform.

PubMed

Larkin, D Justin; Swanson, R Chad; Fuller, Spencer; Cortese, Denis A

2016-02-01

The current health system in the United States is the result of a history of patchwork policy decisions and cultural assumptions that have led to persistent contradictions in practice, gaps in coverage, unsustainable costs, and inconsistent outcomes. In working toward a more efficient health system, understanding and applying complexity science concepts will allow for policy that better promotes desired outcomes and minimizes the effects of unintended consequences. This paper will consider three applied complexity science concepts in the context of the Patient Protection and Affordable Care Act (PPACA): developing a shared vision around reimbursement for value, creating an environment for emergence through simple rules, and embracing transformational leadership at all levels. Transforming the US health system, or any other health system, will be neither easy nor quick. Applying complexity concepts to health reform efforts, however, will facilitate long-term change in all levels, leading to health systems that are more effective, efficient, and equitable. © 2014 John Wiley & Sons, Ltd.

A Complexity Approach to Evaluating National Scientific Systems through International Scientific Collaborations

ERIC Educational Resources Information Center

Zelnio, Ryan J.

2013-01-01

This dissertation seeks to contribute to a fuller understanding of how international scientific collaboration has affected national scientific systems. It does this by developing three methodological approaches grounded in social complexity theory and applying them to the evaluation of national scientific systems. The first methodology identifies…

Modeling Earth's Climate

ERIC Educational Resources Information Center

Pallant, Amy; Lee, Hee-Sun; Pryputniewicz, Sara

2012-01-01

Systems thinking suggests that one can best understand a complex system by studying the interrelationships of its component parts rather than looking at the individual parts in isolation. With ongoing concern about the effects of climate change, using innovative materials to help students understand how Earth's systems connect with each other is…

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

ERIC Educational Resources Information Center

Forjan, Matej; Grubelnik, Vladimir

2015-01-01

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

An integrated strategy for the planetary sciences: 1995 - 2010

NASA Technical Reports Server (NTRS)

1994-01-01

In 1992, the National Research Council's Space Studies Board charged its Committee on Planetary and Lunar Exploration (COMPLEX) to: (1) summarize current understanding of the planets and the solar system; (2) pose the most significant scientific questions that remain; and (3) establish the priorities for scientific exploration of the planets for the period from 1995 to 2010. The broad scientific goals of solar system exploration include: (1) understanding how physical and chemical processes determine the major characteristics of the planets, and thereby help us to understand the operation of Earth; (2) learning about how planetary systems originate and evolve; (3) determining how life developed in the solar system, particularly on Earth, and in what ways life modifies planetary environments; and (4) discovering how relatively simple, basic laws of physics and chemistry can lead to the diverse phenomena observed in complex systems. COMPLEX maintains that the most useful new programs to emphasize in the period from 1995 to 2010 are detailed investigations of comets, Mars, and Jupiter and an intensive search for, and characterization of, extrasolar planets.

Multivariate analysis: greater insights into complex systems

USDA-ARS?s Scientific Manuscript database

Many agronomic researchers measure and collect multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate (MV) statistical methods encompass the simultaneous analysis of all random variables (RV) measured on each experimental or sampling ...

Integrated research in natural resources: the key role of problem framing.

Treesearch

Roger N. Clark; George H. Stankey

2006-01-01

Integrated research is about achieving holistic understanding of complex biophysical and social issues and problems. It is driven by the need to improve understanding about such systems and to improve resource management by using the results of integrated research processes.Traditional research tends to fragment complex problems, focusing more on the pieces...

Does the Detection of Misunderstanding Lead to Its Revision?

ERIC Educational Resources Information Center

García-Rodicio, Héctor; Sánchez, Emilio

2014-01-01

When dealing with complex conceptual systems, low-prior- knowledge learners develop fragmentary and incorrect understanding. To learn complex topics deeply, these learners have to (a) monitor understanding to detect flaws and (b) generate explanations to revise and repair the flaws. In this research we explored if the detection of a flaw in…

A protocol for parameterization and calibration of RZWQM2 in field research

USDA-ARS?s Scientific Manuscript database

Use of agricultural system models in field research requires a full understanding of both the model and the system it simulates. Since the 1960s, agricultural system models have increased tremendously in their complexity due to greater understanding of the processes simulated, their application to r...

Children's and Adolescents' Thoughts on Pollution: Cognitive Abilities Required to Understand Environmental Systems

ERIC Educational Resources Information Center

Rodríguez, Manuel; Kohen, Raquel; Delval, Juan

2015-01-01

Pollution phenomena are complex systems in which different parts are integrated by means of causal and temporal relationships. To understand pollution, children must develop some cognitive abilities related to system thinking and temporal and causal inferential reasoning. These cognitive abilities constrain and guide how children understand…

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

Challenges in the analysis of complex systems: introduction and overview

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

[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.

Facilitating and Learning at the Edge of Chaos: Expanding the Context of Experiential Education.

ERIC Educational Resources Information Center

Oekerman, Carl

Significant recent discoveries within a number of scientific disciplines, collectively referred to as the science of complexity, are creating a major shift in how human beings understand the complex, adaptive systems that make up the world. A complex adaptive system consists of networks of large numbers of agents that interact with each other and…

What is New in Understanding how the Whole Works

NASA Astrophysics Data System (ADS)

San Miguel, Maxi

Cybernetics, systems science, synergetics, global systems, complexity - what is new in understanding how the whole works? There are two new opportunities that pose at least two challenges: the availability of massive data and the direct social relevance of the field of research...

Chaos, complexity and complicatedness: lessons from rocket science.

PubMed

Norman, Geoff

2011-06-01

Recently several authors have drawn parallels between educational research and some theories of natural science, in particular complexity theory and chaos theory. The central claim is that both the natural science theories are useful metaphors for education research in that they deal with phenomena that involve many variables interacting in complex, non-linear and unstable ways, and leading to effects that are neither reproducible nor comprehensible. This paper presents a counter-argument. I begin by carefully examining the concepts of uncertainty, complexity and chaos, as described in physical science. I distinguish carefully between systems that are, respectively, complex, chaotic and complicated. I demonstrate that complex and chaotic systems have highly specific characteristics that are unlikely to be present in education systems. I then suggest that, in fact, there is ample evidence that human learning can be understood adequately with conventional linear models. The implications of these opposing world views are substantial. If education science has the properties of complex or chaotic systems, we should abandon any attempt at control or understanding. However, as I point out, to do so would ignore a number of recent developments in our understanding of learning that hold promise to yield substantial improvements in effectiveness and efficiency of learning. © Blackwell Publishing Ltd 2011.

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…

The architecture of a modern military health information system.

PubMed

Mukherji, Raj J; Egyhazy, Csaba J

2004-06-01

This article describes a melding of a government-sponsored architecture for complex systems with open systems engineering architecture developed by the Institute for Electrical and Electronics Engineers (IEEE). Our experience in using these two architectures in building a complex healthcare system is described in this paper. The work described shows that it is possible to combine these two architectural frameworks in describing the systems, operational, and technical views of a complex automation system. The advantage in combining the two architectural frameworks lies in the simplicity of implementation and ease of understanding of automation system architectural elements by medical professionals.

Patterns, Probabilities, and People: Making Sense of Quantitative Change in Complex Systems

ERIC Educational Resources Information Center

Wilkerson-Jerde, Michelle Hoda; Wilensky, Uri J.

2015-01-01

The learning sciences community has made significant progress in understanding how people think and learn about complex systems. But less is known about how people make sense of the quantitative patterns and mathematical formalisms often used to study these systems. In this article, we make a case for attending to and supporting connections…

ADAM: analysis of discrete models of biological systems using computer algebra.

PubMed

Hinkelmann, Franziska; Brandon, Madison; Guang, Bonny; McNeill, Rustin; Blekherman, Grigoriy; Veliz-Cuba, Alan; Laubenbacher, Reinhard

2011-07-20

Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics.

"Structure and dynamics in complex chemical systems: Gaining new insights through recent advances in time-resolved spectroscopies.” ACS Division of Physical Chemistry Symposium presented at the Fall National ACS Meeting in Boston, MA, August 2015

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

Crawford, Daniel

8-Session Symposium on STRUCTURE AND DYNAMICS IN COMPLEX CHEMICAL SYSTEMS: GAINING NEW INSIGHTS THROUGH RECENT ADVANCES IN TIME-RESOLVED SPECTROSCOPIES. The intricacy of most chemical, biochemical, and material processes and their applications are underscored by the complex nature of the environments in which they occur. Substantial challenges for building a global understanding of a heterogeneous system include (1) identifying unique signatures associated with specific structural motifs within the heterogeneous distribution, and (2) resolving the significance of each of multiple time scales involved in both small- and large-scale nuclear reorganization. This symposium focuses on the progress in our understanding of dynamics inmore » complex systems driven by recent innovations in time-resolved spectroscopies and theoretical developments. Such advancement is critical for driving discovery at the molecular level facilitating new applications. Broad areas of interest include: Structural relaxation and the impact of structure on dynamics in liquids, interfaces, biochemical systems, materials, and other heterogeneous environments.« less

An integrative model of evolutionary covariance: a symposium on body shape in fishes.

PubMed

Walker, Jeffrey A

2010-12-01

A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).

Connected Worlds: Connecting the public with complex environmental systems

NASA Astrophysics Data System (ADS)

Uzzo, S. M.; Chen, R. S.; Downs, R. R.

2016-12-01

Among the most important concepts in environmental science learning is the structure and dynamics of coupled human and natural systems (CHANS). But the fundamental epistemology for understanding CHANS requires systems thinking, interdisciplinarity, and complexity. Although the Next Generation Science Standards mandate connecting ideas across disciplines and systems, traditional approaches to education do not provide more than superficial understanding of this concept. Informal science learning institutions have a key role in bridging gaps between the reductive nature of classroom learning and contemporary data-driven science. The New York Hall of Science, in partnership with Design I/O and Columbia University's Center for International Earth Science Information Network, has developed an approach to immerse visitors in complex human nature interactions and provide opportunities for those of all ages to elicit and notice environmental consequences of their actions. Connected Worlds is a nearly 1,000 m2 immersive, playful environment in which students learn about complexity and interconnectedness in ecosystems and how ecosystems might respond to human intervention. It engages students through direct interactions with fanciful flora and fauna within and among six biomes: desert, rainforest, grassland, mountain valley, reservoir, and wetlands, which are interconnected through stocks and flows of water. Through gestures and the manipulation of a dynamic water system, Connected Worlds enables students, teachers, and parents to experience how the ecosystems of planet Earth are connected and to observe relationships between the behavior of Earth's inhabitants and our shared world. It is also a cyberlearning platform to study how visitors notice and scaffold their understanding of complex environmental processes and the responses of these processes to human intervention, to help inform the improvement of education practices in complex environmental science.

The effect of multiple external representations (MERs) worksheets toward complex system reasoning achievement

NASA Astrophysics Data System (ADS)

Sumarno; Ibrahim, M.; Supardi, Z. A. I.

2018-03-01

The application of a systems approach to assessing biological systems provides hope for a coherent understanding of cell dynamics patterns and their relationship to plant life. This action required the reasoning about complex systems. In other sides, there were a lot of researchers who provided the proof about the instructional successions. They involved the multiple external representations which improved the biological learning. The researcher conducted an investigation using one shoot case study design which involved 30 students in proving that the MERs worksheets could affect the student's achievement of reasoning about complex system. The data had been collected based on test of reasoning about complex system and student's identification result who worked through MERs. The result showed that only partially students could achieve reasoning about system complex, but their MERs skill could support their reasoning ability of complex system. This study could bring a new hope to develop the MERs worksheet as a tool to facilitate the reasoning about complex system.

Grounding explanations in evolving, diagnostic situations

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

Developing Seventh Grade Students' Understanding of Complex Environmental Problems with Systems Tools and Representations: A Quasi-Experimental Study

ERIC Educational Resources Information Center

Doganca Kucuk, Zerrin; Saysel, Ali Kerem

2018-01-01

A systems-based classroom intervention on environmental education was designed for seventh grade students; the results were evaluated to see its impact on the development of systems thinking skills and standard science achievement and whether the systems approach is a more effective way to teach environmental issues that are dynamic and complex. A…

A method for work modeling at complex systems: towards applying information systems in family health care units.

PubMed

Jatobá, Alessandro; de Carvalho, Paulo Victor R; da Cunha, Amauri Marques

2012-01-01

Work in organizations requires a minimum level of consensus on the understanding of the practices performed. To adopt technological devices to support the activities in environments where work is complex, characterized by the interdependence among a large number of variables, understanding about how work is done not only takes an even greater importance, but also becomes a more difficult task. Therefore, this study aims to present a method for modeling of work in complex systems, which allows improving the knowledge about the way activities are performed where these activities do not simply happen by performing procedures. Uniting techniques of Cognitive Task Analysis with the concept of Work Process, this work seeks to provide a method capable of providing a detailed and accurate vision of how people perform their tasks, in order to apply information systems for supporting work in organizations.

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].

The Transfer of Abstract Principles Governing Complex Adaptive Systems

ERIC Educational Resources Information Center

Goldstone, Robert L.; Sakamoto, Yasuaki

2003-01-01

Four experiments explored participants' understanding of the abstract principles governing computer simulations of complex adaptive systems. Experiments 1, 2, and 3 showed better transfer of abstract principles across simulations that were relatively dissimilar, and that this effect was due to participants who performed relatively poorly on the…

Design of experiments (DOE) - history, concepts, and relevance to in vitro culture

USDA-ARS?s Scientific Manuscript database

Design of experiments (DOE) is a large and well-developed field for understanding and improving the performance of complex systems. Because in vitro culture systems are complex, but easily manipulated in controlled conditions, they are particularly well-suited for the application of DOE principle...

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.

Systems thinking perspectives applied to healthcare transition for youth with disabilities: a paradigm shift for practice, policy and research.

PubMed

Hamdani, Y; Jetha, A; Norman, C

2011-11-01

Healthcare transition (HCT) for youth with disabilities is a complex phenomenon influenced by multiple interacting factors, including health, personal and environmental factors. Current research on the transition to adulthood for disabled youth has primarily focused on identifying these multilevel factors to guide the development of interventions to improve the HCT process. However, little is known about how this complex array of factors interacts and contributes to successful HCT. Systems thinking provides a theoretically informed perspective that accounts for complexity and can contribute to enhanced understanding of the interactions among HCT factors. The objective of this paper is to introduce general concepts of systems thinking as applied to HCT practice and research. Several systems thinking concepts and principles are introduced and a discussion of HCT as a complex system is provided. Systems dynamics methodology is described as one systems method for conceptualizing HCT. A preliminary systems dynamics model is presented to facilitate discourse on the application of systems thinking principles to HCT practice, policy and research. An understanding of the complex interactions and patterns of relationships in HCT can assist health policy makers and practitioners in determining key areas of intervention, the impact of these interventions on the system and the potential intended and unintended consequences of change. This paper provides initial examination of applying systems thinking to inform future research and practice on HCT. © 2011 Blackwell Publishing Ltd.

Techniques for Fault Detection and Visualization of Telemetry Dependence Relationships for Root Cause Fault Analysis in Complex Systems

NASA Astrophysics Data System (ADS)

Guy, Nathaniel

This thesis explores new ways of looking at telemetry data, from a time-correlative perspective, in order to see patterns within the data that may suggest root causes of system faults. It was thought initially that visualizing an animated Pearson Correlation Coefficient (PCC) matrix for telemetry channels would be sufficient to give new understanding; however, testing showed that the high dimensionality and inability to easily look at change over time in this approach impeded understanding. Different correlative techniques, combined with the time curve visualization proposed by Bach et al (2015), were adapted to visualize both raw telemetry and telemetry data correlations. Review revealed that these new techniques give insights into the data, and an intuitive grasp of data families, which show the effectiveness of this approach for enhancing system understanding and assisting with root cause analysis for complex aerospace systems.

A framework for complexity in palliative care: A qualitative study with patients, family carers and professionals.

PubMed

Pask, Sophie; Pinto, Cathryn; Bristowe, Katherine; van Vliet, Liesbeth; Nicholson, Caroline; Evans, Catherine J; George, Rob; Bailey, Katharine; Davies, Joanna M; Guo, Ping; Daveson, Barbara A; Higginson, Irene J; Murtagh, Fliss Em

2018-06-01

Palliative care patients are often described as complex but evidence on complexity is limited. We need to understand complexity, including at individual patient-level, to define specialist palliative care, characterise palliative care populations and meaningfully compare interventions/outcomes. To explore palliative care stakeholders' views on what makes a patient more or less complex and insights on capturing complexity at patient-level. In-depth qualitative interviews, analysed using Framework analysis. Semi-structured interviews across six UK centres with patients, family, professionals, managers and senior leads, purposively sampled by experience, background, location and setting (hospital, hospice and community). 65 participants provided an understanding of complexity, which extended far beyond the commonly used physical, psychological, social and spiritual domains. Complexity included how patients interact with family/professionals, how services' respond to needs and societal perspectives on care. 'Pre-existing', 'cumulative' and 'invisible' complexity are further important dimensions to delivering effective palliative and end-of-life care. The dynamic nature of illness and needs over time was also profoundly influential. Adapting Bronfenbrenner's Ecological Systems Theory, we categorised findings into the microsystem (person, needs and characteristics), chronosystem (dynamic influences of time), mesosystem (interactions with family/health professionals), exosystem (palliative care services/systems) and macrosystem (societal influences). Stakeholders found it acceptable to capture complexity at the patient-level, with perceived benefits for improving palliative care resource allocation. Our conceptual framework encompasses additional elements beyond physical, psychological, social and spiritual domains and advances systematic understanding of complexity within the context of palliative care. This framework helps capture patient-level complexity and target resource provision in specialist palliative care.

Studying the HIT-Complexity Interchange.

PubMed

Kuziemsky, Craig E; Borycki, Elizabeth M; Kushniruk, Andre W

2016-01-01

The design and implementation of health information technology (HIT) is challenging, particularly when it is being introduced into complex settings. While complex adaptive system (CASs) can be a valuable means of understanding relationships between users, HIT and tasks, much of the existing work using CASs is descriptive in nature. This paper addresses that issue by integrating a model for analyzing task complexity with approaches for HIT evaluation and systems analysis. The resulting framework classifies HIT-user tasks and issues as simple, complicated or complex, and provides insight on how to study them.

Policy experimentation and innovation as a response to complexity in China's management of health reforms.

PubMed

Husain, Lewis

2017-08-03

There are increasing criticisms of dominant models for scaling up health systems in developing countries and a recognition that approaches are needed that better take into account the complexity of health interventions. Since Reform and Opening in the late 1970s, Chinese government has managed complex, rapid and intersecting reforms across many policy areas. As with reforms in other policy areas, reform of the health system has been through a process of trial and error. There is increasing understanding of the importance of policy experimentation and innovation in many of China's reforms; this article argues that these processes have been important in rebuilding China's health system. While China's current system still has many problems, progress is being made in developing a functioning system able to ensure broad population access. The article analyses Chinese thinking on policy experimentation and innovation and their use in management of complex reforms. It argues that China's management of reform allows space for policy tailoring and innovation by sub-national governments under a broad agreement over the ends of reform, and that shared understandings of policy innovation, alongside informational infrastructures for the systemic propagation and codification of useful practices, provide a framework for managing change in complex environments and under conditions of uncertainty in which 'what works' is not knowable in advance. The article situates China's use of experimentation and innovation in management of health system reform in relation to recent literature which applies complex systems thinking to global health, and concludes that there are lessons to be learnt from China's approaches to managing complexity in development of health systems for the benefit of the poor.

The services-oriented architecture: ecosystem services as a framework for diagnosing change in social ecological systems

Treesearch

Philip A. Loring; F. Stuart Chapin; S. Craig Gerlach

2008-01-01

Computational thinking (CT) is a way to solve problems and understand complex systems that draws on concepts fundamental to computer science and is well suited to the challenges that face researchers of complex, linked social-ecological systems. This paper explores CT's usefulness to sustainability science through the application of the services-oriented...

Energy Analysis Publications | Energy Analysis | NREL

Science.gov Websites

Systems Impact Analysis We perform impact analysis to evaluate and understand the impact of markets publications. Featured Publications Complex Systems Analysis Complex systems analysis integrates all aspects of , policies, and financing on technology uptake and the impact of new technologies on markets and policy

A Quantitative Systems Pharmacology Approach to Infer Pathways Involved in Complex Disease Phenotypes.

PubMed

Schurdak, Mark E; Pei, Fen; Lezon, Timothy R; Carlisle, Diane; Friedlander, Robert; Taylor, D Lansing; Stern, Andrew M

2018-01-01

Designing effective therapeutic strategies for complex diseases such as cancer and neurodegeneration that involve tissue context-specific interactions among multiple gene products presents a major challenge for precision medicine. Safe and selective pharmacological modulation of individual molecular entities associated with a disease often fails to provide efficacy in the clinic. Thus, development of optimized therapeutic strategies for individual patients with complex diseases requires a more comprehensive, systems-level understanding of disease progression. Quantitative systems pharmacology (QSP) is an approach to drug discovery that integrates computational and experimental methods to understand the molecular pathogenesis of a disease at the systems level more completely. Described here is the chemogenomic component of QSP for the inference of biological pathways involved in the modulation of the disease phenotype. The approach involves testing sets of compounds of diverse mechanisms of action in a disease-relevant phenotypic assay, and using the mechanistic information known for the active compounds, to infer pathways and networks associated with the phenotype. The example used here is for monogenic Huntington's disease (HD), which due to the pleiotropic nature of the mutant phenotype has a complex pathogenesis. The overall approach, however, is applicable to any complex disease.

Thiol/disulfide redox states in signaling and sensing

PubMed Central

Go, Young-Mi; Jones, Dean P.

2015-01-01

Rapid advances in redox systems biology are creating new opportunities to understand complexities of human disease and contributions of environmental exposures. New understanding of thiol-disulfide systems have occurred during the past decade as a consequence of the discoveries that thiol and disulfide systems are maintained in kinetically controlled steady-states displaced from thermodynamic equilibrium, that a widely distributed family of NADPH oxidases produces oxidants that function in cell signaling, and that a family of peroxiredoxins utilize thioredoxin as a reductant to complement the well-studied glutathione antioxidant system for peroxide elimination and redox regulation. This review focuses on thiol/disulfide redox state in biologic systems and the knowledge base available to support development of integrated redox systems biology models to better understand the function and dysfunction of thiol-disulfide redox systems. In particular, central principles have emerged concerning redox compartmentalization and utility of thiol/disulfide redox measures as indicators of physiologic function. Advances in redox proteomics show that, in addition to functioning in protein active sites and cell signaling, cysteine residues also serve as redox sensors to integrate biologic functions. These advances provide a framework for translation of redox systems biology concepts to practical use in understanding and treating human disease. Biological responses to cadmium, a widespread environmental agent, are used to illustrate the utility of these advances to the understanding of complex pleiotropic toxicities. PMID:23356510

"Unhelpfully Complex and Exceedingly Opaque": Australia's School Funding System

ERIC Educational Resources Information Center

Dowling, Andrew

2008-01-01

Australia's system of school funding is notoriously complex and difficult to understand. This article shines some light on this issue by describing clearly the processes of school funding that currently exist in Australia. It describes the steps taken by federal and state governments to provide over $30 billion each year to government and…

Challenges in Integrating a Complex Systems Computer Simulation in Class: An Educational Design Research

ERIC Educational Resources Information Center

Loke, Swee-Kin; Al-Sallami, Hesham S.; Wright, Daniel F. B.; McDonald, Jenny; Jadhav, Sheetal; Duffull, Stephen B.

2012-01-01

Complex systems are typically difficult for students to understand and computer simulations offer a promising way forward. However, integrating such simulations into conventional classes presents numerous challenges. Framed within an educational design research, we studied the use of an in-house built simulation of the coagulation network in four…

The Use of Complexity Theory and Strange Attractors to Understand and Explain Information System Development

ERIC Educational Resources Information Center

Tomasino, Arthur P.

2013-01-01

In spite of the best efforts of researchers and practitioners, Information Systems (IS) developers are having problems "getting it right". IS developments are challenged by the emergence of unanticipated IS characteristics undermining managers ability to predict and manage IS change. Because IS are complex, development formulas, best…

Focusing on the Complexity of Emotion Issues in Academic Learning: A Dynamical Component Systems Approach

ERIC Educational Resources Information Center

Eynde, Peter Op 't; Turner, Jeannine E.

2006-01-01

Understanding the interrelations among students' cognitive, emotional, motivational, and volitional processes is an emergening focus in educational psychology. A dynamical, component systems theory of emotions is presented as a promising framework to further unravel these complex interrelations. This framework considers emotions to be a process…

Structural Complexity in Linguistic Systems Research Topic 3: Mathematical Sciences

DTIC Science & Technology

2015-04-01

understanding of structure (pattern, correlation, memory , semantics , ...) observed in linguistic systems and process? On this score we believe the...on our understanding of structure (pattern, correlation, memory , semantics , ...) observed in linguistic systems and process? On this score we believe...promised to overcome these difficulties, since it gives a clear and constructive view of structure in memoryful stochastic processes. In principle, this

Predictors of Interpersonal Trust in Virtual Distributed Teams

DTIC Science & Technology

2008-09-01

understand systems that are very complex in nature . Such understanding is essential to facilitate building or maintaining operators’ mental models of the...a significant impact on overall system performance. Specifically, the level of automation that combined human generation of options with computer...and/or computer servers had a significant impact on automated system performance. Additionally, Parasuraman, Sheridan, & Wickens (2000) proposed

Surficial geological tools in fluvial geomorphology: Chapter 2

USGS Publications Warehouse

Jacobson, Robert B.; O'Connor, James E.; Oguchi, Takashi

2016-01-01

Increasingly, environmental scientists are being asked to develop an understanding of how rivers and streams have been altered by environmental stresses, whether rivers are subject to physical or chemical hazards, how they can be restored, and how they will respond to future environmental change. These questions present substantive challenges to the discipline of fluvial geomorphology, especially since decades of geomorphologic research have demonstrated the general complexity of fluvial systems. It follows from the concept of complex response that synoptic and short-term historical views of rivers will often give misleading understanding of future behavior. Nevertheless, broadly trained geomorphologists can address questions involving complex natural systems by drawing from a tool box that commonly includes the principles and methods of geology, hydrology, hydraulics, engineering, and ecology.

Pattern dynamics of the reaction-diffusion immune system.

PubMed

Zheng, Qianqian; Shen, Jianwei; Wang, Zhijie

2018-01-01

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

Health Policy and Management: in praise of political science. Comment on "On Health Policy and Management (HPAM): mind the theory-policy-practice gap".

PubMed

Hunter, David J

2015-03-12

Health systems have entered a third era embracing whole systems thinking and posing complex policy and management challenges. Understanding how such systems work and agreeing what needs to be put in place to enable them to undergo effective and sustainable change are more pressing issues than ever for policy-makers. The theory-policy-practice-gap and its four dimensions, as articulated by Chinitz and Rodwin, is acknowledged. It is suggested that insights derived from political science can both enrich our understanding of the gap and suggest what changes are needed to tackle the complex challenges facing health systems. © 2015 by Kerman University of Medical Sciences.

Early Elementary Students' Understanding of Complex Ecosystems: A Learning Progression Approach

ERIC Educational Resources Information Center

Hokayem, Hayat; Gotwals, Amelia Wenk

2016-01-01

Engaging in systemic reasoning about ecological issues is critical for early elementary students to develop future understanding of critical environmental issues such as global warming and loss of biodiversity. However, ecological issues are rarely taught in ways to highlight systemic reasoning in elementary schools. In this study, we conducted…

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…

Environmental Systems Microbiology of Contaminated Environments

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

Sayler, Gary; Hazen, Terry C.

Environmental Systems Microbiology is well positioned to move forward in dynamic complex system analysis probing new questions and developing new insight into the function, robustness and resilience in response to anthropogenic perturbations. Recent studies have demonstrated that natural bacterial communities can be used as quantitative biosensors in both groundwater and deep ocean water, predicting oil concentration from the Gulf of Mexico Deep Water Horizon spill and from groundwater at nuclear production waste sites (16, 17, 25). Since the first demonstration of catabolic gene expression in soil remediation (34) it has been clear that extension beyond organismal abundance to process andmore » function of microbial communities as a whole using the whole suite of omic tools available to the post genomic era. Metatranscriptomics have been highlighted as a prime vehicle for understanding responses to environmental drivers (35) in complex systems and with rapidly developing metabolomics, full functional understanding of complex community biogeochemical cycling is an achievable goal. Perhaps more exciting is the dynamic nature of these systems and their complex adaptive strategies that may lead to new control paradigms and emergence of new states and function in the course of a changing environment.« less

From STEM to STEAM: Toward a Human-Centered Education

NASA Technical Reports Server (NTRS)

Boy, Guy A.

2013-01-01

The 20th century was based on local linear engineering of complicated systems. We made cars, airplanes and chemical plants for example. The 21st century has opened a new basis for holistic non-linear design of complex systems, such as the Internet, air traffic management and nanotechnologies. Complexity, interconnectivity, interaction and communication are major attributes of our evolving society. But, more interestingly, we have started to understand that chaos theories may be more important than reductionism, to better understand and thrive on our planet. Systems need to be investigated and tested as wholes, which requires a cross-disciplinary approach and new conceptual principles and tools. Consequently, schools cannot continue to teach isolated disciplines based on simple reductionism. Science; Technology, Engineering, and Mathematics (STEM) should be integrated together with the Arts1 to promote creativity together with rationalization, and move to STEAM (with an "A" for Arts). This new concept emphasizes the possibility of longer-term socio-technical futures instead of short-term financial predictions that currently lead to uncontrolled economies. Human-centered design (HCD) can contribute to improving STEAM education technologies, systems and practices. HCD not only provides tools and techniques to build useful and usable things, but also an integrated approach to learning by doing, expressing and critiquing, exploring possible futures, and understanding complex systems.

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

Ab Initio and Monte Carlo Approaches For the MagnetocaloricEffect in Co- and In-Doped Ni-Mn-Ga Heusler Alloys

NASA Astrophysics Data System (ADS)

Sokolovskiy, Vladimir; Grünebohm, Anna; Buchelnikov, Vasiliy; Entel, Peter

2014-09-01

This special issue collects contributions from the participants of the "Information in Dynamical Systems and Complex Systems" workshop, which cover a wide range of important problems and new approaches that lie in the intersection of information theory and dynamical systems. The contributions include theoretical characterization and understanding of the different types of information flow and causality in general stochastic processes, inference and identification of coupling structure and parameters of system dynamics, rigorous coarse-grain modeling of network dynamical systems, and exact statistical testing of fundamental information-theoretic quantities such as the mutual information. The collective efforts reported herein reflect a modern perspective of the intimate connection between dynamical systems and information flow, leading to the promise of better understanding and modeling of natural complex systems and better/optimal design of engineering systems.

An evolving systems-based methodology for healthcare planning.

PubMed

Warwick, Jon; Bell, Gary

2007-01-01

Healthcare planning seems beset with problems at all hierarchical levels. These are caused by the 'soft' nature of many of the issues present in healthcare planning and the high levels of complexity inherent in healthcare services. There has, in recent years, been a move to utilize systems thinking ideas in an effort to gain a better understanding of the forces at work within the healthcare environment and these have had some success. This paper argues that systems-based methodologies can be further enhanced by metrication and modeling which assist in exploring the changed emergent behavior of a system resulting from management intervention. The paper describes the Holon Framework as an evolving systems-based approach that has been used to help clients understand complex systems (in the education domain) that would have application in the analysis of healthcare problems.

The way to uncover community structure with core and diversity

NASA Astrophysics Data System (ADS)

Chang, Y. F.; Han, S. K.; Wang, X. D.

2018-07-01

Communities are ubiquitous in nature and society. Individuals that share common properties often self-organize to form communities. Avoiding the shortages of computation complexity, pre-given information and unstable results in different run, in this paper, we propose a simple and efficient method to deepen our understanding of the emergence and diversity of communities in complex systems. By introducing the rational random selection, our method reveals the hidden deterministic and normal diverse community states of community structure. To demonstrate this method, we test it with real-world systems. The results show that our method could not only detect community structure with high sensitivity and reliability, but also provide instructional information about the hidden deterministic community world and the real normal diverse community world by giving out the core-community, the real-community, the tide and the diversity. Thizs is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in complex systems.

From the Director: The Joy of Science, the Courage of Research

MedlinePlus

... Dr. Zerhouni , one that combines an appreciation of biological complexity with the fearless search for scientific knowledge. ... techniques for greater understanding of the complexity of biological systems. The one thing that has driven my ...

The problem of ecological scaling in spatially complex, nonequilibrium ecological systems [chapter 3

Treesearch

Samuel A. Cushman; Jeremy Littell; Kevin McGarigal

2010-01-01

In the previous chapter we reviewed the challenges posed by spatial complexity and temporal disequilibrium to efforts to understand and predict the structure and dynamics of ecological systems. The central theme was that spatial variability in the environment and population processes fundamentally alters the interactions between species and their environments, largely...

Using multi-criteria analysis of simulation models to understand complex biological systems

Treesearch

Maureen C. Kennedy; E. David Ford

2011-01-01

Scientists frequently use computer-simulation models to help solve complex biological problems. Typically, such models are highly integrated, they produce multiple outputs, and standard methods of model analysis are ill suited for evaluating them. We show how multi-criteria optimization with Pareto optimality allows for model outputs to be compared to multiple system...

Emerging themes in the ecology and management of North American forests

Treesearch

Terry L. Sharik; William Adair; Fred A. Baker; Michael Battaglia; Emily J. Comfort; Anthony W. D' Amato; Craig Delong; R. Justin DeRose; Mark J. Ducey; Mark Harmon; Louise Levy; Jesse A. Logan; Joseph O' Brien; Brian J. Palik; Scott D. Roberts; Paul C. Rogers; Douglas J. Shinneman; Thomas Spies; Sarah L. Taylor; Christopher Woodall; Andrew Youngblood

2010-01-01

Forests are extremely complex systems that respond to an overwhelming number of biological and environmental factors, which can act singularly and in concert with each other, as exemplified by Puettmann et al. [1]. The complexity of forest systems presents an enormous challenge for forest researchers who try to deepen their understanding of the structure and function...

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.

ADAM: Analysis of Discrete Models of Biological Systems Using Computer Algebra

PubMed Central

2011-01-01

Background Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed. Results We propose a method for efficiently identifying attractors and introduce the web-based tool Analysis of Dynamic Algebraic Models (ADAM), which provides this and other analysis methods for discrete models. ADAM converts several discrete model types automatically into polynomial dynamical systems and analyzes their dynamics using tools from computer algebra. Specifically, we propose a method to identify attractors of a discrete model that is equivalent to solving a system of polynomial equations, a long-studied problem in computer algebra. Based on extensive experimentation with both discrete models arising in systems biology and randomly generated networks, we found that the algebraic algorithms presented in this manuscript are fast for systems with the structure maintained by most biological systems, namely sparseness and robustness. For a large set of published complex discrete models, ADAM identified the attractors in less than one second. Conclusions Discrete modeling techniques are a useful tool for analyzing complex biological systems and there is a need in the biological community for accessible efficient analysis tools. ADAM provides analysis methods based on mathematical algorithms as a web-based tool for several different input formats, and it makes analysis of complex models accessible to a larger community, as it is platform independent as a web-service and does not require understanding of the underlying mathematics. PMID:21774817

A perspective on the advancement of natural language processing tasks via topological analysis of complex networks. Comment on "Approaching human language with complex networks" by Cong and Liu

NASA Astrophysics Data System (ADS)

Amancio, Diego Raphael

2014-12-01

Concepts and methods of complex networks have been applied to probe the properties of a myriad of real systems [1]. The finding that written texts modeled as graphs share several properties of other completely different real systems has inspired the study of language as a complex system [2]. Actually, language can be represented as a complex network in its several levels of complexity. As a consequence, morphological, syntactical and semantical properties have been employed in the construction of linguistic networks [3]. Even the character level has been useful to unfold particular patterns [4,5]. In the review by Cong and Liu [6], the authors emphasize the need to use the topological information of complex networks modeling the various spheres of the language to better understand its origins, evolution and organization. In addition, the authors cite the use of networks in applications aiming at holistic typology and stylistic variations. In this context, I will discuss some possible directions that could be followed in future research directed towards the understanding of language via topological characterization of complex linguistic networks. In addition, I will comment the use of network models for language processing applications. Additional prospects for future practical research lines will also be discussed in this comment.

Impacting Early Childhood Teachers' Understanding of the Complexities of Place Value

ERIC Educational Resources Information Center

Cady, Jo Ann; Hopkins, Theresa M.; Price, Jamie

2014-01-01

In order to help children gain a more robust understanding of place value, teachers must understand the connections and relationships among the related concepts as well as possess knowledge of how children learn early number concepts. Unfortunately, teachers' familiarity with the base-ten number system and/or lack of an understanding of…

The New Kid on the Block: A Specialized Secretion System during Bacterial Sporulation.

PubMed

Morlot, Cécile; Rodrigues, Christopher D A

2018-02-02

The transport of proteins across the bacterial cell envelope is mediated by protein complexes called specialized secretion systems. These nanomachines exist in both Gram-positive and Gram-negative bacteria and have been categorized into different types based on their structural components and function. Interestingly, multiple studies suggest the existence of a protein complex in endospore-forming bacteria that appears to be a new type of specialized secretion system. This protein complex is called the SpoIIIA-SpoIIQ complex and is an exception to the categorical norm since it appears to be a hybrid composed of different parts from well-defined specialized secretion systems. Here we summarize and discuss the current understanding of this complex and its potential role as a specialized secretion system. Copyright © 2018 Elsevier Ltd. All rights reserved.

Root Systems Biology: Integrative Modeling across Scales, from Gene Regulatory Networks to the Rhizosphere1

PubMed Central

Hill, Kristine; Porco, Silvana; Lobet, Guillaume; Zappala, Susan; Mooney, Sacha; Draye, Xavier; Bennett, Malcolm J.

2013-01-01

Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment. PMID:24143806

The dynamics of discrete-time computation, with application to recurrent neural networks and finite state machine extraction.

PubMed

Casey, M

1996-08-15

Recurrent neural networks (RNNs) can learn to perform finite state computations. It is shown that an RNN performing a finite state computation must organize its state space to mimic the states in the minimal deterministic finite state machine that can perform that computation, and a precise description of the attractor structure of such systems is given. This knowledge effectively predicts activation space dynamics, which allows one to understand RNN computation dynamics in spite of complexity in activation dynamics. This theory provides a theoretical framework for understanding finite state machine (FSM) extraction techniques and can be used to improve training methods for RNNs performing FSM computations. This provides an example of a successful approach to understanding a general class of complex systems that has not been explicitly designed, e.g., systems that have evolved or learned their internal structure.

Realizing actual feedback control of complex network

NASA Astrophysics Data System (ADS)

Tu, Chengyi; Cheng, Yuhua

2014-06-01

In this paper, we present the concept of feedbackability and how to identify the Minimum Feedbackability Set of an arbitrary complex directed network. Furthermore, we design an estimator and a feedback controller accessing one MFS to realize actual feedback control, i.e. control the system to our desired state according to the estimated system internal state from the output of estimator. Last but not least, we perform numerical simulations of a small linear time-invariant dynamics network and a real simple food network to verify the theoretical results. The framework presented here could make an arbitrary complex directed network realize actual feedback control and deepen our understanding of complex systems.

Ecological Understanding 1: Ways of Experiencing Photosynthesis.

ERIC Educational Resources Information Center

Carlsson, Britta

2002-01-01

Investigates 10 student teachers' understanding of the different ways in which the function of the ecosystem could be experienced. Explores the functional aspects of the ecosystem using a system approach. Concludes that the idea of transformation is crucial to more complex ways of understanding photosynthesis. (Contains 62 references.) (Author/YDS)

On the Multi-Modal Object Tracking and Image Fusion Using Unsupervised Deep Learning Methodologies

NASA Astrophysics Data System (ADS)

LaHaye, N.; Ott, J.; Garay, M. J.; El-Askary, H. M.; Linstead, E.

2017-12-01

The number of different modalities of remote-sensors has been on the rise, resulting in large datasets with different complexity levels. Such complex datasets can provide valuable information separately, yet there is a bigger value in having a comprehensive view of them combined. As such, hidden information can be deduced through applying data mining techniques on the fused data. The curse of dimensionality of such fused data, due to the potentially vast dimension space, hinders our ability to have deep understanding of them. This is because each dataset requires a user to have instrument-specific and dataset-specific knowledge for optimum and meaningful usage. Once a user decides to use multiple datasets together, deeper understanding of translating and combining these datasets in a correct and effective manner is needed. Although there exists data centric techniques, generic automated methodologies that can potentially solve this problem completely don't exist. Here we are developing a system that aims to gain a detailed understanding of different data modalities. Such system will provide an analysis environment that gives the user useful feedback and can aid in research tasks. In our current work, we show the initial outputs our system implementation that leverages unsupervised deep learning techniques so not to burden the user with the task of labeling input data, while still allowing for a detailed machine understanding of the data. Our goal is to be able to track objects, like cloud systems or aerosols, across different image-like data-modalities. The proposed system is flexible, scalable and robust to understand complex likenesses within multi-modal data in a similar spatio-temporal range, and also to be able to co-register and fuse these images when needed.

Graphical Understanding of Simple Feedback Systems.

ERIC Educational Resources Information Center

Janvier, Claude; Garancon, Maurice

1989-01-01

Shows that graphs can reveal much about feedback systems that formula conceal, especially as microcomputers can provide complex graphs presented as animations and allow students to interact easily with them. Describes feedback systems, evolution of the system, and phase diagram. (YP)

Data Science in the Research Domain Criteria Era: Relevance of Machine Learning to the Study of Stress Pathology, Recovery, and Resilience

PubMed Central

Galatzer-Levy, Isaac R.; Ruggles, Kelly; Chen, Zhe

2017-01-01

Diverse environmental and biological systems interact to influence individual differences in response to environmental stress. Understanding the nature of these complex relationships can enhance the development of methods to: (1) identify risk, (2) classify individuals as healthy or ill, (3) understand mechanisms of change, and (4) develop effective treatments. The Research Domain Criteria (RDoC) initiative provides a theoretical framework to understand health and illness as the product of multiple inter-related systems but does not provide a framework to characterize or statistically evaluate such complex relationships. Characterizing and statistically evaluating models that integrate multiple levels (e.g. synapses, genes, environmental factors) as they relate to outcomes that a free from prior diagnostic benchmarks represents a challenge requiring new computational tools that are capable to capture complex relationships and identify clinically relevant populations. In the current review, we will summarize machine learning methods that can achieve these goals. PMID:29527592

Reflexivity-in-Action: How Complex Instruction Can Work for Equity in the Classroom

ERIC Educational Resources Information Center

Pescarmona, Isabella

2017-01-01

This study explores how experimenting with Complex Instruction can broaden teachers' perspectives and develop understanding of the classroom as a complex social and cultural system. It critically presents and interweaves data collected during ethnographic research, which was carried out with a group of in-service teachers, plus four workshops…

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…

Action Learning for Organizational and Systemic Development: Towards a "Both-and" Understanding of "I" and "We"

ERIC Educational Resources Information Center

Rigg, Clare

2008-01-01

In public services delivery, action learning is increasingly employed in the hope of improving capacity to address complex, multi-casual and "wicked" social issues to improve the lives of citizens. Yet the understanding of how and why action learning might have potential for enhancing organizational or systemic capability rarely goes…

Scientific Models Help Students Understand the Water Cycle

ERIC Educational Resources Information Center

Forbes, Cory; Vo, Tina; Zangori, Laura; Schwarz, Christina

2015-01-01

The water cycle is a large, complex system that encompasses ideas across the K-12 science curriculum. By the time students leave fifth grade, they should understand "that a system is a group of related parts that make up a whole and can carry out functions its individual parts cannot" and be able to describe both components and processes…

Understanding a successful obesity prevention initiative in children under 5 from a systems perspective.

PubMed

Owen, Brynle; Brown, Andrew D; Kuhlberg, Jill; Millar, Lynne; Nichols, Melanie; Economos, Christina; Allender, Steven

2018-01-01

Systems thinking represents an innovative and logical approach to understanding complexity in community-based obesity prevention interventions. We report on an approach to apply systems thinking to understand the complexity of a successful obesity prevention intervention in early childhood (children aged up to 5 years) conducted in a regional city in Victoria, Australia. A causal loop diagram (CLD) was developed to represent system elements related to a successful childhood obesity prevention intervention in early childhood. Key stakeholder interviews (n = 16) were examined retrospectively to generate purposive text data, create microstructures, and form a CLD. A CLD representing key stakeholder perceptions of a successful intervention comprised six key feedback loops explaining changes in project implementation over time. The loops described the dynamics of collaboration, network formation, community awareness, human resources, project clarity, and innovation. The CLD developed provides a replicable means to capture, evaluate and disseminate a description of the dynamic elements of a successful obesity prevention intervention in early childhood.

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.

Teaching Systems Thinking in the Context of the Water Cycle

NASA Astrophysics Data System (ADS)

Lee, Tammy D.; Gail Jones, M.; Chesnutt, Katherine

2017-06-01

Complex systems affect every part of our lives from the ecosystems that we inhabit and share with other living organisms to the systems that supply our water (i.e., water cycle). Evaluating events, entities, problems, and systems from multiple perspectives is known as a systems thinking approach. New curriculum standards have made explicit the call for teaching with a systems thinking approach in our science classrooms. However, little is known about how elementary in-service or pre-service teachers understand complex systems especially in terms of systems thinking. This mixed methods study investigated 67 elementary in-service teachers' and 69 pre-service teachers' knowledge of a complex system (e.g., water cycle) and their knowledge of systems thinking. Semi-structured interviews were conducted with a sub-sample of participants. Quantitative and qualitative analyses of content assessment data and questionnaires were conducted. Results from this study showed elementary in-service and pre-service teachers applied different levels of systems thinking from novice to intermediate. Common barriers to complete systems thinking were identified with both in-service and pre-service teachers and included identifying components and processes, recognizing multiple interactions and relationships between subsystems and hidden dimensions, and difficulty understanding the human impact on the water cycle system.

The value of mechanistic biophysical information for systems-level understanding of complex biological processes such as cytokinesis.

PubMed

Pollard, Thomas D

2014-12-02

This review illustrates the value of quantitative information including concentrations, kinetic constants and equilibrium constants in modeling and simulating complex biological processes. Although much has been learned about some biological systems without these parameter values, they greatly strengthen mechanistic accounts of dynamical systems. The analysis of muscle contraction is a classic example of the value of combining an inventory of the molecules, atomic structures of the molecules, kinetic constants for the reactions, reconstitutions with purified proteins and theoretical modeling to account for the contraction of whole muscles. A similar strategy is now being used to understand the mechanism of cytokinesis using fission yeast as a favorable model system. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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.

Modeling Patient Treatment With Medical Records: An Abstraction Hierarchy to Understand User Competencies and Needs.

PubMed

St-Maurice, Justin D; Burns, Catherine M

2017-07-28

Health care is a complex sociotechnical system. Patient treatment is evolving and needs to incorporate the use of technology and new patient-centered treatment paradigms. Cognitive work analysis (CWA) is an effective framework for understanding complex systems, and work domain analysis (WDA) is useful for understanding complex ecologies. Although previous applications of CWA have described patient treatment, due to their scope of work patients were previously characterized as biomedical machines, rather than patient actors involved in their own care. An abstraction hierarchy that characterizes patients as beings with complex social values and priorities is needed. This can help better understand treatment in a modern approach to care. The purpose of this study was to perform a WDA to represent the treatment of patients with medical records. The methods to develop this model included the analysis of written texts and collaboration with subject matter experts. Our WDA represents the ecology through its functional purposes, abstract functions, generalized functions, physical functions, and physical forms. Compared with other work domain models, this model is able to articulate the nuanced balance between medical treatment, patient education, and limited health care resources. Concepts in the analysis were similar to the modeling choices of other WDAs but combined them in as a comprehensive, systematic, and contextual overview. The model is helpful to understand user competencies and needs. Future models could be developed to model the patient's domain and enable the exploration of the shared decision-making (SDM) paradigm. Our work domain model links treatment goals, decision-making constraints, and task workflows. This model can be used by system developers who would like to use ecological interface design (EID) to improve systems. Our hierarchy is the first in a future set that could explore new treatment paradigms. Future hierarchies could model the patient as a controller and could be useful for mobile app development. ©Justin D St-Maurice, Catherine M Burns. Originally published in JMIR Human Factors (http://humanfactors.jmir.org), 28.07.2017.

Modeling Patient Treatment With Medical Records: An Abstraction Hierarchy to Understand User Competencies and Needs

PubMed Central

2017-01-01

Background Health care is a complex sociotechnical system. Patient treatment is evolving and needs to incorporate the use of technology and new patient-centered treatment paradigms. Cognitive work analysis (CWA) is an effective framework for understanding complex systems, and work domain analysis (WDA) is useful for understanding complex ecologies. Although previous applications of CWA have described patient treatment, due to their scope of work patients were previously characterized as biomedical machines, rather than patient actors involved in their own care. Objective An abstraction hierarchy that characterizes patients as beings with complex social values and priorities is needed. This can help better understand treatment in a modern approach to care. The purpose of this study was to perform a WDA to represent the treatment of patients with medical records. Methods The methods to develop this model included the analysis of written texts and collaboration with subject matter experts. Our WDA represents the ecology through its functional purposes, abstract functions, generalized functions, physical functions, and physical forms. Results Compared with other work domain models, this model is able to articulate the nuanced balance between medical treatment, patient education, and limited health care resources. Concepts in the analysis were similar to the modeling choices of other WDAs but combined them in as a comprehensive, systematic, and contextual overview. The model is helpful to understand user competencies and needs. Future models could be developed to model the patient’s domain and enable the exploration of the shared decision-making (SDM) paradigm. Conclusion Our work domain model links treatment goals, decision-making constraints, and task workflows. This model can be used by system developers who would like to use ecological interface design (EID) to improve systems. Our hierarchy is the first in a future set that could explore new treatment paradigms. Future hierarchies could model the patient as a controller and could be useful for mobile app development. PMID:28754650

Systems biology approach to bioremediation

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

Chakraborty, Romy; Wu, Cindy H.; Hazen, Terry C.

2012-06-01

Bioremediation has historically been approached as a ‘black box’ in terms of our fundamental understanding. Thus it succeeds and fails, seldom without a complete understanding of why. Systems biology is an integrated research approach to study complex biological systems, by investigating interactions and networks at the molecular, cellular, community, and ecosystem level. The knowledge of these interactions within individual components is fundamental to understanding the dynamics of the ecosystem under investigation. Finally, understanding and modeling functional microbial community structure and stress responses in environments at all levels have tremendous implications for our fundamental understanding of hydrobiogeochemical processes and the potentialmore » for making bioremediation breakthroughs and illuminating the ‘black box’.« less

Atomic switch networks as complex adaptive systems

NASA Astrophysics Data System (ADS)

Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

2018-03-01

Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

Reaction-diffusion controlled growth of complex structures

NASA Astrophysics Data System (ADS)

Noorduin, Willem; Mahadevan, L.; Aizenberg, Joanna

2013-03-01

Understanding how the emergence of complex forms and shapes in biominerals came about is both of fundamental and practical interest. Although biomineralization processes and organization strategies to give higher order architectures have been studied extensively, synthetic approaches to mimic these self-assembled structures are highly complex and have been difficult to emulate, let alone replicate. The emergence of solution patterns has been found in reaction-diffusion systems such as Turing patterns and the BZ reaction. Intrigued by this spontaneous formation of complexity we explored if similar processes can lead to patterns in the solid state. We here identify a reaction-diffusion system in which the shape of the solidified products is a direct readout of the environmental conditions. Based on insights in the underlying mechanism, we developed a toolbox of engineering strategies to deterministically sculpt patterns and shapes, and combine different morphologies to create a landscape of hierarchical multi scale-complex tectonic architectures with unprecedented levels of complexity. These findings may hold profound implications for understanding, mimicking and ultimately expanding upon nature's morphogenesis strategies, allowing the synthesis of advanced highly complex microscale materials and devices. WLN acknowledges the Netherlands Organization for Scientific Research for financial support

A Landscape Indicator Approach to the Identification and Articulation of the Ecological Consequences of Land Cover Change in the Chesapeake Bay Watershed, 1970-2000

USGS Publications Warehouse

Slonecker, Terrence

2008-01-01

The advancement of geographic science in the area of land surface status and trends and land cover change is at the core of the current geographic scientific research of the U.S. Geological Survey (USGS) (McMahon and others, 2005). Perhaps the least developed or articulated aspects of USGS land change science have been the identification and analysis of the ecological consequences of land cover change. Changes in land use and land cover significantly affect the ability of ecosystems to provide essential ecological goods and services, which, in turn, affect the economic, public health, and social benefits that these ecosystems provide. One of the great scientific challenges for geographic science is to understand and calibrate the effects of land use and land cover change and the complex interaction between human and biotic systems at a variety of natural, geographic, and political scales. Understanding the dynamics of land surface change requires an increased understanding of the complex nature of human-environmental systems and will require a suite of scientific tools that include traditional geographic data and analysis methods, such as remote sensing and geographic information systems (GIS), as well as innovative approaches to understanding the dynamics of complex systems. One such approach that has gained much recent scientific attention is the landscape indicator, or landscape assessment, approach, which has been developed with the emergence of the science of landscape ecology.

Renal Tumor Anatomic Complexity: Clinical Implications for Urologists.

PubMed

Joshi, Shreyas S; Uzzo, Robert G

2017-05-01

Anatomic tumor complexity can be objectively measured and reported using nephrometry. Various scoring systems have been developed in an attempt to correlate tumor complexity with intraoperative and postoperative outcomes. Nephrometry may also predict tumor biology in a noninvasive, reproducible manner. Other scoring systems can help predict surgical complexity and the likelihood of complications, independent of tumor characteristics. The accumulated data in this new field provide provocative evidence that objectifying anatomic complexity can consolidate reporting mechanisms and improve metrics of comparisons. Further prospective validation is needed to understand the full descriptive and predictive ability of the various nephrometry scores. Copyright © 2017 Elsevier Inc. All rights reserved.

The 1990 update to strategy for exploration of the inner planets

NASA Technical Reports Server (NTRS)

Esposito, Larry W.; Pepin, Robert O.; Cheng, Andrew F.; Jakosky, Bruce M.; Lunine, Jonathan I.; Mcfadden, Lucy-Ann; Mckay, Christopher P.; Mckinnon, William B.; Muhleman, Duane O.; Nicholson, Philip

1990-01-01

The Committee on Planetary and Lunar Exploration (COMPLEX) has undertaken to review and revise the 1978 report Strategy for Exploration of the Inner Planets, 1977-1987. The committee has found the 1978 report to be generally still pertinent. COMPLEX therefore issues its new report in the form of an update. The committee reaffirms the basic objectives for exploration of the planets: to determine the present state of the planets and their satellites, to understand the processes active now and at the origin of the solar system, and to understand planetary evolution, including appearance of life and its relation to the chemical history of the solar system.

Do endothelial cells dream of eclectic shape?

PubMed

Bentley, Katie; Philippides, Andrew; Ravasz Regan, Erzsébet

2014-04-28

Endothelial cells (ECs) exhibit dramatic plasticity of form at the single- and collective-cell level during new vessel growth, adult vascular homeostasis, and pathology. Understanding how, when, and why individual ECs coordinate decisions to change shape, in relation to the myriad of dynamic environmental signals, is key to understanding normal and pathological blood vessel behavior. However, this is a complex spatial and temporal problem. In this review we show that the multidisciplinary field of Adaptive Systems offers a refreshing perspective, common biological language, and straightforward toolkit that cell biologists can use to untangle the complexity of dynamic, morphogenetic systems. Copyright © 2014 Elsevier Inc. All rights reserved.

A molecular signaling approach to linking intraspecific variation and macro-evolutionary patterns.

PubMed

Swanson, Eli M; Snell-Rood, Emilie C

2014-11-01

Macro-evolutionary comparisons are a valued tool in evolutionary biology. Nevertheless, our understanding of how systems involved in molecular signaling change in concert with phenotypic diversification has lagged. We argue that integrating our understanding of the evolution of molecular signaling systems with phylogenetic comparative methods is an important step toward understanding the processes linking variation among individuals with variation among species. Focusing mostly on the endocrine system, we discuss how the complexity and mechanistic nature of molecular signaling systems may influence the application and interpretation of macro-evolutionary comparisons. We also detail five hypotheses concerning the role that physiological mechanisms can play in shaping macro-evolutionary patterns, and discuss ways in which these hypotheses could influence phenotypic diversification. Finally, we review a series of tools able to analyze the complexity of physiological systems and the way they change in concert with the phenotypes for which they coordinate development. © The Author 2014. 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.

Towards systemic theories in biological psychiatry.

PubMed

Bender, W; Albus, M; Möller, H-J; Tretter, F

2006-02-01

Although still rather controversial, empirical data on the neurobiology of schizophrenia have reached a degree of complexity that makes it hard to obtain a coherent picture of the malfunctions of the brain in schizophrenia. Theoretical neuropsychiatry should therefore use the tools of theoretical sciences like cybernetics, informatics, computational neuroscience or systems science. The methodology of systems science permits the modeling of complex dynamic nonlinear systems. Such procedures might help us to understand brain functions and the disorders and actions of psychiatric drugs better.

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.

CASE STUDY RESEARCH: THE VIEW FROM COMPLEXITY SCIENCE

PubMed Central

Anderson, Ruth; Crabtree, Benjamin F.; Steele, David J.; McDaniel, Reuben R.

2005-01-01

Many wonder why there has been so little change in care quality, despite substantial quality improvement efforts. Questioning why current approaches are not making true changes draws attention to the organization as a source of answers. We bring together the case study method and complexity science to suggest new ways to study health care organizations. The case study provides a method for studying systems. Complexity theory suggests that keys to understanding the system are contained in patterns of relationships and interactions among the system’s agents. We propose some of the “objects” of study that are implicated by complexity theory and discuss how studying these using case methods may provide useful maps of the system. We offer complexity theory, partnered with case study method, as a place to begin the daunting task of studying a system as an integrated whole. PMID:15802542

Complex adaptive systems and their relevance for nursing: An evolutionary concept analysis.

PubMed

Notarnicola, Ippolito; Petrucci, Cristina; De Jesus Barbosa, Maria Rosimar; Giorgi, Fabio; Stievano, Alessandro; Rocco, Gennaro; Lancia, Loreto

2017-06-01

This study aimed to analyse the concept of "complex adaptive systems." The construct is still nebulous in the literature, and a further explanation of the idea is needed to have a shared knowledge of it. A concept analysis was conducted utilizing Rodgers evolutionary method. The inclusive years of bibliographic search started from 2005 to 2015. The search was conducted at PubMed©, CINAHL© (EBSCO host©), Scopus©, Web of Science©, and Academic Search Premier©. Retrieved papers were critically analysed to explore the attributes, antecedents, and consequences of the concept. Moreover, surrogates, related terms, and a pattern recognition scheme were identified. The concept analysis showed that complex systems are adaptive and have the ability to process information. They can adapt to the environment and consequently evolve. Nursing is a complex adaptive system, and the nursing profession in practice exhibits complex adaptive system characteristics. Complexity science through complex adaptive systems provides new ways of seeing and understanding the mechanisms that underpin the nursing profession. © 2017 John Wiley & Sons Australia, Ltd.

A Framework for Understanding and Generating Integrated Solutions for Residential Peak Energy Demand

PubMed Central

Buys, Laurie; Vine, Desley; Ledwich, Gerard; Bell, John; Mengersen, Kerrie; Morris, Peter; Lewis, Jim

2015-01-01

Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times. PMID:25807384

A framework for understanding and generating integrated solutions for residential peak energy demand.

PubMed

Buys, Laurie; Vine, Desley; Ledwich, Gerard; Bell, John; Mengersen, Kerrie; Morris, Peter; Lewis, Jim

2015-01-01

Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times.

Automated reverse engineering of nonlinear dynamical systems

PubMed Central

Bongard, Josh; Lipson, Hod

2007-01-01

Complex nonlinear dynamics arise in many fields of science and engineering, but uncovering the underlying differential equations directly from observations poses a challenging task. The ability to symbolically model complex networked systems is key to understanding them, an open problem in many disciplines. Here we introduce for the first time a method that can automatically generate symbolic equations for a nonlinear coupled dynamical system directly from time series data. This method is applicable to any system that can be described using sets of ordinary nonlinear differential equations, and assumes that the (possibly noisy) time series of all variables are observable. Previous automated symbolic modeling approaches of coupled physical systems produced linear models or required a nonlinear model to be provided manually. The advance presented here is made possible by allowing the method to model each (possibly coupled) variable separately, intelligently perturbing and destabilizing the system to extract its less observable characteristics, and automatically simplifying the equations during modeling. We demonstrate this method on four simulated and two real systems spanning mechanics, ecology, and systems biology. Unlike numerical models, symbolic models have explanatory value, suggesting that automated “reverse engineering” approaches for model-free symbolic nonlinear system identification may play an increasing role in our ability to understand progressively more complex systems in the future. PMID:17553966

Automated reverse engineering of nonlinear dynamical systems.

PubMed

Bongard, Josh; Lipson, Hod

2007-06-12

Complex nonlinear dynamics arise in many fields of science and engineering, but uncovering the underlying differential equations directly from observations poses a challenging task. The ability to symbolically model complex networked systems is key to understanding them, an open problem in many disciplines. Here we introduce for the first time a method that can automatically generate symbolic equations for a nonlinear coupled dynamical system directly from time series data. This method is applicable to any system that can be described using sets of ordinary nonlinear differential equations, and assumes that the (possibly noisy) time series of all variables are observable. Previous automated symbolic modeling approaches of coupled physical systems produced linear models or required a nonlinear model to be provided manually. The advance presented here is made possible by allowing the method to model each (possibly coupled) variable separately, intelligently perturbing and destabilizing the system to extract its less observable characteristics, and automatically simplifying the equations during modeling. We demonstrate this method on four simulated and two real systems spanning mechanics, ecology, and systems biology. Unlike numerical models, symbolic models have explanatory value, suggesting that automated "reverse engineering" approaches for model-free symbolic nonlinear system identification may play an increasing role in our ability to understand progressively more complex systems in the future.

Making a Map of Science: General Systems Theory as a Conceptual Framework for Tertiary Science Education.

ERIC Educational Resources Information Center

Gulyaev, Sergei A.; Stonyer, Heather R.

2002-01-01

Develops an integrated approach based on the use of general systems theory (GST) and the concept of 'mapping' scientific knowledge to provide students with tools for a more holistic understanding of science. Uses GST as the core methodology for understanding science and its complexity. Discusses the role of scientific community in producing…

Design Experiments: Developing and Testing an Intervention for Elementary School-Age Students Who Use Non-Mainstream American English Dialects

ERIC Educational Resources Information Center

Thomas-Tate, Shurita; Connor, Carol McDonald; Johnson, Lakeisha

2013-01-01

Reading comprehension, defined as the active extraction and construction of meaning from all kinds of text, requires children to fluently decode and understand what they are reading. Basic processes underlying reading comprehension are complex and call on the oral language system and a conscious understanding of this system, i.e., metalinguistic…

Undergraduate Students' Mental Models of the Climate System

ERIC Educational Resources Information Center

Mehta, Jignesh

2017-01-01

The climate, being a complex system, is difficult for people to understand. If better education is to be designed to improve the public's understanding of the subject, educators must be aware of the prior knowledge that students bring with them to the classroom since it is through that prism that people make sense of the world. As such, the aim of…

Lessons Learned in Systemic District Reform: A Cross-District Analysis from the Comprehensive Aligned Instructional System (CAIS) Benchmarking Study

ERIC Educational Resources Information Center

Waters, Louise Bay; Vargo, Merrill

2008-01-01

Urban district reform has been hampered by the challenge of understanding and supporting the tremendous complexity of district change. Improving this understanding through actionable, practice-based research is the purpose of this study. The authors began the study with the hypothesis that achieving districts both align their instructional systems…

Revisiting the Blended Learning Literature: Using a Complex Adaptive Systems Framework

ERIC Educational Resources Information Center

Wang, Yuping; Han, Xibin; Yang, Juan

2015-01-01

This research has two aims: (1) to bridge a gap in blended learning research--the lack of a systems approach to the understanding of blended learning research and practice, and (2) to promote a more comprehensive understanding of what has been achieved and what needs to be achieved in blended learning research and practice. To achieve these aims,…

Integrated Safety Analysis Teams

NASA Technical Reports Server (NTRS)

Wetherholt, Jonathan C.

2008-01-01

Today's complex systems require understanding beyond one person s capability to comprehend. Each system requires a team to divide the system into understandable subsystems which can then be analyzed with an Integrated Hazard Analysis. The team must have both specific experiences and diversity of experience. Safety experience and system understanding are not always manifested in one individual. Group dynamics make the difference between success and failure as well as the difference between a difficult task and a rewarding experience. There are examples in the news which demonstrate the need to connect the pieces of a system into a complete picture. The Columbia disaster is now a standard example of a low consequence hazard in one part of the system; the External Tank is a catastrophic hazard cause for a companion subsystem, the Space Shuttle Orbiter. The interaction between the hardware, the manufacturing process, the handling, and the operations contributed to the problem. Each of these had analysis performed, but who constituted the team which integrated this analysis together? This paper will explore some of the methods used for dividing up a complex system; and how one integration team has analyzed the parts. How this analysis has been documented in one particular launch space vehicle case will also be discussed.

Brain evolution by brain pathway duplication

PubMed Central

Chakraborty, Mukta; Jarvis, Erich D.

2015-01-01

Understanding the mechanisms of evolution of brain pathways for complex behaviours is still in its infancy. Making further advances requires a deeper understanding of brain homologies, novelties and analogies. It also requires an understanding of how adaptive genetic modifications lead to restructuring of the brain. Recent advances in genomic and molecular biology techniques applied to brain research have provided exciting insights into how complex behaviours are shaped by selection of novel brain pathways and functions of the nervous system. Here, we review and further develop some insights to a new hypothesis on one mechanism that may contribute to nervous system evolution, in particular by brain pathway duplication. Like gene duplication, we propose that whole brain pathways can duplicate and the duplicated pathway diverge to take on new functions. We suggest that one mechanism of brain pathway duplication could be through gene duplication, although other mechanisms are possible. We focus on brain pathways for vocal learning and spoken language in song-learning birds and humans as example systems. This view presents a new framework for future research in our understanding of brain evolution and novel behavioural traits. PMID:26554045

Learning To Live with Complexity.

ERIC Educational Resources Information Center

Dosa, Marta

Neither the design of information systems and networks nor the delivery of library services can claim true user centricity without an understanding of the multifaceted psychological environment of users and potential users. The complexity of the political process, social problems, challenges to scientific inquiry, entrepreneurship, and…

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

Complexity versus certainty in understanding species’ declines

USGS Publications Warehouse

Sundstrom, Shana M.; Allen, Craig R.

2014-01-01

Traditional approaches to predict species declines (e.g. government processes or IUCN Red Lists), may be too simplistic and may therefore misguide management and conservation. Using complex systems approaches that account for scale-specific patterns and processes have the potential to overcome these limitations.

Simple processes drive unpredictable differences in estuarine fish assemblages: Baselines for understanding site-specific ecological and anthropogenic impacts

NASA Astrophysics Data System (ADS)

Sheaves, Marcus

2016-03-01

Predicting patterns of abundance and composition of biotic assemblages is essential to our understanding of key ecological processes, and our ability to monitor, evaluate and manage assemblages and ecosystems. Fish assemblages often vary from estuary to estuary in apparently unpredictable ways, making it challenging to develop a general understanding of the processes that determine assemblage composition. This makes it problematic to transfer understanding from one estuary situation to another and therefore difficult to assemble effective management plans or to assess the impacts of natural and anthropogenic disturbance. Although system-to-system variability is a common property of ecological systems, rather than being random it is the product of complex interactions of multiple causes and effects at a variety of spatial and temporal scales. I investigate the drivers of differences in estuary fish assemblages, to develop a simple model explaining the diversity and complexity of observed estuary-to-estuary differences, and explore its implications for management and conservation. The model attributes apparently unpredictable differences in fish assemblage composition from estuary to estuary to the interaction of species-specific, life history-specific and scale-specific processes. In explaining innate faunal differences among estuaries without the need to invoke complex ecological or anthropogenic drivers, the model provides a baseline against which the effects of additional natural and anthropogenic factors can be evaluated.

Reliability analysis in interdependent smart grid systems

NASA Astrophysics Data System (ADS)

Peng, Hao; Kan, Zhe; Zhao, Dandan; Han, Jianmin; Lu, Jianfeng; Hu, Zhaolong

2018-06-01

Complex network theory is a useful way to study many real complex systems. In this paper, a reliability analysis model based on complex network theory is introduced in interdependent smart grid systems. In this paper, we focus on understanding the structure of smart grid systems and studying the underlying network model, their interactions, and relationships and how cascading failures occur in the interdependent smart grid systems. We propose a practical model for interdependent smart grid systems using complex theory. Besides, based on percolation theory, we also study the effect of cascading failures effect and reveal detailed mathematical analysis of failure propagation in such systems. We analyze the reliability of our proposed model caused by random attacks or failures by calculating the size of giant functioning components in interdependent smart grid systems. Our simulation results also show that there exists a threshold for the proportion of faulty nodes, beyond which the smart grid systems collapse. Also we determine the critical values for different system parameters. In this way, the reliability analysis model based on complex network theory can be effectively utilized for anti-attack and protection purposes in interdependent smart grid systems.

The reconstruction of narrative identity during mental health recovery: a complex adaptive systems perspective.

PubMed

Kerr, Douglas J R; Crowe, Trevor P; Oades, Lindsay G

2013-06-01

1) to understand the reconstruction of narrative identity during mental health recovery using a complex adaptive systems perspective, 2) to address the need for alternative approaches that embrace the complexities of health care. A narrative review of published literature was conducted. A complex adaptive systems perspective offers a framework and language that can assist individuals to make sense of their experiences and reconstruct their narratives during an often erratic and uncertain life transition. It is a novel research direction focused on a critical area of recovery and addresses the need for alternative approaches that embrace the complexities of health care. A complexity research approach to narrative identity reconstruction is valuable. It is an accessible model for addressing the complexities of recovery and may underpin the development of simple, practical recovery coaching tools. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Hierarchical coordinate systems for understanding complexity and its evolution, with applications to genetic regulatory networks.

PubMed

Egri-Nagy, Attila; Nehaniv, Chrystopher L

2008-01-01

Beyond complexity measures, sometimes it is worthwhile in addition to investigate how complexity changes structurally, especially in artificial systems where we have complete knowledge about the evolutionary process. Hierarchical decomposition is a useful way of assessing structural complexity changes of organisms modeled as automata, and we show how recently developed computational tools can be used for this purpose, by computing holonomy decompositions and holonomy complexity. To gain insight into the evolution of complexity, we investigate the smoothness of the landscape structure of complexity under minimal transitions. As a proof of concept, we illustrate how the hierarchical complexity analysis reveals symmetries and irreversible structure in biological networks by applying the methods to the lac operon mechanism in the genetic regulatory network of Escherichia coli.

Using an Adaptive Expertise Lens to Understand the Quality of Teachers' Classroom Implementation of Computer-Supported Complex Systems Curricula in High School Science

ERIC Educational Resources Information Center

Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

2015-01-01

Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to…

Feedback (F) Fueling Adaptation (A) Network Growth (N) and Self-Organization (S): A Complex Systems Design and Evaluation Approach to Professional Development

ERIC Educational Resources Information Center

Yoon, Susan A.; Klopfer, Eric

2006-01-01

This paper reports on the efficacy of a professional development framework premised on four complex systems design principles: Feedback, Adaptation, Network Growth and Self-organization (FANS). The framework is applied to the design and delivery of the first 2 years of a 3-year study aimed at improving teacher and student understanding of…

Conveying the Complex: Updating U.S. Joint Systems Analysis Doctrine with Complexity Theory

DTIC Science & Technology

2013-12-10

screech during a public address, or sustain and amplify it during a guitar solo. Since the systems are nonlinear, understanding cause and effect... Classics , 2007), 12. 34 those frames.58 A technique to cope with the potentially confusing...Reynolds, Paul Davidson. A Primer in Theory Construction. Boston: Allyn and Bacon Classics , 2007. Riolo, Rick L. “The Effects and Evolution of Tag

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

EPA Science Inventory

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

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

Search for organising principles: understanding in systems biology.

PubMed

Mesarovic, M D; Sreenath, S N; Keene, J D

2004-06-01

Due in large measure to the explosive progress in molecular biology, biology has become arguably the most exciting scientific field. The first half of the 21st century is sometimes referred to as the 'era of biology', analogous to the first half of the 20th century, which was considered to be the 'era of physics'. Yet, biology is facing a crisis--or is it an opportunity--reminiscent of the state of biology in pre-double-helix time. The principal challenge facing systems biology is complexity. According to Hood, 'Systems biology defines and analyses the interrelationships of all of the elements in a functioning system in order to understand how the system works.' With 30000+ genes in the human genome the study of all relationships simultaneously becomes a formidably complex problem. Hanahan and Weinberg raised the question as to whether progress will consist of 'adding further layers of complexity to a scientific literature that is already complex almost beyond measure' or whether the progress will lead to a 'science with a conceptual structure and logical coherence that rivals that of chemistry or physics.' At the core of the challenge is the need for a new approach, a shift from reductionism to a holistic perspective. However, more than just a pronouncement of a new approach is needed. We suggest that what is needed is to provide a conceptual framework for systems biology research. We propose that the concept of a complex system, i.e. a system of systems as defined in mathematical general systems theory (MGST), is central to provide such a framework. We further argue that for a deeper understanding in systems biology investigations should go beyond building numerical mathematical or computer models--important as they are. Biological phenomena cannot be predicted with the level of numerical precision as in classical physics. Explanations in terms of how the categories of systems are organised to function in ever changing conditions are more revealing. Non-numerical mathematical tools are appropriate for the task. Such a categorical perspective led us to propose that the core of understanding in systems biology depends on the search for organising principles rather than solely on construction of predictive descriptions (i.e. models) that exactly outline the evolution of systems in space and time. The search for organising principles requires an identification/discovery of new concepts and hypotheses. Some of them, such as coordination motifs for transcriptional regulatory networks and bounded autonomy of levccels in a hierarchy, are outlined in this article. Experimental designs are outlined to help verify the applicability of the interaction balance principle of coordination to transcriptional and posttranscriptional networks.

Reading, Complexity and the Brain

ERIC Educational Resources Information Center

Goswami, Usha

2008-01-01

Brain imaging offers a new technology for understanding the acquisition of reading by children. It can contribute novel evidence concerning the key mechanisms supporting reading, and the brain systems that are involved. The extensive neural architecture that develops to support efficient reading testifies to the complex developmental processes…

A probabilistic process model for pelagic marine ecosystems informed by Bayesian inverse analysis

EPA Science Inventory

Marine ecosystems are complex systems with multiple pathways that produce feedback cycles, which may lead to unanticipated effects. Models abstract this complexity and allow us to predict, understand, and hypothesize. In ecological models, however, the paucity of empirical data...

Understanding the complexity of redesigning care around the clinical microsystem.

PubMed

Barach, P; Johnson, J K

2006-12-01

The microsystem is an organizing design construct in which social systems cut across traditional discipline boundaries. Because of its interdisciplinary focus, the clinical microsystem provides a conceptual and practical framework for simplifying complex organizations that deliver care. It also provides an important opportunity for organizational learning. Process mapping and microworld simulation may be especially useful for redesigning care around the microsystem concept. Process mapping, in which the core processes of the microsystem are delineated and assessed from the perspective of how the individual interacts with the system, is an important element of the continuous learning cycle of the microsystem and the healthcare organization. Microworld simulations are interactive computer based models that can be used as an experimental platform to test basic questions about decision making misperceptions, cause-effect inferences, and learning within the clinical microsystem. Together these tools offer the user and organization the ability to understand the complexity of healthcare systems and to facilitate the redesign of optimal outcomes.

Soft System Methodology as a Tool to Understand Issues of Governmental Affordable Housing Programme of India: A Case Study Approach

NASA Astrophysics Data System (ADS)

Ghosh, Sukanya; Roy, Souvanic; Sanyal, Manas Kumar

2016-09-01

With the help of a case study, the article has explored current practices of implementation of governmental affordable housing programme for urban poor in a slum of India. This work shows that the issues associated with the problems of governmental affordable housing programme has to be addressed to with a suitable methodology as complexities are not only dealing with quantitative data but qualitative data also. The Hard System Methodologies (HSM), which is conventionally applied to address the issues, deals with real and known problems which can be directly solved. Since most of the issues of affordable housing programme as found in the case study are subjective and complex in nature, Soft System Methodology (SSM) has been tried for better representation from subjective points of views. The article explored drawing of Rich Picture as an SSM approach for better understanding and analysing complex issues and constraints of affordable housing programme so that further exploration of the issues is possible.

Exploring the practicing-connections hypothesis: using gesture to support coordination of ideas in understanding a complex statistical concept.

PubMed

Son, Ji Y; Ramos, Priscilla; DeWolf, Melissa; Loftus, William; Stigler, James W

2018-01-01

In this article, we begin to lay out a framework and approach for studying how students come to understand complex concepts in rich domains. Grounded in theories of embodied cognition, we advance the view that understanding of complex concepts requires students to practice, over time, the coordination of multiple concepts, and the connection of this system of concepts to situations in the world. Specifically, we explore the role that a teacher's gesture might play in supporting students' coordination of two concepts central to understanding in the domain of statistics: mean and standard deviation. In Study 1 we show that university students who have just taken a statistics course nevertheless have difficulty taking both mean and standard deviation into account when thinking about a statistical scenario. In Study 2 we show that presenting the same scenario with an accompanying gesture to represent variation significantly impacts students' interpretation of the scenario. Finally, in Study 3 we present evidence that instructional videos on the internet fail to leverage gesture as a means of facilitating understanding of complex concepts. Taken together, these studies illustrate an approach to translating current theories of cognition into principles that can guide instructional design.

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

Developing a framework for qualitative engineering: Research in design and analysis of complex structural systems

NASA Technical Reports Server (NTRS)

Franck, Bruno M.

1990-01-01

The research is focused on automating the evaluation of complex structural systems, whether for the design of a new system or the analysis of an existing one, by developing new structural analysis techniques based on qualitative reasoning. The problem is to identify and better understand: (1) the requirements for the automation of design, and (2) the qualitative reasoning associated with the conceptual development of a complex system. The long-term objective is to develop an integrated design-risk assessment environment for the evaluation of complex structural systems. The scope of this short presentation is to describe the design and cognition components of the research. Design has received special attention in cognitive science because it is now identified as a problem solving activity that is different from other information processing tasks (1). Before an attempt can be made to automate design, a thorough understanding of the underlying design theory and methodology is needed, since the design process is, in many cases, multi-disciplinary, complex in size and motivation, and uses various reasoning processes involving different kinds of knowledge in ways which vary from one context to another. The objective is to unify all the various types of knowledge under one framework of cognition. This presentation focuses on the cognitive science framework that we are using to represent the knowledge aspects associated with the human mind's abstraction abilities and how we apply it to the engineering knowledge and engineering reasoning in design.

Using an adaptive expertise lens to understand the quality of teachers' classroom implementation of computer-supported complex systems curricula in high school science

NASA Astrophysics Data System (ADS)

Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

2015-05-01

Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to better understand teachers' classroom practices as they attempt to navigate myriad variables in the implementation of biology units that include working with computer simulations, and learning about and teaching through complex systems ideas. Sample: Research participants were three high school biology teachers, two females and one male, ranging in teaching experience from six to 16 years. Their teaching contexts also ranged in student achievement from 14-47% advanced science proficiency. Design and methods: We used a holistic multiple case study methodology and collected data during the 2011-2012 school year. Data sources include classroom observations, teacher and student surveys, and interviews. Data analyses and trustworthiness measures were conducted through qualitative mining of data sources and triangulation of findings. Results: We illustrate the characteristics of adaptive expertise of more or less successful teaching and learning when implementing complex systems curricula. We also demonstrate differences between case study teachers in terms of particular variables associated with adaptive expertise. Conclusions: This research contributes to scholarship on practices and professional development needed to better support teachers to teach through a complex systems pedagogical and curricular approach.

Continuous whole-system monitoring toward rapid understanding of production HPC applications and systems

DOE PAGES

Agelastos, Anthony; Allan, Benjamin; Brandt, Jim; ...

2016-05-18

A detailed understanding of HPC applications’ resource needs and their complex interactions with each other and HPC platform resources are critical to achieving scalability and performance. Such understanding has been difficult to achieve because typical application profiling tools do not capture the behaviors of codes under the potentially wide spectrum of actual production conditions and because typical monitoring tools do not capture system resource usage information with high enough fidelity to gain sufficient insight into application performance and demands. In this paper we present both system and application profiling results based on data obtained through synchronized system wide monitoring onmore » a production HPC cluster at Sandia National Laboratories (SNL). We demonstrate analytic and visualization techniques that we are using to characterize application and system resource usage under production conditions for better understanding of application resource needs. Furthermore, our goals are to improve application performance (through understanding application-to-resource mapping and system throughput) and to ensure that future system capabilities match their intended workloads.« less

Experiments on Lunar Core Composition: Phase Equilibrium Analysis of A Multi-Element (Fe-Ni-S-C) System

NASA Technical Reports Server (NTRS)

Go, B. M.; Righter, K.; Danielson, L.; Pando, K.

2015-01-01

Previous geochemical and geophysical experiments have proposed the presence of a small, metallic lunar core, but its composition is still being investigated. Knowledge of core composition can have a significant effect on understanding the thermal history of the Moon, the conditions surrounding the liquid-solid or liquid-liquid field, and siderophile element partitioning between mantle and core. However, experiments on complex bulk core compositions are very limited. One limitation comes from numerous studies that have only considered two or three element systems such as Fe-S or Fe-C, which do not supply a comprehensive understanding for complex systems such as Fe-Ni-S-Si-C. Recent geophysical data suggests the presence of up to 6% lighter elements. Reassessments of Apollo seismological analyses and samples have also shown the need to acquire more data for a broader range of pressures, temperatures, and compositions. This study considers a complex multi-element system (Fe-Ni-S-C) for a relevant pressure and temperature range to the Moon's core conditions.

Development of a Systems Science Curriculum to Engage Rural African American Teens in Understanding and Addressing Childhood Obesity Prevention

ERIC Educational Resources Information Center

Frerichs, Leah; Lich, Kristen Hassmiller; Young, Tiffany L.; Dave, Gaurav; Stith, Doris; Corbie-Smith, Giselle

2018-01-01

Engaging youth from racial and ethnic minority communities as leaders for change is a potential strategy to mobilize support for addressing childhood obesity, but there are limited curricula designed to help youth understand the complex influences on obesity. Our aim was to develop and pilot test a systems science curriculum to elicit rural…

Synthetic biology: insights into biological computation.

PubMed

Manzoni, Romilde; Urrios, Arturo; Velazquez-Garcia, Silvia; de Nadal, Eulàlia; Posas, Francesc

2016-04-18

Organisms have evolved a broad array of complex signaling mechanisms that allow them to survive in a wide range of environmental conditions. They are able to sense external inputs and produce an output response by computing the information. Synthetic biology attempts to rationally engineer biological systems in order to perform desired functions. Our increasing understanding of biological systems guides this rational design, while the huge background in electronics for building circuits defines the methodology. In this context, biocomputation is the branch of synthetic biology aimed at implementing artificial computational devices using engineered biological motifs as building blocks. Biocomputational devices are defined as biological systems that are able to integrate inputs and return outputs following pre-determined rules. Over the last decade the number of available synthetic engineered devices has increased exponentially; simple and complex circuits have been built in bacteria, yeast and mammalian cells. These devices can manage and store information, take decisions based on past and present inputs, and even convert a transient signal into a sustained response. The field is experiencing a fast growth and every day it is easier to implement more complex biological functions. This is mainly due to advances in in vitro DNA synthesis, new genome editing tools, novel molecular cloning techniques, continuously growing part libraries as well as other technological advances. This allows that digital computation can now be engineered and implemented in biological systems. Simple logic gates can be implemented and connected to perform novel desired functions or to better understand and redesign biological processes. Synthetic biological digital circuits could lead to new therapeutic approaches, as well as new and efficient ways to produce complex molecules such as antibiotics, bioplastics or biofuels. Biological computation not only provides possible biomedical and biotechnological applications, but also affords a greater understanding of biological systems.

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…

Holistic School Leadership: Systems Thinking as an Instructional Leadership Enabler

ERIC Educational Resources Information Center

Shaked, Haim; Schechter, Chen

2016-01-01

As instructional leadership involves attempts to understand and improve complex systems, this study explored principals' perceptions regarding possible contributions of systems thinking to instructional leadership. Based on a qualitative analysis, systems thinking was perceived by middle and high school principals to contribute to the following…

A Telecommunications Industry Primer: A Systems Model.

ERIC Educational Resources Information Center

Obermier, Timothy R.; Tuttle, Ronald H.

2003-01-01

Describes the Telecommunications Systems Model to help technical educators and students understand the increasingly complex telecommunications infrastructure. Specifically looks at ownership and regulatory status, service providers, transport medium, network protocols, and end-user services. (JOW)

Systems Biology Perspectives on Minimal and Simpler Cells

PubMed Central

Xavier, Joana C.; Patil, Kiran Raosaheb

2014-01-01

SUMMARY The concept of the minimal cell has fascinated scientists for a long time, from both fundamental and applied points of view. This broad concept encompasses extreme reductions of genomes, the last universal common ancestor (LUCA), the creation of semiartificial cells, and the design of protocells and chassis cells. Here we review these different areas of research and identify common and complementary aspects of each one. We focus on systems biology, a discipline that is greatly facilitating the classical top-down and bottom-up approaches toward minimal cells. In addition, we also review the so-called middle-out approach and its contributions to the field with mathematical and computational models. Owing to the advances in genomics technologies, much of the work in this area has been centered on minimal genomes, or rather minimal gene sets, required to sustain life. Nevertheless, a fundamental expansion has been taking place in the last few years wherein the minimal gene set is viewed as a backbone of a more complex system. Complementing genomics, progress is being made in understanding the system-wide properties at the levels of the transcriptome, proteome, and metabolome. Network modeling approaches are enabling the integration of these different omics data sets toward an understanding of the complex molecular pathways connecting genotype to phenotype. We review key concepts central to the mapping and modeling of this complexity, which is at the heart of research on minimal cells. Finally, we discuss the distinction between minimizing the number of cellular components and minimizing cellular complexity, toward an improved understanding and utilization of minimal and simpler cells. PMID:25184563

Navigating the Perfect Storm: Research Strategies for Socialecological Systems in a Rapidly Evolving World

NASA Astrophysics Data System (ADS)

Dearing, John A.; Bullock, Seth; Costanza, Robert; Dawson, Terry P.; Edwards, Mary E.; Poppy, Guy M.; Smith, Graham M.

2012-04-01

The `Perfect Storm' metaphor describes a combination of events that causes a surprising or dramatic impact. It lends an evolutionary perspective to how social-ecological interactions change. Thus, we argue that an improved understanding of how social-ecological systems have evolved up to the present is necessary for the modelling, understanding and anticipation of current and future social-ecological systems. Here we consider the implications of an evolutionary perspective for designing research approaches. One desirable approach is the creation of multi-decadal records produced by integrating palaeoenvironmental, instrument and documentary sources at multiple spatial scales. We also consider the potential for improved analytical and modelling approaches by developing system dynamical, cellular and agent-based models, observing complex behaviour in social-ecological systems against which to test systems dynamical theory, and drawing better lessons from history. Alongside these is the need to find more appropriate ways to communicate complex systems, risk and uncertainty to the public and to policy-makers.

Understanding the value of mixed methods research: the Children’s Safety Initiative-Emergency Medical Services

PubMed Central

Hansen, Matthew; O’Brien, Kerth; Meckler, Garth; Chang, Anna Marie; Guise, Jeanne-Marie

2016-01-01

Mixed methods research has significant potential to broaden the scope of emergency care and specifically emergency medical services investigation. Mixed methods studies involve the coordinated use of qualitative and quantitative research approaches to gain a fuller understanding of practice. By combining what is learnt from multiple methods, these approaches can help to characterise complex healthcare systems, identify the mechanisms of complex problems such as medical errors and understand aspects of human interaction such as communication, behaviour and team performance. Mixed methods approaches may be particularly useful for out-of-hospital care researchers because care is provided in complex systems where equipment, interpersonal interactions, societal norms, environment and other factors influence patient outcomes. The overall objectives of this paper are to (1) introduce the fundamental concepts and approaches of mixed methods research and (2) describe the interrelation and complementary features of the quantitative and qualitative components of mixed methods studies using specific examples from the Children’s Safety Initiative-Emergency Medical Services (CSI-EMS), a large National Institutes of Health-funded research project conducted in the USA. PMID:26949970

Using conceptual maps to assess students' climate change understanding and misconceptions

NASA Astrophysics Data System (ADS)

Gautier, C.

2011-12-01

The complex and interdisciplinary nature of climate change science poses special challenges for educators in helping students understand the climate system, and how it is evolving under natural and anthropogenic forcing. Students and citizens alike have existing mental models that may limit their perception and processing of the multiple relationships between processes (e.g., feedback) that arise in global change science, and prevent adoption of complex scientific concepts. Their prior knowledge base serves as the scaffold for all future learning and grasping its range and limitations serves as an important basis upon which to anchor instruction. Different instructional strategies can be adopted to help students understand the inherently interdisciplinary topic of global climate change, its interwoven human and natural causes, and the connections it has with society through a complex range of political, social, technological and economic factors. One assessment method for students' understanding of global climate change with its many uncertainties, whether associated with the workings of the climate system or with respect to social, cultural and economic processes that mediate human responses to changes within the system, is through the use of conceptual maps. When well designed, they offer a representation of students' mental model prior and post instruction. We will present two conceptual mapping activities used in the classroom to assess students' knowledge and understanding about global climate change and uncover misconceptions. For the first one, concept maps will be used to demonstrate evidence of learning and conceptual change, while for the second we will show how conceptual maps can provide information about gaps in knowledge and misconceptions students have about the topic.

Understanding, creating, and managing complex techno-socio-economic systems: Challenges and perspectives

NASA Astrophysics Data System (ADS)

Helbing, D.; Balietti, S.; Bishop, S.; Lukowicz, P.

2011-05-01

This contribution reflects on the comments of Peter Allen [1], Bikas K. Chakrabarti [2], Péter Érdi [3], Juval Portugali [4], Sorin Solomon [5], and Stefan Thurner [6] on three White Papers (WP) of the EU Support Action Visioneer (www.visioneer.ethz.ch). These White Papers are entitled "From Social Data Mining to Forecasting Socio-Economic Crises" (WP 1) [7], "From Social Simulation to Integrative System Design" (WP 2) [8], and "How to Create an Innovation Accelerator" (WP 3) [9]. In our reflections, the need and feasibility of a "Knowledge Accelerator" is further substantiated by fundamental considerations and recent events around the globe. newpara The Visioneer White Papers propose research to be carried out that will improve our understanding of complex techno-socio-economic systems and their interaction with the environment. Thereby, they aim to stimulate multi-disciplinary collaborations between ICT, the social sciences, and complexity science. Moreover, they suggest combining the potential of massive real-time data, theoretical models, large-scale computer simulations and participatory online platforms. By doing so, it would become possible to explore various futures and to expand the limits of human imagination when it comes to the assessment of the often counter-intuitive behavior of these complex techno-socio-economic-environmental systems. In this contribution, we also highlight the importance of a pluralistic modeling approach and, in particular, the need for a fruitful interaction between quantitative and qualitative research approaches. newpara In an appendix we briefly summarize the concept of the FuturICT flagship project, which will build on and go beyond the proposals made by the Visioneer White Papers. EU flagships are ambitious multi-disciplinary high-risk projects with a duration of at least 10 years amounting to an envisaged overall budget of 1 billion EUR [10]. The goal of the FuturICT flagship initiative is to understand and manage complex, global, socially interactive systems, with a focus on sustainability and resilience.

Fundamental Challenges in Mechanistic Enzymology: Progress toward Understanding the Rate Enhancements of Enzymes

PubMed Central

Herschlag, Daniel; Natarajan, Aditya

2013-01-01

Enzymes are remarkable catalysts that lie at the heart of biology, accelerating chemical reactions to an astounding extent with extraordinary specificity. Enormous progress in understanding the chemical basis of enzymatic transformations and the basic mechanisms underlying rate enhancements over the past decades is apparent. Nevertheless, it has been difficult to achieve a quantitative understanding of how the underlying mechanisms account for the energetics of catalysis, because of the complexity of enzyme systems and the absence of underlying energetic additivity. We review case studies from our own work that illustrate the power of precisely defined and clearly articulated questions when dealing with such complex and multi-faceted systems, and we also use this approach to evaluate our current ability to design enzymes. We close by highlighting a series of questions that help frame some of what remains to be understood, and we encourage the reader to define additional questions and directions that will deepen and broaden our understanding of enzymes and their catalysis. PMID:23488725

Fundamental challenges in mechanistic enzymology: progress toward understanding the rate enhancements of enzymes.

PubMed

Herschlag, Daniel; Natarajan, Aditya

2013-03-26

Enzymes are remarkable catalysts that lie at the heart of biology, accelerating chemical reactions to an astounding extent with extraordinary specificity. Enormous progress in understanding the chemical basis of enzymatic transformations and the basic mechanisms underlying rate enhancements over the past decades is apparent. Nevertheless, it has been difficult to achieve a quantitative understanding of how the underlying mechanisms account for the energetics of catalysis, because of the complexity of enzyme systems and the absence of underlying energetic additivity. We review case studies from our own work that illustrate the power of precisely defined and clearly articulated questions when dealing with such complex and multifaceted systems, and we also use this approach to evaluate our current ability to design enzymes. We close by highlighting a series of questions that help frame some of what remains to be understood, and we encourage the reader to define additional questions and directions that will deepen and broaden our understanding of enzymes and their catalysis.

Dispersion Modeling in Complex Urban Systems

EPA Science Inventory

Models are used to represent real systems in an understandable way. They take many forms. A conceptual model explains the way a system works. In environmental studies, for example, a conceptual model may delineate all the factors and parameters for determining how a particle move...

Simulating Mercury And Methyl Mercury Stream Concentrations At Multiple Scales in a Wetland Influenced Coastal Plain Watershed (McTier Creek, SC, USA)

EPA Science Inventory

Use of Mechanistic Models to?Improve Understanding: Differential, mass balance, process-based Spatial and temporal resolution Necessary simplifications of system complexity Combing field monitoring and modeling efforts Balance between capturing complexity and maintaining...

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.

The emergence of complex behaviours in molecular magnetic materials.

PubMed

Goss, Karin; Gatteschi, Dante; Bogani, Lapo

2014-09-14

Molecular magnetism is considered an area where magnetic phenomena that are usually difficult to demonstrate can emerge with particular clarity. Over the years, however, less understandable systems have appeared in the literature of molecular magnetic materials, in some cases showing features that hint at the spontaneous emergence of global structures out of local interactions. This ingredient is typical of a wider class of problems, called complex behaviours, where the theory of complexity is currently being developed. In this perspective we wish to focus our attention on these systems and the underlying problematic that they highlight. We particularly highlight the emergence of the signatures of complexity in several molecular magnetic systems, which may provide unexplored opportunities for physical and chemical investigations.

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.

Synchronization in human musical rhythms and mutually interacting complex systems

PubMed Central

Hennig, Holger

2014-01-01

Though the music produced by an ensemble is influenced by multiple factors, including musical genre, musician skill, and individual interpretation, rhythmic synchronization is at the foundation of musical interaction. Here, we study the statistical nature of the mutual interaction between two humans synchronizing rhythms. We find that the interbeat intervals of both laypeople and professional musicians exhibit scale-free (power law) cross-correlations. Surprisingly, the next beat to be played by one person is dependent on the entire history of the other person’s interbeat intervals on timescales up to several minutes. To understand this finding, we propose a general stochastic model for mutually interacting complex systems, which suggests a physiologically motivated explanation for the occurrence of scale-free cross-correlations. We show that the observed long-term memory phenomenon in rhythmic synchronization can be imitated by fractal coupling of separately recorded or synthesized audio tracks and thus applied in electronic music. Though this study provides an understanding of fundamental characteristics of timing and synchronization at the interbrain level, the mutually interacting complex systems model may also be applied to study the dynamics of other complex systems where scale-free cross-correlations have been observed, including econophysics, physiological time series, and collective behavior of animal flocks. PMID:25114228

Quantifying the adaptive cycle

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Garmestani, Ahjond S.; Gunderson, Lance H.; Hjerne, Olle; Winder, Monika

2015-01-01

The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994–2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

Using a complex adaptive system lens to understand family caregiving experiences navigating the stroke rehabilitation system.

PubMed

Ghazzawi, Andrea; Kuziemsky, Craig; O'Sullivan, Tracey

2016-10-01

Family caregivers provide the stroke survivor with social support and continuity during the transition home from a rehabilitation facility. In this exploratory study we examined family caregivers' perceptions and experiences navigating the stroke rehabilitation system. The theories of continuity of care and complex adaptive systems were integrated to examine the transition from a stroke rehabilitation facility to the patient's home. This study provides an understanding of the interacting complexities at the macro and micro levels. A convenient sample of family caregivers (n = 14) who provide care for a stroke survivor were recruited 4-12 weeks following the patient's discharge from a stroke rehabilitation facility in Ontario, Canada. Interviews were conducted with family caregivers to examine their perceptions and experiences navigating the stroke rehabilitation system. Directed and inductive content analysis and the theory of Complex Adaptive Systems were used to interpret the perceptions of family caregivers. Health system policies and procedures at the macro-level determined the types and timing of information being provided to caregivers, and impacted continuity of care and access to supports and services at the micro-level. Supports and services in the community, such as outpatient physiotherapy services, were limited or did not meet the specific needs of the stroke survivors or family caregivers. Relationships with health providers, informational support, and continuity in case management all influence the family caregiving experience and ultimately the quality of care for the stroke survivor, during the transition home from a rehabilitation facility.

Quantifying the Adaptive Cycle.

PubMed

Angeler, David G; Allen, Craig R; Garmestani, Ahjond S; Gunderson, Lance H; Hjerne, Olle; Winder, Monika

2015-01-01

The adaptive cycle was proposed as a conceptual model to portray patterns of change in complex systems. Despite the model having potential for elucidating change across systems, it has been used mainly as a metaphor, describing system dynamics qualitatively. We use a quantitative approach for testing premises (reorganisation, conservatism, adaptation) in the adaptive cycle, using Baltic Sea phytoplankton communities as an example of such complex system dynamics. Phytoplankton organizes in recurring spring and summer blooms, a well-established paradigm in planktology and succession theory, with characteristic temporal trajectories during blooms that may be consistent with adaptive cycle phases. We used long-term (1994-2011) data and multivariate analysis of community structure to assess key components of the adaptive cycle. Specifically, we tested predictions about: reorganisation: spring and summer blooms comprise distinct community states; conservatism: community trajectories during individual adaptive cycles are conservative; and adaptation: phytoplankton species during blooms change in the long term. All predictions were supported by our analyses. Results suggest that traditional ecological paradigms such as phytoplankton successional models have potential for moving the adaptive cycle from a metaphor to a framework that can improve our understanding how complex systems organize and reorganize following collapse. Quantifying reorganization, conservatism and adaptation provides opportunities to cope with the intricacies and uncertainties associated with fast ecological change, driven by shifting system controls. Ultimately, combining traditional ecological paradigms with heuristics of complex system dynamics using quantitative approaches may help refine ecological theory and improve our understanding of the resilience of ecosystems.

Dependency visualization for complex system understanding

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

Smart, J. Allison Cory

1994-09-01

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

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

Planetary Rings

NASA Astrophysics Data System (ADS)

Gordon, M. K.; Araki, S.; Black, G. J.; Bosh, A. S.; Brahic, A.; Brooks, S. M.; Charnoz, S.; Colwell, J. E.; Cuzzi, J. N.; Dones, L.; Durisen, R. H.; Esposito, L. W.; Ferrari, C.; Festou, M.; French, R. G.; Giuliatti-Winter, S. M.; Graps, A. L.; Hamilton, D. P.; Horanyi, M.; Karjalainen, R. M.; Krivov, A. V.; Krueger, H.; Larson, S. M.; Levison, H. F.; Lewis, M. C.; Lissauer, J. J.; Murray, C. D.; Namouni, F.; Nicholson, P. D.; Olkin, C. B.; Poulet, F.; Rappaport, N. J.; Salo, H. J.; Schmidt, J.; Showalter, M. R.; Spahn, F.; Spilker, L. J.; Srama, R.; Stewart, G. R.; Yanamandra-Fisher, P.

2002-08-01

The past two decades have witnessed dramatic changes in our view and understanding of planetary rings. We now know that each of the giant planets in the Solar System possesses a complex and unique ring system. Recent studies have identified complex gravitational interactions between the rings and their retinues of attendant satellites. Among the four known ring systems, we see elegant examples of Lindblad and corotation resonances (first invoked in the context of galactic disks), electromagnetic resonances, spiral density waves and bending waves, narrow ringlets which exhibit internal modes due to collective instabilities, sharp-edged gaps maintained via tidal torques from embedded moonlets, and tenuous dust belts created by meteoroid impact onto, or collisions between, parent bodies. Yet, as far as we have come, our understanding is far from complete. The fundamental questions confronting ring scientists at the beginning of the twenty-first century are those regarding the origin, age and evolution of the various ring systems, in the broadest context. Understanding the origin and age requires us to know the current ring properties, and to understand the dominant evolutionary processes and how they influence ring properties. Here we discuss a prioritized list of the key questions, the answers to which would provide the greatest improvement in our understanding of planetary rings. We then outline the initiatives, missions, and other supporting activities needed to address those questions, and recommend priorities for the coming decade in planetary ring science.

The threshold algorithm: Description of the methodology and new developments

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

An illustration of whole systems thinking.

PubMed

Kalim, Kanwal; Carson, Ewart; Cramp, Derek

2006-08-01

The complexity of policy-making in the NHS is such that systemic, holistic thinking is needed if the current government's plans are to be realized. This paper describes systems thinking and illustrates its value in understanding the complexity of the diabetes National Service Framework (NSF); its role in identifying problems and barriers previously not predicted; and in reaching conclusions as to how it should be implemented. The approach adopted makes use of soft systems methodology (SSM) devised by Peter Checkland. This analysis reveals issues relating to human communication, information provision and resource allocation needing to be addressed. From this, desirable and feasible changes are explored as means of achieving a more effective NSF, examining possible changes from technical, organizational, economic and cultural perspectives. As well as testing current health policies and plans, SSM can be used to test the feasibility of new health policies. This is achieved by providing a greater understanding and appreciation of what is happening in the real world and how people work. Soft systems thinking is the best approach, given the complexity of health care. It is a flexible, cost-effective solution, which should be a prerequisite before any new health policy is launched.

Learning the organization: a model for health system analysis for new nurse administrators.

PubMed

Clark, Mary Jo

2004-01-01

Health systems are large and complex organizations in which multiple components and processes influence system outcomes. In order to effectively position themselves in such organizations, nurse administrators new to a system must gain a rapid understanding of overall system operation. Such understanding is facilitated by use of a model for system analysis. The model presented here examines the dynamic interrelationships between and among internal and external elements as they affect system performance. External elements to be analyzed include environmental factors and characteristics of system clientele. Internal elements flow from the mission and goals of the system and include system culture, services, resources, and outcomes.

Understanding global health governance as a complex adaptive system.

PubMed

Hill, Peter S

2011-01-01

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

Enhancing implementation science by applying best principles of systems science.

PubMed

Northridge, Mary E; Metcalf, Sara S

2016-10-04

Implementation science holds promise for better ensuring that research is translated into evidence-based policy and practice, but interventions often fail or even worsen the problems they are intended to solve due to a lack of understanding of real world structures and dynamic complexity. While systems science alone cannot possibly solve the major challenges in public health, systems-based approaches may contribute to changing the language and methods for conceptualising and acting within complex systems. The overarching goal of this paper is to improve the modelling used in dissemination and implementation research by applying best principles of systems science. Best principles, as distinct from the more customary term 'best practices', are used to underscore the need to extract the core issues from the context in which they are embedded in order to better ensure that they are transferable across settings. Toward meaningfully grappling with the complex and challenging problems faced in adopting and integrating evidence-based health interventions and changing practice patterns within specific settings, we propose and illustrate four best principles derived from our systems science experience: (1) model the problem, not the system; (2) pay attention to what is important, not just what is quantifiable; (3) leverage the utility of models as boundary objects; and (4) adopt a portfolio approach to model building. To improve our mental models of the real world, system scientists have created methodologies such as system dynamics, agent-based modelling, geographic information science and social network simulation. To understand dynamic complexity, we need the ability to simulate. Otherwise, our understanding will be limited. The practice of dynamic systems modelling, as discussed herein, is the art and science of linking system structure to behaviour for the purpose of changing structure to improve behaviour. A useful computer model creates a knowledge repository and a virtual library for internally consistent exploration of alternative assumptions. Among the benefits of systems modelling are iterative practice, participatory potential and possibility thinking. We trust that the best principles proposed here will resonate with implementation scientists; applying them to the modelling process may abet the translation of research into effective policy and practice.

Understanding the biological underpinnings of ecohydrological processes

NASA Astrophysics Data System (ADS)

Huxman, T. E.; Scott, R. L.; Barron-Gafford, G. A.; Hamerlynck, E. P.; Jenerette, D.; Tissue, D. T.; Breshears, D. D.; Saleska, S. R.

2012-12-01

Climate change presents a challenge for predicting ecosystem response, as multiple factors drive both the physical and life processes happening on the land surface and their interactions result in a complex, evolving coupled system. For example, changes in surface temperature and precipitation influence near-surface hydrology through impacts on system energy balance, affecting a range of physical processes. These changes in the salient features of the environment affect biological processes and elicit responses along the hierarchy of life (biochemistry to community composition). Many of these structural or process changes can alter patterns of soil water-use and influence land surface characteristics that affect local climate. Of the many features that affect our ability to predict the future dynamics of ecosystems, it is this hierarchical response of life that creates substantial complexity. Advances in the ability to predict or understand aspects of demography help describe thresholds in coupled ecohydrological system. Disentangling the physical and biological features that underlie land surface dynamics following disturbance are allowing a better understanding of the partitioning of water in the time-course of recovery. Better predicting the timing of phenology and key seasonal events allow for a more accurate description of the full functional response of the land surface to climate. In addition, explicitly considering the hierarchical structural features of life are helping to describe complex time-dependent behavior in ecosystems. However, despite this progress, we have yet to build an ability to fully account for the generalization of the main features of living systems into models that can describe ecohydrological processes, especially acclimation, assembly and adaptation. This is unfortunate, given that many key ecosystem services are functions of these coupled co-evolutionary processes. To date, both the lack of controlled measurements and experimentation has precluded determination of sufficient theoretical development. Understanding the land-surface response and feedback to climate change requires a mechanistic understanding of the coupling of ecological and hydrological processes and an expansion of theory from the life sciences to appropriately contribute to the broader Earth system science goal.

A computational approach to achieve situational awareness from limited observations of a complex system

NASA Astrophysics Data System (ADS)

Sherwin, Jason

At the start of the 21st century, the topic of complexity remains a formidable challenge in engineering, science and other aspects of our world. It seems that when disaster strikes it is because some complex and unforeseen interaction causes the unfortunate outcome. Why did the financial system of the world meltdown in 2008--2009? Why are global temperatures on the rise? These questions and other ones like them are difficult to answer because they pertain to contexts that require lengthy descriptions. In other words, these contexts are complex. But we as human beings are able to observe and recognize this thing we call 'complexity'. Furthermore, we recognize that there are certain elements of a context that form a system of complex interactions---i.e., a complex system. Many researchers have even noted similarities between seemingly disparate complex systems. Do sub-atomic systems bear resemblance to weather patterns? Or do human-based economic systems bear resemblance to macroscopic flows? Where do we draw the line in their resemblance? These are the kinds of questions that are asked in complex systems research. And the ability to recognize complexity is not only limited to analytic research. Rather, there are many known examples of humans who, not only observe and recognize but also, operate complex systems. How do they do it? Is there something superhuman about these people or is there something common to human anatomy that makes it possible to fly a plane? Or to drive a bus? Or to operate a nuclear power plant? Or to play Chopin's etudes on the piano? In each of these examples, a human being operates a complex system of machinery, whether it is a plane, a bus, a nuclear power plant or a piano. What is the common thread running through these abilities? The study of situational awareness (SA) examines how people do these types of remarkable feats. It is not a bottom-up science though because it relies on finding general principles running through a host of varied human activities. Nevertheless, since it is not constrained by computational details, the study of situational awareness provides a unique opportunity to approach complex tasks of operation from an analytical perspective. In other words, with SA, we get to see how humans observe, recognize and react to complex systems on which they exert some control. Reconciling this perspective on complexity with complex systems research, it might be possible to further our understanding of complex phenomena if we can probe the anatomical mechanisms by which we, as humans, do it naturally. At this unique intersection of two disciplines, a hybrid approach is needed. So in this work, we propose just such an approach. In particular, this research proposes a computational approach to the situational awareness (SA) of complex systems. Here we propose to implement certain aspects of situational awareness via a biologically-inspired machine-learning technique called Hierarchical Temporal Memory (HTM). In doing so, we will use either simulated or actual data to create and to test computational implementations of situational awareness. This will be tested in two example contexts, one being more complex than the other. The ultimate goal of this research is to demonstrate a possible approach to analyzing and understanding complex systems. By using HTM and carefully developing techniques to analyze the SA formed from data, it is believed that this goal can be obtained.

Controllability of complex networks for sustainable system dynamics

EPA Science Inventory

Successful implementation of sustainability ideas in ecosystem management requires a basic understanding of the often non-linear and non-intuitive relationships among different dimensions of sustainability, particularly the system-wide implications of human actions. This basic un...

ngVLA Key Science Goal 2: Probing the Initial Conditions for Planetary Systems and Life with Astrochemistry

NASA Astrophysics Data System (ADS)

McGuire, Brett; ngVLA Science Working Group 1

2018-01-01

One of the most challenging aspects in understanding the origin and evolution of planets and planetary systems is tracing the influence of chemistry on the physical evolution of a system from a molecular cloud to a solar system. Existing facilities have already shown the stunning degree of molecular complexity present in these systems. The unique combination of sensitivity and spatial resolution offered by the ngVLA will permit the observation of both highly complex and very low-abundance chemical species that are exquisitely sensitive to the physical conditions and evolutionary history of their sources, which are out of reach of current observatories. In turn, by understanding the chemical evolution of these complex molecules, unprecedentedly detailed astrophysical insight can be gleaned from these astrochemical observations.This poster will overview a number of key science goals in astrochemistry which will be enabled by the ngVLA, including:1) imaging of the deepest, densest regions in protoplanetary disks and unveiling the physical history through isotopic ratios2) probing the ammonia snow line in these disks, thought to be the only viable tracer of the water snowline3) observations of the molecular content of giant planet atmospheres4) detections of new, complex molecules, potentially including the simplest amino acids and sugars5) tracing the origin of chiral excess in star-forming regions

Applications of systems approaches in the study of rheumatic diseases.

PubMed

Kim, Ki-Jo; Lee, Saseong; Kim, Wan-Uk

2015-03-01

The complex interaction of molecules within a biological system constitutes a functional module. These modules are then acted upon by both internal and external factors, such as genetic and environmental stresses, which under certain conditions can manifest as complex disease phenotypes. Recent advances in high-throughput biological analyses, in combination with improved computational methods for data enrichment, functional annotation, and network visualization, have enabled a much deeper understanding of the mechanisms underlying important biological processes by identifying functional modules that are temporally and spatially perturbed in the context of disease development. Systems biology approaches such as these have produced compelling observations that would be impossible to replicate using classical methodologies, with greater insights expected as both the technology and methods improve in the coming years. Here, we examine the use of systems biology and network analysis in the study of a wide range of rheumatic diseases to better understand the underlying molecular and clinical features.

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

Moore, Thomas W.; Quach, Tu-Thach; Detry, Richard Joseph

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

Developing Causal Understanding with Causal Maps: The Impact of Total Links, Temporal Flow, and Lateral Position of Outcome Nodes

ERIC Educational Resources Information Center

Jeong, Allan; Lee, Woon Jee

2012-01-01

This study examined some of the methodological approaches used by students to construct causal maps in order to determine which approaches help students understand the underlying causes and causal mechanisms in a complex system. This study tested the relationship between causal understanding (ratio of root causes correctly/incorrectly identified,…

Is complex signal processing for bone conduction hearing aids useful?

PubMed

Kompis, Martin; Kurz, Anja; Pfiffner, Flurin; Senn, Pascal; Arnold, Andreas; Caversaccio, Marco

2014-05-01

To establish whether complex signal processing is beneficial for users of bone anchored hearing aids. Review and analysis of two studies from our own group, each comparing a speech processor with basic digital signal processing (either Baha Divino or Baha Intenso) and a processor with complex digital signal processing (either Baha BP100 or Baha BP110 power). The main differences between basic and complex signal processing are the number of audiologist accessible frequency channels and the availability and complexity of the directional multi-microphone noise reduction and loudness compression systems. Both studies show a small, statistically non-significant improvement of speech understanding in quiet with the complex digital signal processing. The average improvement for speech in noise is +0.9 dB, if speech and noise are emitted both from the front of the listener. If noise is emitted from the rear and speech from the front of the listener, the advantage of the devices with complex digital signal processing as opposed to those with basic signal processing increases, on average, to +3.2 dB (range +2.3 … +5.1 dB, p ≤ 0.0032). Complex digital signal processing does indeed improve speech understanding, especially in noise coming from the rear. This finding has been supported by another study, which has been published recently by a different research group. When compared to basic digital signal processing, complex digital signal processing can increase speech understanding of users of bone anchored hearing aids. The benefit is most significant for speech understanding in noise.

Could a neuroscientist understand a microprocessor?

DOE PAGES

Jonas, Eric; Kording, Konrad Paul; Diedrichsen, Jorn

2017-01-12

There is a popular belief in neuroscience that we are primarily data limited, and that producing large, multimodal, and complex datasets will, with the help of advanced data analysis algorithms, lead to fundamental insights into the way the brain processes information. These datasets do not yet exist, and if they did we would have no way of evaluating whether or not the algorithmically-generated insights were sufficient or even correct. To address this, here we take a classical microprocessor as a model organism, and use our ability to perform arbitrary experiments on it to see if popular data analysis methods frommore » neuroscience can elucidate the way it processes information. Microprocessors are among those artificial information processing systems that are both complex and that we understand at all levels, from the overall logical flow, via logical gates, to the dynamics of transistors. We show that the approaches reveal interesting structure in the data but do not meaningfully describe the hierarchy of information processing in the microprocessor. This suggests current analytic approaches in neuroscience may fall short of producing meaningful understanding of neural systems, regardless of the amount of data. Furthermore, we argue for scientists using complex non-linear dynamical systems with known ground truth, such as the microprocessor as a validation platform for time-series and structure discovery methods.« less

Rating Correlations Between Customs Codes and Export Control Lists: Assessing the Needs and Challenges

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

Chatelus, Renaud; Heine, Pete

Correlation tables are the linchpins between the customs codes used to classify commodities in international trade and the control lists used for strategic trade control (STC) purposes. While understanding the customs classification system can help the STC community better understand strategic trade flows, better identify which trade operations require permits, and more effectively detect illegal exports, the two systems are different in scope, philosophy, content, and objectives. Many indications point to the limitations of these correlation tables, and it is important to understand the nature of the limitations and the complex underlying reasons to conceive possible improvements. As part ofmore » its Strategic Trade and Supply Chain Analytics Initiative, Argonne National Laboratory supported a study of a subset of the European Union’s TARIC correlation table. The study included development of a methodology and an approach to rating the quality and relevance of individual correlations. The study was intended as a first step to engage the STC community in deflections and initiatives to improve the conception and use of correlations, and its conclusions illustrate the scope and complex nature of the challenges to overcome. This paper presents the two classification systems, analyzes the needs for correlation tables and the complex challenges associated with them, summarizes key findings, and proposes possible ways forward.« less

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

A framework for unravelling the complexities of unsustainable water resource use

NASA Astrophysics Data System (ADS)

Dermody, Brian; Bierkens, Marc; Wassen, Martin; Dekker, Stefan

2016-04-01

The majority of unsustainable water resource use is associated with food production, with the agricultural sector accounting for up to 70% of total freshwater use by humans. Water resource use in food production emerges as a result of dynamic interactions between humans and their environment in importing and exporting regions as well as the physical and socioeconomic trade infrastructure linking the two. Thus in order to understand unsustainable water resource use, it is essential to understand the complex socioecological food production and trade system. We present a modelling framework of the food production and trade system that facilitates an understanding of complex socioenvironmental processes that lead to unsustainable water resource use. Our framework is based on a coupling of the global hydrological model PC Raster Global Water Balance (PCR-GLOBWB) with a multi-agent socioeconomic food production and trade network. In our framework, agents perceive environmental conditions. They make food supply decisions based upon those perceptions and the heterogeneous socioeconomic conditions in which they exist. Agent decisions modify land and water resources. Those environmental changes feedback to influence decision making further. The framework presented has the potential to go beyond a diagnosis of the causes of unsustainable water resource and provide pathways towards a sustainable food system in terms of water resources.

Could a Neuroscientist Understand a Microprocessor?

PubMed Central

Kording, Konrad Paul

2017-01-01

There is a popular belief in neuroscience that we are primarily data limited, and that producing large, multimodal, and complex datasets will, with the help of advanced data analysis algorithms, lead to fundamental insights into the way the brain processes information. These datasets do not yet exist, and if they did we would have no way of evaluating whether or not the algorithmically-generated insights were sufficient or even correct. To address this, here we take a classical microprocessor as a model organism, and use our ability to perform arbitrary experiments on it to see if popular data analysis methods from neuroscience can elucidate the way it processes information. Microprocessors are among those artificial information processing systems that are both complex and that we understand at all levels, from the overall logical flow, via logical gates, to the dynamics of transistors. We show that the approaches reveal interesting structure in the data but do not meaningfully describe the hierarchy of information processing in the microprocessor. This suggests current analytic approaches in neuroscience may fall short of producing meaningful understanding of neural systems, regardless of the amount of data. Additionally, we argue for scientists using complex non-linear dynamical systems with known ground truth, such as the microprocessor as a validation platform for time-series and structure discovery methods. PMID:28081141

Could a Neuroscientist Understand a Microprocessor?

PubMed

Jonas, Eric; Kording, Konrad Paul

2017-01-01

There is a popular belief in neuroscience that we are primarily data limited, and that producing large, multimodal, and complex datasets will, with the help of advanced data analysis algorithms, lead to fundamental insights into the way the brain processes information. These datasets do not yet exist, and if they did we would have no way of evaluating whether or not the algorithmically-generated insights were sufficient or even correct. To address this, here we take a classical microprocessor as a model organism, and use our ability to perform arbitrary experiments on it to see if popular data analysis methods from neuroscience can elucidate the way it processes information. Microprocessors are among those artificial information processing systems that are both complex and that we understand at all levels, from the overall logical flow, via logical gates, to the dynamics of transistors. We show that the approaches reveal interesting structure in the data but do not meaningfully describe the hierarchy of information processing in the microprocessor. This suggests current analytic approaches in neuroscience may fall short of producing meaningful understanding of neural systems, regardless of the amount of data. Additionally, we argue for scientists using complex non-linear dynamical systems with known ground truth, such as the microprocessor as a validation platform for time-series and structure discovery methods.

Could a neuroscientist understand a microprocessor?

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

Jonas, Eric; Kording, Konrad Paul; Diedrichsen, Jorn

There is a popular belief in neuroscience that we are primarily data limited, and that producing large, multimodal, and complex datasets will, with the help of advanced data analysis algorithms, lead to fundamental insights into the way the brain processes information. These datasets do not yet exist, and if they did we would have no way of evaluating whether or not the algorithmically-generated insights were sufficient or even correct. To address this, here we take a classical microprocessor as a model organism, and use our ability to perform arbitrary experiments on it to see if popular data analysis methods frommore » neuroscience can elucidate the way it processes information. Microprocessors are among those artificial information processing systems that are both complex and that we understand at all levels, from the overall logical flow, via logical gates, to the dynamics of transistors. We show that the approaches reveal interesting structure in the data but do not meaningfully describe the hierarchy of information processing in the microprocessor. This suggests current analytic approaches in neuroscience may fall short of producing meaningful understanding of neural systems, regardless of the amount of data. Furthermore, we argue for scientists using complex non-linear dynamical systems with known ground truth, such as the microprocessor as a validation platform for time-series and structure discovery methods.« less

Computer modeling of Epilepsy

PubMed Central

Lytton, William W.

2009-01-01

Preface Epilepsy is a complex set of disorders that can involve many areas of cortex as well as underlying deep brain systems. The myriad manifestations of seizures, as varied as déjà vu and olfactory hallucination, can thereby give researchers insights into regional functions and relations. Epilepsy is also complex genetically and pathophysiologically, involving microscopic (ion channels, synaptic proteins), macroscopic (brain trauma and rewiring) and intermediate changes in a complex interplay of causality. It has long been recognized that computer modeling will be required to disentangle causality, to better understand seizure spread and to understand and eventually predict treatment efficacy. Over the past few years, substantial progress has been made modeling epilepsy at levels ranging from the molecular to the socioeconomic. We review these efforts and connect them to the medical goals of understanding and treating this disorder. PMID:18594562

Understanding the National Energy Dilemma.

ERIC Educational Resources Information Center

Georgetown Univ., Washington, DC. Center for Strategic and International Studies.

This graphic representation of our energy dilemma provides government officials, industry, and general public with an understanding of the broad problems and complexity of our energy crisis. An energy display system projects effects of energy policies on our domestic energy situation. This display contains sheets indicating total energy flow…

Understanding the structure

Treesearch

David J. Nowak

1994-01-01

Urban forests are complex ecosystems created by the interaction of anthropogenic and natural processes. One key to better management of these systems is to understand urban forest structure and its relationship to forest functions. Through sampling and inventories, urban foresters often obtain structural information (e.g., numbers, location, size, and condition) on...

Systemic Change for RTI: Key Shifts for Practice

ERIC Educational Resources Information Center

Kozleski, Elizabeth B.; Huber, Jennifer J.

2010-01-01

RTI has the potential to meet the challenges of increasing diversity in student populations and the need for increasingly complex systems of instructional design. Three fundamental shifts in understanding systems and systems change must ground RTI policy and implementation work. First, RTI must be seen as an activity system nested within a larger…

Protein-Protein Interactions of Azurin Complex by Coarse-Grained Simulations with a Gō-Like Model

NASA Astrophysics Data System (ADS)

Rusmerryani, Micke; Takasu, Masako; Kawaguchi, Kazutomo; Saito, Hiroaki; Nagao, Hidemi

Proteins usually perform their biological functions by forming a complex with other proteins. It is very important to study the protein-protein interactions since these interactions are crucial in many processes of a living organism. In this study, we develop a coarse grained model to simulate protein complex in liquid system. We carry out molecular dynamics simulations with topology-based potential interactions to simulate dynamical properties of Pseudomonas Aeruginosa azurin complex systems. Azurin is known to play an essential role as an anticancer agent and bind many important intracellular molecules. Some physical properties are monitored during simulation time to get a better understanding of the influence of protein-protein interactions to the azurin complex dynamics. These studies will provide valuable insights for further investigation on protein-protein interactions in more realistic system.

Teachers' Beliefs and Practices: A Dynamic and Complex Relationship

ERIC Educational Resources Information Center

Zheng, Hongying

2013-01-01

Research on teachers' beliefs has provided useful insights into understanding processes of teaching. However, no research has explored teachers' beliefs as a system nor have researchers investigated the substance of interactions between teachers' beliefs, practices and context. Therefore, the author adopts complexity theory to explore the features…

Combining Toxicological and Chemical Characterization of Complex Mixtures to Understand the Impact of the Unknown Fraction

EPA Science Inventory

Toxicological assessment of adverse health outcomes associated with exposure to complex mixtures provides an integrated response of the organism (or in vitro test system) that accounts for additivity among the components (both dose and response) as well as any greater than or les...

Designing and Validating Assessments of Complex Thinking in Science

ERIC Educational Resources Information Center

Ryoo, Kihyun; Linn, Marcia C.

2015-01-01

Typical assessment systems often measure isolated ideas rather than the coherent understanding valued in current science classrooms. Such assessments may motivate students to memorize, rather than to use new ideas to solve complex problems. To meet the requirements of the Next Generation Science Standards, instruction needs to emphasize sustained…

From Complex to Simple: Interdisciplinary Stochastic Models

ERIC Educational Resources Information Center

Mazilu, D. A.; Zamora, G.; Mazilu, I.

2012-01-01

We present two simple, one-dimensional, stochastic models that lead to a qualitative understanding of very complex systems from biology, nanoscience and social sciences. The first model explains the complicated dynamics of microtubules, stochastic cellular highways. Using the theory of random walks in one dimension, we find analytical expressions…

Attention Guidance in Learning from a Complex Animation: Seeing Is Understanding?

ERIC Educational Resources Information Center

de Koning, Bjorn B.; Tabbers, Huib K.; Rikers, Remy M. J. P.; Paas, Fred

2010-01-01

To examine how visual attentional resources are allocated when learning from a complex animation about the cardiovascular system, eye movements were registered in the absence and presence of visual cues. Cognitive processing was assessed using cued retrospective reporting, whereas comprehension and transfer tests measured the quality of the…

Using Iceland as a Model for Interdisciplinary Honors Study

ERIC Educational Resources Information Center

Andersen, Kim; Thorgaard, Gary

2014-01-01

Interdisciplinary approaches do not merely satisfy an abstract longing; in post-educational life--especially in a secular, Western, post-modern culture--young people must confront complex issues that transcend any one discipline. Educational systems accordingly have a duty to offer frameworks for understanding this complexity that go beyond any…

The Influence of Free Space Environment in the Mission Life Cycle: Material Selection

NASA Technical Reports Server (NTRS)

Edwards, David L.; Burns, Howard D.; de Groh, Kim K.

2014-01-01

The natural space environment has a great influence on the ability of space systems to perform according to mission design specification. Understanding the natural space environment and its influence on space system performance is critical to the concept formulation, design, development, and operation of space systems. Compatibility with the natural space environment is a primary factor in determining the functional lifetime of the space system. Space systems being designed and developed today are growing in complexity. In many instances, the increased complexity also increases its sensitivity to space environmental effects. Sensitivities to the natural space environment can be tempered through appropriate design measures, material selection, ground processing, mitigation strategies, and/or the acceptance of known risks. The design engineer must understand the effects of the natural space environment on the space system and its components. This paper will discuss the influence of the natural space environment in the mission life cycle with a specific focus on the role of material selection.

Elementary student and prospective teachers' agri-food system literacy: Understandings of agricultural and science education's goals for learning

NASA Astrophysics Data System (ADS)

Trexler, Cary Jay

1999-09-01

Although rhetoric abounds in the agricultural education literature regarding the public's dearth of agri-food system literacy, problems arise when establishing educational interventions to help ameliorate illiteracy. Researchers do not fully know what individuals understand about the complex agri-food system. Hence, educational programs and curricula may focus on areas where students already possess well developed and scientifically accurate schemata, while ignoring other areas where incompatible or naive understandings persist. Democratic decisions about complex societal and environmental issues, such as trade-offs of our industrial agri-food system, require individuals to possess understandings of complex interrelationships. This exploratory qualitative study determines what two groups---elementary students and prospective elementary school teachers---understand about selected concepts foundational to agri-food system literacy. To ground the study in current national education curricular standards, a synthesis of both agricultural and science education benchmarks was developed. This helped structure interviews with the study's informants: nine elementary students and nine prospective elementary teachers. Analysis of discourse was based upon a conceptual change methodology. Findings showed that informant background and non-school experiences were linked to agri-food system literacy, while formal, in-school learning was not. For elementary students, high socio-economic status, gardening and not living in urban areas were correlates with literacy; the prospective teacher group exhibited similar trends. Informants understood that food came from farms where plants and animals were raised. For the majority, however, farms were described as large gardens. Additionally, informants lacked a clear understanding of the roles soil and fertilizers play in crop production. Further, few spoke of weeds as competitors with crops for growth requirements. Informants understood that agricultural technologies saved time and reduced labor and were concerned with the immediate impact of agricultural pollution. They, however, did not link their food and fiber consumption with resources use or environmental impact. Additionally, half of the prospective teachers did not understand genetics well enough to discuss how humans engineer life. Notable differences were found between teachers and students in 17% of the elementary benchmarks. Differences between the two groups were found in the elementary students' lack of ability to proffer cause-effect relationships, especially in regard to the use of agricultural technologies.

Dual-phase evolution in complex adaptive systems

PubMed Central

Paperin, Greg; Green, David G.; Sadedin, Suzanne

2011-01-01

Understanding the origins of complexity is a key challenge in many sciences. Although networks are known to underlie most systems, showing how they contribute to well-known phenomena remains an issue. Here, we show that recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. We identify properties that are typical of systems in different connectivity phases, as well as characteristics commonly associated with the phase transitions. We synthesize these common features into a common framework, which we term dual-phase evolution (DPE). Using this framework, we review the literature from several disciplines to show that recurrent connectivity phase transitions underlie the complex properties of many biological, physical and human systems. We argue that the DPE framework helps to explain many complex phenomena, including perpetual novelty, modularity, scale-free networks and criticality. Our review concludes with a discussion of the way DPE relates to other frameworks, in particular, self-organized criticality and the adaptive cycle. PMID:21247947

Dual-phase evolution in complex adaptive systems.

PubMed

Paperin, Greg; Green, David G; Sadedin, Suzanne

2011-05-06

Understanding the origins of complexity is a key challenge in many sciences. Although networks are known to underlie most systems, showing how they contribute to well-known phenomena remains an issue. Here, we show that recurrent phase transitions in network connectivity underlie emergent phenomena in many systems. We identify properties that are typical of systems in different connectivity phases, as well as characteristics commonly associated with the phase transitions. We synthesize these common features into a common framework, which we term dual-phase evolution (DPE). Using this framework, we review the literature from several disciplines to show that recurrent connectivity phase transitions underlie the complex properties of many biological, physical and human systems. We argue that the DPE framework helps to explain many complex phenomena, including perpetual novelty, modularity, scale-free networks and criticality. Our review concludes with a discussion of the way DPE relates to other frameworks, in particular, self-organized criticality and the adaptive cycle.

Student Cognitive Difficulties and Mental Model Development of Complex Earth and Environmental Systems

NASA Astrophysics Data System (ADS)

Sell, K.; Herbert, B.; Schielack, J.

2004-05-01

Students organize scientific knowledge and reason about environmental issues through manipulation of mental models. The nature of the environmental sciences, which are focused on the study of complex, dynamic systems, may present cognitive difficulties to students in their development of authentic, accurate mental models of environmental systems. The inquiry project seeks to develop and assess the coupling of information technology (IT)-based learning with physical models in order to foster rich mental model development of environmental systems in geoscience undergraduate students. The manipulation of multiple representations, the development and testing of conceptual models based on available evidence, and exposure to authentic, complex and ill-constrained problems were the components of investigation utilized to reach the learning goals. Upper-level undergraduate students enrolled in an environmental geology course at Texas A&M University participated in this research which served as a pilot study. Data based on rubric evaluations interpreted by principal component analyses suggest students' understanding of the nature of scientific inquiry is limited and the ability to cross scales and link systems proved problematic. Results categorized into content knowledge and cognition processes where reasoning, critical thinking and cognitive load were driving factors behind difficulties in student learning. Student mental model development revealed multiple misconceptions and lacked complexity and completeness to represent the studied systems. Further, the positive learning impacts of the implemented modules favored the physical model over the IT-based learning projects, likely due to cognitive load issues. This study illustrates the need to better understand student difficulties in solving complex problems when using IT, where the appropriate scaffolding can then be implemented to enhance student learning of the earth system sciences.

Taking Systems Medicine to Heart.

PubMed

Trachana, Kalliopi; Bargaje, Rhishikesh; Glusman, Gustavo; Price, Nathan D; Huang, Sui; Hood, Leroy E

2018-04-27

Systems medicine is a holistic approach to deciphering the complexity of human physiology in health and disease. In essence, a living body is constituted of networks of dynamically interacting units (molecules, cells, organs, etc) that underlie its collective functions. Declining resilience because of aging and other chronic environmental exposures drives the system to transition from a health state to a disease state; these transitions, triggered by acute perturbations or chronic disturbance, manifest as qualitative shifts in the interactions and dynamics of the disease-perturbed networks. Understanding health-to-disease transitions poses a high-dimensional nonlinear reconstruction problem that requires deep understanding of biology and innovation in study design, technology, and data analysis. With a focus on the principles of systems medicine, this Review discusses approaches for deciphering this biological complexity from a novel perspective, namely, understanding how disease-perturbed networks function; their study provides insights into fundamental disease mechanisms. The immediate goals for systems medicine are to identify early transitions to cardiovascular (and other chronic) diseases and to accelerate the translation of new preventive, diagnostic, or therapeutic targets into clinical practice, a critical step in the development of personalized, predictive, preventive, and participatory (P4) medicine. © 2018 American Heart Association, Inc.

Shadows of complexity: what biological networks reveal about epistasis and pleiotropy

PubMed Central

Tyler, Anna L.; Asselbergs, Folkert W.; Williams, Scott M.; Moore, Jason H.

2011-01-01

Pleiotropy, in which one mutation causes multiple phenotypes, has traditionally been seen as a deviation from the conventional observation in which one gene affects one phenotype. Epistasis, or gene-gene interaction, has also been treated as an exception to the Mendelian one gene-one phenotype paradigm. This simplified perspective belies the pervasive complexity of biology and hinders progress toward a deeper understanding of biological systems. We assert that epistasis and pleiotropy are not isolated occurrences, but ubiquitous and inherent properties of biomolecular networks. These phenomena should not be treated as exceptions, but rather as fundamental components of genetic analyses. A systems level understanding of epistasis and pleiotropy is, therefore, critical to furthering our understanding of human genetics and its contribution to common human disease. Finally, graph theory offers an intuitive and powerful set of tools with which to study the network bases of these important genetic phenomena. PMID:19204994

Clinical review: International comparisons in critical care - lessons learned.

PubMed

Murthy, Srinivas; Wunsch, Hannah

2012-12-12

Critical care medicine is a global specialty and epidemiologic research among countries provides important data on availability of critical care resources, best practices, and alternative options for delivery of care. Understanding the diversity across healthcare systems allows us to explore that rich variability and understand better the nature of delivery systems and their impact on outcomes. However, because the delivery of ICU services is complex (for example, interplay of bed availability, cultural norms and population case-mix), the diversity among countries also creates challenges when interpreting and applying data. This complexity has profound influences on reported outcomes, often obscuring true differences. Future research should emphasize determination of resource data worldwide in order to understand current practices in different countries; this will permit rational pandemic and disaster planning, allow comparisons of in-ICU processes of care, and facilitate addition of pre- and post-ICU patient data to better interpret outcomes.

Interactions Among Plants, Insects, and Microbes: Elucidation of Inter-Organismal Chemical Communications in Agricultural Ecology.

PubMed

Beck, John J; Alborn, Hans; Block, Anna; Christensen, Shawn A; Hunter, Charles T; Rering, Caitlin C; Seidl-Adams, Irmgard; Stuhl, Charles; Torto, Baldwyn; Tumlinson, James H

2018-06-12

The last two decades have witnessed a sustained increase in the study of plant-emitted volatiles and their role in plant-insect, plant-microbe and plant-plant interactions. While each of these binary systems involves complex chemical and biochemical processes between two organisms, the progression of increasing complexity of a ternary system (i.e., plant-insect-microbe), and the study of a ternary system requires non-trivial planning. This planning can include: an experimental design that factors in potential overarching ecological interactions regarding the binary or ternary system; correctly identifying and understanding unexpected observations that may occur during the experiment; and, thorough interpretation of the resultant data. This challenge of planning, performing and interpreting a plant's defensive response to multiple biotic stressors will be even greater when abiotic stressors (i.e., temperature or water) are factored into the system. To fully understand the system, we need to not only continue to investigate and understand the volatile profiles, but also include and understand the biochemistry of the plant's response to these stressors. In this paper, we provide examples and discuss interaction considerations with respect to how readers and future authors of the Journal of Agricultural and Food Chemistry can contribute their expertise toward the extraction and interpretation of chemical information exchanged between agricultural commodities and their associated pests. This holistic, multidisciplinary and thoughtful approach to interactions of plants, insects, and microbes, and the resultant response of the plants, can lead to a better understanding of agricultural ecology, in turn leading to practical and viable solutions to agricultural problems.

Prediction of Rate Constant for Supramolecular Systems with Multiconfigurations.

PubMed

Guo, Tao; Li, Haiyan; Wu, Li; Guo, Zhen; Yin, Xianzhen; Wang, Caifen; Sun, Lixin; Shao, Qun; Gu, Jingkai; York, Peter; Zhang, Jiwen

2016-02-25

The control of supramolecular systems requires a thorough understanding of their dynamics, especially on a molecular level. It is extremely difficult to determine the thermokinetic parameters of supramolecular systems, such as drug-cyclodextrin complexes with fast association/dissociation processes by experimental techniques. In this paper, molecular modeling combined with novel mathematical relationships integrating the thermodynamic/thermokinetic parameters of a series of isomeric multiconfigurations to predict the overall parameters in a range of pH values have been employed to study supramolecular dynamics at the molecular level. A suitable form of Eyring's equation was derived and a two-stage model was introduced. The new approach enabled accurate prediction of the apparent dissociation/association (k(off)/k(on)) and unbinding/binding (k-r/kr) rate constants of the ubiquitous multiconfiguration complexes of the supramolecular system. The pyronine Y (PY) was used as a model system for the validation of the presented method. Interestingly, the predicted k(off) value ((40 ± 1) × 10(5) s(-1), 298 K) of PY is largely in agreement with that previously determined by fluorescence correlation spectroscopy ((5 ± 3) × 10(5) s(-1), 298 K). Moreover, the k(off)/k(on) and k-r/kr for flurbiprofen-β-cylcodextrin and ibuprofen-β-cyclodextrin systems were also predicted and suggested that the association processes are diffusion-controlled. The methodology is considered to be especially useful in the design and selection of excipients for a supramolecular system with preferred association and dissociation rate constants and understanding their mechanisms. It is believed that this new approach could be applicable to a wide range of ligand-receptor supramolecular systems and will surely help in understanding their complex mechanism.

Emergence of Scale-Free Syntax Networks

NASA Astrophysics Data System (ADS)

Corominas-Murtra, Bernat; Valverde, Sergi; Solé, Ricard V.

The evolution of human language allowed the efficient propagation of nongenetic information, thus creating a new form of evolutionary change. Language development in children offers the opportunity of exploring the emergence of such complex communication system and provides a window to understanding the transition from protolanguage to language. Here we present the first analysis of the emergence of syntax in terms of complex networks. A previously unreported, sharp transition is shown to occur around two years of age from a (pre-syntactic) tree-like structure to a scale-free, small world syntax network. The observed combinatorial patterns provide valuable data to understand the nature of the cognitive processes involved in the acquisition of syntax, introducing a new ingredient to understand the possible biological endowment of human beings which results in the emergence of complex language. We explore this problem by using a minimal, data-driven model that is able to capture several statistical traits, but some key features related to the emergence of syntactic complexity display important divergences.

Managed care: employers' influence on the health care system.

PubMed

Corder, K T; Phoon, J; Barter, M

1996-01-01

Health care reform is a complex issue involving many key sectors including providers, consumers, insurers, employers, and the government. System changes must involve all sectors for reform to be effective. Each sector has a responsibility to understand not only its own role in the health care system, but the roles of others as well. The role of business employers is often not apparent to health care providers, especially nurses. Understanding the influence employers have on the health care system is vital if providers want to be proactive change agents ensuring quality care.

A systems biology approach to studying Tai Chi, physiological complexity and healthy aging: design and rationale of a pragmatic randomized controlled trial.

PubMed

Wayne, Peter M; Manor, Brad; Novak, Vera; Costa, Madelena D; Hausdorff, Jeffrey M; Goldberger, Ary L; Ahn, Andrew C; Yeh, Gloria Y; Peng, C-K; Lough, Matthew; Davis, Roger B; Quilty, Mary T; Lipsitz, Lewis A

2013-01-01

Aging is typically associated with progressive multi-system impairment that leads to decreased physical and cognitive function and reduced adaptability to stress. Due to its capacity to characterize complex dynamics within and between physiological systems, the emerging field of complex systems biology and its array of quantitative tools show great promise for improving our understanding of aging, monitoring senescence, and providing biomarkers for evaluating novel interventions, including promising mind-body exercises, that treat age-related disease and promote healthy aging. An ongoing, two-arm randomized clinical trial is evaluating the potential of Tai Chi mind-body exercise to attenuate age-related loss of complexity. A total of 60 Tai Chi-naïve healthy older adults (aged 50-79) are being randomized to either six months of Tai Chi training (n=30), or to a waitlist control receiving unaltered usual medical care (n=30). Our primary outcomes are complexity-based measures of heart rate, standing postural sway and gait stride interval dynamics assessed at 3 and 6months. Multiscale entropy and detrended fluctuation analysis are used as entropy- and fractal-based measures of complexity, respectively. Secondary outcomes include measures of physical and psychological function and tests of physiological adaptability also assessed at 3 and 6months. Results of this study may lead to novel biomarkers that help us monitor and understand the physiological processes of aging and explore the potential benefits of Tai Chi and related mind-body exercises for healthy aging. Copyright © 2012 Elsevier Inc. All rights reserved.

Understanding patient safety performance and educational needs using the 'Safety-II' approach for complex systems.

PubMed

McNab, Duncan; Bowie, Paul; Morrison, Jill; Ross, Alastair

2016-11-01

Participation in projects to improve patient safety is a key component of general practice (GP) specialty training, appraisal and revalidation. Patient safety training priorities for GPs at all career stages are described in the Royal College of General Practitioners' curriculum. Current methods that are taught and employed to improve safety often use a 'find-and-fix' approach to identify components of a system (including humans) where performance could be improved. However, the complex interactions and inter-dependence between components in healthcare systems mean that cause and effect are not always linked in a predictable manner. The Safety-II approach has been proposed as a new way to understand how safety is achieved in complex systems that may improve quality and safety initiatives and enhance GP and trainee curriculum coverage. Safety-II aims to maximise the number of events with a successful outcome by exploring everyday work. Work-as-done often differs from work-as-imagined in protocols and guidelines and various ways to achieve success, dependent on work conditions, may be possible. Traditional approaches to improve the quality and safety of care often aim to constrain variability but understanding and managing variability may be a more beneficial approach. The application of a Safety-II approach to incident investigation, quality improvement projects, prospective analysis of risk in systems and performance indicators may offer improved insight into system performance leading to more effective change. The way forward may be to combine the Safety-II approach with 'traditional' methods to enhance patient safety training, outcomes and curriculum coverage.

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

PubMed

Cohen, Alan A

2016-02-01

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

Approximate Matching as a Key Technique in Organization of Natural and Artificial Intelligence

NASA Technical Reports Server (NTRS)

Mack, Marilyn; Lapir, Gennadi M.; Berkovich, Simon

2000-01-01

The basic property of an intelligent system, natural or artificial, is "understanding". We consider the following formalization of the idea of "understanding" among information systems. When system I issues a request to system 2, it expects a certain kind of desirable reaction. If such a reaction occurs, system I assumes that its request was "understood". In application to simple, "push-button" systems the situation is trivial because in a small system the required relationship between input requests and desired outputs could be specified exactly. As systems grow, the situation becomes more complex and matching between requests and actions becomes approximate.

Using Activity Theory to Understand Learning Design Requirements of Patient Self-Management Environments

ERIC Educational Resources Information Center

Schaffer, Scott P.; Reyes, Lisette; Kim, Hannah; Collins, Bart

2010-01-01

Learning designs aimed at supporting transformational change could significantly benefit from the adoption of socio-historical and socio-cultural analysis approaches. Such systemic perspectives are gaining more importance in education as they facilitate understanding of complex interactions between learning environments and human activity. The…

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

NASA Astrophysics Data System (ADS)

Goswami, Monojoy; Sumpter, Bobby

2014-03-01

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

Diversity Driven Coexistence: Collective Stability in the Cyclic Competition of Three Species

NASA Astrophysics Data System (ADS)

Bassler, Kevin E.; Frey, Erwin; Zia, R. K. P.

2015-03-01

The basic physics of collective behavior are often difficult to quantify and understand, particularly when the system is driven out of equilibrium. Many complex systems are usefully described as complex networks, consisting of nodes and links. The nodes specify individual components of the system and the links describe their interactions. When both nodes and links change dynamically, or `co-evolve', as happens in many realistic systems, complex mathematical structures are encountered, posing challenges to our understanding. In this context, we introduce a minimal system of node and link degrees of freedom, co-evolving with stochastic rules. Specifically, we show that diversity of social temperament (intro- or extroversion) can produce collective stable coexistence when three species compete cyclically. It is well-known that when only extroverts exist in a stochastic rock-paper-scissors game, or in a conserved predator-prey, Lotka-Volterra system, extinction occurs at times of O(N), where N is the number of nodes. We find that when both introverts and extroverts exist, where introverts sever social interactions and extroverts create them, collective coexistence prevails in long-living, quasi-stationary states. Work supported by the NSF through Grants DMR-1206839 (KEB) and DMR-1244666 (RKPZ), and by the AFOSR and DARPA through Grant FA9550-12-1-0405 (KEB).

GESA--a two-dimensional processing system using knowledge base techniques.

PubMed

Rowlands, D G; Flook, A; Payne, P I; van Hoff, A; Niblett, T; McKee, S

1988-12-01

The successful analysis of two-dimensional (2-D) polyacrylamide electrophoresis gels demands considerable experience and understanding of the protein system under investigation as well as knowledge of the separation technique itself. The present work concerns the development of a computer system for analysing 2-D electrophoretic separations which incorporates concepts derived from artificial intelligence research such that non-experts can use the technique as a diagnostic or identification tool. Automatic analysis of 2-D gel separations has proved to be extremely difficult using statistical methods. Non-reproducibility of gel separations is also difficult to overcome using automatic systems. However, the human eye is extremely good at recognising patterns in images, and human intervention in semi-automatic computer systems can reduce the computational complexities of fully automatic systems. Moreover, the expertise and understanding of an "expert" is invaluable in reducing system complexity if it can be encapsulated satisfactorily in an expert system. The combination of user-intervention in the computer system together with the encapsulation of expert knowledge characterises the present system. The domain within which the system has been developed is that of wheat grain storage proteins (gliadins) which exhibit polymorphism to such an extent that cultivars can be uniquely identified by their gliadin patterns. The system can be adapted to other domains where a range of polymorpic protein sub-units exist. In its generalised form, the system can also be used for comparing more complex 2-D gel electrophoretic separations.

Honey bee surveillance: a tool for understanding and improving honey bee health.

PubMed

Lee, Kathleen; Steinhauer, Nathalie; Travis, Dominic A; Meixner, Marina D; Deen, John; vanEngelsdorp, Dennis

2015-08-01

Honey bee surveillance systems are increasingly used to characterize honey bee health and disease burdens of bees in different regions and/or over time. In addition to quantifying disease prevalence, surveillance systems can identify risk factors associated with colony morbidity and mortality. Surveillance systems are often observational, and prove particularly useful when searching for risk factors in real world complex systems. We review recent examples of surveillance systems with particular emphasis on how these efforts have helped increase our understanding of honey bee health. Copyright © 2015 Elsevier Inc. All rights reserved.

Synchronization in complex networks

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

Arenas, A.; Diaz-Guilera, A.; Moreno, Y.

Synchronization processes in populations of locally interacting elements are in the focus of intense research in physical, biological, chemical, technological and social systems. The many efforts devoted to understand synchronization phenomena in natural systems take now advantage of the recent theory of complex networks. In this review, we report the advances in the comprehension of synchronization phenomena when oscillating elements are constrained to interact in a complex network topology. We also overview the new emergent features coming out from the interplay between the structure and the function of the underlying pattern of connections. Extensive numerical work as well as analyticalmore » approaches to the problem are presented. Finally, we review several applications of synchronization in complex networks to different disciplines: biological systems and neuroscience, engineering and computer science, and economy and social sciences.« less

Higher Education Provision Using Systems Thinking Approach--Case Studies

ERIC Educational Resources Information Center

Dhukaram, Anandhi Vivekanandan; Sgouropoulou, Cleo; Feldman, Gerald; Amini, Ardavan

2018-01-01

The purpose of this paper is to highlight the complexities involved in higher education provision and how systems thinking and socio-technical systems (STS) thinking approach can be used to understand the education ecosystem. Systems thinking perspective is provided using two case studies: the development of European Learner Mobility (EuroLM)…

Structural complexity, movement bias, and metapopulation extinction risk in dendritic ecological networks

USGS Publications Warehouse

Campbell Grant, Evan H.

2011-01-01

Spatial complexity in metacommunities can be separated into 3 main components: size (i.e., number of habitat patches), spatial arrangement of habitat patches (network topology), and diversity of habitat patch types. Much attention has been paid to lattice-type networks, such as patch-based metapopulations, but interest in understanding ecological networks of alternative geometries is building. Dendritic ecological networks (DENs) include some increasingly threatened ecological systems, such as caves and streams. The restrictive architecture of dendritic ecological networks might have overriding implications for species persistence. I used a modeling approach to investigate how number and spatial arrangement of habitat patches influence metapopulation extinction risk in 2 DENs of different size and topology. Metapopulation persistence was higher in larger networks, but this relationship was mediated by network topology and the dispersal pathways used to navigate the network. Larger networks, especially those with greater topological complexity, generally had lower extinction risk than smaller and less-complex networks, but dispersal bias and magnitude affected the shape of this relationship. Applying these general results to real systems will require empirical data on the movement behavior of organisms and will improve our understanding of the implications of network complexity on population and community patterns and processes.

Connectivity in the human brain dissociates entropy and complexity of auditory inputs☆

PubMed Central

Nastase, Samuel A.; Iacovella, Vittorio; Davis, Ben; Hasson, Uri

2015-01-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. PMID:25536493

Biological robustness.

PubMed

Kitano, Hiroaki

2004-11-01

Robustness is a ubiquitously observed property of biological systems. It is considered to be a fundamental feature of complex evolvable systems. It is attained by several underlying principles that are universal to both biological organisms and sophisticated engineering systems. Robustness facilitates evolvability and robust traits are often selected by evolution. Such a mutually beneficial process is made possible by specific architectural features observed in robust systems. But there are trade-offs between robustness, fragility, performance and resource demands, which explain system behaviour, including the patterns of failure. Insights into inherent properties of robust systems will provide us with a better understanding of complex diseases and a guiding principle for therapy design.

Systems biology perspectives on minimal and simpler cells.

PubMed

Xavier, Joana C; Patil, Kiran Raosaheb; Rocha, Isabel

2014-09-01

The concept of the minimal cell has fascinated scientists for a long time, from both fundamental and applied points of view. This broad concept encompasses extreme reductions of genomes, the last universal common ancestor (LUCA), the creation of semiartificial cells, and the design of protocells and chassis cells. Here we review these different areas of research and identify common and complementary aspects of each one. We focus on systems biology, a discipline that is greatly facilitating the classical top-down and bottom-up approaches toward minimal cells. In addition, we also review the so-called middle-out approach and its contributions to the field with mathematical and computational models. Owing to the advances in genomics technologies, much of the work in this area has been centered on minimal genomes, or rather minimal gene sets, required to sustain life. Nevertheless, a fundamental expansion has been taking place in the last few years wherein the minimal gene set is viewed as a backbone of a more complex system. Complementing genomics, progress is being made in understanding the system-wide properties at the levels of the transcriptome, proteome, and metabolome. Network modeling approaches are enabling the integration of these different omics data sets toward an understanding of the complex molecular pathways connecting genotype to phenotype. We review key concepts central to the mapping and modeling of this complexity, which is at the heart of research on minimal cells. Finally, we discuss the distinction between minimizing the number of cellular components and minimizing cellular complexity, toward an improved understanding and utilization of minimal and simpler cells. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

New and improved proteomics technologies for understanding complex biological systems: Addressing a grand challenge in the life sciences

PubMed Central

Hood, Leroy E.; Omenn, Gilbert S.; Moritz, Robert L.; Aebersold, Ruedi; Yamamoto, Keith R.; Amos, Michael; Hunter-Cevera, Jennie; Locascio, Laurie

2014-01-01

This White Paper sets out a Life Sciences Grand Challenge for Proteomics Technologies to enhance our understanding of complex biological systems, link genomes with phenotypes, and bring broad benefits to the biosciences and the US economy. The paper is based on a workshop hosted by the National Institute of Standards and Technology (NIST) in Gaithersburg, MD, 14–15 February 2011, with participants from many federal R&D agencies and research communities, under the aegis of the US National Science and Technology Council (NSTC). Opportunities are identified for a coordinated R&D effort to achieve major technology-based goals and address societal challenges in health, agriculture, nutrition, energy, environment, national security, and economic development. PMID:22807061

Considerations Regardingthe Integration-Intrication Processin the Nature and Technology

NASA Astrophysics Data System (ADS)

Tecaru Berekmeri, Camelia Velia; Blebea, Ioan

2014-11-01

The big challenges in education and R&D activities in the century just started are related on the complexity and transdisciplinarity understanding and promotion.The approaches are necessary in order to understand the unity of the world we live in through the unity of knowledge.The complexity is the result of the integration process.The paper presents fundamentals of the integration-intrication process in the nature and technology.The concept of integronics and the basic principles of the integration process are outlined too. Also the main features of mechatronics as environment for transdisciplinarity learning and the concept of integral education promotion are presented.The advanced mechatronics and the embedded systems are fundamentals of the cyberphysical systems of the future

Toward the modelling of safety violations in healthcare systems.

PubMed

Catchpole, Ken

2013-09-01

When frontline staff do not adhere to policies, protocols, or checklists, managers often regard these violations as indicating poor practice or even negligence. More often than not, however, these policy and protocol violations reflect the efforts of well intentioned professionals to carry out their work efficiently in the face of systems poorly designed to meet the diverse demands of patient care. Thus, non-compliance with institutional policies and protocols often signals a systems problem, rather than a people problem, and can be influenced among other things by training, competing goals, context, process, location, case complexity, individual beliefs, the direct or indirect influence of others, job pressure, flexibility, rule definition, and clinician-centred design. Three candidates are considered for developing a model of safety behaviour and decision making. The dynamic safety model helps to understand the relationship between systems designs and human performance. The theory of planned behaviour suggests that intention is a function of attitudes, social norms and perceived behavioural control. The naturalistic decision making paradigm posits that decisions are based on a wider view of multiple patients, expertise, systems complexity, behavioural intention, individual beliefs and current understanding of the system. Understanding and predicting behavioural safety decisions could help us to encourage compliance to current processes and to design better interventions.

How synthetic membrane systems contribute to the understanding of lipid-driven endocytosis.

PubMed

Schubert, Thomas; Römer, Winfried

2015-11-01

Synthetic membrane systems, such as giant unilamellar vesicles and solid supported lipid bilayers, have widened our understanding of biological processes occurring at or through membranes. Artificial systems are particularly suited to study the inherent properties of membranes with regard to their components and characteristics. This review critically reflects the emerging molecular mechanism of lipid-driven endocytosis and the impact of model membrane systems in elucidating the complex interplay of biomolecules within this process. Lipid receptor clustering induced by binding of several toxins, viruses and bacteria to the plasma membrane leads to local membrane bending and formation of tubular membrane invaginations. Here, lipid shape, and protein structure and valency are the essential parameters in membrane deformation. Combining observations of complex cellular processes and their reconstitution on minimal systems seems to be a promising future approach to resolve basic underlying mechanisms. This article is part of a Special Issue entitled: Mechanobiology. Copyright © 2015 Elsevier B.V. All rights reserved.

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

The clinical educator and complexity: a review.

PubMed

Schoo, Adrian; Kumar, Koshila

2018-02-08

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

Auditory Processing of Complex Sounds Across Frequency Channels.

DTIC Science & Technology

1992-06-26

towards gaining an understanding how the auditory system processes complex sounds. "The results of binaural psychophysical experiments in human subjects...suggest (1) that spectrally synthetic binaural processing is the rule when the number of components in the tone complex are relatively few (less than...10) and there are no dynamic binaural cues to aid segregation of the target from the background, and (2) that waveforms having large effective

Understanding Parkinson Disease: A Complex and Multifaceted Illness.

PubMed

Gopalakrishna, Apoorva; Alexander, Sheila A

2015-12-01

Parkinson disease is an incredibly complex and multifaceted illness affecting millions of people in the United States. Parkinson disease is characterized by progressive dopaminergic neuronal dysfunction and loss, leading to debilitating motor, cognitive, and behavioral symptoms. Parkinson disease is an enigmatic illness that is still extensively researched today to search for a better understanding of the disease, develop therapeutic interventions to halt or slow progression of the disease, and optimize patient outcomes. This article aims to examine in detail the normal function of the basal ganglia and dopaminergic neurons in the central nervous system, the etiology and pathophysiology of Parkinson disease, related signs and symptoms, current treatment, and finally, the profound impact of understanding the disease on nursing care.

Connections Matter: Social Networks and Lifespan Health in Primate Translational Models

PubMed Central

McCowan, Brenda; Beisner, Brianne; Bliss-Moreau, Eliza; Vandeleest, Jessica; Jin, Jian; Hannibal, Darcy; Hsieh, Fushing

2016-01-01

Humans live in societies full of rich and complex relationships that influence health. The ability to improve human health requires a detailed understanding of the complex interplay of biological systems that contribute to disease processes, including the mechanisms underlying the influence of social contexts on these biological systems. A longitudinal computational systems science approach provides methods uniquely suited to elucidate the mechanisms by which social systems influence health and well-being by investigating how they modulate the interplay among biological systems across the lifespan. In the present report, we argue that nonhuman primate social systems are sufficiently complex to serve as model systems allowing for the development and refinement of both analytical and theoretical frameworks linking social life to health. Ultimately, developing systems science frameworks in nonhuman primate models will speed discovery of the mechanisms that subserve the relationship between social life and human health. PMID:27148103

The Physics of Life and Quantum Complex Matter: A Case of Cross-Fertilization

PubMed Central

Poccia, Nicola; Bianconi, Antonio

2011-01-01

Progress in the science of complexity, from the Big Bang to the coming of humankind, from chemistry and biology to geosciences and medicine, and from materials engineering to energy sciences, is leading to a shift of paradigm in the physical sciences. The focus is on the understanding of the non-equilibrium process in fine tuned systems. Quantum complex materials such as high temperature superconductors and living matter are both non-equilibrium and fine tuned systems. These topics have been subbjects of scientific discussion in the Rome Symposium on the “Quantum Physics of Living Matter”. PMID:26791661

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.

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…

Assessment of national biomass in complex forests and technical capacity scenarios

Treesearch

Matieu Henry; Javier G. P. Gamarra; Gael Sola; Luca Birigazzi; Emily Donegan; Julian Murillo; Tommaso Chiti; Nicolas Picard; Miguel Cifuentes-Jara; S Sandeep; Laurent Saint-André

2015-01-01

Understanding forest ecosystems is paramount for their sustainable management and for the livelihoods and ecosystem services which depend on them. However, the complexity and diversity of these systems poses a challenge to interpreting data patterns. The availability and accessibility of data and tools often determine the method selected for forest assessment. Capacity...

Life in the Hive: Supporting Inquiry into Complexity within the Zone of Proximal Development

ERIC Educational Resources Information Center

Danish, Joshua A.; Peppler, Kylie; Phelps, David; Washington, DiAnna

2011-01-01

Research into students' understanding of complex systems typically ignores young children because of misinterpretations of young children's competencies. Furthermore, studies that do recognize young children's competencies tend to focus on what children can do in isolation. As an alternative, we propose an approach to designing for young children…

Evaluating Action Learning: A Critical Realist Complex Network Theory Approach

ERIC Educational Resources Information Center

Burgoyne, John G.

2010-01-01

This largely theoretical paper will argue the case for the usefulness of applying network and complex adaptive systems theory to an understanding of action learning and the challenge it is evaluating. This approach, it will be argued, is particularly helpful in the context of improving capability in dealing with wicked problems spread around…

Designing and Developing Assessments of Complex Thinking in Mathematics for the Middle Grades

ERIC Educational Resources Information Center

Graf, Edith Aurora; Arieli-Attali, Meirav

2015-01-01

Designing an assessment system for complex thinking in mathematics involves decisions at every stage, from how to represent the target competencies to how to interpret evidence from student performances. Beyond learning to solve particular problems in a particular area, learning mathematics with understanding involves comprehending connections…

An integrated view of complex landscapes: a big data-model integration approach to trans-disciplinary science

USDA-ARS?s Scientific Manuscript database

The Earth is a complex system comprised of many interacting spatial and temporal scales. Understanding, predicting, and managing for these dynamics requires a trans-disciplinary integrated approach. Although there have been calls for this integration, a general approach is needed. We developed a Tra...

Chaordic Systems Thinking: Some Suggestions for a Complexity Framework to Inform a Learning Organization

ERIC Educational Resources Information Center

van Eijnatten, Frans M.

2004-01-01

This contribution suggests a conceptual framework for using complexity to understand human interactions in learning organizations. The particular lens adopted for this purpose is that of the Chaos perspective. The following general concepts are described: discontinuous growth, attractors: their basins and landscapes, the chaordic properties of…

Spatial Characterization of Riparian Buffer Effects on Sediment Loads from Watershed Systems

EPA Science Inventory

Understanding all watershed systems and their interactions is a complex, but critical, undertaking when developing practices designed to reduce topsoil loss and chemical/nutrient transport from agricultural fields. The presence of riparian buffer vegetation in agricultural lands...

Teaching Environmental Geochemistry: An Authentic Inquiry Approach

ERIC Educational Resources Information Center

Koretsky, Carla M.; Petcovic, Heather L.; Rowbotham, Katherine L.

2012-01-01

A field-based environmental geochemistry course was developed at Western Michigan University for undergraduate geosciences and environmental studies students to (1) improve student understanding of complex environmental systems, specifically targeting lake systems; (2) facilitate student development of professional-level, field- and…

SYSTEM INSTALLATION AND OPERATION MANUAL FOR THE EPA THIRD-GENERATION AIR QUALITY MODELING SYSTEM (MODELS-3) VERSION 3.0

EPA Science Inventory

Models-3 is a flexible software system designed to simplify the development and use of environmental assessment and other decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of atmospheri...

Cognitive Complexity and Verbal Response Mode Use in Discussion.

ERIC Educational Resources Information Center

Kline, Susan L.; And Others

1990-01-01

Uses William B. Stiles' discourse analysis system to determine whether there are general differences in the way individuals varying in construct system development use their utterances to establish understanding with each other. Finds that construct system development was positively correlated with edification and question response mode use, and…

Theorising Systemic Change: Learning from the Academisation Project in England

ERIC Educational Resources Information Center

Rayner, Stephen M.; Courtney, Steven J.; Gunter, Helen M.

2018-01-01

The research reported in this article contributes new understandings of systemic change by studying the form of system redesign known in England as "academisation." The data illuminate tensions within the neoliberal policy complex that are surfaced in a single secondary school. Although several studies have described academy conversions…

A Framework for Understanding and Assessing Systemic Change.

ERIC Educational Resources Information Center

Anderson, Beverly L.

The education system, like most organizational structures, needs fundamental changes to keep pace with the social and economic conditions of an increasingly complex global society. Taking an aerial view, this paper describes the topography of systemic change to provide multiple stakeholders a better vantage point for communicating and making…

Quantum Approximate Methods for the Atomistic Modeling of Multicomponent Alloys. Chapter 7

NASA Technical Reports Server (NTRS)

Bozzolo, Guillermo; Garces, Jorge; Mosca, Hugo; Gargano, pablo; Noebe, Ronald D.; Abel, Phillip

2007-01-01

This chapter describes the role of quantum approximate methods in the understanding of complex multicomponent alloys at the atomic level. The need to accelerate materials design programs based on economical and efficient modeling techniques provides the framework for the introduction of approximations and simplifications in otherwise rigorous theoretical schemes. As a promising example of the role that such approximate methods might have in the development of complex systems, the BFS method for alloys is presented and applied to Ru-rich Ni-base superalloys and also to the NiAI(Ti,Cu) system, highlighting the benefits that can be obtained from introducing simple modeling techniques to the investigation of such complex systems.

Reflecting on the efficacy of cognitive mapping for decision-making in intellectual disability care: a case study.

PubMed

Duryan, Meri; Nikolik, Dragan; van Merode, Godefridus; Curfs, Leopold M G

2015-01-01

The central aspect of this study is a set of reflections on the efficacy of soft operational research techniques in understanding the dynamics of a complex system such as intellectual disability (ID) care providers. Organizations providing services to ID patients are complex and have many interacting stakeholders with often different and competing interests. Understanding the causes for failures in complex systems is crucial for appreciating the multiple perspectives of the key stakeholders of the system. Knowing the factors that adversely affect delivery of a patient-centred care by ID provider organizations offers the potential for identifying more effective resource-allocation solutions. The authors suggest cognitive mapping as a starting point for system dynamics modelling of optimal resource-allocation projects in ID care. The application of the method is illustrated via a case study in one of the ID care providers in the Netherlands. The paper discusses some of the practical implications of applying problem-structuring methods that support gathering feedback from vulnerable service users and front-line workers. The authors concluded that cognitive mapping technique can assist the management of healthcare organizations in strategic decision-making. Copyright © 2013 John Wiley & Sons, Ltd.

Computer modelling of epilepsy.

PubMed

Lytton, William W

2008-08-01

Epilepsy is a complex set of disorders that can involve many areas of the cortex, as well as underlying deep-brain systems. The myriad manifestations of seizures, which can be as varied as déjà vu and olfactory hallucination, can therefore give researchers insights into regional functions and relations. Epilepsy is also complex genetically and pathophysiologically: it involves microscopic (on the scale of ion channels and synaptic proteins), macroscopic (on the scale of brain trauma and rewiring) and intermediate changes in a complex interplay of causality. It has long been recognized that computer modelling will be required to disentangle causality, to better understand seizure spread and to understand and eventually predict treatment efficacy. Over the past few years, substantial progress has been made in modelling epilepsy at levels ranging from the molecular to the socioeconomic. We review these efforts and connect them to the medical goals of understanding and treating the disorder.

Representation of People's Decisions in Health Information Systems. A Complementary Approach for Understanding Health Care Systems and Population Health.

PubMed

Gonzalez Bernaldo de Quiros, Fernan; Dawidowski, Adriana R; Figar, Silvana

2017-02-01

In this study, we aimed: 1) to conceptualize the theoretical challenges facing health information systems (HIS) to represent patients' decisions about health and medical treatments in everyday life; 2) to suggest approaches for modeling these processes. The conceptualization of the theoretical and methodological challenges was discussed in 2015 during a series of interdisciplinary meetings attended by health informatics staff, epidemiologists and health professionals working in quality management and primary and secondary prevention of chronic diseases of the Hospital Italiano de Buenos Aires, together with sociologists, anthropologists and e-health stakeholders. HIS are facing the need and challenge to represent social human processes based on constructivist and complexity theories, which are the current frameworks of human sciences for understanding human learning and socio-cultural changes. Computer systems based on these theories can model processes of social construction of concrete and subjective entities and the interrelationships between them. These theories could be implemented, among other ways, through the mapping of health assets, analysis of social impact through community trials and modeling of complexity with system simulation tools. This analysis suggested the need to complement the traditional linear causal explanations of disease onset (and treatments) that are the bases for models of analysis of HIS with constructivist and complexity frameworks. Both may enlighten the complex interrelationships among patients, health services and the health system. The aim of this strategy is to clarify people's decision making processes to improve the efficiency, quality and equity of the health services and the health system.

A conceptual connectivity framework for understanding geomorphic change in human-impacted fluvial systems

NASA Astrophysics Data System (ADS)

Poeppl, Ronald E.; Keesstra, Saskia D.; Maroulis, Jerry

2017-01-01

Human-induced landscape change is difficult to predict due to the complexity inherent in both geomorphic and social systems as well as due to the coupling relationships between them. To better understand system complexity and system response to changing inputs, "connectivity thinking" has become an important recent paradigm within various disciplines including ecology, hydrology and geomorphology. With the presented conceptual connectivity framework on geomorphic change in human-impacted fluvial systems a cautionary note is flagged regarding the need (i) to include and to systematically conceptualise the role of different types of human agency in altering connectivity relationships in geomorphic systems and (ii) to integrate notions of human-environment interactions to connectivity concepts in geomorphology to better explain causes and trajectories of landscape change. Geomorphic response of fluvial systems to human disturbance is shown to be determined by system-specific boundary conditions (incl. system history, related legacy effects and lag times), vegetation dynamics and human-induced functional relationships (i.e. feedback mechanisms) between the different spatial dimensions of connectivity. It is further demonstrated how changes in social systems can trigger a process-response feedback loop between social and geomorphic systems that further governs the trajectory of landscape change in coupled human-geomorphic systems.

Functional vision and cognition in infants with congenital disorders of the peripheral visual system.

PubMed

Dale, Naomi; Sakkalou, Elena; O'Reilly, Michelle; Springall, Clare; De Haan, Michelle; Salt, Alison

2017-07-01

To investigate how vision relates to early development by studying vision and cognition in a national cohort of 1-year-old infants with congenital disorders of the peripheral visual system and visual impairment. This was a cross-sectional observational investigation of a nationally recruited cohort of infants with 'simple' and 'complex' congenital disorders of the peripheral visual system. Entry age was 8 to 16 months. Vision level (Near Detection Scale) and non-verbal cognition (sensorimotor understanding, Reynell Zinkin Scales) were assessed. Parents completed demographic questionnaires. Of 90 infants (49 males, 41 females; mean 13mo, standard deviation [SD] 2.5mo; range 7-17mo); 25 (28%) had profound visual impairment (light perception at best) and 65 (72%) had severe visual impairment (basic 'form' vision). The Near Detection Scale correlated significantly with sensorimotor understanding developmental quotients in the 'total', 'simple', and 'complex' groups (all p<0.001). Age and vision accounted for 48% of sensorimotor understanding variance. Infants with profound visual impairment, especially in the 'complex' group with congenital disorders of the peripheral visual system with known brain involvement, showed the greatest cognitive delay. Lack of vision is associated with delayed early-object manipulative abilities and concepts; 'form' vision appeared to support early developmental advance. This paper provides baseline characteristics for cross-sectional and longitudinal follow-up investigations in progress. A methodological strength of the study was the representativeness of the cohort according to national epidemiological and population census data. © 2017 Mac Keith Press.

Getting a Grip on Complexes

PubMed Central

Nie, Yan; Viola, Cristina; Bieniossek, Christoph; Trowitzsch, Simon; Vijay-achandran, Lakshmi Sumitra; Chaillet, Maxime; Garzoni, Frederic; Berger, Imre

2009-01-01

We are witnessing tremendous advances in our understanding of the organization of life. Complete genomes are being deciphered with ever increasing speed and accuracy, thereby setting the stage for addressing the entire gene product repertoire of cells, towards understanding whole biological systems. Advances in bioinformatics and mass spectrometric techniques have revealed the multitude of interactions present in the proteome. Multiprotein complexes are emerging as a paramount cornerstone of biological activity, as many proteins appear to participate, stably or transiently, in large multisubunit assemblies. Analysis of the architecture of these assemblies and their manifold interactions is imperative for understanding their function at the molecular level. Structural genomics efforts have fostered the development of many technologies towards achieving the throughput required for studying system-wide single proteins and small interaction motifs at high resolution. The present shift in focus towards large multiprotein complexes, in particular in eukaryotes, now calls for a likewise concerted effort to develop and provide new technologies that are urgently required to produce in quality and quantity the plethora of multiprotein assemblies that form the complexome, and to routinely study their structure and function at the molecular level. Current efforts towards this objective are summarized and reviewed in this contribution. PMID:20514218

Process mining is an underutilized clinical research tool in transfusion medicine.

PubMed

Quinn, Jason G; Conrad, David M; Cheng, Calvino K

2017-03-01

To understand inventory performance, transfusion services commonly use key performance indicators (KPIs) as summary descriptors of inventory efficiency that are graphed, trended, and used to benchmark institutions. Here, we summarize current limitations in KPI-based evaluation of blood bank inventory efficiency and propose process mining as an ideal methodology for application to inventory management research to improve inventory flows and performance. The transit of a blood product from inventory receipt to final disposition is complex and relates to many internal and external influences, and KPIs may be inadequate to fully understand the complexity of the blood supply chain and how units interact with its processes. Process mining lends itself well to analysis of blood bank inventories, and modern laboratory information systems can track nearly all of the complex processes that occur in the blood bank. Process mining is an analytical tool already used in other industries and can be applied to blood bank inventory management and research through laboratory information systems data using commercial applications. Although the current understanding of real blood bank inventories is value-centric through KPIs, it potentially can be understood from a process-centric lens using process mining. © 2017 AABB.

When 'solutions of yesterday become problems of today': crisis-ridden decision making in a complex adaptive system (CAS)--the Additional Duty Hours Allowance in Ghana.

PubMed

Agyepong, Irene Akua; Kodua, Augustina; Adjei, Sam; Adam, Taghreed

2012-10-01

Implementation of policies (decisions) in the health sector is sometimes defeated by the system's response to the policy itself. This can lead to counter-intuitive, unanticipated, or more modest effects than expected by those who designed the policy. The health sector fits the characteristics of complex adaptive systems (CAS) and complexity is at the heart of this phenomenon. Anticipating both positive and negative effects of policy decisions, understanding the interests, power and interaction between multiple actors; and planning for the delayed and distal impact of policy decisions are essential for effective decision making in CAS. Failure to appreciate these elements often leads to a series of reductionist approach interventions or 'fixes'. This in turn can initiate a series of negative feedback loops that further complicates the situation over time. In this paper we use a case study of the Additional Duty Hours Allowance (ADHA) policy in Ghana to illustrate these points. Using causal loop diagrams, we unpack the intended and unintended effects of the policy and how these effects evolved over time. The overall goal is to advance our understanding of decision making in complex adaptive systems; and through this process identify some essential elements in formulating, updating and implementing health policy that can help to improve attainment of desired outcomes and minimize negative unintended effects.

­Understanding Information Flow Interaction along Separable Causal Paths in Environmental Signals

NASA Astrophysics Data System (ADS)

Jiang, P.; Kumar, P.

2017-12-01

Multivariate environmental signals reflect the outcome of complex inter-dependencies, such as those in ecohydrologic systems. Transfer entropy and information partitioning approaches have been used to characterize such dependencies. However, these approaches capture net information flow occurring through a multitude of pathways involved in the interaction and as a result mask our ability to discern the causal interaction within an interested subsystem through specific pathways. We build on recent developments of momentary information transfer along causal paths proposed by Runge [2015] to develop a framework for quantifying information decomposition along separable causal paths. Momentary information transfer along causal paths captures the amount of information flow between any two variables lagged at two specific points in time. Our approach expands this concept to characterize the causal interaction in terms of synergistic, unique and redundant information flow through separable causal paths. Multivariate analysis using this novel approach reveals precise understanding of causality and feedback. We illustrate our approach with synthetic and observed time series data. We believe the proposed framework helps better delineate the internal structure of complex systems in geoscience where huge amounts of observational datasets exist, and it will also help the modeling community by providing a new way to look at the complexity of real and modeled systems. Runge, Jakob. "Quantifying information transfer and mediation along causal pathways in complex systems." Physical Review E 92.6 (2015): 062829.

Understanding interfirm relationships in business ecosystems with interactive visualization.

PubMed

Basole, Rahul C; Clear, Trustin; Hu, Mengdie; Mehrotra, Harshit; Stasko, John

2013-12-01

Business ecosystems are characterized by large, complex, and global networks of firms, often from many different market segments, all collaborating, partnering, and competing to create and deliver new products and services. Given the rapidly increasing scale, complexity, and rate of change of business ecosystems, as well as economic and competitive pressures, analysts are faced with the formidable task of quickly understanding the fundamental characteristics of these interfirm networks. Existing tools, however, are predominantly query- or list-centric with limited interactive, exploratory capabilities. Guided by a field study of corporate analysts, we have designed and implemented dotlink360, an interactive visualization system that provides capabilities to gain systemic insight into the compositional, temporal, and connective characteristics of business ecosystems. dotlink360 consists of novel, multiple connected views enabling the analyst to explore, discover, and understand interfirm networks for a focal firm, specific market segments or countries, and the entire business ecosystem. System evaluation by a small group of prototypical users shows supporting evidence of the benefits of our approach. This design study contributes to the relatively unexplored, but promising area of exploratory information visualization in market research and business strategy.

Global change modeling for Northern Eurasia: a review and strategies to move forward

NASA Astrophysics Data System (ADS)

Monier, E.; Kicklighter, D. W.; Sokolov, A. P.; Zhuang, Q.; Sokolik, I. N.; Lawford, R. G.; Kappas, M.; Paltsev, S.; Groisman, P. Y.

2017-12-01

Northern Eurasia is made up of a complex and diverse set of physical, ecological, climatic and human systems, which provide important ecosystem services including the storage of substantial stocks of carbon in its terrestrial ecosystems. At the same time, the region has experienced dramatic climate change, natural disturbances and changes in land management practices over the past century. For these reasons, Northern Eurasia is both a critical region to understand and a complex system with substantial challenges for the modeling community. This review is designed to highlight the state of past and ongoing efforts of the research community to understand and model these environmental, socioeconomic, and climatic changes. We further aim to provide perspectives on the future direction of global change modeling to improve our understanding of the role of Northern Eurasia in the coupled human-Earth system. Modeling efforts have shown that environmental and socioeconomic changes in Northern Eurasia can have major impacts on biodiversity, ecosystems services, environmental sustainability, and the carbon cycle of the region, and beyond. These impacts have the potential to feedback onto and alter the global Earth system. We find that past and ongoing studies have largely focused on specific components of Earth system dynamics and have not systematically examined their feedbacks to the global Earth system and to society. We identify the crucial role of Earth system models in advancing our understanding of feedbacks within the region and with the global system. We further argue for the need for integrated assessment models (IAMs), a suite of models that couple human activity models to Earth system models, which are key to address many emerging issues that require a representation of the coupled human-Earth system.

A review of and perspectives on global change modeling for Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Kicklighter, David W.; Sokolov, Andrei P.; Zhuang, Qianlai; Sokolik, Irina N.; Lawford, Richard; Kappas, Martin; Paltsev, Sergey V.; Groisman, Pavel Ya

2017-08-01

Northern Eurasia is made up of a complex and diverse set of physical, ecological, climatic and human systems, which provide important ecosystem services including the storage of substantial stocks of carbon in its terrestrial ecosystems. At the same time, the region has experienced dramatic climate change, natural disturbances and changes in land management practices over the past century. For these reasons, Northern Eurasia is both a critical region to understand and a complex system with substantial challenges for the modeling community. This review is designed to highlight the state of past and ongoing efforts of the research community to understand and model these environmental, socioeconomic, and climatic changes. We further aim to provide perspectives on the future direction of global change modeling to improve our understanding of the role of Northern Eurasia in the coupled human-Earth system. Modeling efforts have shown that environmental and socioeconomic changes in Northern Eurasia can have major impacts on biodiversity, ecosystems services, environmental sustainability, and the carbon cycle of the region, and beyond. These impacts have the potential to feedback onto and alter the global Earth system. We find that past and ongoing studies have largely focused on specific components of Earth system dynamics and have not systematically examined their feedbacks to the global Earth system and to society. We identify the crucial role of Earth system models in advancing our understanding of feedbacks within the region and with the global system. We further argue for the need for integrated assessment models (IAMs), a suite of models that couple human activity models to Earth system models, which are key to address many emerging issues that require a representation of the coupled human-Earth system.

Integrated, systems metabolic picture of acetone-butanol-ethanol fermentation by Clostridium acetobutylicum.

PubMed

Liao, Chen; Seo, Seung-Oh; Celik, Venhar; Liu, Huaiwei; Kong, Wentao; Wang, Yi; Blaschek, Hans; Jin, Yong-Su; Lu, Ting

2015-07-07

Microbial metabolism involves complex, system-level processes implemented via the orchestration of metabolic reactions, gene regulation, and environmental cues. One canonical example of such processes is acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum, during which cells convert carbon sources to organic acids that are later reassimilated to produce solvents as a strategy for cellular survival. The complexity and systems nature of the process have been largely underappreciated, rendering challenges in understanding and optimizing solvent production. Here, we present a system-level computational framework for ABE fermentation that combines metabolic reactions, gene regulation, and environmental cues. We developed the framework by decomposing the entire system into three modules, building each module separately, and then assembling them back into an integrated system. During the model construction, a bottom-up approach was used to link molecular events at the single-cell level into the events at the population level. The integrated model was able to successfully reproduce ABE fermentations of the WT C. acetobutylicum (ATCC 824), as well as its mutants, using data obtained from our own experiments and from literature. Furthermore, the model confers successful predictions of the fermentations with various network perturbations across metabolic, genetic, and environmental aspects. From foundation to applications, the framework advances our understanding of complex clostridial metabolism and physiology and also facilitates the development of systems engineering strategies for the production of advanced biofuels.

Integrated, systems metabolic picture of acetone-butanol-ethanol fermentation by Clostridium acetobutylicum

PubMed Central

Liao, Chen; Seo, Seung-Oh; Celik, Venhar; Liu, Huaiwei; Kong, Wentao; Wang, Yi; Blaschek, Hans; Jin, Yong-Su; Lu, Ting

2015-01-01

Microbial metabolism involves complex, system-level processes implemented via the orchestration of metabolic reactions, gene regulation, and environmental cues. One canonical example of such processes is acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum, during which cells convert carbon sources to organic acids that are later reassimilated to produce solvents as a strategy for cellular survival. The complexity and systems nature of the process have been largely underappreciated, rendering challenges in understanding and optimizing solvent production. Here, we present a system-level computational framework for ABE fermentation that combines metabolic reactions, gene regulation, and environmental cues. We developed the framework by decomposing the entire system into three modules, building each module separately, and then assembling them back into an integrated system. During the model construction, a bottom-up approach was used to link molecular events at the single-cell level into the events at the population level. The integrated model was able to successfully reproduce ABE fermentations of the WT C. acetobutylicum (ATCC 824), as well as its mutants, using data obtained from our own experiments and from literature. Furthermore, the model confers successful predictions of the fermentations with various network perturbations across metabolic, genetic, and environmental aspects. From foundation to applications, the framework advances our understanding of complex clostridial metabolism and physiology and also facilitates the development of systems engineering strategies for the production of advanced biofuels. PMID:26100881

Positioning infrastructure and technologies for low-carbon urbanization

NASA Astrophysics Data System (ADS)

Chester, Mikhail V.; Sperling, Josh; Stokes, Eleanor; Allenby, Braden; Kockelman, Kara; Kennedy, Christopher; Baker, Lawrence A.; Keirstead, James; Hendrickson, Chris T.

2014-10-01

The expected urbanization of the planet in the coming century coupled with aging infrastructure in developed regions, increasing complexity of man-made systems, and pressing climate change impacts have created opportunities for reassessing the role of infrastructure and technologies in cities and how they contribute to greenhouse gas (GHG) emissions. Modern urbanization is predicated on complex, increasingly coupled infrastructure systems, and energy use continues to be largely met from fossil fuels. Until energy infrastructures evolve away from carbon-based fuels, GHG emissions are critically tied to the urbanization process. Further complicating the challenge of decoupling urban growth from GHG emissions are lock-in effects and interdependencies. This paper synthesizes state-of-the-art thinking for transportation, fuels, buildings, water, electricity, and waste systems and finds that GHG emissions assessments tend to view these systems as static and isolated from social and institutional systems. Despite significant understanding of methods and technologies for reducing infrastructure-related GHG emissions, physical, institutional, and cultural constraints continue to work against us, pointing to knowledge gaps that must be addressed. This paper identifies three challenge themes to improve our understanding of the role of infrastructure and technologies in urbanization processes and position these increasingly complex systems for low-carbon growth. The challenges emphasize how we can reimagine the role of infrastructure in the future and how people, institutions, and ecological systems interface with infrastructure.

Aicardi-Goutières syndrome: a model disease for systemic autoimmunity.

PubMed

Lee-Kirsch, M A; Wolf, C; Günther, C

2014-01-01

Systemic autoimmunity is a complex disease process that results from a loss of immunological tolerance characterized by the inability of the immune system to discriminate self from non-self. In patients with the prototypic autoimmune disease systemic lupus erythematosus (SLE), formation of autoantibodies targeting ubiquitous nuclear antigens and subsequent deposition of immune complexes in the vascular bed induces inflammatory tissue injury that can affect virtually any organ system. Given the extraordinary genetic and phenotypic heterogeneity of SLE, one approach to the genetic dissection of complex SLE is to study monogenic diseases, for which a single gene defect is responsible. Considerable success has been achieved from the analysis of the rare monogenic disorder Aicardi-Goutières syndrome (AGS), an inflammatory encephalopathy that clinically resembles in-utero-acquired viral infection and that also shares features with SLE. Progress in understanding the cellular and molecular functions of the AGS causing genes has revealed novel pathways of the metabolism of intracellular nucleic acids, the major targets of the autoimmune attack in patients with SLE. Induction of autoimmunity initiated by immune recognition of endogenous nucleic acids originating from processes such as DNA replication/repair or endogenous retro-elements represents novel paradigms of SLE pathogenesis. These findings illustrate how investigating rare monogenic diseases can also fuel discoveries that advance our understanding of complex disease. This will not only aid the development of improved tools for SLE diagnosis and disease classification, but also the development of novel targeted therapeutic approaches. © 2013 British Society for Immunology.

Convergent Adaptation in Small Groups: Understanding Professional Development Activities through a Complex Systems Lens

ERIC Educational Resources Information Center

Yoon, Susan; Liu, Lei; Goh, Sao-Ee

2010-01-01

Understanding the dynamics of individual or group adaptation can provide valuable information for constructing professional development strategies to increase chances of instructional success. This paper reports on an exploratory study that identifies indicators of convergent vs. non-convergent adaptation in two cases of teachers working together…

Pedagogical Considerations for Effectively Teaching Qualitative Research to Students in an Online Environment

ERIC Educational Resources Information Center

Bender, Sara; Hill, Karlie

2016-01-01

Qualitative research aims to understand both individual meaning as well as complex systemic interactions as they apply to social problems or individual experiences. This method of research is both inductive and flexible, allowing for a holistic approach that facilitates a rich understanding of the content examined. Past research identifies a…

Do Students Understand Our Course Structure? Implications for Important Classroom Attitudes and Behavior

ERIC Educational Resources Information Center

Elicker, Joelle D.; Foust, Michelle Singer; Perry, Jennifer L.

2015-01-01

The complexity of a course's structure may influence how well students understand what is expected of them. Using the foundation of the industrial/organizational (I/O) psychology literature, the authors modified a measure of "Perceived System Knowledge" (Williams & Levy, 1992) for employee performance appraisal to be appropriate for…

The Culture of High Technology: Is It "Female Friendly?"

ERIC Educational Resources Information Center

Kelly, Jan Wallace

To better understand the complexity of organizational life as a cultural system whose members share particular values, attitudes, and ways of knowing, and to understand the role of women in this culture, a study was conducted using female managers at 12 high technology companies in California's "Silicon Valley." Informants were selected…

Understanding Immigrant College Students: Applying a Developmental Ecology Framework to the Practice of Academic Advising

ERIC Educational Resources Information Center

Stebleton, Michael J.

2011-01-01

Immigrant college student populations continue to grow, but the complexity of their unique needs and issues remain relatively unknown. To gain a better understanding of the multiple contextual factors impacting immigrant students from a systems-based approach, I applied Bronfenbrenner's (1977) human ecology framework to the study. Students…

Peer Assisted Learning in the Clinical Setting: An Activity Systems Analysis

ERIC Educational Resources Information Center

Bennett, Deirdre; O'Flynn, Siun; Kelly, Martina

2015-01-01

Peer assisted learning (PAL) is a common feature of medical education. Understanding of PAL has been based on processes and outcomes in controlled settings, such as clinical skills labs. PAL in the clinical setting, a complex learning environment, requires fresh evaluation. Socio-cultural theory is proposed as a means to understand educational…

Coming to Understand Diversity and Education: Life Experiences and Educational Opportunities

ERIC Educational Resources Information Center

Chamberlain, Steven Paul

2015-01-01

Coming to understand how cultural differences influence interactions between educators and students and their parents is a complex and perhaps life-long discovery. Culture helps to define groups' belief systems and expectations for appropriate behavior, often at a hidden level. Pre-service teachers need multiple opportunities to interact with…

On the Axiomatization of Mathematical Understanding: Continuous Functions in the Transition to Topology

ERIC Educational Resources Information Center

Cheshire, Daniel C.

2017-01-01

The introduction to general topology represents a challenging transition for students of advanced mathematics. It requires the generalization of their previous understanding of ideas from fields like geometry, linear algebra, and real or complex analysis to fit within a more abstract conceptual system. Students must adopt a new lexicon of…

Environmental Context of Learning: Introduction to the Special Topic

ERIC Educational Resources Information Center

Burns, Matthew K.

2015-01-01

Understanding individual students is a complex process. Bronfenbrenner's (1986) seminal Ecological Systems Theory (EST) provides a framework for understanding students by examining the environments in which the child lives including the home, school, community, culture, and so on. One of the main tenets of EST is that it provides a process for…

Glacier generated floods

USGS Publications Warehouse

Walder, J.S.; Fountain, A.G.; ,

1997-01-01

Destructive floods result from drainage of glacier-dammed lakes and sudden release of water stored within glaciers. There is a good basis - both empirical and theoretical - for predicting the magnitude of floods from ice-dammed lakes, although some aspects of flood initiation need to be better understood. In contrast, an understanding of floods resulting from release of internally stored water remains elusive, owing to lack of knowledge of how and where water is stored and to inadequate understanding of the complex physics of the temporally and spatially variable subglacial drainage system.Destructive floods result from drainage of glacier-dammed lakes and sudden release of water stored within glaciers. There is a good basis - both empirical and theoretical - for predicting the magnitude of floods from ice-dammed lakes, although some aspects of flood initiation need to be better understood. In contrast, an understanding of floods resulting from release of internally stored water remains elusive, owing to lack of knowledge of how and where water is stored and to inadequate understanding of the complex physics of the temporally and spatially variable subglacial drainage system.

Inference, simulation, modeling, and analysis of complex networks, with special emphasis on complex networks in systems biology

NASA Astrophysics Data System (ADS)

Christensen, Claire Petra

Across diverse fields ranging from physics to biology, sociology, and economics, the technological advances of the past decade have engendered an unprecedented explosion of data on highly complex systems with thousands, if not millions of interacting components. These systems exist at many scales of size and complexity, and it is becoming ever-more apparent that they are, in fact, universal, arising in every field of study. Moreover, they share fundamental properties---chief among these, that the individual interactions of their constituent parts may be well-understood, but the characteristic behaviour produced by the confluence of these interactions---by these complex networks---is unpredictable; in a nutshell, the whole is more than the sum of its parts. There is, perhaps, no better illustration of this concept than the discoveries being made regarding complex networks in the biological sciences. In particular, though the sequencing of the human genome in 2003 was a remarkable feat, scientists understand that the "cellular-level blueprints" for the human being are cellular-level parts lists, but they say nothing (explicitly) about cellular-level processes. The challenge of modern molecular biology is to understand these processes in terms of the networks of parts---in terms of the interactions among proteins, enzymes, genes, and metabolites---as it is these processes that ultimately differentiate animate from inanimate, giving rise to life! It is the goal of systems biology---an umbrella field encapsulating everything from molecular biology to epidemiology in social systems---to understand processes in terms of fundamental networks of core biological parts, be they proteins or people. By virtue of the fact that there are literally countless complex systems, not to mention tools and techniques used to infer, simulate, analyze, and model these systems, it is impossible to give a truly comprehensive account of the history and study of complex systems. The author's own publications have contributed network inference, simulation, modeling, and analysis methods to the much larger body of work in systems biology, and indeed, in network science. The aim of this thesis is therefore twofold: to present this original work in the historical context of network science, but also to provide sufficient review and reference regarding complex systems (with an emphasis on complex networks in systems biology) and tools and techniques for their inference, simulation, analysis, and modeling, such that the reader will be comfortable in seeking out further information on the subject. The review-like Chapters 1, 2, and 4 are intended to convey the co-evolution of network science and the slow but noticeable breakdown of boundaries between disciplines in academia as research and comparison of diverse systems has brought to light the shared properties of these systems. It is the author's hope that theses chapters impart some sense of the remarkable and rapid progress in complex systems research that has led to this unprecedented academic synergy. Chapters 3 and 5 detail the author's original work in the context of complex systems research. Chapter 3 presents the methods and results of a two-stage modeling process that generates candidate gene-regulatory networks of the bacterium B.subtilis from experimentally obtained, yet mathematically underdetermined microchip array data. These networks are then analyzed from a graph theoretical perspective, and their biological viability is critiqued by comparing the networks' graph theoretical properties to those of other biological systems. The results of topological perturbation analyses revealing commonalities in behavior at multiple levels of complexity are also presented, and are shown to be an invaluable means by which to ascertain the level of complexity to which the network inference process is robust to noise. Chapter 5 outlines a learning algorithm for the development of a realistic, evolving social network (a city) into which a disease is introduced. The results of simulations in populations spanning two orders of magnitude are compared to prevaccine era measles data for England and Wales and demonstrate that the simulations are able to capture the quantitative and qualitative features of epidemics in populations as small as 10,000 people. The work presented in Chapter 5 validates the utility of network simulation in concurrently probing contact network dynamics and disease dynamics.

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

PubMed

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

2018-04-19

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

The role of future scenarios to understand deep uncertainty

EPA Science Inventory

The environment and its interaction with human systems(economic, social and political) is complex and dynamic. Key drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions precisely. This kind of deep uncertainty presents a challe...

Climate metrics and aviation : analysis of current understanding and uncertainties

DOT National Transportation Integrated Search

2008-01-22

The impact of climate-altering agents on the atmospheric system is a result of a complex system : of interactions and feedbacks within the atmosphere, and with the oceans, the land surface, the : biosphere and the cryosphere. Climate metrics are used...

Multi-Modal Traveler Information System - Performance Criteria for Evaluating GCM Corridor Strategies & Technologies

DOT National Transportation Integrated Search

1997-07-16

The Gary-Chicago-Milwaukee (GCM) Multi-Modal Traveler Information System (MMTIS) is a complex project involving a wide spectrum of participants. In order to facilitate its implementation it is important to understand the direction of the MMTIS. This ...

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

PubMed

Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

2016-02-01

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Tailoring Healthy Workplace Interventions to Local Healthcare Settings: A Complexity Theory-Informed Workplace of Well-Being Framework

PubMed Central

Brand, Sarah L.; Fleming, Lora E.; Wyatt, Katrina M.

2015-01-01

Many healthy workplace interventions have been developed for healthcare settings to address the consistently low scores of healthcare professionals on assessments of mental and physical well-being. Complex healthcare settings present challenges for the scale-up and spread of successful interventions from one setting to another. Despite general agreement regarding the importance of the local setting in affecting intervention success across different settings, there is no consensus on what it is about a local setting that needs to be taken into account to design healthy workplace interventions appropriate for different local settings. Complexity theory principles were used to understand a workplace as a complex adaptive system and to create a framework of eight domains (system characteristics) that affect the emergence of system-level behaviour. This Workplace of Well-being (WoW) framework is responsive and adaptive to local settings and allows a shared understanding of the enablers and barriers to behaviour change by capturing local information for each of the eight domains. We use the results of applying the WoW framework to one workplace, a UK National Health Service ward, to describe the utility of this approach in informing design of setting-appropriate healthy workplace interventions that create workplaces conducive to healthy behaviour change. PMID:26380358

Tailoring Healthy Workplace Interventions to Local Healthcare Settings: A Complexity Theory-Informed Workplace of Well-Being Framework.

PubMed

Brand, Sarah L; Fleming, Lora E; Wyatt, Katrina M

2015-01-01

Many healthy workplace interventions have been developed for healthcare settings to address the consistently low scores of healthcare professionals on assessments of mental and physical well-being. Complex healthcare settings present challenges for the scale-up and spread of successful interventions from one setting to another. Despite general agreement regarding the importance of the local setting in affecting intervention success across different settings, there is no consensus on what it is about a local setting that needs to be taken into account to design healthy workplace interventions appropriate for different local settings. Complexity theory principles were used to understand a workplace as a complex adaptive system and to create a framework of eight domains (system characteristics) that affect the emergence of system-level behaviour. This Workplace of Well-being (WoW) framework is responsive and adaptive to local settings and allows a shared understanding of the enablers and barriers to behaviour change by capturing local information for each of the eight domains. We use the results of applying the WoW framework to one workplace, a UK National Health Service ward, to describe the utility of this approach in informing design of setting-appropriate healthy workplace interventions that create workplaces conducive to healthy behaviour change.

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

PubMed

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

2018-01-30

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

Identifying States of a Financial Market

NASA Astrophysics Data System (ADS)

Münnix, Michael C.; Shimada, Takashi; Schäfer, Rudi; Leyvraz, Francois; Seligman, Thomas H.; Guhr, Thomas; Stanley, H. Eugene

2012-09-01

The understanding of complex systems has become a central issue because such systems exist in a wide range of scientific disciplines. We here focus on financial markets as an example of a complex system. In particular we analyze financial data from the S&P 500 stocks in the 19-year period 1992-2010. We propose a definition of state for a financial market and use it to identify points of drastic change in the correlation structure. These points are mapped to occurrences of financial crises. We find that a wide variety of characteristic correlation structure patterns exist in the observation time window, and that these characteristic correlation structure patterns can be classified into several typical ``market states''. Using this classification we recognize transitions between different market states. A similarity measure we develop thus affords means of understanding changes in states and of recognizing developments not previously seen.

Identifying states of a financial market.

PubMed

Münnix, Michael C; Shimada, Takashi; Schäfer, Rudi; Leyvraz, Francois; Seligman, Thomas H; Guhr, Thomas; Stanley, H Eugene

2012-01-01

The understanding of complex systems has become a central issue because such systems exist in a wide range of scientific disciplines. We here focus on financial markets as an example of a complex system. In particular we analyze financial data from the S&P 500 stocks in the 19-year period 1992-2010. We propose a definition of state for a financial market and use it to identify points of drastic change in the correlation structure. These points are mapped to occurrences of financial crises. We find that a wide variety of characteristic correlation structure patterns exist in the observation time window, and that these characteristic correlation structure patterns can be classified into several typical "market states". Using this classification we recognize transitions between different market states. A similarity measure we develop thus affords means of understanding changes in states and of recognizing developments not previously seen.

Use of complex adaptive systems metaphor to achieve professional and organizational change.

PubMed

Rowe, Ann; Hogarth, Annette

2005-08-01

This paper uses the experiences of a programme designed to bring about change in performance of public health nurses (health visitors and school nurses) in an inner city primary care trust, to explore the issues of professional and organizational change in health care organizations. The United Kingdom government has given increasing emphasis to programmes of modernization within the National Health Service. A central facet of this policy shift has been an expectation of behaviour and practice change by health care professionals. Change was brought about through use of a Complex Adaptive Systems approach. This enabled change to be seen as an inclusive, evolving and unpredictable process rather one which is linear and mechanistic. The paper examines in detail how the use of concepts and metaphors associated with Complex Adaptive Systems influenced the development of the programme, its implementation and outcomes. The programme resulted in extensive change in professional behaviour, service delivery and transformational change in the organizational structures and processes of the employing organization. This gave greater opportunities for experimentation and innovation, leading to new developments in service delivery, but also meant higher levels of uncertainty, responsibility, decision-making and risk management for practitioners. Using a Complex Adaptive Systems approach was helpful for developing alternative views of change and for understanding why and how some aspects of change were more successful than others. Its use encouraged the confrontation of some long-standing assumptions about change and service delivery patterns in the National Health Service, and the process exposed challenging tensions within the Service. The consequent destabilising of organizational and professional norms resulted in considerable emotional impacts for practitioners, an area which was found to be underplayed within the Complex Adaptive Systems literature. A Complex Adaptive Systems approach can support change, in particular a recognition and understanding of the emergence of unexpected structures, patterns and processes. The approach can support nurses to change their behaviour and innovate, but requires high levels of accountability, individual and professional creativity.

A Systems Approach to Comprehensive School Reform: Using the Realms of Meaning and the Baldridge Approach as a Systems Framework

ERIC Educational Resources Information Center

Miller-Williams, Sheri L.; Kritsonis, William Allan

2009-01-01

A system is a group of interacting, interrelated, and interdependent components that form a complex and unified whole. Systems thinking is a way of understanding reality that emphasizes the relationships among systems parts, rather than the parts themselves. Based on a field of study known as "system dynamics", systems thinking has a practical…

Groundwater dynamics in subterranean estuaries of coastal unconfined aquifers: Controls on submarine groundwater discharge and chemical inputs to the ocean

NASA Astrophysics Data System (ADS)

Robinson, Clare E.; Xin, Pei; Santos, Isaac R.; Charette, Matthew A.; Li, Ling; Barry, D. A.

2018-05-01

Sustainable coastal resource management requires sound understanding of interactions between coastal unconfined aquifers and the ocean as these interactions influence the flux of chemicals to the coastal ocean and the availability of fresh groundwater resources. The importance of submarine groundwater discharge in delivering chemical fluxes to the coastal ocean and the critical role of the subterranean estuary (STE) in regulating these fluxes is well recognized. STEs are complex and dynamic systems exposed to various physical, hydrological, geological, and chemical conditions that act on disparate spatial and temporal scales. This paper provides a review of the effect of factors that influence flow and salt transport in STEs, evaluates current understanding on the interactions between these influences, and synthesizes understanding of drivers of nutrient, carbon, greenhouse gas, metal and organic contaminant fluxes to the ocean. Based on this review, key research needs are identified. While the effects of density and tides are well understood, episodic and longer-period forces as well as the interactions between multiple influences remain poorly understood. Many studies continue to focus on idealized nearshore aquifer systems and future work needs to consider real world complexities such as geological heterogeneities, and non-uniform and evolving alongshore and cross-shore morphology. There is also a significant need for multidisciplinary research to unravel the interactions between physical and biogeochemical processes in STEs, as most existing studies treat these processes in isolation. Better understanding of this complex and dynamic system can improve sustainable management of coastal water resources under the influence of anthropogenic pressures and climate change.

Neurological Disease in Lupus: Toward a Personalized Medicine Approach.

PubMed

McGlasson, Sarah; Wiseman, Stewart; Wardlaw, Joanna; Dhaun, Neeraj; Hunt, David P J

2018-01-01

The brain and nervous system are important targets for immune-mediated damage in systemic lupus erythematosus (SLE), resulting in a complex spectrum of neurological syndromes. Defining nervous system disease in lupus poses significant challenges. Among the difficulties to be addressed are a diversity of clinical manifestations and a lack of understanding of their mechanistic basis. However, despite these challenges, progress has been made in the identification of pathways which contribute to neurological disease in SLE. Understanding the molecular pathogenesis of neurological disease in lupus will inform both classification and approaches to clinical trials.

Sensemaking in a Value Based Context for Large Scale Complex Engineered Systems

NASA Astrophysics Data System (ADS)

Sikkandar Basha, Nazareen

The design and the development of Large-Scale Complex Engineered Systems (LSCES) requires the involvement of multiple teams and numerous levels of the organization and interactions with large numbers of people and interdisciplinary departments. Traditionally, requirements-driven Systems Engineering (SE) is used in the design and development of these LSCES. The requirements are used to capture the preferences of the stakeholder for the LSCES. Due to the complexity of the system, multiple levels of interactions are required to elicit the requirements of the system within the organization. Since LSCES involves people and interactions between the teams and interdisciplinary departments, it should be socio-technical in nature. The elicitation of the requirements of most large-scale system projects are subjected to creep in time and cost due to the uncertainty and ambiguity of requirements during the design and development. In an organization structure, the cost and time overrun can occur at any level and iterate back and forth thus increasing the cost and time. To avoid such creep past researches have shown that rigorous approaches such as value based designing can be used to control it. But before the rigorous approaches can be used, the decision maker should have a proper understanding of requirements creep and the state of the system when the creep occurs. Sensemaking is used to understand the state of system when the creep occurs and provide a guidance to decision maker. This research proposes the use of the Cynefin framework, sensemaking framework which can be used in the design and development of LSCES. It can aide in understanding the system and decision making to minimize the value gap due to requirements creep by eliminating ambiguity which occurs during design and development. A sample hierarchical organization is used to demonstrate the state of the system at the occurrence of requirements creep in terms of cost and time using the Cynefin framework. These trials are continued for different requirements and at different sub-system level. The results obtained show that the Cynefin framework can be used to improve the value of the system and can be used for predictive analysis. The decision makers can use these findings and use rigorous approaches and improve the design of Large Scale Complex Engineered Systems.

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

ERIC Educational Resources Information Center

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

2013-01-01

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

Student Teachers' Pedagogical Content Knowledge for Teaching Systems Thinking: Effects of Different Interventions

ERIC Educational Resources Information Center

Rosenkränzer, Frank; Hörsch, Christian; Schuler, Stephan; Riess, Werner

2017-01-01

Systems' thinking has become increasingly relevant not only in education for sustainable development but also in everyday life. Even if teachers know the dynamics and complexity of living systems in biology and geography, they might not be able to effectively explain it to students. Teachers need an understanding of systems and their behaviour…

System Thinking and Feeding Relations: Learning with a Live Ecosystem Model

ERIC Educational Resources Information Center

Eilam, Billie

2012-01-01

Considering well-documented difficulties in mastering ecology concepts and system thinking, the aim of the study was to examine 9th graders' understanding of the complex, multilevel, systemic construct of feeding relations, nested within a larger system of a live model. Fifty students interacted with the model and manipulated a variable within it…

Intermittent dynamics in complex systems driven to depletion.

PubMed

Escobar, Juan V; Pérez Castillo, Isaac

2018-03-19

When complex systems are driven to depletion by some external factor, their non-stationary dynamics can present an intermittent behaviour between relative tranquility and burst of activity whose consequences are often catastrophic. To understand and ultimately be able to predict such dynamics, we propose an underlying mechanism based on sharp thresholds of a local generalized energy density that naturally leads to negative feedback. We find a transition from a continuous regime to an intermittent one, in which avalanches can be predicted despite the stochastic nature of the process. This model may have applications in many natural and social complex systems where a rapid depletion of resources or generalized energy drives the dynamics. In particular, we show how this model accurately describes the time evolution and avalanches present in a real social system.

Understanding the complexities of Salmonella-host crosstalk as revealed by in vivo model organisms.

PubMed

Verma, Smriti; Srikanth, Chittur V

2015-07-01

Foodborne infections caused by non-typhoidal Salmonellae, such as Salmonella enterica serovar Typhimurium (ST), pose a major challenge in the developed and developing world. With constant rise of drug-resistant strains, understanding the epidemiology, microbiology, pathogenesis and host-pathogen interactions biology is a mandatory requirement to enable health systems to be ready to combat these illnesses. Patient data from hospitals, at least from some parts of the world, have aided in epidemiological understanding of ST-mediated disease. Most of the other aspects connected to Salmonella-host crosstalk have come from model systems that offer convenience, genetic tractability and low maintenance costs that make them extremely valuable tools. Complex model systems such as the bovine model have helped in understanding key virulence factors needed for infection. Simple systems such as fruit flies and Caenorhabditis elegans have aided in identification of novel virulence factors, host pathways and mechanistic details of interactions. Some of the path-breaking concepts of the field have come from mice model of ST colitis, which allows genetic manipulations as well as high degree of similarity to human counterpart. Together, they are invaluable for correlating in vitro findings of ST-induced disease progression in vivo. The current review is a compilation of various advances of ST-host interactions at cellular and molecular levels that has come from investigations involving model organisms. © 2015 International Union of Biochemistry and Molecular Biology.

Applications of fidelity measures to complex quantum systems

PubMed Central

2016-01-01

We revisit fidelity as a measure for the stability and the complexity of the quantum motion of single-and many-body systems. Within the context of cold atoms, we present an overview of applications of two fidelities, which we call static and dynamical fidelity, respectively. The static fidelity applies to quantum problems which can be diagonalized since it is defined via the eigenfunctions. In particular, we show that the static fidelity is a highly effective practical detector of avoided crossings characterizing the complexity of the systems and their evolutions. The dynamical fidelity is defined via the time-dependent wave functions. Focusing on the quantum kicked rotor system, we highlight a few practical applications of fidelity measurements in order to better understand the large variety of dynamical regimes of this paradigm of a low-dimensional system with mixed regular–chaotic phase space. PMID:27140967

Anatomy and Physiology of Multiscale Modeling and Simulation in Systems Medicine.

PubMed

Mizeranschi, Alexandru; Groen, Derek; Borgdorff, Joris; Hoekstra, Alfons G; Chopard, Bastien; Dubitzky, Werner

2016-01-01

Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.

Topological Principles of Control in Dynamical Networks

NASA Astrophysics Data System (ADS)

Kim, Jason; Pasqualetti, Fabio; Bassett, Danielle

Networked biological systems, such as the brain, feature complex patterns of interactions. To predict and correct the dynamic behavior of such systems, it is imperative to understand how the underlying topological structure affects and limits the function of the system. Here, we use network control theory to extract topological features that favor or prevent network controllability, and to understand the network-wide effect of external stimuli on large-scale brain systems. Specifically, we treat each brain region as a dynamic entity with real-valued state, and model the time evolution of all interconnected regions using linear, time-invariant dynamics. We propose a simplified feed-forward scheme where the effect of upstream regions (drivers) on the connected downstream regions (non-drivers) is characterized in closed-form. Leveraging this characterization of the simplified model, we derive topological features that predict the controllability properties of non-simplified networks. We show analytically and numerically that these predictors are accurate across a large range of parameters. Among other contributions, our analysis shows that heterogeneity in the network weights facilitate controllability, and allows us to implement targeted interventions that profoundly improve controllability. By assuming an underlying dynamical mechanism, we are able to understand the complex topology of networked biological systems in a functionally meaningful way.

Systems thinking, complexity and managerial decision-making: an analytical review.

PubMed

Cramp, D G; Carson, E R

2009-05-01

One feature that characterizes the organization and delivery of health care is its inherent complexity. All too often, with so much information and so many activities involved, it is difficult for decision-makers to determine in an objective fashion an appropriate course of action. It would appear that a holistic rather than a reductionist approach would be advantageous. The aim of this paper is to review how formal systems thinking can aid decision-making in complex situations. Consideration is given as to how the use of a number of systems modelling methodologies can help in gaining an understanding of a complex decision situation. This in turn can enhance the possibility of a decision being made in a more rational, explicit and transparent fashion. The arguments and approaches are illustrated using examples taken from the public health arena.

Using a biased qubit to probe complex systems

NASA Astrophysics Data System (ADS)

Pollock, Felix A.; Checińska, Agata; Pascazio, Saverio; Modi, Kavan

2016-09-01

Complex mesoscopic systems play increasingly important roles in modern science, from understanding biological functions at the molecular level to designing solid-state information processing devices. The operation of these systems typically depends on their energetic structure, yet probing their energy landscape can be extremely challenging; they have many degrees of freedom, which may be hard to isolate and measure independently. Here, we show that a qubit (a two-level quantum system) with a biased energy splitting can directly probe the spectral properties of a complex system, without knowledge of how they couple. Our work is based on the completely positive and trace-preserving map formalism, which treats any unknown dynamics as a "black-box" process. This black box contains information about the system with which the probe interacts, which we access by measuring the survival probability of the initial state of the probe as function of the energy splitting and the process time. Fourier transforming the results yields the energy spectrum of the complex system. Without making assumptions about the strength or form of its coupling, our probe could determine aspects of a complex molecule's energy landscape as well as, in many cases, test for coherent superposition of its energy eigenstates.

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

Fostering Creative Engineers: A Key to Face the Complexity of Engineering Practice

ERIC Educational Resources Information Center

Zhou, Chunfang

2012-01-01

Recent studies have argued a shift of thinking about engineering practice from a linear conception to a system understanding. The complexity of engineering practice has been thought of as the root of challenges for engineers. Moreover, creativity has been emphasised as one key capability that engineering students should master. This paper aims to…

The State of the Field: Qualitative Analyses of Text Complexity

ERIC Educational Resources Information Center

Pearson, P. David; Hiebert, Elfrieda H.

2014-01-01

The purpose of this article is to understand the function, logic, and impact of qualitative systems for analyzing text complexity, focusing on their benefits and imperfections. We identified two primary functions for their use: (a) to match texts to reader ability so that readers read books that are within their grasp, and (b) to unearth, and then…

Small-Group Problem-Based Learning as a Complex Adaptive System

ERIC Educational Resources Information Center

Mennin, Stewart

2007-01-01

Small-group problem-based learning (PBL) is widely embraced as a method of study in health professions schools and at many different levels of education. Complexity science provides a different lens with which to view and understand the application of this method. It presents new concepts and vocabulary that may be unfamiliar to practitioners of…

"I Want to Listen to My Students' Lives": Developing an Ecological Perspective in Learning to Teach

ERIC Educational Resources Information Center

Cook-Sather, Alison; Curl, Heather

2014-01-01

Preparing teachers who want to "listen to their students' lives"requires creating opportunities for prospective teachers to perceive and learn about their students' lives and how those unfold within and as part of complex systems. That means supporting prospective teachers not only in understanding students as complex beings who have to…

Using Representational Tools to Learn about Complex Systems: A Tale of Two Classrooms

ERIC Educational Resources Information Center

Hmelo-Silver, Cindy E.; Liu, Lei; Gray, Steven; Jordan, Rebecca

2015-01-01

Orchestrating inquiry-based science learning in the classroom is a complex undertaking. It requires fitting the culture of the classroom with the teacher's teaching and inquiry practices. To understand the interactions between these variables in relation to student learning, we conducted an investigation in two different classroom settings to…

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.

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

ERIC Educational Resources Information Center

Howard, Sarah K.; Thompson, Kate

2016-01-01

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

Visualizing and Quantifying the Suppressive Effects of Glucocorticoids on the Tadpole Immune System in Vivo

ERIC Educational Resources Information Center

Schreiber, Alexander M.

2011-01-01

A challenging topic in undergraduate physiology courses is the complex interaction between the vertebrate endocrine system and the immune system. There are relatively few established and accessible laboratory exercises available to instructors to help their students gain a working understanding of these interactions. The present laboratory module…

Systems Thinking to Improve the Public’s Health

PubMed Central

Leischow, Scott J.; Best, Allan; Trochim, William M.; Clark, Pamela I.; Gallagher, Richard S.; Marcus, Stephen E.; Matthews, Eva

2014-01-01

Improving population health requires understanding and changing societal structures and functions, but countervailing forces sometimes undermine those changes, thus reflecting the adaptive complexity inherent in public health systems. The purpose of this paper is to propose systems thinking as a conceptual rubric for the practice of team science in public health, and transdisciplinary, translational research as a catalyst for promoting the functional efficiency of science. The paper lays a foundation for the conceptual understanding of systems thinking and transdisciplinary research, and will provide illustrative examples within and beyond public health. A set of recommendations for a systems-centric approach to translational science will be presented. PMID:18619400

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.

National Ecosystem Services Classification System (NESCS): Framework Design and Policy Application

EPA Science Inventory

Understanding the ways in which ecosystems provide flows of “services” to humans is critical for decision making in many contexts; however, relationships between natural and human systems are complex. A well-defined framework for classifying ecosystem services is essential for sy...

The role of future scenarios to understand deep uncertainty in air quality management

EPA Science Inventory

The environment and it’s interaction with human systems (economic, social and political) is complex and dynamic. Key drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions precisely. This kind of deep uncertainty presents ...

ASSESSMENT OF NEUROTOXICITY USING ASSAYS OF NEURON-GLIA LOCALIZED PROTEINS: CHRONOLOGY AND CRITIQUE

EPA Science Inventory

The achievements in neuroscience research over recent years have greatly advanced our understanding of nervous system structure and function. et, with each increment in knowledge, we are increasingly faced with the realization of the overwhelming complexity of this organ system. ...

New and improved proteomics technologies for understanding complex biological systems: addressing a grand challenge in the life sciences.

PubMed

Hood, Leroy E; Omenn, Gilbert S; Moritz, Robert L; Aebersold, Ruedi; Yamamoto, Keith R; Amos, Michael; Hunter-Cevera, Jennie; Locascio, Laurie

2012-09-01

This White Paper sets out a Life Sciences Grand Challenge for Proteomics Technologies to enhance our understanding of complex biological systems, link genomes with phenotypes, and bring broad benefits to the biosciences and the US economy. The paper is based on a workshop hosted by the National Institute of Standards and Technology (NIST) in Gaithersburg, MD, 14-15 February 2011, with participants from many federal R&D agencies and research communities, under the aegis of the US National Science and Technology Council (NSTC). Opportunities are identified for a coordinated R&D effort to achieve major technology-based goals and address societal challenges in health, agriculture, nutrition, energy, environment, national security, and economic development. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Correlations in electrically coupled chaotic lasers.

PubMed

Rosero, E J; Barbosa, W A S; Martinez Avila, J F; Khoury, A Z; Rios Leite, J R

2016-09-01

We show how two electrically coupled semiconductor lasers having optical feedback can present simultaneous antiphase correlated fast power fluctuations, and strong in-phase synchronized spikes of chaotic power drops. This quite counterintuitive phenomenon is demonstrated experimentally and confirmed by numerical solutions of a deterministic dynamical system of rate equations. The occurrence of negative and positive cross correlation between parts of a complex system according to time scales, as proved in our simple arrangement, is relevant for the understanding and characterization of collective properties in complex networks.

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

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

Camouflage and visual perception

PubMed Central

Troscianko, Tom; Benton, Christopher P.; Lovell, P. George; Tolhurst, David J.; Pizlo, Zygmunt

2008-01-01

How does an animal conceal itself from visual detection by other animals? This review paper seeks to identify general principles that may apply in this broad area. It considers mechanisms of visual encoding, of grouping and object encoding, and of search. In most cases, the evidence base comes from studies of humans or species whose vision approximates to that of humans. The effort is hampered by a relatively sparse literature on visual function in natural environments and with complex foraging tasks. However, some general constraints emerge as being potentially powerful principles in understanding concealment—a ‘constraint’ here means a set of simplifying assumptions. Strategies that disrupt the unambiguous encoding of discontinuities of intensity (edges), and of other key visual attributes, such as motion, are key here. Similar strategies may also defeat grouping and object-encoding mechanisms. Finally, the paper considers how we may understand the processes of search for complex targets in complex scenes. The aim is to provide a number of pointers towards issues, which may be of assistance in understanding camouflage and concealment, particularly with reference to how visual systems can detect the shape of complex, concealed objects. PMID:18990671

Connectivity in the human brain dissociates entropy and complexity of auditory inputs.

PubMed

Nastase, Samuel A; Iacovella, Vittorio; Davis, Ben; Hasson, Uri

2015-03-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. Copyright © 2014. Published by Elsevier Inc.

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

Agelastos, Anthony; Allan, Benjamin; Brandt, Jim

A detailed understanding of HPC applications’ resource needs and their complex interactions with each other and HPC platform resources are critical to achieving scalability and performance. Such understanding has been difficult to achieve because typical application profiling tools do not capture the behaviors of codes under the potentially wide spectrum of actual production conditions and because typical monitoring tools do not capture system resource usage information with high enough fidelity to gain sufficient insight into application performance and demands. In this paper we present both system and application profiling results based on data obtained through synchronized system wide monitoring onmore » a production HPC cluster at Sandia National Laboratories (SNL). We demonstrate analytic and visualization techniques that we are using to characterize application and system resource usage under production conditions for better understanding of application resource needs. Furthermore, our goals are to improve application performance (through understanding application-to-resource mapping and system throughput) and to ensure that future system capabilities match their intended workloads.« less

Landscape change in the southern Piedmont: challenges, solutions, and uncertainty across scales

USGS Publications Warehouse

Conroy, M.J.; Allen, Craig R.; Peterson, J.T.; Pritchard, L.J.; Moore, C.T.

2003-01-01

The southern Piedmont of the southeastern United States epitomizes the complex and seemingly intractable problems and hard decisions that result from uncontrolled urban and suburban sprawl. Here we consider three recurrent themes in complicated problems involving complex systems: (1) scale dependencies and cross-scale, often nonlinear relationships; (2) resilience, in particular the potential for complex systems to move to alternate stable states with decreased ecological and/or economic value; and (3) uncertainty in the ability to understand and predict outcomes, perhaps particularly those that occur as a result of human impacts. We consider these issues in the context of landscape-level decision making, using as an example water resources and lotic systems in the Piedmont region of the southeastern United States.

An Actor-Network Theory Analysis of Policy Innovation for Smoke-Free Places: Understanding Change in Complex Systems

PubMed Central

Borland, Ron; Coghill, Ken

2010-01-01

Complex, transnational issues like the tobacco epidemic are major challenges that defy analysis and management by conventional methods, as are other public health issues, such as those associated with global food distribution and climate change. We examined the evolution of indoor smoke-free regulations, a tobacco control policy innovation, and identified the key attributes of those jurisdictions that successfully pursued this innovation and those that to date have not. In doing so, we employed the actor-network theory, a comprehensive framework for the analysis of fundamental system change. Through our analysis, we identified approaches to help overcome some systemic barriers to the solution of the tobacco problem and comment on other complex transnational problems. PMID:20466949

An actor-network theory analysis of policy innovation for smoke-free places: understanding change in complex systems.

PubMed

Young, David; Borland, Ron; Coghill, Ken

2010-07-01

Complex, transnational issues like the tobacco epidemic are major challenges that defy analysis and management by conventional methods, as are other public health issues, such as those associated with global food distribution and climate change. We examined the evolution of indoor smoke-free regulations, a tobacco control policy innovation, and identified the key attributes of those jurisdictions that successfully pursued this innovation and those that to date have not. In doing so, we employed the actor-network theory, a comprehensive framework for the analysis of fundamental system change. Through our analysis, we identified approaches to help overcome some systemic barriers to the solution of the tobacco problem and comment on other complex transnational problems.

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

PubMed

Satanarachchi, Niranji; Mino, Takashi

2014-01-01

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

Systems Medicine: Sketching the Landscape.

PubMed

Kirschner, Marc

2016-01-01

To understand the meaning of the term Systems Medicine and to distinguish it from seemingly related other expressions currently in use, such as precision, personalized, -omics, or big data medicine, its underlying history and development into present time needs to be highlighted. Having this development in mind, it becomes evident that Systems Medicine is a genuine concept as well as a novel way of tackling the manifold complexity that occurs in nowadays clinical medicine-and not just a rebranding of what has previously been done in the past. So looking back it seems clear to many in the field that Systems Medicine has its origin in an integrative method to unravel biocomplexity, namely, Systems Biology. Here scientist by now gained useful experience that is on the verge toward implementation in clinical research and practice.Systems Medicine and Systems Biology have the same underlying theoretical principle in systems-based thinking-a methodology to understand complexity that can be traced back to ancient Greece. During the last decade, however, and due to a rapid methodological development in the life sciences and computing/IT technologies, Systems Biology has evolved from a scientific concept into an independent discipline most competent to tackle key questions of biocomplexity-with the potential to transform medicine and how it will be practiced in the future. To understand this process in more detail, the following section will thus give a short summary of the foundation of systems-based thinking and the different developmental stages including systems theory, the development of modern Systems Biology, and its transition into clinical practice. These are the components to pave the way toward Systems Medicine.

Understanding Global Change (UGC) as a Unifying Conceptual Framework for Teaching Ecology: Using UGC in a High School Biology Program to Integrate Earth Science and Biology, and to Demonstrate the Value of Modeling Global Systems in Promoting Conceptual Learning

NASA Astrophysics Data System (ADS)

Levine, J.; Bean, J. R.

2017-12-01

Global change science is ideal for NGSS-informed teaching, but presents a serious challenge to K-12 educators because it is complex and interdisciplinary- combining earth science, biology, chemistry, and physics. Global systems are themselves complex. Adding anthropogenic influences on those systems creates a formidable list of topics - greenhouse effect, climate change, nitrogen enrichment, introduced species, land-use change among them - which are often presented as a disconnected "laundry list" of "facts." This complexity, combined with public and mass-media scientific illiteracy, leaves global change science vulnerable to misrepresentation and politicization, creating additional challenges to teachers in public schools. Ample stand-alone, one-off, online resources, many of them excellent, are (to date) underutilized by teachers in the high school science course taken by most students: biology. The Understanding Global Change project (UGC) from the UC Berkeley Museum of Paleontology has created a conceptual framework that organizes, connects, and explains global systems, human and non-human drivers of change in those systems, and measurable changes in those systems. This organization and framework employ core ideas, crosscutting concepts, structure/function relationships, and system models in a unique format that facilitates authentic understanding, rather than memorization. This system serves as an organizing framework for the entire ecology unit of a forthcoming mainstream high school biology program. The UGC system model is introduced up front with its core informational graphic. The model is elaborated, step by step, by adding concepts and processes as they are introduced and explained in each chapter. The informational graphic is thus used in several ways: to organize material as it is presented, to summarize topics in each chapter and put them in perspective, and for review and critical thinking exercises that supplement the usual end-of-chapter lists of key terms.

Simulating complex intracellular processes using object-oriented computational modelling.

PubMed

Johnson, Colin G; Goldman, Jacki P; Gullick, William J

2004-11-01

The aim of this paper is to give an overview of computer modelling and simulation in cellular biology, in particular as applied to complex biochemical processes within the cell. This is illustrated by the use of the techniques of object-oriented modelling, where the computer is used to construct abstractions of objects in the domain being modelled, and these objects then interact within the computer to simulate the system and allow emergent properties to be observed. The paper also discusses the role of computer simulation in understanding complexity in biological systems, and the kinds of information which can be obtained about biology via simulation.

Ultraviolet-B radiation mobilizes uranium from uranium-dissolved organic carbon complexes in aquatic systems, demonstrated by asymmetrical flow field-flow fractionation.

PubMed

Nehete, Sachin Vilas; Christensen, Terje; Salbu, Brit; Teien, Hans-Christian

2017-05-05

Humic substances have a tendency to form complexes with metal ions in aquatic medium, impacting the metal mobility, decreasing bioavailability and toxicity. Ultraviolet-B (UV-B) radiation exposure degrades the humic substance, changes their molecular weight distribution and their metal binding capacity in aquatic medium. In this study, we experimented the effect of UV-B radiation on the uranium complexed with fulvic acids and humic acids in a soft water system at different pH, uranium concentrations and radiant exposure. The concentration and distribution of uranium in a complexed form were investigated by asymmetrical flow field-flow fractionation coupled to multi detection technique (AsFlFFF-UV-ICP-MS). The major concentration of uranium present in complexes was primarily associated with average and higher molecular weight fulvic and humic acids components. The concentration of uranium in a complexed form increased with increasing fulvic and humic acid concentrations as well as pH of the solution. The higher molecular weight fraction of uranium was degraded due to the UV-B exposure, transforming about 50% of the uranium-dissolved organic carbon complexes into low molecular weight uranium species in complex form with organic ligands and/or free form. The result also suggests AsFlFFF-UV-ICP-MS to be an important separation and detection technique for understanding the interaction of radionuclides with dissolved organic matter, tracking size distribution changes during degradation of organic complexes for understanding mobility, bioavailability and ecosystem transfer of radionuclides as well as metals. Copyright © 2017 Elsevier B.V. All rights reserved.

Sharing the responsibility for driver distraction across road transport systems: a systems approach to the management of distracted driving.

PubMed

Young, Kristie L; Salmon, Paul M

2015-01-01

Distracted driving is acknowledged universally as a large and growing road safety problem. Compounding the problem is that distracted driving is a complex, multifaceted issue influenced by a multitude of factors, organisations and individuals. As such, management of the problem is not straightforward. Numerous countermeasures have been developed and implemented across the globe. The vast majority of these measures have derived from the traditional reductionist, driver-centric approach to distraction and have failed to fully reflect the complex mix of actors and components that give rise to drivers becoming distracted. An alternative approach that is gaining momentum in road safety is the systems approach, which considers all components of the system and their interactions as an integrated whole. In this paper, we review the current knowledge base on driver distraction and argue that the systems approach is not currently being realised in practice. Adopting a more holistic, systems approach to distracted driving will not only improve existing knowledge and interventions from the traditional approach, but will enhance our understanding and management of distraction by considering the complex relationships and interactions of the multiple actors and the myriad sources, enablers and interventions that make up the distracted driving system. It is only by recognising and understanding how all of the system components work together to enable distraction to occur, that we can start to work on solutions to help mitigate the occurrence and consequences of distracted driving. Copyright © 2014 Elsevier Ltd. All rights reserved.

Hierarchy and Interactions in Environmental Interfaces Regarded as Biophysical Complex Systems

NASA Astrophysics Data System (ADS)

Mihailovic, Dragutin T.; Balaz, Igor

The field of environmental sciences is abundant with various interfaces and is the right place for the application of new fundamental approaches leading towards a better understanding of environmental phenomena. For example, following the definition of environmental interface by Mihailovic and Balaž [23], such interface can be placed between: human or animal bodies and surrounding air, aquatic species and water and air around them, and natural or artificially built surfaces (vegetation, ice, snow, barren soil, water, urban communities) and the atmosphere. Complex environmental interface systems are open and hierarchically organised, interactions between their constituent parts are nonlinear, and the interaction with the surrounding environment is noisy. These systems are therefore very sensitive to initial conditions, deterministic external perturbations and random fluctuations always present in nature. The study of noisy non-equilibrium processes is fundamental for modelling the dynamics of environmental interface systems and for understanding the mechanisms of spatio-temporal pattern formation in contemporary environmental sciences, particularly in environmental fluid mechanics. In modelling complex biophysical systems one of the main tasks is to successfully create an operative interface with the external environment. It should provide a robust and prompt translation of the vast diversity of external physical and/or chemical changes into a set of signals, which are "understandable" for an organism. Although the establishment of organisation in any system is of crucial importance for its functioning, it should not be forgotten that in biophysical systems we deal with real-life problems where a number of other conditions should be reached in order to put the system to work. One of them is the proper supply of the system by the energy. Therefore, we will investigate an aspect of dynamics of energy flow based on the energy balance equation. The energy as well as the exchange of biological, chemical and other physical quantities between interacting environmental interfaces can be represented by coupled maps. In this chapter we will address only two illustrative issues important for the modelling of interacting environmental interfaces regarded as complex systems. These are (i) use of algebra for modelling the autonomous establishment of local hierarchies in biophysical systems and (ii) numerical investigation of coupled maps representing exchange of energy, chemical and other relevant biophysical quantities between biophysical entities in their surrounding environment.

Characterizing Complexity of Containerized Cargo X-ray Images

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

Wang, Guangxing; Martz, Harry; Glenn, Steven

X-ray imaging can be used to inspect cargos imported into the United States. In order to better understand the performance of X-ray inspection systems, the X-ray characteristics (density, complexity) of cargo need to be quantified. In this project, an image complexity measure called integrated power spectral density (IPSD) was studied using both DNDO engineered cargos and stream-of-commerce (SOC) cargos. A joint distribution of cargo density and complexity was obtained. A support vector machine was used to classify the SOC cargos into four categories to estimate the relative fractions.

The methodology of multi-viewpoint clustering analysis

NASA Technical Reports Server (NTRS)

Mehrotra, Mala; Wild, Chris

1993-01-01

One of the greatest challenges facing the software engineering community is the ability to produce large and complex computer systems, such as ground support systems for unmanned scientific missions, that are reliable and cost effective. In order to build and maintain these systems, it is important that the knowledge in the system be suitably abstracted, structured, and otherwise clustered in a manner which facilitates its understanding, manipulation, testing, and utilization. Development of complex mission-critical systems will require the ability to abstract overall concepts in the system at various levels of detail and to consider the system from different points of view. Multi-ViewPoint - Clustering Analysis MVP-CA methodology has been developed to provide multiple views of large, complicated systems. MVP-CA provides an ability to discover significant structures by providing an automated mechanism to structure both hierarchically (from detail to abstract) and orthogonally (from different perspectives). We propose to integrate MVP/CA into an overall software engineering life cycle to support the development and evolution of complex mission critical systems.

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

PubMed

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

2018-02-01

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

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase one, volume 1 : summary report.

DOT National Transportation Integrated Search

2009-12-01

The Integrated Remote Sensing and Visualization System (IRSV) is being designed to accommodate the needs of todays Bridge : Engineers at the state and local level from the following aspects: : Better understanding and enforcement of a complex ...

Implementing New Teacher Evaluation Systems: Principals' Concerns and Supervisor Support

ERIC Educational Resources Information Center

Derrington, Mary Lynne; Campbell, John W.

2015-01-01

Principal leadership is the key to successful implementation of mandated, high-accountability, teacher evaluation systems. Given the magnitude and complexity of change at the school level, understanding principals' perceptions, responses, and concerns is essential for effective change and support during implementation. Thus, research that…

Role of future scenarios in understanding deep uncertainty in long-term air quality management

EPA Science Inventory

The environment and its interactions with human systems, whether economic, social or political, are complex. Relevant drivers may disrupt system dynamics in unforeseen ways, making it difficult to predict future conditions. This kind of deep uncertainty presents a challenge to ...

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.

Multiparametric Imaging of Organ System Interfaces

PubMed Central

Vandoorne, Katrien; Nahrendorf, Matthias

2017-01-01

Cardiovascular diseases are a consequence of genetic and environmental risk factors that together generate arterial wall and cardiac pathologies. Blood vessels connect multiple systems throughout the entire body and allow organs to interact via circulating messengers. These same interactions facilitate nervous and metabolic system influence on cardiovascular health. Multiparametric imaging offers the opportunity to study these interfacing systems’ distinct processes, to quantify their interactions and to explore how these contribute to cardiovascular disease. Noninvasive multiparametric imaging techniques are emerging tools that can further our understanding of this complex and dynamic interplay. PET/MRI and multichannel optical imaging are particularly promising because they can simultaneously sample multiple biomarkers. Preclinical multiparametric diagnostics could help discover clinically relevant biomarker combinations pivotal for understanding cardiovascular disease. Interfacing systems important to cardiovascular disease include the immune, nervous and hematopoietic systems. These systems connect with ‘classical’ cardiovascular organs, like the heart and vasculature, and with the brain. The dynamic interplay between these systems and organs enables processes such as hemostasis, inflammation, angiogenesis, matrix remodeling, metabolism and fibrosis. As the opportunities provided by imaging expand, mapping interconnected systems will help us decipher the complexity of cardiovascular disease and monitor novel therapeutic strategies. PMID:28360260

Systems microscopy: an emerging strategy for the life sciences.

PubMed

Lock, John G; Strömblad, Staffan

2010-05-01

Dynamic cellular processes occurring in time and space are fundamental to all physiology and disease. To understand complex and dynamic cellular processes therefore demands the capacity to record and integrate quantitative multiparametric data from the four spatiotemporal dimensions within which living cells self-organize, and to subsequently use these data for the mathematical modeling of cellular systems. To this end, a raft of complementary developments in automated fluorescence microscopy, cell microarray platforms, quantitative image analysis and data mining, combined with multivariate statistics and computational modeling, now coalesce to produce a new research strategy, "systems microscopy", which facilitates systems biology analyses of living cells. Systems microscopy provides the crucial capacities to simultaneously extract and interrogate multiparametric quantitative data at resolution levels ranging from the molecular to the cellular, thereby elucidating a more comprehensive and richly integrated understanding of complex and dynamic cellular systems. The unique capacities of systems microscopy suggest that it will become a vital cornerstone of systems biology, and here we describe the current status and future prospects of this emerging field, as well as outlining some of the key challenges that remain to be overcome. Copyright 2010 Elsevier Inc. All rights reserved.

Plant Systems Biology at the Single-Cell Level.

PubMed

Libault, Marc; Pingault, Lise; Zogli, Prince; Schiefelbein, John

2017-11-01

Our understanding of plant biology is increasingly being built upon studies using 'omics and system biology approaches performed at the level of the entire plant, organ, or tissue. Although these approaches open new avenues to better understand plant biology, they suffer from the cellular complexity of the analyzed sample. Recent methodological advances now allow plant scientists to overcome this limitation and enable biological analyses of single-cells or single-cell-types. Coupled with the development of bioinformatics and functional genomics resources, these studies provide opportunities for high-resolution systems analyses of plant phenomena. In this review, we describe the recent advances, current challenges, and future directions in exploring the biology of single-cells and single-cell-types to enhance our understanding of plant biology as a system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automated speech understanding: the next generation

NASA Astrophysics Data System (ADS)

Picone, J.; Ebel, W. J.; Deshmukh, N.

1995-04-01

Modern speech understanding systems merge interdisciplinary technologies from Signal Processing, Pattern Recognition, Natural Language, and Linguistics into a unified statistical framework. These systems, which have applications in a wide range of signal processing problems, represent a revolution in Digital Signal Processing (DSP). Once a field dominated by vector-oriented processors and linear algebra-based mathematics, the current generation of DSP-based systems rely on sophisticated statistical models implemented using a complex software paradigm. Such systems are now capable of understanding continuous speech input for vocabularies of several thousand words in operational environments. The current generation of deployed systems, based on small vocabularies of isolated words, will soon be replaced by a new technology offering natural language access to vast information resources such as the Internet, and provide completely automated voice interfaces for mundane tasks such as travel planning and directory assistance.

The System of the Learner Experiencing Difficulty: Some Reflections on the Use of a Simulation as a Tool for Investigating and Analysing Elements of a Complex System.

ERIC Educational Resources Information Center

Thatcher, Donald; Robinson, June

1990-01-01

Discusses learning systems and learning difficulties, and describes the use of a simulation to help professionals better understand people with learning difficulties. The General Systems Theory and a systems approach are discussed, the role of debriefing is considered, and theoretical perspectives on the development of learning disabilities are…

Using Systems Thinking to train future leaders in global health.

PubMed

Paxton, Anne; Frost, Laura J

2017-07-09

Systems Thinking provides a useful set of concepts and tools that can be used to train students to be effective and innovative global health leaders in an ever-changing and often chaotic world. This paper describes an experiential, multi-disciplinary curriculum that uses Systems Thinking to frame and analyse global health policies and practices. The curriculum uses case studies and hands-on activities to deepen students' understanding of the following concepts: complex adaptive systems, dynamic complexity, inter-relationships, feedback loops, policy resistance, mental models, boundary critique, leverage points, and multi-disciplinary, multi-sectoral, and multi-stakeholder thinking and action. A sample of Systems Thinking tools for analysing global health policies and practices are also introduced.

Making sense in a complex landscape: how the Cynefin Framework from Complex Adaptive Systems Theory can inform health promotion practice.

PubMed

Van Beurden, Eric K; Kia, Annie M; Zask, Avigdor; Dietrich, Uta; Rose, Lauren

2013-03-01

Health promotion addresses issues from the simple (with well-known cause/effect links) to the highly complex (webs and loops of cause/effect with unpredictable, emergent properties). Yet there is no conceptual framework within its theory base to help identify approaches appropriate to the level of complexity. The default approach favours reductionism--the assumption that reducing a system to its parts will inform whole system behaviour. Such an approach can yield useful knowledge, yet is inadequate where issues have multiple interacting causes, such as social determinants of health. To address complex issues, there is a need for a conceptual framework that helps choose action that is appropriate to context. This paper presents the Cynefin Framework, informed by complexity science--the study of Complex Adaptive Systems (CAS). It introduces key CAS concepts and reviews the emergence and implications of 'complex' approaches within health promotion. It explains the framework and its use with examples from contemporary practice, and sets it within the context of related bodies of health promotion theory. The Cynefin Framework, especially when used as a sense-making tool, can help practitioners understand the complexity of issues, identify appropriate strategies and avoid the pitfalls of applying reductionist approaches to complex situations. The urgency to address critical issues such as climate change and the social determinants of health calls for us to engage with complexity science. The Cynefin Framework helps practitioners make the shift, and enables those already engaged in complex approaches to communicate the value and meaning of their work in a system that privileges reductionist approaches.

Structure, dynamics and biophysics of the cytoplasmic protein–protein complexes of the bacterial phosphoenolpyruvate: Sugar phosphotransferase system

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

Clore, G. Marius; Venditti, Vincenzo

2013-10-01

The bacterial phosphotransferase system (PTS) couples phosphoryl transfer, via a series of bimolecular protein–protein interactions, to sugar transport across the membrane. The multitude of complexes in the PTS provides a paradigm for studying protein interactions, and for understanding how the same binding surface can specifically recognize a diverse array of targets. Fifteen years of work aimed at solving the solution structures of all soluble protein–protein complexes of the PTS has served as a test bed for developing NMR and integrated hybrid approaches to study larger complexes in solution and to probe transient, spectroscopically invisible states, including encounter complexes. We reviewmore » these approaches, highlighting the problems that can be tackled with these methods, and summarize the current findings on protein interactions.« less

Cognitive process modelling of controllers in en route air traffic control.

PubMed

Inoue, Satoru; Furuta, Kazuo; Nakata, Keiichi; Kanno, Taro; Aoyama, Hisae; Brown, Mark

2012-01-01

In recent years, various efforts have been made in air traffic control (ATC) to maintain traffic safety and efficiency in the face of increasing air traffic demands. ATC is a complex process that depends to a large degree on human capabilities, and so understanding how controllers carry out their tasks is an important issue in the design and development of ATC systems. In particular, the human factor is considered to be a serious problem in ATC safety and has been identified as a causal factor in both major and minor incidents. There is, therefore, a need to analyse the mechanisms by which errors occur due to complex factors and to develop systems that can deal with these errors. From the cognitive process perspective, it is essential that system developers have an understanding of the more complex working processes that involve the cooperative work of multiple controllers. Distributed cognition is a methodological framework for analysing cognitive processes that span multiple actors mediated by technology. In this research, we attempt to analyse and model interactions that take place in en route ATC systems based on distributed cognition. We examine the functional problems in an ATC system from a human factors perspective, and conclude by identifying certain measures by which to address these problems. This research focuses on the analysis of air traffic controllers' tasks for en route ATC and modelling controllers' cognitive processes. This research focuses on an experimental study to gain a better understanding of controllers' cognitive processes in air traffic control. We conducted ethnographic observations and then analysed the data to develop a model of controllers' cognitive process. This analysis revealed that strategic routines are applicable to decision making.

An association account of false belief understanding.

PubMed

De Bruin, L C; Newen, A

2012-05-01

The elicited-response false belief task has traditionally been considered as reliably indicating that children acquire an understanding of false belief around 4 years of age. However, recent investigations using spontaneous-response tasks suggest that false belief understanding emerges much earlier. This leads to a developmental paradox: if young infants already understand false belief, then why do they fail the elicited-response false belief task? We postulate two systems to account for the development of false belief understanding: an association module, which provides infants with the capacity to register congruent associations between agents and objects, and an operating system, which allows them to transform these associations into incongruent associations through a process of inhibition, selection and representation. The interaction between the association module and the operating system enables infants to register increasingly complex associations on the basis of another agent's movements, visual perspective and propositional attitudes. This allows us account for the full range of findings on false belief understanding. Copyright © 2012 Elsevier B.V. All rights reserved.

Retention Mechanisms of Citric Acid in Ternary Kaolinite-Fe(III)-Citrate Acid Systems Using Fe K-edge EXAFS and L3,2-edge XANES Spectroscopy

PubMed Central

Yang, Jianjun; Wang, Jian; Pan, Weinan; Regier, Tom; Hu, Yongfeng; Rumpel, Cornelia; Bolan, Nanthi; Sparks, Donald

2016-01-01

Organic carbon (OC) stability in tropical soils is strongly interlinked with multivalent cation interaction and mineral association. Low molecular weight organic acids (LMWOAs) represent the readily biodegradable OC. Therefore, investigating retention mechanisms of LMWOAs in mineral-cation-LMWOAs systems is critical to understanding soil C cycling. Given the general acidic conditions and dominance of kaolinite in tropical soils, we investigated the retention mechanisms of citric acid (CA) in kaolinite-Fe(III)-CA systems with various Fe/CA molar ratios at pH ~3.5 using Fe K-edge EXAFS and L3,2-edge XANES techniques. With Fe/CA molar ratios >2, the formed ferrihydrite mainly contributed to CA retention through adsorption and/or coprecipitation. With Fe/CA molar ratios from 2 to 0.5, ternary complexation of CA to kaolinite via a five-coordinated Fe(III) bridge retained higher CA than ferrihydrite-induced adsorption and/or coprecipitation. With Fe/CA molar ratios ≤0.5, kaolinite-Fe(III)-citrate complexation preferentially occurred, but less CA was retained than via outer-sphere kaolinite-CA complexation. This study highlighted the significant impact of varied Fe/CA molar ratios on CA retention mechanisms in kaolinite-Fe(III)-CA systems under acidic conditions, and clearly showed the important contribution of Fe-bridged ternary complexation on CA retention. These findings will enhance our understanding of the dynamics of CA and other LMWOAs in tropical soils. PMID:27212680

Retention mechanisms of citric acid in ternary kaolinite-Fe(III)-citrate acid systems using Fe K-edge EXAFS and L 3,2-edge XANES spectroscopy

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

Yang, Jianjun; Wang, Jian; Pan, Weinan

Organic carbon (OC) stability in tropical soils is strongly interlinked with multivalent cation interaction and mineral association. Low molecular weight organic acids (LMWOAs) represent the readily biodegradable OC. Therefore, investigating retention mechanisms of LMWOAs in mineral-cation-LMWOAs systems is critical to understanding soil C cycling. Given the general acidic conditions and dominance of kaolinite in tropical soils, we investigated the retention mechanisms of citric acid (CA) in kaolinite-Fe(III)-CA systems with various Fe/CA molar ratios at pH ~3.5 using Fe K-edge EXAFS and L- 3,2-edge XANES techniques. With Fe/CA molar ratios >2, the formed ferrihydrite mainly contributed to CA retention through adsorptionmore » and/or coprecipitation. With Fe/CA molar ratios from 2 to 0.5, ternary complexation of CA to kaolinite via a five-coordinated Fe(III) bridge retained higher CA than ferrihydrite-induced adsorption and/or coprecipitation. With Fe/CA molar ratios ≤ 0.5, kaolinite-Fe(III)-citrate complexation preferentially occurred, but less CA was retained than via outer-sphere kaolinite-CA complexation. This study highlighted the significant impact of varied Fe/CA molar ratios on CA retention mechanisms in kaolinite-Fe(III)-CA systems under acidic conditions, and clearly showed the important contribution of Fe-bridged ternary complexation on CA retention. In conclusion, these findings will enhance our understanding of the dynamics of CA and other LMWOAs in tropical soils.« less

Retention mechanisms of citric acid in ternary kaolinite-Fe(III)-citrate acid systems using Fe K-edge EXAFS and L 3,2-edge XANES spectroscopy

DOE PAGES

Yang, Jianjun; Wang, Jian; Pan, Weinan; ...

2016-05-23

Organic carbon (OC) stability in tropical soils is strongly interlinked with multivalent cation interaction and mineral association. Low molecular weight organic acids (LMWOAs) represent the readily biodegradable OC. Therefore, investigating retention mechanisms of LMWOAs in mineral-cation-LMWOAs systems is critical to understanding soil C cycling. Given the general acidic conditions and dominance of kaolinite in tropical soils, we investigated the retention mechanisms of citric acid (CA) in kaolinite-Fe(III)-CA systems with various Fe/CA molar ratios at pH ~3.5 using Fe K-edge EXAFS and L- 3,2-edge XANES techniques. With Fe/CA molar ratios >2, the formed ferrihydrite mainly contributed to CA retention through adsorptionmore » and/or coprecipitation. With Fe/CA molar ratios from 2 to 0.5, ternary complexation of CA to kaolinite via a five-coordinated Fe(III) bridge retained higher CA than ferrihydrite-induced adsorption and/or coprecipitation. With Fe/CA molar ratios ≤ 0.5, kaolinite-Fe(III)-citrate complexation preferentially occurred, but less CA was retained than via outer-sphere kaolinite-CA complexation. This study highlighted the significant impact of varied Fe/CA molar ratios on CA retention mechanisms in kaolinite-Fe(III)-CA systems under acidic conditions, and clearly showed the important contribution of Fe-bridged ternary complexation on CA retention. In conclusion, these findings will enhance our understanding of the dynamics of CA and other LMWOAs in tropical soils.« less

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

An evolutionary link between capsular biogenesis and surface motility in bacteria.

PubMed

Agrebi, Rym; Wartel, Morgane; Brochier-Armanet, Céline; Mignot, Tâm

2015-05-01

Studying the evolution of macromolecular assemblies is important to improve our understanding of how complex cellular structures evolved, and to identify the functional building blocks that are involved. Recent studies suggest that the macromolecular complexes that are involved in two distinct processes in Myxococcus xanthus - surface motility and sporulation - are derived from an ancestral polysaccharide capsule assembly system. In this Opinion article, we argue that the available data suggest that the motility machinery evolved from this capsule assembly system following a gene duplication event, a change in carbohydrate polymer specificity and the acquisition of additional proteins by the motility complex, all of which are key features that distinguish the motility and sporulation systems. Furthermore, the presence of intermediates of these systems in bacterial genomes suggests a testable evolutionary model for their emergence and spread.

Adjoint equations and analysis of complex systems: Application to virus infection modelling

NASA Astrophysics Data System (ADS)

Marchuk, G. I.; Shutyaev, V.; Bocharov, G.

2005-12-01

Recent development of applied mathematics is characterized by ever increasing attempts to apply the modelling and computational approaches across various areas of the life sciences. The need for a rigorous analysis of the complex system dynamics in immunology has been recognized since more than three decades ago. The aim of the present paper is to draw attention to the method of adjoint equations. The methodology enables to obtain information about physical processes and examine the sensitivity of complex dynamical systems. This provides a basis for a better understanding of the causal relationships between the immune system's performance and its parameters and helps to improve the experimental design in the solution of applied problems. We show how the adjoint equations can be used to explain the changes in hepatitis B virus infection dynamics between individual patients.

Understanding the complex relationships among actors involved in the implementation of public-private mix (PPM) for TB control in India, using social theory.

PubMed

Salve, Solomon; Harris, Kristine; Sheikh, Kabir; Porter, John D H

2018-06-07

Public Private Partnerships (PPP) are increasingly utilized as a public health strategy for strengthening health systems and have become a core component for the delivery of TB control services in India, as promoted through national policy. However, partnerships are complex systems that rely on relationships between a myriad of different actors with divergent agendas and backgrounds. Relationship is a crucial element of governance, and relationship building an important aspect of partnerships. To understand PPPs a multi-disciplinary perspective that draws on insights from social theory is needed. This paper demonstrates how social theory can aid the understanding of the complex relationships of actors involved in implementation of Public-Private Mix (PPM)-TB policy in India. Ethnographic research was conducted within a district in a Southern state of India over a 14 month period, combining participant observations, informal interactions and in-depth interviews with a wide range of respondents across public, private and non-government organisation (NGO) sectors. Drawing on the theoretical insights from Bourdieu's "theory of practice" this study explores the relationships between the different actors. The study found that programme managers, frontline TB workers, NGOs, and private practitioners all had a crucial role to play in TB partnerships. They were widely regarded as valued contributors with distinct social skills and capabilities within their organizations and professions. However, their potential contributions towards programme implementation tended to be unrecognized both at the top and bottom of the policy implementation chain. These actors constantly struggled for recognition and used different mechanisms to position themselves alongside other actors within the programme that further complicated the relationships between different actors. This paper demonstrates that applying social theory can enable a better understanding of the complex relationship across public, private and NGO sectors. A closer understanding of these processes is a prerequisite for bridging the gap between field-level practices and central policy intentions, facilitating a move towards more effective partnership strategies for strengthening local health systems. The study contributes to our understanding of implementation of PPP for TB control and builds knowledge to help policy makers and programme managers strengthen and effectively implement strategies to enable stronger governance of these partnerships.

Can a biologist fix a smartphone?-Just hack it!

PubMed

Kamoun, Sophien

2017-05-08

Biological systems integrate multiscale processes and networks and are, therefore, viewed as difficult to dissect. However, because of the clear-cut separation between the software code (the information encoded in the genome sequence) and hardware (organism), genome editors can operate as software engineers to hack biological systems without any particularly deep understanding of the complexity of the systems.

Application of Intelligent Tutoring Technology to an Apparently Mechanical Task.

ERIC Educational Resources Information Center

Newman, Denis

The increasing automation of many occupations leads to jobs that involve understanding and monitoring the operation of complex computer systems. One case is PATRIOT, an air defense surface-to-air missile system deployed by the U.S. Army. Radar information is processed and presented to the operators in highly abstract form. The system identifies…

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...

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.

A conceptual connectivity framework for understanding geomorphic change in human-impacted fluvial systems

NASA Astrophysics Data System (ADS)

Pöppl, Ronald; Keesstra, Saskia; Maroulis, Jerry

2017-04-01

Human-induced landscape change is difficult to predict due to the complexity inherent in both geomorphic and social systems as well as due to emerging coupling relationships between them. To better understand system complexity and system response to change, connectivity has become an important research paradigm within various disciplines including geomorphology, hydrology and ecology. With the proposed conceptual connectivity framework on geomorphic change in human-impacted fluvial systems a cautionary note is flagged regarding the need (i) to include and to systematically conceptualise the role of different types of human agency in altering connectivity relationships in geomorphic systems and (ii) to integrate notions of human-environment interactions to connectivity concepts in geomorphology to better explain causes and trajectories of landscape change. Underpinned by case study examples, the presented conceptual framework is able to explain how geomorphic response of fluvial systems to human disturbance is determined by system-specific boundary conditions (incl. system history, related legacy effects and lag times), vegetation dynamics and human-induced functional relationships (i.e. feedback mechanisms) between the different spatial dimensions of connectivity. It is further demonstrated how changes in social systems can trigger a process-response feedback loop between social and geomorphic systems that further governs the trajectory of landscape change in coupled human-geomorphic systems.

Investigation of Stimulation-Response Relationships for Complex Fracture Systems in Enhanced Geothermal Reservoirs

DOE Data Explorer

Fu, Pengcheng; Johnson, Scott M.; Carrigan, Charles R.

2011-01-01

Hydraulic fracturing is currently the primary method for stimulating low-permeability geothermal reservoirs and creating Enhanced (or Engineered) Geothermal Systems (EGS) with improved permeability and heat production efficiency. Complex natural fracture systems usually exist in the formations to be stimulated and it is therefore critical to understand the interactions between existing fractures and newly created fractures before optimal stimulation strategies can be developed. Our study aims to improve the understanding of EGS stimulation-response relationships by developing and applying computer-based models that can effectively reflect the key mechanisms governing interactions between complex existing fracture networks and newly created hydraulic fractures. In this paper, we first briefly describe the key modules of our methodology, namely a geomechanics solver, a discrete fracture flow solver, a rock joint response model, an adaptive remeshing module, and most importantly their effective coupling. After verifying the numerical model against classical closed-form solutions, we investigate responses of reservoirs with different preexisting natural fractures to a variety of stimulation strategies. The factors investigated include: the in situ stress states (orientation of the principal stresses and the degree of stress anisotropy), pumping pressure, and stimulation sequences of multiple wells.

Investigating accident causation through information network modelling.

PubMed

Griffin, T G C; Young, M S; Stanton, N A

2010-02-01

Management of risk in complex domains such as aviation relies heavily on post-event investigations, requiring complex approaches to fully understand the integration of multi-causal, multi-agent and multi-linear accident sequences. The Event Analysis of Systemic Teamwork methodology (EAST; Stanton et al. 2008) offers such an approach based on network models. In this paper, we apply EAST to a well-known aviation accident case study, highlighting communication between agents as a central theme and investigating the potential for finding agents who were key to the accident. Ultimately, this work aims to develop a new model based on distributed situation awareness (DSA) to demonstrate that the risk inherent in a complex system is dependent on the information flowing within it. By identifying key agents and information elements, we can propose proactive design strategies to optimize the flow of information and help work towards avoiding aviation accidents. Statement of Relevance: This paper introduces a novel application of an holistic methodology for understanding aviation accidents. Furthermore, it introduces an ongoing project developing a nonlinear and prospective method that centralises distributed situation awareness and communication as themes. The relevance of findings are discussed in the context of current ergonomic and aviation issues of design, training and human-system interaction.

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.

Parasites, ecosystems and sustainability: an ecological and complex systems perspective.

PubMed

Horwitz, Pierre; Wilcox, Bruce A

2005-06-01

Host-parasite relationships can be conceptualised either narrowly, where the parasite is metabolically dependent on the host, or more broadly, as suggested by an ecological-evolutionary and complex systems perspective. In this view Host-parasite relationships are part of a larger set of ecological and co-evolutionary interdependencies and a complex adaptive system. These interdependencies affect not just the hosts, vectors, parasites, the immediate agents, but also those indirectly or consequentially affected by the relationship. Host-parasite relationships also can be viewed as systems embedded within larger systems represented by ecological communities and ecosystems. So defined, it can be argued that Host-parasite relationships may often benefit their hosts and contribute significantly to the structuring of ecological communities. The broader, complex adaptive system view also contributes to understanding the phenomenon of disease emergence, the ecological and evolutionary mechanisms involved, and the role of parasitology in research and management of ecosystems in light of the apparently growing problem of emerging infectious diseases in wildlife and humans. An expanded set of principles for integrated parasite management is suggested by this perspective.

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.

Concussion As a Multi-Scale Complex System: An Interdisciplinary Synthesis of Current Knowledge

PubMed Central

Kenzie, Erin S.; Parks, Elle L.; Bigler, Erin D.; Lim, Miranda M.; Chesnutt, James C.; Wakeland, Wayne

2017-01-01

Traumatic brain injury (TBI) has been called “the most complicated disease of the most complex organ of the body” and is an increasingly high-profile public health issue. Many patients report long-term impairments following even “mild” injuries, but reliable criteria for diagnosis and prognosis are lacking. Every clinical trial for TBI treatment to date has failed to demonstrate reliable and safe improvement in outcomes, and the existing body of literature is insufficient to support the creation of a new classification system. Concussion, or mild TBI, is a highly heterogeneous phenomenon, and numerous factors interact dynamically to influence an individual’s recovery trajectory. Many of the obstacles faced in research and clinical practice related to TBI and concussion, including observed heterogeneity, arguably stem from the complexity of the condition itself. To improve understanding of this complexity, we review the current state of research through the lens provided by the interdisciplinary field of systems science, which has been increasingly applied to biomedical issues. The review was conducted iteratively, through multiple phases of literature review, expert interviews, and systems diagramming and represents the first phase in an effort to develop systems models of concussion. The primary focus of this work was to examine concepts and ways of thinking about concussion that currently impede research design and block advancements in care of TBI. Results are presented in the form of a multi-scale conceptual framework intended to synthesize knowledge across disciplines, improve research design, and provide a broader, multi-scale model for understanding concussion pathophysiology, classification, and treatment. PMID:29033888

Data based identification and prediction of nonlinear and complex dynamical systems

NASA Astrophysics Data System (ADS)

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

2016-07-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods outlined in this Review are principled on various concepts in complexity science and engineering such as phase transitions, bifurcations, stabilities, and robustness. The methodologies have the potential to significantly improve our ability to understand a variety of complex dynamical systems ranging from gene regulatory systems to social networks toward the ultimate goal of controlling such systems.

Equilibrium Speciation of Select Lanthanides in the Presence of Acidic Ligands in Homo- and Heterogeneous Solutions

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

Robinson, Troy A

2011-08-01

This dissertation explores lanthanide speciation in liquid solution systems related to separation schemes involving the acidic ligands: bis(2-ethylhexyl) phosphoric acid (HDEHP), lactate, and 8-hydroxyquinoline. Equilibrium speciation of neodymium (Nd 3+), sodium (Na+), HDEHP, water, and lactate in the TALSPEAK liquid-liquid extraction system was explored under varied Nd 3+ loading of HDEHP in the organic phase and through extraction from aqueous HCl and lactate media. System speciation was probed through vapor pressure osmometry, visible and Fourier Transform Infrared (FTIR) spectroscopy, 22Na and 13C labeled lactate radiotracer distribution measurements, Karl Fischer titrations, and equilibrium pH measurements. Distribution of Nd 3+, Na +,more » lactate, and equilibrium pH were modeled using the SXLSQI software to obtain logKNd and logKNa extraction constants under selected conditions. Results showed that high Nd 3+ loading of the HDEHP led to Nd 3+ speciation that departs from the ion exchange mechanism and includes formation of highly aggregated, polynuclear [NdLactate(DEHP) 2] x; (with x > 1). By substituting lanthanum (La 3+) for Nd 3+ in this system, NMR scoping experiments using 23Na, 31P nuclei and 13C labeled lactate were performed. Results indicated that this technique is sensitive to changes in system speciation, and that further experiments are warranted. In a homogeneous system representing the TALSPEAK aqueous phase, Lactate protonation behavior at various temperatures was characterized using a combination of potentiometric titration and modeling with the Hyperquad computer program. The temperature dependent deprotonation behavior of lactate showed little change with temperature at 2.0 M NaCl ionic strength. Cloud point extraction is a non-traditional separation technique that starts with a homogeneous phase that becomes heterogeneous by the micellization of surfactants through the increase of temperature. To better understand the behavior of europium (Eu 3+) and 8-hydroxyquinoline under cloud point extraction conditions, potentiometric and spectrophotometric titrations coupled with modeling with Hyperquad and SQUAD computer programs were performed to assess europium (Eu 3+) and 8-hydroxyquinoline speciation. Experiments in both water and a 1wt% Triton X-114/water mixed solvent were compared to understand the effect of Triton X-114 on the system speciation. Results indicated that increased solvation of 8-hydroxyquinoline by the mixed solvent lead to more stable complexes involving 8-hydroxyquinoline than in water, whereas competition between hydroxide and Triton X-114 for Eu 3+ led to lower stability hydrolysis complexes in the mixed solvent than in water. Lanthanide speciation is challenging due to the trivalent oxidation state that leads to multiple ligand complexes, including some mixed complexes. The complexity of the system demands well-designed and precise experiments that capture the nuances of the chemistry. This work increased the understanding of lanthanide speciation in the explored systems, but more work is required to produce a comprehensive understanding of the speciation involved.« less

Approaching human language with complex networks

NASA Astrophysics Data System (ADS)

Cong, Jin; Liu, Haitao

2014-12-01

The interest in modeling and analyzing human language with complex networks is on the rise in recent years and a considerable body of research in this area has already been accumulated. We survey three major lines of linguistic research from the complex network approach: 1) characterization of human language as a multi-level system with complex network analysis; 2) linguistic typological research with the application of linguistic networks and their quantitative measures; and 3) relationships between the system-level complexity of human language (determined by the topology of linguistic networks) and microscopic linguistic (e.g., syntactic) features (as the traditional concern of linguistics). We show that the models and quantitative tools of complex networks, when exploited properly, can constitute an operational methodology for linguistic inquiry, which contributes to the understanding of human language and the development of linguistics. We conclude our review with suggestions for future linguistic research from the complex network approach: 1) relationships between the system-level complexity of human language and microscopic linguistic features; 2) expansion of research scope from the global properties to other levels of granularity of linguistic networks; and 3) combination of linguistic network analysis with other quantitative studies of language (such as quantitative linguistics).

Understanding the value of mixed methods research: the Children's Safety Initiative-Emergency Medical Services.

PubMed

Hansen, Matthew; O'Brien, Kerth; Meckler, Garth; Chang, Anna Marie; Guise, Jeanne-Marie

2016-07-01

Mixed methods research has significant potential to broaden the scope of emergency care and specifically emergency medical services investigation. Mixed methods studies involve the coordinated use of qualitative and quantitative research approaches to gain a fuller understanding of practice. By combining what is learnt from multiple methods, these approaches can help to characterise complex healthcare systems, identify the mechanisms of complex problems such as medical errors and understand aspects of human interaction such as communication, behaviour and team performance. Mixed methods approaches may be particularly useful for out-of-hospital care researchers because care is provided in complex systems where equipment, interpersonal interactions, societal norms, environment and other factors influence patient outcomes. The overall objectives of this paper are to (1) introduce the fundamental concepts and approaches of mixed methods research and (2) describe the interrelation and complementary features of the quantitative and qualitative components of mixed methods studies using specific examples from the Children's Safety Initiative-Emergency Medical Services (CSI-EMS), a large National Institutes of Health-funded research project conducted in the USA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Active Learning to Understand Infectious Disease Models and Improve Policy Making

PubMed Central

Vladislavleva, Ekaterina; Broeckhove, Jan; Beutels, Philippe; Hens, Niel

2014-01-01

Modeling plays a major role in policy making, especially for infectious disease interventions but such models can be complex and computationally intensive. A more systematic exploration is needed to gain a thorough systems understanding. We present an active learning approach based on machine learning techniques as iterative surrogate modeling and model-guided experimentation to systematically analyze both common and edge manifestations of complex model runs. Symbolic regression is used for nonlinear response surface modeling with automatic feature selection. First, we illustrate our approach using an individual-based model for influenza vaccination. After optimizing the parameter space, we observe an inverse relationship between vaccination coverage and cumulative attack rate reinforced by herd immunity. Second, we demonstrate the use of surrogate modeling techniques on input-response data from a deterministic dynamic model, which was designed to explore the cost-effectiveness of varicella-zoster virus vaccination. We use symbolic regression to handle high dimensionality and correlated inputs and to identify the most influential variables. Provided insight is used to focus research, reduce dimensionality and decrease decision uncertainty. We conclude that active learning is needed to fully understand complex systems behavior. Surrogate models can be readily explored at no computational expense, and can also be used as emulator to improve rapid policy making in various settings. PMID:24743387

Active learning to understand infectious disease models and improve policy making.

PubMed

Willem, Lander; Stijven, Sean; Vladislavleva, Ekaterina; Broeckhove, Jan; Beutels, Philippe; Hens, Niel

2014-04-01

Modeling plays a major role in policy making, especially for infectious disease interventions but such models can be complex and computationally intensive. A more systematic exploration is needed to gain a thorough systems understanding. We present an active learning approach based on machine learning techniques as iterative surrogate modeling and model-guided experimentation to systematically analyze both common and edge manifestations of complex model runs. Symbolic regression is used for nonlinear response surface modeling with automatic feature selection. First, we illustrate our approach using an individual-based model for influenza vaccination. After optimizing the parameter space, we observe an inverse relationship between vaccination coverage and cumulative attack rate reinforced by herd immunity. Second, we demonstrate the use of surrogate modeling techniques on input-response data from a deterministic dynamic model, which was designed to explore the cost-effectiveness of varicella-zoster virus vaccination. We use symbolic regression to handle high dimensionality and correlated inputs and to identify the most influential variables. Provided insight is used to focus research, reduce dimensionality and decrease decision uncertainty. We conclude that active learning is needed to fully understand complex systems behavior. Surrogate models can be readily explored at no computational expense, and can also be used as emulator to improve rapid policy making in various settings.

USER MANUAL FOR THE EPA THIRD-GENERATION AIR QUALITY MODELING SYSTEM (MODELS-3 VERSION 3.0)

EPA Science Inventory

Models-3 is a flexible software system designed to simplify the development and use of environmental assessment and other decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of atmospheri...

The World of Juvenile Justice According to the Numbers

ERIC Educational Resources Information Center

Rozalski, Michael; Deignan, Marilyn; Engel, Suzanne

2008-01-01

Intended to be an instructive, yet sobering, introduction to the complex and disturbing nature of the juvenile justice system, this article details the "numbers," including selected percentages, ratios, and dollar amounts, that are relevant to developing a better understanding of the juvenile justice system. General statistics about juvenile and…

MODELS-3 INSTALLATION PROCEDURES FOR A PC WITH AN NT OPERATING SYSTEM (MODELS-3 VERSION 4.0)

EPA Science Inventory

Models-3 is a flexible software system designed to simplify the development and use of air quality models and other environmental decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of at...

MODELS-3 INSTALLATION PROCEDURES FOR A PERSONAL COMPUTER WITH A NT OPERATING SYSTEM (MODELS-3 VERSION 4.1)

EPA Science Inventory

Models-3 is a flexible system designed to simplify the development and use of air quality models and other environmental decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of atmospheric...

Entropy: A Unifying Path for Understanding Complexity in Natural, Artificial and Social Systems

DTIC Science & Technology

2011-07-01

data in what concerns its consequences. Definitively the BG entropy can only be understood nowadays as a first, most important, step, but not as the...applications to natural systems (trapped ions, spin-glass, dusty plasma, earthquakes, turbulence, astrophysical objects, cosmology , black holes, etc

Understanding and Advancing Campus Sustainability Using a Systems Framework

ERIC Educational Resources Information Center

Posner, Stephen M.; Stuart, Ralph

2013-01-01

Purpose: University campuses behave as complex systems, and sustainability in higher education is best seen as an emergent quality that arises from interactions both within an institution and between the institution and the environmental and social contexts in which it operates. A framework for strategically prioritizing campus sustainability work…

Synthesis for the Interdisciplinary Environmental Sciences: Integrating Systems Approaches and Service Learning

ERIC Educational Resources Information Center

Simon, Gregory L.; Wee, Bryan Shao-Chang; Chin, Anne; Tindle, Amy Depierre; Guth, Dan; Mason, Hillary

2013-01-01

As our understanding of complex environmental issues increases, institutions of higher education are evolving to develop new learning models that emphasize synthesis across disciplines, concepts, data, and methodologies. To this end, we argue for the implementation of environmental science education at the intersection of systems theory and…

CARBON AND NITROGEN ALLOCATION MODEL FOR THE SEAGRASS THALASSIA TESTUDUNUM IN LOWER LAGUNA MADRE

EPA Science Inventory

Inverse modeling methods are a powerful tool for understanding complex physiological relationships between seagrasses and their environment. The power of the method is a result of using ranges of data in a system of constraints to describe the biological system, in this case, t...

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Science of the science, drug discovery and artificial neural networks.

PubMed

Patel, Jigneshkumar

2013-03-01

Drug discovery process many times encounters complex problems, which may be difficult to solve by human intelligence. Artificial Neural Networks (ANNs) are one of the Artificial Intelligence (AI) technologies used for solving such complex problems. ANNs are widely used for primary virtual screening of compounds, quantitative structure activity relationship studies, receptor modeling, formulation development, pharmacokinetics and in all other processes involving complex mathematical modeling. Despite having such advanced technologies and enough understanding of biological systems, drug discovery is still a lengthy, expensive, difficult and inefficient process with low rate of new successful therapeutic discovery. In this paper, author has discussed the drug discovery science and ANN from very basic angle, which may be helpful to understand the application of ANN for drug discovery to improve efficiency.

The role of TREX in gene expression and disease

PubMed Central

Heath, Catherine G.; Viphakone, Nicolas; Wilson, Stuart A.

2016-01-01

TRanscription and EXport (TREX) is a conserved multisubunit complex essential for embryogenesis, organogenesis and cellular differentiation throughout life. By linking transcription, mRNA processing and export together, it exerts a physiologically vital role in the gene expression pathway. In addition, this complex prevents DNA damage and regulates the cell cycle by ensuring optimal gene expression. As the extent of TREX activity in viral infections, amyotrophic lateral sclerosis and cancer emerges, the need for a greater understanding of TREX function becomes evident. A complete elucidation of the composition, function and interactions of the complex will provide the framework for understanding the molecular basis for a variety of diseases. This review details the known composition of TREX, how it is regulated and its cellular functions with an emphasis on mammalian systems. PMID:27679854

Toward the adoption of complexity science in health care: implications for risk-taking and decision-making activities.

PubMed

Perez, Bianca; Liberman, Aaron

2011-01-01

This article explores the issues of risk taking and decision making in health care. An analysis of various sociocultural and psychological influences is provided for understanding of the dominant mind set in this industry. In tandem with this analysis, the evolution of system theories is described so as to promote understanding of the relative merits of the mechanistic and complexity philosophies. These philosophies are at odds with each other, conceptually and practically speaking; however, it seems that the complexity approach offers more promising strategies for the growth and development of health care. Recommendations for improving employee competencies and the organizational structure and culture in health care are offered in light of this analysis. These recommendations are relevant to activities that are clinical and administrative in nature.

Systematic approach to understanding the pathogenesis of systemic sclerosis.

PubMed

Zuo, Xiaoxia; Zhang, Lihua; Luo, Hui; Li, Yisha; Zhu, Honglin

2017-10-01

Systemic sclerosis (SSc) is a complex heterogeneous autoimmune disease. Progressive organ fibrosis is a major contributor to SSc mortality. Despite extensive efforts, the underlying mechanism of SSc remains unclear. Efforts to understand the pathogenesis of SSc have included genomics, epigenetics, transcriptomic, proteomic and metabolomic studies in the last decade. This review focuses on recent studies in SSc research based on multi-omics. The combination of these technologies can help us understand the pathogenesis of SSc. This review aims to provide important information for disease identification, therapeutic targets and potential biomarkers. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Neurological Disease in Lupus: Toward a Personalized Medicine Approach

PubMed Central

McGlasson, Sarah; Wiseman, Stewart; Wardlaw, Joanna; Dhaun, Neeraj; Hunt, David P. J.

2018-01-01

The brain and nervous system are important targets for immune-mediated damage in systemic lupus erythematosus (SLE), resulting in a complex spectrum of neurological syndromes. Defining nervous system disease in lupus poses significant challenges. Among the difficulties to be addressed are a diversity of clinical manifestations and a lack of understanding of their mechanistic basis. However, despite these challenges, progress has been made in the identification of pathways which contribute to neurological disease in SLE. Understanding the molecular pathogenesis of neurological disease in lupus will inform both classification and approaches to clinical trials. PMID:29928273

The Role of Microbiota on the Gut Immunology.

PubMed

Min, Yang Won; Rhee, Poong-Lyul

2015-05-01

The human gut contains >100 trillion microbes. This microbiota plays a crucial role in the gut homeostasis. Importantly, the microbiota contributes to the development and regulation of the gut immune system. Dysbiosis of the gut microbiota could also cause several intestinal and extraintestinal diseases. Many experimental studies help us to understand the complex interplay between the host and microbiota. This review presents our current understanding of the mucosal immune system and the role of gut microbiota for the development and functionality of the mucosal immunity, with a particular focus on gut-associated lymphoid tissues, mucosal barrier, TH17 cells, regulatory T cells, innate lymphoid cells, dendritic cells, and IgA-producing B cells and plasma cells. Comparative studies using germ-free and conventionally-raised animals reveal that the presence of microbiota is important for the development and regulation of innate and adaptive immune systems. The host-microbial symbiosis seems necessary for gut homeostasis. However, the precise mechanisms by which microbiota contributes to development and functionality of the immune system remain to be elucidated. Understanding the complex interplay between the host and microbiota and further investigation of the host-microbiota relationship could provide us the insight into the therapeutic and/or preventive strategy for the disorders related to dysbiosis of the gut microbiota. Copyright © 2015 Elsevier HS Journals, Inc. All rights reserved.

PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows

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

Deelman, Ewa; Carothers, Christopher; Mandal, Anirban

Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation andmore » data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.« less

Disaster preparedness in a complex urban system: the case of Kathmandu Valley, Nepal.

PubMed

Carpenter, Samuel; Grünewald, François

2016-07-01

The city is a growing centre of humanitarian concern. Yet, aid agencies, governments and donors are only beginning to comprehend the scale and, importantly, the complexity of the humanitarian challenge in urban areas. Using the case study of the Kathmandu Valley, Nepal, this paper examines the analytical utility of recent research on complex urban systems in strengthening scholarly understanding of urban disaster risk management, and outlines its operational relevance to disaster preparedness. Drawing on a literature review and 26 interviews with actors from across the Government of Nepal, the International Red Cross and Red Crescent Movement, non-governmental organisations, United Nations agencies, and at-risk communities, the study argues that complexity can be seen as a defining feature of urban systems and the risks that confront them. To manage risk in these systems effectively, preparedness efforts must be based on adaptive and agile approaches, incorporating the use of network analysis, partnerships, and new technologies. © 2016 The Author(s). Disasters © Overseas Development Institute, 2016.

PANORAMA: An approach to performance modeling and diagnosis of extreme-scale workflows

DOE PAGES

Deelman, Ewa; Carothers, Christopher; Mandal, Anirban; ...

2015-07-14

Here we report that computational science is well established as the third pillar of scientific discovery and is on par with experimentation and theory. However, as we move closer toward the ability to execute exascale calculations and process the ensuing extreme-scale amounts of data produced by both experiments and computations alike, the complexity of managing the compute and data analysis tasks has grown beyond the capabilities of domain scientists. Therefore, workflow management systems are absolutely necessary to ensure current and future scientific discoveries. A key research question for these workflow management systems concerns the performance optimization of complex calculation andmore » data analysis tasks. The central contribution of this article is a description of the PANORAMA approach for modeling and diagnosing the run-time performance of complex scientific workflows. This approach integrates extreme-scale systems testbed experimentation, structured analytical modeling, and parallel systems simulation into a comprehensive workflow framework called Pegasus for understanding and improving the overall performance of complex scientific workflows.« less

The mucosal immune system of fish: the evolution of tolerating commensals while fighting pathogens

PubMed Central

Gomez, Daniela; Sunyer, J Oriol; Salinas, Irene

2013-01-01

The field of mucosal immunology research has grown fast over the past few years, and our understanding on how mucosal surfaces respond to complex antigenic cocktails is expanding tremendously. With the advent of new molecular sequencing techniques, it is easier to understand how the immune system of vertebrates is, to a great extent, orchestrated by the complex microbial communities that live in symbiosis with their hosts. The commensal microbiota is now seen as the “extended self” by many scientists. Similarly, fish immunologist are devoting important research efforts to the field of mucosal immunity and commensals. Recent breakthroughs on our understanding of mucosal immune responses in teleost fish open up the potential of teleosts as animal research models for the study of human mucosal diseases. Additionally, this new knowledge places immunologists in a better position to specifically target the fish mucosal immune system while rationally designing mucosal vaccines and other immunotherapies. In this review, an updated view on how teleost skin, gills and gut immune cells and molecules, function in response to pathogens and commensals is provided. Finally, some of the future avenues that the field of fish mucosal immunity may follow in the next years are highlighted. PMID:24099804

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.

Towards sustainable infrastructure management: knowledge-based service-oriented computing framework for visual analytics

NASA Astrophysics Data System (ADS)

Vatcha, Rashna; Lee, Seok-Won; Murty, Ajeet; Tolone, William; Wang, Xiaoyu; Dou, Wenwen; Chang, Remco; Ribarsky, William; Liu, Wanqiu; Chen, Shen-en; Hauser, Edd

2009-05-01

Infrastructure management (and its associated processes) is complex to understand, perform and thus, hard to make efficient and effective informed decisions. The management involves a multi-faceted operation that requires the most robust data fusion, visualization and decision making. In order to protect and build sustainable critical assets, we present our on-going multi-disciplinary large-scale project that establishes the Integrated Remote Sensing and Visualization (IRSV) system with a focus on supporting bridge structure inspection and management. This project involves specific expertise from civil engineers, computer scientists, geographers, and real-world practitioners from industry, local and federal government agencies. IRSV is being designed to accommodate the essential needs from the following aspects: 1) Better understanding and enforcement of complex inspection process that can bridge the gap between evidence gathering and decision making through the implementation of ontological knowledge engineering system; 2) Aggregation, representation and fusion of complex multi-layered heterogeneous data (i.e. infrared imaging, aerial photos and ground-mounted LIDAR etc.) with domain application knowledge to support machine understandable recommendation system; 3) Robust visualization techniques with large-scale analytical and interactive visualizations that support users' decision making; and 4) Integration of these needs through the flexible Service-oriented Architecture (SOA) framework to compose and provide services on-demand. IRSV is expected to serve as a management and data visualization tool for construction deliverable assurance and infrastructure monitoring both periodically (annually, monthly, even daily if needed) as well as after extreme events.

State-of-the-art Nanofabrication in Catalysis.

PubMed

Karim, Waiz; Tschupp, Simon A; Herranz, Juan; Schmidt, Thomas J; Ekinci, Yasin; van Bokhovenac, Jeroen A

2017-04-26

We present recent developments in top-down nanofabrication that have found application in catalysis research. To unravel the complexity of catalytic systems, the design and use of models with control of size, morphology, shape and inter-particle distances is a necessity. The study of well-defined and ordered nanoparticles on a support contributes to the understanding of complex phenomena that govern reactions in heterogeneous and electro-catalysis. We review the strengths and limitations of different nanolithography methods such as electron beam lithography (EBL), photolithography, extreme ultraviolet (EUV) lithography and colloidal lithography for the creation of such highly tunable catalytic model systems and their applications in catalysis. Innovative strategies have enabled particle sizes reaching dimensions below 10 nm. It is now possible to create pairs of particles with distance controlled with an extremely high precision in the order of one nanometer. We discuss our approach to study these model systems at the single-particle level using X-ray absorption spectroscopy and show new ways to fabricate arrays of single nanoparticles or nanoparticles in pairs over a large area using EBL and EUV-achromatic Talbot lithography. These advancements have provided new insights into the active sites in metal catalysts and enhanced the understanding of the role of inter-particle interactions and catalyst supports, such as in the phenomenon of hydrogen spillover. We present a perspective on future directions for employing top-down nanofabrication in heterogeneous and electrocatalysis. The rapid development in nanofabrication and characterization methods will continue to have an impact on understanding of complex catalytic processes.

Evaluation in context: ATC automation in the field

NASA Technical Reports Server (NTRS)

Harwood, Kelly; Sanford, Beverly

1994-01-01

The process for incorporating advanced technologies into complex aviation systems is as important as the final product itself. This paper described a process that is currently being applied to the development and assessment of an advanced ATC automation system, CTAS. The key element of the process is field exposure early in the system development cycle. The process deviates from current established practices of system development -- where field testing is an implementation endpoint -- and has been deemed necessary by the FAA for streamlining development and bringing system functions to a level of stability and usefulness. Methods and approaches for field assessment are borrowed from human factors engineering, cognitive engineering, and usability engineering and are tailored for the constraints of an operational ATC environment. To date, the focus has been on the qualitative assessment of the match between TMA capabilities and the context for their use. Capturing the users' experience with the automation tool and understanding tool use in the context of the operational environment is important, not only for developing a tool that is an effective problem-solving instrument but also for defining meaningful operational requirements. Such requirements form the basis for certifying the safety and efficiency of the system. CTAS is the first U.S. advanced ATC automation system of its scope and complexity to undergo this field development and assessment process. With the rapid advances in aviation technologies and our limited understanding of their impact on system performance, it is time we opened our eyes to new possibilities for developing, validating, and ultimately certifying complex aviation systems.

Watersheds in Baltimore, Maryland: understanding and application of integrated ecological and social processes

Treesearch

Steward T.A. Pickett; Kenneth T. Belt; Michael F. Galvin; Peter M. Groffman; J. Morgan Grove; Donald C. Outen; Richard V. Pouyat; William P. Stack; Mary L. Cadenasso

2007-01-01

The Water and Watersheds program has made significant and lasting contributions to the basic understanding of the complex ecological system of Baltimore, MD. Funded at roughly the same time as the urban Long- Term Ecological Research (LTER) project in Baltimore, the Water and Watersheds grant and the LTER grant together established the Baltimore Ecosystem Study (BES)...

Understanding a Brazilian High School Blended Learning Environment from the Perspective of Complex Systems

ERIC Educational Resources Information Center

de Barros, Ana Paula Rodrigues Magalhães; Simmt, Elaine; Maltempi, Marcus Vinicius

2017-01-01

The use of technological resources has the potential to make viable new and less traditional methodologies of teaching that take into account student differences. Blended learning can be a way to rethink classes so that students have more freedom in their processes of learning. The goal of this article is to understand a blended learning…

Normal venous anatomy and physiology of the lower extremity.

PubMed

Notowitz, L B

1993-06-01

Venous disease of the lower extremities is common but is often misunderstood. It seems that the focus is on the exciting world of arterial anatomy and pathology, while the topic of venous anatomy and pathology comes in second place. However, venous diseases such as chronic venous insufficiency, leg ulcers, and varicose veins affect much of the population and may lead to disability and death. Nurses are often required to answer complex questions from the patients and his or her family about the patient's disease. Patients depend on nurses to provide accurate information in terms they can understand. Therefore it is important to have an understanding of the normal venous system of the legs before one can understand the complexities of venous diseases and treatments. This presents an overview of normal venous anatomy and physiology.

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

Complex Intelligent Systems: Juxtaposition of Foundational Notions and a Research Agenda

NASA Astrophysics Data System (ADS)

Gelepithis, Petros A.

2001-11-01

The cardinality of the class, C , of complex intelligent systems, i.e., systems of intelligent systems and their resources, is steadily increasing. Such an increase, whether designed, sometimes changes significantly and fundamentally, the structure of C . Recently,the study of members of C and its structure comes under a variety of multidisciplinary headings the most prominent of which include General Systems Theory, Complexity Science, Artificial Life, and Cybernetics. Their common characteristic is the quest for a unified theory of a certain class of systems like a living system or an organisation. So far, the only candidate for a general theory of intelligent systems is Newell's Soar. To my knowledge there is presently no candidate theory of C except Newell's claimed extensibility of Soar. This paper juxtaposes the elements of Newell's conceptual basis with those of an alternative conceptual framework based on the thesis that communication and understanding are the primary processes shaping the structure of C and its members. It is patently obvious that a research agenda for the study of C can be extremely varied and long. The third section of this paper presents a highly selective research agenda that aims to provoke discussion among complexity theory scientists.

How to predict community responses to perturbations in the face of imperfect knowledge and network complexity

USGS Publications Warehouse

Aufderheide, Helge; Rudolf, Lars; Gross, Thilo; Lafferty, Kevin D.

2013-01-01

Recent attempts to predict the response of large food webs to perturbations have revealed that in larger systems increasingly precise information on the elements of the system is required. Thus, the effort needed for good predictions grows quickly with the system's complexity. Here, we show that not all elements need to be measured equally well, suggesting that a more efficient allocation of effort is possible. We develop an iterative technique for determining an efficient measurement strategy. In model food webs, we find that it is most important to precisely measure the mortality and predation rates of long-lived, generalist, top predators. Prioritizing the study of such species will make it easier to understand the response of complex food webs to perturbations.

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

PubMed

Haimes, Yacov Y

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Statistical Physics of Cascading Failures in Complex Networks

NASA Astrophysics Data System (ADS)

Panduranga, Nagendra Kumar

Systems such as the power grid, world wide web (WWW), and internet are categorized as complex systems because of the presence of a large number of interacting elements. For example, the WWW is estimated to have a billion webpages and understanding the dynamics of such a large number of individual agents (whose individual interactions might not be fully known) is a challenging task. Complex network representations of these systems have proved to be of great utility. Statistical physics is the study of emergence of macroscopic properties of systems from the characteristics of the interactions between individual molecules. Hence, statistical physics of complex networks has been an effective approach to study these systems. In this dissertation, I have used statistical physics to study two distinct phenomena in complex systems: i) Cascading failures and ii) Shortest paths in complex networks. Understanding cascading failures is considered to be one of the "holy grails" in the study of complex systems such as the power grid, transportation networks, and economic systems. Studying failures of these systems as percolation on complex networks has proved to be insightful. Previously, cascading failures have been studied extensively using two different models: k-core percolation and interdependent networks. The first part of this work combines the two models into a general model, solves it analytically, and validates the theoretical predictions through extensive computer simulations. The phase diagram of the percolation transition has been systematically studied as one varies the average local k-core threshold and the coupling between networks. The phase diagram of the combined processes is very rich and includes novel features that do not appear in the models which study each of the processes separately. For example, the phase diagram consists of first- and second-order transition regions separated by two tricritical lines that merge together and enclose a two-stage transition region. In the two-stage transition, the size of the giant component undergoes a first-order jump at a certain occupation probability followed by a continuous second-order transition at a smaller occupation probability. Furthermore, at certain fixed interdependencies, the percolation transition cycles from first-order to second-order to two-stage to first-order as the k-core threshold is increased. We setup the analytical equations describing the phase boundaries of the two-stage transition region and we derive the critical exponents for each type of transition. Understanding the shortest paths between individual elements in systems like communication networks and social media networks is important in the study of information cascades in these systems. Often, large heterogeneity can be present in the connections between nodes in these networks. Certain sets of nodes can be more highly connected among themselves than with the nodes from other sets. These sets of nodes are often referred to as 'communities'. The second part of this work studies the effect of the presence of communities on the distribution of shortest paths in a network using a modular Erdős-Renyi network model. In this model, the number of communities and the degree of modularity of the network can be tuned using the parameters of the model. We find that the model reaches a percolation threshold while tuning the degree of modularity of the network and the distribution of the shortest paths in the network can be used as an indicator of how the communities are connected.

Qualitative "trial-sibling" studies and "unrelated" qualitative studies contributed to complex intervention reviews.

PubMed

Noyes, Jane; Hendry, Margaret; Lewin, Simon; Glenton, Claire; Chandler, Jackie; Rashidian, Arash

2016-06-01

To compare the contribution of "trial-sibling" and "unrelated" qualitative studies in complex intervention reviews. Researchers are using qualitative "trial-sibling" studies undertaken alongside trials to provide explanations to understand complex interventions. In the absence of qualitative "trial-sibling" studies, it is not known if qualitative studies "unrelated" to trials are helpful. Trials, "trial-sibling," and "unrelated" qualitative studies looking at three health system interventions were identified. We looked for similarities and differences between the two types of qualitative studies, such as participants, intervention delivery, context, study quality and reporting, and contribution to understanding trial results. Reporting was generally poor in both qualitative study types. We detected no substantial differences in participant characteristics. Interventions in qualitative "trial-sibling" studies were delivered using standardized protocols, whereas interventions in "unrelated" qualitative studies were delivered in routine care. Qualitative "trial-sibling" studies alone provided insufficient data to develop meaningful transferrable explanations beyond the trial context, and their limited focus on immediate implementation did not address all phenomena of interest. Together, "trial-sibling" and "unrelated" qualitative studies provided larger, richer data sets across contexts to better understand the phenomena of interest. Findings support inclusion of "trial-sibling" and "unrelated" qualitative studies to explore complexity in complex intervention reviews. Copyright © 2016 Elsevier Inc. All rights reserved.

The principles of collective animal behaviour

PubMed Central

Sumpter, D.J.T

2005-01-01

In recent years, the concept of self-organization has been used to understand collective behaviour of animals. The central tenet of self-organization is that simple repeated interactions between individuals can produce complex adaptive patterns at the level of the group. Inspiration comes from patterns seen in physical systems, such as spiralling chemical waves, which arise without complexity at the level of the individual units of which the system is composed. The suggestion is that biological structures such as termite mounds, ant trail networks and even human crowds can be explained in terms of repeated interactions between the animals and their environment, without invoking individual complexity. Here, I review cases in which the self-organization approach has been successful in explaining collective behaviour of animal groups and societies. Ant pheromone trail networks, aggregation of cockroaches, the applause of opera audiences and the migration of fish schools have all been accurately described in terms of individuals following simple sets of rules. Unlike the simple units composing physical systems, however, animals are themselves complex entities, and other examples of collective behaviour, such as honey bee foraging with its myriad of dance signals and behavioural cues, cannot be fully understood in terms of simple individuals alone. I argue that the key to understanding collective behaviour lies in identifying the principles of the behavioural algorithms followed by individual animals and of how information flows between the animals. These principles, such as positive feedback, response thresholds and individual integrity, are repeatedly observed in very different animal societies. The future of collective behaviour research lies in classifying these principles, establishing the properties they produce at a group level and asking why they have evolved in so many different and distinct natural systems. Ultimately, this research could inform not only our understanding of animal societies, but also the principles by which we organize our own society. PMID:16553306

The principles of collective animal behaviour.

PubMed

Sumpter, D J T

2006-01-29

In recent years, the concept of self-organization has been used to understand collective behaviour of animals. The central tenet of self-organization is that simple repeated interactions between individuals can produce complex adaptive patterns at the level of the group. Inspiration comes from patterns seen in physical systems, such as spiralling chemical waves, which arise without complexity at the level of the individual units of which the system is composed. The suggestion is that biological structures such as termite mounds, ant trail networks and even human crowds can be explained in terms of repeated interactions between the animals and their environment, without invoking individual complexity. Here, I review cases in which the self-organization approach has been successful in explaining collective behaviour of animal groups and societies. Ant pheromone trail networks, aggregation of cockroaches, the applause of opera audiences and the migration of fish schools have all been accurately described in terms of individuals following simple sets of rules. Unlike the simple units composing physical systems, however, animals are themselves complex entities, and other examples of collective behaviour, such as honey bee foraging with its myriad of dance signals and behavioural cues, cannot be fully understood in terms of simple individuals alone. I argue that the key to understanding collective behaviour lies in identifying the principles of the behavioural algorithms followed by individual animals and of how information flows between the animals. These principles, such as positive feedback, response thresholds and individual integrity, are repeatedly observed in very different animal societies. The future of collective behaviour research lies in classifying these principles, establishing the properties they produce at a group level and asking why they have evolved in so many different and distinct natural systems. Ultimately, this research could inform not only our understanding of animal societies, but also the principles by which we organize our own society.

From Molecules to Life: Quantifying the Complexity of Chemical and Biological Systems in the Universe.

PubMed

Böttcher, Thomas

2018-01-01

Life is a complex phenomenon and much research has been devoted to both understanding its origins from prebiotic chemistry and discovering life beyond Earth. Yet, it has remained elusive how to quantify this complexity and how to compare chemical and biological units on one common scale. Here, a mathematical description of molecular complexity was applied allowing to quantitatively assess complexity of chemical structures. This in combination with the orthogonal measure of information complexity resulted in a two-dimensional complexity space ranging over the entire spectrum from molecules to organisms. Entities with a certain level of information complexity directly require a functionally complex mechanism for their production or replication and are hence indicative for life-like systems. In order to describe entities combining molecular and information complexity, the term biogenic unit was introduced. Exemplified biogenic unit complexities were calculated for ribozymes, protein enzymes, multimeric protein complexes, and even an entire virus particle. Complexities of prokaryotic and eukaryotic cells, as well as multicellular organisms, were estimated. Thereby distinct evolutionary stages in complexity space were identified. The here developed approach to compare the complexity of biogenic units allows for the first time to address the gradual characteristics of prebiotic and life-like systems without the need for a definition of life. This operational concept may guide our search for life in the Universe, and it may direct the investigations of prebiotic trajectories that lead towards the evolution of complexity at the origins of life.

Are attractors 'strange', or is life more complicated than the simple laws of physics?

PubMed

Pogun, S

2001-01-01

Interesting and intriguing questions involve complex systems whose properties cannot be explained fully by reductionist approaches. Last century was dominated by physics, and applying the simple laws of physics to biology appeared to be a practical solution to understand living organisms. However, although some attributes of living organisms involve physico-chemical properties, the genetic program and evolutionary history of complex biological systems make them unique and unpredictable. Furthermore, there are and will be 'unobservable' phenomena in biology which have to be accounted for.

Multiscale Mathematics for Biomass Conversion to Renewable Hydrogen

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

Plechac, Petr

2016-03-01

The overall objective of this project was to develop multiscale models for understanding and eventually designing complex processes for renewables. To the best of our knowledge, our work is the first attempt at modeling complex reacting systems, whose performance relies on underlying multiscale mathematics and developing rigorous mathematical techniques and computational algorithms to study such models. Our specific application lies at the heart of biofuels initiatives of DOE and entails modeling of catalytic systems, to enable economic, environmentally benign, and efficient conversion of biomass into either hydrogen or valuable chemicals.

Weak Links: Stabilizers of Complex Systems from Proteins to Social Networks

NASA Astrophysics Data System (ADS)

Csermely, Peter

Why do women stabilize our societies? Why can we enjoy and understand Shakespeare? Why are fruitflies uniform? Why do omnivorous eating habits aid our survival? Why is Mona Lisa's smile beautiful? -- Is there any answer to these questions? This book shows that the statement: "weak links stabilize complex systems" holds the answers to all of the surprising questions above. The author (recipientof several distinguished science communication prizes) uses weak (low affinity, low probability) interactions as a thread to introduce a vast varietyof networks from proteins to ecosystems.

U.S. Geological Survey Groundwater Modeling Software: Making Sense of a Complex Natural Resource

USGS Publications Warehouse

Provost, Alden M.; Reilly, Thomas E.; Harbaugh, Arlen W.; Pollock, David W.

2009-01-01

Computer models of groundwater systems simulate the flow of groundwater, including water levels, and the transport of chemical constituents and thermal energy. Groundwater models afford hydrologists a framework on which to organize their knowledge and understanding of groundwater systems, and they provide insights water-resources managers need to plan effectively for future water demands. Building on decades of experience, the U.S. Geological Survey (USGS) continues to lead in the development and application of computer software that allows groundwater models to address scientific and management questions of increasing complexity.

Complexity: the organizing principle at the interface of biological (dis)order.

PubMed

Bhat, Ramray; Pally, Dharma

2017-07-01

The term complexity means several things to biologists.When qualifying morphological phenotype, on the one hand, it is used to signify the sheer complicatedness of living systems, especially as a result of the multicomponent aspect of biological form. On the other hand, it has been used to represent the intricate nature of the connections between constituents that make up form: a more process-based explanation. In the context of evolutionary arguments, complexity has been defined, in a quantifiable fashion, as the amount of information, an informatic template such as a sequence of nucleotides or amino acids stores about its environment. In this perspective, we begin with a brief review of the history of complexity theory. We then introduce a developmental and an evolutionary understanding of what it means for biological systems to be complex.We propose that the complexity of living systems can be understood through two interdependent structural properties: multiscalarity of interconstituent mechanisms and excitability of the biological materials. The answer to whether a system becomes more or less complex over time depends on the potential for its constituents to interact in novel ways and combinations to give rise to new structures and functions, as well as on the evolution of excitable properties that would facilitate the exploration of interconstituent organization in the context of their microenvironments and macroenvironments.

Understanding the immune response to seasonal influenza vaccination in older adults: a systems biology approach.

PubMed

Lambert, Nathaniel D; Ovsyannikova, Inna G; Pankratz, V Shane; Jacobson, Robert M; Poland, Gregory A

2012-08-01

Annual vaccination against seasonal influenza is recommended to decrease disease-related mortality and morbidity. However, one population that responds suboptimally to influenza vaccine is adults over the age of 65 years. The natural aging process is associated with a complex deterioration of multiple components of the host immune system. Research into this phenomenon, known as immunosenescence, has shown that aging alters both the innate and adaptive branches of the immune system. The intricate mechanisms involved in immune response to influenza vaccine, and how these responses are altered with age, have led us to adopt a more encompassing systems biology approach to understand exactly why the response to vaccination diminishes with age. Here, the authors review what changes occur with immunosenescence, and some immunogenetic factors that influence response, and outline the systems biology approach to understand the immune response to seasonal influenza vaccination in older adults.

A systemic approach to understanding mental health and services.

PubMed

Cohen, Mark

2017-10-01

In the UK mental health and associated NHS services face considerable challenges. This paper aims to form an understanding both of the complexity of context in which services operate and the means by which services have sought to meet these challenges. Systemic principles as have been applied to public service organisations with reference to interpersonal relations, the wider social culture and its manifestation in service provision. The analysis suggests that the wider culture has shaped service demand and the approaches adopted by services resulting in a number of unintended consequences, reinforcing loops, increased workload demands and the limited value of services. The systemic modelling of this situation provides a necessary overview prior to future policy development. The paper concludes that mental health and attendant services requires a systemic understanding and a whole system approach to reform. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Designing Better Scaffolding in Teaching Complex Systems with Graphical Simulations

NASA Astrophysics Data System (ADS)

Li, Na

Complex systems are an important topic in science education today, but they are usually difficult for secondary-level students to learn. Although graphic simulations have many advantages in teaching complex systems, scaffolding is a critical factor for effective learning. This dissertation study was conducted around two complementary research questions on scaffolding: (1) How can we chunk and sequence learning activities in teaching complex systems? (2) How can we help students make connections among system levels across learning activities (level bridging)? With a sample of 123 seventh-graders, this study employed a 3x2 experimental design that factored sequencing methods (independent variable 1; three levels) with level-bridging scaffolding (independent variable 2; two levels) and compared the effectiveness of each combination. The study measured two dependent variables: (1) knowledge integration (i.e., integrating and connecting content-specific normative concepts and providing coherent scientific explanations); (2) understanding of the deep causal structure (i.e., being able to grasp and transfer the causal knowledge of a complex system). The study used a computer-based simulation environment as the research platform to teach the ideal gas law as a system. The ideal gas law is an emergent chemical system that has three levels: (1) experiential macro level (EM) (e.g., an aerosol can explodes when it is thrown into the fire); (2) abstract macro level (AM) (i.e., the relationships among temperature, pressure and volume); (3) micro level (Mi) (i.e., molecular activity). The sequencing methods of these levels were manipulated by changing the order in which they were delivered with three possibilities: (1) EM-AM-Mi; (2) Mi-AM-EM; (3) AM-Mi-EM. The level-bridging scaffolding variable was manipulated on two aspects: (1) inserting inter-level questions among learning activities; (2) two simulations dynamically linked in the final learning activity. Addressing the first research question, the Experiential macro-Abstract macro-Micro (EM-AM-Mi) sequencing method, following the "concrete to abstract" principle, produced better knowledge integration while the Micro-Abstract macro-Experiential macro (Mi-AM-EM) sequencing method, congruent with the causal direction of the emergent system, produced better understanding of the deep causal structure only when level-bridging scaffolding was provided. The Abstract macro-Micro-Experiential macro (AM-Mi-EM) sequencing method produced worse performance in general, because it did not follow the "concrete to abstract" principle, nor did it align with the causal structure of the emergent system. As to the second research question, the results showed that level-bridging scaffolding was important for both knowledge integration and understanding of the causal structure in learning the ideal gas law system.

Physics and psychophysics of color reproduction

NASA Astrophysics Data System (ADS)

Giorgianni, Edward J.

1991-08-01

The successful design of a color-imaging system requires knowledge of the factors used to produce and control color. This knowledge can be derived, in part, from measurements of the physical properties of the imaging system. Color itself, however, is a perceptual response and cannot be directly measured. Though the visual process begins with physics, as radiant energy reaching the eyes, it is in the mind of the observer that the stimuli produced from this radiant energy are interpreted and organized to form meaningful perceptions, including the perception of color. A comprehensive understanding of color reproduction, therefore, requires not only a knowledge of the physical properties of color-imaging systems but also an understanding of the physics, psychophysics, and psychology of the human observer. The human visual process is quite complex; in many ways the physical properties of color-imaging systems are easier to understand.

Systems biology: A tool for charting the antiviral landscape.

PubMed

Bowen, James R; Ferris, Martin T; Suthar, Mehul S

2016-06-15

The host antiviral programs that are initiated following viral infection form a dynamic and complex web of responses that we have collectively termed as "the antiviral landscape". Conventional approaches to studying antiviral responses have primarily used reductionist systems to assess the function of a single or a limited subset of molecules. Systems biology is a holistic approach that considers the entire system as a whole, rather than individual components or molecules. Systems biology based approaches facilitate an unbiased and comprehensive analysis of the antiviral landscape, while allowing for the discovery of emergent properties that are missed by conventional approaches. The antiviral landscape can be viewed as a hierarchy of complexity, beginning at the whole organism level and progressing downward to isolated tissues, populations of cells, and single cells. In this review, we will discuss how systems biology has been applied to better understand the antiviral landscape at each of these layers. At the organismal level, the Collaborative Cross is an invaluable genetic resource for assessing how genetic diversity influences the antiviral response. Whole tissue and isolated bulk cell transcriptomics serves as a critical tool for the comprehensive analysis of antiviral responses at both the tissue and cellular levels of complexity. Finally, new techniques in single cell analysis are emerging tools that will revolutionize our understanding of how individual cells within a bulk infected cell population contribute to the overall antiviral landscape. Copyright © 2016 Elsevier B.V. All rights reserved.

Proof of Concept: A review on how network and systems biology approaches aid in the discovery of potent anticancer drug combinations

PubMed Central

Azmi, Asfar S.; Wang, Zhiwei; Philip, Philip A.; Mohammad, Ramzi M.; Sarkar, Fazlul H.

2010-01-01

Cancer therapies that target key molecules have not fulfilled expected promises for most common malignancies. Major challenges include the incomplete understanding and validation of these targets in patients, the multiplicity and complexity of genetic and epigenetic changes in the majority of cancers, and the redundancies and cross-talk found in key signaling pathways. Collectively, the uses of single-pathway targeted approaches are not effective therapies for human malignances. To overcome these barriers, it is important to understand the molecular cross-talk among key signaling pathways and how they may be altered by targeted agents. This requires innovative approaches such as understanding the global physiological environment of target proteins and the effects of modifying them without losing key molecular details. Such strategies will aid the design of novel therapeutics and their combinations against multifaceted diseases where efficacious combination therapies will focus on altering multiple pathways rather than single proteins. Integrated network modeling and systems biology has emerged as a powerful tool benefiting our understanding of drug mechanism of action in real time. This mini-review highlights the significance of the network and systems biology-based strategy and presents a “proof-of-concept” recently validated in our laboratory using the example of a combination treatment of oxaliplatin and the MDM2 inhibitor MI-219 in genetically complex and incurable pancreatic adenocarcinoma. PMID:21041384

System on a Chip (SoC) Overview

NASA Technical Reports Server (NTRS)

LaBel, Kenneth A.

2010-01-01

System-on-a-chip or system on chip (SoC or SOC) refers to integrating all components of a computer or other electronic system into a single integrated circuit (chip). It may contain digital, analog, mixed-signal, and often radio-frequency functions all on a single chip substrate. Complexity drives it all: Radiation tolerance and testability are challenges for fault isolation, propagation, and validation. Bigger single silicon die than flown before and technology is scaling below 90nm (new qual methods). Packages have changed and are bigger and more difficult to inspect, test, and understand. Add in embedded passives. Material interfaces are more complex (underfills, processing). New rules for board layouts. Mechanical and thermal designs, etc.

Study of the neural dynamics for understanding communication in terms of complex hetero systems.

PubMed

Tsuda, Ichiro; Yamaguchi, Yoko; Hashimoto, Takashi; Okuda, Jiro; Kawasaki, Masahiro; Nagasaka, Yasuo

2015-01-01

The purpose of the research project was to establish a new research area named "neural information science for communication" by elucidating its neural mechanism. The research was performed in collaboration with applied mathematicians in complex-systems science and experimental researchers in neuroscience. The project included measurements of brain activity during communication with or without languages and analyses performed with the help of extended theories for dynamical systems and stochastic systems. The communication paradigm was extended to the interactions between human and human, human and animal, human and robot, human and materials, and even animal and animal. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Balancing Broad Ideas with Context: An Evaluation of Student Accuracy in Describing Ecosystem Processes after a System-Level Intervention

ERIC Educational Resources Information Center

Jordan, Rebecca C.; Brooks, Wesley R.; Hmelo-Silver, Cindy; Eberbach, Catherine; Sinha, Suparna

2014-01-01

Promoting student understanding of ecosystem processes is critical to biological education. Yet, teaching complex life systems can be difficult because systems are dynamic and often behave in a non-linear manner. In this paper, we discuss assessment results from a middle school classroom intervention in which a conceptual representation framework…

Taking a systems approach to ecological systems

USGS Publications Warehouse

Grace, James B.

2015-01-01

Increasingly, there is interest in a systems-level understanding of ecological problems, which requires the evaluation of more complex, causal hypotheses. In this issue of the Journal of Vegetation Science, Soliveres et al. use structural equation modeling to test a causal network hypothesis about how tree canopies affect understorey communities. Historical analysis suggests structural equation modeling has been under-utilized in ecology.

Promoting Student Teachers' Content Related Knowledge in Teaching Systems Thinking: Measuring Effects of an Intervention through Evaluating a Videotaped Lesson

ERIC Educational Resources Information Center

Rosenkränzer, Frank; Kramer, Tim; Hörsch, Christian; Schuler, Stephan; Rieß, Werner

2016-01-01

The understanding of complex, dynamic and animate systems has a special standing in education for sustainable development and biology. Thus one important role of science teacher education is to promote student teachers' Content Related Knowledge (CRK) for teaching systems thinking, consisting of extensive Content Knowledge (CK) and well formed…

Transdisciplinary Application of Cross-Scale Resilience ...

EPA Pesticide Factsheets

The cross-scale resilience model was developed in ecology to explain the emergence of resilience from the distribution of ecological functions within and across scales, and as a tool to assess resilience. We propose that the model and the underlyingdiscontinuity hypothesis are relevant to other complex adaptive systems, and can be used to identify and track changes in system parameters related to resilience. We explain the theory behind the cross-scale resilience model, review the cases where it has been applied to non-ecological systems, and discuss some examples of social-ecological, archaeological/anthropological, and economic systems where a cross-scale resilience analysis could add a quantitative dimension to our current understanding of system dynamics and resilience. We argue that the scaling and diversity parameters suitable for a resilience analysis of ecological systems are appropriate for a broad suite of systems where non-normative quantitative assessments of resilience are desired. Our planet is currently characterized by fast environmental and social change, and the cross-scale resilience model has the potential to quantify resilience across many types of complex adaptive systems. Comparative analyses of complex systems have, in fact, demonstrated commonalities among distinctly different types of systems (Schneider & Kay 1994; Holling 2001; Lansing 2003; Foster 2005; Bullmore et al. 2009). Both biological and non-biological complex systems appear t

The Mechanism of Room-Temperature Ionic-Liquid-Based Electrochemical CO₂ Reduction: A Review.

PubMed

Lim, Hyung-Kyu; Kim, Hyungjun

2017-03-28

Electrochemical CO₂ conversion technology is becoming indispensable in the development of a sustainable carbon-based economy. While various types of electrocatalytic systems have been designed, those based on room-temperature ionic liquids (RTILs) have attracted considerable attention because of their high efficiencies and selectivities. Furthermore, it should be possible to develop more advanced electrocatalytic systems for commercial use because target-specific characteristics can be fine-tuned using various combinations of RTIL ions. To achieve this goal, we require a systematic understanding of the role of the RTIL components in electrocatalytic systems, however, their role has not yet been clarified by experiment or theory. Thus, the purpose of this short review is to summarize recent experimental and theoretical mechanistic studies to provide insight into and to develop guidelines for the successful development of new CO₂ conversion systems. The results discussed here can be summarized as follows. Complex physical and chemical interactions between the RTIL components and the reaction intermediates, in particular at the electrode surface, are critical for determining the activity and selectivity of the electrocatalytic system, although no single factor dominates. Therefore, more fundamental research is required to understand the physical, chemical, and thermodynamic characteristics of complex RTIL-based electrocatalytic systems.

The Challenge of Wireless Reliability and Coexistence.

PubMed

Berger, H Stephen

2016-09-01

Wireless communication plays an increasingly important role in healthcare delivery. This further heightens the importance of wireless reliability, but quantifying wireless reliability is a complex and difficult challenge. Understanding the risks that accompany the many benefits of wireless communication should be a component of overall risk management. The emerging trend of using sensors and other device-to-device communications, as part of the emerging Internet of Things concept, is evident in healthcare delivery. The trend increases both the importance and complexity of this challenge. As with most system problems, finding a solution requires breaking down the problem into manageable steps. Understanding the operational reliability of a new wireless device and its supporting system requires developing solid, quantified answers to three questions: 1) How well can this new device and its system operate in a spectral environment where many other wireless devices are also operating? 2) What is the spectral environment in which this device and its system are expected to operate? Are the risks and reliability in its operating environment acceptable? 3) How might the new device and its system affect other devices and systems already in use? When operated under an insightful risk management process, wireless technology can be safely implemented, resulting in improved delivery of care.

Characterizing Tityus discrepans scorpion venom from a fractal perspective: Venom complexity, effects of captivity, sexual dimorphism, differences among species.

PubMed

D'Suze, Gina; Sandoval, Moisés; Sevcik, Carlos

2015-12-15

A characteristic of venom elution patterns, shared with many other complex systems, is that many their features cannot be properly described with statistical or euclidean concepts. The understanding of such systems became possible with Mandelbrot's fractal analysis. Venom elution patterns were produced using the reversed phase high performance liquid chromatography (HPLC) with 1 mg of venom. One reason for the lack of quantitative analyses of the sources of venom variability is parametrizing the venom chromatograms' complexity. We quantize this complexity by means of an algorithm which estimates the contortedness (Q) of a waveform. Fractal analysis was used to compare venoms and to measure inter- and intra-specific venom variability. We studied variations in venom complexity derived from gender, seasonal and environmental factors, duration of captivity in the laboratory, technique used to milk venom. Copyright © 2015 Elsevier Ltd. All rights reserved.

Carbonatite ring-complexes explained by caldera-style volcanism

PubMed Central

Andersson, Magnus; Malehmir, Alireza; Troll, Valentin R.; Dehghannejad, Mahdieh; Juhlin, Christopher; Ask, Maria

2013-01-01

Carbonatites are rare, carbonate-rich magmatic rocks that make up a minute portion of the crust only, yet they are of great relevance for our understanding of crustal and mantle processes. Although they occur in all continents and from Archaean to present, the deeper plumbing system of carbonatite ring-complexes is usually poorly constrained. Here, we show that carbonatite ring-complexes can be explained by caldera-style volcanism. Our geophysical investigation of the Alnö carbonatite ring-complex in central Sweden identifies a solidified saucer-shaped magma chamber at ~3 km depth that links to surface exposures through a ring fault system. Caldera subsidence during final stages of activity caused carbonatite eruptions north of the main complex, providing the crucial element to connect plutonic and eruptive features of carbonatite magmatism. The way carbonatite magmas are stored, transported and erupt at the surface is thus comparable to known emplacement styles from silicic calderas. PMID:23591904

Carbonatite ring-complexes explained by caldera-style volcanism.

PubMed

Andersson, Magnus; Malehmir, Alireza; Troll, Valentin R; Dehghannejad, Mahdieh; Juhlin, Christopher; Ask, Maria

2013-01-01

Carbonatites are rare, carbonate-rich magmatic rocks that make up a minute portion of the crust only, yet they are of great relevance for our understanding of crustal and mantle processes. Although they occur in all continents and from Archaean to present, the deeper plumbing system of carbonatite ring-complexes is usually poorly constrained. Here, we show that carbonatite ring-complexes can be explained by caldera-style volcanism. Our geophysical investigation of the Alnö carbonatite ring-complex in central Sweden identifies a solidified saucer-shaped magma chamber at ~3 km depth that links to surface exposures through a ring fault system. Caldera subsidence during final stages of activity caused carbonatite eruptions north of the main complex, providing the crucial element to connect plutonic and eruptive features of carbonatite magmatism. The way carbonatite magmas are stored, transported and erupt at the surface is thus comparable to known emplacement styles from silicic calderas.

System crash as dynamics of complex networks.

PubMed

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

2016-10-18

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

Using systems thinking to support clinical system transformation.

PubMed

Best, Allan; Berland, Alex; Herbert, Carol; Bitz, Jennifer; van Dijk, Marlies W; Krause, Christina; Cochrane, Douglas; Noel, Kevin; Marsden, Julian; McKeown, Shari; Millar, John

2016-05-16

Purpose - The British Columbia Ministry of Health's Clinical Care Management initiative was used as a case study to better understand large-scale change (LSC) within BC's health system. Using a complex system framework, the purpose of this paper is to examine mechanisms that enable and constrain the implementation of clinical guidelines across various clinical settings. Design/methodology/approach - Researchers applied a general model of complex adaptive systems plus two specific conceptual frameworks (realist evaluation and system dynamics mapping) to define and study enablers and constraints. Focus group sessions and interviews with clinicians, executives, managers and board members were validated through an online survey. Findings - The functional themes for managing large-scale clinical change included: creating a context to prepare clinicians for health system transformation initiatives; promoting shared clinical leadership; strengthening knowledge management, strategic communications and opportunities for networking; and clearing pathways through the complexity of a multilevel, dynamic system. Research limitations/implications - The action research methodology was designed to guide continuing improvement of implementation. A sample of initiatives was selected; it was not intended to compare and contrast facilitators and barriers across all initiatives and regions. Similarly, evaluating the results or process of guideline implementation was outside the scope; the methods were designed to enable conversations at multiple levels - policy, management and practice - about how to improve implementation. The study is best seen as a case study of LSC, offering a possible model for replication by others and a tool to shape further dialogue. Practical implications - Recommended action-oriented strategies included engaging local champions; supporting local adaptation for implementation of clinical guidelines; strengthening local teams to guide implementation; reducing change fatigue; ensuring adequate resources; providing consistent communication especially for front-line care providers; and supporting local teams to demonstrate the clinical value of the guidelines to their colleagues. Originality/value - Bringing a complex systems perspective to clinical guideline implementation resulted in a clear understanding of the challenges involved in LSC.

A global "imaging'' view on systems approaches in immunology.

PubMed

Ludewig, Burkhard; Stein, Jens V; Sharpe, James; Cervantes-Barragan, Luisa; Thiel, Volker; Bocharov, Gennady

2012-12-01

The immune system exhibits an enormous complexity. High throughput methods such as the "-omic'' technologies generate vast amounts of data that facilitate dissection of immunological processes at ever finer resolution. Using high-resolution data-driven systems analysis, causal relationships between complex molecular processes and particular immunological phenotypes can be constructed. However, processes in tissues, organs, and the organism itself (so-called higher level processes) also control and regulate the molecular (lower level) processes. Reverse systems engineering approaches, which focus on the examination of the structure, dynamics and control of the immune system, can help to understand the construction principles of the immune system. Such integrative mechanistic models can properly describe, explain, and predict the behavior of the immune system in health and disease by combining both higher and lower level processes. Moving from molecular and cellular levels to a multiscale systems understanding requires the development of methodologies that integrate data from different biological levels into multiscale mechanistic models. In particular, 3D imaging techniques and 4D modeling of the spatiotemporal dynamics of immune processes within lymphoid tissues are central for such integrative approaches. Both dynamic and global organ imaging technologies will be instrumental in facilitating comprehensive multiscale systems immunology analyses as discussed in this review. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

From biological and social network metaphors to coupled bio-social wireless networks

PubMed Central

Barrett, Christopher L.; Eubank, Stephen; Anil Kumar, V.S.; Marathe, Madhav V.

2010-01-01

Biological and social analogies have been long applied to complex systems. Inspiration has been drawn from biological solutions to solve problems in engineering products and systems, ranging from Velcro to camouflage to robotics to adaptive and learning computing methods. In this paper, we present an overview of recent advances in understanding biological systems as networks and use this understanding to design and analyse wireless communication networks. We expand on two applications, namely cognitive sensing and control and wireless epidemiology. We discuss how our work in these two applications is motivated by biological metaphors. We believe that recent advances in computing and communications coupled with advances in health and social sciences raise the possibility of studying coupled bio-social communication networks. We argue that we can better utilise the advances in our understanding of one class of networks to better our understanding of the other. PMID:21643462