Address the Major Societal Challenges

NASA Astrophysics Data System (ADS)

Laubichler, Manfred

In his famous historical account about the origins of molecular biology Gunther Stent introduced a three phase sequence that turns out to be characteristic for many newly emerging paradigms within science. New ideas, according to Stent, follow a sequence of romantic, dogmatic, and academic phases. One can easily see that complex systems science followed this path. The question now is whether we are in an extended academic phase of gradually expanding both theoretical and practical knowledge, or whether we are entering a new transformation of complex systems science that might well bring about a new romantic phase. I would argue that complexity science, indeed, is at the dawn of a new period - let's call it complexity 3.0. The last academic phase has seen the application of complex systems ideas and methods in a variety of different domains. It has been to a large extent business as usual...

The Complexity of Primary Care Psychology: Theoretical Foundations.

PubMed

Smit, E H; Derksen, J J L

2015-07-01

How does primary care psychology deal with organized complexity? Has it escaped Newtonian science? Has it, as Weaver (1991) suggests, found a way to 'manage problems with many interrelated factors that cannot be dealt by statistical techniques'? Computer simulations and mathematical models in psychology are ongoing positive developments in the study of complex systems. However, the theoretical development of complex systems in psychology lags behind these advances. In this article we use complexity science to develop a theory on experienced complexity in the daily practice of primary care psychologists. We briefly answer the ontological question of what we see (from the perspective of primary care psychology) as reality, the epistemological question of what we can know, the methodological question of how to act, and the ethical question of what is good care. Following our empirical study, we conclude that complexity science can describe the experienced complexity of the psychologist and offer room for personalized client-centered care. Complexity science is slowly filling the gap between the dominant reductionist theory and complex daily practice.

Systems Science Methods in Public Health

PubMed Central

Luke, Douglas A.; Stamatakis, Katherine A.

2012-01-01

Complex systems abound in public health. Complex systems are made up of heterogeneous elements that interact with one another, have emergent properties that are not explained by understanding the individual elements of the system, persist over time and adapt to changing circumstances. Public health is starting to use results from systems science studies to shape practice and policy, for example in preparing for global pandemics. However, systems science study designs and analytic methods remain underutilized and are not widely featured in public health curricula or training. In this review we present an argument for the utility of systems science methods in public health, introduce three important systems science methods (system dynamics, network analysis, and agent-based modeling), and provide three case studies where these methods have been used to answer important public health science questions in the areas of infectious disease, tobacco control, and obesity. PMID:22224885

When complexity science meets implementation science: a theoretical and empirical analysis of systems change.

PubMed

Braithwaite, Jeffrey; Churruca, Kate; Long, Janet C; Ellis, Louise A; Herkes, Jessica

2018-04-30

Implementation science has a core aim - to get evidence into practice. Early in the evidence-based medicine movement, this task was construed in linear terms, wherein the knowledge pipeline moved from evidence created in the laboratory through to clinical trials and, finally, via new tests, drugs, equipment, or procedures, into clinical practice. We now know that this straight-line thinking was naïve at best, and little more than an idealization, with multiple fractures appearing in the pipeline. The knowledge pipeline derives from a mechanistic and linear approach to science, which, while delivering huge advances in medicine over the last two centuries, is limited in its application to complex social systems such as healthcare. Instead, complexity science, a theoretical approach to understanding interconnections among agents and how they give rise to emergent, dynamic, systems-level behaviors, represents an increasingly useful conceptual framework for change. Herein, we discuss what implementation science can learn from complexity science, and tease out some of the properties of healthcare systems that enable or constrain the goals we have for better, more effective, more evidence-based care. Two Australian examples, one largely top-down, predicated on applying new standards across the country, and the other largely bottom-up, adopting medical emergency teams in over 200 hospitals, provide empirical support for a complexity-informed approach to implementation. The key lessons are that change can be stimulated in many ways, but a triggering mechanism is needed, such as legislation or widespread stakeholder agreement; that feedback loops are crucial to continue change momentum; that extended sweeps of time are involved, typically much longer than believed at the outset; and that taking a systems-informed, complexity approach, having regard for existing networks and socio-technical characteristics, is beneficial. Construing healthcare as a complex adaptive system implies that getting evidence into routine practice through a step-by-step model is not feasible. Complexity science forces us to consider the dynamic properties of systems and the varying characteristics that are deeply enmeshed in social practices, whilst indicating that multiple forces, variables, and influences must be factored into any change process, and that unpredictability and uncertainty are normal properties of multi-part, intricate systems.

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.

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.

Increasing complexity with quantum physics.

PubMed

Anders, Janet; Wiesner, Karoline

2011-09-01

We argue that complex systems science and the rules of quantum physics are intricately related. We discuss a range of quantum phenomena, such as cryptography, computation and quantum phases, and the rules responsible for their complexity. We identify correlations as a central concept connecting quantum information and complex systems science. We present two examples for the power of correlations: using quantum resources to simulate the correlations of a stochastic process and to implement a classically impossible computational task.

The Difference between Uncertainty and Information, and Why This Matters

NASA Astrophysics Data System (ADS)

Nearing, G. S.

2016-12-01

Earth science investigation and arbitration (for decision making) is very often organized around a concept of uncertainty. It seems relatively straightforward that the purpose of our science is to reduce uncertainty about how environmental systems will react and evolve under different conditions. I propose here that approaching a science of complex systems as a process of quantifying and reducing uncertainty is a mistake, and specifically a mistake that is rooted in certain rather hisoric logical errors. Instead I propose that we should be asking questions about information. I argue here that an information-based perspective facilitates almost trivial answers to environmental science questions that are either difficult or theoretically impossible to answer when posed as questions about uncertainty. In particular, I propose that an information-centric perspective leads to: Coherent and non-subjective hypothesis tests for complex system models. Process-level diagnostics for complex systems models. Methods for building complex systems models that allow for inductive inference without the need for a priori specification of likelihood functions or ad hoc error metrics. Asymptotically correct quantification of epistemic uncertainty. To put this in slightly more basic terms, I propose that an information-theoretic philosophy of science has the potential to resolve certain important aspects of the Demarcation Problem and the Duhem-Quine Problem, and that Hydrology and other Earth Systems Sciences can immediately capitalize on this to address some of our most difficult and persistent problems.

Statistical Features of Complex Systems ---Toward Establishing Sociological Physics---

NASA Astrophysics Data System (ADS)

Kobayashi, Naoki; Kuninaka, Hiroto; Wakita, Jun-ichi; Matsushita, Mitsugu

2011-07-01

Complex systems have recently attracted much attention, both in natural sciences and in sociological sciences. Members constituting a complex system evolve through nonlinear interactions among each other. This means that in a complex system the multiplicative experience or, so to speak, the history of each member produces its present characteristics. If attention is paid to any statistical property in any complex system, the lognormal distribution is the most natural and appropriate among the standard or ``normal'' statistics to overview the whole system. In fact, the lognormality emerges rather conspicuously when we examine, as familiar and typical examples of statistical aspects in complex systems, the nursing-care period for the aged, populations of prefectures and municipalities, and our body height and weight. Many other examples are found in nature and society. On the basis of these observations, we discuss the possibility of sociological physics.

Providing data science support for systems pharmacology and its implications to drug discovery.

PubMed

Hart, Thomas; Xie, Lei

2016-01-01

The conventional one-drug-one-target-one-disease drug discovery process has been less successful in tracking multi-genic, multi-faceted complex diseases. Systems pharmacology has emerged as a new discipline to tackle the current challenges in drug discovery. The goal of systems pharmacology is to transform huge, heterogeneous, and dynamic biological and clinical data into interpretable and actionable mechanistic models for decision making in drug discovery and patient treatment. Thus, big data technology and data science will play an essential role in systems pharmacology. This paper critically reviews the impact of three fundamental concepts of data science on systems pharmacology: similarity inference, overfitting avoidance, and disentangling causality from correlation. The authors then discuss recent advances and future directions in applying the three concepts of data science to drug discovery, with a focus on proteome-wide context-specific quantitative drug target deconvolution and personalized adverse drug reaction prediction. Data science will facilitate reducing the complexity of systems pharmacology modeling, detecting hidden correlations between complex data sets, and distinguishing causation from correlation. The power of data science can only be fully realized when integrated with mechanism-based multi-scale modeling that explicitly takes into account the hierarchical organization of biological systems from nucleic acid to proteins, to molecular interaction networks, to cells, to tissues, to patients, and to populations.

Applying Principles from Complex Systems to Studying the Efficacy of CAM Therapies

PubMed Central

Nahin, Richard L.; Calabrese, Carlo; Folkman, Susan; Kimbrough, Elizabeth; Shoham, Jacob; Haramati, Aviad

2010-01-01

Abstract In October 2007, a National Center for Complementary and Alternative Medicine (NCCAM)–sponsored workshop, entitled “Applying Principles from Complex Systems to Studying the Efficacy of CAM Therapies,” was held at Georgetown University in Washington, DC. Over a 2-day period, the workshop engaged a small group of experts from the fields of complementary and alternative medicine (CAM) research and complexity science to discuss and examine ways in which complexity science can be applied to CAM research. After didactic presentations and small-group discussions, a number of salient themes and ideas emerged. This paper article describes the workshop program and summarizes these emergent ideas, which are divided into five broad categories: (1) introduction to complexity; (2) challenges to CAM research; (3) applications of complexity science to CAM; (4) CAM as a model of complexity applied to medicine; and (5) future directions. This discusses possible benefits and challenges associated with applying complexity science to CAM research. By providing an introductory framework for this collaboration and exchange, it is hoped that this article may stimulate further inquiry into this largely unexplored area of research. PMID:20715978

Nutrition and the science of disease prevention: a systems approach to support metabolic health

PubMed Central

Bennett, Brian J.; Hall, Kevin D.; Hu, Frank B.; McCartney, Anne L.; Roberto, Christina

2017-01-01

Progress in nutritional science, genetics, computer science, and behavioral economics can be leveraged to address the challenge of noncommunicable disease. This report highlights the connection between nutrition and the complex science of preventing disease and discusses the promotion of optimal metabolic health, building on input from several complementary disciplines. The discussion focuses on (1) the basic science of optimal metabolic health, including data from gene–diet interactions, microbiome, and epidemiological research in nutrition, with the goal of defining better targets and interventions, and (2) how nutrition, from pharma to lifestyle, can build on systems science to address complex issues. PMID:26415028

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...

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.

SQL is Dead; Long-live SQL: Relational Database Technology in Science Contexts

NASA Astrophysics Data System (ADS)

Howe, B.; Halperin, D.

2014-12-01

Relational databases are often perceived as a poor fit in science contexts: Rigid schemas, poor support for complex analytics, unpredictable performance, significant maintenance and tuning requirements --- these idiosyncrasies often make databases unattractive in science contexts characterized by heterogeneous data sources, complex analysis tasks, rapidly changing requirements, and limited IT budgets. In this talk, I'll argue that although the value proposition of typical relational database systems are weak in science, the core ideas that power relational databases have become incredibly prolific in open source science software, and are emerging as a universal abstraction for both big data and small data. In addition, I'll talk about two open source systems we are building to "jailbreak" the core technology of relational databases and adapt them for use in science. The first is SQLShare, a Database-as-a-Service system supporting collaborative data analysis and exchange by reducing database use to an Upload-Query-Share workflow with no installation, schema design, or configuration required. The second is Myria, a service that supports much larger scale data, complex analytics, and supports multiple back end systems. Finally, I'll describe some of the ways our collaborators in oceanography, astronomy, biology, fisheries science, and more are using these systems to replace script-based workflows for reasons of performance, flexibility, and convenience.

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

Gaming science innovations to integrate health systems science into medical education and practice

PubMed Central

White, Earla J; Lewis, Joy H; McCoy, Lise

2018-01-01

Health systems science (HSS) is an emerging discipline addressing multiple, complex, interdependent variables that affect providers’ abilities to deliver patient care and influence population health. New perspectives and innovations are required as physician leaders and medical educators strive to accelerate changes in medical education and practice to meet the needs of evolving populations and systems. The purpose of this paper is to introduce gaming science as a lens to magnify HSS integration opportunities in the scope of medical education and practice. Evidence supports gaming science innovations as effective teaching and learning tools to promote learner engagement in scientific and systems thinking for decision making in complex scenarios. Valuable insights and lessons gained through the history of war games have resulted in strategic thinking to minimize risk and save lives. In health care, where decisions can affect patient and population outcomes, gaming science innovations have the potential to provide safe learning environments to practice crucial decision-making skills. Research of gaming science limitations, gaps, and strategies to maximize innovations to further advance HSS in medical education and practice is required. Gaming science holds promise to equip health care teams with HSS knowledge and skills required for transformative practice. The ultimate goals are to empower providers to work in complex systems to improve patient and population health outcomes and experiences, and to reduce costs and improve care team well-being.

Gaming science innovations to integrate health systems science into medical education and practice.

PubMed

White, Earla J; Lewis, Joy H; McCoy, Lise

2018-01-01

Health systems science (HSS) is an emerging discipline addressing multiple, complex, interdependent variables that affect providers' abilities to deliver patient care and influence population health. New perspectives and innovations are required as physician leaders and medical educators strive to accelerate changes in medical education and practice to meet the needs of evolving populations and systems. The purpose of this paper is to introduce gaming science as a lens to magnify HSS integration opportunities in the scope of medical education and practice. Evidence supports gaming science innovations as effective teaching and learning tools to promote learner engagement in scientific and systems thinking for decision making in complex scenarios. Valuable insights and lessons gained through the history of war games have resulted in strategic thinking to minimize risk and save lives. In health care, where decisions can affect patient and population outcomes, gaming science innovations have the potential to provide safe learning environments to practice crucial decision-making skills. Research of gaming science limitations, gaps, and strategies to maximize innovations to further advance HSS in medical education and practice is required. Gaming science holds promise to equip health care teams with HSS knowledge and skills required for transformative practice. The ultimate goals are to empower providers to work in complex systems to improve patient and population health outcomes and experiences, and to reduce costs and improve care team well-being.

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…

Elementary Teachers' Selection and Use of Visual Models

ERIC Educational Resources Information Center

Lee, Tammy D.; Jones, M. Gail

2018-01-01

As science grows in complexity, science teachers face an increasing challenge of helping students interpret models that represent complex science systems. Little is known about how teachers select and use models when planning lessons. This mixed methods study investigated the pedagogical approaches and visual models used by elementary in-service…

Space Power Integration: Perspectives from Space Weapons Officers

DTIC Science & Technology

2006-12-01

staff at Air University Press, Dr. Philip Adkins, Mrs. Sherry Terrell , and Mrs. Vivian O’Neal. Their creation of an integrated book from nine...Techniques of Complex Systems Science: An Overview ( Ann Arbor, MI: Center for the Study of Complex Sys- tems, University of Michigan, 9 July 2003), 34...Depart- ment of the Navy Space Policy, 26 August 1993. Shalizi, Cosma Rohilla. Methods and Techniques of Complex Systems Science: An Overview. Ann

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

DTIC Science & Technology

1977-11-16

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

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.

How do precision medicine and system biology response to human body's complex adaptability?

PubMed

Yuan, Bing

2016-12-01

In the field of life sciences, although system biology and "precision medicine" introduce some complex scientifific methods and techniques, it is still based on the "analysis-reconstruction" of reductionist theory as a whole. Adaptability of complex system increase system behaviour uncertainty as well as the difficulties of precise identifification and control. It also put systems biology research into trouble. To grasp the behaviour and characteristics of organism fundamentally, systems biology has to abandon the "analysis-reconstruction" concept. In accordance with the guidelines of complexity science, systems biology should build organism model from holistic level, just like the Chinese medicine did in dealing with human body and disease. When we study the living body from the holistic level, we will fifind the adaptability of complex system is not the obstacle that increases the diffificulty of problem solving. It is the "exceptional", "right-hand man" that helping us to deal with the complexity of life more effectively.

Management Strategies for Complex Adaptive Systems: Sensemaking, Learning, and Improvisation

ERIC Educational Resources Information Center

McDaniel, Reuben R., Jr.

2007-01-01

Misspecification of the nature of organizations may be a major reason for difficulty in achieving performance improvement. Organizations are often viewed as machine-like, but complexity science suggests that organizations should be viewed as complex adaptive systems. I identify the characteristics of complex adaptive systems and give examples of…

Solve the Dilemma of Over-Simplification

NASA Astrophysics Data System (ADS)

Schmitt, Gerhard

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

Integrated Science: Providing a More Complete Understanding of Complex Problems

USGS Publications Warehouse

,

2006-01-01

Integration among sciences is critical in order to address some of our most pressing problems. Because of the inherent complexity of natural systems, and the increasing complexity of human demands on them, narrowly-focused approaches are no longer sufficient. USGS Workshop on Enhancing Integrated Science, November 1998. The Mid-Continent Geographic Science Center is actively participating in several integrated science studies that include research partners from the other disciplines of the U.S. Geological Survey (USGS), other Federal and State agencies, universities, and private non-government organizations. The following three examples illustrate the diversity of these studies.

An Evolutionary Approach to Harnessing Complex Systems Thinking in the Science and Technology Classroom

ERIC Educational Resources Information Center

Yoon, Susan A.

2008-01-01

Educational efforts to incorporate ethical decision-making in science classrooms about current science and technology issues have met with great challenges. Some research suggests that the inherent complexity in both the subject matter content and the structure and dynamics of classrooms contribute to this challenge. This study seeks to…

An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

NASA Astrophysics Data System (ADS)

Haghnevis, Moeed

The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

Network science of biological systems at different scales: A review

NASA Astrophysics Data System (ADS)

Gosak, Marko; Markovič, Rene; Dolenšek, Jurij; Slak Rupnik, Marjan; Marhl, Marko; Stožer, Andraž; Perc, Matjaž

2018-03-01

Network science is today established as a backbone for description of structure and function of various physical, chemical, biological, technological, and social systems. Here we review recent advances in the study of complex biological systems that were inspired and enabled by methods of network science. First, we present

Annual Research Briefs - 2006

DTIC Science & Technology

2006-12-01

IACCARINO AND Q. WANG 3 Strain and stress analysis of uncertain engineering systems . D. GHOSH, C. FARHAT AND P. AVERY 17 Separated flow in a three...research in predictive science in complex systems , CTR has strived to maintain a critical mass in numerical analysis , computer science and physics based... analysis for a linear problem: heat conduction The design and analysis of complex engineering systems is challenging not only be- cause of the physical

JPRS Report, Science & Technology USSR: Science & Technology Policy.

DTIC Science & Technology

1988-04-06

YESTESTVOZNANIYA I TEKHNIKI, No 3, Mar 87] 15 Work of Nadezhnost mashin Interbranch Complex [K. Frolov et al; NTR: PROBLEMYIRESHEN1YA, No 21, 3-16 Nov 86...Equipment By Rotor Complex [L. Koshkin; PLANOVOYE KHOZYAYSTVO, No 3, Mar 87] 29 Training, Use of Engineers Severely Criticized [V.G. Aynshteyn; ZNANIYE... complex systems, were painful lessons. In other words, the social role and, let us stress, the social responsibility of science today have increased

On Chaotic and Hyperchaotic Complex Nonlinear Dynamical Systems

NASA Astrophysics Data System (ADS)

Mahmoud, Gamal M.

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

The Bogus Science.

ERIC Educational Resources Information Center

Anderson, C. C.

1981-01-01

Discusses three sorts of psychological science: Science 1, a natural science with conditional (causal) laws; Science 2, with probabilistic laws; and Science 3, a "human science" trying to capture the complexity of human experience and behavior. Argues that Science 2 and Science 3 should be treated as belief systems which people may find useful for…

Can complexity science inform physician leadership development?

PubMed

Grady, Colleen Marie

2016-07-04

Purpose The purpose of this paper is to describe research that examined physician leadership development using complexity science principles. Design/methodology/approach Intensive interviewing of 21 participants and document review provided data regarding physician leadership development in health-care organizations using five principles of complexity science (connectivity, interdependence, feedback, exploration-of-the-space-of-possibilities and co-evolution), which were grouped in three areas of inquiry (relationships between agents, patterns of behaviour and enabling functions). Findings Physician leaders are viewed as critical in the transformation of healthcare and in improving patient outcomes, and yet significant challenges exist that limit their development. Leadership in health care continues to be associated with traditional, linear models, which are incongruent with the behaviour of a complex system, such as health care. Physician leadership development remains a low priority for most health-care organizations, although physicians admit to being limited in their capacity to lead. This research was based on five principles of complexity science and used grounded theory methodology to understand how the behaviours of a complex system can provide data regarding leadership development for physicians. The study demonstrated that there is a strong association between physician leadership and patient outcomes and that organizations play a primary role in supporting the development of physician leaders. Findings indicate that a physician's relationship with their patient and their capacity for innovation can be extended as catalytic behaviours in a complex system. The findings also identified limiting factors that impact physicians who choose to lead, such as reimbursement models that do not place value on leadership and medical education that provides minimal opportunity for leadership skill development. Practical Implications This research provides practical applications for physician leadership development and emphasizes that it is incumbent upon physicians and organizations to focus attention on this to achieve improved patient and organizational outcomes. Originality/value This study pairing complexity science and physician leadership represents a unique way to view the development of physician leaders within the context of the complex system that is health care.

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

Complexity in Nature and Society: Complexity Management in the Age of Globalization

NASA Astrophysics Data System (ADS)

Mainzer, Klaus

The theory of nonlinear complex systems has become a proven problem-solving approach in the natural sciences from cosmic and quantum systems to cellular organisms and the brain. Even in modern engineering science self-organizing systems are developed to manage complex networks and processes. It is now recognized that many of our ecological, social, economic, and political problems are also of a global, complex, and nonlinear nature. What are the laws of sociodynamics? Is there a socio-engineering of nonlinear problem solving? What can we learn from nonlinear dynamics for complexity management in social, economic, financial and political systems? Is self-organization an acceptable strategy to handle the challenges of complexity in firms, institutions and other organizations? It is a main thesis of the talk that nature and society are basically governed by nonlinear and complex information dynamics. How computational is sociodynamics? What can we hope for social, economic and political problem solving in the age of globalization?.

Preparing new nurses with complexity science and problem-based learning.

PubMed

Hodges, Helen F

2011-01-01

Successful nurses function effectively with adaptability, improvability, and interconnectedness, and can see emerging and unpredictable complex problems. Preparing new nurses for complexity requires a significant change in prevalent but dated nursing education models for rising graduates. The science of complexity coupled with problem-based learning and peer review contributes a feasible framework for a constructivist learning environment to examine real-time systems data; explore uncertainty, inherent patterns, and ambiguity; and develop skills for unstructured problem solving. This article describes a pilot study of a problem-based learning strategy guided by principles of complexity science in a community clinical nursing course. Thirty-five senior nursing students participated during a 3-year period. Assessments included peer review, a final project paper, reflection, and a satisfaction survey. Results were higher than expected levels of student satisfaction, increased breadth and analysis of complex data, acknowledgment of community as complex adaptive systems, and overall higher level thinking skills than in previous years. 2011, SLACK Incorporated.

Social determinants of health inequalities: towards a theoretical perspective using systems science.

PubMed

Jayasinghe, Saroj

2015-08-25

A systems approach offers a novel conceptualization to natural and social systems. In recent years, this has led to perceiving population health outcomes as an emergent property of a dynamic and open, complex adaptive system. The current paper explores these themes further and applies the principles of systems approach and complexity science (i.e. systems science) to conceptualize social determinants of health inequalities. The conceptualization can be done in two steps: viewing health inequalities from a systems approach and extending it to include complexity science. Systems approach views health inequalities as patterns within the larger rubric of other facets of the human condition, such as educational outcomes and economic development. This anlysis requires more sophisticated models such as systems dynamic models. An extension of the approach is to view systems as complex adaptive systems, i.e. systems that are 'open' and adapt to the environment. They consist of dynamic adapting subsystems that exhibit non-linear interactions, while being 'open' to a similarly dynamic environment of interconnected systems. They exhibit emergent properties that cannot be estimated with precision by using the known interactions among its components (such as economic development, political freedom, health system, culture etc.). Different combinations of the same bundle of factors or determinants give rise to similar patterns or outcomes (i.e. property of convergence), and minor variations in the initial condition could give rise to widely divergent outcomes. Novel approaches using computer simulation models (e.g. agent-based models) would shed light on possible mechanisms as to how factors or determinants interact and lead to emergent patterns of health inequalities of populations.

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

On the Creative Logic of Education, or: Re-Reading Dewey through the Lens of Complexity Science

ERIC Educational Resources Information Center

Semetsky, Inna

2008-01-01

This paper rereads John Dewey's works in the light of complexity theory and self-organising systems. Dewey's pragmatic inquiry is posited as inspirational for developing a logic of education and learning that would incorporate novelty and creativity, these artistic elements being part and parcel of the science of complexity. Dewey's philosophical…

A Framework for Understanding the Characteristics of Complexity in Biology

ERIC Educational Resources Information Center

Dauer, Joseph; Dauer, Jenny

2016-01-01

Understanding the functioning of natural systems is not easy, although there is general agreement that understanding complex systems is an important goal for science education. Defining what makes a natural system complex will assist in identifying gaps in research on student reasoning about systems. The goal of this commentary is to propose a…

Complex systems: physics beyond physics

NASA Astrophysics Data System (ADS)

Holovatch, Yurij; Kenna, Ralph; Thurner, Stefan

2017-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

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.

The sleeping brain as a complex system.

PubMed

Olbrich, Eckehard; Achermann, Peter; Wennekers, Thomas

2011-10-13

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

Practical Measurement of Complexity In Dynamic Systems

DTIC Science & Technology

2012-01-01

policies that produce highly complex behaviors , yet yield no benefit. 21Jason B. Clark and David R. Jacques / Procedia Computer Science 8 (2012) 14... Procedia Computer Science 8 (2012) 14 – 21 1877-0509 © 2012 Published by Elsevier B.V. doi:10.1016/j.procs.2012.01.008 Available online at...www.sciencedirect.com Procedia Computer Science Procedia Computer Science 00 (2012) 000–000 www.elsevier.com/locate/ procedia Available online at

Designing Better Scaffolding in Teaching Complex Systems with Graphical Simulations

ERIC Educational Resources Information Center

Li, Na

2013-01-01

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…

Science with society in the anthropocene.

PubMed

Seidl, Roman; Brand, Fridolin Simon; Stauffacher, Michael; Krütli, Pius; Le, Quang Bao; Spörri, Andy; Meylan, Grégoire; Moser, Corinne; González, Monica Berger; Scholz, Roland Werner

2013-02-01

Interdisciplinary scientific knowledge is necessary but not sufficient when it comes to addressing sustainable transformations, as science increasingly has to deal with normative and value-related issues. A systems perspective on coupled human-environmental systems (HES) helps to address the inherent complexities. Additionally, a thorough interaction between science and society (i.e., transdisciplinarity = TD) is necessary, as sustainable transitions are sometimes contested and can cause conflicts. In order to navigate complexities regarding the delicate interaction of scientific research with societal decisions these processes must proceed in a structured and functional way. We thus propose HES-based TD processes to provide a basis for reorganizing science in coming decades.

Gender, Complexity, and Science for All: Systemizing and Its Impact on Motivation to Learn Science for Different Science Subjects

ERIC Educational Resources Information Center

Zeyer, Albert

2018-01-01

The present study is based on a large cross-cultural study, which showed that a systemizing cognition type has a high impact on motivation to learn science, while the impact of gender is only indirect thorough systemizing. The present study uses the same structural equation model as in the cross-cultural study and separately tests it for physics,…

Earth Systems Science: An Analytic Framework

ERIC Educational Resources Information Center

Finley, Fred N.; Nam, Younkeyong; Oughton, John

2011-01-01

Earth Systems Science (ESS) is emerging rapidly as a discipline and is being used to replace the older earth science education that has been taught as unrelated disciplines--geology, meteorology, astronomy, and oceanography. ESS is complex and is based on the idea that the earth can be understood as a set of interacting natural and social systems.…

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

PubMed

West, Bruce J; Clancy, Thomas R

2010-11-01

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

Complex Systems Simulation and Optimization | Computational Science | NREL

Science.gov Websites

account. Stochastic Optimization and Control: Formulation and implementation of advanced optimization and account uncertainty. Contact Wesley Jones Group Manager, Complex Systems Simulation and Optimiziation

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...

National Nanotechnology Initiative: Driving Innovation & Competitiveness

DTIC Science & Technology

2007-09-19

networking & IT National Nanotechnology Initiative Complex biological systems Environment Next Generation Air Transportation Systems Federal scientific ... collections Science of Science Policy Slide 9: A little history about the National Nanotechnology Initiative: The interagency program was

The 1992 annual report on scientific programs: A broad research program on the sciences of complexity

NASA Astrophysics Data System (ADS)

In 1992 the Santa Fe Institute hosted more than 100 short- and long-term research visitors who conducted a total of 212 person-months of residential research in complex systems. To date this 1992 work has resulted in more than 50 SFI Working Papers and nearly 150 publications in the scientific literature. The Institute's book series in the sciences of complexity continues to grow, now numbering more than 20 volumes. The fifth annual complex systems summer school brought nearly 60 graduate students and postdoctoral fellows to Santa Fe for an intensive introduction to the field. 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 adaptive behavior range upwards from DNA through cells and evolutionary systems to human societies. Research models exhibiting complex behavior include spin glasses, cellular automata, and genetic algorithms. Some of the major questions facing complex systems researchers are: (1) explaining how complexity arises from the nonlinear interaction of simple 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, and the Gross National Product (GNP) of an economy); and (3) creating a theoretical framework to enable predictions about the likely behavior of such systems in various conditions.

1992 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

1992-12-31

In 1992 the Santa Fe Institute hosted more than 100 short- and long-term research visitors who conducted a total of 212 person-months of residential research in complex systems. To date this 1992 work has resulted in more than 50 SFI Working Papers and nearly 150 publications in the scientific literature. The Institute`s book series in the sciences of complexity continues to grow, now numbering more than 20 volumes. The fifth annual complex systems summer school brought nearly 60 graduate students and postdoctoral fellows to Santa Fe for an intensive introduction to the field. Research on complex systems-the focus of workmore » at SFI-involves an extraordinary range of topics normally studied in seemingly disparate fields. Natural systems displaying complex adaptive behavior range upwards from DNA through cells and evolutionary systems to human societies. Research models exhibiting complex behavior include spin glasses, cellular automata, and genetic algorithms. Some of the major questions facing complex systems researchers are: (1) explaining how complexity arises from the nonlinear interaction of simple 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.« less

Science information systems: Visualization

NASA Technical Reports Server (NTRS)

Wall, Ray J.

1991-01-01

Future programs in earth science, planetary science, and astrophysics will involve complex instruments that produce data at unprecedented rates and volumes. Current methods for data display, exploration, and discovery are inadequate. Visualization technology offers a means for the user to comprehend, explore, and examine complex data sets. The goal of this program is to increase the effectiveness and efficiency of scientists in extracting scientific information from large volumes of instrument data.

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…

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…

Joined up Thinking? Evaluating the Use of Concept-Mapping to Develop Complex System Learning

ERIC Educational Resources Information Center

Stewart, Martyn

2012-01-01

In the physical and natural sciences, the complexity of natural systems and their interactions is becoming better understood. With increased emphasis on learning about complex systems, students will be encountering concepts that are dynamic, ill-structured and interconnected. Concept-mapping is a method considered particularly valuable for…

Systems science and obesity policy: a novel framework for analyzing and rethinking population-level planning.

PubMed

Johnston, Lee M; Matteson, Carrie L; Finegood, Diane T

2014-07-01

We demonstrate the use of a systems-based framework to assess solutions to complex health problems such as obesity. We coded 12 documents published between 2004 and 2013 aimed at influencing obesity planning for complex systems design (9 reports from US and Canadian governmental or health authorities, 1 Cochrane review, and 2 Institute of Medicine reports). We sorted data using the intervention-level framework (ILF), a novel solutions-oriented approach to complex problems. An in-depth comparison of 3 documents provides further insight into complexity and systems design in obesity policy. The majority of strategies focused mainly on changing the determinants of energy imbalance (food intake and physical activity). ILF analysis brings to the surface actions aimed at higher levels of system function and points to a need for more innovative policy design. Although many policymakers acknowledge obesity as a complex problem, many strategies stem from the paradigm of individual choice and are limited in scope. The ILF provides a template to encourage natural systems thinking and more strategic policy design grounded in complexity science.

Evaluating the Science of Discovery in Complex Health Systems

ERIC Educational Resources Information Center

Norman, Cameron D.; Best, Allan; Mortimer, Sharon; Huerta, Timothy; Buchan, Alison

2011-01-01

Complex health problems such as chronic disease or pandemics require knowledge that transcends disciplinary boundaries to generate solutions. Such transdisciplinary discovery requires researchers to work and collaborate across boundaries, combining elements of basic and applied science. At the same time, calls for more interdisciplinary health…

Scientists are from Mars, educators are from Venus: Relationships in the ecosystem of science teacher preparation

NASA Astrophysics Data System (ADS)

Duggan-Haas, Don Andrew

2000-10-01

Great problems exist in science teaching from kindergarten through the college level (NRC, 1996; NSF, 1996). The problem may be attributed to the failure of teachers to integrate their own understanding of science content with appropriate pedagogy (Shulman, 1986, 1987). All teachers were trained by college faculty and therefore some of the blame for these problems rests on those faculty. This dissertation presents three models for describing secondary science teacher preparation. Two Programs, Two Cultures adapts C. P. Snow's classic work (1959) to describe the work of a science teacher candidate as that of an individual who navigates between two discrete programs: one in college science and the second in teacher education. The second model, Scientists Are from Mars, Educators Are from Venus adapts the popular work of John Gray to describe the system of science teacher education as hobbled by the dysfunctional relationships among the major players and describes the teacher as progeny from this relationship. The third model, The Ecosystem of Science Teacher Preparation reveals some of the deeper complexities of science teacher education and posits that the traditional college science approach treats students as a monoculture when great diversity in fact exists. The three models are described in the context of a large Midwestern university's teacher education program as that program is construed for future biology teachers. Four undergraduate courses typically taken by future biology teachers were observed and described: an introductory biology course; an introductory teacher education course; an upper division course in biochemistry and a senior level science teaching methods course. Seven second semester seniors who were biological Science majors were interviewed. All seven students had taken all of the courses observed. An organization of scientists and educators working together to improve science teaching from kindergarten through graduate school is also described in a case study. The three models described in the dissertation build upon one another and the third model, that of the ecosystem is recognized as both the most accurate portrayal and most complex and therefore most difficult to apply. The system of science teacher preparation is in many ways a system under stress and that stress will result in system evolution. Through better understanding Complex Adaptive Systems and applying that understanding to the system of science teacher education, individuals may be able to influence the nature of system evolution.

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.

Using Authentic Data in High School Earth System Science Research - Inspiring Future Scientists

NASA Astrophysics Data System (ADS)

Bruck, L. F.

2006-05-01

Using authentic data in a science research class is an effective way to teach students the scientific process, problem solving, and communication skills. In Frederick County Public Schools, MD a course has been developed to hone scientific research skills, and inspire interest in careers in science and technology. The Earth System Science Research course provides eleventh and twelfth grade students an opportunity to study Earth System Science using the latest information developed through current technologies. The system approach to this course helps students understand the complexity and interrelatedness of the Earth system. Consequently students appreciate the dynamics of local and global environments as part of a complex system. This course is an elective offering designed to engage students in the study of the atmosphere, biosphere, cryosphere, geosphere, and hydrosphere. This course allows students to utilize skills and processes gained from previous science courses to study the physical, chemical, and biological aspects of the Earth system. The research component of the course makes up fifty percent of course time in which students perform independent research on the interactions within the Earth system. Students are required to produce a scientific presentation to communicate the results of their research. Posters are then presented to the scientific community. Some of these presentations have led to internships and other scientific opportunities.

Complex Systems Models and Their Applications: Towards a New Science of Verification, Validation & Uncertainty Quantification

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

Tsao, Jeffrey Y.; Trucano, Timothy G.; Kleban, Stephen D.

This report contains the written footprint of a Sandia-hosted workshop held in Albuquerque, New Mexico, June 22-23, 2016 on “Complex Systems Models and Their Applications: Towards a New Science of Verification, Validation and Uncertainty Quantification,” as well as of pre-work that fed into the workshop. The workshop’s intent was to explore and begin articulating research opportunities at the intersection between two important Sandia communities: the complex systems (CS) modeling community, and the verification, validation and uncertainty quantification (VVUQ) community The overarching research opportunity (and challenge) that we ultimately hope to address is: how can we quantify the credibility of knowledgemore » gained from complex systems models, knowledge that is often incomplete and interim, but will nonetheless be used, sometimes in real-time, by decision makers?« less

Architectures Toward Reusable Science Data Systems

NASA Technical Reports Server (NTRS)

Moses, John Firor

2014-01-01

Science Data Systems (SDS) comprise an important class of data processing systems that support product generation from remote sensors and in-situ observations. These systems enable research into new science data products, replication of experiments and verification of results. NASA has been building systems for satellite data processing since the first Earth observing satellites launched and is continuing development of systems to support NASA science research and NOAA's Earth observing satellite operations. The basic data processing workflows and scenarios continue to be valid for remote sensor observations research as well as for the complex multi-instrument operational satellite data systems being built today.

From Dr. Steven Ashby, Director of PNNL

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

Ashby, Steven

Powered by the creativity and imagination of more than 4,000 exceptional scientists, engineers and support professionals, at PNNL we advance the frontiers of science and address some of the most challenging problems in energy, the environment and national security. As DOE’s premier chemistry, environmental sciences and data analytics laboratory, we provide national leadership in four areas: deepening our understanding of climate science; inventing the future power grid; preventing nuclear proliferation; and speeding environmental remediation. Other areas where we make important contributions include energy storage, microbial biology and cyber security. PNNL also is home to EMSL (the Environmental Molecular Sciences Laboratory),more » one of DOE’s scientific user facilities. We apply these science strengths to address both national and international problems in complex adaptive systems that are too difficult for one institution to tackle alone. Take earth systems, for instance. The earth is a complex adaptive system because it involves everything from climate and microbial communities in the soil to emissions from cars and coal-powered industrial plants. All of these factors and others ultimately influence not only our environment and overall quality of life, but cause the earth to adapt in ways that must be further addressed. PNNL researchers are playing a vital role in finding solutions across every area of this complex adaptive system.« less

Is Self-organization a Rational Expectation?

NASA Astrophysics Data System (ADS)

Luediger, Heinz

Over decades and under varying names the study of biology-inspired algorithms applied to non-living systems has been the subject of a small and somewhat exotic research community. Only the recent coincidence of a growing inability to master the design, development and operation of increasingly intertwined systems and processes, and an accelerated trend towards a naïve if not romanticizing view of nature in the sciences, has led to the adoption of biology-inspired algorithmic research by a wider range of sciences. Adaptive systems, as we apparently observe in nature, are meanwhile viewed as a promising way out of the complexity trap and, propelled by a long list of ‘self’ catchwords, complexity research has become an influential stream in the science community. This paper presents four provocative theses that cast doubt on the strategic potential of complexity research and the viability of large scale deployment of biology-inspired algorithms in an expectation driven world.

A complex systems science perspective for whole systems of complementary and alternative medicine research.

PubMed

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

2012-01-01

Whole systems complementary and alternative medicine (WS-CAM) approaches share a basic worldview that embraces interconnectedness; emergent, non-linear outcomes to treatment that include both local and global changes in the human condition; a contextual view of human beings that are inseparable from and responsive to their environments; and interventions that are complex, synergistic, and interdependent. These fundamental beliefs and principles run counter to the assumptions of reductionism and conventional biomedical research methods that presuppose unidimensional simple causes and thus dismantle and individually test various interventions that comprise only single aspects of the WSCAM system. This paper will demonstrate the superior fit and practical advantages of using complex adaptive systems (CAS) and related modeling approaches to develop the scientific basis for WS-CAM. Furthermore, the details of these CAS models will be used to provide working hypotheses to explain clinical phenomena such as (a) persistence of changes for weeks to months between treatments and/or after cessation of treatment, (b) nonlocal and whole systems changes resulting from therapy, (c) Hering's law, and (d) healing crises. Finally, complex systems science will be used to offer an alternative perspective on cause, beyond the simple reductionism of mainstream mechanistic ontology and more parsimonious than the historical vitalism of WS-CAM. Rather, complex systems science provides a scientifically rigorous, yet essentially holistic ontological perspective with which to conceptualize and empirically explore the development of disease and illness experiences, as well as experiences of healing and wellness. Copyright © 2012 S. Karger AG, Basel.

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.

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

ERIC Educational Resources Information Center

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

2007-01-01

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

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...

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

ERIC Educational Resources Information Center

Gregg, Kevin R.

2010-01-01

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

Elementary Teachers' Selection and Use of Visual Models

NASA Astrophysics Data System (ADS)

Lee, Tammy D.; Gail Jones, M.

2018-02-01

As science grows in complexity, science teachers face an increasing challenge of helping students interpret models that represent complex science systems. Little is known about how teachers select and use models when planning lessons. This mixed methods study investigated the pedagogical approaches and visual models used by elementary in-service and preservice teachers in the development of a science lesson about a complex system (e.g., water cycle). Sixty-seven elementary in-service and 69 elementary preservice teachers completed a card sort task designed to document the types of visual models (e.g., images) that teachers choose when planning science instruction. Quantitative and qualitative analyses were conducted to analyze the card sort task. Semistructured interviews were conducted with a subsample of teachers to elicit the rationale for image selection. Results from this study showed that both experienced in-service teachers and novice preservice teachers tended to select similar models and use similar rationales for images to be used in lessons. Teachers tended to select models that were aesthetically pleasing and simple in design and illustrated specific elements of the water cycle. The results also showed that teachers were not likely to select images that represented the less obvious dimensions of the water cycle. Furthermore, teachers selected visual models more as a pedagogical tool to illustrate specific elements of the water cycle and less often as a tool to promote student learning related to complex systems.

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

Reconciling statistical and systems science approaches to public health.

PubMed

Ip, Edward H; Rahmandad, Hazhir; Shoham, David A; Hammond, Ross; Huang, Terry T-K; Wang, Youfa; Mabry, Patricia L

2013-10-01

Although systems science has emerged as a set of innovative approaches to study complex phenomena, many topically focused researchers including clinicians and scientists working in public health are somewhat befuddled by this methodology that at times appears to be radically different from analytic methods, such as statistical modeling, to which the researchers are accustomed. There also appears to be conflicts between complex systems approaches and traditional statistical methodologies, both in terms of their underlying strategies and the languages they use. We argue that the conflicts are resolvable, and the sooner the better for the field. In this article, we show how statistical and systems science approaches can be reconciled, and how together they can advance solutions to complex problems. We do this by comparing the methods within a theoretical framework based on the work of population biologist Richard Levins. We present different types of models as representing different tradeoffs among the four desiderata of generality, realism, fit, and precision.

Reconciling Statistical and Systems Science Approaches to Public Health

PubMed Central

Ip, Edward H.; Rahmandad, Hazhir; Shoham, David A.; Hammond, Ross; Huang, Terry T.-K.; Wang, Youfa; Mabry, Patricia L.

2016-01-01

Although systems science has emerged as a set of innovative approaches to study complex phenomena, many topically focused researchers including clinicians and scientists working in public health are somewhat befuddled by this methodology that at times appears to be radically different from analytic methods, such as statistical modeling, to which the researchers are accustomed. There also appears to be conflicts between complex systems approaches and traditional statistical methodologies, both in terms of their underlying strategies and the languages they use. We argue that the conflicts are resolvable, and the sooner the better for the field. In this article, we show how statistical and systems science approaches can be reconciled, and how together they can advance solutions to complex problems. We do this by comparing the methods within a theoretical framework based on the work of population biologist Richard Levins. We present different types of models as representing different tradeoffs among the four desiderata of generality, realism, fit, and precision. PMID:24084395

General System Theory: Toward a Conceptual Framework for Science and Technology Education for All.

ERIC Educational Resources Information Center

Chen, David; Stroup, Walter

1993-01-01

Suggests using general system theory as a unifying theoretical framework for science and technology education for all. Five reasons are articulated: the multidisciplinary nature of systems theory, the ability to engage complexity, the capacity to describe system dynamics, the ability to represent the relationship between microlevel and…

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

Scaled CMOS Reliability and Considerations for Spacecraft Systems : Bottom-Up and Top-Down Perspectives

NASA Technical Reports Server (NTRS)

White, Mark

2012-01-01

The recently launched Mars Science Laboratory (MSL) flagship mission, named Curiosity, is the most complex rover ever built by NASA and is scheduled to touch down on the red planet in August, 2012 in Gale Crater. The rover and its instruments will have to endure the harsh environments of the surface of Mars to fulfill its main science objectives. Such complex systems require reliable microelectronic components coupled with adequate component and system-level design margins. Reliability aspects of these elements of the spacecraft system are presented from bottom- up and top-down perspectives.

Establishing and Sustaining Networked Improvement Communities: Lessons from Michigan and Minnesota. REL 2017-264

ERIC Educational Resources Information Center

Proger, Amy R.; Bhatt, Monica P.; Cirks, Victoria; Gurke, Deb

2017-01-01

There is growing interest in the ability of improvement science--the systematic study of improvement strategies to identify promising practices for addressing issues in complex systems (Improvement Science Research Network, 2016)--to spur innovation and address complex problems. In education this methodology is often implemented through…

Effective control of complex turbulent dynamical systems through statistical functionals.

PubMed

Majda, Andrew J; Qi, Di

2017-05-30

Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among complex systems in science and engineering, including climate, material, and neural science. Control of these complex systems is a grand challenge, for example, in mitigating the effects of climate change or safe design of technology with fully developed shear turbulence. Control of flows in the transition to turbulence, where there is a small dimension of instabilities about a basic mean state, is an important and successful discipline. In complex turbulent dynamical systems, it is impossible to track and control the large dimension of instabilities, which strongly interact and exchange energy, and new control strategies are needed. The goal of this paper is to propose an effective statistical control strategy for complex turbulent dynamical systems based on a recent statistical energy principle and statistical linear response theory. We illustrate the potential practical efficiency and verify this effective statistical control strategy on the 40D Lorenz 1996 model in forcing regimes with various types of fully turbulent dynamics with nearly one-half of the phase space unstable.

JPRS Report, Science & Technology, USSR: Computers, Control Systems and Machines

DTIC Science & Technology

1989-03-14

optimizatsii slozhnykh sistem (Coding Theory and Complex System Optimization ). Alma-Ata, Nauka Press, 1977, pp. 8-16. 11. Author’s certificate number...Interpreter Specifics [0. I. Amvrosova] ............................................. 141 Creation of Modern Computer Systems for Complex Ecological...processor can be designed to decrease degradation upon failure and assure more reliable processor operation, without requiring more complex software or

Automated Derivation of Complex System Constraints from User Requirements

NASA Technical Reports Server (NTRS)

Muery, Kim; Foshee, Mark; Marsh, Angela

2006-01-01

International Space Station (ISS) payload developers submit their payload science requirements for the development of on-board execution timelines. The ISS systems required to execute the payload science operations must be represented as constraints for the execution timeline. Payload developers use a software application, User Requirements Collection (URC), to submit their requirements by selecting a simplified representation of ISS system constraints. To fully represent the complex ISS systems, the constraints require a level of detail that is beyond the insight of the payload developer. To provide the complex representation of the ISS system constraints, HOSC operations personnel, specifically the Payload Activity Requirements Coordinators (PARC), manually translate the payload developers simplified constraints into detailed ISS system constraints used for scheduling the payload activities in the Consolidated Planning System (CPS). This paper describes the implementation for a software application, User Requirements Integration (URI), developed to automate the manual ISS constraint translation process.

The natural science underlying big history.

PubMed

Chaisson, Eric J

2014-01-01

Nature's many varied complex systems-including galaxies, stars, planets, life, and society-are islands of order within the increasingly disordered Universe. All organized systems are subject to physical, biological, or cultural evolution, which together comprise the grander interdisciplinary subject of cosmic evolution. A wealth of observational data supports the hypothesis that increasingly complex systems evolve unceasingly, uncaringly, and unpredictably from big bang to humankind. These are global history greatly extended, big history with a scientific basis, and natural history broadly portrayed across ∼14 billion years of time. Human beings and our cultural inventions are not special, unique, or apart from Nature; rather, we are an integral part of a universal evolutionary process connecting all such complex systems throughout space and time. Such evolution writ large has significant potential to unify the natural sciences into a holistic understanding of who we are and whence we came. No new science (beyond frontier, nonequilibrium thermodynamics) is needed to describe cosmic evolution's major milestones at a deep and empirical level. Quantitative models and experimental tests imply that a remarkable simplicity underlies the emergence and growth of complexity for a wide spectrum of known and diverse systems. Energy is a principal facilitator of the rising complexity of ordered systems within the expanding Universe; energy flows are as central to life and society as they are to stars and galaxies. In particular, energy rate density-contrasting with information content or entropy production-is an objective metric suitable to gauge relative degrees of complexity among a hierarchy of widely assorted systems observed throughout the material Universe. Operationally, those systems capable of utilizing optimum amounts of energy tend to survive, and those that cannot are nonrandomly eliminated.

Challenges in network science: Applications to infrastructures, climate, social systems and economics

NASA Astrophysics Data System (ADS)

Havlin, S.; Kenett, D. Y.; Ben-Jacob, E.; Bunde, A.; Cohen, R.; Hermann, H.; Kantelhardt, J. W.; Kertész, J.; Kirkpatrick, S.; Kurths, J.; Portugali, J.; Solomon, S.

2012-11-01

Network theory has become one of the most visible theoretical frameworks that can be applied to the description, analysis, understanding, design and repair of multi-level complex systems. Complex networks occur everywhere, in man-made and human social systems, in organic and inorganic matter, from nano to macro scales, and in natural and anthropogenic structures. New applications are developed at an ever-increasing rate and the promise for future growth is high, since increasingly we interact with one another within these vital and complex environments. Despite all the great successes of this field, crucial aspects of multi-level complex systems have been largely ignored. Important challenges of network science are to take into account many of these missing realistic features such as strong coupling between networks (networks are not isolated), the dynamics of networks (networks are not static), interrelationships between structure, dynamics and function of networks, interdependencies in given networks (and other classes of links, including different signs of interactions), and spatial properties (including geographical aspects) of networks. This aim of this paper is to introduce and discuss the challenges that future network science needs to address, and how different disciplines will be accordingly affected.

The FuturICT education accelerator

NASA Astrophysics Data System (ADS)

Johnson, J.; Buckingham Shum, S.; Willis, A.; Bishop, S.; Zamenopoulos, T.; Swithenby, S.; MacKay, R.; Merali, Y.; Lorincz, A.; Costea, C.; Bourgine, P.; Louçã, J.; Kapenieks, A.; Kelley, P.; Caird, S.; Bromley, J.; Deakin Crick, R.; Goldspink, C.; Collet, P.; Carbone, A.; Helbing, D.

2012-11-01

Education is a major force for economic and social wellbeing. Despite high aspirations, education at all levels can be expensive and ineffective. Three Grand Challenges are identified: (1) enable people to learn orders of magnitude more effectively, (2) enable people to learn at orders of magnitude less cost, and (3) demonstrate success by exemplary interdisciplinary education in complex systems science. A ten year `man-on-the-moon' project is proposed in which FuturICT's unique combination of Complexity, Social and Computing Sciences could provide an urgently needed transdisciplinary language for making sense of educational systems. In close dialogue with educational theory and practice, and grounded in the emerging data science and learning analytics paradigms, this will translate into practical tools (both analytical and computational) for researchers, practitioners and leaders; generative principles for resilient educational ecosystems; and innovation for radically scalable, yet personalised, learner engagement and assessment. The proposed Education Accelerator will serve as a `wind tunnel' for testing these ideas in the context of real educational programmes, with an international virtual campus delivering complex systems education exploiting the new understanding of complex, social, computationally enhanced organisational structure developed within FuturICT.

Challenges in Developing Models Describing Complex Soil Systems

NASA Astrophysics Data System (ADS)

Simunek, J.; Jacques, D.

2014-12-01

Quantitative mechanistic models that consider basic physical, mechanical, chemical, and biological processes have the potential to be powerful tools to integrate our understanding of complex soil systems, and the soil science community has often called for models that would include a large number of these diverse processes. However, once attempts have been made to develop such models, the response from the community has not always been overwhelming, especially after it discovered that these models are consequently highly complex, requiring not only a large number of parameters, not all of which can be easily (or at all) measured and/or identified, and which are often associated with large uncertainties, but also requiring from their users deep knowledge of all/most of these implemented physical, mechanical, chemical and biological processes. Real, or perceived, complexity of these models then discourages users from using them even for relatively simple applications, for which they would be perfectly adequate. Due to the nonlinear nature and chemical/biological complexity of the soil systems, it is also virtually impossible to verify these types of models analytically, raising doubts about their applicability. Code inter-comparisons, which is then likely the most suitable method to assess code capabilities and model performance, requires existence of multiple models of similar/overlapping capabilities, which may not always exist. It is thus a challenge not only to developed models describing complex soil systems, but also to persuade the soil science community in using them. As a result, complex quantitative mechanistic models are still an underutilized tool in soil science research. We will demonstrate some of the challenges discussed above on our own efforts in developing quantitative mechanistic models (such as HP1/2) for complex soil systems.

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.

Improving processes through evolutionary optimization.

PubMed

Clancy, Thomas R

2011-09-01

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies on 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 18th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. In this article, I discuss methods to optimize complex healthcare processes through learning, adaptation, and evolutionary planning.

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.

Language Networks as Complex Systems

ERIC Educational Resources Information Center

Lee, Max Kueiming; Ou, Sheue-Jen

2008-01-01

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

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.

Authentic scientific data collection in support of an integrative model-based class: A framework for student engagement in the classroom

NASA Astrophysics Data System (ADS)

Sorensen, A. E.; Dauer, J. M.; Corral, L.; Fontaine, J. J.

2017-12-01

A core component of public scientific literacy, and thereby informed decision-making, is the ability of individuals to reason about complex systems. In response to students having difficulty learning about complex systems, educational research suggests that conceptual representations, or mental models, may help orient student thinking. Mental models provide a framework to support students in organizing and developing ideas. The PMC-2E model is a productive tool in teaching ideas of modeling complex systems in the classroom because the conceptual representation framework allows for self-directed learning where students can externalize systems thinking. Beyond mental models, recent work emphasizes the importance of facilitating integration of authentic science into the formal classroom. To align these ideas, a university class was developed around the theme of carnivore ecology, founded on PMC-2E framework and authentic scientific data collection. Students were asked to develop a protocol, collect, and analyze data around a scientific question in partnership with a scientist, and then use data to inform their own learning about the system through the mental model process. We identified two beneficial outcomes (1) scientific data is collected to address real scientific questions at a larger scale and (2) positive outcomes for student learning and views of science. After participating in the class, students report enjoying class structure, increased support for public understanding of science, and shifts in nature of science and interest in pursuing science metrics on post-assessments. Further work is ongoing investigating the linkages between engaging in authentic scientific practices that inform student mental models, and how it might promote students' systems-thinking skills, implications for student views of nature of science, and development of student epistemic practices.

Positive deviance: an elegant solution to a complex problem.

PubMed

Lindberg, Curt; Clancy, Thomas R

2010-04-01

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on 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 13th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. This article provides one example of how concepts taken from complex systems theory can be applied to real-world problems facing nurses today.

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.

The Natural Science Underlying Big History

PubMed Central

Chaisson, Eric J.

2014-01-01

Nature's many varied complex systems—including galaxies, stars, planets, life, and society—are islands of order within the increasingly disordered Universe. All organized systems are subject to physical, biological, or cultural evolution, which together comprise the grander interdisciplinary subject of cosmic evolution. A wealth of observational data supports the hypothesis that increasingly complex systems evolve unceasingly, uncaringly, and unpredictably from big bang to humankind. These are global history greatly extended, big history with a scientific basis, and natural history broadly portrayed across ∼14 billion years of time. Human beings and our cultural inventions are not special, unique, or apart from Nature; rather, we are an integral part of a universal evolutionary process connecting all such complex systems throughout space and time. Such evolution writ large has significant potential to unify the natural sciences into a holistic understanding of who we are and whence we came. No new science (beyond frontier, nonequilibrium thermodynamics) is needed to describe cosmic evolution's major milestones at a deep and empirical level. Quantitative models and experimental tests imply that a remarkable simplicity underlies the emergence and growth of complexity for a wide spectrum of known and diverse systems. Energy is a principal facilitator of the rising complexity of ordered systems within the expanding Universe; energy flows are as central to life and society as they are to stars and galaxies. In particular, energy rate density—contrasting with information content or entropy production—is an objective metric suitable to gauge relative degrees of complexity among a hierarchy of widely assorted systems observed throughout the material Universe. Operationally, those systems capable of utilizing optimum amounts of energy tend to survive, and those that cannot are nonrandomly eliminated. PMID:25032228

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.

From Metaphors to Models: Broadening the Lens of the Hunter Warrior Experiment with a Complex Adaptive System Tool

DTIC Science & Technology

1999-01-01

chemistry tells us why it is inevitable, pervasive, and won’t go away. Fortunately, there is the companion new science of complexity, rooted in...article. 30llachinski, Land Warfare and Complexity, Part II, 43. 32 Ilachinski, 43. Etymologically , metaphor (the Greek metafora, "carry over") means...anthropology, chemistry , economics, military and political science among others. Santa Fe Institute, http://www.santafe.edu/sfl/research. 53SAIC

Variable speed limit strategies analysis with mesoscopic traffic flow model based on complex networks

NASA Astrophysics Data System (ADS)

Li, Shu-Bin; Cao, Dan-Ni; Dang, Wen-Xiu; Zhang, Lin

As a new cross-discipline, the complexity science has penetrated into every field of economy and society. With the arrival of big data, the research of the complexity science has reached its summit again. In recent years, it offers a new perspective for traffic control by using complex networks theory. The interaction course of various kinds of information in traffic system forms a huge complex system. A new mesoscopic traffic flow model is improved with variable speed limit (VSL), and the simulation process is designed, which is based on the complex networks theory combined with the proposed model. This paper studies effect of VSL on the dynamic traffic flow, and then analyzes the optimal control strategy of VSL in different network topologies. The conclusion of this research is meaningful to put forward some reasonable transportation plan and develop effective traffic management and control measures to help the department of traffic management.

Professional development for science teachers.

PubMed

Wilson, Suzanne M

2013-04-19

The Next Generation Science Standards will require large-scale professional development (PD) for all science teachers. Existing research on effective teacher PD suggests factors that are associated with substantial changes in teacher knowledge and practice, as well as students' science achievement. But the complexity of the U.S. educational system continues to thwart the search for a straightforward answer to the question of how to support teachers. Interventions that take a systemic approach to reform hold promise for improving PD effectiveness.

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

ERIC Educational Resources Information Center

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

2004-01-01

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

Syllabus for Weizmann Course: Earth System Science 101

NASA Technical Reports Server (NTRS)

Wiscombe, Warren J.

2011-01-01

This course aims for an understanding of Earth System Science and the interconnection of its various "spheres" (atmosphere, hydrosphere, etc.) by adopting the view that "the microcosm mirrors the macrocosm". We shall study a small set of microcosims, each residing primarily in one sphere, but substantially involving at least one other sphere, in order to illustrate the kinds of coupling that can occur and gain a greater appreciation of the complexity of even the smallest Earth System Science phenomenon.

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.

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.

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…

Final Report: A Broad Research Project on the Sciences of Complexity, September 15, 1994 - November 15, 1999

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

None

2000-02-01

DOE support for a broad research program in the sciences of complexity permitted the Santa Fe Institute to initiate new collaborative research within its integrative core activities as well as to host visitors to participate in research on specific topics that serve as motivation and testing ground for the study of the general principles of complex systems. Results are presented on computational biology, biodiversity and ecosystem research, and advanced computing and simulation.

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'…

Conceptualising population health: from mechanistic thinking to complexity science.

PubMed

Jayasinghe, Saroj

2011-01-20

The mechanistic interpretation of reality can be traced to the influential work by René Descartes and Sir Isaac Newton. Their theories were able to accurately predict most physical phenomena relating to motion, optics and gravity. This paradigm had at least three principles and approaches: reductionism, linearity and hierarchy. These ideas appear to have influenced social scientists and the discourse on population health. In contrast, Complexity Science takes a more holistic view of systems. It views natural systems as being 'open', with fuzzy borders, constantly adapting to cope with pressures from the environment. These are called Complex Adaptive Systems (CAS). The sub-systems within it lack stable hierarchies, and the roles of agency keep changing. The interactions with the environment and among sub-systems are non-linear interactions and lead to self-organisation and emergent properties. Theoretical frameworks such as epi+demos+cracy and the ecosocial approach to health have implicitly used some of these concepts of interacting dynamic sub-systems. Using Complexity Science we can view population health outcomes as an emergent property of CAS, which has numerous dynamic non-linear interactions among its interconnected sub-systems or agents. In order to appreciate these sub-systems and determinants, one should acquire a basic knowledge of diverse disciplines and interact with experts from different disciplines. Strategies to improve health should be multi-pronged, and take into account the diversity of actors, determinants and contexts. The dynamic nature of the system requires that the interventions are constantly monitored to provide early feedback to a flexible system that takes quick corrections.

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…

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.

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.

Big Data and Data Science in Critical Care.

PubMed

Sanchez-Pinto, L Nelson; Luo, Yuan; Churpek, Matthew M

2018-05-09

The digitalization of the health-care system has resulted in a deluge of clinical Big Data and has prompted the rapid growth of data science in medicine. Data science, which is the field of study dedicated to the principled extraction of knowledge from complex data, is particularly relevant in the critical care setting. The availability of large amounts of data in the ICU, the need for better evidence-based care, and the complexity of critical illness makes the use of data science techniques and data-driven research particularly appealing to intensivists. Despite the increasing number of studies and publications in the field, thus far there have been few examples of data science projects that have resulted in successful implementations of data-driven systems in the ICU. However, given the expected growth in the field, intensivists should be familiar with the opportunities and challenges of Big Data and data science. The present article reviews the definitions, types of algorithms, applications, challenges, and future of Big Data and data science in critical care. Copyright © 2018 American College of Chest Physicians. Published by 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.

Critical issues in NASA information systems

NASA Technical Reports Server (NTRS)

1987-01-01

The National Aeronautics and Space Administration has developed a globally-distributed complex of earth resources data bases since LANDSAT 1 was launched in 1972. NASA envisages considerable growth in the number, extent, and complexity of such data bases, due to the improvements expected in its remote sensing data rates, and the increasingly multidisciplinary nature of its scientific investigations. Work already has begun on information systems to support multidisciplinary research activities based on data acquired by the space station complex and other space-based and terrestrial sources. In response to a request from NASA's former Associate Administrator for Space Science and Applications, the National Research Council convened a committee in June 1985 to identify the critical issues involving information systems support to space science and applications. The committee has suggested that OSSA address four major information systems issues; centralization of management functions, interoperability of user involvement in the planning and implementation of its programs, and technology.

An operationalized post-normal science framework for assisting in the development of complex science policy solutions: the case of nanotechnology governance

NASA Astrophysics Data System (ADS)

Bernstein, Michael J.; Foley, Rider W.; Bennett, Ira

2014-07-01

Scientists, engineers, and policy analysts commonly suggest governance regimes for technology to maximize societal benefits and minimize negative societal and environmental impacts of innovation processes. Yet innovation is a complex socio-technical process that does not respond predictably to modification. Our human propensity to exclude complexity when attempting to manage systems often results in insufficient, one-dimensional solutions. The tendency to exclude complexity (1) reinforces itself by diminishing experience and capacity in the design of simple solutions to complex problems, and (2) leads to solutions that do not address the identified problem. To address the question of how to avoid a complexity- exclusion trap, this article operationalizes a post-normal science framework to assist in the enhancement or design of science policy proposals. A literature review of technological fixes, policy panaceas, and knowledge-to-action gaps is conducted to survey examples of post-normal science frameworks. Next, an operational framework is used to assess the case of a proposed international nanotechnology advisory board. The framework reveals that the board addresses a slice of the broader, more complex problem of nanotechnology governance. We argue that while the formation of an international advisory board is not problematic in-and-of-itself, it is symptomatic of and plays into a complexity- exclusion trap. We offer researchers, policy analysts, and decision-makers three recommendations that incorporate a more appropriate level of complexity into governance proposals.

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…

Resilience | Science Inventory | US EPA

EPA Pesticide Factsheets

Resilience is an important framework for understanding and managing complex systems of people and nature that are subject to abrupt and nonlinear change. The idea of ecological resilience was slow to gain acceptance in the scientific community, taking thirty years to become widely accepted (Gunderson 2000, cited under Original Definition). Currently, the concept is commonplace in academics, management, and policy. Although the idea has quantitative roots in the ecological sciences and was proposed as a measurable quality of ecosystems, the broad use of resilience led to an expansion of definitions and applications. Holling’s original definition, presented in 1973 (Holling 1973, cited under Original Definition), was simply the amount of disturbance that a system can withstand before it shifts into an alternative stability domain. Ecological resilience, therefore, emphasizes that the dynamics of complex systems are nonlinear, meaning that these systems can transition, often abruptly, between dynamic states with substantially different structures, functions, and processes. The transition of ecological systems from one state to another frequently has important repercussions for humans. Recent definitions are more normative and qualitative, especially in the social sciences, and a competing definition, that of engineering resilience, is still often used. Resilience is an emergent phenomenon of complex systems, which means it cannot be deduced from the behavior of t

Taking Advantage of Automated Assessment of Student-Constructed Graphs in Science

ERIC Educational Resources Information Center

Vitale, Jonathan M.; Lai, Kevin; Linn, Marcia C.

2015-01-01

We present a new system for automated scoring of graph construction items that address complex science concepts, feature qualitative prompts, and support a range of possible solutions. This system utilizes analysis of spatial features (e.g., slope of a line) to evaluate potential student ideas represented within graphs. Student ideas are then…

Addressing the Complexities of Evaluating Interdisciplinary Multimedia Learning Environments.

ERIC Educational Resources Information Center

McGee, Steven; Howard, Bruce C.; Dimitrov, Dimiter M.; Hong, Namsoo S.; Shia, Regina

This study was a summative evaluation of Astronomy Village[R]: Investigating the Solar System[TM]. Funded by the National Science Foundation, Astronomy Village is designed to teach students fundamental concepts in life, earth, and physical science by having them investigate cutting-edge questions related to the solar system. In Astronomy Village…

Dissemination, Implementation, and Improvement Science Research in Population Health: Opportunities for Public Health and CTSAs.

PubMed

Kuo, Tony; Gase, Lauren N; Inkelas, Moira

2015-12-01

The complex, dynamic nature of health systems requires dissemination, implementation, and improvement (DII) sciences to effectively translate emerging knowledge into practice. Although they hold great promise for informing multisector policies and system-level changes, these methods are often not strategically used by public health. More than 120 stakeholders from Southern California, including the community, federal and local government, university, and health services were convened to identify key priorities and opportunities for public health departments and Clinical and Translational Science Awards programs (CTSAs) to advance DII sciences in population health. Participants identified challenges (mismatch of practice realities with narrowly focused research questions; lack of iterative learning) and solutions (using methods that fit the dynamic nature of the real world; aligning theories of change across sectors) for applying DII science research to public health problems. Pragmatic steps that public health and CTSAs can take to facilitate DII science research include: employing appropriate study designs; training scientists and practicing professionals in these methods; securing resources to advance this work; and supporting team science to solve complex-systems issues. Public health and CTSAs represent a unique model of practice for advancing DII research in population health. The partnership can inform policy and program development in local communities. © 2015 Wiley Periodicals, Inc.

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

On complex adaptive systems and terrorism [rapid communication

NASA Astrophysics Data System (ADS)

Ahmed, E.; Elgazzar, A. S.; Hegazi, A. S.

2005-03-01

Complex adaptive systems (CAS) are ubiquitous in nature. They are basic in social sciences. An overview of CAS is given with emphasize on the occurrence of bad side effects to seemingly “wise” decisions. Hence application to terrorism is given. Some conclusions on how to deal with this phenomena are proposed.

Asset - An application in mission automation for science planning

NASA Technical Reports Server (NTRS)

Finnerty, D. F.; Martin, J.; Doms, P. E.

1987-01-01

Recent advances in computer technology were used to great advantage in planning science observation sequences for the Voyager 2 encounter with Uranus in 1986. Despite a loss of experienced personnel, a challenging schedule, workforce limitations, and the complex nature of the Uranus encounter itself, the resultant science observation timelines were the most highly optimized of the five Voyager encounters with the outer planets. In part, this was due to the development of a microcomputer-based system, called ASSET (Automated Science Sequence Encounter Timelines generator), which was used to design those science observation timelines. This paper details the development of that system. ASSET demonstrates several features essential to the design of the first expert systems for science planning which will be applied for future missions.

Complex network problems in physics, computer science and biology

NASA Astrophysics Data System (ADS)

Cojocaru, Radu Ionut

There is a close relation between physics and mathematics and the exchange of ideas between these two sciences are well established. However until few years ago there was no such a close relation between physics and computer science. Even more, only recently biologists started to use methods and tools from statistical physics in order to study the behavior of complex system. In this thesis we concentrate on applying and analyzing several methods borrowed from computer science to biology and also we use methods from statistical physics in solving hard problems from computer science. In recent years physicists have been interested in studying the behavior of complex networks. Physics is an experimental science in which theoretical predictions are compared to experiments. In this definition, the term prediction plays a very important role: although the system is complex, it is still possible to get predictions for its behavior, but these predictions are of a probabilistic nature. Spin glasses, lattice gases or the Potts model are a few examples of complex systems in physics. Spin glasses and many frustrated antiferromagnets map exactly to computer science problems in the NP-hard class defined in Chapter 1. In Chapter 1 we discuss a common result from artificial intelligence (AI) which shows that there are some problems which are NP-complete, with the implication that these problems are difficult to solve. We introduce a few well known hard problems from computer science (Satisfiability, Coloring, Vertex Cover together with Maximum Independent Set and Number Partitioning) and then discuss their mapping to problems from physics. In Chapter 2 we provide a short review of combinatorial optimization algorithms and their applications to ground state problems in disordered systems. We discuss the cavity method initially developed for studying the Sherrington-Kirkpatrick model of spin glasses. We extend this model to the study of a specific case of spin glass on the Bethe lattice at zero temperature and then we apply this formalism to the K-SAT problem defined in Chapter 1. The phase transition which physicists study often corresponds to a change in the computational complexity of the corresponding computer science problem. Chapter 3 presents phase transitions which are specific to the problems discussed in Chapter 1 and also known results for the K-SAT problem. We discuss the replica method and experimental evidences of replica symmetry breaking. The physics approach to hard problems is based on replica methods which are difficult to understand. In Chapter 4 we develop novel methods for studying hard problems using methods similar to the message passing techniques that were discussed in Chapter 2. Although we concentrated on the symmetric case, cavity methods show promise for generalizing our methods to the un-symmetric case. As has been highlighted by John Hopfield, several key features of biological systems are not shared by physical systems. Although living entities follow the laws of physics and chemistry, the fact that organisms adapt and reproduce introduces an essential ingredient that is missing in the physical sciences. In order to extract information from networks many algorithm have been developed. In Chapter 5 we apply polynomial algorithms like minimum spanning tree in order to study and construct gene regulatory networks from experimental data. As future work we propose the use of algorithms like min-cut/max-flow and Dijkstra for understanding key properties of these networks.

Self-organization versus self-management: two sides of the same coin?

PubMed

Clancy, Thomas R

2009-03-01

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 eighth 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 author explores self-organization as it relates to self-management in complex social organizations.

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.

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…

The emergence of mind and brain: an evolutionary, computational, and philosophical approach.

PubMed

Mainzer, Klaus

2008-01-01

Modern philosophy of mind cannot be understood without recent developments in computer science, artificial intelligence (AI), robotics, neuroscience, biology, linguistics, and psychology. Classical philosophy of formal languages as well as symbolic AI assume that all kinds of knowledge must explicitly be represented by formal or programming languages. This assumption is limited by recent insights into the biology of evolution and developmental psychology of the human organism. Most of our knowledge is implicit and unconscious. It is not formally represented, but embodied knowledge, which is learnt by doing and understood by bodily interacting with changing environments. That is true not only for low-level skills, but even for high-level domains of categorization, language, and abstract thinking. The embodied mind is considered an emergent capacity of the brain as a self-organizing complex system. Actually, self-organization has been a successful strategy of evolution to handle the increasing complexity of the world. Genetic programs are not sufficient and cannot prepare the organism for all kinds of complex situations in the future. Self-organization and emergence are fundamental concepts in the theory of complex dynamical systems. They are also applied in organic computing as a recent research field of computer science. Therefore, cognitive science, AI, and robotics try to model the embodied mind in an artificial evolution. The paper analyzes these approaches in the interdisciplinary framework of complex dynamical systems and discusses their philosophical impact.

NASA's Solar Dynamics Observatory (SDO): A Systems Approach to a Complex Mission

NASA Technical Reports Server (NTRS)

Ruffa, John A.; Ward, David K.; Bartusek, LIsa M.; Bay, Michael; Gonzales, Peter J.; Pesnell, William D.

2012-01-01

The Solar Dynamics Observatory (SDO) includes three advanced instruments, massive science data volume, stringent science data completeness requirements, and a custom ground station to meet mission demands. The strict instrument science requirements imposed a number of challenging drivers on the overall mission system design, leading the SDO team to adopt an integrated systems engineering presence across all aspects of the mission to ensure that mission science requirements would be met. Key strategies were devised to address these system level drivers and mitigate identified threats to mission success. The global systems engineering team approach ensured that key drivers and risk areas were rigorously addressed through all phases of the mission, leading to the successful SDO launch and on-orbit operation. Since launch, SDO's on-orbit performance has met all mission science requirements and enabled groundbreaking science observations, expanding our understanding of the Sun and its dynamic processes.

NASA's Solar Dynamics Observatory (SDO): A Systems Approach to a Complex Mission

NASA Technical Reports Server (NTRS)

Ruffa, John A.; Ward, David K.; Bartusek, Lisa M.; Bay, Michael; Gonzales, Peter J.; Pesnell, William D.

2012-01-01

The Solar Dynamics Observatory (SDO) includes three advanced instruments, massive science data volume, stringent science data completeness requirements, and a custom ground station to meet mission demands. The strict instrument science requirements imposed a number of challenging drivers on the overall mission system design, leading the SDO team to adopt an integrated systems engineering presence across all aspects of the mission to ensure that mission science requirements would be met. Key strategies were devised to address these system level drivers and mitigate identified threats to mission success. The global systems engineering team approach ensured that key drivers and risk areas were rigorously addressed through all phases of the mission, leading to the successful SDO launch and on-orbit operation. Since launch, SDO s on-orbit performance has met all mission science requirements and enabled groundbreaking science observations, expanding our understanding of the Sun and its dynamic processes.

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

PubMed

Sturmberg, Joachim P; Martin, Carmel M

2012-02-01

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

Does Cloud Computing in the Atmospheric Sciences Make Sense? A case study of hybrid cloud computing at NASA Langley Research Center

NASA Astrophysics Data System (ADS)

Nguyen, L.; Chee, T.; Minnis, P.; Spangenberg, D.; Ayers, J. K.; Palikonda, R.; Vakhnin, A.; Dubois, R.; Murphy, P. R.

2014-12-01

The processing, storage and dissemination of satellite cloud and radiation products produced at NASA Langley Research Center are key activities for the Climate Science Branch. A constellation of systems operates in sync to accomplish these goals. Because of the complexity involved with operating such intricate systems, there are both high failure rates and high costs for hardware and system maintenance. Cloud computing has the potential to ameliorate cost and complexity issues. Over time, the cloud computing model has evolved and hybrid systems comprising off-site as well as on-site resources are now common. Towards our mission of providing the highest quality research products to the widest audience, we have explored the use of the Amazon Web Services (AWS) Cloud and Storage and present a case study of our results and efforts. This project builds upon NASA Langley Cloud and Radiation Group's experience with operating large and complex computing infrastructures in a reliable and cost effective manner to explore novel ways to leverage cloud computing resources in the atmospheric science environment. Our case study presents the project requirements and then examines the fit of AWS with the LaRC computing model. We also discuss the evaluation metrics, feasibility, and outcomes and close the case study with the lessons we learned that would apply to others interested in exploring the implementation of the AWS system in their own atmospheric science computing environments.

Photo-realistic Terrain Modeling and Visualization for Mars Exploration Rover Science Operations

NASA Technical Reports Server (NTRS)

Edwards, Laurence; Sims, Michael; Kunz, Clayton; Lees, David; Bowman, Judd

2005-01-01

Modern NASA planetary exploration missions employ complex systems of hardware and software managed by large teams of. engineers and scientists in order to study remote environments. The most complex and successful of these recent projects is the Mars Exploration Rover mission. The Computational Sciences Division at NASA Ames Research Center delivered a 30 visualization program, Viz, to the MER mission that provides an immersive, interactive environment for science analysis of the remote planetary surface. In addition, Ames provided the Athena Science Team with high-quality terrain reconstructions generated with the Ames Stereo-pipeline. The on-site support team for these software systems responded to unanticipated opportunities to generate 30 terrain models during the primary MER mission. This paper describes Viz, the Stereo-pipeline, and the experiences of the on-site team supporting the scientists at JPL during the primary MER mission.

The science of complexity and the role of mathematics

NASA Astrophysics Data System (ADS)

Bountis, T.; Johnson, J.; Provata, A.; Tsironis, G.

2016-09-01

In the middle of the second decade of the 21st century, Complexity Science has reached a turning point. Its rapid advancement over the last 30 years has led to remarkable new concepts, methods and techniques, whose applications to complex systems of the physical, biological and social sciences has produced a great number of exciting results. The approach has so far depended almost exclusively on the solution of a wide variety of mathematical models by sophisticated numerical techniques and extensive simulations that have inspired a new generation of researchers interested in complex systems. Still, the impact of Complexity beyond the natural sciences, its applications to Medicine, Technology, Economics, Society and Policy are only now beginning to be explored. Furthermore, its basic principles and methods have so far remained within the realm of high level research institutions, out of reach of society's urgent need for practical applications. To address these issues, evaluate the current situation and bring Complexity Science closer to university students, a series of Ph.D. Schools on Mathematical Modeling of Complex Systems was launched, starting in July 2011 at the University of Patras, Greece (see http://www.math.upatras.gr/˜phdsch11). These Schools lasted two weeks each and included, beyond introductory lectures, a conference component of 2-3 days where students were exposed to recent results mainly presented by young researchers. The Ph.D. Schools continued successfully, the 2nd one taking place at Pescara, Italy (2012), (see http://www.nodycosy.unich.it), the 3d one at Heraklion, Crete, Greece (2013) (see http://nlsconf2013.physics.uoc.gr) and the 4th one in Athens, Greece (2014) (see http://nlsconf2014.physics.uoc.gr) (2014). This Special Theme volume contains the proceedings of the 5th Ph.D. School-Conference of this series held at the University of Patras, Greece, 20 30 July, 2015 (see http://www.math.upatras.gr/˜phdsch15) and includes many of the introductory lectures and research talks presented at this event. The primary concern of all those that participated in these events was to emphasize the role of mathematics, modeling and numerical simulation, which are indispensable for understanding what we call complex behavior of physical, biological, technological and socio - economical systems. In the discussions that took place, a great number of participants expressed the need to formulate a unifying theory of complex systems based on the main conclusions that have been reached so far in the science of Complexity. As Guest Editors of this volume, we also feel that it is important to reach some fundamental conclusions concerning common phenomena, theories and methodologies that arise in Complexity. We should all work to explore common rules and approaches, particularly in view of the remarkable challenges that face us all regarding complex social problems that threaten present day society and civilization as we know them.

University participation via UNIDATA, part 1

NASA Technical Reports Server (NTRS)

Dutton, J.

1986-01-01

The UNIDATA Project is a cooperative university project, operated by the University Corporation for Atmospheric Research (UCAR) with National Science Foundation (NSF) funding, aimed at providing interactive communication and computations to the university community in the atmospheric and oceanic sciences. The initial focus has been on providing access to data for weather analysis and prediction. However, UNIDATA is in the process of expanding and possibly providing access to the Pilot Climate Data System (PCDS) through the UNIDATA system in an effort to develop prototypes for an Earth science information system. The notion of an Earth science information system evolved from discussions within NASA and several advisory committees in anticipation of receiving data from the many Earth observing instruments on the space station complex (Earth Observing System).

Towards Understanding and Managing Sustainable Complex, Dynamic Environmental/Economic/Social Systems - The Evolving Role of the Natural Sciences

EPA Science Inventory

Historically the natural sciences have played a major role in informing environmental management decisions. However, review of landmark cases like Love Canal, NY and Times Beach, MO have shown that the value of natural science information in decision making can be overwhelmed by ...

Cultural Emergence: Theorizing Culture in and from the Margins of Science Education

ERIC Educational Resources Information Center

Wood, Nathan Brent; Erichsen, Elizabeth Anne; Anicha, Cali L.

2013-01-01

This special issue of the Journal of Research in Science Teaching seeks to explore conceptualizations of culture that address contemporary challenges in science education. Toward this end, we unite two theoretical perspectives to advance a conceptualization of culture as a complex system, emerging from iterative processes of cultural bricolage,…

NASA's Space Launch System (SLS) Program: Mars Program Utilization

NASA Technical Reports Server (NTRS)

May, Todd A.; Creech, Stephen D.

2012-01-01

NASA's Space Launch System is being designed for safe, affordable, and sustainable human and scientific exploration missions beyond Earth's orbit (BEO), as directed by the NASA Authorization Act of 2010 and NASA's 2011 Strategic Plan. This paper describes how the SLS can dramatically change the Mars program's science and human exploration capabilities and objectives. Specifically, through its high-velocity change (delta V) and payload capabilities, SLS enables Mars science missions of unprecedented size and scope. By providing direct trajectories to Mars, SLS eliminates the need for complicated gravity-assist missions around other bodies in the solar system, reducing mission time, complexity, and cost. SLS's large payload capacity also allows for larger, more capable spacecraft or landers with more instruments, which can eliminate the need for complex packaging or "folding" mechanisms. By offering this capability, SLS can enable more science to be done more quickly than would be possible through other delivery mechanisms using longer mission times.

Building Systems from Scratch: An Exploratory Study of Students Learning about Climate Change

ERIC Educational Resources Information Center

Puttick, Gillian; Tucker-Raymond, Eli

2018-01-01

Science and computational practices such as modeling and abstraction are critical to understanding the complex systems that are integral to climate science. Given the demonstrated affordances of game design in supporting such practices, we implemented a free 4-day intensive workshop for middle school girls that focused on using the visual…

Providing Health Sciences Services in a Joint-Use Distributed Learning Library System: An Organizational Case Study.

PubMed

Enslow, Electra; Fricke, Suzanne; Vela, Kathryn

2017-01-01

The purpose of this organizational case study is to describe the complexities librarians face when serving a multi-campus institution that supports both a joint-use library and expanding health sciences academic partnerships. In a system without a centralized health science library administration, liaison librarians are identifying dispersed programs and user groups and collaborating to define their unique service and outreach needs within a larger land-grant university. Using a team-based approach, health sciences librarians are communicating to integrate research and teaching support, systems differences across dispersed campuses, and future needs of a new community-based medical program.

Cells distribution in the modeling of fibrosis. Comment on "Towards a unified approach in the modeling of fibrosis: A review with research perspectives" by Martine Ben Amar and Carlo Bianca

NASA Astrophysics Data System (ADS)

Abdel-Aty, Mahmoud

2016-07-01

The modeling of a complex system requires the analysis of all microscopic constituents and in particular of their interactions [1]. The interest in this research field has increased considering also recent developments in the information sciences. However interaction among scholars working in various fields of the applied sciences can be considered the true motor for the definition of a general framework for the analysis of complex systems. In particular biological systems constitute the platform where many scientists have decided to collaborate in order to gain a global description of the system. Among others, cancer-immune system competition (see [2] and the review papers [3,4]) has attracted much attention.

Using DCOM to support interoperability in forest ecosystem management decision support systems

Treesearch

W.D. Potter; S. Liu; X. Deng; H.M. Rauscher

2000-01-01

Forest ecosystems exhibit complex dynamics over time and space. Management of forest ecosystems involves the need to forecast future states of complex systems that are often undergoing structural changes. This in turn requires integration of quantitative science and engineering components with sociopolitical, regulatory, and economic considerations. The amount of data...

Systems Thinking Tools as Applied to Community-Based Participatory Research: A Case Study

ERIC Educational Resources Information Center

BeLue, Rhonda; Carmack, Chakema; Myers, Kyle R.; Weinreb-Welch, Laurie; Lengerich, Eugene J.

2012-01-01

Community-based participatory research (CBPR) is being used increasingly to address health disparities and complex health issues. The authors propose that CBPR can benefit from a systems science framework to represent the complex and dynamic characteristics of a community and identify intervention points and potential "tipping points."…

Modelling the Burstiness of Complex Space Plasmas Using Linear Fractional Stable Motion

NASA Astrophysics Data System (ADS)

Watkins, N. W.; Rosenberg, S. J.; Chapman, S. C.; Sanchez, R.; Credgington, D.

2009-12-01

The Earth's magnetosphere is quite clearly “complex" in the everyday sense of the word. However, in the last 15 to 20 years there has been a growing thread in space physics (e.g. Freeman & Watkins [Science, 2002] , Chapman & Watkins [Space Science Reviews, 2001]) using and developing some of the emerging science of complex systems (e.g. Sornette, 2nd Edition, 2004). A particularly well-studied set of system properties has been derived from those used in the study of critical phenomena, notably correlation functions, power spectra, distributions of bursts above a threshold, and so on (e.g. Watkins [Nonlinear Processes in Geophysics, 2002]). These have revealed behaviours familiar from many other complex systems, such as burstiness, long range dependence, heavy tailed probability distributions and so forth. The results of these studies are typically interpreted within existing paradigms, most notably self-organised criticality. However, just as in other developing areas of complexity science (Sornette, op. cit.; Watkins & Freeman [Science, 2008]), it is increasingly being realised that the diagnostics in use have not been extensively studied outside the context in which they were originally proposed. This means that, for example, it is not well established what the expected distribution of bursts above a fixed threshold will be for time series other than Brownian (or fractional Brownian) motion. We will describe some preliminary investigations (Watkins et al [Physical Review E, 2009]) into the burst distribution problem, using Linear Fractional Stable Motion as a controllable toy model of a process exhibiting both long-range dependence and heavy tails. A by product of the work was a differential equation for LFSM (Watkins et al, op cit), which we also briefly discuss. Current and future work will also focus on the thorny problem of distinguishing turbulence from SOC in natural datasets (Watkins et al; Uritsky et al [Physical Review Letters, 2009]) with limited dynamic range, an area which will also be briefly discussed.

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

Informatics Metrics and Measures for a Smart Public Health Systems Approach: Information Science Perspective

PubMed Central

Shea, Christopher Michael

2017-01-01

Public health informatics is an evolving domain in which practices constantly change to meet the demands of a highly complex public health and healthcare delivery system. Given the emergence of various concepts, such as learning health systems, smart health systems, and adaptive complex health systems, health informatics professionals would benefit from a common set of measures and capabilities to inform our modeling, measuring, and managing of health system “smartness.” Here, we introduce the concepts of organizational complexity, problem/issue complexity, and situational awareness as three codependent drivers of smart public health systems characteristics. We also propose seven smart public health systems measures and capabilities that are important in a public health informatics professional's toolkit. PMID:28167999

Informatics Metrics and Measures for a Smart Public Health Systems Approach: Information Science Perspective.

PubMed

Carney, Timothy Jay; Shea, Christopher Michael

2017-01-01

Public health informatics is an evolving domain in which practices constantly change to meet the demands of a highly complex public health and healthcare delivery system. Given the emergence of various concepts, such as learning health systems, smart health systems, and adaptive complex health systems, health informatics professionals would benefit from a common set of measures and capabilities to inform our modeling, measuring, and managing of health system "smartness." Here, we introduce the concepts of organizational complexity, problem/issue complexity, and situational awareness as three codependent drivers of smart public health systems characteristics. We also propose seven smart public health systems measures and capabilities that are important in a public health informatics professional's toolkit.

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.

Can there be a physics of financial markets? Methodological reflections on econophysics

NASA Astrophysics Data System (ADS)

Huber, Tobias A.; Sornette, Didier

2016-12-01

We address the question whether there can be a physical science of financial markets. In particular, we examine the argument that, given the reflexivity of financial markets (i.e., the feedback mechanism between expectations and prices), there is a fundamental difference between social and physical systems, which demands a new scientific method. By providing a selective history of the mutual cross-fertilization between physics and economics, we reflect on the methodological differences of how models and theories get constructed in these fields. We argue that the novel conception of financial markets as complex adaptive systems is one of the most important contributions of econophysics and show that this field of research provides the methods, concepts, and tools to scientifically account for reflexivity. We conclude by arguing that a new science of economic and financial systems should not only be physics-based, but needs to integrate findings from other scientific fields, so that a truly multi-disciplinary complex systems science of financial markets can be built.

Five schools of thought about complexity: Implications for design and process science

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

Warfield, J.N.

1996-12-31

The prevalence of complexity is a fact of life in virtually all aspects of system design today. Five schools of thought concerning complexity seem to be present in areas where people strive to gain more facility with difficult issues: (1) Interdisciplinary or Cross-Disciplinary {open_quotes}approaches{close_quotes} or {open_quotes}methods{close_quotes} (fostered by the Association for Integrative Studies, a predominantly liberal-arts faculty activity), (2) Systems Dynamics (fostered by Jay Forrester, Dennis Meadows, Peter Senge, and others closely associated with MIT), (3) Chaos Theory (arising in small groups in many locations), (4) Adaptive Systems Theory (predominantly associated with the Santa Fe Institute), and (5) The Structure-Basedmore » school (developed by the author, his colleagues and associates). A comparison of these five schools of thought will be offered, in order to show the implications of them upon the development and application of design and process science. The following criteria of comparison will be used: (a) how complexity is defined, (b) analysis versus synthesis, (c) potential for acquiring practical competence in coping with complexity, and (d) relationship to underlying formalisms that facilitate computer assistance in applications. Through these comparisons, the advantages and disadvantages of each school of thought can be clarified, and the possibilities of changes in the educational system to provide for the management of complexity in system design can be articulated.« less

Big Data in Plant Science: Resources and Data Mining Tools for Plant Genomics and Proteomics.

PubMed

Popescu, George V; Noutsos, Christos; Popescu, Sorina C

2016-01-01

In modern plant biology, progress is increasingly defined by the scientists' ability to gather and analyze data sets of high volume and complexity, otherwise known as "big data". Arguably, the largest increase in the volume of plant data sets over the last decade is a consequence of the application of the next-generation sequencing and mass-spectrometry technologies to the study of experimental model and crop plants. The increase in quantity and complexity of biological data brings challenges, mostly associated with data acquisition, processing, and sharing within the scientific community. Nonetheless, big data in plant science create unique opportunities in advancing our understanding of complex biological processes at a level of accuracy without precedence, and establish a base for the plant systems biology. In this chapter, we summarize the major drivers of big data in plant science and big data initiatives in life sciences with a focus on the scope and impact of iPlant, a representative cyberinfrastructure platform for plant science.

Can multilayer brain networks be a real step forward?. Comment on "Network science of biological systems at different scales: A review" by M. Gosak et al.

NASA Astrophysics Data System (ADS)

Buldú, Javier M.; Papo, David

2018-03-01

Over the last two decades Network Science has become one of the most active fields in science, whose growth has been supported by four fundamental pillars: statistical physics, nonlinear dynamics, graph theory and Big Data [1]. Initially concerned with analyzing the structure of networks, Network Science rapidly turned its attention, focused on the implications of network topology, on the dynamics of and processes unfolding on networked systems, greatly improving our understanding of diffusion, synchronization, epidemics and information transmission in complex systems [2]. The network approach typically considered complex systems as evolving in a vacuum; however real networks are generally not isolated systems, but are in continuous and evolving contact with other networks, with which they interact in multiple qualitative different and typically time-varying ways. These systems can then be represented as a collection of subsystems with connectivity layers, which are simply collapsed when considering the traditional monolayer representation. Surprisingly, such an "unpacking" of layers has proven to bear profound consequences on the structural and dynamical properties of networks, leading for instance to counter-intuitive synchronization phenomena, where maximization synchronization is achieved through strategies opposite of those maximizing synchronization in isolated networks [3].

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 ...

Networks in cognitive science.

PubMed

Baronchelli, Andrea; Ferrer-i-Cancho, Ramon; Pastor-Satorras, Romualdo; Chater, Nick; Christiansen, Morten H

2013-07-01

Networks of interconnected nodes have long played a key role in Cognitive Science, from artificial neural networks to spreading activation models of semantic memory. Recently, however, a new Network Science has been developed, providing insights into the emergence of global, system-scale properties in contexts as diverse as the Internet, metabolic reactions, and collaborations among scientists. Today, the inclusion of network theory into Cognitive Sciences, and the expansion of complex-systems science, promises to significantly change the way in which the organization and dynamics of cognitive and behavioral processes are understood. In this paper, we review recent contributions of network theory at different levels and domains within the Cognitive Sciences. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Doganca Kucuk, Zerrin; Saysel, Ali Kerem

2017-03-01

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 quasi-experimental methodology was used to compare performances of the participants in various dimensions, including systems thinking skills, competence in dynamic environmental problem solving and success in science achievement tests. The same pre-, post- and delayed tests were used with both the comparison and experimental groups in the same public middle school in Istanbul. Classroom activities designed for the comparison group (N = 20) followed the directives of the Science and Technology Curriculum, while the experimental group (N = 22) covered the same subject matter through activities benefiting from systems tools and representations such as behaviour over time graphs, causal loop diagrams, stock-flow structures and hands-on dynamic modelling. After a one-month systems-based instruction, the experimental group demonstrated significantly better systems thinking and dynamic environmental problem solving skills. Achievement in dynamic problem solving was found to be relatively stable over time. However, standard science achievement did not improve at all. This paper focuses on the quantitative analysis of the results, the weaknesses of the curriculum and educational implications.

Linking Student Achievement and Teacher Science Content Knowledge about Climate Change: Ensuring the Nations 3 Million Teachers Understand the Science through an Electronic Professional Development System

NASA Astrophysics Data System (ADS)

Niepold, F.; Byers, A.

2009-12-01

The scientific complexities of global climate change, with wide-ranging economic and social significance, create an intellectual challenge that mandates greater public understanding of climate change research and the concurrent ability to make informed decisions. The critical need for an engaged, science literate public has been repeatedly emphasized by multi-disciplinary entities like the Intergovernmental Panel on Climate Change (IPCC), the National Academies (Rising Above the Gathering Storm report), and the interagency group responsible for the recently updated Climate Literacy: The Essential Principles of Climate Science. There is a clear need for an American public that is climate literate and for K-12 teachers confident in teaching relevant science content. A key goal in the creation of a climate literate society is to enhance teachers’ knowledge of global climate change through a national, scalable, and sustainable professional development system, using compelling climate science data and resources to stimulate inquiry-based student interest in science, technology, engineering, and mathematics (STEM). This session will explore innovative e-learning technologies to address the limitations of one-time, face-to-face workshops, thereby adding significant sustainability and scalability. The resources developed will help teachers sift through the vast volume of global climate change information and provide research-based, high-quality science content and pedagogical information to help teachers effectively teach their students about the complex issues surrounding global climate change. The Learning Center is NSTA's e-professional development portal to help the nations teachers and informal educators learn about the scientific complexities of global climate change through research-based techniques and is proven to significantly improve teacher science content knowledge.

Interdisciplinary Team Science in Cell Biology.

PubMed

Horwitz, Rick

2016-11-01

The cell is complex. With its multitude of components, spatial-temporal character, and gene expression diversity, it is challenging to comprehend the cell as an integrated system and to develop models that predict its behaviors. I suggest an approach to address this issue, involving system level data analysis, large scale team science, and philanthropy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Ethics in Publishing: Complexity Science and Human Factors Offer Insights to Develop a Just Culture.

PubMed

Saurin, Tarcisio Abreu

2016-12-01

While ethics in publishing has been increasingly debated, there seems to be a lack of a theoretical framework for making sense of existing rules of behavior as well as for designing, managing and enforcing such rules. This letter argues that systems-oriented disciplines, such as complexity science and human factors, offer insights into new ways of dealing with ethics in publishing. Some examples of insights are presented. Also, a call is made for empirical studies that unveil the context and details of both retracted papers and the process of writing and publishing academic papers. This is expected to shed light on the complexity of the publication system as well as to support the development of a just culture, in which all participants are accountable.

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.

The computational challenges of Earth-system science.

PubMed

O'Neill, Alan; Steenman-Clark, Lois

2002-06-15

The Earth system--comprising atmosphere, ocean, land, cryosphere and biosphere--is an immensely complex system, involving processes and interactions on a wide range of space- and time-scales. To understand and predict the evolution of the Earth system is one of the greatest challenges of modern science, with success likely to bring enormous societal benefits. High-performance computing, along with the wealth of new observational data, is revolutionizing our ability to simulate the Earth system with computer models that link the different components of the system together. There are, however, considerable scientific and technical challenges to be overcome. This paper will consider four of them: complexity, spatial resolution, inherent uncertainty and time-scales. Meeting these challenges requires a significant increase in the power of high-performance computers. The benefits of being able to make reliable predictions about the evolution of the Earth system should, on their own, amply repay this investment.

The new challenges of multiplex networks: Measures and models

NASA Astrophysics Data System (ADS)

Battiston, Federico; Nicosia, Vincenzo; Latora, Vito

2017-02-01

What do societies, the Internet, and the human brain have in common? They are all examples of complex relational systems, whose emerging behaviours are largely determined by the non-trivial networks of interactions among their constituents, namely individuals, computers, or neurons, rather than only by the properties of the units themselves. In the last two decades, network scientists have proposed models of increasing complexity to better understand real-world systems. Only recently we have realised that multiplexity, i.e. the coexistence of several types of interactions among the constituents of a complex system, is responsible for substantial qualitative and quantitative differences in the type and variety of behaviours that a complex system can exhibit. As a consequence, multilayer and multiplex networks have become a hot topic in complexity science. Here we provide an overview of some of the measures proposed so far to characterise the structure of multiplex networks, and a selection of models aiming at reproducing those structural properties and quantifying their statistical significance. Focusing on a subset of relevant topics, this brief review is a quite comprehensive introduction to the most basic tools for the analysis of multiplex networks observed in the real-world. The wide applicability of multiplex networks as a framework to model complex systems in different fields, from biology to social sciences, and the colloquial tone of the paper will make it an interesting read for researchers working on both theoretical and experimental analysis of networked systems.

The AGING Initiative experience: a call for sustained support for team science networks.

PubMed

Garg, Tullika; Anzuoni, Kathryn; Landyn, Valentina; Hajduk, Alexandra; Waring, Stephen; Hanson, Leah R; Whitson, Heather E

2018-05-18

Team science, defined as collaborative research efforts that leverage the expertise of diverse disciplines, is recognised as a critical means to address complex healthcare challenges, but the practical implementation of team science can be difficult. Our objective is to describe the barriers, solutions and lessons learned from our team science experience as applied to the complex and growing challenge of multiple chronic conditions (MCC). MCC is the presence of two or more chronic conditions that have a collective adverse effect on health status, function or quality of life, and that require complex healthcare management, decision-making or coordination. Due to the increasing impact on the United States society, MCC research has been identified as a high priority research area by multiple federal agencies. In response to this need, two national research entities, the Healthcare Systems Research Network (HCSRN) and the Claude D. Pepper Older Americans Independence Centers (OAIC), formed the Advancing Geriatrics Infrastructure and Network Growth (AGING) Initiative to build nationwide capacity for MCC team science. This article describes the structure, lessons learned and initial outcomes of the AGING Initiative. We call for funding mechanisms to sustain infrastructures that have demonstrated success in fostering team science and innovation in translating findings to policy change necessary to solve complex problems in healthcare.

Technology of Synergy Manifestation in the Research of Solution's Stability of Differential Equations System

ERIC Educational Resources Information Center

Dvoryatkina, Svetlana N.; Melnikov, Roman A. M.; Smirnov, Eugeny I.

2017-01-01

Effectiveness of mathematical education as non-linear, composite and open system, formation and development of cognitive abilities of the trainee are wholly defined in the solution of complex tasks by means of modern achievements in science to high school practice adaptation. The possibility of complex tasks solution arises at identification of…

Plenary Speech: Researching Complex Dynamic Systems--"Retrodictive Qualitative Modelling" in the Language Classroom

ERIC Educational Resources Information Center

Dörnyei, Zoltán

2014-01-01

While approaching second language acquisition from a complex dynamic systems perspective makes a lot of intuitive sense, it is difficult for a number of reasons to operationalise such a dynamic approach in research terms. For example, the most common research paradigms in the social sciences tend to examine variables in relative isolation rather…

U.S. Geological Survey core science systems strategy: characterizing, synthesizing, and understanding the critical zone through a modular science framework

USGS Publications Warehouse

Bristol, R. Sky; Euliss, Ned H.; Booth, Nathaniel L.; Burkardt, Nina; Diffendorfer, Jay E.; Gesch, Dean B.; McCallum, Brian E.; Miller, David M.; Morman, Suzette A.; Poore, Barbara S.; Signell, Richard P.; Viger, Roland J.

2013-01-01

Core Science Systems is a new mission of the U.S. Geological Survey (USGS) that resulted from the 2007 Science Strategy, "Facing Tomorrow's Challenges: U.S. Geological Survey Science in the Decade 2007-2017." This report describes the Core Science Systems vision and outlines a strategy to facilitate integrated characterization and understanding of the complex Earth system. The vision and suggested actions are bold and far-reaching, describing a conceptual model and framework to enhance the ability of the USGS to bring its core strengths to bear on pressing societal problems through data integration and scientific synthesis across the breadth of science. The context of this report is inspired by a direction set forth in the 2007 Science Strategy. Specifically, ecosystem-based approaches provide the underpinnings for essentially all science themes that define the USGS. Every point on Earth falls within a specific ecosystem where data, other information assets, and the expertise of USGS and its many partners can be employed to quantitatively understand how that ecosystem functions and how it responds to natural and anthropogenic disturbances. Every benefit society obtains from the planet-food, water, raw materials to build infrastructure, homes and automobiles, fuel to heat homes and cities, and many others, are derived from or affect ecosystems. The vision for Core Science Systems builds on core strengths of the USGS in characterizing and understanding complex Earth and biological systems through research, modeling, mapping, and the production of high quality data on the Nation's natural resource infrastructure. Together, these research activities provide a foundation for ecosystem-based approaches through geologic mapping, topographic mapping, and biodiversity mapping. The vision describes a framework founded on these core mapping strengths that makes it easier for USGS scientists to discover critical information, share and publish results, and identify potential collaborations that transcend all USGS missions. The framework is designed to improve the efficiency of scientific work within USGS by establishing a means to preserve and recall data for future applications, organizing existing scientific knowledge and data to facilitate new use of older information, and establishing a future workflow that naturally integrates new data, applications, and other science products to make interdisciplinary research easier and more efficient. Given the increasing need for integrated data and interdisciplinary approaches to solve modern problems, leadership by the Core Science Systems mission will facilitate problem solving by all USGS missions in ways not formerly possible. The report lays out a strategy to achieve this vision through three goals with accompanying objectives and actions. The first goal builds on and enhances the strengths of the Core Science Systems mission in characterizing and understanding the Earth system from the geologic framework to the topographic characteristics of the land surface and biodiversity across the Nation. The second goal enhances and develops new strengths in computer and information science to make it easier for USGS scientists to discover data and models, share and publish results, and discover connections between scientific information and knowledge. The third goal brings additional focus to research and development methods to address complex issues affecting society that require integration of knowledge and new methods for synthesizing scientific information. Collectively, the report lays out a strategy to create a seamless connection between all USGS activities to accelerate and make USGS science more efficient by fully integrating disciplinary expertise within a new and evolving science paradigm for a changing world in the 21st century.

Science strategy for Core Science Systems in the U.S. Geological Survey, 2013-2023

USGS Publications Warehouse

Bristol, R. Sky; Euliss, Ned H.; Booth, Nathaniel L.; Burkardt, Nina; Diffendorfer, Jay E.; Gesch, Dean B.; McCallum, Brian E.; Miller, David M.; Morman, Suzette A.; Poore, Barbara S.; Signell, Richard P.; Viger, Roland J.

2012-01-01

Core Science Systems is a new mission of the U.S. Geological Survey (USGS) that grew out of the 2007 Science Strategy, “Facing Tomorrow’s Challenges: U.S. Geological Survey Science in the Decade 2007–2017.” This report describes the vision for this USGS mission and outlines a strategy for Core Science Systems to facilitate integrated characterization and understanding of the complex earth system. The vision and suggested actions are bold and far-reaching, describing a conceptual model and framework to enhance the ability of USGS to bring its core strengths to bear on pressing societal problems through data integration and scientific synthesis across the breadth of science.The context of this report is inspired by a direction set forth in the 2007 Science Strategy. Specifically, ecosystem-based approaches provide the underpinnings for essentially all science themes that define the USGS. Every point on earth falls within a specific ecosystem where data, other information assets, and the expertise of USGS and its many partners can be employed to quantitatively understand how that ecosystem functions and how it responds to natural and anthropogenic disturbances. Every benefit society obtains from the planet—food, water, raw materials to build infrastructure, homes and automobiles, fuel to heat homes and cities, and many others, are derived from or effect ecosystems.The vision for Core Science Systems builds on core strengths of the USGS in characterizing and understanding complex earth and biological systems through research, modeling, mapping, and the production of high quality data on the nation’s natural resource infrastructure. Together, these research activities provide a foundation for ecosystem-based approaches through geologic mapping, topographic mapping, and biodiversity mapping. The vision describes a framework founded on these core mapping strengths that makes it easier for USGS scientists to discover critical information, share and publish results, and identify potential collaborations that transcend all USGS missions. The framework is designed to improve the efficiency of scientific work within USGS by establishing a means to preserve and recall data for future applications, organizing existing scientific knowledge and data to facilitate new use of older information, and establishing a future workflow that naturally integrates new data, applications, and other science products to make it easier and more efficient to conduct interdisciplinary research over time. Given the increasing need for integrated data and interdisciplinary approaches to solve modern problems, leadership by the Core Science Systems mission will facilitate problem solving by all USGS missions in ways not formerly possible.The report lays out a strategy to achieve this vision through three goals with accompanying objectives and actions. The first goal builds on and enhances the strengths of the Core Science Systems mission in characterizing and understanding the earth system from the geologic framework to the topographic characteristics of the land surface and biodiversity across the nation. The second goal enhances and develops new strengths in computer and information science to make it easier for USGS scientists to discover data and models, share and publish results, and discover connections between scientific information and knowledge. The third goal brings additional focus to research and development methods to address complex issues affecting society that require integration of knowledge and new methods for synthesizing scientific information. Collectively, the report lays out a strategy to create a seamless connection between all USGS activities to accelerate and make USGS science more efficient by fully integrating disciplinary expertise within a new and evolving science paradigm for a changing world in the 21st century.

A multi-level systems perspective for the science of team science.

PubMed

Börner, Katy; Contractor, Noshir; Falk-Krzesinski, Holly J; Fiore, Stephen M; Hall, Kara L; Keyton, Joann; Spring, Bonnie; Stokols, Daniel; Trochim, William; Uzzi, Brian

2010-09-15

This Commentary describes recent research progress and professional developments in the study of scientific teamwork, an area of inquiry termed the "science of team science" (SciTS, pronounced "sahyts"). It proposes a systems perspective that incorporates a mixed-methods approach to SciTS that is commensurate with the conceptual, methodological, and translational complexities addressed within the SciTS field. The theoretically grounded and practically useful framework is intended to integrate existing and future lines of SciTS research to facilitate the field's evolution as it addresses key challenges spanning macro, meso, and micro levels of analysis.

High rate information systems - Architectural trends in support of the interdisciplinary investigator

NASA Technical Reports Server (NTRS)

Handley, Thomas H., Jr.; Preheim, Larry E.

1990-01-01

Data systems requirements in the Earth Observing System (EOS) Space Station Freedom (SSF) eras indicate increasing data volume, increased discipline interplay, higher complexity and broader data integration and interpretation. A response to the needs of the interdisciplinary investigator is proposed, considering the increasing complexity and rising costs of scientific investigation. The EOS Data Information System, conceived to be a widely distributed system with reliable communication links between central processing and the science user community, is described. Details are provided on information architecture, system models, intelligent data management of large complex databases, and standards for archiving ancillary data, using a research library, a laboratory and collaboration services.

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.

Emerging Challenges and Opportunities for Education and Research in Weed Science

PubMed Central

Chauhan, Bhagirath S.; Matloob, Amar; Mahajan, Gulshan; Aslam, Farhena; Florentine, Singarayer K.; Jha, Prashant

2017-01-01

In modern agriculture, with more emphasis on high input systems, weed problems are likely to increase and become more complex. With heightened awareness of adverse effects of herbicide residues on human health and environment and the evolution of herbicide-resistant weed biotypes, a significant focus within weed science has now shifted to the development of eco-friendly technologies with reduced reliance on herbicides. Further, with the large-scale adoption of herbicide-resistant crops, and uncertain climatic optima under climate change, the problems for weed science have become multi-faceted. To handle these complex weed problems, a holistic line of action with multi-disciplinary approaches is required, including adjustments to technology, management practices, and legislation. Improved knowledge of weed ecology, biology, genetics, and molecular biology is essential for developing sustainable weed control practices. Additionally, judicious use of advanced technologies, such as site-specific weed management systems and decision support modeling, will play a significant role in reducing costs associated with weed control. Further, effective linkages between farmers and weed researchers will be necessary to facilitate the adoption of technological developments. To meet these challenges, priorities in research need to be determined and the education system for weed science needs to be reoriented. In respect of the latter imperative, closer collaboration between weed scientists and other disciplines can help in defining and solving the complex weed management challenges of the 21st century. This consensus will provide more versatile and diverse approaches to innovative teaching and training practices, which will be needed to prepare future weed science graduates who are capable of handling the anticipated challenges of weed science facing in contemporary agriculture. To build this capacity, mobilizing additional funding for both weed research and weed management education is essential. PMID:28928765

Emerging Challenges and Opportunities for Education and Research in Weed Science.

PubMed

Chauhan, Bhagirath S; Matloob, Amar; Mahajan, Gulshan; Aslam, Farhena; Florentine, Singarayer K; Jha, Prashant

2017-01-01

In modern agriculture, with more emphasis on high input systems, weed problems are likely to increase and become more complex. With heightened awareness of adverse effects of herbicide residues on human health and environment and the evolution of herbicide-resistant weed biotypes, a significant focus within weed science has now shifted to the development of eco-friendly technologies with reduced reliance on herbicides. Further, with the large-scale adoption of herbicide-resistant crops, and uncertain climatic optima under climate change, the problems for weed science have become multi-faceted. To handle these complex weed problems, a holistic line of action with multi-disciplinary approaches is required, including adjustments to technology, management practices, and legislation. Improved knowledge of weed ecology, biology, genetics, and molecular biology is essential for developing sustainable weed control practices. Additionally, judicious use of advanced technologies, such as site-specific weed management systems and decision support modeling, will play a significant role in reducing costs associated with weed control. Further, effective linkages between farmers and weed researchers will be necessary to facilitate the adoption of technological developments. To meet these challenges, priorities in research need to be determined and the education system for weed science needs to be reoriented. In respect of the latter imperative, closer collaboration between weed scientists and other disciplines can help in defining and solving the complex weed management challenges of the 21st century. This consensus will provide more versatile and diverse approaches to innovative teaching and training practices, which will be needed to prepare future weed science graduates who are capable of handling the anticipated challenges of weed science facing in contemporary agriculture. To build this capacity, mobilizing additional funding for both weed research and weed management education is essential.

Grip on health: A complex systems approach to transform health care.

PubMed

van Wietmarschen, Herman A; Wortelboer, Heleen M; van der Greef, Jan

2018-02-01

This article addresses the urgent need for a transition in health care to deal with the increasing prevalence of chronic diseases and associated rapid rise of health care costs. Chronic diseases evolve and are predominantly related to lifestyle and environment. A shift is needed from a reductionist repair mode of thinking, toward a more integrated biopsychosocial way of thinking about health. The aim of this article is to discuss the opportunities that complexity science offer for transforming health care toward optimal treatment and prevention of chronic lifestyle diseases. Health and health care is discussed from a complexity science perspective. The benefits of concepts developed in the field of complexity science for stimulating transitions in health care are explored. Complexity science supports the elucidation of the essence of health processes. It provides a unique perspective on health with a focus on the relationships within networks of dynamically interacting factors and the emergence of health out of the organization of those relationships. Novel types of complexity science-based intervention strategies are being developed. The first application in practice is the integrated obesity treatment program currently piloted in the Netherlands, focusing on health awareness and healing relationships. Complexity science offers various theories and methods to capture the path toward unhealthy and healthy states, facilitating the development of a dynamic integrated biopsychosocial perspective on health. This perspective offers unique insights into health processes for patients and citizens. In addition, dynamic models driven by personal data provide simulations of health processes and the ability to detect transitions between health states. Such models are essential for aligning and reconnecting the many institutions and disciplines involved in the health care sector and evolve toward an integrated health care ecosystem. © 2016 John Wiley & Sons, Ltd.

The Hydraulic Jump: Finding Complexity in Turbulent Water

ERIC Educational Resources Information Center

Vondracek, Mark

2013-01-01

Students who do not progress to more advanced science disciplines in college generally do not realize that seemingly simple physical systems are--when studied in detail--more complex than one might imagine. This article presents one such phenomenon--the hydraulic jump--as a way to help students see the complexity behind the seemingly simple, and…

Complexity-Based Learning and Teaching: A Case Study in Higher Education

ERIC Educational Resources Information Center

Fabricatore, Carlo; López, María Ximena

2014-01-01

This paper presents a learning and teaching strategy based on complexity science and explores its impacts on a higher education game design course. The strategy aimed at generating conditions fostering individual and collective learning in educational complex adaptive systems, and led the design of the course through an iterative and adaptive…

How new concepts become universal scientific approaches: insights from citation network analysis of agent-based complex systems science.

PubMed

Vincenot, Christian E

2018-03-14

Progress in understanding and managing complex systems comprised of decision-making agents, such as cells, organisms, ecosystems or societies, is-like many scientific endeavours-limited by disciplinary boundaries. These boundaries, however, are moving and can actively be made porous or even disappear. To study this process, I advanced an original bibliometric approach based on network analysis to track and understand the development of the model-based science of agent-based complex systems (ACS). I analysed research citations between the two communities devoted to ACS research, namely agent-based (ABM) and individual-based modelling (IBM). Both terms refer to the same approach, yet the former is preferred in engineering and social sciences, while the latter prevails in natural sciences. This situation provided a unique case study for grasping how a new concept evolves distinctly across scientific domains and how to foster convergence into a universal scientific approach. The present analysis based on novel hetero-citation metrics revealed the historical development of ABM and IBM, confirmed their past disjointedness, and detected their progressive merger. The separation between these synonymous disciplines had silently opposed the free flow of knowledge among ACS practitioners and thereby hindered the transfer of methodological advances and the emergence of general systems theories. A surprisingly small number of key publications sparked the ongoing fusion between ABM and IBM research. Beside reviews raising awareness of broad-spectrum issues, generic protocols for model formulation and boundary-transcending inference strategies were critical means of science integration. Accessible broad-spectrum software similarly contributed to this change. From the modelling viewpoint, the discovery of the unification of ABM and IBM demonstrates that a wide variety of systems substantiate the premise of ACS research that microscale behaviours of agents and system-level dynamics are inseparably bound. © 2018 The Author(s).

Animated computer graphics models of space and earth sciences data generated via the massively parallel processor

NASA Technical Reports Server (NTRS)

Treinish, Lloyd A.; Gough, Michael L.; Wildenhain, W. David

1987-01-01

The capability was developed of rapidly producing visual representations of large, complex, multi-dimensional space and earth sciences data sets via the implementation of computer graphics modeling techniques on the Massively Parallel Processor (MPP) by employing techniques recently developed for typically non-scientific applications. Such capabilities can provide a new and valuable tool for the understanding of complex scientific data, and a new application of parallel computing via the MPP. A prototype system with such capabilities was developed and integrated into the National Space Science Data Center's (NSSDC) Pilot Climate Data System (PCDS) data-independent environment for computer graphics data display to provide easy access to users. While developing these capabilities, several problems had to be solved independently of the actual use of the MPP, all of which are outlined.

System Definition of the James Webb Space Telescope (JWST) Integrated Science Instrument Module (ISIM)

NASA Technical Reports Server (NTRS)

Lundquist, Ray; Aymergen, Cagatay; VanCampen, Julie; Abell, James; Smith, Miles; Driggers, Phillip

2008-01-01

The Integrated Science Instrument Module (ISIM) for the James Webb Space Telescope (JWST) provides the critical functions and the environment for the four science instruments on JWST. This complex system development across many international organizations presents unique challenges and unique solutions. Here we describe how the requirement flow has been coordinated through the documentation system, how the tools and processes are used to minimize impact to the development of the affected interfaces, how the system design has matured, how the design review process operates, and how the system implementation is managed through reporting to ensure a truly world class scientific instrument compliment is created as the final product.

The Importance of Why: An Intelligence Approach for a Multi-Polar World

DTIC Science & Technology

2016-04-04

December 27, 2015). 12. 2 Jupiter Scientific, “Definitions of Important Terms in Chaos Theory ,” Jupiter Scientific website, http...Important Terms in Chaos Theory .” Linearizing a system is approximating a nonlinear system through the application of linear system model. 25...Complexity Theory to Anticipate Strategic Surprise,” 24. 16 M. Mitchell Waldrop, Complexity: The Emerging Science at the Edge of Order and Chaos (New

A science data gateway for environmental management: A SCIENCE DATA GATEWAY FOR ENVIRONMENTAL MANAGEMENT

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

Agarwal, Deborah A.; Faybishenko, Boris; Freedman, Vicky L.

Science data gateways are effective in providing complex science data collections to the world-wide user communities. In this paper we describe a gateway for the Advanced Simulation Capability for Environmental Management (ASCEM) framework. Built on top of established web service technologies, the ASCEM data gateway is specifically designed for environmental modeling applications. Its key distinguishing features include: (1) handling of complex spatiotemporal data, (2) offering a variety of selective data access mechanisms, (3) providing state of the art plotting and visualization of spatiotemporal data records, and (4) integrating seamlessly with a distributed workflow system using a RESTful interface. ASCEM projectmore » scientists have been using this data gateway since 2011.« less

A brief history of the most remarkable numbers e, i and γ in mathematical sciences with applications

NASA Astrophysics Data System (ADS)

Debnath, Lokenath

2015-08-01

This paper deals with a brief history of the most remarkable Euler numbers e, i and γ in mathematical sciences. Included are many properties of the constants e, i and γ and their applications in algebra, geometry, physics, chemistry, ecology, business and industry. Special attention is given to the growth and decay phenomena in many real-world problems including stability and instability of their solutions. Some specific and modern applications of logarithms, complex numbers and complex exponential functions to electrical circuits and mechanical systems are presented with examples. Included are the use of complex numbers and complex functions in the description and analysis of chaos and fractals with the aid of modern computer technology. In addition, the phasor method is described with examples of applications in engineering science. The major focus of this paper is to provide basic information through historical approach to mathematics teaching and learning of the fundamental knowledge and skills required for students and teachers at all levels so that they can understand the concepts of mathematics, and mathematics education in science and technology.

Putting it altogether: improving performance in heart failure outcomes, part 2.

PubMed

Clancy, Thomas R

2009-09-01

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 10th in a series of articles applying complex systems science to the traditional management concepts of planning, organizing, directing, coordinating, and controlling. As follow-up to the case study in this column's June 2009 article, this article highlights the interventions and outcomes of the study.

Mental health services conceptualised as complex adaptive systems: what can be learned?

PubMed

Ellis, Louise A; Churruca, Kate; Braithwaite, Jeffrey

2017-01-01

Despite many attempts at promoting systems integration, seamless care, and partnerships among service providers and users, mental health services internationally continue to be fragmented and piecemeal. We exploit recent ideas from complexity science to conceptualise mental health services as complex adaptive systems (CASs). The core features of CASs are described and Australia's headspace initiative is used as an example of the kinds of problems currently being faced. We argue that adopting a CAS lens can transform services, creating more connected care for service users with mental health conditions.

Brief history of patient safety culture and science.

PubMed

Ilan, Roy; Fowler, Robert

2005-03-01

The science of safety is well established in such disciplines as the automotive and aviation industry. In this brief history of safety science as it pertains to patient care, we review remote and recent publications that have guided the maturation of this field that has particular relevance to the complex structure of systems, personnel, and therapies involved in caring for the critically ill.

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.

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…

Collaboratively Architecting a Scalable and Adaptable Petascale Infrastructure to Support Transdisciplinary Scientific Research for the Australian Earth and Environmental Sciences

NASA Astrophysics Data System (ADS)

Wyborn, L. A.; Evans, B. J. K.; Pugh, T.; Lescinsky, D. T.; Foster, C.; Uhlherr, A.

2014-12-01

The National Computational Infrastructure (NCI) at the Australian National University (ANU) is a partnership between CSIRO, ANU, Bureau of Meteorology (BoM) and Geoscience Australia. Recent investments in a 1.2 PFlop Supercomputer (Raijin), ~ 20 PB data storage using Lustre filesystems and a 3000 core high performance cloud have created a hybrid platform for higher performance computing and data-intensive science to enable large scale earth and climate systems modelling and analysis. There are > 3000 users actively logging in and > 600 projects on the NCI system. Efficiently scaling and adapting data and software systems to petascale infrastructures requires the collaborative development of an architecture that is designed, programmed and operated to enable users to interactively invoke different forms of in-situ computation over complex and large scale data collections. NCI makes available major and long tail data collections from both the government and research sectors based on six themes: 1) weather, climate and earth system science model simulations, 2) marine and earth observations, 3) geosciences, 4) terrestrial ecosystems, 5) water and hydrology and 6) astronomy, bio and social. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. Collections are the operational form for data management and access. Similar data types from individual custodians are managed cohesively. Use of international standards for discovery and interoperability allow complex interactions within and between the collections. This design facilitates a transdisciplinary approach to research and enables a shift from small scale, 'stove-piped' science efforts to large scale, collaborative systems science. This new and complex infrastructure requires a move to shared, globally trusted software frameworks that can be maintained and updated. Workflow engines become essential and need to integrate provenance, versioning, traceability, repeatability and publication. There are also human resource challenges as highly skilled HPC/HPD specialists, specialist programmers, and data scientists are required whose skills can support scaling to the new paradigm of effective and efficient data-intensive earth science analytics on petascale, and soon to be exascale systems.

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

Not Available

The Boston Christian Science Center recently purchased its own packaged boiler system to provide heating and cooling steam for its building complex. The system is expected to reduce the center's energy costs by $450,000 in the first year.

Automated Derivation of Complex System Constraints from User Requirements

NASA Technical Reports Server (NTRS)

Foshee, Mark; Murey, Kim; Marsh, Angela

2010-01-01

The Payload Operations Integration Center (POIC) located at the Marshall Space Flight Center has the responsibility of integrating US payload science requirements for the International Space Station (ISS). All payload operations must request ISS system resources so that the resource usage will be included in the ISS on-board execution timelines. The scheduling of resources and building of the timeline is performed using the Consolidated Planning System (CPS). The ISS resources are quite complex due to the large number of components that must be accounted for. The planners at the POIC simplify the process for Payload Developers (PD) by providing the PDs with a application that has the basic functionality PDs need as well as list of simplified resources in the User Requirements Collection (URC) application. The planners maintained a mapping of the URC resources to the CPS resources. The process of manually converting PD's science requirements from a simplified representation to a more complex CPS representation is a time-consuming and tedious process. The goal is to provide a software solution to allow the planners to build a mapping of the complex CPS constraints to the basic URC constraints and automatically convert the PD's requirements into systems requirements during export to CPS.

Multilayer network modeling of integrated biological systems. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

De Domenico, Manlio

2018-03-01

Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several studies are highlighting how simple networks - obtained by aggregating or neglecting temporal or categorical description of biological data - are not able to account for the richness of information characterizing biological systems. More complex models, namely multilayer networks, are needed to account for interdependencies, often varying across time, of biological interacting units within a cell, a tissue or parts of an organism.

An integrated science-based methodology to assess potential risks and implications of engineered nanomaterials

EPA Science Inventory

There is an urgent need for broad and integrated studies that address the risks of engineered nanomaterials (ENMs) along the different endpoints of the society, environment, and economy (SEE) complex adaptive system. This article presents an integrated science-based methodology ...

Data systems and computer science: Software Engineering Program

NASA Technical Reports Server (NTRS)

Zygielbaum, Arthur I.

1991-01-01

An external review of the Integrated Technology Plan for the Civil Space Program is presented. This review is specifically concerned with the Software Engineering Program. The goals of the Software Engineering Program are as follows: (1) improve NASA's ability to manage development, operation, and maintenance of complex software systems; (2) decrease NASA's cost and risk in engineering complex software systems; and (3) provide technology to assure safety and reliability of software in mission critical applications.

Using RDF to Model the Structure and Process of Systems

NASA Astrophysics Data System (ADS)

Rodriguez, Marko A.; Watkins, Jennifer H.; Bollen, Johan; Gershenson, Carlos

Many systems can be described in terms of networks of discrete elements and their various relationships to one another. A semantic network, or multi-relational network, is a directed labeled graph consisting of a heterogeneous set of entities connected by a heterogeneous set of relationships. Semantic networks serve as a promising general-purpose modeling substrate for complex systems. Various standardized formats and tools are now available to support practical, large-scale semantic network models. First, the Resource Description Framework (RDF) offers a standardized semantic network data model that can be further formalized by ontology modeling languages such as RDF Schema (RDFS) and the Web Ontology Language (OWL). Second, the recent introduction of highly performant triple-stores (i.e. semantic network databases) allows semantic network models on the order of 109 edges to be efficiently stored and manipulated. RDF and its related technologies are currently used extensively in the domains of computer science, digital library science, and the biological sciences. This article will provide an introduction to RDF/RDFS/OWL and an examination of its suitability to model discrete element complex systems.

Thrust Direction Optimization: Satisfying Dawn's Attitude Agility Constraints

NASA Technical Reports Server (NTRS)

Whiffen, Gregory J.

2013-01-01

The science objective of NASA's Dawn Discovery mission is to explore the two largest members of the main asteroid belt, the giant asteroid Vesta and the dwarf planet Ceres. Dawn successfully completed its orbital mission at Vesta. The Dawn spacecraft has complex, difficult to quantify, and in some cases severe limitations on its attitude agility. The low-thrust transfers between science orbits at Vesta required very complex time varying thrust directions due to the strong and complex gravity and various science objectives. Traditional thrust design objectives (like minimum (Delta)V or minimum transfer time) often result in thrust direction time evolutions that can not be accommodated with the attitude control system available on Dawn. This paper presents several new optimal control objectives, collectively called thrust direction optimization that were developed and necessary to successfully navigate Dawn through all orbital transfers at Vesta.

Panarchy use in environmental science for risk and resilience planning

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Garmestani, Ahjond S.; Gunderson, Lance H.; Linkov, Igor

2016-01-01

Environmental sciences have an important role in informing sustainable management of built environments by providing insights about the drivers and potentially negative impacts of global environmental change. Here, we discuss panarchy theory, a multi-scale hierarchical concept that accounts for the dynamism of complex socio-ecological systems, especially for those systems with strong cross-scale feedbacks. The idea of panarchy underlies much of system resilience, focusing on how systems respond to known and unknown threats. Panarchy theory can provide a framework for qualitative and quantitative research and application in the environmental sciences, which can in turn inform the ongoing efforts in socio-technical resilience thinking and adaptive and transformative approaches to management.

Challenges of the NGSS for Future Geoscience Education

NASA Astrophysics Data System (ADS)

Wysession, M. E.; Colson, M.; Duschl, R. A.; Lopez, R. E.; Messina, P.; Speranza, P.

2013-12-01

The new Next Generation Science Standards (NGSS), which spell out a set of K-12 performance expectations for life science, physical science, and Earth and space science (ESS), pose a variety of opportunities and challenges for geoscience education. Among the changes recommended by the NGSS include establishing ESS on an equal footing with both life science and physical sciences, at the full K-12 level. This represents a departure from the traditional high school curriculum in most states. In addition, ESS is presented as a complex, integrated, interdisciplinary, quantitative Earth Systems-oriented set of sciences that includes complex and politically controversial topics such as climate change and human impacts. The geoscience communities will need to mobilize in order to assist and aid in the full implementation of ESS aspects of the NGSS in as many states as possible. In this context, the NGSS highlight Earth and space science to an unprecedented degree. If the NGSS are implemented in an optimal manner, a year of ESS will be taught in both middle and high school. In addition, because of the complexity and interconnectedness of the ESS content (with material such as climate change and human sustainability), it is recommended (Appendix K of the NGSS release) that much of it be taught following physics, chemistry, and biology. However, there are considerable challenges to a full adoption of the NGSS. A sufficient work force of high school geoscientists qualified in modern Earth Systems Science does not exist and will need to be trained. Many colleges do not credit high school geoscience as a lab science with respect to college admission. The NGSS demand curricular practices that include analyzing and interpreting real geoscience data, and these curricular modules do not yet exist. However, a concerted effort on the part of geoscience research and education organizations can help resolve these challenges.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering☆

PubMed Central

Rabitz, Herschel; Welsh, William J.; Kohn, Joachim; de Boer, Jan

2016-01-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. PMID:26876875

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.

A Science Rationale for Mobility in Planetary Environments

NASA Technical Reports Server (NTRS)

1999-01-01

For the last several decades, the Committee on Planetary and Lunar Exploration (COMPLEX) has advocated a systematic approach to exploration of the solar system; that is, the information and understanding resulting from one mission provide the scientific foundations that motivate subsequent, more elaborate investigations. COMPLEX's 1994 report, An Integrated Strategy for the Planetary Sciences: 1995-2010,1 advocated an approach to planetary studies emphasizing "hypothesizing and comprehending" rather than "cataloging and categorizing." More recently, NASA reports, including The Space Science Enterprise Strategic Plan2 and, in particular, Mission to the Solar System: Exploration and Discovery-A Mission and Technology Roadmap,3 have outlined comprehensive plans for planetary exploration during the next several decades. The missions outlined in these plans are both generally consistent with the priorities outlined in the Integrated Strategy and other NRC reports,4-5 and are replete with examples of devices embodying some degree of mobility in the form of rovers, robotic arms, and the like. Because the change in focus of planetary studies called for in the Integrated Strategy appears to require an evolutionary change in the technical means by which solar system exploration missions are conducted, the Space Studies Board charged COMPLEX to review the science that can be uniquely addressed by mobility in planetary environments. In particular, COMPLEX was asked to address the following questions: (1) What are the practical methods for achieving mobility? (2) For surface missions, what are the associated needs for sample acquisition? (3) What is the state of technology for planetary mobility in the United States and elsewhere, and what are the key requirements for technology development? (4) What terrestrial field demonstrations are required prior to spaceflight missions?

Science, Semantics, and Social Change.

ERIC Educational Resources Information Center

Lemke, J. L.

Social semiotics suggests that social and cultural formations, including the language and practice of science and the ways in which new generations and communities advance them, develop as an integral part of the evolution of social ecosystems. Some recent models of complex dynamic systems in physics, chemistry, and biology focus more on the…

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

PubMed

Karwowski, Waldemar

2012-12-01

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

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…

Teaching climate change: A 16-year record of introducing undergraduates to the fundamentals of the climate system and its complexities

NASA Astrophysics Data System (ADS)

Winckler, G.; Pfirman, S. L.; Hays, J. D.; Schlosser, P.; Ting, M.

2011-12-01

Responding to climate change challenges in the near and far future, will require a wide range of knowledge, skills and a sense of the complexities involved. Since 1995, Columbia University and Barnard College have offered an undergraduate class that strives to provide students with some of these skills. The 'Climate System' course is a component of the three-part 'Earth Environmental Systems' series and provides the fundamentals needed for understanding the Earth's climate system and its variability. Being designed both for science majors and non-science majors, the emphasis of the course is on basic physical explanations, rather than mathematical derivations of the laws that govern the climate system. The course includes lectures, labs and discussion. Laboratory exercises primarily explore the climate system using global datasets, augmented by hands-on activities. Course materials are available for public use at http://eesc.columbia.edu/courses/ees/climate/camel_modules/ and http://ncseonline.org/climate/cms.cfm?id=3783. In this presentation we discuss the experiences, challenges and future demands of conveying the science of the Earth's Climate System and the risks facing the planet to a wide spectrum of undergraduate students, many of them without a background in the sciences. Using evaluation data we reflect how the course, the students, and the faculty have evolved over the past 16 years as the earth warmed, pressures for adaptation planning and mitigation measures increased, and public discourse became increasingly polarized.

A new decision sciences for complex systems.

PubMed

Lempert, Robert J

2002-05-14

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

Promoting evaluation capacity building in a complex adaptive system.

PubMed

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

2018-04-10

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

Manifesto of computational social science

NASA Astrophysics Data System (ADS)

Conte, R.; Gilbert, N.; Bonelli, G.; Cioffi-Revilla, C.; Deffuant, G.; Kertesz, J.; Loreto, V.; Moat, S.; Nadal, J.-P.; Sanchez, A.; Nowak, A.; Flache, A.; San Miguel, M.; Helbing, D.

2012-11-01

The increasing integration of technology into our lives has created unprecedented volumes of data on society's everyday behaviour. Such data opens up exciting new opportunities to work towards a quantitative understanding of our complex social systems, within the realms of a new discipline known as Computational Social Science. Against a background of financial crises, riots and international epidemics, the urgent need for a greater comprehension of the complexity of our interconnected global society and an ability to apply such insights in policy decisions is clear. This manifesto outlines the objectives of this new scientific direction, considering the challenges involved in it, and the extensive impact on science, technology and society that the success of this endeavour is likely to bring about.

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

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

NASA Astrophysics Data System (ADS)

Piccinini, Nicola

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

When the Dog Must Talk to the Cat: Communicating Science to Politicians - or - Science and Politics: Thoughts about a Complex Relationship

NASA Astrophysics Data System (ADS)

Madsen, Claus

From a communication view, political lobbying for Science means targeted communication about a long established, well-tested, fact-based and logically robust system of inquiry to a highly dynamic environment in which decision-taking is influenced by many non-scientific factors and with norms that differ widely from the tenets of science. The paper discusses some of the communication issues that arise when these very different worlds meet.

[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.

Risk-Return Relationship in a Complex Adaptive System

PubMed Central

Song, Kunyu; An, Kenan; Yang, Guang; Huang, Jiping

2012-01-01

For survival and development, autonomous agents in complex adaptive systems involving the human society must compete against or collaborate with others for sharing limited resources or wealth, by using different methods. One method is to invest, in order to obtain payoffs with risk. It is a common belief that investments with a positive risk-return relationship (namely, high risk high return and vice versa) are dominant over those with a negative risk-return relationship (i.e., high risk low return and vice versa) in the human society; the belief has a notable impact on daily investing activities of investors. Here we investigate the risk-return relationship in a model complex adaptive system, in order to study the effect of both market efficiency and closeness that exist in the human society and play an important role in helping to establish traditional finance/economics theories. We conduct a series of computer-aided human experiments, and also perform agent-based simulations and theoretical analysis to confirm the experimental observations and reveal the underlying mechanism. We report that investments with a negative risk-return relationship have dominance over those with a positive risk-return relationship instead in such a complex adaptive systems. We formulate the dynamical process for the system's evolution, which helps to discover the different role of identical and heterogeneous preferences. This work might be valuable not only to complexity science, but also to finance and economics, to management and social science, and to physics. PMID:22479416

Risk-return relationship in a complex adaptive system.

PubMed

Song, Kunyu; An, Kenan; Yang, Guang; Huang, Jiping

2012-01-01

For survival and development, autonomous agents in complex adaptive systems involving the human society must compete against or collaborate with others for sharing limited resources or wealth, by using different methods. One method is to invest, in order to obtain payoffs with risk. It is a common belief that investments with a positive risk-return relationship (namely, high risk high return and vice versa) are dominant over those with a negative risk-return relationship (i.e., high risk low return and vice versa) in the human society; the belief has a notable impact on daily investing activities of investors. Here we investigate the risk-return relationship in a model complex adaptive system, in order to study the effect of both market efficiency and closeness that exist in the human society and play an important role in helping to establish traditional finance/economics theories. We conduct a series of computer-aided human experiments, and also perform agent-based simulations and theoretical analysis to confirm the experimental observations and reveal the underlying mechanism. We report that investments with a negative risk-return relationship have dominance over those with a positive risk-return relationship instead in such a complex adaptive systems. We formulate the dynamical process for the system's evolution, which helps to discover the different role of identical and heterogeneous preferences. This work might be valuable not only to complexity science, but also to finance and economics, to management and social science, and to physics.

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.

Thrust Direction Optimization: Satisfying Dawn's Attitude Agility Constraints

NASA Technical Reports Server (NTRS)

Whiffen, Gregory J.

2013-01-01

The science objective of NASA's Dawn Discovery mission is to explore the giant asteroid Vesta and the dwarf planet Ceres, the two largest members of the main asteroid belt. Dawn successfully completed its orbital mission at Vesta. The Dawn spacecraft has complex, difficult to quantify, and in some cases severe limitations on its attitude agility. The low-thrust transfers between science orbits at Vesta required very complex time varying thrust directions due to the strong and complex gravity and various science objectives. Traditional low-thrust design objectives (like minimum change in velocity or minimum transfer time) often result in thrust direction time evolutions that cannot be accommodated with the attitude control system available on Dawn. This paper presents several new optimal control objectives, collectively called thrust direction optimization that were developed and turned out to be essential to the successful navigation of Dawn at Vesta.

COALA-System for Visual Representation of Cryptography Algorithms

ERIC Educational Resources Information Center

Stanisavljevic, Zarko; Stanisavljevic, Jelena; Vuletic, Pavle; Jovanovic, Zoran

2014-01-01

Educational software systems have an increasingly significant presence in engineering sciences. They aim to improve students' attitudes and knowledge acquisition typically through visual representation and simulation of complex algorithms and mechanisms or hardware systems that are often not available to the educational institutions. This paper…

Fort Collins Science Center Ecosystem Dynamics Branch

USGS Publications Warehouse

Wilson, Jim; Melcher, C.; Bowen, Z.

2009-01-01

Complex natural resource issues require understanding a web of interactions among ecosystem components that are (1) interdisciplinary, encompassing physical, chemical, and biological processes; (2) spatially complex, involving movements of animals, water, and airborne materials across a range of landscapes and jurisdictions; and (3) temporally complex, occurring over days, weeks, or years, sometimes involving response lags to alteration or exhibiting large natural variation. Scientists in the Ecosystem Dynamics Branch of the U.S. Geological Survey, Fort Collins Science Center, investigate a diversity of these complex natural resource questions at the landscape and systems levels. This Fact Sheet describes the work of the Ecosystems Dynamics Branch, which is focused on energy and land use, climate change and long-term integrated assessments, herbivore-ecosystem interactions, fire and post-fire restoration, and environmental flows and river restoration.

Changing a Generation's Way of Thinking: Teaching Computational Thinking through Programming

ERIC Educational Resources Information Center

Buitrago Flórez, Francisco; Casallas, Rubby; Hernández, Marcela; Reyes, Alejandro; Restrepo, Silvia; Danies, Giovanna

2017-01-01

Computational thinking (CT) uses concepts that are essential to computing and information science to solve problems, design and evaluate complex systems, and understand human reasoning and behavior. This way of thinking has important implications in computer sciences as well as in almost every other field. Therefore, we contend that CT should be…

Supply Chain Development: Insights from Strategic Niche Management

ERIC Educational Resources Information Center

Caniels, Marjolein C. J.; Romijn, Henny A.

2008-01-01

Purpose: The purpose of this paper is to contribute to the study of supply chain design from the perspective of complex dynamic systems. Unlike extant studies that use formal simulation modelling and associated methodologies rooted in the physical sciences, it adopts a framework rooted in the social sciences, strategic niche management, which…

A Technology-Enhanced Intervention for Self-Regulated Learning in Science

ERIC Educational Resources Information Center

Berglas-Shapiro, Tali; Eylon, Bat-Sheva; Scherz, Zahava

2017-01-01

This article describes the development of a technology-enhanced self-regulated learning (Te- SRL) environment designed to foster students' SRL of complex science topics. The environment consists of three components, one of which is a specially designed computerized system that offers students a choice between different types of scaffolding and…

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…

The best of both worlds : integrating textual and visual command interfaces for Mars Rover Operations

NASA Technical Reports Server (NTRS)

Maxwell, Scott A.; Cooper, Brian; Hartman, Frank; Wright, John; Yen, Jeng; Leger, Chris

2005-01-01

A Mars rover is a complex system, and driving one is a complex endeavor. Rover driver must be intimately familiar with the hardware and software of the mobility system and of the robotic arm. They must rapidly assess threats in the terrain, then creatively combine their knowledge o f the vehicle and its environment to achieve each day's science and engineering objective.

Topics in Complexity: Dynamical Patterns in the Cyberworld

NASA Astrophysics Data System (ADS)

Qi, Hong

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

Fostering Environmental Literacy For A Changing Earth: Interactive and Participatory Outreach Programs at Biosphere 2

NASA Astrophysics Data System (ADS)

Pavao-Zuckerman, M.; Huxman, T.; Morehouse, B.

2008-12-01

Earth system and ecological sustainability problems are complex outcomes of biological, physical, social, and economic interactions. A common goal of outreach and education programs is to foster a scientifically literate community that possesses the knowledge to contribute to environmental policies and decision making. Uncertainty and variability that is both inherent in Earth system and ecological sciences can confound such goals of improved ecological literacy. Public programs provide an opportunity to engage lay-persons in the scientific method, allowing them to experience science in action and confront these uncertainties face-on. We begin with a definition of scientific literacy that expands its conceptualization of science beyond just a collection of facts and concepts to one that views science as a process to aid understanding of natural phenomena. A process-based scientific literacy allows the public, teachers, and students to assimilate new information, evaluate climate research, and to ultimately make decisions that are informed by science. The Biosphere 2 facility (B2) is uniquely suited for such outreach programs because it allows linking Earth system and ecological science research activities in a large scale controlled environment setting with outreach and education opportunities. A primary outreach goal is to demonstrate science in action to an audience that ranges from K-12 groups to retired citizens. Here we discuss approaches to outreach programs that focus on soil-water-atmosphere-plant interactions and their roles in the impacts and causes of global environmental change. We describe a suite of programs designed to vary the amount of participation a visitor has with the science process (from passive learning to data collection to helping design experiments) to test the hypothesis that active learning fosters increased scientific literacy and the creation of science advocates. We argue that a revised framing of the scientific method with a more open role for citizens in science will have greater success in fostering science literacy and produce a citizenry that is equipped to tackle complex environmental decision making.

Thermal Control Technologies for Complex Spacecraft

NASA Technical Reports Server (NTRS)

Swanson, Theodore D.

2004-01-01

Thermal control is a generic need for all spacecraft. In response to ever more demanding science and exploration requirements, spacecraft are becoming ever more complex, and hence their thermal control systems must evolve. This paper briefly discusses the process of technology development, the state-of-the-art in thermal control, recent experiences with on-orbit two-phase systems, and the emerging thermal control technologies to meet these evolving needs. Some "lessons learned" based on experience with on-orbit systems are also presented.

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

Dress, W.B.

Rosen's modeling relation is embedded in Popper's three worlds to provide an heuristic tool for model building and a guide for thinking about complex systems. The utility of this construct is demonstrated by suggesting a solution to the problem of pseudo science and a resolution of the famous Bohr-Einstein debates. A theory of bizarre systems is presented by an analogy with entangled particles of quantum mechanics. This theory underscores the poverty of present-day computational systems (e.g., computers) for creating complex and bizarre entities by distinguishing between mechanism and organism.

Research on application of intelligent computation based LUCC model in urbanization process

NASA Astrophysics Data System (ADS)

Chen, Zemin

2007-06-01

Global change study is an interdisciplinary and comprehensive research activity with international cooperation, arising in 1980s, with the largest scopes. The interaction between land use and cover change, as a research field with the crossing of natural science and social science, has become one of core subjects of global change study as well as the front edge and hot point of it. It is necessary to develop research on land use and cover change in urbanization process and build an analog model of urbanization to carry out description, simulation and analysis on dynamic behaviors in urban development change as well as to understand basic characteristics and rules of urbanization process. This has positive practical and theoretical significance for formulating urban and regional sustainable development strategy. The effect of urbanization on land use and cover change is mainly embodied in the change of quantity structure and space structure of urban space, and LUCC model in urbanization process has been an important research subject of urban geography and urban planning. In this paper, based upon previous research achievements, the writer systematically analyzes the research on land use/cover change in urbanization process with the theories of complexity science research and intelligent computation; builds a model for simulating and forecasting dynamic evolution of urban land use and cover change, on the basis of cellular automation model of complexity science research method and multi-agent theory; expands Markov model, traditional CA model and Agent model, introduces complexity science research theory and intelligent computation theory into LUCC research model to build intelligent computation-based LUCC model for analog research on land use and cover change in urbanization research, and performs case research. The concrete contents are as follows: 1. Complexity of LUCC research in urbanization process. Analyze urbanization process in combination with the contents of complexity science research and the conception of complexity feature to reveal the complexity features of LUCC research in urbanization process. Urban space system is a complex economic and cultural phenomenon as well as a social process, is the comprehensive characterization of urban society, economy and culture, and is a complex space system formed by society, economy and nature. It has dissipative structure characteristics, such as opening, dynamics, self-organization, non-balance etc. Traditional model cannot simulate these social, economic and natural driving forces of LUCC including main feedback relation from LUCC to driving force. 2. Establishment of Markov extended model of LUCC analog research in urbanization process. Firstly, use traditional LUCC research model to compute change speed of regional land use through calculating dynamic degree, exploitation degree and consumption degree of land use; use the theory of fuzzy set to rewrite the traditional Markov model, establish structure transfer matrix of land use, forecast and analyze dynamic change and development trend of land use, and present noticeable problems and corresponding measures in urbanization process according to research results. 3. Application of intelligent computation research and complexity science research method in LUCC analog model in urbanization process. On the basis of detailed elaboration of the theory and the model of LUCC research in urbanization process, analyze the problems of existing model used in LUCC research (namely, difficult to resolve many complexity phenomena in complex urban space system), discuss possible structure realization forms of LUCC analog research in combination with the theories of intelligent computation and complexity science research. Perform application analysis on BP artificial neural network and genetic algorithms of intelligent computation and CA model and MAS technology of complexity science research, discuss their theoretical origins and their own characteristics in detail, elaborate the feasibility of them in LUCC analog research, and bring forward improvement methods and measures on existing problems of this kind of model. 4. Establishment of LUCC analog model in urbanization process based on theories of intelligent computation and complexity science. Based on the research on abovementioned BP artificial neural network, genetic algorithms, CA model and multi-agent technology, put forward improvement methods and application assumption towards their expansion on geography, build LUCC analog model in urbanization process based on CA model and Agent model, realize the combination of learning mechanism of BP artificial neural network and fuzzy logic reasoning, express the regulation with explicit formula, and amend the initial regulation through self study; optimize network structure of LUCC analog model and methods and procedures of model parameters with genetic algorithms. In this paper, I introduce research theory and methods of complexity science into LUCC analog research and presents LUCC analog model based upon CA model and MAS theory. Meanwhile, I carry out corresponding expansion on traditional Markov model and introduce the theory of fuzzy set into data screening and parameter amendment of improved model to improve the accuracy and feasibility of Markov model in the research on land use/cover change.

A COTS-Based Attitude Dependent Contact Scheduling System

NASA Technical Reports Server (NTRS)

DeGumbia, Jonathan D.; Stezelberger, Shane T.; Woodard, Mark

2006-01-01

The mission architecture of the Gamma-ray Large Area Space Telescope (GLAST) requires a sophisticated ground system component for scheduling the downlink of science data. Contacts between the ````````````````` satellite and the Tracking and Data Relay Satellite System (TDRSS) are restricted by the limited field-of-view of the science data downlink antenna. In addition, contacts must be scheduled when permitted by the satellite s complex and non-repeating attitude profile. Complicating the matter further, the long lead-time required to schedule TDRSS services, combined with the short duration of the downlink contact opportunities, mandates accurate GLAST orbit and attitude modeling. These circumstances require the development of a scheduling system that is capable of predictively and accurately modeling not only the orbital position of GLAST but also its attitude. This paper details the methods used in the design of a Commercial Off The Shelf (COTS)-based attitude-dependent. TDRSS contact Scheduling system that meets the unique scheduling requirements of the GLAST mission, and it suggests a COTS-based scheduling approach to support future missions. The scheduling system applies filtering and smoothing algorithms to telemetered GPS data to produce high-accuracy predictive GLAST orbit ephemerides. Next, bus pointing commands from the GLAST Science Support Center are used to model the complexities of the two dynamic science gathering attitude modes. Attitude-dependent view periods are then generated between GLAST and each of the supporting TDRSs. Numerous scheduling constraints are then applied to account for various mission specific resource limitations. Next, an optimization engine is used to produce an optimized TDRSS contact schedule request which is sent to TDRSS scheduling for confirmation. Lastly, the confirmed TDRSS contact schedule is rectified with an updated ephemeris and adjusted bus pointing commands to produce a final science downlink contact schedule.

Integration science and distributed networks

NASA Astrophysics Data System (ADS)

Landauer, Christopher; Bellman, Kirstie L.

2002-07-01

Our work on integration of data and knowledge sources is based in a common theoretical treatment of 'Integration Science', which leads to systematic processes for combining formal logical and mathematical systems, computational and physical systems, and human systems and organizations. The theory is based on the processing of explicit meta-knowledge about the roles played by the different knowledge sources and the methods of analysis and semantic implications of the different data values, together with information about the context in which and the purpose for which they are being combined. The research treatment is primarily mathematical, and though this kind of integration mathematics is still under development, there are some applicable common threads that have emerged already. Instead of describing the current state of the mathematical investigations, since they are not yet crystallized enough for formalisms, we describe our applications of the approach in several different areas, including our focus area of 'Constructed Complex Systems', which are complex heterogeneous systems managed or mediated by computing systems. In this context, it is important to remember that all systems are embedded, all systems are autonomous, and that all systems are distributed networks.

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

Panarchy use in environmental science for risk and resilience ...

EPA Pesticide Factsheets

Environmental sciences have an important role in informing sustainable management of built environments by providing insights about the drivers and potentially negative impacts of global environmental change. Here, we discuss panarchy theory, a multi-scale hierarchical concept that accounts for the dynamism of complex socio-ecological systems, especially for those systems with strong cross-scale feedbacks. The idea of panarchy underlies much of system resilience, focusing on how systems respond to known and unknown threats. Panarchy theory can provide a framework for qualitative and quantitative research and application in the environmental sciences, which can in turn inform the ongoing efforts in socio-technical resilience thinking and adaptive and transformative approaches to management. The environmental sciences strive for understanding, mitigating and reversing the negative impacts of global environmental change, including chemical pollution, to maintain sustainability options for the future, and therefore play an important role for informing management.

Understanding Life : The Evolutionary Dynamics of Complexity and Semiosis

NASA Astrophysics Data System (ADS)

Loeckenhoff, Helmut K.

2010-11-01

Post-Renaissance sciences created different cultures. To establish an epistemological base, Physics were separated from the Mental domain. Consciousness was excluded from science. Life Sciences were left in between e.g. LaMettrie's `man—machine' (1748) and 'vitalism' [e.g. Bergson 4]. Causative thinking versus intuitive arguing limited strictly comprehensive concepts. First ethology established a potential shared base for science, proclaiming the `biology paradigm' in the middle of the 20th century. Initially procured by Cybernetics and Systems sciences, `constructivist' models prepared a new view on human perception and thus also of scientific `objectivity when introducing the `observer'. In sequel Computer sciences triggered the ICT revolution. In turn ICT helped to develop Chaos and Complexity sciences, Non-linear Mathematics and its spin-offs in the formal sciences [Spencer-Brown 49] as e.g. (proto-)logics. Models of life systems, as e.g. Anticipatory Systems, integrated epistemology with mathematics and Anticipatory Computing [Dubois 11, 12, 13, 14] connecting them with Semiotics. Seminal ideas laid in the turn of the 19th to the 20th century [J. v. Uexküll 53] detected the co-action and co-evolvement of environments and life systems. Bio-Semiotics ascribed purpose, intent and meaning as essential qualities of life. The concepts of Systems Biology and Qualitative Research enriched and develop also anthropologies and humanities. Brain research added models of (higher) consciousness. An avant-garde is contemplating a science including consciousness as one additional base. New insights from the extended qualitative approach led to re-conciliation of basic assumptions of scientific inquiry, creating the `epistemological turn'. Paradigmatically, resting on macro- micro- and recently on nano-biology, evolution biology sired fresh scripts of evolution [W. Wieser 60,61]. Its results tie to hypotheses describing the emergence of language, of the human mind and of culture [e.g. R. Logan 34]. The different but related approaches are yet but loosely connected. Recent efforts search for a shared foundation e.g. in a set of Transdisciplinary base models [Loeckenhoff 30, 31]. The domain of pure mental constructions as ideologies/religions and spiritual phenomena will be implied.

Water Conservation and Hydrological Transitions in Cities

NASA Astrophysics Data System (ADS)

Hornberger, G. M.; Gilligan, J. M.; Hess, D. J.

2014-12-01

A 2012 report by the National Research Council, Challenges and Opportunities in the Hydrologic Sciences, called for the development of "translational hydrologic science." Translational research in this context requires knowledge about the communication of science to decision makers and to the public but also improved understanding of the public by the scientists. This kind of knowledge is inherently interdisciplinary because it requires understanding of the complex sociotechnical dimensions of water, policy, and user relations. It is axiomatic that good governance of water resources and water infrastructure requires information about water resources themselves and about the institutions that govern water use. This "socio-hydrologic" or "hydrosociological" knowledge is often characterized by complex dynamics between and among human and natural systems. Water Resources Research has provided a forum for presentation of interdisciplinary research in coupled natural-human systems since its inception 50 years ago. The evolution of ideas presented in the journal provides a basis for framing new work, an example of which is water conservation in cities. In particular, we explore the complex interactions of political, sociodemographic, economic, and hydroclimatological factors in affecting decisions that either advance or retard the development of water conservation policies.

Advanced Kalman Filter for Real-Time Responsiveness in Complex Systems

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

Welch, Gregory Francis; Zhang, Jinghe

2014-06-10

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

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.

Self-reference and predictive, normative and prescriptive approaches in applications of systems thinking in social sciences—(Survey)

NASA Astrophysics Data System (ADS)

Mesjasz, Czesław

2000-05-01

Cybernetics, systems thinking or systems theory, have been viewed as instruments of enhancing predictive, normative and prescriptive capabilities of the social sciences, beginning from microscale-management and ending with various reference to the global system. Descriptions, explanations and predictions achieved thanks to various systems ideas were also viewed as supportive for potential governance of social phenomena. The main aim of the paper is to examine what could be the possible applications of modern systems thinking in predictive, normative and prescriptive approaches in modern social sciences, beginning from management theory and ending with global studies. Attention is paid not only to "classical" mathematical systems models but also to the role of predictive, normative and prescriptive interpretations of analogies and metaphors associated with application of the classical ("first order cybernetics") and modern ("second order cybernetics", "complexity theory") systems thinking in social sciences.

Questions regarding the predictive value of one evolved complex adaptive system for a second: exemplified by the SOD1 mouse.

PubMed

Greek, Ray; Hansen, Lawrence A

2013-11-01

We surveyed the scientific literature regarding amyotrophic lateral sclerosis, the SOD1 mouse model, complex adaptive systems, evolution, drug development, animal models, and philosophy of science in an attempt to analyze the SOD1 mouse model of amyotrophic lateral sclerosis in the context of evolved complex adaptive systems. Humans and animals are examples of evolved complex adaptive systems. It is difficult to predict the outcome from perturbations to such systems because of the characteristics of complex systems. Modeling even one complex adaptive system in order to predict outcomes from perturbations is difficult. Predicting outcomes to one evolved complex adaptive system based on outcomes from a second, especially when the perturbation occurs at higher levels of organization, is even more problematic. Using animal models to predict human outcomes to perturbations such as disease and drugs should have a very low predictive value. We present empirical evidence confirming this and suggest a theory to explain this phenomenon. We analyze the SOD1 mouse model of amyotrophic lateral sclerosis in order to illustrate this position. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Statistical mechanics of complex neural systems and high dimensional data

NASA Astrophysics Data System (ADS)

Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

2013-03-01

Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks.

Precision medicine: Towards complexity science age.

PubMed

Yuan, Bing

2016-04-01

Precision medicine (PM) refers to the tailoring of the prevention and treatment strategies to the individual characteristics of each patient. Following the vigorous advocacy of the U.S. President Obama and China's President Xi, PM has now become a hot topic of common concern worldwide. PM does not merely refer to the skill set level but rather a comprehensive medical methodology. Hence, there is PM that builds on the analytical methodology of Western medical system as well as PM that builds on Chinese medicine (CM). The differences between the two systems, fundamentally speaking, are the differences in methodology to describe the body constitution that based on reductionism and holism. Today, as science advances to complex systems, the mainstream analytical reductionism advances to the holistic synthesis era, it is imperative to introduce CM's holistic body constitution to the modern medical system in order to progress to PM. PM with its foundation on holistic body constitution, is a medical system that integrates Western medicine and CM, is the highest attainment of "PM" in the future.

Watershed System Model: The Essentials to Model Complex Human-Nature System at the River Basin Scale

NASA Astrophysics Data System (ADS)

Li, Xin; Cheng, Guodong; Lin, Hui; Cai, Ximing; Fang, Miao; Ge, Yingchun; Hu, Xiaoli; Chen, Min; Li, Weiyue

2018-03-01

Watershed system models are urgently needed to understand complex watershed systems and to support integrated river basin management. Early watershed modeling efforts focused on the representation of hydrologic processes, while the next-generation watershed models should represent the coevolution of the water-land-air-plant-human nexus in a watershed and provide capability of decision-making support. We propose a new modeling framework and discuss the know-how approach to incorporate emerging knowledge into integrated models through data exchange interfaces. We argue that the modeling environment is a useful tool to enable effective model integration, as well as create domain-specific models of river basin systems. The grand challenges in developing next-generation watershed system models include but are not limited to providing an overarching framework for linking natural and social sciences, building a scientifically based decision support system, quantifying and controlling uncertainties, and taking advantage of new technologies and new findings in the various disciplines of watershed science. The eventual goal is to build transdisciplinary, scientifically sound, and scale-explicit watershed system models that are to be codesigned by multidisciplinary communities.

Complex Physical, Biophysical and Econophysical Systems

NASA Astrophysics Data System (ADS)

Dewar, Robert L.; Detering, Frank

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

Is management still a science?

PubMed

Freedman, D H

1992-01-01

New technologies are transforming products, markets, and entire industries. Yet the more science and technology reshape the essence of business, the less useful the concept of management itself as a science seems to be. On reflection, this paradox is not so surprising. The traditional scientific approach to management promised to provide managers with the capacity to analyze, predict, and control the behavior of the complex organizations they led. But the world most managers currently inhabit often appears to be unpredictable, uncertain, and even uncontrollable. In the face of this more volatile business environment, the old-style mechanisms of "scientific management" seem positively counterproductive. And science itself appears less and less relevant to the practical concerns of managers. In this article, science journalist David Freedman argues that the problem lies less in the shortcomings of a scientific approach to management than in managers' understanding of science. What most managers think of as scientific management is based on a conception of science that few current scientists would defend. What's more, just as managers have become more preoccupied with the volatility of the business environment, scientists have also become preoccupied with the inherent volatility--the "chaos" and "complexity"--of nature. They are developing new rules for complex behavior in physical systems that have intriguing parallels to the kind of organizational behaviors companies are trying to encourage. In fact, science, long esteemed by business as a source of technological innovation, may ultimately prove of greatest value to managers as a source of something else: useful ways of looking at the world.

The Teaching of Creativity in Information Systems Programmes at South African Higher Education Institutions

ERIC Educational Resources Information Center

Turpin, Marita; Matthee, Machdel; Kruger, Anine

2015-01-01

The development of problem solving skills is a shared goal in science, engineering, mathematics and technology education. In the applied sciences, problems are often open-ended and complex, requiring a multidisciplinary approach as well as new designs. In such cases, problem solving requires not only analytical capabilities, but also creativity…

Narrative and Chaos Acknowledging the Novelty of Lives-in-Time

ERIC Educational Resources Information Center

Randall, William L.

2007-01-01

In this paper I propose that interest in "narrative" within the human sciences is comparable to interest in "chaos" within the natural sciences. In their respective ways, theories on narrative and theories on chaos are aimed at appreciating the dynamics of complex, multi-dimensional systems which otherwise resist our attempts to predict, measure,…

"I'm the Same Teacher": The Attitudes of Science and Computer Literacy Teachers Regarding Integrating ICT in Instruction to Advance Meaningful Learning

ERIC Educational Resources Information Center

Steiner, Dasi; Mendelovitch, Miriam

2017-01-01

The communications revolution reaches all sectors of the population and makes information accessible to all. This development presents complex challenges which require changes in the education system, teaching methods and learning environment. The integration of ICT (Information and Communications Technology) and science teaching requires…

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.

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...

DCL System Using Deep Learning Approaches for Land-Based or Ship-Based Real Time Recognition and Localization of Marine Mammals

DTIC Science & Technology

2015-09-30

Clark (2014), "Using High Performance Computing to Explore Large Complex Bioacoustic Soundscapes : Case Study for Right Whale Acoustics," Procedia...34Using High Performance Computing to Explore Large Complex Bioacoustic Soundscapes : Case Study for Right Whale Acoustics," Procedia Computer Science 20

Complex Systems Education for natural Hazards and from down to up Pushing of Government and Officials: A Case Study

NASA Astrophysics Data System (ADS)

Zvelebil, J.

2009-04-01

There is no point to discuss necessity of knowledge of Complex System or Nonlinear Science sensu lato at all education levels and practical decision making. Author feels that fulfilling of this strategic task needs to apply three tactics. However, each of them possesses different urgency. The highest priority has extensive education of new alternative paradigm for students. The reason is, study of Natural Science is highly fragmented into too one-theme-narrowly aimed specializations at Czech Universities. Common introductions into general methodology of science are unfortunately old fashioned, if any. They stress regular, reductionist, and time-less paradigm of classical physics without any alternatives, even the one of quantum theory by statistical physics. According former, our world is full of passive, simple, material items, which are being displaced, dragged, and changed (reversibly) by outer forces. Their interplays gradually, reaching one-by one higher levels of causal organization - all levels with the same types of canonical description, finally form the visible macro-reality. This view is in direct contradiction with student's personal experience. They see their World full of self-sustaining items actively using to that their own, inner intrinsic mechanisms. From molecules up, they are not simple things. In contrary, they are highly organized, and are even further organizing themselves into higher complexes by rich mutual interactions. In biology, those items are even caring-about-themselves entities, which actively survey and manipulate their outer environment to gain energy to increase their organization. Moreover, unhappy students are facing common view there is no "hard science" without being able to reduce results of their scientific work into a few mathematical equations, by which the observed "fata morgana" is reduced into "really scientific" description by "basic rules of Nature", which, hidden behind the scene, are causes of all the observed interplays of highly organized entities. Of course, such efforts mainly fail due to existence of qualitative differences between description of the same phenomena on different time-space scales or functional levels. Main features of a basic course "Application of nonlinear dynamics and Theory of Complex Systems for Physical Geographers" are described. They also partially follow the course reader's opinion about necessity of new reunion of modern philosophy and methodology of natural and human sciences Dangerous distortion of reflections of reality by the frequently proposed substitution of human science methodology by the natural science one is stressed. On the contrary, examples from philosophy (Bergson 1919, Wittgenstein 1953), which had anticipated and even defined some profound themes of Complex Systems (e.g. Kauffman 1993), as e.g. self-organizing, entropy decreasing behavior, or existence of discontinuities between description of the same phenomena on different time-space scales or functional levels. The second priority has information dissemination for decisions makers of natural Hazards management. Any successful Case history is better then ten popular lectures for those decision makers. A case history of highly computerized Integrated Information System (IIS) for unstable rock slope monitoring, on-line rock fall precursors diagnostics of time series and automated early warning launching, the both with the use of predominantly nonlinear tools is outlined. It stands to support author's opinion that pushing of officials is effective only if it is provided from down to up. That means it is based on satisfactory solution of specific community needs, instead of from up to down flowing more or less general directives of some far away sitting clerks. The third tactical item is rather long-distance run. Change of paradigm cannot be ordered, it is matter of generation change, as on scientific, as well as on decision makers (hopefully recruited from students already aware of Complex Systems Theory). Acknowledgement: The study was supported by T110190504 Project of Academy of Sciences of Czech Republic, by MSN 00216 20831 Project of Ministry of Education, Youth and Sports of Czech Republic, and by IPL -M121 Project of ICL.

Fractal and multifractal models for extreme bursts in space plasmas.

NASA Astrophysics Data System (ADS)

Watkins, Nicholas; Chapman, Sandra; Credgington, Dan; Rosenberg, Sam; Sanchez, Raul

2010-05-01

Space plasmas may be said to show at least two types of "universality". One type arises from the fact that plasma physics underpins all astrophysical systems, while another arises from the generic properties of coupled nonlinear physical systems, a branch of the emerging science of complexity. Much work in complexity science is contributing to the physical understanding of the ways by which complex interactions in such systems cause driven or random perturbations to be nonlinearly amplified in amplitude and/or spread out over a wide range of frequencies. These mechanisms lead to non-Gaussian fluctuations and long-ranged temporal memory (referred to by Mandelbrot as the "Noah" and "Joseph" effects, respectively). This poster discusses a standard toy model (linear fractional stable motion, LFSM) which combines the Noah and Joseph effects in a controllable way. I will describe how LFSM is being used to explore the interplay of the above two effects in the distribution of bursts above thresholds, with applications to extreme events in space time series. I will describe ongoing work to improve the accuracy of maximum likelihood-based estimation of burst size and waiting time distributions for LFSM first reported in Watkins et al [Space Science Review, 2005; PRE, 2009]. The relevance of turbulent cascades to space plasmas necessitates comparison between this model and multifractal models, and early results will be described [Watkins et al, PRL comment, 2009].

A network engineering perspective on probing and perturbing cognition with neurofeedback.

PubMed

Bassett, Danielle S; Khambhati, Ankit N

2017-05-01

Network science and engineering provide a flexible and generalizable tool set to describe and manipulate complex systems characterized by heterogeneous interaction patterns among component parts. While classically applied to social systems, these tools have recently proven to be particularly useful in the study of the brain. In this review, we describe the nascent use of these tools to understand human cognition, and we discuss their utility in informing the meaningful and predictable perturbation of cognition in combination with the emerging capabilities of neurofeedback. To blend these disparate strands of research, we build on emerging conceptualizations of how the brain functions (as a complex network) and how we can develop and target interventions or modulations (as a form of network control). We close with an outline of current frontiers that bridge neurofeedback, connectomics, and network control theory to better understand human cognition. © 2017 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals Inc. on behalf of The New York Academy of Sciences.

Modeling for Integrated Science Management and Resilient Systems Development

NASA Technical Reports Server (NTRS)

Shelhamer, M.; Mindock, J.; Lumpkins, S.

2014-01-01

Many physiological, environmental, and operational risks exist for crewmembers during spaceflight. An understanding of these risks from an integrated perspective is required to provide effective and efficient mitigations during future exploration missions that typically have stringent limitations on resources available, such as mass, power, and crew time. The Human Research Program (HRP) is in the early stages of developing collaborative modeling approaches for the purposes of managing its science portfolio in an integrated manner to support cross-disciplinary risk mitigation strategies and to enable resilient human and engineered systems in the spaceflight environment. In this talk, we will share ideas being explored from fields such as network science, complexity theory, and system-of-systems modeling. Initial work on tools to support these explorations will be discussed briefly, along with ideas for future efforts.

Looking Down on the Earth: How Satellites Have Revolutionized Our Understanding of Our Home Planet

NASA Astrophysics Data System (ADS)

Freilich, Michael

2017-04-01

Earth is a complex, dynamic system we do not yet fully understand. The Earth system, like the human body, comprises diverse components that interact in complex ways. We need to understand the Earth's atmosphere, lithosphere, hydrosphere, cryosphere, and biosphere as a single connected system. Our planet is changing on all spatial and temporal scales. This presentation will highlight how satellite observations are revolutionizing our understanding of and its response to natural or human-induced changes, and to improve prediction of climate, weather, and natural hazards. Bio: MICHAEL H. FREILICH, Director of the Earth Science Division, Science Mission Directorate at NASA Headquarters. Prior to NASA, he was a Professor and Associate Dean in the College of Oceanic and Atmospheric Sciences at Oregon State University. He received Ph.D. in Oceanography from Scripps Institution of Oceanography (Univ. of CA., San Diego) in 1982. Dr. Freilich's research focuses on the determination, validation, and geophysical analysis of ocean surface wind velocity measured by satellite-borne microwave radar and radiometer instruments. He has developed scatterometer and altimeter wind model functions, as well as innovative validation techniques for accurately quantifying the accuracy of spaceborne environmental measurements. Dr. Freilich has served on many NASA, National Research Council (NRC), and research community advisory and steering groups, including the WOCE Science Steering Committee, the NASA EOS Science Executive Committee, the NRC Ocean Studies Board, and several NASA data system review committees. Freilich's non-scientific passions include nature photography and soccer refereeing at the youth, high school, and adult levels.

Looking Down on the Earth: How Satellites Have Revolutionized Our Understanding of Our Home Planet

NASA Astrophysics Data System (ADS)

Freilich, Michael

2016-04-01

Earth is a complex, dynamic system we do not yet fully understand. The Earth system, like the human body, comprises diverse components that interact in complex ways. We need to understand the Earth's atmosphere, lithosphere, hydrosphere, cryosphere, and biosphere as a single connected system. Our planet is changing on all spatial and temporal scales. This presentation will highlight how satellite observations are revolutionizing our understanding of and its response to natural or human-induced changes, and to improve prediction of climate, weather, and natural hazards. Bio: MICHAEL H. FREILICH, Director of the Earth Science Division, Science Mission Directorate at NASA Headquarters. Prior to NASA, he was a Professor and Associate Dean in the College of Oceanic and Atmospheric Sciences at Oregon State University. He received Ph.D. in Oceanography from Scripps Institution of Oceanography (Univ. of CA., San Diego) in 1982. Dr. Freilich's research focuses on the determination, validation, and geophysical analysis of ocean surface wind velocity measured by satellite-borne microwave radar and radiometer instruments. He has developed scatterometer and altimeter wind model functions, as well as innovative validation techniques for accurately quantifying the accuracy of spaceborne environmental measurements. Dr. Freilich has served on many NASA, National Research Council (NRC), and research community advisory and steering groups, including the WOCE Science Steering Committee, the NASA EOS Science Executive Committee, the NRC Ocean Studies Board, and several NASA data system review committees. Freilich's non-scientific passions include nature photography and soccer refereeing at the youth, high school, and adult levels.

Forecasting Effects of Influence Operations: A Generative Social Science Methodology

DTIC Science & Technology

2012-03-22

that can be made in a turn (commAttempts). Two forms of this agent are used in this case study : a pamphlet distributor and an internet campaigner. The...model Echo (1995). Echo captures the behavior of complex adaptive systems by using a digital analogue to genetics. As agents replicate, “child...Sugarscape model demonstrated a new paradigm for the study of the social sciences using ABM, which they call generative social science (GSS). In

The Home Stretch Almost! Science with the Hubble and James Webb Space Telescope V

NASA Technical Reports Server (NTRS)

Ochs, Bill

2017-01-01

JWST has Made tremendous progress in the last few years. JWST Is fully immersed in integration and test, but testing JWST is a formable challenge. JWST's size, complexity, and cryogenic characteristics require a multifaceted test plan to verify mission readiness. Each of these tests are opportunities to uncover issues which must be corrected to be able to move forward. All observatory control, science planning, and science data processing operational systems are on schedule.?

A Systems Perspective on Responses to Climate Change

EPA Science Inventory

The science of climate change integrates many scientific fields to explain and predict the complex effects of greenhouse gas concentrations on the planet’s energy balance, weather patterns, and ecosystems as well as economic and social systems. A changing climate requires respons...

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...

Proteomics and Systems Biology: Current and Future Applications in the Nutritional Sciences1

PubMed Central

Moore, J. Bernadette; Weeks, Mark E.

2011-01-01

In the last decade, advances in genomics, proteomics, and metabolomics have yielded large-scale datasets that have driven an interest in global analyses, with the objective of understanding biological systems as a whole. Systems biology integrates computational modeling and experimental biology to predict and characterize the dynamic properties of biological systems, which are viewed as complex signaling networks. Whereas the systems analysis of disease-perturbed networks holds promise for identification of drug targets for therapy, equally the identified critical network nodes may be targeted through nutritional intervention in either a preventative or therapeutic fashion. As such, in the context of the nutritional sciences, it is envisioned that systems analysis of normal and nutrient-perturbed signaling networks in combination with knowledge of underlying genetic polymorphisms will lead to a future in which the health of individuals will be improved through predictive and preventative nutrition. Although high-throughput transcriptomic microarray data were initially most readily available and amenable to systems analysis, recent technological and methodological advances in MS have contributed to a linear increase in proteomic investigations. It is now commonplace for combined proteomic technologies to generate complex, multi-faceted datasets, and these will be the keystone of future systems biology research. This review will define systems biology, outline current proteomic methodologies, highlight successful applications of proteomics in nutrition research, and discuss the challenges for future applications of systems biology approaches in the nutritional sciences. PMID:22332076

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.

A Multi-Level Systems Perspective for the Science of Team Science

PubMed Central

Börner, Katy; Contractor, Noshir; Falk-Krzesinski, Holly J.; Fiore, Stephen M.; Hall, Kara L.; Keyton, Joann; Spring, Bonnie; Stokols, Daniel; Trochim, William; Uzzi, Brian

2012-01-01

This Commentary describes recent research progress and professional developments in the study of scientific teamwork, an area of inquiry termed the “science of team science” (SciTS, pronounced “sahyts”). It proposes a systems perspective that incorporates a mixed-methods approach to SciTS that is commensurate with the conceptual, methodological, and translational complexities addressed within the SciTS field. The theoretically grounded and practically useful framework is intended to integrate existing and future lines of SciTS research to facilitate the field’s evolution as it addresses key challenges spanning macro, meso, and micro levels of analysis. PMID:20844283

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik; Marwan, Norbert; Dijkstra, Henk; Kurths, Jürgen

2016-04-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology. pyunicorn is available online at https://github.com/pik-copan/pyunicorn. Reference: J.F. Donges, J. Heitzig, B. Beronov, M. Wiedermann, J. Runge, Q.-Y. Feng, L. Tupikina, V. Stolbova, R.V. Donner, N. Marwan, H.A. Dijkstra, and J. Kurths, Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Chaos 25, 113101 (2015), DOI: 10.1063/1.4934554, Preprint: arxiv.org:1507.01571 [physics.data-an].

Bringing Data Science, Xinformatics and Semantic eScience into the Graduate Curriculum

NASA Astrophysics Data System (ADS)

Fox, P.

2012-04-01

Recent advances in acquisition techniques quickly provide massive amount of complex data characterized by source heterogeneity, multiple modalities, high volume, high dimensionality, and multiple scales (temporal, spatial, and function). In turn, science and engineering disciplines are rapidly becoming more and more data driven with goals of higher sample throughput, better understanding/modeling of complex systems and their dynamics, and ultimately engineering products for practical applications. However, analyzing libraries of complex data requires managing its complexity and integrating the information and knowledge across multiple scales over different disciplines. Attention to Data Science is now ubiquitous - The Fourth Paradigm publication, Nature and Science special issues on Data, and explicit emphasis on Data in national and international agency programs, foundations (Keck, Moore) and corporations (IBM, GE, Microsoft, etc.). Surrounding this attention is a proliferation of studies, reports, conferences and workshops on Data, Data Science and workforce. Examples include: "Train a new generation of data scientists, and broaden public understanding" from an EU Expert Group, "…the nation faces a critical need for a competent and creative workforce in science, technology, engineering and mathematics (STEM)...", "We note two possible approaches to addressing the challenge of this transformation: revolutionary (paradigmatic shifts and systemic structural reform) and evolutionary (such as adding data mining courses to computational science education or simply transferring textbook organized content into digital textbooks).", and "The training programs that NSF establishes around such a data infrastructure initiative will create a new generation of data scientists, data curators, and data archivists that is equipped to meet the challenges and jobs of the future." Further, interim report of the International Council for Science's (ICSU) Strategic Coordinating Committee on Information and Data (SCCID), features this excerpt from section 4.2.4 Data scientists and professionals: "An unfortunate state in the recognition of data science, is that there is a lack of appreciation of the need for a set of professional knowledge in skill in key areas, many of which have not been emphasized to date, e.g. professional approaches to the management of data over its lifecycle. As such, the effort required to be a data scientists is not valued sufficiently by the remainder of the scientific community." SCCID Recommendation 6 reads: "We recommend the development of education at university level in the new and vital field of data science. The curriculum included in appendix D can be used as a starting point for curriculum development. Appendix D. is entitled "Example curriculum for data science" and explicitly uses the "Curriculum for Data Science taught at Rensselaer Polytechnic Institute, USA" . This contribution will present relevant curriculum offerings at the Rensselaer Polytechnic Institute. http://tw.rpi.edu/web/Courses

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.

Systems architecture: a new model for sustainability and the built environment using nanotechnology, biotechnology, information technology, and cognitive science with living technology.

PubMed

Armstrong, Rachel

2010-01-01

This report details a workshop held at the Bartlett School of Architecture, University College London, to initiate interdisciplinary collaborations for the practice of systems architecture, which is a new model for the generation of sustainable architecture that combines the discipline of the study of the built environment with the scientific study of complexity, or systems science, and adopts the perspective of systems theory. Systems architecture offers new perspectives on the organization of the built environment that enable architects to consider architecture as a series of interconnected networks with embedded links into natural systems. The public workshop brought together architects and scientists working with the convergence of nanotechnology, biotechnology, information technology, and cognitive science and with living technology to investigate the possibility of a new generation of smart materials that are implied by this approach.

A systems science perspective and transdisciplinary models for food and nutrition security

PubMed Central

Hammond, Ross A.; Dubé, Laurette

2012-01-01

We argue that food and nutrition security is driven by complex underlying systems and that both research and policy in this area would benefit from a systems approach. We present a framework for such an approach, examine key underlying systems, and identify transdisciplinary modeling tools that may prove especially useful. PMID:22826247

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…

Unpacking the Complex Relationship Between Beliefs, Practice, and Change Related to Inquiry-Based Instruction of One Science Teacher

NASA Astrophysics Data System (ADS)

Lebak, Kimberly

2015-12-01

This case study examines the complex relationship between beliefs, practice, and change related to inquiry-based instruction of one science teacher teaching in a high-poverty urban school. This study explores how video-supported collaboration with peers can provide the catalyst for change. Transcribed collaborative dialogue sessions, written self-reflections, and videotapes of lessons were used to identify and isolate the belief systems that were critical to the teacher's decision making. The Interconnected Model of Professional Growth was then used to trace the trajectories of change of the individual belief systems. Analysis of the data revealed the relationship between beliefs and practices was complex in which initially espoused beliefs were often inconsistent with enacted practice and some beliefs emerged as more salient than others for influencing practice. Furthermore, this research indicates change in both beliefs and practice was an interactive process mediated by collaborative and self-reflection through participation in the video-supported process.

Methodological Problems of Nanotechnoscience

NASA Astrophysics Data System (ADS)

Gorokhov, V. G.

Recently, we have reported on the definitions of nanotechnology as a new type of NanoTechnoScience and on the nanotheory as a cluster of the different natural and engineering theories. Nanotechnology is not only a new type of scientific-engineering discipline, but it evolves also in a “nonclassical” way. Nanoontology or nano scientific world view has a function of the methodological orientation for the choice the theoretical means and methods toward a solution to the scientific and engineering problems. This allows to change from one explanation and scientific world view to another without any problems. Thus, nanotechnology is both a field of scientific knowledge and a sphere of engineering activity, in other words, NanoTechnoScience is similar to Systems Engineering as the analysis and design of large-scale, complex, man/machine systems but micro- and nanosystems. Nano systems engineering as well as Macro systems engineering includes not only systems design but also complex research. Design orientation has influence on the change of the priorities in the complex research and of the relation to the knowledge, not only to “the knowledge about something”, but also to the knowledge as the means of activity: from the beginning control and restructuring of matter at the nano-scale is a necessary element of nanoscience.

Prioritized System Science Targets for Heliophysics

NASA Astrophysics Data System (ADS)

Spann, J. F.; Christensen, A. B.; St Cyr, O. C.; Posner, A.; Giles, B. L.

2009-12-01

Heliophysics is a discipline that investigates the science at work from the interface of Earth and space, to the core of the Sun, and to the outer edge of our solar system. This solar-interplanetary-planetary system is vast and inherently coupled on many spatial, temporal and energy scales. The Sun’s explosive energy output creates complicated field and plasma structures that when coupled with our terrestrial magnetized space, generates an extraordinary complex environment that has practical implications for humanity as we are becoming increasingly dependent on space-based assets. This immense volume of our cosmic neighborhood is the domain of heliophysics. Understanding this domain and the dominant mechanisms that control the transfer of mass and energy requires a system approach that addresses all aspects and regions of the system. The 2009 NASA Heliophysics Roadmap presents a science-focused strategic approach to advance the goal of heliophysics: why does the Sun vary; how do the Earth and heliosphere respond; and what are the impacts on humanity? This talk will present the top 6 prioritized science targets to understand the coupled heliophysics system as presented in the 2009 NASA Heliophysics Roadmap. An exposition of each science target and how it addresses outstanding questions in heliophysics will be discussed.

Future System Science Mission Targets for Heliophysics

NASA Technical Reports Server (NTRS)

Spann, James; Christensen, Andrew B.; SaintCyr, O. C.; Giles, Barbara I.; Posner, Arik

2009-01-01

Heliophysics is a discipline that investigates the science at work from the interface of Earth and space, to the core of the Sun, and to the outer edge of our solar system. This solar-interplanetary-planetary system is vast and inherently coupled on many spatial, temporal and energy scales. The Sun's explosive energy output creates complicated field and plasma structures that when coupled without terrestrial magnetized space, generates an extraordinary complex environment that has practical implications for humanity as we are becoming increasingly dependent on space-based assets. The immense volume of our cosmic neighborhood is the domain of heliophysics. Understanding this domain and the dominant mechanisms that control the transfer of mass and energy requires a system approach that addresses all aspects and regions of the system. The 2009 NASA Heliophysics Roadmap presents a science-focused strategic approach to advance the goal of heliophysics: why does the Sun vary; how do the Earth and heliosphere respond; and what are the impacts on humanity? This talk will present the top 6 prioritized science targets to understand the coupled heliophysics system as presented in the 2009 NASA Heliophysics Roadmap. An exposition of each science target and how it addresses outstanding questions in heliophysics will be discussed.

Prioritized System Science Targets for Heliophysics

NASA Technical Reports Server (NTRS)

Spann, James Frederick; Christensen, Andrew B.; SaintCyr, Orville Chris; Posner, Arik; Giles, Barbara L.

2009-01-01

Heliophysics is a discipline that investigates the science at work from the interface of Earth and space, to the core of the Sun, and to the outer edge of our solar system. This solar-interplanetary-planetary system is vast and inherently coupled on many spatial, temporal and energy scales. The Sun's explosive energy output creates complicated field and plasma structures that when coupled with our terrestrial magnetized space, generates an extraordinary complex environment that has practical implications for humanity as we are becoming increasingly dependent on space-based assets. This immense volume of our cosmic neighborhood is the domain of heliophysics. Understanding this domain and the dominant mechanisms that control the transfer of mass and energy requires a system approach that addresses all aspects and regions of the system. The 2009 NASA Heliophysics Roadmap presents a science-focused strategic approach to advance the goal of heliophysics: why does the Sun vary; how do the Earth and heliosphere respond; and what are the impacts on humanity? This talk will present the top 6 prioritized science targets to understand the coupled heliophysics system as presented in the 2009 NASA Heliophysics Roadmap. An exposition of each science target and how it addresses outstanding questions in heliophysics will be discussed.

An integrated science-based methodology to assess potential risks and implications of engineered nanomaterials.

PubMed

Tolaymat, Thabet; El Badawy, Amro; Sequeira, Reynold; Genaidy, Ash

2015-11-15

There is an urgent need for broad and integrated studies that address the risks of engineered nanomaterials (ENMs) along the different endpoints of the society, environment, and economy (SEE) complex adaptive system. This article presents an integrated science-based methodology to assess the potential risks of engineered nanomaterials. To achieve the study objective, two major tasks are accomplished, knowledge synthesis and algorithmic computational methodology. The knowledge synthesis task is designed to capture "what is known" and to outline the gaps in knowledge from ENMs risk perspective. The algorithmic computational methodology is geared toward the provision of decisions and an understanding of the risks of ENMs along different endpoints for the constituents of the SEE complex adaptive system. The approach presented herein allows for addressing the formidable task of assessing the implications and risks of exposure to ENMs, with the long term goal to build a decision-support system to guide key stakeholders in the SEE system towards building sustainable ENMs and nano-enabled products. Published by Elsevier B.V.

Combining pressure and temperature control in dynamics on energy landscapes

NASA Astrophysics Data System (ADS)

Hoffmann, Karl Heinz; Christian Schön, J.

2017-05-01

Complex systems from science, technology or mathematics usually appear to be very different in their specific dynamical evolution. However, the concept of an energy landscape with its basins corresponding to locally ergodic regions separated by energy barriers provides a unifying approach to the description of complex systems dynamics. In such systems one is often confronted with the task to control the dynamics such that a certain basin is reached with the highest possible probability. Typically one aims for the global minimum, e.g. when dealing with global optimization problems, but frequently other local minima such as the metastable compounds in materials science are of primary interest. Here we show how this task can be solved by applying control theory using magnesium fluoride as an example system, where different modifications of MgF2 are considered as targets. In particular, we generalize previous work restricted to temperature controls only and present controls which simultaneously adjust temperature and pressure in an optimal fashion.

A Tricky Trait: Applying the Fruits of the "Function Debate" in the Philosophy of Biology to the "Venom Debate" in the Science of Toxinology.

PubMed

Jackson, Timothy N W; Fry, Bryan G

2016-09-07

The "function debate" in the philosophy of biology and the "venom debate" in the science of toxinology are conceptually related. Venom systems are complex multifunctional traits that have evolved independently numerous times throughout the animal kingdom. No single concept of function, amongst those popularly defended, appears adequate to describe these systems in all their evolutionary contexts and extant variations. As such, a pluralistic view of function, previously defended by some philosophers of biology, is most appropriate. Venom systems, like many other functional traits, exist in nature as points on a continuum and the boundaries between "venomous" and "non-venomous" species may not always be clearly defined. This paper includes a brief overview of the concept of function, followed by in-depth discussion of its application to venom systems. A sound understanding of function may aid in moving the venom debate forward. Similarly, consideration of a complex functional trait such as venom may be of interest to philosophers of biology.

NASA's Earth Science Flight Program Meets the Challenges of Today and Tomorrow

NASA Technical Reports Server (NTRS)

Ianson, Eric E.

2016-01-01

NASA's Earth science flight program is a dynamic undertaking that consists of a large fleet of operating satellites, an array of satellite and instrument projects in various stages of development, a robust airborne science program, and a massive data archiving and distribution system. Each element of the flight program is complex and present unique challenges. NASA builds upon its successes and learns from its setbacks to manage this evolving portfolio to meet NASA's Earth science objectives. NASA fleet of 16 operating missions provide a wide range of scientific measurements made from dedicated Earth science satellites and from instruments mounted to the International Space Station. For operational missions, the program must address issues such as an aging satellites operating well beyond their prime mission, constellation flying, and collision avoidance with other spacecraft and orbital debris. Projects in development are divided into two broad categories: systematic missions and pathfinders. The Earth Systematic Missions (ESM) include a broad range of multi-disciplinary Earth-observing research satellite missions aimed at understanding the Earth system and its response to natural and human-induced forces and changes. Understanding these forces will help determine how to predict future changes, and how to mitigate or adapt to these changes. The Earth System Science Pathfinder (ESSP) program provides frequent, regular, competitively selected Earth science research opportunities that accommodate new and emerging scientific priorities and measurement capabilities. This results in a series of relatively low-cost, small-sized investigations and missions. Principal investigators whose scientific objectives support a variety of studies lead these missions, including studies of the atmosphere, oceans, land surface, polar ice regions, or solid Earth. This portfolio of missions and investigations provides opportunity for investment in innovative Earth science that enhances NASA's capability for better understanding the current state of the Earth system. ESM and ESSP projects often involve partnerships with other US agencies and/or international organizations. This adds to the complexity of mission development, but allows for a greater scientific return on NASA's investments. The Earth Science Airborne Science Program provides manned and unmanned aircraft systems that further science and advance the use of satellite data. NASA uses these assets worldwide in campaigns to investigate extreme weather events, observe Earth system processes, obtain data for Earth science modeling activities, and calibrate instruments flying aboard Earth science spacecraft. The Airborne Science Program has six dedicated aircraft and access to many other platforms. The Earth Science Multi-Mission Operations program acquires, preserves, and distributes observational data from operating spacecraft to support Earth Science research focus areas. The Earth Observing System Data and Information System (EOSDIS), which has been in operations since 1994, primarily accomplishes this. EOSDIS acquires, processes, archives, and distributes Earth Science data and information products. The archiving of NASA Earth Science information happens at eight Distributed Active Archive Centers (DAACs) and four disciplinary data centers located across the United States. The DAACs specialize by topic area, and make their data available to researchers around the world. The DAACs currently house over 9 petabytes of data, growing at a rate of 6.4 terabytes per day. NASA's current Earth Science portfolio is responsive to the National Research Council (NRC) 2007 Earth Science Decadal Survey and well as the 2010 NASA Response to President Obama's Climate Plan. As the program evolves into the future it will leverage the lessons learned from the current missions in operations and development, and plan for adjustments to future objectives in response to the anticipated 2017 NRC Decadal Survey.

BeeSign: A Computationally-Mediated Intervention to Examine K-1 Students' Representational Activities in the Context of Teaching Complex Systems Concepts

ERIC Educational Resources Information Center

Danish, Joshua Adam

2009-01-01

Representations such as drawings, graphs, and computer simulations, are central to learning and doing science. Furthermore, ongoing success in science learning requires students to build on the representations and associated practices that they are presumed to have learned throughout their schooling career. Without these practices, students have…

Knowledge and Values in Science Textbooks Concerning Complexity in Ecological Systems and Environmental Problems: A Cross-cultural Study on Secondary School Manuals

ERIC Educational Resources Information Center

Boujemaa, Agorram; Silvia, Caravita; Adriana, Valente; Daniela, Luzi; Nicola, Margnelli

2009-01-01

The study was carried out within the European research project "Biology, Health and Environmental Education for Better Citizenship" that joined 18 European and North-African countries. We report here the methodology and some of the conclusions drawn from an analysis of science textbooks that considered the topics ecology and…

Starting a Learning Progression for Agricultural Literacy: A Qualitative Study of Urban Elementary Student Understandings of Agricultural and Science Education Benchmarks

ERIC Educational Resources Information Center

Hess, Alexander Jay

2010-01-01

Science and agriculture professional organizations have argued for agricultural literacy as a goal for K-12 public education. Due to the complexity of our modern agri-food system, with social, economic, and environmental concerns embedded, an agriculturally literate society is needed for informed decision making, democratic participation, and…

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

Wang, Ucilia

This report has the following articles: (1) Deconstructing Microbes--metagenomic research on bugs in termites relies on new data analysis tools; (2) Popular Science--a nanomaterial research paper in Nano Letters drew strong interest from the scientific community; (3) Direct Approach--researchers employ an algorithm to solve an energy-reduction issue essential in describing complex physical system; and (4) SciDAC Special--A science journal features research on petascale enabling technologies.

Advanced Materials, Technologies, and Complex Systems Analyses: Emerging Opportunities to Enhance Urban Water Security.

PubMed

Zodrow, Katherine R; Li, Qilin; Buono, Regina M; Chen, Wei; Daigger, Glen; Dueñas-Osorio, Leonardo; Elimelech, Menachem; Huang, Xia; Jiang, Guibin; Kim, Jae-Hong; Logan, Bruce E; Sedlak, David L; Westerhoff, Paul; Alvarez, Pedro J J

2017-09-19

Innovation in urban water systems is required to address the increasing demand for clean water due to population growth and aggravated water stress caused by water pollution, aging infrastructure, and climate change. Advances in materials science, modular water treatment technologies, and complex systems analyses, coupled with the drive to minimize the energy and environmental footprints of cities, provide new opportunities to ensure a resilient and safe water supply. We present a vision for enhancing efficiency and resiliency of urban water systems and discuss approaches and research needs for overcoming associated implementation challenges.

Exposing the Strategies that can Reduce the Obstacles: Improving the Science User Experience

NASA Astrophysics Data System (ADS)

Lindsay, F. E.; Brennan, J.; Behnke, J.; Lynnes, C.

2017-12-01

It is now well established that pursuing generic solutions to what seem are common problems in Earth science data access and use can often lead to disappointing results for both system developers and the intended users. This presentation focuses on real-world experience of managing a large and complex data system, NASA's Earth Science Data and Information Science System (EOSDIS), whose mission is to serve both broad user communities and those in smaller niche applications of Earth science data and services. In the talk, we focus on our experiences with known data user obstacles characterizing EOSDIS approaches, including various technological techniques, for engaging and bolstering, where possible, user experiences with EOSDIS. For improving how existing and prospective users discover and access NASA data from EOSDIS we introduce our cross-archive tool: Earthdata Search. This new search and order tool further empowers users to quickly access data sets using clever and intuitive features. The Worldview data visualization tool is also discussed highlighting how many users are now performing extensive data exploration without necessarily downloading data. Also, we explore our EOSDIS data discovery and access webinars, data recipes and short tutorials, targeted technical and data publications, user profiles and and social media as additional tools and methods used for improving our outreach and communications to a diverse user community. These efforts have paid substantial dividends for our user communities by allowing us to target discipline specific community needs. The desired take-away from this presentation will be an improved understanding of how EOSDIS has approached, and in several instances achieved, removing or lowering the barriers to data access and use. As we look ahead to more complex Earth science missions, EOSDIS will continue to focus on our user communities, both broad and specialized, so that our overall data system can continue to serve the needs of science and applications users.

Exposing the Strategies that Can Reduce the Obstacles: Improving the Science User Experience

NASA Technical Reports Server (NTRS)

Lindsay, Francis E.; Brennan, Jennifer; Behnke, Jeanne; Lynnes, Chris

2017-01-01

It is now well established that pursuing generic solutions to what seem are common problems in Earth science data access and use can often lead to disappointing results for both system developers and the intended users. This presentation focuses on real-world experience of managing a large and complex data system, NASAs Earth Science Data and Information Science System (EOSDIS), whose mission is to serve both broad user communities and those in smaller niche applications of Earth science data and services. In the talk, we focus on our experiences with known data user obstacles characterizing EOSDIS approaches, including various technological techniques, for engaging and bolstering, where possible, user experiences with EOSDIS. For improving how existing and prospective users discover and access NASA data from EOSDIS we introduce our cross-archive tool: Earthdata Search. This new search and order tool further empowers users to quickly access data sets using clever and intuitive features. The Worldview data visualization tool is also discussed highlighting how many users are now performing extensive data exploration without necessarily downloading data. Also, we explore our EOSDIS data discovery and access webinars, data recipes and short tutorials, targeted technical and data publications, user profiles and social media as additional tools and methods used for improving our outreach and communications to a diverse user community. These efforts have paid substantial dividends for our user communities by allowing us to target discipline specific community needs. The desired take-away from this presentation will be an improved understanding of how EOSDIS has approached, and in several instances achieved, removing or lowering the barriers to data access and use. As we look ahead to more complex Earth science missions, EOSDIS will continue to focus on our user communities, both broad and specialized, so that our overall data system can continue to serve the needs of science and applications users.

Design and Development of a Web-Based Interactive Software Tool for Teaching Operating Systems

ERIC Educational Resources Information Center

Garmpis, Aristogiannis

2011-01-01

Operating Systems (OS) is an important and mandatory discipline in many Computer Science, Information Systems and Computer Engineering curricula. Some of its topics require a careful and detailed explanation from the instructor as they often involve theoretical concepts and somewhat complex mechanisms, demanding a certain degree of abstraction…

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…

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…

Gas-analytic measurement complexes of Baikal atmospheric-limnological observatory

NASA Astrophysics Data System (ADS)

Pestunov, D. A.; Shamrin, A. M.; Shmargunov, V. P.; Panchenko, M. V.

2015-11-01

The paper presents the present-day structure of stationary and mobile hardware-software gas-analytical complexes of Baikal atmospheric-limnological observatory (BALO) Siberian Branch Russian Academy of Sciences (SB RAS), designed to study the processes of gas exchange of carbon-containing gases in the "atmosphere-water" system, which are constantly updated to include new measuring and auxiliary instrumentation.

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

Branched-Chain Amino and Keto Acid Biochemistry and Cellular Biology in Central Nervous System Diseases

DTIC Science & Technology

2009-05-21

pyruvate dehydrogenase complex (PDC) and 2-oxo- glutarate dehydrogenase complex. These dehydrogenase complexes share the same basic structure, perform the...Science 312 (2006) 927-930. [20] J. Dancis, M. Levitz, R.G. Westall, Maple syrup urine disease: branched- chain keto- aciduria , Pediatrics 25 (1960...2127 2128 Dancis J, Levitz M, Westall RG. 1960. Maple syrup urine disease: branched-chain keto- aciduria . Pediatrics 25:72-9. Danner DJ, Lemmon

Brief history of agricultural systems modeling.

PubMed

Jones, James W; Antle, John M; Basso, Bruno; Boote, Kenneth J; Conant, Richard T; Foster, Ian; Godfray, H Charles J; Herrero, Mario; Howitt, Richard E; Janssen, Sander; Keating, Brian A; Munoz-Carpena, Rafael; Porter, Cheryl H; Rosenzweig, Cynthia; Wheeler, Tim R

2017-07-01

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the "next generation" models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of this history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. The lessons from history should be considered to help avoid roadblocks and pitfalls as the community develops this next generation of agricultural systems models.

Brief history of agricultural systems modeling

DOE PAGES

Jones, James W.; Antle, John M.; Basso, Bruno; ...

2017-06-21

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the "next generation" models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of thismore » history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. Furthermore, the lessons from history should be considered to help avoid roadblocks and pitfalls as the community develops this next generation of agricultural systems models.« less

Brief history of agricultural systems modeling

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

Jones, James W.; Antle, John M.; Basso, Bruno

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the "next generation" models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of thismore » history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. Furthermore, the lessons from history should be considered to help avoid roadblocks and pitfalls as the community develops this next generation of agricultural systems models.« less

Brief History of Agricultural Systems Modeling

NASA Technical Reports Server (NTRS)

Jones, James W.; Antle, John M.; Basso, Bruno O.; Boote, Kenneth J.; Conant, Richard T.; Foster, Ian; Godfray, H. Charles J.; Herrrero, Mario; Howitt, Richard E.; Janssen, Sandor;

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.

Intent, Future, Anticipation: A Semiotic, Transdisciplinary Approach

NASA Astrophysics Data System (ADS)

Loeckenhoff, Hellmut

2008-10-01

Encouraged e.g. by chaos theory and (bio-)semiotics science is trying to attempt a deeper understanding of life. The paradigms of physics alone prove not sufficient to explain f. ex. evolution or phylogenesis and ontogenesis. In complement, research on life systems reassesses paradigmatic models not only for living systems and not only on the strict biological level. The ontological as well as the epistemological base of science in toto is to be reconsidered. Science itself proves a historical and cultural phenomenon and can be seen as shaped by evolution and semiosis. -Living systems are signified by purpose, intent and, necessarily, by the faculty to anticipate e.g. the cyclic changes of their environment. To understand the concepts behind a proposal is developed towards a model set constituting a transdisciplinary approach. It rests e.g. on concepts of systems, evolution, complexity and semiodynamics.

From process complexity to communication effectiveness: A challenge to those within and outside of the environmental sciences

NASA Astrophysics Data System (ADS)

Kaiser, K. E.; McGlynn, B. L.

2014-12-01

Interdisciplinary work has become a cornerstone in research across the environmental sciences. Our work does so by evaluating biogeochemical cycling, specifically methane, in the context of landscape hydrology. Atmospheric methane is a greenhouse gas 27 times more potent than carbon dioxide and has been increasing at an unprecedented rate. This drastic increase in atmospheric methane has been attributed to anthropogenic activities such as burning of fossil fuels, ruminants, and rice cultivation, which together constitute approximately 67% of global methane sources. Characterizing CH4 flux in natural systems has remained difficult due to complex relationships among environmental variables (e.g. soil temperature and soil water content). To address this, we focus on how the redistribution of water in complex terrain influences the magnitude and direction of flux in upland and riparian soils. Distilling this complex behavior and scaling these observations is complicated by interacting feedback loops and uncertainties associated with global scale modeling. However, progress is critical given that predicting future climate is necessary to forecasting the quantity and distribution of available fresh water, and understanding how ecosystem processes, and energy/food production will be affected. Water sciences and environmental science as a whole must improve communication to a range of audiences, and advocate for researchers, policy makers, and business leaders to work together for a more sustainable future. A crucial step in this process is to optimize the appropriate level of information to convey that is both memorable and meaningful given the complexity of environmental systems. The challenge also extends to artists and filmmakers to present the subject in compelling ways that inspire audiences to take action in their own communities. True integration of professionals across environmental, social, political, and economic disciplines while motivating local involvement will be necessary for development and success of innovative solutions for improving the trajectory of climate change.

Complex Clouds

Atmospheric Science Data Center

2013-04-16

... article title:  Multi-layer Clouds Over the South Indian Ocean     View Larger Image ... System-2 path 155. MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission ...

Unifying Complexity and Information

NASA Astrophysics Data System (ADS)

Ke, Da-Guan

2013-04-01

Complex systems, arising in many contexts in the computer, life, social, and physical sciences, have not shared a generally-accepted complexity measure playing a fundamental role as the Shannon entropy H in statistical mechanics. Superficially-conflicting criteria of complexity measurement, i.e. complexity-randomness (C-R) relations, have given rise to a special measure intrinsically adaptable to more than one criterion. However, deep causes of the conflict and the adaptability are not much clear. Here I trace the root of each representative or adaptable measure to its particular universal data-generating or -regenerating model (UDGM or UDRM). A representative measure for deterministic dynamical systems is found as a counterpart of the H for random process, clearly redefining the boundary of different criteria. And a specific UDRM achieving the intrinsic adaptability enables a general information measure that ultimately solves all major disputes. This work encourages a single framework coving deterministic systems, statistical mechanics and real-world living organisms.

Perspectives on modeling in cognitive science.

PubMed

Shiffrin, Richard M

2010-10-01

This commentary gives a personal perspective on modeling and modeling developments in cognitive science, starting in the 1950s, but focusing on the author's personal views of modeling since training in the late 1960s, and particularly focusing on advances since the official founding of the Cognitive Science Society. The range and variety of modeling approaches in use today are remarkable, and for many, bewildering. Yet to come to anything approaching adequate insights into the infinitely complex fields of mind, brain, and intelligent systems, an extremely wide array of modeling approaches is vital and necessary. Copyright © 2010 Cognitive Science Society, Inc.

Agent Technology, Complex Adaptive Systems, and Autonomic Systems: Their Relationships

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Rash, James; Rouff, Chistopher; Hincheny, Mike

2004-01-01

To reduce the cost of future spaceflight missions and to perform new science, NASA has been investigating autonomous ground and space flight systems. These goals of cost reduction have been further complicated by nanosatellites for future science data-gathering which will have large communications delays and at times be out of contact with ground control for extended periods of time. This paper describes two prototype agent-based systems, the Lights-out Ground Operations System (LOGOS) and the Agent Concept Testbed (ACT), and their autonomic properties that were developed at NASA Goddard Space Flight Center (GSFC) to demonstrate autonomous operations of future space flight missions. The paper discusses the architecture of the two agent-based systems, operational scenarios of both, and the two systems autonomic properties.

Fort Collins Science Center Ecosystem Dynamics branch--interdisciplinary research for addressing complex natural resource issues across landscapes and time

USGS Publications Warehouse

Bowen, Zachary H.; Melcher, Cynthia P.; Wilson, Juliette T.

2013-01-01

The Ecosystem Dynamics Branch of the Fort Collins Science Center offers an interdisciplinary team of talented and creative scientists with expertise in biology, botany, ecology, geology, biogeochemistry, physical sciences, geographic information systems, and remote-sensing, for tackling complex questions about natural resources. As demand for natural resources increases, the issues facing natural resource managers, planners, policy makers, industry, and private landowners are increasing in spatial and temporal scope, often involving entire regions, multiple jurisdictions, and long timeframes. Needs for addressing these issues include (1) a better understanding of biotic and abiotic ecosystem components and their complex interactions; (2) the ability to easily monitor, assess, and visualize the spatially complex movements of animals, plants, water, and elements across highly variable landscapes; and (3) the techniques for accurately predicting both immediate and long-term responses of system components to natural and human-caused change. The overall objectives of our research are to provide the knowledge, tools, and techniques needed by the U.S. Department of the Interior, state agencies, and other stakeholders in their endeavors to meet the demand for natural resources while conserving biodiversity and ecosystem services. Ecosystem Dynamics scientists use field and laboratory research, data assimilation, and ecological modeling to understand ecosystem patterns, trends, and mechanistic processes. This information is used to predict the outcomes of changes imposed on species, habitats, landscapes, and climate across spatiotemporal scales. The products we develop include conceptual models to illustrate system structure and processes; regional baseline and integrated assessments; predictive spatial and mathematical models; literature syntheses; and frameworks or protocols for improved ecosystem monitoring, adaptive management, and program evaluation. The descriptions in this fact sheet provide snapshots of our three research emphases, followed by descriptions of select current projects.

A Scientific Rationale for Mobility in Planetary Environments

NASA Astrophysics Data System (ADS)

1999-01-01

For the last several decades, the COMmittee on Planetary and Lunar EXploration (COMPLEX) has advocated a systematic approach to exploration of the solar system; that is, the information and understanding resulting from one mission provide the scientific foundations that motivate subsequent, more elaborate investigations. COMPLEX's 1994 report, An Integrated Strategy for the Planetary Sciences: 1995-2010,1 advocated an approach to planetary studies emphasizing "hypothesizing and comprehending" rather than "cataloging and categorizing." More recently, NASA reports, including The Space Science Enterprise Strategic Plan' and, in particular, Mission to the Solar System: Exploration and Discovery-A Mission and Technology Roadmap, 3 have outlined comprehensive plans for planetary exploration during the next several decades. The missions outlined in these plans are both generally consistent with the priorities outlined in the Integrated Strategy and other NRC reports,4,5 and are replete with examples of devices embodying some degree of mobility in the form of rovers, robotic arms, and the like. Because the change in focus of planetary studies called for in the Integrated Strategy appears to require an evolutionary change in the technical means by which solar system exploration missions are conducted, the Space Studies Board charged COMPLEX to review the science that can be uniquely addressed by mobility in planetary environments. In particular, COMPLEX was asked to address the following questions: 1. What are the practical methods for achieving mobility? 2. For surface missions, what are the associated needs for sample acquisition? 3. What is the state of technology for planetary mobility in the United States and elsewhere, and what are the key requirements for technology development? 4. What terrestrial field demonstrations are required prior to spaceflight missions?

Is cognitive science usefully cast as complexity science?

PubMed

Van Orden, Guy; Stephen, Damian G

2012-01-01

Readers of TopiCS are invited to join a debate about the utility of ideas and methods of complexity science. The topics of debate include empirical instances of qualitative change in cognitive activity and whether this empirical work demonstrates sufficiently the empirical flags of complexity. In addition, new phenomena discovered by complexity scientists, and motivated by complexity theory, call into question some basic assumptions of conventional cognitive science such as stable equilibria and homogeneous variance. The articles and commentaries that appear in this issue also illustrate a new debate style format for topiCS. Copyright © 2011 Cognitive Science Society, Inc.

The Telecommunications and Data Acquisition Report

NASA Technical Reports Server (NTRS)

Yuen, Joseph H. (Editor)

1996-01-01

This quarterly publication provides archival reports on developments in programs managed by JPL's Telecommunications and Mission Operations Directorate (TMOD), which now includes the former Telecommunications and Data Acquisition (TDA) Office. In space communications, radio navigation, radio science, and ground-based radio and radar astronomy, it reports on activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. The preceding work is all performed for NASA's Office of Space Communications (OSC). TMOD also performs work funded by other NASA program offices through and with the cooperation of OSC. The first of these is the Orbital Debris Radar Program funded by the Office of Space Systems Development. It exists at Goldstone only and makes use of the planetary radar capability when the antennas are configured as science instruments making direct observations of the planets, their satellites, and asteroids of our solar system. The Office of Space Sciences funds the data reduction and science analyses of data obtained by the Goldstone Solar System Radar. The antennas at all three complexes are also configured for radio astronomy research and, as such, conduct experiments funded by the National Science Foundation in the U.S. and other agencies at the overseas complexes. These experiments are either in microwave spectroscopy or very long baseline interferometry. Finally, tasks funded under the JPL Director's Discretionary Fund and the Caltech President's Fund that involve TMOD are included. This and each succeeding issue of 'The Telecommunications and Data Acquisition Progress Report' will present material in some, but not necessarily all, of the aforementioned programs.

Neutrons for biologists: a beginner's guide, or why you should consider using neutrons.

PubMed

Lakey, Jeremy H

2009-10-06

From the structures of isolated protein complexes to the molecular dynamics of whole cells, neutron methods can achieve a resolution in complex systems that is inaccessible to other techniques. Biology is fortunate in that it is rich in water and hydrogen, and this allows us to exploit the differential sensitivity of neutrons to this element and its major isotope, deuterium. Furthermore, neutrons exhibit wave properties that allow us to use them in similar ways to light, X-rays and electrons. This review aims to explain the basics of biological neutron science to encourage its greater use in solving difficult problems in the life sciences.

Neutrons for biologists: a beginner's guide, or why you should consider using neutrons

PubMed Central

Lakey, Jeremy H.

2009-01-01

From the structures of isolated protein complexes to the molecular dynamics of whole cells, neutron methods can achieve a resolution in complex systems that is inaccessible to other techniques. Biology is fortunate in that it is rich in water and hydrogen, and this allows us to exploit the differential sensitivity of neutrons to this element and its major isotope, deuterium. Furthermore, neutrons exhibit wave properties that allow us to use them in similar ways to light, X-rays and electrons. This review aims to explain the basics of biological neutron science to encourage its greater use in solving difficult problems in the life sciences. PMID:19656821

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

PubMed

Jedlicka, Peter

2017-01-01

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

Ontology of Earth's nonlinear dynamic complex systems

NASA Astrophysics Data System (ADS)

Babaie, Hassan; Davarpanah, Armita

2017-04-01

As a complex system, Earth and its major integrated and dynamically interacting subsystems (e.g., hydrosphere, atmosphere) display nonlinear behavior in response to internal and external influences. The Earth Nonlinear Dynamic Complex Systems (ENDCS) ontology formally represents the semantics of the knowledge about the nonlinear system element (agent) behavior, function, and structure, inter-agent and agent-environment feedback loops, and the emergent collective properties of the whole complex system as the result of interaction of the agents with other agents and their environment. It also models nonlinear concepts such as aperiodic, random chaotic behavior, sensitivity to initial conditions, bifurcation of dynamic processes, levels of organization, self-organization, aggregated and isolated functionality, and emergence of collective complex behavior at the system level. By incorporating several existing ontologies, the ENDCS ontology represents the dynamic system variables and the rules of transformation of their state, emergent state, and other features of complex systems such as the trajectories in state (phase) space (attractor and strange attractor), basins of attractions, basin divide (separatrix), fractal dimension, and system's interface to its environment. The ontology also defines different object properties that change the system behavior, function, and structure and trigger instability. ENDCS will help to integrate the data and knowledge related to the five complex subsystems of Earth by annotating common data types, unifying the semantics of shared terminology, and facilitating interoperability among different fields of Earth science.

Using the Eclipse Parallel Tools Platform to Assist Earth Science Model Development and Optimization on High Performance Computers

NASA Astrophysics Data System (ADS)

Alameda, J. C.

2011-12-01

Development and optimization of computational science models, particularly on high performance computers, and with the advent of ubiquitous multicore processor systems, practically on every system, has been accomplished with basic software tools, typically, command-line based compilers, debuggers, performance tools that have not changed substantially from the days of serial and early vector computers. However, model complexity, including the complexity added by modern message passing libraries such as MPI, and the need for hybrid code models (such as openMP and MPI) to be able to take full advantage of high performance computers with an increasing core count per shared memory node, has made development and optimization of such codes an increasingly arduous task. Additional architectural developments, such as many-core processors, only complicate the situation further. In this paper, we describe how our NSF-funded project, "SI2-SSI: A Productive and Accessible Development Workbench for HPC Applications Using the Eclipse Parallel Tools Platform" (WHPC) seeks to improve the Eclipse Parallel Tools Platform, an environment designed to support scientific code development targeted at a diverse set of high performance computing systems. Our WHPC project to improve Eclipse PTP takes an application-centric view to improve PTP. We are using a set of scientific applications, each with a variety of challenges, and using PTP to drive further improvements to both the scientific application, as well as to understand shortcomings in Eclipse PTP from an application developer perspective, to drive our list of improvements we seek to make. We are also partnering with performance tool providers, to drive higher quality performance tool integration. We have partnered with the Cactus group at Louisiana State University to improve Eclipse's ability to work with computational frameworks and extremely complex build systems, as well as to develop educational materials to incorporate into computational science and engineering codes. Finally, we are partnering with the lead PTP developers at IBM, to ensure we are as effective as possible within the Eclipse community development. We are also conducting training and outreach to our user community, including conference BOF sessions, monthly user calls, and an annual user meeting, so that we can best inform the improvements we make to Eclipse PTP. With these activities we endeavor to encourage use of modern software engineering practices, as enabled through the Eclipse IDE, with computational science and engineering applications. These practices include proper use of source code repositories, tracking and rectifying issues, measuring and monitoring code performance changes against both optimizations as well as ever-changing software stacks and configurations on HPC systems, as well as ultimately encouraging development and maintenance of testing suites -- things that have become commonplace in many software endeavors, but have lagged in the development of science applications. We view that the challenge with the increased complexity of both HPC systems and science applications demands the use of better software engineering methods, preferably enabled by modern tools such as Eclipse PTP, to help the computational science community thrive as we evolve the HPC landscape.

New ethical challenges in science and technology

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

NONE

The published research features some of the nation's leading scientists and engineers, as well as science policy experts, and discusses a wide range of issues and topics. These include the economic and social pressure impacting biomedical research, the impossibility of predicting all the behaviors of increasingly complex, engineered systems, a look at the new federal guidelines for misconduct and new wrinkles on faculty conflicts of interest.

The Role of School District Science Coordinators in the District-Wide Appropriation of an Online Resource Discovery and Sharing Tool for Teachers

ERIC Educational Resources Information Center

Lee, Victor R.; Leary, Heather M.; Sellers, Linda; Recker, Mimi

2014-01-01

When introducing and implementing a new technology for science teachers within a school district, we must consider not only the end users but also the roles and influence district personnel have on the eventual appropriation of that technology. School districts are, by their nature, complex systems with multiple individuals at different levels in…

Balancing Management and Leadership in Complex Health Systems Comment on "Management Matters: A Leverage Point for Health Systems Strengthening in Global Health".

PubMed

Kwamie, Aku

2015-08-14

Health systems, particularly those in low- and middle-income countries (LMICs), need stronger management and leadership capacities. Management and leadership are not synonymous, yet should be considered together as there can be too much of one and not enough of the other. In complex adaptive health systems, the multiple interactions and relationships between people and elements of the system mean that management and leadership, so often treated as domains of the individual, are additionally systemic phenomena, emerging from these relational interactions. This brief commentary notes some significant implications for how we can support capacity strengthening interventions for complex management and leadership. These would necessarily move away from competency-based models focused on training for individuals, and would rather encompass longer-term initiatives explicitly focused on systemic goals of accountability, innovation, and learning. © 2015 by Kerman University of Medical Sciences.

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

Complex Topographic Feature Ontology Patterns

USGS Publications Warehouse

Varanka, Dalia E.; Jerris, Thomas J.

2015-01-01

Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

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.

Homeward Bound: Ecological Design of Domestic Information Systems

NASA Astrophysics Data System (ADS)

Wastell, David G.; Sauer, Juergen S.; Schmeink, Claudia

Information technology artefacts are steadily permeating everyday life, just as they have colonized the business domain. Although research in our field has largely addressed the workplace, researchers are beginning to take an interest in the home environment too. Here, we address the domestic realm, focusing on the design of complex, interactive information systems. As such, our work sits in the design science version rather than behavioral science paradigm of IS research. We argue that the home is in many ways a more challenging environment for the designer than the workplace, making good design of critical importance. Regrettably, the opposite would appear to be the norm. Two experiments are reported, both concerned with the design of the user interface for domestic heating systems. Of note is our use of a medium-fidelity laboratory simulation or "microworld" in this work. Two main substantive findings resulted. First, that ecologically designed feedback, embodying a strong mapping between task goals and system status, produced superior task performance. Second, that predictive decision aids provided clear benefits over other forms of user support, such as advisory systems. General implications for the design of domestic information systems are discussed, followed by reflections on the nature of design work in IS, and on the design science project itself. It is concluded that the microworld approach has considerable potential for developing IS design theory. The methodological challenges of design research are highlighted, especially the presence of additional validity threats posed by the need to construct artefacts in order to evaluate theory. It is argued that design theory is necessarily complex, modal, and uncertain, and that design science (like design itself) should be prosecuted in an open, heuristic spirit, drawing more on the proven methods of "good design" (e.g.,prototyping, user participation) in terms of its own praxis.

New ARCH: Future Generation Internet Architecture

DTIC Science & Technology

2004-08-01

a vocabulary to talk about a system . This provides a framework ( a “reference model ...layered model Modularity and abstraction are central tenets of Computer Science thinking. Modularity breaks a system into parts, normally to permit...this complexity is hidden. Abstraction suggests a structure for the system . A popular and simple structure is a layered model : lower layer

A Middleware Platform for Providing Mobile and Embedded Computing Instruction to Software Engineering Students

ERIC Educational Resources Information Center

Mattmann, C. A.; Medvidovic, N.; Malek, S.; Edwards, G.; Banerjee, S.

2012-01-01

As embedded software systems have grown in number, complexity, and importance in the modern world, a corresponding need to teach computer science students how to effectively engineer such systems has arisen. Embedded software systems, such as those that control cell phones, aircraft, and medical equipment, are subject to requirements and…

Contingency Software in Autonomous Systems: Technical Level Briefing

NASA Technical Reports Server (NTRS)

Lutz, Robyn R.; Patterson-Hines, Ann

2006-01-01

Contingency management is essential to the robust operation of complex systems such as spacecraft and Unpiloted Aerial Vehicles (UAVs). Automatic contingency handling allows a faster response to unsafe scenarios with reduced human intervention on low-cost and extended missions. Results, applied to the Autonomous Rotorcraft Project and Mars Science Lab, pave the way to more resilient autonomous systems.

Air Force Laboratory’s 2005 Technology Milestones

DTIC Science & Technology

2006-01-01

Computational materials science methods can benefit the design and property prediction of complex real-world materials. With these models , scientists and...Warfighter Page Air High - Frequency Acoustic System...800) 203-6451 High - Frequency Acoustic System Payoff Scientists created the High - Frequency Acoustic Suppression Technology (HiFAST) airflow control

Design Patterns for Learning and Assessment: Facilitating the Introduction of a Complex Simulation-Based Learning Environment into a Community of Instructors

ERIC Educational Resources Information Center

Frezzo, Dennis C.; Behrens, John T.; Mislevy, Robert J.

2010-01-01

Simulation environments make it possible for science and engineering students to learn to interact with complex systems. Putting these capabilities to effective use for learning, and assessing learning, requires more than a simulation environment alone. It requires a conceptual framework for the knowledge, skills, and ways of thinking that are…

Animal models and conserved processes

PubMed Central

2012-01-01

Background The concept of conserved processes presents unique opportunities for using nonhuman animal models in biomedical research. However, the concept must be examined in the context that humans and nonhuman animals are evolved, complex, adaptive systems. Given that nonhuman animals are examples of living systems that are differently complex from humans, what does the existence of a conserved gene or process imply for inter-species extrapolation? Methods We surveyed the literature including philosophy of science, biological complexity, conserved processes, evolutionary biology, comparative medicine, anti-neoplastic agents, inhalational anesthetics, and drug development journals in order to determine the value of nonhuman animal models when studying conserved processes. Results Evolution through natural selection has employed components and processes both to produce the same outcomes among species but also to generate different functions and traits. Many genes and processes are conserved, but new combinations of these processes or different regulation of the genes involved in these processes have resulted in unique organisms. Further, there is a hierarchy of organization in complex living systems. At some levels, the components are simple systems that can be analyzed by mathematics or the physical sciences, while at other levels the system cannot be fully analyzed by reducing it to a physical system. The study of complex living systems must alternate between focusing on the parts and examining the intact whole organism while taking into account the connections between the two. Systems biology aims for this holism. We examined the actions of inhalational anesthetic agents and anti-neoplastic agents in order to address what the characteristics of complex living systems imply for inter-species extrapolation of traits and responses related to conserved processes. Conclusion We conclude that even the presence of conserved processes is insufficient for inter-species extrapolation when the trait or response being studied is located at higher levels of organization, is in a different module, or is influenced by other modules. However, when the examination of the conserved process occurs at the same level of organization or in the same module, and hence is subject to study solely by reductionism, then extrapolation is possible. PMID:22963674

On the complex interaction between mathematics and the sciences of living systems. Comment on "Move me, astonish me...delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates" by Matthew Pelowski et al.

NASA Astrophysics Data System (ADS)

Bellomo, Nicola; Outada, Nisrine

2017-07-01

Cultural framework: Our comment looks at the general framework given by the interactions between the so-called ;soft; and ;hard; sciences. Specifically, it looks at the development of a mathematics for living systems. Our comment aims at showing how the interesting survey [11] can contribute to the aforementioned challenging task.

[Integration of nursing in science and technology policies].

PubMed

Rocha, Semíramis Melani Melo; Ogata, Márcia Niituma; Arantes, Cássia Irene Spinelli

2003-01-01

Brazilian nursing is included in the national science and technology system, as part of the health knowledge area. Its scientific production is reknown but is yet to strengthen its position. Among the strategies to be used, we can emphasize: study different ways to promote a closer relationship between university and services; create or intensify interfacing between clinical and academic nurses; promote strategic research for the use of technological innovations, continuing education of human resources, and implement studies on Nursing care while integrating skills required by complex technological systems and intersubjectivity, acting in a therapeutic way.

Analysis of Major Histocompatibility Complex (MHC) Immunopeptidomes Using Mass Spectrometry.

PubMed

Caron, Etienne; Kowalewski, Daniel J; Chiek Koh, Ching; Sturm, Theo; Schuster, Heiko; Aebersold, Ruedi

2015-12-01

The myriad of peptides presented at the cell surface by class I and class II major histocompatibility complex (MHC) molecules are referred to as the immunopeptidome and are of great importance for basic and translational science. For basic science, the immunopeptidome is a critical component for understanding the immune system; for translational science, exact knowledge of the immunopeptidome can directly fuel and guide the development of next-generation vaccines and immunotherapies against autoimmunity, infectious diseases, and cancers. In this mini-review, we summarize established isolation techniques as well as emerging mass spectrometry-based platforms (i.e. SWATH-MS) to identify and quantify MHC-associated peptides. We also highlight selected biological applications and discuss important current technical limitations that need to be solved to accelerate the development of this field. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Managing Complexity in the MSL/Curiosity Entry, Descent, and Landing Flight Software and Avionics Verification and Validation Campaign

NASA Technical Reports Server (NTRS)

Stehura, Aaron; Rozek, Matthew

2013-01-01

The complexity of the Mars Science Laboratory (MSL) mission presented the Entry, Descent, and Landing systems engineering team with many challenges in its Verification and Validation (V&V) campaign. This paper describes some of the logistical hurdles related to managing a complex set of requirements, test venues, test objectives, and analysis products in the implementation of a specific portion of the overall V&V program to test the interaction of flight software with the MSL avionics suite. Application-specific solutions to these problems are presented herein, which can be generalized to other space missions and to similar formidable systems engineering problems.

How the Center for Public Partnerships and Research Navigates Complex Social Problems to Make a Collective Difference.

PubMed

Counts, Jacqueline; Gillam, Rebecca; Garstka, Teri A; Urbach, Ember

2018-01-01

The challenge of maximizing the well-being of children, youth, and families is recognizing that change occurs within complex social systems. Organizations dedicated to improving practice, advancing knowledge, and informing policy for the betterment of all must have the right approach, structure, and personnel to work in these complex systems. The University of Kansas Center for Public Partnerships and Research cultivates a portfolio of innovation, research, and data science approaches positioned to help move social service fields locally, regionally, and nationally. Mission, leadership, and smart growth guide our work and drive our will to affect positive change in the world.

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.

Conceptual Foundations of Systems Biology Explaining Complex Cardiac Diseases.

PubMed

Louridas, George E; Lourida, Katerina G

2017-02-21

Systems biology is an important concept that connects molecular biology and genomics with computing science, mathematics and engineering. An endeavor is made in this paper to associate basic conceptual ideas of systems biology with clinical medicine. Complex cardiac diseases are clinical phenotypes generated by integration of genetic, molecular and environmental factors. Basic concepts of systems biology like network construction, modular thinking, biological constraints (downward biological direction) and emergence (upward biological direction) could be applied to clinical medicine. Especially, in the field of cardiology, these concepts can be used to explain complex clinical cardiac phenotypes like chronic heart failure and coronary artery disease. Cardiac diseases are biological complex entities which like other biological phenomena can be explained by a systems biology approach. The above powerful biological tools of systems biology can explain robustness growth and stability during disease process from modulation to phenotype. The purpose of the present review paper is to implement systems biology strategy and incorporate some conceptual issues raised by this approach into the clinical field of complex cardiac diseases. Cardiac disease process and progression can be addressed by the holistic realistic approach of systems biology in order to define in better terms earlier diagnosis and more effective therapy.

From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments

NASA Astrophysics Data System (ADS)

Glynn, Pierre D.; Voinov, Alexey A.; Shapiro, Carl D.; White, Paul A.

2017-04-01

Our different kinds of minds and types of thinking affect the ways we decide, take action, and cooperate (or not). Derived from these types of minds, innate biases, beliefs, heuristics, and values (BBHV) influence behaviors, often beneficially, when individuals or small groups face immediate, local, acute situations that they and their ancestors faced repeatedly in the past. BBHV, though, need to be recognized and possibly countered or used when facing new, complex issues or situations especially if they need to be managed for the benefit of a wider community, for the longer-term and the larger-scale. Taking BBHV into account, we explain and provide a cyclic science-infused adaptive framework for (1) gaining knowledge of complex systems and (2) improving their management. We explore how this process and framework could improve the governance of science and policy for different types of systems and issues, providing examples in the area of natural resources, hazards, and the environment. Lastly, we suggest that an "Open Traceable Accountable Policy" initiative that followed our suggested adaptive framework could beneficially complement recent Open Data/Model science initiatives.

The First Korean Experience of Telemanipulative Robot-Assisted Laparoscopic Cholecystectomy Using the da Vinci System

PubMed Central

Kang, Chang Moo; Chi, Hoon Sang; Hyeung, Woo Jin; Kim, Kyung Sik; Choi, Jin Sub; Kim, Byong Ro

2007-01-01

With the advancement of laparoscopic instruments and computer sciences, complex surgical procedures are expected to be safely performed by robot assisted telemanipulative laparoscopic surgery. The da Vinci system (Intuitive Surgical, Mountain View, CA, USA) became available at the many surgical fields. The wrist like movements of the instrument's tip, as well as 3-dimensional vision, could be expected to facilitate more complex laparoscopic procedure. Here, we present the first Korean experience of da Vinci robotic assisted laparoscopic cholecystectomy and discuss the introduction and perspectives of this robotic system. PMID:17594166

CONFERENCE ANNOUNCEMENT: European Conference on Complex Systems 2009 European Conference on Complex Systems 2009

NASA Astrophysics Data System (ADS)

2009-05-01

The 2009 European Conference on Complex Systems will take place 21-25 September 2009 at the University of Warwick in the UK. Local Organising Committee Markus Kirkilionis (Warwick, Chair), Francois Kepes (Genopole, Programme Chair), Robert MacKay (Warwick), Robin Ball (Warwick), Jeff Johnson (Open University). International Steering Committee Markus Kirkilionis (Warwick; Chair 2008-10), Fatihcan Atay (Leipzig), Jürgen Jost (Leipzig), Scott Kirkpatrick (Jerusalem), David Lane (University of Modena and Reggio Emillia), Andreas Lorincz (Hungarian Academy of Sciences), Denise Pumain (Sorbonne), Felix Reed-Tsochas (Oxford), Eörs Szathmáry (Collegium Budapest, Hungary), Stephan Thurner (Wien), Paul Verschure (Barcelona), Alessandro Vespignani (Indiana, ISI), Riccardo Zecchina (Torino). Main tracks and Organisers Policy, Planning & Infrastructure: Jeff Johnson (Open University, Chair), Arnaud Banos (Strasbourg) Collective Human Behaviour and Society: Felix Reed-Tsochas (Oxford, Chair), Frances Griffiths (Warwick), Edmund Chattoe-Brown (Leicester) Interacting Populations and Environment: TBA Complexity and Computer Science: András Lörincz (Eötvös Loránd University), Paul Verschure (Zürich) From Molecules to Living Systems: Mark Chaplain (Dundee, Chair), Wolfgang Marwan (Magdeburg) Mathematics and Simulation: Holger Kantz (Dresden, Chair), Fatihcan Atay (Leipzig), Matteo Marsili (Trieste). Deadlines Paper submission: 31 March 2009 with decisions 15 May 2009. Paper submission deadline likely to be extended. See http://www.eccs09.info for more information. Meeting registration: early registration July 2009; last assured chance 1 Sept. Further information For contacts and the most up-to-date information visit http://www.eccs09.info.

Science and Technology Review September 1999

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

Eimerl, D

1999-09-01

This review consists of the following titles; The Laboratory in the News; Life Performance of Complex Systems; A Better Picture of Aging Materials; Researchers Determine Chernobyl Liquidators' Exposure; and Target Chamber's Dedication Marks a Giant Milestone.

Complexity Science Framework for Big Data: Data-enabled Science

NASA Astrophysics Data System (ADS)

Surjalal Sharma, A.

2016-07-01

The ubiquity of Big Data has stimulated the development of analytic tools to harness the potential for timely and improved modeling and prediction. While much of the data is available near-real time and can be compiled to specify the current state of the system, the capability to make predictions is lacking. The main reason is the basic nature of Big Data - the traditional techniques are challenged in their ability to cope with its velocity, volume and variability to make optimum use of the available information. Another aspect is the absence of an effective description of the time evolution or dynamics of the specific system, derived from the data. Once such dynamical models are developed predictions can be made readily. This approach of " letting the data speak for itself " is distinct from the first-principles models based on the understanding of the fundamentals of the system. The predictive capability comes from the data-derived dynamical model, with no modeling assumptions, and can address many issues such as causality and correlation. This approach provides a framework for addressing the challenges in Big Data, especially in the case of spatio-temporal time series data. The reconstruction of dynamics from time series data is based on recognition that in most systems the different variables or degrees of freedom are coupled nonlinearly and in the presence of dissipation the state space contracts, effectively reducing the number of variables, thus enabling a description of its dynamical evolution and consequently prediction of future states. The predictability is analysed from the intrinsic characteristics of the distribution functions, such as Hurst exponents and Hill estimators. In most systems the distributions have heavy tails, which imply higher likelihood for extreme events. The characterization of the probabilities of extreme events are critical in many cases e. g., natural hazards, for proper assessment of risk and mitigation strategies. Big Data with such new analytics can yield improved risk estimates. The challenges of scientific inference from complex and massive data are addressed by data-enabled science, also referred as the Fourth paradigm, after experiment, theory and simulation. An example of this approach is the modelling of dynamical and statistical features of natural systems, without assumptions of specific processes. An effective use of the techniques of complexity science to yield the inherent features of a system from extensive data from observations and large scale numerical simulations is evident in the case of Earth's magnetosphere. The multiscale nature of the magnetosphere makes the numerical simulations a challenge, requiring very large computing resources. The reconstruction of dynamics from observational data can however yield the inherent characteristics using typical desktop computers. Such studies for other systems are in progress. Data-enabled approach using the framework of complexity science provides new techniques for modelling and prediction using Big Data. The studies of Earth's magnetosphere, provide an example of the potential for a new approach to the development of quantitative analytic tools.

Developing the Next Generation of Science Data System Engineers

NASA Technical Reports Server (NTRS)

Moses, John F.; Behnke, Jeanne; Durachka, Christopher D.

2016-01-01

At Goddard, engineers and scientists with a range of experience in science data systems are needed to employ new technologies and develop advances in capabilities for supporting new Earth and Space science research. Engineers with extensive experience in science data, software engineering and computer-information architectures are needed to lead and perform these activities. The increasing types and complexity of instrument data and emerging computer technologies coupled with the current shortage of computer engineers with backgrounds in science has led the need to develop a career path for science data systems engineers and architects.The current career path, in which undergraduate students studying various disciplines such as Computer Engineering or Physical Scientist, generally begins with serving on a development team in any of the disciplines where they can work in depth on existing Goddard data systems or serve with a specific NASA science team. There they begin to understand the data, infuse technologies, and begin to know the architectures of science data systems. From here the typical career involves peermentoring, on-the-job training or graduate level studies in analytics, computational science and applied science and mathematics. At the most senior level, engineers become subject matter experts and system architect experts, leading discipline-specific data centers and large software development projects. They are recognized as a subject matter expert in a science domain, they have project management expertise, lead standards efforts and lead international projects. A long career development remains necessary not only because of the breadth of knowledge required across physical sciences and engineering disciplines, but also because of the diversity of instrument data being developed today both by NASA and international partner agencies and because multidiscipline science and practitioner communities expect to have access to all types of observational data.This paper describes an approach to defining career-path guidance for college-bound high school and undergraduate engineering students, junior and senior engineers from various disciplines.

Developing the Next Generation of Science Data System Engineers

NASA Astrophysics Data System (ADS)

Moses, J. F.; Durachka, C. D.; Behnke, J.

2015-12-01

At Goddard, engineers and scientists with a range of experience in science data systems are needed to employ new technologies and develop advances in capabilities for supporting new Earth and Space science research. Engineers with extensive experience in science data, software engineering and computer-information architectures are needed to lead and perform these activities. The increasing types and complexity of instrument data and emerging computer technologies coupled with the current shortage of computer engineers with backgrounds in science has led the need to develop a career path for science data systems engineers and architects. The current career path, in which undergraduate students studying various disciplines such as Computer Engineering or Physical Scientist, generally begins with serving on a development team in any of the disciplines where they can work in depth on existing Goddard data systems or serve with a specific NASA science team. There they begin to understand the data, infuse technologies, and begin to know the architectures of science data systems. From here the typical career involves peer mentoring, on-the-job training or graduate level studies in analytics, computational science and applied science and mathematics. At the most senior level, engineers become subject matter experts and system architect experts, leading discipline-specific data centers and large software development projects. They are recognized as a subject matter expert in a science domain, they have project management expertise, lead standards efforts and lead international projects. A long career development remains necessary not only because of the breath of knowledge required across physical sciences and engineering disciplines, but also because of the diversity of instrument data being developed today both by NASA and international partner agencies and because multi-discipline science and practitioner communities expect to have access to all types of observational data. This paper describes an approach to defining career-path guidance for college-bound high school and undergraduate engineering students, junior and senior engineers from various disciplines.

[Application of microelectronics CAD tools to synthetic biology].

PubMed

Madec, Morgan; Haiech, Jacques; Rosati, Élise; Rezgui, Abir; Gendrault, Yves; Lallement, Christophe

2017-02-01

Synthetic biology is an emerging science that aims to create new biological functions that do not exist in nature, based on the knowledge acquired in life science over the last century. Since the beginning of this century, several projects in synthetic biology have emerged. The complexity of the developed artificial bio-functions is relatively low so that empirical design methods could be used for the design process. Nevertheless, with the increasing complexity of biological circuits, this is no longer the case and a large number of computer aided design softwares have been developed in the past few years. These tools include languages for the behavioral description and the mathematical modelling of biological systems, simulators at different levels of abstraction, libraries of biological devices and circuit design automation algorithms. All of these tools already exist in other fields of engineering sciences, particularly in microelectronics. This is the approach that is put forward in this paper. © 2017 médecine/sciences – Inserm.

Visual analytics as a translational cognitive science.

PubMed

Fisher, Brian; Green, Tera Marie; Arias-Hernández, Richard

2011-07-01

Visual analytics is a new interdisciplinary field of study that calls for a more structured scientific approach to understanding the effects of interaction with complex graphical displays on human cognitive processes. Its primary goal is to support the design and evaluation of graphical information systems that better support cognitive processes in areas as diverse as scientific research and emergency management. The methodologies that make up this new field are as yet ill defined. This paper proposes a pathway for development of visual analytics as a translational cognitive science that bridges fundamental research in human/computer cognitive systems and design and evaluation of information systems in situ. Achieving this goal will require the development of enhanced field methods for conceptual decomposition of human/computer cognitive systems that maps onto laboratory studies, and improved methods for conducting laboratory investigations that might better map onto real-world cognitive processes in technology-rich environments. Copyright © 2011 Cognitive Science Society, Inc.

Framework to Define Structure and Boundaries of Complex Health Intervention Systems: The ALERT Project

PubMed Central

Boriani, Elena; Esposito, Roberto; Frazzoli, Chiara; Fantke, Peter; Hald, Tine; Rüegg, Simon R.

2017-01-01

Health intervention systems are complex and subject to multiple variables in different phases of implementation. This constitutes a concrete challenge for the application of translational science in real life. Complex systems as health-oriented interventions call for interdisciplinary approaches with carefully defined system boundaries. Exploring individual components of such systems from different viewpoints gives a wide overview and helps to understand the elements and the relationships that drive actions and consequences within the system. In this study, we present an application and assessment of a framework with focus on systems and system boundaries of interdisciplinary projects. As an example on how to apply our framework, we analyzed ALERT [an integrated sensors and biosensors’ system (BEST) aimed at monitoring the quality, health, and traceability of the chain of the bovine milk], a multidisciplinary and interdisciplinary project based on the application of measurable biomarkers at strategic points of the milk chain for improved food security (including safety), human, and ecosystem health (1). In fact, the European food safety framework calls for science-based support to the primary producers’ mandate for legal, scientific, and ethical responsibility in food supply. Because of its multidisciplinary and interdisciplinary approach involving human, animal, and ecosystem health, ALERT can be considered as a One Health project. Within the ALERT context, we identified the need to take into account the main actors, interactions, and relationships of stakeholders to depict a simplified skeleton of the system. The framework can provide elements to highlight how and where to improve the project development when project evaluations are required. PMID:28804707

Framework to Define Structure and Boundaries of Complex Health Intervention Systems: The ALERT Project.

PubMed

Boriani, Elena; Esposito, Roberto; Frazzoli, Chiara; Fantke, Peter; Hald, Tine; Rüegg, Simon R

2017-01-01

Health intervention systems are complex and subject to multiple variables in different phases of implementation. This constitutes a concrete challenge for the application of translational science in real life. Complex systems as health-oriented interventions call for interdisciplinary approaches with carefully defined system boundaries. Exploring individual components of such systems from different viewpoints gives a wide overview and helps to understand the elements and the relationships that drive actions and consequences within the system. In this study, we present an application and assessment of a framework with focus on systems and system boundaries of interdisciplinary projects. As an example on how to apply our framework, we analyzed ALERT [an integrated sensors and biosensors' system (BEST) aimed at monitoring the quality, health, and traceability of the chain of the bovine milk], a multidisciplinary and interdisciplinary project based on the application of measurable biomarkers at strategic points of the milk chain for improved food security (including safety), human, and ecosystem health (1). In fact, the European food safety framework calls for science-based support to the primary producers' mandate for legal, scientific, and ethical responsibility in food supply. Because of its multidisciplinary and interdisciplinary approach involving human, animal, and ecosystem health, ALERT can be considered as a One Health project. Within the ALERT context, we identified the need to take into account the main actors, interactions, and relationships of stakeholders to depict a simplified skeleton of the system. The framework can provide elements to highlight how and where to improve the project development when project evaluations are required.

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

PubMed Central

Jedlicka, Peter

2017-01-01

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

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.

Construction of the Hunveyor-Husar space probe model system for planetary science education and analog studies and simulations in universities and colleges of Hungary.

NASA Astrophysics Data System (ADS)

Bérczi, Sz.; Hegyi, S.; Hudoba, Gy.; Hargitai, H.; Kokiny, A.; Drommer, B.; Gucsik, A.; Pintér, A.; Kovács, Zs.

Several teachers and students had the possibility to visit International Space Camp in the vicinity of the MSFC NASA in Huntsville Alabama USA where they learned the success of simulators in space science education To apply these results in universities and colleges in Hungary we began a unified complex modelling in planetary geology robotics electronics and complex environmental analysis by constructing an experimental space probe model system First a university experimental lander HUNVEYOR Hungarian UNiversity surVEYOR then a rover named HUSAR Hungarian University Surface Analyser Rover has been built For Hunveyor the idea and example was the historical Surveyor program of NASA in the 1960-ies for the Husar the idea and example was the Pathfinder s rover Sojouner rover The first step was the construction of the lander a year later the rover followed The main goals are 1 to build the lander structure and basic electronics from cheap everyday PC compatible elements 2 to construct basic experiments and their instruments 3 to use the system as a space activity simulator 4 this simulator contains lander with on board computer for works on a test planetary surface and a terrestrial control computer 5 to harmonize the assemblage of the electronic system and instruments in various levels of autonomy from the power and communication circuits 6 to use the complex system in education for in situ understanding complex planetary environmental problems 7 to build various planetary environments for application of the

Do complexity-informed health interventions work? A scoping review.

PubMed

Brainard, Julii; Hunter, Paul R

2016-09-20

The lens of complexity theory is widely advocated to improve health care delivery. However, empirical evidence that this lens has been useful in designing health care remains elusive. This review assesses whether it is possible to reliably capture evidence for efficacy in results or process within interventions that were informed by complexity science and closely related conceptual frameworks. Systematic searches of scientific and grey literature were undertaken in late 2015/early 2016. Titles and abstracts were screened for interventions (A) delivered by the health services, (B) that explicitly stated that complexity science provided theoretical underpinning, and (C) also reported specific outcomes. Outcomes had to relate to changes in actual practice, service delivery or patient clinical indicators. Data extraction and detailed analysis was undertaken for studies in three developed countries: Canada, UK and USA. Data were extracted for intervention format, barriers encountered and quality aspects (thoroughness or possible biases) of evaluation and reporting. From 5067 initial finds in scientific literature and 171 items in grey literature, 22 interventions described in 29 articles were selected. Most interventions relied on facilitating collaboration to find solutions to specific or general problems. Many outcomes were very positive. However, some outcomes were measured only subjectively, one intervention was designed with complexity theory in mind but did not reiterate this in subsequent evaluation and other interventions were credited as compatible with complexity science but reported no relevant theoretical underpinning. Articles often omitted discussion on implementation barriers or unintended consequences, which suggests that complexity theory was not widely used in evaluation. It is hard to establish cause and effect when attempting to leverage complex adaptive systems and perhaps even harder to reliably find evidence that confirms whether complexity-informed interventions are usually effective. While it is possible to show that interventions that are compatible with complexity science seem efficacious, it remains difficult to show that explicit planning with complexity in mind was particularly valuable. Recommendations are made to improve future evaluation reports, to establish a better evidence base about whether this conceptual framework is useful in intervention design and implementation.

Using integrated research and interdisciplinary science: Potential benefits and challenges to managers of parks and protected areas

USGS Publications Warehouse

van Riper, Charles; Powell, Robert B.; Machlis, Gary; van Wagtendonk, Jan W.; van Riper, Carena J.; von Ruschkowski, Eick; Schwarzbach, Steven E.; Galipeau, Russell E.

2012-01-01

Our purpose in this paper is to build a case for utilizing interdisciplinary science to enhance the management of parks and protected areas. We suggest that interdisciplinary science is necessary for dealing with the complex issues of contemporary resource management, and that using the best available integrated scientific information be embraced and supported at all levels of agencies that manage parks and protected areas. It will take the commitment of park managers, scientists, and agency leaders to achieve the goal of implementing the results of interdisciplinary science into park management. Although such calls go back at least several decades, today interdisciplinary science is sporadically being promoted as necessary for supporting effective protected area management(e.g., Machlis et al. 1981; Kelleher and Kenchington 1991). Despite this history, rarely has "interdisciplinary science" been defined, its importance explained, or guidance provided on how to translate and then implement the associated research results into management actions (Tress et al. 2006; Margles et al. 2010). With the extremely complex issues that now confront protected areas (e.g., climate change influences, extinctions and loss of biodiversity, human and wildlife demographic changes, and unprecedented human population growth) information from more than one scientific discipline will need to be brought to bear in order to achieve sustained management solutions that resonate with stakeholders (Ostrom 2009). Although interdisciplinary science is not the solution to all problems, we argue that interdisciplinary research is an evolving and widely supported best practice. In the case of park and protected area management, interdisciplinary science is being driven by the increasing recognition of the complexity and interconnectedness of human and natural systems, and the notion that addressing many problems can be more rapidly advanced through interdisciplinary study and analysis.

Chaos and The Changing Nature of Science and Medicine. Proceedings

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

Herbert, D.E.; Croft, P.; Silver, D.S.

1996-09-01

These proceedings represent the lectures given at the workshop on chaos and the changing nature of science and medicine. The workshop was sponsored by the University of South Alabama and the American Association of Physicists in Medicine. The topics discussed covered nonlinear dynamical systems, complexity theory, fractals, chaos in biology and medicine and in fluid dynamics. Applications of chaotic dynamics in climatology were also discussed. There were 8 lectures at the workshop and all 8 have been abstracted for the Energy Science and Technology database.(AIP)

Northern Gulf of Mexico: USGS science contributions to a resilient coast, 2006-2011

USGS Publications Warehouse

,

2007-01-01

The devastating hurricane season of 2005 challenged U.S. Geological Survey (USGS) to develop a science base for resource managers and policy makers that could provide an understanding of the multiple stressors and influence affecting the northern Gulf of Mexico coast and to rack changes in linked coastal systems. The complexity of the Gulf Coast requires a science strategy for data collection and data reporting that is consistent across regional ecosystems and that can be applied to both short-term and long-term responses to stressors.

European Science Notes Information Bulletin Reports on Current European/ Middle Eastern Science

DTIC Science & Technology

1991-06-01

particularly those that involve shock wave/boundary layer cell-centered, finite-volume, explicit, Runge-Kutta interactions , still prov;de considerble...aircraft configuration attributed to using an interactive vcual grid generation was provided by A. Bocci and A. Baxendale, the Aircraft system developed...the surface pressure the complex problem of wing/body/pylon/store distributions with and without the mass flow through the interaction . Reasonable

Robust Modeling of Complex Systems with Heavy Tails and Long Memory

DTIC Science & Technology

2014-07-16

cluster model, Scandinavian Actuarial Journal , (09 2011): 0. doi: Gennady Samorodnitsky, Sami Umut Can, Thomas Mikosch. Weak convergence of the...further studies in science , mathematics, engineering or technology fields: Student Metrics This section only applies to graduating undergraduates...0.00 0.00 0.00 0.00 The number of undergraduates funded by this agreement who graduated during this period with a degree in science , mathematics

Molecular Mechanics and Dynamics Characterization of an "in silico" Mutated Protein: A Stand-Alone Lab Module or Support Activity for "in vivo" and "in vitro" Analyses of Targeted Proteins

ERIC Educational Resources Information Center

Chiang, Harry; Robinson, Lucy C.; Brame, Cynthia J.; Messina, Troy C.

2013-01-01

Over the past 20 years, the biological sciences have increasingly incorporated chemistry, physics, computer science, and mathematics to aid in the development and use of mathematical models. Such combined approaches have been used to address problems from protein structure-function relationships to the workings of complex biological systems.…

KSC-2014-3131

NASA Image and Video Library

2014-07-03

CAPE CANAVERAL, Fla. – Lights flickered and balloons fell as former NASA astronaut Tom Jones, left, and Therrin Protze, chief operating officer of Delaware North Parks and Resorts at NASA’s Kennedy Space Center Visitor Complex in Florida, welcomed guests to the grand opening of the Great Balls of Fire exhibit at the visitor complex. Great Balls of Fire shares the story of the origins of our solar system, asteroids and comets and their possible impacts and risks. The 1,500-square-foot exhibit, located in the East Gallery of the IMAX theatre at the visitor complex, features several interactive displays, real meteorites and replica asteroid models. The exhibit is a production of The Space Science Institute's National Center for Interactive Learning. It is a traveling exhibition that also receives funding from NASA and the National Science Foundation. Photo credit: NASA/Daniel Casper

KSC-2014-3136

NASA Image and Video Library

2014-07-03

CAPE CANAVERAL, Fla. – The grand opening of the new Great Balls of Fire exhibit was held at NASA’s Kennedy Space Center Visitor Complex in Florida. The grand opening featured remarks by former NASA astronaut Tom Jones, and Therrin Protze, chief operating officer at Delaware North Parks and Resorts at the visitor complex. Great Balls of Fire shares the story of the origins of our solar system, asteroids and comets and their possible impacts and risks. The 1,500-square-foot exhibit, located in the East Gallery of the IMAX theatre at the visitor complex, features several interactive displays, real meteorites and replica asteroid models. The exhibit is a production of The Space Science Institute's National Center for Interactive Learning. It is a traveling exhibition that also receives funding from NASA and the National Science Foundation. Photo credit: NASA/Daniel Casper

KSC-2014-3134

NASA Image and Video Library

2014-07-03

CAPE CANAVERAL, Fla. – A real asteroid is on display at the new Great Balls of Fire exhibit at NASA’s Kennedy Space Center Visitor Complex in Florida. The grand opening of the new attraction featured remarks by former NASA astronaut Tom Jones, and Therrin Protze, chief operating officer at Delaware North Parks and Resorts at the visitor complex. Great Balls of Fire shares the story of the origins of our solar system, asteroids and comets and their possible impacts and risks. The 1,500-square-foot exhibit, located in the East Gallery of the IMAX theatre at the visitor complex, features several interactive displays, real meteorites and replica asteroid models. The exhibit is a production of The Space Science Institute's National Center for Interactive Learning. It is a traveling exhibition that also receives funding from NASA and the National Science Foundation. Photo credit: NASA/Daniel Casper

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.

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

Scaling the Pyramid Model across Complex Systems Providing Early Care for Preschoolers: Exploring How Models for Decision Making May Enhance Implementation Science

ERIC Educational Resources Information Center

Johnson, LeAnne D.

2017-01-01

Bringing effective practices to scale across large systems requires attending to how information and belief systems come together in decisions to adopt, implement, and sustain those practices. Statewide scaling of the Pyramid Model, a framework for positive behavior intervention and support, across different types of early childhood programs…

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.

An Education for Peace Model That Centres on Belief Systems: The Theory behind The Model

ERIC Educational Resources Information Center

Willis, Alison

2017-01-01

The education for peace model (EFPM) presented in this paper was developed within a theoretical framework of complexity science and critical theory and was derived from a review of an empirical research project conducted in a conflict affected environment. The model positions belief systems at the centre and is socioecologically systemic in design…

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…

1993 Annual report on scientific programs: A broad research program on the sciences of complexity

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

NONE

1993-12-31

This report provides a summary of many of the research projects completed by the Santa Fe Institute (SFI) during 1993. These research efforts continue to focus on two general areas: the study of, and search for, underlying scientific principles governing complex adaptive systems, and the exploration of new theories of computation that incorporate natural mechanisms of adaptation (mutation, genetics, evolution).

Thermostatted kinetic equations as models for complex systems in physics and life sciences.

PubMed

Bianca, Carlo

2012-12-01

Statistical mechanics is a powerful method for understanding equilibrium thermodynamics. An equivalent theoretical framework for nonequilibrium systems has remained elusive. The thermodynamic forces driving the system away from equilibrium introduce energy that must be dissipated if nonequilibrium steady states are to be obtained. Historically, further terms were introduced, collectively called a thermostat, whose original application was to generate constant-temperature equilibrium ensembles. This review surveys kinetic models coupled with time-reversible deterministic thermostats for the modeling of large systems composed both by inert matter particles and living entities. The introduction of deterministic thermostats allows to model the onset of nonequilibrium stationary states that are typical of most real-world complex systems. The first part of the paper is focused on a general presentation of the main physical and mathematical definitions and tools: nonequilibrium phenomena, Gauss least constraint principle and Gaussian thermostats. The second part provides a review of a variety of thermostatted mathematical models in physics and life sciences, including Kac, Boltzmann, Jager-Segel and the thermostatted (continuous and discrete) kinetic for active particles models. Applications refer to semiconductor devices, nanosciences, biological phenomena, vehicular traffic, social and economics systems, crowds and swarms dynamics. Copyright © 2012 Elsevier B.V. All rights reserved.

Unlocking the full potential of open innovation in the life sciences through a classification system.

PubMed

Nilsson, Niclas; Minssen, Timo

2018-04-01

A common understanding of expectations and requirements is critical for boosting research-driven business opportunities in open innovation (OI) settings. Transparent communication requires common definitions and standards for OI to align the expectations of both parties. Here, we suggest a five-level classification system for OI models, reflecting the degree of openness. The aim of this classification system is to reduce contract negotiation complexity and times between two parties looking to engage in OI. Systematizing definitions and contractual terms for OI in the life sciences helps to reduce entry barriers and boosts collaborative value generation. By providing a contractual framework with predefined rules, science will be allowed to move more freely, thus maximizing the potential of OI. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Preface

NASA Astrophysics Data System (ADS)

Gidea, Marian; Sieber, Jan; Silber, Mary; Wieczorek, Sebastian

2015-05-01

This special issue on "Tipping Points: Fundamentals and Applications" is an offspring of the workshop with the same title held at the International Centre for Mathematical Sciences (ICMS), Edinburgh, between September 09-13, 2013. The theme of the meeting was the study of threshold behavior in complex environmental systems, such as Earth's climate, or ecological, sociological or economic systems.

An Undergraduate Research Experience Studying Ras and Ras Mutants

ERIC Educational Resources Information Center

Griffeth, Nancy; Batista, Naralys; Grosso, Terri; Arianna, Gianluca; Bhatia, Ravnit; Boukerche, Faiza; Crispi, Nicholas; Fuller, Neno; Gauza, Piotr; Kingsbury, Lyle; Krynski, Kamil; Levine, Alina; Ma, Rui Yan; Nam, Jennifer; Pearl, Eitan; Rosa, Alessandro; Salarbux, Stephanie; Sun, Dylan

2016-01-01

Each January from 2010 to 2014, an undergraduate workshop on modeling biological systems was held at Lehman College of the City University of New York. The workshops were funded by a National Science Foundation (NSF) Expedition in Computing, "Computational Modeling and Analysis of Complex Systems (CMACS)." The primary goal was to…

The science of decisionmaking: applications for sustainable forest and grassland management in the National Forest System

Treesearch

Matthew P. Thompson; Bruce G. Marcot; Frank R. Thompson; Steven McNulty; Larry A. Fisher; Michael C. Runge; David Cleaves; Monica Tomosy

2013-01-01

Sustainable management of national forests and grasslands within the National Forest System (NFS) often requires managers to make tough decisions under considerable uncertainty, complexity, and potential conflict. Resource decisionmakers must weigh a variety of risks, stressors, and challenges to sustainable management, including climate change, wildland fire, invasive...

Impact of Hands-On Research Experience on Students' Learning in an Introductory Management Information System Course

ERIC Educational Resources Information Center

Wu, Yun; Sankar, Chetan S.

2013-01-01

Although students in Introductory Information Systems courses are taught new technology concepts, the complexity and constantly changing nature of these technologies makes it challenging to deliver the concepts effectively. Aiming to improve students' learning experiences, this research utilized the five phases of design science methodology to…

Q&A: The Basics of California's School Finance System

ERIC Educational Resources Information Center

EdSource, 2006

2006-01-01

In a state as large and complex as California, education financing can become as complicated as rocket science. This two-page Q&A provides a brief, easy-to-understand explanation of California's school finance system and introduces the issues of its adequacy and equity. A list of resources providing additional information is provided.

Restoration of neurological functions by neuroprosthetic technologies: future prospects and trends towards micro-, nano-, and biohybrid systems.

PubMed

Stieglitz, T

2007-01-01

Today applications of neural prostheses that successfully help patients to increase their activities of daily living and participate in social life again are quite simple implants that yield definite tissue response and are well recognized as foreign body. Latest developments in genetic engineering, nanotechnologies and materials sciences have paved the way to new scenarios towards highly complex systems to interface the human nervous system. Combinations of neural cells with microimplants promise stable biohybrid interfaces. Nanotechnology opens the door to macromolecular landscapes on implants that mimic the biologic topology and surface interaction of biologic cells. Computer sciences dream of technical cognitive systems that act and react due to knowledge-based conclusion mechanisms to a changing or adaptive environment. Different sciences start to interact and discuss the synergies when methods and paradigms from biology, computer sciences and engineering, neurosciences, psychology will be combined. They envision the era of "converging technologies" to completely change the understanding of science and postulate a new vision of humans. In this chapter, these research lines will be discussed on some examples as well as the societal implications and ethical questions that arise from these new opportunities.

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.

A Tricky Trait: Applying the Fruits of the “Function Debate” in the Philosophy of Biology to the “Venom Debate” in the Science of Toxinology

PubMed Central

Jackson, Timothy N. W.; Fry, Bryan G.

2016-01-01

The “function debate” in the philosophy of biology and the “venom debate” in the science of toxinology are conceptually related. Venom systems are complex multifunctional traits that have evolved independently numerous times throughout the animal kingdom. No single concept of function, amongst those popularly defended, appears adequate to describe these systems in all their evolutionary contexts and extant variations. As such, a pluralistic view of function, previously defended by some philosophers of biology, is most appropriate. Venom systems, like many other functional traits, exist in nature as points on a continuum and the boundaries between “venomous” and “non-venomous” species may not always be clearly defined. This paper includes a brief overview of the concept of function, followed by in-depth discussion of its application to venom systems. A sound understanding of function may aid in moving the venom debate forward. Similarly, consideration of a complex functional trait such as venom may be of interest to philosophers of biology. PMID:27618098

Autonomous aerial observations to extend and complement the Earth Observing System: a science-driven systems-oriented approach

NASA Astrophysics Data System (ADS)

Sandford, Stephen P.; Harrison, F. W.; Langford, John; Johnson, James W.; Qualls, Garry; Emmitt, David; Jones, W. Linwood; Shugart, Herman H., Jr.

2004-12-01

The current Earth observing capability depends primarily on spacecraft missions and ground-based networks to provide the critical on-going observations necessary for improved understanding of the Earth system. Aircraft missions play an important role in process studies but are limited to relatively short-duration flights. Suborbital observations have contributed to global environmental knowledge by providing in-depth, high-resolution observations that space-based and in-situ systems are challenged to provide; however, the limitations of aerial platforms - e.g., limited observing envelope, restrictions associated with crew safety and high cost of operations have restricted the suborbital program to a supporting role. For over a decade, it has been recognized that autonomous aerial observations could potentially be important. Advances in several technologies now enable autonomous aerial observation systems (AAOS) that can provide fundamentally new observational capability for Earth science and applications and thus lead scientists and engineers to rethink how suborbital assets can best contribute to Earth system science. Properly developed and integrated, these technologies will enable new Earth science and operational mission scenarios with long term persistence, higher-spatial and higher-temporal resolution at lower cost than space or ground based approaches. This paper presents the results of a science driven, systems oriented study of broad Earth science measurement needs. These needs identify aerial mission scenarios that complement and extend the current Earth Observing System. These aerial missions are analogous to space missions in their complexity and potential for providing significant data sets for Earth scientists. Mission classes are identified and presented based on science driven measurement needs in atmospheric, ocean and land studies. Also presented is a nominal concept of operations for an AAOS: an innovative set of suborbital assets that complements and augments current and planned space-based observing systems.

Making sense of the emerging conversation in evaluation about systems thinking and complexity science.

PubMed

Gates, Emily F

2016-12-01

In the last twenty years, a conversation has emerged in the evaluation field about the potential of systems thinking and complexity science (STCS) to transform the practice of evaluating social interventions. Documenting and interpreting this conversation are necessary to advance our understanding of the significance of using STCS in planning, implementing, and evaluating social interventions. Guided by a generic framework for evaluation practice, this paper reports on an inter-disciplinary literature review and argues that STCS raises some new ways of thinking about and carrying out the following six activities: 1) supporting social problem solving; 2) framing interventions and contexts; 3) selecting and using methods; 4) engaging in valuing; 5) producing and justifying knowledge; and 6) facilitating use. Following a discussion of these issues, future directions for research and practice are suggested. Copyright © 2016 Elsevier Ltd. All rights reserved.

Useful theories make predictions.

PubMed

Howes, Andrew

2012-01-01

Stephen and Van Orden (this issue) propose that there is a complex system approach to cognitive science, and collectively the authors of the papers presented in this issue believe that this approach provides the means to drive a revolution in the science of the mind. Unfortunately, however illuminating, this explanation is absent and hyperbole is all too extensive. In contrast, I argue (1) that dynamic systems theory is not new to cognitive science and does not provide a basis for a revolution, (2) it is not necessary to reject cognitive science in order to explain the constraints imposed by the body and the environment, (3) it is not necessary, as Silberstein and Chemero (this issue) appear to do, to reject cognitive science in order to explain consciousness, and (4) our understanding of pragmatics is not advanced by Gibbs and Van Orden's (this issue) "self-organized criticality".? Any debate about the future of cognitive science could usefully focus on predictive adequacy. Unfortunately, this is not the approach taken by the authors of this issue. Copyright © 2012 Cognitive Science Society, Inc.

Exponential rise of dynamical complexity in quantum computing through projections.

PubMed

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

2014-10-10

The ability of quantum systems to host exponentially complex dynamics has the potential to revolutionize science and technology. Therefore, much effort has been devoted to developing of protocols for computation, communication and metrology, which exploit this scaling, despite formidable technical difficulties. Here we show that the mere frequent observation of a small part of a quantum system can turn its dynamics from a very simple one into an exponentially complex one, capable of universal quantum computation. After discussing examples, we go on to show that this effect is generally to be expected: almost any quantum dynamics becomes universal once 'observed' as outlined above. Conversely, we show that any complex quantum dynamics can be 'purified' into a simpler one in larger dimensions. We conclude by demonstrating that even local noise can lead to an exponentially complex dynamics.

Nonlinear dynamical systems for theory and research in ergonomics.

PubMed

Guastello, Stephen J

2017-02-01

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

Technology transfer from the science of medicine to the real world: the potential role played by artificial adaptive systems.

PubMed

Grossi, Enzo

2007-01-01

The author describes a refiguration of medical thought that originates from nonlinear dynamics and chaos theory. The coupling of computer science and these new theoretical bases coming from complex systems mathematics allows the creation of "intelligent" agents capable of adapting themselves dynamically to problems of high complexity: the artificial neural networks (ANNs). ANNs are able to reproduce the dynamic interaction of multiple factors simultaneously, allowing the study of complexity; they can also draw conclusions on an individual basis and not as average trends. These tools can allow a more efficient technology transfer from the science of medicine to the real world, overcoming many obstacles responsible for the present translational failure. They also contribute to a new holistic vision of the human subject person, contrasting the statistical reductionism that tends to squeeze or even delete the single subject, sacrificing him to his group of belongingness. A remarkable contribution to this individual approach comes from fuzzy logic, according to which there are no sharp limits between opposite things, such as wealth and disease. This approach allows one to partially escape from the probability theory trap in situations where it is fundamental to express a judgement based on a single case and favor a novel humanism directed to the management of the patient as an individual subject person.

Statistics and bioinformatics in nutritional sciences: analysis of complex data in the era of systems biology⋆

PubMed Central

Fu, Wenjiang J.; Stromberg, Arnold J.; Viele, Kert; Carroll, Raymond J.; Wu, Guoyao

2009-01-01

Over the past two decades, there have been revolutionary developments in life science technologies characterized by high throughput, high efficiency, and rapid computation. Nutritionists now have the advanced methodologies for the analysis of DNA, RNA, protein, low-molecular-weight metabolites, as well as access to bioinformatics databases. Statistics, which can be defined as the process of making scientific inferences from data that contain variability, has historically played an integral role in advancing nutritional sciences. Currently, in the era of systems biology, statistics has become an increasingly important tool to quantitatively analyze information about biological macromolecules. This article describes general terms used in statistical analysis of large, complex experimental data. These terms include experimental design, power analysis, sample size calculation, and experimental errors (type I and II errors) for nutritional studies at population, tissue, cellular, and molecular levels. In addition, we highlighted various sources of experimental variations in studies involving microarray gene expression, real-time polymerase chain reaction, proteomics, and other bioinformatics technologies. Moreover, we provided guidelines for nutritionists and other biomedical scientists to plan and conduct studies and to analyze the complex data. Appropriate statistical analyses are expected to make an important contribution to solving major nutrition-associated problems in humans and animals (including obesity, diabetes, cardiovascular disease, cancer, ageing, and intrauterine fetal retardation). PMID:20233650

Advancing One Health Policy and Implementation Through the Concept of One Medicine One Science.

PubMed

Cardona, Carol; Travis, Dominic A; Berger, Kavita; Coat, Gwenaële; Kennedy, Shaun; Steer, Clifford J; Murtaugh, Michael P; Sriramarao, P

2015-09-01

Numerous interspecies disease transmission events, Ebola virus being a recent and cogent example, highlight the complex interactions between human, animal, and environmental health and the importance of addressing medicine and health in a comprehensive scientific manner. The diversity of information gained from the natural, social, behavioral, and systems sciences is critical to developing and sustainably promoting integrated health approaches that can be implemented at the local, national, and international levels to meet grand challenges. The Concept of One Medicine One Science (COMOS) as outlined herein describes the interplay between scientific knowledge that underpins health and medicine and efforts toward stabilizing local systems using 2 linked case studies: the food system and emerging infectious disease. Forums such as the International Conference of One Medicine One Science (iCOMOS), where science and policy can be debated together, missing pieces identified, and science-based collaborations formed among industry, governmental, and nongovernmental policy makers and funders, is an essential step in addressing global health. The expertise of multiple disciplines and research foci to support policy development is critical to the implementation of one health and the successful achievement of global health security goals.

KSC-2014-3129

NASA Image and Video Library

2014-07-03

CAPE CANAVERAL, Fla. – Former NASA astronaut Tom Jones welcomes visitors to the grand opening of the Great Balls of Fire exhibit at NASA’s Kennedy Space Center Visitor Complex in Florida. Great Balls of Fire shares the story of the origins of our solar system, asteroids and comets and their possible impacts and risks. The 1,500-square-foot exhibit, located in the East Gallery of the IMAX theatre at the visitor complex, features several interactive displays, real meteorites and replica asteroid models. The exhibit is a production of The Space Science Institute's National Center for Interactive Learning. It is a traveling exhibition that also receives funding from NASA and the National Science Foundation. Photo credit: NASA/Daniel Casper

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.

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.

ENERGY-NET (Energy, Environment and Society Learning Network): Enhancing opportunities for learning using an Earth systems science framework

NASA Astrophysics Data System (ADS)

Elliott, E. M.; Bain, D. J.; Divers, M. T.; Crowley, K. J.; Povis, K.; Scardina, A.; Steiner, M.

2012-12-01

We describe a newly funded collaborative NSF initiative, ENERGY-NET (Energy, Environment and Society Learning Network), that brings together the Carnegie Museum of Natural History (CMNH) with the Learning Science and Geoscience research strengths at the University of Pittsburgh. ENERGY-NET aims to create rich opportunities for participatory learning and public education in the arena of energy, the environment, and society using an Earth systems science framework. We build upon a long-established teen docent program at CMNH and to form Geoscience Squads comprised of underserved teens. Together, the ENERGY-NET team, including museum staff, experts in informal learning sciences, and geoscientists spanning career stage (undergraduates, graduate students, faculty) provides inquiry-based learning experiences guided by Earth systems science principles. Together, the team works with Geoscience Squads to design "Exploration Stations" for use with CMNH visitors that employ an Earth systems science framework to explore the intersecting lenses of energy, the environment, and society. The goals of ENERGY-NET are to: 1) Develop a rich set of experiential learning activities to enhance public knowledge about the complex dynamics between Energy, Environment, and Society for demonstration at CMNH; 2) Expand diversity in the geosciences workforce by mentoring underrepresented teens, providing authentic learning experiences in earth systems science and life skills, and providing networking opportunities with geoscientists; and 3) Institutionalize ENERGY-NET collaborations among geosciences expert, learning researchers, and museum staff to yield long-term improvements in public geoscience education and geoscience workforce recruiting.

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.

Mineral Surface-Templated Self-Assembling Systems: Case Studies from Nanoscience and Surface Science towards Origins of Life Research.

PubMed

Gillams, Richard J; Jia, Tony Z

2018-05-08

An increasing body of evidence relates the wide range of benefits mineral surfaces offer for the development of early living systems, including adsorption of small molecules from the aqueous phase, formation of monomeric subunits and their subsequent polymerization, and supramolecular assembly of biopolymers and other biomolecules. Each of these processes was likely a necessary stage in the emergence of life on Earth. Here, we compile evidence that templating and enhancement of prebiotically-relevant self-assembling systems by mineral surfaces offers a route to increased structural, functional, and/or chemical complexity. This increase in complexity could have been achieved by early living systems before the advent of evolvable systems and would not have required the generally energetically unfavorable formation of covalent bonds such as phosphodiester or peptide bonds. In this review we will focus on various case studies of prebiotically-relevant mineral-templated self-assembling systems, including supramolecular assemblies of peptides and nucleic acids, from nanoscience and surface science. These fields contain valuable information that is not yet fully being utilized by the origins of life and astrobiology research communities. Some of the self-assemblies that we present can promote the formation of new mineral surfaces, similar to biomineralization, which can then catalyze more essential prebiotic reactions; this could have resulted in a symbiotic feedback loop by which geology and primitive pre-living systems were closely linked to one another even before life’s origin. We hope that the ideas presented herein will seed some interesting discussions and new collaborations between nanoscience/surface science researchers and origins of life/astrobiology researchers.

Social and ethical dimension of the natural sciences, complex problems of the age, interdisciplinarity, and the contribution of education

NASA Astrophysics Data System (ADS)

Develaki, Maria

2008-09-01

In view of the complex problems of this age, the question of the socio-ethical dimension of science acquires particular importance. We approach this matter from a philosophical and sociological standpoint, looking at such focal concerns as the motivation, purposes and methods of scientific activity, the ambivalence of scientific research and the concomitant risks, and the conflict between research freedom and external socio-political intervention. We then point out the impediments to the effectiveness of cross-disciplinary or broader meetings for addressing these complex problems and managing the associated risks, given the difficulty in communication between experts in different fields and non-experts, difficulties that education is challenged to help resolve. We find that the social necessity of informed decision-making on the basis of cross-disciplinary collaboration is reflected in the newer curricula, such as that of Greece, in aims like the acquisition of cross-subject knowledge and skills, and the ability to make decisions on controversial issues involving value conflicts. The interest and the reflections of the science education community in these matters increase its—traditionally limited—contribution to the theoretical debate on education and, by extension, the value of science education in the education system.

Using Science Driven Technologies for the Defense and Security Applications

NASA Technical Reports Server (NTRS)

Habib, Shahid; Zukor, Dorthy; Ambrose, Stephen D.

2004-01-01

For the past three decades, Earth science remote sensing technologies have been providing enormous amounts of useful data and information in broadening our understanding of our home planet as a system. This research, as it has expanded our learning process, has also generated additional questions. This has further resulted in establishing new science requirements, which have culminated in defining and pushing the state-of-the-art technology needs. NASA s Earth science program has deployed 18 highly complex satellites, with a total of 80 sensors, so far and is in a process of defining and launching multiple observing systems in the next decade. Due to the heightened security alert of the nation, researchers and technologists are paying serious attention to the use of these science driven technologies for dual use. In other words, how such sophisticated observing and measuring systems can be used in detecting multiple types of security concerns with a substantial lead time so that the appropriate law enforcement agencies can take adequate steps to defuse any potential risky scenarios. This paper examines numerous NASA technologies such as laser/lidar systems, microwave and millimeter wave technologies, optical observing systems, high performance computational techniques for rapid analyses, and imaging products that can have a tremendous pay off for security applications.

The fusion of biology, computer science, and engineering: towards efficient and successful synthetic biology.

PubMed

Linshiz, Gregory; Goldberg, Alex; Konry, Tania; Hillson, Nathan J

2012-01-01

Synthetic biology is a nascent field that emerged in earnest only around the turn of the millennium. It aims to engineer new biological systems and impart new biological functionality, often through genetic modifications. The design and construction of new biological systems is a complex, multistep process, requiring multidisciplinary collaborative efforts from "fusion" scientists who have formal training in computer science or engineering, as well as hands-on biological expertise. The public has high expectations for synthetic biology and eagerly anticipates the development of solutions to the major challenges facing humanity. This article discusses laboratory practices and the conduct of research in synthetic biology. It argues that the fusion science approach, which integrates biology with computer science and engineering best practices, including standardization, process optimization, computer-aided design and laboratory automation, miniaturization, and systematic management, will increase the predictability and reproducibility of experiments and lead to breakthroughs in the construction of new biological systems. The article also discusses several successful fusion projects, including the development of software tools for DNA construction design automation, recursive DNA construction, and the development of integrated microfluidics systems.

A Second Chance: What can informal science learning institutions uniquely contribute to public inquiry about climate change? (Invited)

NASA Astrophysics Data System (ADS)

Bartels, D.

2009-12-01

The science of climate change is complicated. Even for adult audiences, scientific ideas such as non-linear modeling, probability and uncertainty, complexity and multivariate relationships, and the dynamic relationship between physical and human systems were not part of the typical curriculum for most of us in school. Moreover, many adults are invested in the myth that the aim of scientists is “truth-seeking” as opposed to finding the best interpretation that fits the best available empirical data. Science too often is presented even to adults as sets of answers and certainties. The forthcoming “Green Book” from the NSF Advisory Committee on Environmental Research and Education makes a novel recommendation that in these times adult environmental science literacy is as critical as education programs for K-12 and university students. Its reasoning is the stakes regarding the most pressing global environmental issues of our day—climate change chief among them—likely require such significant change in human behavior in the immediate term that it cannot wait for another generation of children to grow up. Practices and behaviors must change immediately. The report identifies the approximately 15,000 informal science learning institutions across the United States as the perfect adult science education delivery system to address this challenge. However, for the informal science learning community to engage this challenge most effectively, it must take care in its response given the complexity of the science, even for adults. It cannot perpetuate the idea of science as static and certain or separate itself from the social sciences. Yet the scientific community has very important stories to tell which have an immediate urgency to humankind. How do you explain the importance of uncertainty and science as a process while at the same time conveying confidence about scientific consensus where it exists? We will discuss ways of framing these important questions about adult learning and the science of climate change to assist scientists, informal science learning institutions and others increase the probability of enhanced credibility, understanding and action on the part of those of us beyond our school years.

Pedotransfer functions in Earth system science: challenges and perspectives

NASA Astrophysics Data System (ADS)

Van Looy, K.; Minasny, B.; Nemes, A.; Verhoef, A.; Weihermueller, L.; Vereecken, H.

2017-12-01

We make a stronghold for a new generation of Pedotransfer functions (PTFs) that is currently developed in the different disciplines of Earth system science, offering strong perspectives for improvement of integrated process-based models, from local to global scale applications. PTFs are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. To meet the methodological challenges for a successful application in Earth system modeling, we highlight how PTF development needs to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly capture the spatial heterogeneity of soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration and organic carbon content, root density and vegetation water uptake. We present an outlook and stepwise approach to the development of a comprehensive set of PTFs that can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques and soil information availability provide a true breakthrough for this, yet further improvements are necessary in three domains: 1) the determining of unknown relationships and dealing with uncertainty in Earth system modeling; 2) the step of spatially deploying this knowledge with PTF validation at regional to global scales; and 3) the integration and linking of the complex model parameterizations (coupled parameterization). Integration is an achievable goal we will show.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering.

PubMed

Groen, Nathalie; Guvendiren, Murat; Rabitz, Herschel; Welsh, William J; Kohn, Joachim; de Boer, Jan

2016-04-01

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. In this opinion paper, we postulate that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. Copyright © 2016. Published by Elsevier Ltd.

Ferrocene-containing non-interlocked molecular machines.

PubMed

Scottwell, Synøve Ø; Crowley, James D

2016-02-11

Ferrocene is the prototypical organometallic sandwich complex and despite over 60 years passing since the discovery and elucidation of ferrocene's structure, research into ferrocene-containing compounds continues to grow as potential new applications in catalysis, biology and the material sciences are found. Ferrocene is chemically robust and readily functionalized which enables its facile incorporation into more complex molecular systems. This coupled with ferrocene's reversible redox properties and ability function as a "molecular ball bearing" has led to the use of ferrocene as a component in wide range of interlocked and non-interlocked synthetic molecular machine systems. This review will focus on the exploitation of ferrocene (and related sandwich complexes) for the development of non-interlocked synthetic molecular machines.

Recurrence quantity analysis based on singular value decomposition

NASA Astrophysics Data System (ADS)

Bian, Songhan; Shang, Pengjian

2017-05-01

Recurrence plot (RP) has turned into a powerful tool in many different sciences in the last three decades. To quantify the complexity and structure of RP, recurrence quantification analysis (RQA) has been developed based on the measures of recurrence density, diagonal lines, vertical lines and horizontal lines. This paper will study the RP based on singular value decomposition which is a new perspective of RP study. Principal singular value proportion (PSVP) will be proposed as one new RQA measure and bigger PSVP means higher complexity for one system. In contrast, smaller PSVP reflects a regular and stable system. Considering the advantage of this method in detecting the complexity and periodicity of systems, several simulation and real data experiments are chosen to examine the performance of this new RQA.

Evolving Scale-Free Networks by Poisson Process: Modeling and Degree Distribution.

PubMed

Feng, Minyu; Qu, Hong; Yi, Zhang; Xie, Xiurui; Kurths, Jurgen

2016-05-01

Since the great mathematician Leonhard Euler initiated the study of graph theory, the network has been one of the most significant research subject in multidisciplinary. In recent years, the proposition of the small-world and scale-free properties of complex networks in statistical physics made the network science intriguing again for many researchers. One of the challenges of the network science is to propose rational models for complex networks. In this paper, in order to reveal the influence of the vertex generating mechanism of complex networks, we propose three novel models based on the homogeneous Poisson, nonhomogeneous Poisson and birth death process, respectively, which can be regarded as typical scale-free networks and utilized to simulate practical networks. The degree distribution and exponent are analyzed and explained in mathematics by different approaches. In the simulation, we display the modeling process, the degree distribution of empirical data by statistical methods, and reliability of proposed networks, results show our models follow the features of typical complex networks. Finally, some future challenges for complex systems are discussed.

Engineering science research issues in high power density transmission dynamics for aerospace applications. [rotorcraft geared rotors

NASA Technical Reports Server (NTRS)

Singh, Rajendra; Houser, Donald R.

1993-01-01

This paper discusses analytical and experimental approaches that will be needed to understand dynamic, vibro-acoustic and design characteristics of high power density rotorcraft transmissions. Complexities associated with mathematical modeling of such systems will be discussed. An overview of research work planned during the next several years will be presented, with emphasis on engineering science issues such as gear contact mechanics, multi-mesh drive dynamics, parameter uncertainties, vibration transmission through bearings, and vibro-acoustic characteristics of geared rotor systems and housing-mount structures. A few examples of work in progress are cited.

Collaborative adaptive rangeland management fosters management-science partnerships

USDA-ARS?s Scientific Manuscript database

Rangelands of the western Great Plains of North America are complex social-ecological systems where management objectives for livestock production, grassland bird conservation and vegetation structure and composition converge. The Collaborative Adaptive Rangeland Management (CARM) experiment is a 10...

The Computational Ecologist’s Toolbox

EPA Science Inventory

Computational ecology, nestled in the broader field of data science, is an interdisciplinary field that attempts to improve our understanding of complex ecological systems through the use of modern computational methods. Computational ecology is based on a union of competence in...

Behavior Models for Software Architecture

DTIC Science & Technology

2014-11-01

MP. Existing process modeling frameworks (BPEL, BPMN [Grosskopf et al. 2009], IDEF) usually follow the “single flowchart” paradigm. MP separates...Process: Business Process Modeling using BPMN , Meghan Kiffer Press. HAREL, D., 1987, A Visual Formalism for Complex Systems. Science of Computer

Implications of Aggregated DoD Information Systems for Information Assurance Certification and Accreditation

DTIC Science & Technology

2010-01-01

offshoring, or producing major software components overseas (Defense Science Board, 2009). These trends raise concerns about the level of trust that...7 Software Complexity...7 Increasing Software Vulnerabilities and Malware Population . . . . . . . . . . . . . . . . 9 Limitations of

Prediction in complex systems: The case of the international trade network

NASA Astrophysics Data System (ADS)

Vidmer, Alexandre; Zeng, An; Medo, Matúš; Zhang, Yi-Cheng

2015-10-01

Predicting the future evolution of complex systems is one of the main challenges in complexity science. Based on a current snapshot of a network, link prediction algorithms aim to predict its future evolution. We apply here link prediction algorithms to data on the international trade between countries. This data can be represented as a complex network where links connect countries with the products that they export. Link prediction techniques based on heat and mass diffusion processes are employed to obtain predictions for products exported in the future. These baseline predictions are improved using a recent metric of country fitness and product similarity. The overall best results are achieved with a newly developed metric of product similarity which takes advantage of causality in the network evolution.

PREFACE: International & Interdisciplinary Workshop on Novel Phenomena in Integrated Complex Sciences: from Non-living to Living Systems

NASA Astrophysics Data System (ADS)

Yoshimura, Kazuyoshi; Ohta, Hiroto; Murase, Masatoshi; Nishimura, Kazuo

2012-03-01

In this workshop recent advancements in experiments and theories were discussed on magnetism and superconductivity, emergent phenomena in biological material, chemical properties and economic problems of non-living and living systems. The aim of the workshop was to discuss old, but also new problems from a multidisciplinary perspective, and to understand the general features behind diversity in condensed matter physics, experimental chemistry and physics in biology and economic science. The workshop was broadly based, and was titled 'International & Interdisciplinary Workshop on Novel Phenomena in Integrated Complex Sciences from Non-living to Living Systems'. However, the primary focus was on magnetism and superconductivity, and NMR research into strongly correlated electrons. The meeting was held as an ICAM workshop, upon official approval in January 2010. Both young scientists and graduate students were invited. We hope that these young scientists had the chance to talk with invited speakers and organizers on their own interests. We thank the participants who contributed through their presentations, discussions and these papers to the advancement of the subject and our understanding. The proceedings are published here in the Journal of Physics: Conference Series (UK). We thank the International Advisory Committee for their advice and guidance: Evgeny Antipov Moscow State University, Russia Nicholas Curro University of California, Davis, USA Minghu Fang Zhejiang University, China Jurgen Haase University of Leipzig, Germany Takashi Imai McMaster University, Canada Peter Lemmens TU Braunschweig, Germany Herwig Michor Vienna TU, Austria Takamasa Momose University of British Columbia, Canada Raivo Stern NICPB, Estonia Louis Taillefer University of Sherbrooke, Canada Masashi Takigawa University of Tokyo, Japan This workshop was mainly organized by the International Research Unit of Integrated Complex System Science, Kyoto University, and was supported by ICAM (Institute for Complex and Adaptive Matter, USA), Yukawa Institute for Theoretical Physics (Kyoto University), Institute of Economic Research (Kyoto University) and Kyoto University GCOEs (Global Centers Of Excellence: Physics, Chemistry, and Economics). The workshop was also supported by Niki Glass Company Ltd., THAMWAY Corp., TAIYO NIPPON SANSO, and Quantum Design Japan. The Editors and the Organizing Committee, Masatoshi Murase Kyoto University, Japan Kazuo Nishimura Kyoto University, Japan Kazuyoshi Yoshimura Kyoto University, Japan: Conference Chairman and Chief Editor Hiroto Ohta Kyoto University, Tokyo University of A&T, Japan: Conference Secretary Conference Photograph, 14 October 2010 Conference Photograph Conference Poster Conference Poster

Mineral Surface Reactivity in teaching of Science Materials

NASA Astrophysics Data System (ADS)

Del Hoyo Martínez, Carmen

2013-04-01

In the last fifty years, science materials issues has required the study of air pollution, water and soil to prevent and remedy the adverse effects of waste originating from anthropogenic activity and the development of new energies and new materials. The teaching of this discipline has been marked by lectures on general lines, materials, disciplines, who explained biased objects of reality, but often forgot the task of reconstruction and integration of such visions. Moving from that model, otherwise quite static, to a dynamic relational model, would in our view, a real revolution in education. This means taking a systematic approach to complex both in interpreting reality and in favor when learning. Children relationships are as important or more than single objects, and it is to discover fundamental organizational principles of phenomena we seek to interpret or in other words, find the pattern that connects. Thus, we must work on relationships and also take into account the relation between the observer and the observed. Educate about relationships means that studies should always be considered within a framework of probabilities, not absolute certainties. This model of systemic thinking, dealing with complexity, is a possibility to bring coherence to our educational work, because the complexity is not taught, complexity is live, so that complex thinking is extended (and fed) in a form educate complex. It is the task of teaching to help people move from level to level of decision reviews. This means that systems thinking should be extended in a local action, action that engages the individual and the environment. Science Materials has emerged as a discipline of free choice for pupils attending chemical engineering which has been assigned 6.0 credits. The chemical engineer's professional profile within the current framework is defined as a professional knowledge as a specialization technical / functional, working in a learning organization and the formation of which enables him to continuous innovation. Different materials are used in the adsorption and improvement and design of new adsorbents, most of whom remain under patent, so they do not know the procedures and products used, but in all cases the safety and / or biodegradability of materials used is an important issue in their choice for environmental applications. In regard to materials, safe and low cost must be mentioned clays and clay minerals, whose colloidal properties, ease of generating structural changes, abundance in nature, and low cost make them very suitable for adsorption chemical contaminants. We proposed to use these materials to show the different aspects for the study of the Science Materials. References -del Hoyo, C. (2007b). Layered Double Hydroxides and human health: An overview. Applied Clay Science. 36, 103-121. -Konta, J. (1995). Clay and man: Clay raw materials in the service of man. Applied Clay Science. 10, 275-335. -Volzone, C. (2007). Retention of pollutant gases: Comparison between clay minerals and their modified products. Applied Clay Science. 36, 191-196.

An atom is known by the company it keeps: Content, representation and pedagogy within the epistemic revolution of the complexity sciences

NASA Astrophysics Data System (ADS)

Blikstein, Paulo

The goal of this dissertation is to explore relations between content, representation, and pedagogy, so as to understand the impact of the nascent field of complexity sciences on science, technology, engineering and mathematics (STEM) learning. Wilensky & Papert coined the term "structurations" to express the relationship between knowledge and its representational infrastructure. A change from one representational infrastructure to another they call a "restructuration." The complexity sciences have introduced a novel and powerful structuration: agent-based modeling. In contradistinction to traditional mathematical modeling, which relies on equational descriptions of macroscopic properties of systems, agent-based modeling focuses on a few archetypical micro-behaviors of "agents" to explain emergent macro-behaviors of the agent collective. Specifically, this dissertation is about a series of studies of undergraduate students' learning of materials science, in which two structurations are compared (equational and agent-based), consisting of both design research and empirical evaluation. I have designed MaterialSim, a constructionist suite of computer models, supporting materials and learning activities designed within the approach of agent-based modeling, and over four years conducted an empirical inves3 tigation of an undergraduate materials science course. The dissertation is comprised of three studies: Study 1 - diagnosis . I investigate current representational and pedagogical practices in engineering classrooms. Study 2 - laboratory studies. I investigate the cognition of students engaging in scientific inquiry through programming their own scientific models. Study 3 - classroom implementation. I investigate the characteristics, advantages, and trajectories of scientific content knowledge that is articulated in epistemic forms and representational infrastructures unique to complexity sciences, as well as the feasibility of the integration of constructionist, agent-based learning environments in engineering classrooms. Data sources include classroom observations, interviews, videotaped sessions of model-building, questionnaires, analysis of computer-generated logfiles, and quantitative and qualitative analysis of artifacts. Results shows that (1) current representational and pedagogical practices in engineering classrooms were not up to the challenge of the complex content being taught, (2) by building their own scientific models, students developed a deeper understanding of core scientific concepts, and learned how to better identify unifying principles and behaviors in materials science, and (3) programming computer models was feasible within a regular engineering classroom.

Reconfigurable Computing for Computational Science: A New Focus in High Performance Computing

DTIC Science & Technology

2006-11-01

in the past decade. Researchers are regularly employing the power of large computing systems and parallel processing to tackle larger and more...complex problems in all of the physical sciences. For the past decade or so, most of this growth in computing power has been “free” with increased...the scientific computing community as a means to continued growth in computing capability. This paper offers a glimpse of the hardware and

Expert systems for superalloy studies

NASA Technical Reports Server (NTRS)

Workman, Gary L.; Kaukler, William F.

1990-01-01

There are many areas in science and engineering which require knowledge of an extremely complex foundation of experimental results in order to design methodologies for developing new materials or products. Superalloys are an area which fit well into this discussion in the sense that they are complex combinations of elements which exhibit certain characteristics. Obviously the use of superalloys in high performance, high temperature systems such as the Space Shuttle Main Engine is of interest to NASA. The superalloy manufacturing process is complex and the implementation of an expert system within the design process requires some thought as to how and where it should be implemented. A major motivation is to develop a methodology to assist metallurgists in the design of superalloy materials using current expert systems technology. Hydrogen embrittlement is disasterous to rocket engines and the heuristics can be very complex. Attacking this problem as one module in the overall design process represents a significant step forward. In order to describe the objectives of the first phase implementation, the expert system was designated Hydrogen Environment Embrittlement Expert System (HEEES).

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

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

Neptune and Triton: A Study in Future Exploration

NASA Astrophysics Data System (ADS)

Day, M. D.; Malaska, M. J.; Hosseini, S.; Mcgranaghan, R.; Fernandes, P. A.; Fougere, N.; Clegg, R. N.; Scully, J.; Alibay, F.; Ries, P.; Craig, P. L.; Hutchins, M. L.; Leonard, J.; Uckert, K.; Patthoff, A.; Girazian, Z.

2013-12-01

Neptune provides a unique natural laboratory for studying the dynamics of ice giants. Last visited by Voyager 2 in 1989, Neptune and its moon Triton hold important clues to the evolution of the solar system. The Voyager 2 flyby revealed Neptune to be a dynamic world with large storms, unparalleled wind speeds, and an unusual magnetic field. Triton, Neptune's largest satellite, is believed to be a captured Kuiper Belt Object with a thin atmosphere and possible sub-surface ocean. Further study of the farthest planet in our solar system could offer new insights into the dynamics of ice-giant exoplanets, and help us understand their complex atmospheres. The diverse science questions associated with Neptune and Triton motivate the complex and exciting mission proposed in this study. The proposed mission follows the guidelines of the 2013-2022 Planetary Science Decadal Survey, and optimizes the number of high priority science goals achieved, while still maintaining low mission costs. High priority science goals include understanding the structure, composition, and dynamics of Neptune's atmosphere and magnetosphere, as well as analyzing the surface of Triton. With a budget of $1.5 billion, the mission hosts an atmospheric probe and suite of instruments equipped with technologies significantly more advanced than those carried by Voyager 2. Additionally, the mission offers improved spatial coverage and higher resolution measurements than any previously achieved at Neptune. The proposed spacecraft would complete an orbital tour of Neptune and execute several close flybys of Triton. Further study of Neptune and Triton will provide exciting insights into what lies on the edge of our solar system and beyond. This study was prepared in conjunction with Jet Propulsion Laboratory's 2013 Planetary Science Summer School.

Towards a comprehensive understanding of emerging dynamics and function of pancreatic islets: A complex network approach. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

NASA Astrophysics Data System (ADS)

Loppini, Alessandro

2018-03-01

Complex network theory represents a comprehensive mathematical framework to investigate biological systems, ranging from sub-cellular and cellular scales up to large-scale networks describing species interactions and ecological systems. In their exhaustive and comprehensive work [1], Gosak et al. discuss several scenarios in which the network approach was able to uncover general properties and underlying mechanisms of cells organization and regulation, tissue functions and cell/tissue failure in pathology, by the study of chemical reaction networks, structural networks and functional connectivities.

Cohort: critical science

NASA Astrophysics Data System (ADS)

Digney, Bruce L.

2007-04-01

Unmanned vehicle systems is an attractive technology for the military, but whose promises have remained largely undelivered. There currently exist fielded remote controlled UGVs and high altitude UAV whose benefits are based on standoff in low complexity environments with sufficiently low control reaction time requirements to allow for teleoperation. While effective within there limited operational niche such systems do not meet with the vision of future military UxV scenarios. Such scenarios envision unmanned vehicles operating effectively in complex environments and situations with high levels of independence and effective coordination with other machines and humans pursing high level, changing and sometimes conflicting goals. While these aims are clearly ambitious they do provide necessary targets and inspiration with hopes of fielding near term useful semi-autonomous unmanned systems. Autonomy involves many fields of research including machine vision, artificial intelligence, control theory, machine learning and distributed systems all of which are intertwined and have goals of creating more versatile broadly applicable algorithms. Cohort is a major Applied Research Program (ARP) led by Defence R&D Canada (DRDC) Suffield and its aim is to develop coordinated teams of unmanned vehicles (UxVs) for urban environments. This paper will discuss the critical science being addressed by DRDC developing semi-autonomous systems.

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

NASA Astrophysics Data System (ADS)

Bourgine, P.; Johnson, J.

2009-04-01

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

The Emparassment of Complexity

NASA Astrophysics Data System (ADS)

Nowotny, Helga

My vision of complexity sciences targets their potential to extend the range, precision, and depth in making predictions. While this has always been the ambition and yardstick for the physicalmathematical sciences, complexity sciences now allow to include society and social behavior - to some extent. There is agreement that society is a complex adaptive system, CAS, with a few peculiarities. Ignoring, downplaying, or naturalizing them, i.e. to take them as essential and given, carries the risk to end up with abstractions which are cutoff from the dynamics of societal contexts. One of the peculiarities of society as a CAS is that the models with which we try to make sense of the world are invented and constructed by us. It is humans who make observations and provide the assumptions on which models are based. Humans leave traces that are collected and processed to be transformed into data. Humans decide to which purpose they will be put and how they will be repurposed. Humans are object of research and subject. Coping with these peculiarities requires an inbuilt reflexivity. Practioners must perform a double act and do so repeatedly. They must engage in a focused way with their scientific work and equally distance themselves by critically reflecting their often tacit assumptions. A friend of mine, Yehuda Elkana, called this twotier thinking...

Ultralight Weight Optical Systems Using Nano-Layered Synthesized Materials

NASA Technical Reports Server (NTRS)

Clark, Natalie; Breckinridge, James

2014-01-01

Optical imaging is important for many NASA science missions. Even though complex optical systems have advanced, the optics, based on conventional glass and mirrors, require components that are thick, heavy and expensive. As the need for higher performance expands, glass and mirrors are fast approaching the point where they will be too large, heavy and costly for spacecraft, especially small satellite systems. NASA Langley Research Center is developing a wide range of novel nano-layered synthesized materials that enable the development and fabrication of ultralight weight optical device systems that enable many NASA missions to collect science data imagery using small satellites. In addition to significantly reducing weight, the nano-layered synthesized materials offer advantages in performance, size, and cost.

Understanding health systems, health economies and globalization: the need for social science perspectives.

PubMed

Murray, Susan F; Bisht, Ramila; Baru, Rama; Pitchforth, Emma

2012-08-31

The complex relationship between globalization and health calls for research from many disciplinary and methodological perspectives. This editorial gives an overview of the content trajectory of the interdisciplinary journal 'Globalization and Health' over the first six years of production, 2005 to 2010. The findings show that bio-medical and population health perspectives have been dominant but that social science perspectives have become more evident in recent years. The types of paper published have also changed, with a growing proportion of empirical studies. A special issue on 'Health systems, health economies and globalization: social science perspectives' is introduced, a collection of contributions written from the vantage points of economics, political science, psychology, sociology, business studies, social policy and research policy. The papers concern a range of issues pertaining to the globalization of healthcare markets and governance and regulation issues. They highlight the important contribution that can be made by the social sciences to this field, and also the practical and methodological challenges implicit in the study of globalization and health.

Community Detection in Complex Networks via Clique Conductance.

PubMed

Lu, Zhenqi; Wahlström, Johan; Nehorai, Arye

2018-04-13

Network science plays a central role in understanding and modeling complex systems in many areas including physics, sociology, biology, computer science, economics, politics, and neuroscience. One of the most important features of networks is community structure, i.e., clustering of nodes that are locally densely interconnected. Communities reveal the hierarchical organization of nodes, and detecting communities is of great importance in the study of complex systems. Most existing community-detection methods consider low-order connection patterns at the level of individual links. But high-order connection patterns, at the level of small subnetworks, are generally not considered. In this paper, we develop a novel community-detection method based on cliques, i.e., local complete subnetworks. The proposed method overcomes the deficiencies of previous similar community-detection methods by considering the mathematical properties of cliques. We apply the proposed method to computer-generated graphs and real-world network datasets. When applied to networks with known community structure, the proposed method detects the structure with high fidelity and sensitivity. When applied to networks with no a priori information regarding community structure, the proposed method yields insightful results revealing the organization of these complex networks. We also show that the proposed method is guaranteed to detect near-optimal clusters in the bipartition case.

A numerical study of coarsening in the two-dimensional complex Ginzburg-Landau equation

NASA Astrophysics Data System (ADS)

Liu, Weigang; Tauber, Uwe

The complex Ginzburg-Landau equation with additive noise is a stochastic partial differential equation that describes a remarkably wide range of physical systems: coupled non-linear oscillators subject to external noise near a Hopf bifurcation instability; spontaneous structure formation in non-equilibrium systems, e.g., in cyclically competing populations; and driven-dissipative Bose-Einstein condensation, realized in open systems on the interface of quantum optics and many-body physics. We employ a finite-difference method to numerically solve the noisy complex Ginzburg-Landau equation on a two-dimensional domain with the goal to investigate the coarsening dynamics following a quench from a strongly fluctuating defect turbulence phase to a long-range ordered phase. We start from a simplified amplitude equation, solve it numerically, and then study the spatio-temporal behavior characterized by the spontaneous creation and annihilation of topological defects (spiral waves). We check our simulation results against the known dynamical phase diagram in this non-equilibrium system, tentatively analyze the coarsening kinetics following sudden quenches, and characterize the ensuing aging scaling behavior. In addition, we aim to use Voronoi triangulation to study the cellular structure in the phase turbulence and frozen states. This research is supported by the U. S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Science and Engineering under Award DE-FG02-09ER46613.

The impact of network medicine in gastroenterology and hepatology.

PubMed

Baffy, György

2013-10-01

In the footsteps of groundbreaking achievements made by biomedical research, another scientific revolution is unfolding. Systems biology draws from the chaos and complexity theory and applies computational models to predict emerging behavior of the interactions between genes, gene products, and environmental factors. Adaptation of systems biology to translational and clinical sciences has been termed network medicine, and is likely to change the way we think about preventing, predicting, diagnosing, and treating complex human diseases. Network medicine finds gene-disease associations by analyzing the unparalleled digital information discovered and created by high-throughput technologies (dubbed as "omics" science) and links genetic variance to clinical disease phenotypes through intermediate organizational levels of life such as the epigenome, transcriptome, proteome, and metabolome. Supported by large reference databases, unprecedented data storage capacity, and innovative computational analysis, network medicine is poised to find links between conditions that were thought to be distinct, uncover shared disease mechanisms and key drivers of the pathogenesis, predict individual disease outcomes and trajectories, identify novel therapeutic applications, and help avoid off-target and undesirable drug effects. Recent advances indicate that these perspectives are increasingly within our reach for understanding and managing complex diseases of the digestive system. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.

Drug Delivery Systems For Anti-Cancer Active Complexes of Some Coinage Metals.

PubMed

Zhang, Ming; Saint-Germain, Camille; He, Guiling; Sun, Raymond Wai-Yin

2018-02-12

Although cisplatin and a number of platinum complexes have widely been used for the treatment of neoplasia, patients receiving these treatments have frequently suffered from their severe toxic side effects, the development of resistance with consequent relapse. In the recent decades, numerous complexes of coinage metals including that of gold, copper and silver have been reported to display promising in vitro and/or in vivo anti-cancer activities as well as potent activities towards cisplatin-resistant tumors. Nevertheless, the medical development of these metal complexes has been hampered by their instability in aqueous solutions and the nonspecific binding in biological systems. One of the approaches to overcome these problems is to design and develop adequate drug delivery systems (DDSs) for the transport of these complexes. By functionalization, encapsulation or formulation of the metal complexes, several types of DDSs have been reported to improve the desired pharmacological profile of the metal complexes, improving their overall stability, bioavailability, anti-cancer activity and reducing their toxicity towards normal cells. In this review, we summarized the recent findings for different DDSs for various anti- cancer active complexes of some coinage metals. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

KSC-2014-3130

NASA Image and Video Library

2014-07-03

CAPE CANAVERAL, Fla. – Former NASA astronaut Tom Jones, left, presses the button on a simulated model of an asteroid to mark the grand opening of the new Great Balls of Fire exhibit at NASA’s Kennedy Space Center Visitor Complex in Florida. To his right is Therrin Protze, chief operating officer with Delaware North Parks and Resorts at the visitor complex. Great Balls of Fire shares the story of the origins of our solar system, asteroids and comets and their possible impacts and risks. The 1,500-square-foot exhibit, located in the East Gallery of the IMAX theatre at the visitor complex, features several interactive displays, real meteorites and replica asteroid models. The exhibit is a production of The Space Science Institute's National Center for Interactive Learning. It is a traveling exhibition that also receives funding from NASA and the National Science Foundation. Photo credit: NASA/Daniel Casper

KSC-2014-3137

NASA Image and Video Library

2014-07-03

CAPE CANAVERAL, Fla. – The grand opening of the new Great Balls of Fire exhibit was held at NASA’s Kennedy Space Center Visitor Complex in Florida. The grand opening featured remarks by former NASA astronaut Tom Jones, and Therrin Protze, chief operating officer at Delaware North Parks and Resorts at the visitor complex. Informational displays about future NASA exploration missions are featured along the wall of the new exhibit. Great Balls of Fire shares the story of the origins of our solar system, asteroids and comets and their possible impacts and risks. The 1,500-square-foot exhibit, located in the East Gallery of the IMAX theatre at the visitor complex, features several interactive displays, real meteorites and replica asteroid models. The exhibit is a production of The Space Science Institute's National Center for Interactive Learning. It is a traveling exhibition that also receives funding from NASA and the National Science Foundation. Photo credit: NASA/Daniel Casper

KSC-2014-3135

NASA Image and Video Library

2014-07-03

CAPE CANAVERAL, Fla. – Samples of Earth rocks and real meteorites are featured in an interactive display at the new Great Balls of Fire exhibit at NASA’s Kennedy Space Center Visitor Complex in Florida. The grand opening featured remarks by former NASA astronaut Tom Jones, and Therrin Protze, chief operating officer at Delaware North Parks and Resorts at the visitor complex. Great Balls of Fire shares the story of the origins of our solar system, asteroids and comets and their possible impacts and risks. The 1,500-square-foot exhibit, located in the East Gallery of the IMAX theatre at the visitor complex, features several interactive displays, real meteorites and replica asteroid models. The exhibit is a production of The Space Science Institute's National Center for Interactive Learning. It is a traveling exhibition that also receives funding from NASA and the National Science Foundation. Photo credit: NASA/Daniel Casper

Playful and mindful interactions in the recursive adaptations of the zone of proximal development: a critical complexity science approach

NASA Astrophysics Data System (ADS)

Raia, Federica; Deng, Mario C.

2011-12-01

We discuss Konstantinos Alexakos, Jayson Jones and Victor Rodriguez's hermeneutic study of formation and function of kinship-like relationships among inner city male students of color in a college physics classroom. From our Critical Complexity Science framework we first discuss the reading erlebnisse of students laughing at and with each other as something that immediately captured our attention in being transformative of the classroom. We continue by exploring their classroom and research experience as an emergent structure modifying their collective as well as their individual experiences. As we analyze both the classroom and the research space as a complex system, we reflect on the instructor/students interactions characterized by an asymmetrical "power" relationship. From our analysis we propose to consider the zone of proximal development as the constantly emerging and transforming person experience ( erlebnisse and erfahrung).

A causal framework for integrating contemporary and Vedic holism.

PubMed

Kineman, John J

2017-12-01

Whereas the last Century of science was characterized by epistemological uncertainty; the current Century will likely be characterized by ontological complexity (Gorban and Yablonsky, 2013). Advances in Systems Theory by mathematical biologist Robert Rosen suggest an elegant way forward (Rosen, 2013). "R-theory" (Kineman, 2012) is a synthesis of Rosen's theories explaining complexity and life in terms of a meta-model for 'whole' systems (and their fractions) in terms of "5 th -order holons". Such holons are Rosen "modeling relations" relating system-dependent processes with their formative contexts via closed cycles of four archetypal (Aristotelian) causes. This approach has post-predicted the three most basic taxa of life, plus a quasi-organismic form that may describe proto, component, and ecosystemic life. R-theory thus suggests a fundamentally complex ontology of existence inverting the current view that complexity arises from simple mechanisms. This model of cyclical causality corresponds to the ancient meta-model described in the Vedas and Upanishads of India. Part I of this discussion (Kineman, 2016a) presented a case for associating Vedic philosophy with Harappan civilization, allowing interpretation of ancient concepts of "cosmic order" (Rta) in the Rig Veda, nonduality (advaita), seven-fold beingness (saptanna) and other forms of holism appearing later in the Upanishads. By deciphering the model of wholeness that was applied and tested in ancient times, it is possible to compare, test, and confirm the holon model as a mathematical definition of life, systemic wholeness, and sustainability that may be applied today in modern terms, even as a foundation for holistic science. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2018-03-09

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

Environmental Nutrition: A New Frontier for Public Health

PubMed Central

Sabaté, Joan; Soret, Samuel

2016-01-01

Food systems must operate within environmental constraints to avoid disastrous consequences for the biosphere. Such constraints must also take into account nutritional quality and health outcomes. Given the intrinsic relationships between the environmental sciences and nutritional sciences, it is imperative that public health embraces environmental nutrition as the new frontier of research and practice and begins a concerted focus on the new discipline of environmental nutrition, which seeks to comprehensively address the sustainability of food systems. We provide an overview to justify our proposition, outline a research and practice agenda for environmental nutrition, and explore how the complex relationships within food systems that affect public health could be better understood through the environmental nutrition model. PMID:26985617

The Galileo attitude and articulation control system - A radiation-hard, high precision, state-of-the-art control system

NASA Technical Reports Server (NTRS)

Stephenson, R. Rhoads

1985-01-01

The Galileo mission and spacecraft, consisting of a Jupiter-orbiter and an atmospheric entry probe, are discussed. Components will include: magnetometers and plasma-wave antennas on a boom, high-gain antenna, probe vehicle, two different bus electronics packages, and a radioisotope thermoelectric generator. Instruments, investigators and objectives are tabulated for both probe science and orbiter science investigations. Requirements in the design of the attitude and articulation control system are very stringent because of the complex dynamics, flexible body effects, the need for autonomy, and the severe radiation environment in the Jupiter nighborhood. Galileo was intended to be ready for launch via Space Shuttle in May of 1986.

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…

Opportunities and challenges for the life sciences community.

PubMed

Kolker, Eugene; Stewart, Elizabeth; Ozdemir, Vural

2012-03-01

Twenty-first century life sciences have transformed into data-enabled (also called data-intensive, data-driven, or big data) sciences. They principally depend on data-, computation-, and instrumentation-intensive approaches to seek comprehensive understanding of complex biological processes and systems (e.g., ecosystems, complex diseases, environmental, and health challenges). Federal agencies including the National Science Foundation (NSF) have played and continue to play an exceptional leadership role by innovatively addressing the challenges of data-enabled life sciences. Yet even more is required not only to keep up with the current developments, but also to pro-actively enable future research needs. Straightforward access to data, computing, and analysis resources will enable true democratization of research competitions; thus investigators will compete based on the merits and broader impact of their ideas and approaches rather than on the scale of their institutional resources. This is the Final Report for Data-Intensive Science Workshops DISW1 and DISW2. The first NSF-funded Data Intensive Science Workshop (DISW1, Seattle, WA, September 19-20, 2010) overviewed the status of the data-enabled life sciences and identified their challenges and opportunities. This served as a baseline for the second NSF-funded DIS workshop (DISW2, Washington, DC, May 16-17, 2011). Based on the findings of DISW2 the following overarching recommendation to the NSF was proposed: establish a community alliance to be the voice and framework of the data-enabled life sciences. After this Final Report was finished, Data-Enabled Life Sciences Alliance (DELSA, www.delsall.org ) was formed to become a Digital Commons for the life sciences community.

Opportunities and Challenges for the Life Sciences Community

PubMed Central

Stewart, Elizabeth; Ozdemir, Vural

2012-01-01

Abstract Twenty-first century life sciences have transformed into data-enabled (also called data-intensive, data-driven, or big data) sciences. They principally depend on data-, computation-, and instrumentation-intensive approaches to seek comprehensive understanding of complex biological processes and systems (e.g., ecosystems, complex diseases, environmental, and health challenges). Federal agencies including the National Science Foundation (NSF) have played and continue to play an exceptional leadership role by innovatively addressing the challenges of data-enabled life sciences. Yet even more is required not only to keep up with the current developments, but also to pro-actively enable future research needs. Straightforward access to data, computing, and analysis resources will enable true democratization of research competitions; thus investigators will compete based on the merits and broader impact of their ideas and approaches rather than on the scale of their institutional resources. This is the Final Report for Data-Intensive Science Workshops DISW1 and DISW2. The first NSF-funded Data Intensive Science Workshop (DISW1, Seattle, WA, September 19–20, 2010) overviewed the status of the data-enabled life sciences and identified their challenges and opportunities. This served as a baseline for the second NSF-funded DIS workshop (DISW2, Washington, DC, May 16–17, 2011). Based on the findings of DISW2 the following overarching recommendation to the NSF was proposed: establish a community alliance to be the voice and framework of the data-enabled life sciences. After this Final Report was finished, Data-Enabled Life Sciences Alliance (DELSA, www.delsall.org) was formed to become a Digital Commons for the life sciences community. PMID:22401659

Ontology patterns for complex topographic feature yypes

USGS Publications Warehouse

Varanka, Dalia E.

2011-01-01

Complex feature types are defined as integrated relations between basic features for a shared meaning or concept. The shared semantic concept is difficult to define in commonly used geographic information systems (GIS) and remote sensing technologies. The role of spatial relations between complex feature parts was recognized in early GIS literature, but had limited representation in the feature or coverage data models of GIS. Spatial relations are more explicitly specified in semantic technology. In this paper, semantics for topographic feature ontology design patterns (ODP) are developed as data models for the representation of complex features. In the context of topographic processes, component assemblages are supported by resource systems and are found on local landscapes. The topographic ontology is organized across six thematic modules that can account for basic feature types, resource systems, and landscape types. Types of complex feature attributes include location, generative processes and physical description. Node/edge networks model standard spatial relations and relations specific to topographic science to represent complex features. To demonstrate these concepts, data from The National Map of the U. S. Geological Survey was converted and assembled into ODP.

Social Determinants of Population Health: A Systems Sciences Approach

PubMed Central

Fink, David S.; Keyes, Katherine M.; Cerdá, Magdalena

2016-01-01

Population distributions of health emerge from the complex interplay of health-related factors at multiple levels, from the biological to the societal level. Individuals are aggregated within social networks, affected by their locations, and influenced differently across time. From aggregations of individuals, group properties can emerge, including some exposures that are ubiquitous within populations but variant across populations. By combining a focus on social determinants of health with a conceptual framework for understanding how genetics, biology, behavior, psychology, society, and environment interact, a systems science approach can inform our understanding of the underlying causes of the unequal distribution of health across generations and populations, and can help us identify promising approaches to reduce such inequalities. In this paper, we discuss how systems science approaches have already made several substantive and methodological contributions to the study of population health from a social epidemiology perspective. PMID:27642548

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

Physics transforming the life sciences.

PubMed

Onuchic, José N

2014-10-08

Biological physics is clearly becoming one of the leading sciences of the 21st century. This field involves the cross-fertilization of ideas and methods from biology and biochemistry on the one hand and the physics of complex and far from equilibrium systems on the other. Here I want to discuss how biological physics is a new area of physics and not simply applications of known physics to biological problems. I will focus in particular on the new advances in theoretical physics that are already flourishing today. They will become central pieces in the creation of this new frontier of science.

Complexity Science and Professional Learning for Collaboration: A Critical Reconsideration of Possibilities and Limitations

ERIC Educational Resources Information Center

Fenwick, Tara

2012-01-01

Professionals increasingly must collaborate very closely, such as through inter-professional work arrangements. This involves learning both "in" and "for" collaboration. Some educational researchers have turned to complexity science to better understand these learning dynamics. This discussion asks, How useful is complexity science for examining…

Reduction of Subjective and Objective System Complexity

NASA Technical Reports Server (NTRS)

Watson, Michael D.

2015-01-01

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

Developments of a new data acquisition system at ANNRI

NASA Astrophysics Data System (ADS)

Nakao, T.; Terada, K.; Kimura, A.; Nakamura, S.; Iwamoto, O.; Harada, H.; Katabuchi, T.; Igashira, M.; Hori, J.

2017-09-01

A new data acquisition system (DAQ system) has been developed at the Accurate Neutron-Nucleus Reaction Measurement Instrument (ANNRI) facility in the Japan Proton Accelerator Research Complex, Materials and Life Science Experimental Facility (J-PARC/MLF). DAQ systems for both the Ge detector system and the Li-glass detector system were tested by using a gold sample. The applicability of the time-of-flight method was checked. System performance was evaluated on the basis of digital conversion nonlinearity, energy resolution, multi-channel coincidence and dead time.

A transformative model for undergraduate quantitative biology education.

PubMed

Usher, David C; Driscoll, Tobin A; Dhurjati, Prasad; Pelesko, John A; Rossi, Louis F; Schleiniger, Gilberto; Pusecker, Kathleen; White, Harold B

2010-01-01

The BIO2010 report recommended that students in the life sciences receive a more rigorous education in mathematics and physical sciences. The University of Delaware approached this problem by (1) developing a bio-calculus section of a standard calculus course, (2) embedding quantitative activities into existing biology courses, and (3) creating a new interdisciplinary major, quantitative biology, designed for students interested in solving complex biological problems using advanced mathematical approaches. To develop the bio-calculus sections, the Department of Mathematical Sciences revised its three-semester calculus sequence to include differential equations in the first semester and, rather than using examples traditionally drawn from application domains that are most relevant to engineers, drew models and examples heavily from the life sciences. The curriculum of the B.S. degree in Quantitative Biology was designed to provide students with a solid foundation in biology, chemistry, and mathematics, with an emphasis on preparation for research careers in life sciences. Students in the program take core courses from biology, chemistry, and physics, though mathematics, as the cornerstone of all quantitative sciences, is given particular prominence. Seminars and a capstone course stress how the interplay of mathematics and biology can be used to explain complex biological systems. To initiate these academic changes required the identification of barriers and the implementation of solutions.

A Transformative Model for Undergraduate Quantitative Biology Education

PubMed Central

Driscoll, Tobin A.; Dhurjati, Prasad; Pelesko, John A.; Rossi, Louis F.; Schleiniger, Gilberto; Pusecker, Kathleen; White, Harold B.

2010-01-01

The BIO2010 report recommended that students in the life sciences receive a more rigorous education in mathematics and physical sciences. The University of Delaware approached this problem by (1) developing a bio-calculus section of a standard calculus course, (2) embedding quantitative activities into existing biology courses, and (3) creating a new interdisciplinary major, quantitative biology, designed for students interested in solving complex biological problems using advanced mathematical approaches. To develop the bio-calculus sections, the Department of Mathematical Sciences revised its three-semester calculus sequence to include differential equations in the first semester and, rather than using examples traditionally drawn from application domains that are most relevant to engineers, drew models and examples heavily from the life sciences. The curriculum of the B.S. degree in Quantitative Biology was designed to provide students with a solid foundation in biology, chemistry, and mathematics, with an emphasis on preparation for research careers in life sciences. Students in the program take core courses from biology, chemistry, and physics, though mathematics, as the cornerstone of all quantitative sciences, is given particular prominence. Seminars and a capstone course stress how the interplay of mathematics and biology can be used to explain complex biological systems. To initiate these academic changes required the identification of barriers and the implementation of solutions. PMID:20810949

Understanding and Meeting the Needs of Space Scientists in EPO—Survey Results, Responses, and Strategies

NASA Astrophysics Data System (ADS)

Grier, J.; Buxner, S.; Schneider, N.

2015-11-01

As science literacy is falling in the United States, our world continues to become more complex. Everyone now requires an understanding of science, technology, and the relationship of interconnected systems in order to successfully navigate the complex issues facing us. Scientists are a critical resource, bringing to the table an understanding of the nature of science as a process, as well as up-to-the-minute scientific content. They can function in a wide range of capacities in education and public outreach (EPO) to meet some of the learning challenges of teachers, students, and the general public. Societies that work directly with scientists, such as the American Astronomical Society (AAS) and the Division for Planetary Sciences (DPS) are interested in understanding how their member scientists view the act of reaching out, how they do it, and how the DPS can continue to support them as they engage with a variety of audiences in an EPO capacity. To this end, we (the NASA Science Mission Directorate Planetary Science Forum and DPS leadership) conducted a series of semi-structured interviews with a subsection of DPS members to learn more about their attitudes and needs, and to begin to pinpoint opportunities and strategies for future consideration. Presented here are our preliminary results and the ideas generated for further conversations.

Cassini Information Management System in Distributed Operations Collaboration and Cassini Science Planning

NASA Technical Reports Server (NTRS)

Equils, Douglas J.

2008-01-01

Launched on October 15, 1997, the Cassini-Huygens spacecraft began its ambitious journey to the Saturnian system with a complex suite of 12 scientific instruments, and another 6 instruments aboard the European Space Agencies Huygens Probe. Over the next 6 1/2 years, Cassini would continue its relatively simplistic cruise phase operations, flying past Venus, Earth, and Jupiter. However, following Saturn Orbit Insertion (SOI), Cassini would become involved in a complex series of tasks that required detailed resource management, distributed operations collaboration, and a data base for capturing science objectives. Collectively, these needs were met through a web-based software tool designed to help with the Cassini uplink process and ultimately used to generate more robust sequences for spacecraft operations. In 2001, in conjunction with the Southwest Research Institute (SwRI) and later Venustar Software and Engineering Inc., the Cassini Information Management System (CIMS) was released which enabled the Cassini spacecraft and science planning teams to perform complex information management and team collaboration between scientists and engineers in 17 countries. Originally tailored to help manage the science planning uplink process, CIMS has been actively evolving since its inception to meet the changing and growing needs of the Cassini uplink team and effectively reduce mission risk through a series of resource management validation algorithms. These algorithms have been implemented in the web-based software tool to identify potential sequence conflicts early in the science planning process. CIMS mitigates these sequence conflicts through identification of timing incongruities, pointing inconsistencies, flight rule violations, data volume issues, and by assisting in Deep Space Network (DSN) coverage analysis. In preparation for extended mission operations, CIMS has also evolved further to assist in the planning and coordination of the dual playback redundancy of highvalue data from targets such as Titan and Enceladus. This paper will outline the critical role that CIMS has played for Cassini in the distributed ops paradigm throughout operations. This paper will also examine the evolution that CIMS has undergone in the face of new science discoveries and fluctuating operational needs. And finally, this paper will conclude with theoretical adaptation of CIMS for other projects and the potential savings in cost and risk reduction that could potentially be tapped into by future missions.

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.

VQSEC Home Page

Science.gov Websites

Complex Water Impact Visitor Information Validation and Qualification Sciences Experimental Complex Our the problem space. The Validation and Qualification Sciences Experimental Complex (VQSEC) at Sandia

Toward a new system approach of complexity in geomorphology

NASA Astrophysics Data System (ADS)

Masson, E.

2012-04-01

Since three decades the conceptual vision of catchment and fluvial geomorphology is strongly based on the "fluvial system" (S. A. Schumm, 1977) and the "river continuum system" (R. L. Vannote et al., 1980) concepts that can be embedded in a classical physical "four dimensions system" (C. Amoros and G.-E. Petts, 1993). Catchment and network properties, sediment and water budgets and their time-space variations are playing a major role in this geomorpho-ecological approach of hydro-geomorphosystems in which human impacts are often considered as negative externalities. The European Water Framework Directive (i.e. WFD, Directive 2000/60/EC) and its objective of good environmental status is addressing the question of fluvial/catchment/landscape geomorphology and its integration into IWRM in such a sustainable way that deeply brings back society and social sciences into the water system analysis. The DPSIR methodology can be seen as an attempt to cope with the analysis of unsustainable consequences of society's water-sediment-landscape uses, environmental pressures and their consequences on complex fluvial dynamics. Although more and more scientific fields are engaged in this WFD objective there's still a lack of a global theory that could integrate geomorphology into the multi-disciplinary brainstorming discussion about sustainable use of water resources. Our proposition is to promote and discuss a trans-disciplinary approach of catchments and fluvial networks in which concepts can be broadly shared across scientific communities. The objective is to define a framework for thinking and analyzing geomorphological issues within a whole "Environmental and Social System" (i.e. ESS, E. Masson 2010) with a common set of concepts and "meta-concepts" that could be declined and adapted in any scientific field for any purpose connected with geomorphology. We assume that geomorphological research can benefit from a six dynamic dimensions system approach based on structures, functions, connections, phases, topologies and adaptations. By combining these six dimensions one can easily understand that geomorphological features and dynamics are then considered as very complex systems in which hierarchies, information, discontinuities, openness, resilience and self-organized responses are fundamental properties emerging among many others (E. Masson 2010). This conceptual approach is consistent with many other scientific concepts used in ecological sciences (S-E. Jorgensen et al. 2007, C-S. Holling and al. 2002, I. Prigogine 1997, W-M. Elsasser 1987…) but also in human sciences (A. Dauphiné 2003, Ch.P.Péguy 2001, P. Bourdieu 1987, U. Beck 1986, J. Tricart 1968, C. Levy-Strauss 1958…), in physics (P. Bak, 1996, K-R. Popper 1982, I. Prigogine 1955…) and obviously into systemic science (E. Morin 1977, J-L. Moigne 1977, L. Von Bertalanffy 1968). Our contribution is then an encouraging attempt to expand the frontier of geomorphological theory with a new trans-disciplinary approach that deals with the huge complexity of hydrosystems considered as a whole Environmental and Social System.

Systems thinking.

PubMed

Cabrera, Derek; Colosi, Laura; Lobdell, Claire

2008-08-01

Evaluation is one of many fields where "systems thinking" is popular and is said to hold great promise. However, there is disagreement about what constitutes systems thinking. Its meaning is ambiguous, and systems scholars have made diverse and divergent attempts to describe it. Alternative origins include: von Bertalanffy, Aristotle, Lao Tsu or multiple aperiodic "waves." Some scholars describe it as synonymous with systems sciences (i.e., nonlinear dynamics, complexity, chaos). Others view it as taxonomy-a laundry list of systems approaches. Within so much noise, it is often difficult for evaluators to find the systems thinking signal. Recent work in systems thinking describes it as an emergent property of four simple conceptual patterns (rules). For an evaluator to become a "systems thinker", he or she need not spend years learning many methods or nonlinear sciences. Instead, with some practice, one can learn to apply these four simple rules to existing evaluation knowledge with transformative results.

From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments

USGS Publications Warehouse

Glynn, Pierre D.; Voinov, Alexey A.; Shapiro, Carl D.; White, Paul A.

2017-01-01

Our different kinds of minds and types of thinking affect the ways we decide, take action, and cooperate (or not). Derived from these types of minds, innate biases, beliefs, heuristics, and values (BBHV) influence behaviors, often beneficially, when individuals or small groups face immediate, local, acute situations that they and their ancestors faced repeatedly in the past. BBHV, though, need to be recognized and possibly countered or used when facing new, complex issues or situations especially if they need to be managed for the benefit of a wider community, for the longer-term and the larger-scale. Taking BBHV into account, we explain and provide a cyclic science-infused adaptive framework for (1) gaining knowledge of complex systems and (2) improving their management. We explore how this process and framework could improve the governance of science and policy for different types of systems and issues, providing examples in the area of natural resources, hazards, and the environment. Lastly, we suggest that an “Open Traceable Accountable Policy” initiative that followed our suggested adaptive framework could beneficially complement recent Open Data/Model science initiatives.

Environmental Collaborations Between Indigenous Communities and Western Science: Case Studies and Reflections

NASA Astrophysics Data System (ADS)

Emanuel, R. E.

2016-12-01

The study of coupled natural and human systems in a changing world can benefit greatly from indigenous perspectives, which have the potential to bring deep, placed-based understanding to complex environmental issues while promoting sustainable solutions to pressing socio-environmental problems. In recent years, scientists have begun to embrace indigenous knowledge and perspectives, but indigenous voices in the sciences remain relatively few. At the same time, indigenous communities face wide ranging and unique vulnerabilities to global environmental change on a variety of fronts, particularly where water resources are concerned. Given this situation, indigenous scientists often find themselves bridging both western scientific and indigenous communities, sometimes embodying the nexus in a literal sense. Here I reflect on this nexus from the perspective of an indigenous hydrologist collaborating with American Indian communities in North Carolina, which has the largest American Indian population of any state in the eastern US. Intertwining case studies of coupled natural and human systems illustrate some of the the challenges, complexities, and successes of ongoing collaborations with tribal communities and Native-serving organizations on water resource issues, environmental impacts of food and energy production, and broadening participation of American Indians in the sciences.

Data Processing Center of Radioastron Project: 3 years of operation.

NASA Astrophysics Data System (ADS)

Shatskaya, Marina

ASC DATA PROCESSING CENTER (DPC) of Radioastron Project is a fail-safe complex centralized system of interconnected software/ hardware components along with organizational procedures. Tasks facing of the scientific data processing center are organization of service information exchange, collection of scientific data, storage of all of scientific data, data science oriented processing. DPC takes part in the informational exchange with two tracking stations in Pushchino (Russia) and Green Bank (USA), about 30 ground telescopes, ballistic center, tracking headquarters and session scheduling center. Enormous flows of information go to Astro Space Center. For the inquiring of enormous data volumes we develop specialized network infrastructure, Internet channels and storage. The computer complex has been designed at the Astro Space Center (ASC) of Lebedev Physical Institute and includes: - 800 TB on-line storage, - 2000 TB hard drive archive, - backup system on magnetic tapes (2000 TB); - 24 TB redundant storage at Pushchino Radio Astronomy Observatory; - Web and FTP servers, - DPC management and data transmission networks. The structure and functions of ASC Data Processing Center are fully adequate to the data processing requirements of the Radioastron Mission and has been successfully confirmed during Fringe Search, Early Science Program and first year of Key Science Program.

Clinical Implications of Basic Science Discoveries: Immune Homeostasis and the Microbiome-Dietary and Therapeutic Modulation and Implications for Transplantation.

PubMed

Fishman, J A; Thomson, A W

2015-07-01

Links between the human microbiome and the innate and adaptive immune systems and their impact on autoimmune and inflammatory diseases are only beginning to be recognized. Characterization of the complex human microbial community is facilitated by culture-independent nucleic acid sequencing tools and bioinformatics systems. Specific organisms and microbial antigens are linked with initiation of innate immune responses that, depending on the context, may be associated with tolerogenic or effector immune responses. Further complexity is introduced by preclinical data that demonstrate the impacts of dietary manipulation on the prevention of genetically determined, systemic autoimmune disorders and on gastrointestinal microbiota. Investigation of interactions of complex microbial populations with the human immune system may provide new targets for clinical management in allotransplantation. © Copyright 2015 The American Society of Transplantation and the American Society of Transplant Surgeons.

Investigating engagement, thinking, and learning among culturally diverse, urban sixth graders experiencing an inquiry-based science curriculum, contextualized in the local environment

NASA Astrophysics Data System (ADS)

Kelley, Sybil Schantz

This mixed-methods study combined pragmatism, sociocultural perspectives, and systems thinking concepts to investigate students' engagement, thinking, and learning in science in an urban, K-8 arts, science, and technology magnet school. A grant-funded school-university partnership supported the implementation of an inquiry-based science curriculum, contextualized in the local environment through field experiences. The researcher worked as co-teacher of 3 sixth-grade science classes and was deeply involved in the daily routines of the school. The purposes of the study were to build a deeper understanding of the complex interactions that take place in an urban science classroom, including challenges related to implementing culturally-relevant instruction; and to offer insight into the role educational systems play in supporting teaching and learning. The central hypothesis was that connecting learning to meaningful experiences in the local environment can provide culturally accessible points of engagement from which to build science learning. Descriptive measures provided an assessment of students' engagement in science activities, as well as their levels of thinking and learning throughout the school year. Combined with analyses of students' work files and focus group responses, these findings provided strong evidence of engagement attributable to the inquiry-based curriculum. In some instances, degree of engagement was found to be affected by student "reluctance" and "resistance," terms defined but needing further examination. A confounding result showed marked increases in thinking levels coupled with stasis or decrease in learning. Congruent with past studies, data indicated the presence of tension between the diverse cultures of students and the mainstream cultures of school and science. Findings were synthesized with existing literature to generate the study's principal product, a grounded theory model representing the complex, interacting factors involved in teaching and learning. The model shows that to support learning and to overcome cultural tensions, there must be alignment among three main forces or "causal factors": students, teaching, and school climate. Conclusions emphasize system-level changes to support science learning, including individualized support for students in the form of differentiated instruction; focus on excellence in teaching, particularly through career-spanning professional support for teachers; and attention to identifying key leverage points for implementing effective change.

Science goals and mission concept for the future exploration of Titan and Enceladus

NASA Astrophysics Data System (ADS)

Tobie, G.; Teanby, N. A.; Coustenis, A.; Jaumann, R.; Raulin, F.; Schmidt, J.; Carrasco, N.; Coates, A. J.; Cordier, D.; De Kok, R.; Geppert, W. D.; Lebreton, J.-P.; Lefevre, A.; Livengood, T. A.; Mandt, K. E.; Mitri, G.; Nimmo, F.; Nixon, C. A.; Norman, L.; Pappalardo, R. T.; Postberg, F.; Rodriguez, S.; Schulze-Makuch, D.; Soderblom, J. M.; Solomonidou, A.; Stephan, K.; Stofan, E. R.; Turtle, E. P.; Wagner, R. J.; West, R. A.; Westlake, J. H.

2014-12-01

Saturn's moons, Titan and Enceladus, are two of the Solar System's most enigmatic bodies and are prime targets for future space exploration. Titan provides an analogue for many processes relevant to the Earth, more generally to outer Solar System bodies, and a growing host of newly discovered icy exoplanets. Processes represented include atmospheric dynamics, complex organic chemistry, meteorological cycles (with methane as a working fluid), astrobiology, surface liquids and lakes, geology, fluvial and aeolian erosion, and interactions with an external plasma environment. In addition, exploring Enceladus over multiple targeted flybys will give us a unique opportunity to further study the most active icy moon in our Solar System as revealed by Cassini and to analyse in situ its active plume with highly capable instrumentation addressing its complex chemistry and dynamics. Enceladus' plume likely represents the most accessible samples from an extra-terrestrial liquid water environment in the Solar system, which has far reaching implications for many areas of planetary and biological science. Titan with its massive atmosphere and Enceladus with its active plume are prime planetary objects in the Outer Solar System to perform in situ investigations. In the present paper, we describe the science goals and key measurements to be performed by a future exploration mission involving a Saturn-Titan orbiter and a Titan balloon, which was proposed to ESA in response to the call for definition of the science themes of the next Large-class mission in 2013. The mission scenario is built around three complementary science goals: (A) Titan as an Earth-like system; (B) Enceladus as an active cryovolcanic moon; and (C) Chemistry of Titan and Enceladus - clues for the origin of life. The proposed measurements would provide a step change in our understanding of planetary processes and evolution, with many orders of magnitude improvement in temporal, spatial, and chemical resolution over that which is possible with Cassini-Huygens. This mission concept builds upon the successes of Cassini-Huygens and takes advantage of previous mission heritage in both remote sensing and in situ measurement technologies.

KSC-2014-3126

NASA Image and Video Library

2014-07-03

CAPE CANAVERAL, Fla. – Former NASA astronaut Tom Jones, left, joins Andrea Farmer, senior public relations manager with Delaware North Parks and Resorts at NASA Kennedy Space Center Visitor Complex in Florida, for the grand opening of the Great Balls of Fire exhibit. Great Balls of Fire shares the story of the origins of our solar system, asteroids and comets and their possible impacts and risks. The 1,500-square-foot exhibit, located in the East Gallery of the IMAX theatre at the visitor complex, features several interactive displays, real meteorites and replica asteroid models. The exhibit is a production of The Space Science Institute's National Center for Interactive Learning. It is a traveling exhibition that also receives funding from NASA and the National Science Foundation. Photo credit: NASA/Daniel Casper

KSC-2014-3133

NASA Image and Video Library

2014-07-03

CAPE CANAVERAL, Fla. – Former NASA astronaut Tom Jones discusses the characteristics of asteroids and meteors with a young guest during the grand opening of the Great Balls of Fire exhibit at NASA’s Kennedy Space Center Visitor Complex in Florida. Great Balls of Fire shares the story of the origins of our solar system, asteroids and comets and their possible impacts and risks. The 1,500-square-foot exhibit, located in the East Gallery of the IMAX theatre at the visitor complex, features several interactive displays, real meteorites and replica asteroid models. The exhibit is a production of The Space Science Institute's National Center for Interactive Learning. It is a traveling exhibition that also receives funding from NASA and the National Science Foundation. Photo credit: NASA/Daniel Casper

KSC-2014-3127

NASA Image and Video Library

2014-07-03

CAPE CANAVERAL, Fla. – Therrin Protze, chief operating officer with Delaware North Parks and Resorts at NASA's Kennedy Space Center Visitor Complex in Florida, welcomes guests to the grand opening of the Great Balls of Fire exhibit. Great Balls of Fire shares the story of the origins of our solar system, asteroids and comets and their possible impacts and risks. The 1,500-square-foot exhibit, located in the East Gallery of the IMAX theatre at the visitor complex, features several interactive displays, real meteorites and replica asteroid models. The exhibit is a production of The Space Science Institute's National Center for Interactive Learning. It is a traveling exhibition that also receives funding from NASA and the National Science Foundation. Photo credit: NASA/Daniel Casper

KSC-2014-3132

NASA Image and Video Library

2014-07-03

CAPE CANAVERAL, Fla. – Former NASA astronaut Tom Jones discusses the characteristics of asteroids and meteors with a young guest during the grand opening of the Great Balls of Fire exhibit at NASA’s Kennedy Space Center Visitor Complex in Florida. Great Balls of Fire shares the story of the origins of our solar system, asteroids and comets and their possible impacts and risks. The 1,500-square-foot exhibit, located in the East Gallery of the IMAX theatre at the visitor complex, features several interactive displays, real meteorites and replica asteroid models. The exhibit is a production of The Space Science Institute's National Center for Interactive Learning. It is a traveling exhibition that also receives funding from NASA and the National Science Foundation. Photo credit: NASA/Daniel Casper

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.

Experiments using Semantic Web technologies to connect IUGONET, ESPAS and GFZ ISDC data portals

NASA Astrophysics Data System (ADS)

Ritschel, Bernd; Borchert, Friederike; Kneitschel, Gregor; Neher, Günther; Schildbach, Susanne; Iyemori, Toshihiko; Koyama, Yukinobu; Yatagai, Akiyo; Hori, Tomoaki; Hapgood, Mike; Belehaki, Anna; Galkin, Ivan; King, Todd

2016-11-01

E-science on the Web plays an important role and offers the most advanced technology for the integration of data systems. It also makes available data for the research of more and more complex aspects of the system earth and beyond. The great number of e-science projects founded by the European Union (EU), university-driven Japanese efforts in the field of data services and institutional anchored developments for the enhancement of a sustainable data management in Germany are proof of the relevance and acceptance of e-science or cyberspace-based applications as a significant tool for successful scientific work. The collaboration activities related to near-earth space science data systems and first results in the field of information science between the EU-funded project ESPAS, the Japanese IUGONET project and the GFZ ISDC-based research and development activities are the focus of this paper. The main objective of the collaboration is the use of a Semantic Web approach for the mashup of the project related and so far inoperable data systems. Both the development and use of mapped and/or merged geo and space science controlled vocabularies and the connection of entities in ontology-based domain data model are addressed. The developed controlled vocabularies for the description of geo and space science data and related context information as well as the domain ontologies itself with their domain and cross-domain relationships will be published in Linked Open Data.[Figure not available: see fulltext.

How Earth Educators Can Help Students Develop a Holistic Understanding of Sustainability

NASA Astrophysics Data System (ADS)

Curren, R. R.; Metzger, E. P.

2017-12-01

With their expert understanding of planetary systems, Earth educators play a pivotal role in helping students understand the scientific dimensions of solution-resistant ("wicked") challenges to sustainability that arise from complex interactions between intertwined and co-evolving natural and human systems. However, teaching the science of sustainability in isolation from consideration of human values and social dynamics leaves students with a fragmented understanding and obscures the underlying drivers of unsustainability. Geoscience instructors who wish to address sustainability in their courses may feel ill-equipped to engage students in investigation of the fundamental nature of sustainability and its social and ethical facets. This presentation will blend disciplinary perspectives from Earth system science, philosophy, psychology, and anthropology to: 1) outline a way to conceptualize sustainability that synthesizes scientific, social, and ethical perspectives and 2) provide an overview of resources and teaching strategies designed to help students connect science content to the socio-political dimensions of sustainability through activities and assignments that promote active learning, systems thinking, reflection, and collaborative problem-solving.

Priorities for implementing nutritional science into practice to optimize military performance.

PubMed

Elfenbaum, Pamela; Crawford, Cindy; Enslein, Viviane; Berry, Kevin

2017-06-01

The Metabolically Optimized Brain study explores nutritional science believed to be ready to place into practice to help improve US service member mission-readiness and performance. To this end, an implementation expert panel considered how the US Department of Defense Subsistence Food Service Program, which is operated by each branch of the military in dining facilities within the continental United States, could apply the best nutritional science in a cost-effective manner. The work of this panel was facilitated through a series of thematic conversations guided by evidence generated through systematic reviews, which were performed to identify systems and process gaps and propose possible solutions. The expert panel used a Delphi method of multiple voting, and ultimately proposed 11 systems changes, of which 6 were ranked as highest priority. The proposed highest priority changes were then discussed by the participants with additional stakeholders. The process described here highlights how experts from different sectors operating in a complex system of subsystems can come together to cross talk, identify gaps, and propose mutually beneficial system and process changes to improve the alignment of nutritional science and institutional food-service practice. © The Author(s) 2017. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

In-Space Propulsion Technology Program Solar Electric Propulsion Technologies

NASA Technical Reports Server (NTRS)

Dankanich, John W.

2006-01-01

NASA's In-space Propulsion (ISP) Technology Project is developing new propulsion technologies that can enable or enhance near and mid-term NASA science missions. The Solar Electric Propulsion (SEP) technology area has been investing in NASA s Evolutionary Xenon Thruster (NEXT), the High Voltage Hall Accelerator (HiVHAC), lightweight reliable feed systems, wear testing, and thruster modeling. These investments are specifically targeted to increase planetary science payload capability, expand the envelope of planetary science destinations, and significantly reduce the travel times, risk, and cost of NASA planetary science missions. Status and expected capabilities of the SEP technologies are reviewed in this presentation. The SEP technology area supports numerous mission studies and architecture analyses to determine which investments will give the greatest benefit to science missions. Both the NEXT and HiVHAC thrusters have modified their nominal throttle tables to better utilize diminished solar array power on outbound missions. A new life extension mechanism has been implemented on HiVHAC to increase the throughput capability on low-power systems to meet the needs of cost-capped missions. Lower complexity, more reliable feed system components common to all electric propulsion (EP) systems are being developed. ISP has also leveraged commercial investments to further validate new ion and hall thruster technologies and to potentially lower EP mission costs.

The principle of superposition and its application in ground-water hydraulics

USGS Publications Warehouse

Reilly, T.E.; Franke, O.L.; Bennett, G.D.

1984-01-01

The principle of superposition, a powerful methematical technique for analyzing certain types of complex problems in many areas of science and technology, has important application in ground-water hydraulics and modeling of ground-water systems. The principle of superposition states that solutions to individual problems can be added together to obtain solutions to complex problems. This principle applies to linear systems governed by linear differential equations. This report introduces the principle of superposition as it applies to groundwater hydrology and provides background information, discussion, illustrative problems with solutions, and problems to be solved by the reader. (USGS)

Architectures Toward Reusable Science Data Systems

NASA Astrophysics Data System (ADS)

Moses, J. F.

2014-12-01

Science Data Systems (SDS) comprise an important class of data processing systems that support product generation from remote sensors and in-situ observations. These systems enable research into new science data products, replication of experiments and verification of results. NASA has been building ground systems for satellite data processing since the first Earth observing satellites launched and is continuing development of systems to support NASA science research, NOAA's weather satellites and USGS's Earth observing satellite operations. The basic data processing workflows and scenarios continue to be valid for remote sensor observations research as well as for the complex multi-instrument operational satellite data systems being built today. System functions such as ingest, product generation and distribution need to be configured and performed in a consistent and repeatable way with an emphasis on scalability. This paper will examine the key architectural elements of several NASA satellite data processing systems currently in operation and under development that make them suitable for scaling and reuse. Examples of architectural elements that have become attractive include virtual machine environments, standard data product formats, metadata content and file naming, workflow and job management frameworks, data acquisition, search, and distribution protocols. By highlighting key elements and implementation experience the goal is to recognize architectures that will outlast their original application and be readily adaptable for new applications. Concepts and principles are explored that lead to sound guidance for SDS developers and strategists.

Architectures Toward Reusable Science Data Systems

NASA Technical Reports Server (NTRS)

Moses, John

2015-01-01

Science Data Systems (SDS) comprise an important class of data processing systems that support product generation from remote sensors and in-situ observations. These systems enable research into new science data products, replication of experiments and verification of results. NASA has been building systems for satellite data processing since the first Earth observing satellites launched and is continuing development of systems to support NASA science research and NOAAs Earth observing satellite operations. The basic data processing workflows and scenarios continue to be valid for remote sensor observations research as well as for the complex multi-instrument operational satellite data systems being built today. System functions such as ingest, product generation and distribution need to be configured and performed in a consistent and repeatable way with an emphasis on scalability. This paper will examine the key architectural elements of several NASA satellite data processing systems currently in operation and under development that make them suitable for scaling and reuse. Examples of architectural elements that have become attractive include virtual machine environments, standard data product formats, metadata content and file naming, workflow and job management frameworks, data acquisition, search, and distribution protocols. By highlighting key elements and implementation experience we expect to find architectures that will outlast their original application and be readily adaptable for new applications. Concepts and principles are explored that lead to sound guidance for SDS developers and strategists.

Development of Civic Engagement: Theoretical and Methodological Issues

ERIC Educational Resources Information Center

Lerner, Richard M.; Wang, Jun; Champine, Robey B.; Warren, Daniel J. A.; Erickson, Karl

2014-01-01

Within contemporary developmental science, models derived from relational developmental systems (RDS) metatheory emphasize that the basic process of human development involves mutually-influential relations, termed developmental regulations, between the developing individual and his or her complex and changing physical, social, and cultural…

Applied statistics in agricultural, biological, and environmental sciences.

USDA-ARS?s Scientific Manuscript database

Agronomic research often involves measurement and collection of multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate statistical methods encompass the simultaneous analysis of all random variables measured on each experimental or s...

Convolving engineering and medical pedagogies for training of tomorrow's health care professionals.

PubMed

Lee, Raphael C

2013-03-01

Several fundamental benefits justify why biomedical engineering and medicine should form a more convergent alliance, especially for the training of tomorrow's physicians and biomedical engineers. Herein, we review the rationale underlying the benefits. Biological discovery has advanced beyond the era of molecular biology well into today's era of molecular systems biology, which focuses on understanding the rules that govern the behavior of complex living systems. This has important medical implications. To realize cost-effective personalized medicine, it is necessary to translate the advances in molecular systems biology to higher levels of biological organization (organ, system, and organismal levels) and then to develop new medical therapeutics based on simulation and medical informatics analysis. Higher education in biological and medical sciences must adapt to a new set of training objectives. This will involve a shifting away from reductionist problem solving toward more integrative, continuum, and predictive modeling approaches which traditionally have been more associated with engineering science. Future biomedical engineers and MDs must be able to predict clinical response to therapeutic intervention. Medical education will involve engineering pedagogies, wherein basic governing rules of complex system behavior and skill sets in manipulating these systems to achieve a practical desired outcome are taught. Similarly, graduate biomedical engineering programs will include more practical exposure to clinical problem solving.

The science of science: From the perspective of complex systems

NASA Astrophysics Data System (ADS)

Zeng, An; Shen, Zhesi; Zhou, Jianlin; Wu, Jinshan; Fan, Ying; Wang, Yougui; Stanley, H. Eugene

2017-11-01

The science of science (SOS) is a rapidly developing field which aims to understand, quantify and predict scientific research and the resulting outcomes. The problem is essentially related to almost all scientific disciplines and thus has attracted attention of scholars from different backgrounds. Progress on SOS will lead to better solutions for many challenging issues, ranging from the selection of candidate faculty members by a university to the development of research fields to which a country should give priority. While different measurements have been designed to evaluate the scientific impact of scholars, journals and academic institutions, the multiplex structure, dynamics and evolution mechanisms of the whole system have been much less studied until recently. In this article, we review the recent advances in SOS, aiming to cover the topics from empirical study, network analysis, mechanistic models, ranking, prediction, and many important related issues. The results summarized in this review significantly deepen our understanding of the underlying mechanisms and statistical rules governing the science system. Finally, we review the forefront of SOS research and point out the specific difficulties as they arise from different contexts, so as to stimulate further efforts in this emerging interdisciplinary field.

Complexity Science: A Mechanism for Strategic Foresight and Resiliency in National Security Decision-Making.

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

Ackermann, Mark R.; Hayden, Nancy Kay; Backus, George A.

Most national policy decisions are complex with a variety of stakeholders, disparate interests and the potential for unintended consequences. While a number of analytical tools exist to help decision makers sort through the mountains of data and myriad of options, decision support teams are increasingly turning to complexity science for improved analysis and better insight into the potential impact of policy decisions. While complexity science has great potential, it has only proven useful in limited case s and when properly applied. In advance of more widespread use, a national - level effort to refine complexity science and more rigorously establishmore » its technical underpinnings is recommended.« less

Practical Applications of Cosmic Ray Science: Spacecraft, Aircraft, Ground Based Computation and Control Systems and Human Health and Safety

NASA Technical Reports Server (NTRS)

Atwell, William; Koontz, Steve; Normand, Eugene

2012-01-01

In this paper we review the discovery of cosmic ray effects on the performance and reliability of microelectronic systems as well as on human health and safety, as well as the development of the engineering and health science tools used to evaluate and mitigate cosmic ray effects in earth surface, atmospheric flight, and space flight environments. Three twentieth century technological developments, 1) high altitude commercial and military aircraft; 2) manned and unmanned spacecraft; and 3) increasingly complex and sensitive solid state micro-electronics systems, have driven an ongoing evolution of basic cosmic ray science into a set of practical engineering tools (e.g. ground based test methods as well as high energy particle transport and reaction codes) needed to design, test, and verify the safety and reliability of modern complex electronic systems as well as effects on human health and safety. The effects of primary cosmic ray particles, and secondary particle showers produced by nuclear reactions with spacecraft materials, can determine the design and verification processes (as well as the total dollar cost) for manned and unmanned spacecraft avionics systems. Similar considerations apply to commercial and military aircraft operating at high latitudes and altitudes near the atmospheric Pfotzer maximum. Even ground based computational and controls systems can be negatively affected by secondary particle showers at the Earth's surface, especially if the net target area of the sensitive electronic system components is large. Accumulation of both primary cosmic ray and secondary cosmic ray induced particle shower radiation dose is an important health and safety consideration for commercial or military air crews operating at high altitude/latitude and is also one of the most important factors presently limiting manned space flight operations beyond low-Earth orbit (LEO).

A JavaScript API for the Ice Sheet System Model (ISSM) 4.11: towards an online interactive model for the cryosphere community

NASA Astrophysics Data System (ADS)

Larour, Eric; Cheng, Daniel; Perez, Gilberto; Quinn, Justin; Morlighem, Mathieu; Duong, Bao; Nguyen, Lan; Petrie, Kit; Harounian, Silva; Halkides, Daria; Hayes, Wayne

2017-12-01

Earth system models (ESMs) are becoming increasingly complex, requiring extensive knowledge and experience to deploy and use in an efficient manner. They run on high-performance architectures that are significantly different from the everyday environments that scientists use to pre- and post-process results (i.e., MATLAB, Python). This results in models that are hard to use for non-specialists and are increasingly specific in their application. It also makes them relatively inaccessible to the wider science community, not to mention to the general public. Here, we present a new software/model paradigm that attempts to bridge the gap between the science community and the complexity of ESMs by developing a new JavaScript application program interface (API) for the Ice Sheet System Model (ISSM). The aforementioned API allows cryosphere scientists to run ISSM on the client side of a web page within the JavaScript environment. When combined with a web server running ISSM (using a Python API), it enables the serving of ISSM computations in an easy and straightforward way. The deep integration and similarities between all the APIs in ISSM (MATLAB, Python, and now JavaScript) significantly shortens and simplifies the turnaround of state-of-the-art science runs and their use by the larger community. We demonstrate our approach via a new Virtual Earth System Laboratory (VESL) website (http://vesl.jpl.nasa.gov, VESL(2017)).

A Novel Approach to Develop the Lower Order Model of Multi-Input Multi-Output System

NASA Astrophysics Data System (ADS)

Rajalakshmy, P.; Dharmalingam, S.; Jayakumar, J.

2017-10-01

A mathematical model is a virtual entity that uses mathematical language to describe the behavior of a system. Mathematical models are used particularly in the natural sciences and engineering disciplines like physics, biology, and electrical engineering as well as in the social sciences like economics, sociology and political science. Physicists, Engineers, Computer scientists, and Economists use mathematical models most extensively. With the advent of high performance processors and advanced mathematical computations, it is possible to develop high performing simulators for complicated Multi Input Multi Ouptut (MIMO) systems like Quadruple tank systems, Aircrafts, Boilers etc. This paper presents the development of the mathematical model of a 500 MW utility boiler which is a highly complex system. A synergistic combination of operational experience, system identification and lower order modeling philosophy has been effectively used to develop a simplified but accurate model of a circulation system of a utility boiler which is a MIMO system. The results obtained are found to be in good agreement with the physics of the process and with the results obtained through design procedure. The model obtained can be directly used for control system studies and to realize hardware simulators for boiler testing and operator training.

The SAMPEX Data Center and User Interface for the Heliophysics Community

NASA Astrophysics Data System (ADS)

Davis, A. J.; Kanekal, S. G.; Looper, M. D.; Mazur, J. E.

2012-12-01

The Solar, Anomalous, Magnetospheric Particle Explorer (SAMPEX) was the first of NASA's Small Explorer (SMEX) series. SAMPEX was launched July 3, 1992 into a 520 by 670 km orbit at 82 degrees inclination. SAMPEX carries four instruments designed to study energetic particles of solar, interplanetary, and magnetospheric origin, as well as "anomalous" and galactic cosmic rays. As an outcome of the Senior Review process, the NASA SAMPEX science mission ended on June 30, 2004, leaving a 12-year continuous record of observations. (The spacecraft and instruments are still operating and returning science data under a partnership between NASA and the Aerospace Corporation). SAMPEX was launched before the development of the WWW and implementation of NASA's open data policy. This, and the complexity of the data analysis have made it difficult for the general community to make full use of the SAMPEX science data set. The SAMPEX Data Center remedies the situation. The data center set-up and operation was funded for 3 years by NASA, and it remains in operation. The goals of the data center are to enable community access to the full SAMPEX data set by developing an up-to-date, flexible web-based system, and to provide for the eventual permanent archiving of this version of the SAMPEX data set at the NSSDC. Knowledgeable members of the SAMPEX science team have prepared the data, and members of the ACE Science Center at Caltech are involved in maintaining the data distribution pipeline and user interface. The system is modeled in part on the ACE Science Center, but enhanced to accommodate the more-complex SAMPEX data set. We will describe the current status of the SAMPEX Data Center, the user interface, and the contents of the data that are available.

The SAMPEX Data Center and User Interface for the SEC Community

NASA Astrophysics Data System (ADS)

Davis, A. J.; Mason, G. M.; Walpole, P.; von Rosenvinge, T. T.; Looper, M. D.; Blake, J. B.; Mazur, J. E.; Stone, E. C.; Leske, R. A.; Labrador, A. W.; Mewaldt, R. A.; Kanekal, S. G.; Baker, D. N.; Li, X.; Klecker, B.

2005-05-01

The Solar, Anomalous, Magnetospheric Particle Explorer (SAMPEX) was the first of NASA's Small Explorer (SMEX) series. SAMPEX was launched July 3, 1992 into a 520 by 670 km orbit at 82 degrees inclination. SAMPEX carries four instruments designed to study energetic particles of solar, interplanetary, and magnetospheric origin, as well as "anomalous" and galactic cosmic rays. As an outcome of the Senior Review process, the NASA SAMPEX science mission ended on June 30, 2004, leaving a 12-year continuous record of observations. (The spacecraft and instruments are still operating and returning science data for a 1-year trial period under a partnership between NASA and the Aerospace Corporation). SAMPEX was launched before the development of the WWW and implementation of NASA's open data policy. This, and the complexity of the data analysis have made it difficult for the general community to make full use of the SAMPEX science data set. The SAMPEX Data Center will remedy the situation. The data center set-up and operation is funded for 3 years by NASA. The goals of the data center are to enable community access to the full SAMPEX data set by developing an up-to-date, flexible web-based system, and to provide for the eventual permanent archiving of this version of the SAMPEX data set at the NSSDC. Knowledgeable members of the SAMPEX science team are preparing the data, and members of the ACE Science Center at Caltech are involved in developing the data distribution pipeline and user interface. The system is modeled in part on the ACE Science Center, but enhanced to accommodate the more-complex SAMPEX data set. We will describe the current status of the SAMPEX Data Center development, the user interface, and the contents of the data that will be made available.

The Chaos of Katrina

DTIC Science & Technology

2007-03-01

partners for their mutual benefit. Unfortunately, based on government reports, FEMA did not have adequate control of its supply chain information ...is one attractor . “Edge of chaos” systems have two to eight attractors and in chaotic systems many attractors . Some are called strange attractors ...investigates whether chaos theory, part of complexity science, can extract information from Katrina contracting data to help managers make better logistics

The China Educational Development Yearbook, Volume 1. The Chinese Academy of Social Sciences Yearbooks: Educational Development

ERIC Educational Resources Information Center

Dongping, Yang, Ed.; Chunqing, Chai, Ed.; Yinnian, Zhu, Ed.

2009-01-01

China's education system has grown increasingly complex, creating the need for an annual critical review of the education system by China's top scholars. The "Blue Book of Education," as it is known in Chinese, has gained a reputation for offering the most penetrating perspective in China on educational reform and development. In this…

Will systems biology offer new holistic paradigms to life sciences?

PubMed Central

Conti, Filippo; Valerio, Maria Cristina; Zbilut, Joseph P.

2008-01-01

A biological system, like any complex system, blends stochastic and deterministic features, displaying properties of both. In a certain sense, this blend is exactly what we perceive as the “essence of complexity” given we tend to consider as non-complex both an ideal gas (fully stochastic and understandable at the statistical level in the thermodynamic limit of a huge number of particles) and a frictionless pendulum (fully deterministic relative to its motion). In this commentary we make the statement that systems biology will have a relevant impact on nowadays biology if (and only if) will be able to capture the essential character of this blend that in our opinion is the generation of globally ordered collective modes supported by locally stochastic atomisms. PMID:19003440

What Is a Complex Innovation System?

PubMed Central

Katz, J. Sylvan

2016-01-01

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

Development of a Web-Based Indoor Navigation System Using an Accelerometer and Gyroscope: A Case Study at The Faculty of Natural Sciences of Comenius University

NASA Astrophysics Data System (ADS)

Štefanička, Tomáš; Ďuračiová, Renata; Seres, Csaba

2017-12-01

As a complex of buildings, the Faculty of Natural Sciences of the Comenius University in Bratislava tends to be difficult to navigate in spite of its size. An indoor navigation application could potentially save a lot of time and frustration. There are currently numerous technologies used in indoor navigation systems. Some of them focus on a high degree of precision and require significant financial investment; others provide only static information about a current location. In this paper we focused on the determination of an approximate location using inertial measurement systems available on most smartphones, i.e., a gyroscope and an accelerometer. The actual position of the device was calculated using "a walk detection method" based on a delayed lack of motion. We have developed an indoor navigation application that relies solely on open source JavaScript libraries to visualize the interior of the building and calculate the shortest path utilizing Dijsktra's routing algorithm. The application logic is located on the client side, so the software is able to work offline. Our solution represents an accessible lowcost and platform-independent web application that can significantly improve navigation at the Faculty of Natural Sciences. Although our application has been developed on a specific building complex, it could be used in other interiors as well.