Science.gov

Sample records for dynamic contagion model

  1. Critical Behaviors in Contagion Dynamics

    NASA Astrophysics Data System (ADS)

    Böttcher, L.; Nagler, J.; Herrmann, H. J.

    2017-02-01

    We study the critical behavior of a general contagion model where nodes are either active (e.g., with opinion A , or functioning) or inactive (e.g., with opinion B , or damaged). The transitions between these two states are determined by (i) spontaneous transitions independent of the neighborhood, (ii) transitions induced by neighboring nodes, and (iii) spontaneous reverse transitions. The resulting dynamics is extremely rich including limit cycles and random phase switching. We derive a unifying mean-field theory. Specifically, we analytically show that the critical behavior of systems whose dynamics is governed by processes (i)-(iii) can only exhibit three distinct regimes: (a) uncorrelated spontaneous transition dynamics, (b) contact process dynamics, and (c) cusp catastrophes. This ends a long-standing debate on the universality classes of complex contagion dynamics in mean field and substantially deepens its mathematical understanding.

  2. Critical Behaviors in Contagion Dynamics.

    PubMed

    Böttcher, L; Nagler, J; Herrmann, H J

    2017-02-24

    We study the critical behavior of a general contagion model where nodes are either active (e.g., with opinion A, or functioning) or inactive (e.g., with opinion B, or damaged). The transitions between these two states are determined by (i) spontaneous transitions independent of the neighborhood, (ii) transitions induced by neighboring nodes, and (iii) spontaneous reverse transitions. The resulting dynamics is extremely rich including limit cycles and random phase switching. We derive a unifying mean-field theory. Specifically, we analytically show that the critical behavior of systems whose dynamics is governed by processes (i)-(iii) can only exhibit three distinct regimes: (a) uncorrelated spontaneous transition dynamics, (b) contact process dynamics, and (c) cusp catastrophes. This ends a long-standing debate on the universality classes of complex contagion dynamics in mean field and substantially deepens its mathematical understanding.

  3. Social Contagion, Adolescent Sexual Behavior, and Pregnancy: A Nonlinear Dynamic EMOSA Model.

    ERIC Educational Resources Information Center

    Rodgers, Joseph Lee; Rowe, David C.; Buster, Maury

    1998-01-01

    Expands an existing nonlinear dynamic epidemic model of onset of social activities (EMOSA), motivated by social contagion theory, to quantify the likelihood of pregnancy for adolescent girls of different sexuality statuses. Compares five sexuality/pregnancy models to explain variance in national prevalence curves. Finds that adolescent girls have…

  4. Social Contagion, Adolescent Sexual Behavior, and Pregnancy: A Nonlinear Dynamic EMOSA Model.

    ERIC Educational Resources Information Center

    Rodgers, Joseph Lee; Rowe, David C.; Buster, Maury

    1998-01-01

    Expands an existing nonlinear dynamic epidemic model of onset of social activities (EMOSA), motivated by social contagion theory, to quantify the likelihood of pregnancy for adolescent girls of different sexuality statuses. Compares five sexuality/pregnancy models to explain variance in national prevalence curves. Finds that adolescent girls have…

  5. Clustering determines the dynamics of complex contagions in multiplex networks

    NASA Astrophysics Data System (ADS)

    Zhuang, Yong; Arenas, Alex; Yaǧan, Osman

    2017-01-01

    We present the mathematical analysis of generalized complex contagions in a class of clustered multiplex networks. The model is intended to understand spread of influence, or any other spreading process implying a threshold dynamics, in setups of interconnected networks with significant clustering. The contagion is assumed to be general enough to account for a content-dependent linear threshold model, where each link type has a different weight (for spreading influence) that may depend on the content (e.g., product, rumor, political view) that is being spread. Using the generating functions formalism, we determine the conditions, probability, and expected size of the emergent global cascades. This analysis provides a generalization of previous approaches and is especially useful in problems related to spreading and percolation. The results present nontrivial dependencies between the clustering coefficient of the networks and its average degree. In particular, several phase transitions are shown to occur depending on these descriptors. Generally speaking, our findings reveal that increasing clustering decreases the probability of having global cascades and their size, however, this tendency changes with the average degree. There exists a certain average degree from which on clustering favors the probability and size of the contagion. By comparing the dynamics of complex contagions over multiplex networks and their monoplex projections, we demonstrate that ignoring link types and aggregating network layers may lead to inaccurate conclusions about contagion dynamics, particularly when the correlation of degrees between layers is high.

  6. Effect of social group dynamics on contagion.

    PubMed

    Zhao, Zhenyuan; Calderón, J P; Xu, Chen; Zhao, Guannan; Fenn, Dan; Sornette, Didier; Crane, Riley; Hui, Pak Ming; Johnson, Neil F

    2010-05-01

    Despite the many works on contagion phenomena in both well-mixed systems and heterogeneous networks, there is still a lack of understanding of the intermediate regime where social group structures evolve on a similar time scale to individual-level transmission. We address this question by considering the process of transmission through a model population comprising social groups which follow simple dynamical rules for growth and breakup. Despite the simplicity of our model, the profiles produced bear a striking resemblance to a wide variety of real-world examples--in particular, empirical data that we have obtained for social (i.e., YouTube), financial (i.e., currency markets), and biological (i.e., colds in schools) systems. The observation of multiple resurgent peaks and abnormal decay times is qualitatively reproduced within the model simply by varying the time scales for group coalescence and fragmentation. We provide an approximate analytic treatment of the system and highlight a novel transition which arises as a result of the social group dynamics.

  7. Effect of social group dynamics on contagion

    NASA Astrophysics Data System (ADS)

    Zhao, Zhenyuan; Calderón, J. P.; Xu, Chen; Zhao, Guannan; Fenn, Dan; Sornette, Didier; Crane, Riley; Hui, Pak Ming; Johnson, Neil F.

    2010-05-01

    Despite the many works on contagion phenomena in both well-mixed systems and heterogeneous networks, there is still a lack of understanding of the intermediate regime where social group structures evolve on a similar time scale to individual-level transmission. We address this question by considering the process of transmission through a model population comprising social groups which follow simple dynamical rules for growth and breakup. Despite the simplicity of our model, the profiles produced bear a striking resemblance to a wide variety of real-world examples—in particular, empirical data that we have obtained for social (i.e., YouTube), financial (i.e., currency markets), and biological (i.e., colds in schools) systems. The observation of multiple resurgent peaks and abnormal decay times is qualitatively reproduced within the model simply by varying the time scales for group coalescence and fragmentation. We provide an approximate analytic treatment of the system and highlight a novel transition which arises as a result of the social group dynamics.

  8. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

    PubMed

    Herrera, Mauricio; Armelini, Guillermo; Salvaj, Erica

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

  9. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks

    PubMed Central

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions. PMID:26505473

  10. Contagion spreading on complex networks with local deterministic dynamics

    NASA Astrophysics Data System (ADS)

    Manshour, Pouya; Montakhab, Afshin

    2014-07-01

    Typically, contagion strength is modeled by a transmission rate λ, whereby all nodes in a network are treated uniformly in a mean-field approximation. However, local agents react differently to the same contagion based on their local characteristics. Following our recent work (Montakhab and Manshour, 2012 [42]), we investigate contagion spreading models with local dynamics on complex networks. We therefore quantify contagions by their quality, 0⩽α⩽1, and follow their spreading as their transmission condition (fitness) is evaluated by local agents. Instead of considering stochastic dynamics, here we consider various deterministic local rules. We find that initial spreading with exponential quality-dependent time scales is followed by a stationary state with a prevalence depending on the quality of the contagion. We also observe various interesting phenomena, for example, high prevalence without the participation of the hubs. This special feature of our "threshold rule" provides a mechanism for high prevalence spreading without the participation of "super-spreaders", in sharp contrast with many standard mechanism of spreading where hubs are believed to play the central role. On the other hand, if local nodes act as agents who stop the transmission once a threshold is reached, we find that spreading is severely hindered in a heterogeneous population while in a homogeneous one significant spreading may occur. We further decouple local characteristics from underlying topology in order to study the role of network topology in various models and find that as long as small-world effect exists, the underlying topology does not contribute to the final stationary state but only affects the initial spreading velocity.

  11. Correlations and risk contagion between mixed assets and mixed-asset portfolio VaR measurements in a dynamic view: An application based on time varying copula models

    NASA Astrophysics Data System (ADS)

    Han, Yingying; Gong, Pu; Zhou, Xiang

    2016-02-01

    In this paper, we apply time varying Gaussian and SJC copula models to study the correlations and risk contagion between mixed assets: financial (stock), real estate and commodity (gold) assets in China firstly. Then we study the dynamic mixed-asset portfolio risk through VaR measurement based on the correlations computed by the time varying copulas. This dynamic VaR-copula measurement analysis has never been used on mixed-asset portfolios. The results show the time varying estimations fit much better than the static models, not only for the correlations and risk contagion based on time varying copulas, but also for the VaR-copula measurement. The time varying VaR-SJC copula models are more accurate than VaR-Gaussian copula models when measuring more risky portfolios with higher confidence levels. The major findings suggest that real estate and gold play a role on portfolio risk diversification and there exist risk contagion and flight to quality between mixed-assets when extreme cases happen, but if we take different mixed-asset portfolio strategies with the varying of time and environment, the portfolio risk will be reduced.

  12. The Epidemic Process and The Contagion Model

    ERIC Educational Resources Information Center

    Worthen, Dennis B.

    1973-01-01

    Goffman's epidemic theory is presented and compared to the contagion theory developed by Menzel. An attempt is made to compare the two models presented and examine their similarities and differences. The conclusion drawn is that the two models are very similar in their approach to understanding communication processes. (14 references) (Author/SJ)

  13. A model for the contagion and herding

    NASA Astrophysics Data System (ADS)

    Caetano, Marco Antonio Leonel; Yoneyama, Takashi

    2011-11-01

    This work concerns the modeling of contagion and herding effects which can cause significant movements of prices and volatilities. The idea is to adapt some concepts borrowed from the Biological Sciences and that have emerged as useful analogies to model a variety of phenomena in a large variety of fields such as Engineering and Economics. In this work, the allegory of interacting particles is used to describe the contagion and emergence of herding behavior of financial agents leading to the formation of clusters. The main idea is to adapt the schemes originally employed in particle swarm optimization algorithms, together with the concepts of leaders and followers. As an illustration of the applicability of the proposed model, a case study is presented using data from the World Bank.

  14. Comment on "Social Contagion, Adolescent Sexual Behavior, and Pregnancy: A Nonlinear Dynamic EMOSA Model."

    ERIC Educational Resources Information Center

    Stoolmiller, Mike

    1998-01-01

    Examines the Rodgers, Rowe, and Buster (1998) epidemic model of the onset of social activities for adolescent sexuality. Maintains that its strengths include its theoretical potential to generate new hypotheses for further testing at the individual level. Asserts that its limitations include the lack of a well-developed statistical framework and…

  15. Dynamics of social contagions with memory of nonredundant information

    NASA Astrophysics Data System (ADS)

    Wang, Wei; Tang, Ming; Zhang, Hai-Feng; Lai, Ying-Cheng

    2015-07-01

    A key ingredient in social contagion dynamics is reinforcement, as adopting a certain social behavior requires verification of its credibility and legitimacy. Memory of nonredundant information plays an important role in reinforcement, which so far has eluded theoretical analysis. We first propose a general social contagion model with reinforcement derived from nonredundant information memory. Then, we develop a unified edge-based compartmental theory to analyze this model, and a remarkable agreement with numerics is obtained on some specific models. We use a spreading threshold model as a specific example to understand the memory effect, in which each individual adopts a social behavior only when the cumulative pieces of information that the individual received from his or her neighbors exceeds an adoption threshold. Through analysis and numerical simulations, we find that the memory characteristic markedly affects the dynamics as quantified by the final adoption size. Strikingly, we uncover a transition phenomenon in which the dependence of the final adoption size on some key parameters, such as the transmission probability, can change from being discontinuous to being continuous. The transition can be triggered by proper parameters and structural perturbations to the system, such as decreasing individuals' adoption threshold, increasing initial seed size, or enhancing the network heterogeneity.

  16. Evidence for complex contagion models of social contagion from observational data

    PubMed Central

    Sprague, Daniel A.

    2017-01-01

    Social influence can lead to behavioural ‘fads’ that are briefly popular and quickly die out. Various models have been proposed for these phenomena, but empirical evidence of their accuracy as real-world predictive tools has so far been absent. Here we find that a ‘complex contagion’ model accurately describes the spread of behaviours driven by online sharing. We found that standard, ‘simple’, contagion often fails to capture both the rapid spread and the long tails of popularity seen in real fads, where our complex contagion model succeeds. Complex contagion also has predictive power: it successfully predicted the peak time and duration of the ALS Icebucket Challenge. The fast spread and longer duration of fads driven by complex contagion has important implications for activities such as publicity campaigns and charity drives. PMID:28686719

  17. Dynamics of social contagions with limited contact capacity

    NASA Astrophysics Data System (ADS)

    Wang, Wei; Shu, Panpan; Zhu, Yu-Xiao; Tang, Ming; Zhang, Yi-Cheng

    2015-10-01

    Individuals are always limited by some inelastic resources, such as time and energy, which restrict them to dedicate to social interaction and limit their contact capacities. Contact capacity plays an important role in dynamics of social contagions, which so far has eluded theoretical analysis. In this paper, we first propose a non-Markovian model to understand the effects of contact capacity on social contagions, in which each adopted individual can only contact and transmit the information to a finite number of neighbors. We then develop a heterogeneous edge-based compartmental theory for this model, and a remarkable agreement with simulations is obtained. Through theory and simulations, we find that enlarging the contact capacity makes the network more fragile to behavior spreading. Interestingly, we find that both the continuous and discontinuous dependence of the final adoption size on the information transmission probability can arise. There is a crossover phenomenon between the two types of dependence. More specifically, the crossover phenomenon can be induced by enlarging the contact capacity only when the degree exponent is above a critical degree exponent, while the final behavior adoption size always grows continuously for any contact capacity when degree exponent is below the critical degree exponent.

  18. Testing for contagion under asymmetric dynamics: Evidence from the stock markets between US and Taiwan

    NASA Astrophysics Data System (ADS)

    Wang, Kuan-Min; Nguyen Thi, Thanh-Binh

    2007-03-01

    This article is an attempt to test, through the use of forward forecasting test on dynamic conditional correlation (DCC), for contagion between Taiwan and US stocks under asymmetry. The process includes three steps. The first step uses the iterated cumulative sums of squares (ICSS) algorithm to detect the structural breaks of market return. The second step creates dummy variables for breaks, estimates EGARCH model of conditional generalized error distribution, and computes dynamic conditional correlation coefficients of DCC multivariate GARCH model. The third step employs one-step and N-step forecast test to check for contagion effect. The evidences prove the asymmetric leverage effect of Taiwan weighted stock index and New York-NYSE Composite Index. Interestingly, we discovered that there are two kinds of contagion, “positive” and “negative”, between markets.

  19. Emotional contagion and proto-organizing in human interaction dynamics

    PubMed Central

    Hazy, James K.; Boyatzis, Richard E.

    2015-01-01

    This paper combines the complexity notions of phase transitions and tipping points with recent advances in cognitive neuroscience to propose a general theory of human proto-organizing. It takes as a premise that a necessary prerequisite for organizing, or “proto-organizing,” occurs through emotional contagion in subpopulations of human interaction dynamics in complex ecosystems. Emotional contagion is posited to engender emotional understanding and identification with others, a social process that acts as a mechanism that enables (or precludes) cooperative responses to opportunities and risks. Propositions are offered and further research is suggested. PMID:26124736

  20. Contagion: epidemiological models and financial crises.

    PubMed

    Peckham, Robert

    2014-03-01

    Since the 1990s, economists have drawn on the epidemiology of emerging infectious diseases to explain the diffusion of shock through an increasingly complex financial system. The successful coordination of public health responses to disease threats, and in particular the epidemiological modelling underpinning infection control, has influenced economists' understanding of the risks posed to the stability of the financial system by 'contagion'. While the exportation of analytic models and frames of reference can be fruitful, reinvigorating the destination domain, such analogizing can have a distorting effect. There are differences between biological and financial systems. Moreover, the migration of highly context-specific epidemiological models may undermine the basis of the analogy. Finally, there may be repercussions for the efficacy of public health in the way that its aims are misconstrued in financial analyses.

  1. Establishment of an animal model of depression contagion

    PubMed Central

    Boyko, Matthew; Kutz, Ruslan; Grinshpun, Yulia; Zvenigorodsky, Vladislav; Gruenbaum, Shaun E.; Gruenbaum, Benjamin F.; Brotfain, Evgeni; Shapira, Yoram; Zlotnik, Alexander

    2015-01-01

    Background Depression is a common and important cause of morbidity, and results in a significant economic burden. Recent human studies have demonstrated that that depression is contagious, and depression in family and friends might cumulatively increase the likelihood that a person will exhibit depressive behaviors. The mechanisms underlying contagion depression are poorly understood, and there are currently no animal models for this condition. Methods Rats were divided into 3 groups: depression group, contagion group, and control group. After induction of depression by 5 weeks of chronic unpredictable stress, rats from the contagion group were housed with the depressed rats (1 naïve rat with 2 depressed rats) for 5 weeks. Rats were then subjected to sucrose preference, open field, and forced swim tests. Results The sucrose preference was significantly reduced in the depressed rats (p < 0.01) and contagion depression rats (p < 0.01). Climbing time during forced swim test was reduced in the depression and contagion depression groups (p < 0.001), whereas immobility time was significantly prolonged in only the depression group (p < 0.001). Rats in both the depression (p < 0.05) and depression contagion group (p < 0.005) had decreased total travel distance and decreased mean velocity in the open field test, whereas the time spent in the central part was significantly shorter in only the depression group (p < 0.001). Conclusions In this study, for the first time we demonstrated depression contagion in an animal model. A reliable animal model may help better understand the underlying mechanisms of contagion depression, and may allow for future investigations of the studying therapeutic modalities. PMID:25523029

  2. The price of anarchy in mobility-driven contagion dynamics

    PubMed Central

    Nicolaides, Christos; Cueto-Felgueroso, Luis; Juanes, Ruben

    2013-01-01

    Public policy and individual incentives determine the patterns of human mobility through transportation networks. In the event of a health emergency, the pursuit of maximum social or individual utility may lead to conflicting objectives in the routing strategies of network users. Individuals tend to avoid exposure so as to minimize the risk of contagion, whereas policymakers aim at coordinated behaviour that maximizes the social welfare. Here, we study agent-driven contagion dynamics through transportation networks, coupled to the adoption of either selfish- or policy-driven rerouting strategies. In analogy with the concept of price of anarchy in transportation networks subject to congestion, we show that maximizing individual utility leads to a loss of welfare for the social group, measured here by the total population infected after an epidemic outbreak. PMID:23904588

  3. Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption

    NASA Technical Reports Server (NTRS)

    Hutto, Clayton; Briscoe, Erica; Trewhitt, Ethan

    2012-01-01

    Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.

  4. Estimation of the Heteroskedastic Canonical Contagion Model with Instrumental Variables

    PubMed Central

    2016-01-01

    Knowledge of contagion among economies is a relevant issue in economics. The canonical model of contagion is an alternative in this case. Given the existence of endogenous variables in the model, instrumental variables can be used to decrease the bias of the OLS estimator. In the presence of heteroskedastic disturbances this paper proposes the use of conditional volatilities as instruments. Simulation is used to show that the homoscedastic and heteroskedastic estimators which use them as instruments have small bias. These estimators are preferable in comparison with the OLS estimator and their asymptotic distribution can be used to construct confidence intervals. PMID:28030628

  5. Estimation of the Heteroskedastic Canonical Contagion Model with Instrumental Variables.

    PubMed

    Ribeiro, André L P; Hotta, Luiz K

    2016-01-01

    Knowledge of contagion among economies is a relevant issue in economics. The canonical model of contagion is an alternative in this case. Given the existence of endogenous variables in the model, instrumental variables can be used to decrease the bias of the OLS estimator. In the presence of heteroskedastic disturbances this paper proposes the use of conditional volatilities as instruments. Simulation is used to show that the homoscedastic and heteroskedastic estimators which use them as instruments have small bias. These estimators are preferable in comparison with the OLS estimator and their asymptotic distribution can be used to construct confidence intervals.

  6. Critical behavior of a two-step contagion model with multiple seeds

    NASA Astrophysics Data System (ADS)

    Choi, Wonjun; Lee, Deokjae; Kahng, B.

    2017-06-01

    A two-step contagion model with a single seed serves as a cornerstone for understanding the critical behaviors and underlying mechanism of discontinuous percolation transitions induced by cascade dynamics. When the contagion spreads from a single seed, a cluster of infected and recovered nodes grows without any cluster merging process. However, when the contagion starts from multiple seeds of O (N ) where N is the system size, a node weakened by a seed can be infected more easily when it is in contact with another node infected by a different pathogen seed. This contagion process can be viewed as a cluster merging process in a percolation model. Here we show analytically and numerically that when the density of infectious seeds is relatively small but O (1 ) , the epidemic transition is hybrid, exhibiting both continuous and discontinuous behavior, whereas when it is sufficiently large and reaches a critical point, the transition becomes continuous. We determine the full set of critical exponents describing the hybrid and the continuous transitions. Their critical behaviors differ from those in the single-seed case.

  7. Voting contagion: Modeling and analysis of a century of U.S. presidential elections

    PubMed Central

    de Aguiar, Marcus A. M.

    2017-01-01

    Social influence plays an important role in human behavior and decisions. Sources of influence can be divided as external, which are independent of social context, or as originating from peers, such as family and friends. An important question is how to disentangle the social contagion by peers from external influences. While a variety of experimental and observational studies provided insight into this problem, identifying the extent of contagion based on large-scale observational data with an unknown network structure remains largely unexplored. By bridging the gap between the large-scale complex systems perspective of collective human dynamics and the detailed approach of social sciences, we present a parsimonious model of social influence, and apply it to a central topic in political science—elections and voting behavior. We provide an analytical expression of the county vote-share distribution, which is in excellent agreement with almost a century of observed U.S. presidential election data. Analyzing the social influence topography over this period reveals an abrupt phase transition from low to high levels of social contagion, and robust differences among regions. These results suggest that social contagion effects are becoming more instrumental in shaping large-scale collective political behavior, with implications on democratic electoral processes and policies. PMID:28542409

  8. Dynamical influence processes on networks: general theory and applications to social contagion.

    PubMed

    Harris, Kameron Decker; Danforth, Christopher M; Dodds, Peter Sheridan

    2013-08-01

    We study binary state dynamics on a network where each node acts in response to the average state of its neighborhood. By allowing varying amounts of stochasticity in both the network and node responses, we find different outcomes in random and deterministic versions of the model. In the limit of a large, dense network, however, we show that these dynamics coincide. We construct a general mean-field theory for random networks and show this predicts that the dynamics on the network is a smoothed version of the average response function dynamics. Thus, the behavior of the system can range from steady state to chaotic depending on the response functions, network connectivity, and update synchronicity. As a specific example, we model the competing tendencies of imitation and nonconformity by incorporating an off-threshold into standard threshold models of social contagion. In this way, we attempt to capture important aspects of fashions and societal trends. We compare our theory to extensive simulations of this "limited imitation contagion" model on Poisson random graphs, finding agreement between the mean-field theory and stochastic simulations.

  9. Mathematical modelling of complex contagion on clustered networks

    NASA Astrophysics Data System (ADS)

    O'sullivan, David J.; O'Keeffe, Gary; Fennell, Peter; Gleeson, James

    2015-09-01

    The spreading of behavior, such as the adoption of a new innovation, is influenced bythe structure of social networks that interconnect the population. In the experiments of Centola (Science, 2010), adoption of new behavior was shown to spread further and faster across clustered-lattice networks than across corresponding random networks. This implies that the “complex contagion” effects of social reinforcement are important in such diffusion, in contrast to “simple” contagion models of disease-spread which predict that epidemics would grow more efficiently on random networks than on clustered networks. To accurately model complex contagion on clustered networks remains a challenge because the usual assumptions (e.g. of mean-field theory) regarding tree-like networks are invalidated by the presence of triangles in the network; the triangles are, however, crucial to the social reinforcement mechanism, which posits an increased probability of a person adopting behavior that has been adopted by two or more neighbors. In this paper we modify the analytical approach that was introduced by Hebert-Dufresne et al. (Phys. Rev. E, 2010), to study disease-spread on clustered networks. We show how the approximation method can be adapted to a complex contagion model, and confirm the accuracy of the method with numerical simulations. The analytical results of the model enable us to quantify the level of social reinforcement that is required to observe—as in Centola’s experiments—faster diffusion on clustered topologies than on random networks.

  10. Simulation of emotional contagion using modified SIR model: A cellular automaton approach

    NASA Astrophysics Data System (ADS)

    Fu, Libi; Song, Weiguo; Lv, Wei; Lo, Siuming

    2014-07-01

    Emotion plays an important role in the decision-making of individuals in some emergency situations. The contagion of emotion may induce either normal or abnormal consolidated crowd behavior. This paper aims to simulate the dynamics of emotional contagion among crowds by modifying the epidemiological SIR model to a cellular automaton approach. This new cellular automaton model, entitled the “CA-SIRS model”, captures the dynamic process ‘susceptible-infected-recovered-susceptible', which is based on SIRS contagion in epidemiological theory. Moreover, in this new model, the process is integrated with individual movement. The simulation results of this model show that multiple waves and dynamical stability around a mean value will appear during emotion spreading. It was found that the proportion of initial infected individuals had little influence on the final stable proportion of infected population in a given system, and that infection frequency increased with an increase in the average crowd density. Our results further suggest that individual movement accelerates the spread speed of emotion and increases the stable proportion of infected population. Furthermore, decreasing the duration of an infection and the probability of reinfection can markedly reduce the number of infected individuals. It is hoped that this study will be helpful in crowd management and evacuation organization.

  11. Multi-stage complex contagions

    NASA Astrophysics Data System (ADS)

    Melnik, Sergey; Ward, Jonathan A.; Gleeson, James P.; Porter, Mason A.

    2013-03-01

    The spread of ideas across a social network can be studied using complex contagion models, in which agents are activated by contact with multiple activated neighbors. The investigation of complex contagions can provide crucial insights into social influence and behavior-adoption cascades on networks. In this paper, we introduce a model of a multi-stage complex contagion on networks. Agents at different stages—which could, for example, represent differing levels of support for a social movement or differing levels of commitment to a certain product or idea—exert different amounts of influence on their neighbors. We demonstrate that the presence of even one additional stage introduces novel dynamical behavior, including interplay between multiple cascades, which cannot occur in single-stage contagion models. We find that cascades—and hence collective action—can be driven not only by high-stage influencers but also by low-stage influencers.

  12. Multi-stage complex contagions.

    PubMed

    Melnik, Sergey; Ward, Jonathan A; Gleeson, James P; Porter, Mason A

    2013-03-01

    The spread of ideas across a social network can be studied using complex contagion models, in which agents are activated by contact with multiple activated neighbors. The investigation of complex contagions can provide crucial insights into social influence and behavior-adoption cascades on networks. In this paper, we introduce a model of a multi-stage complex contagion on networks. Agents at different stages-which could, for example, represent differing levels of support for a social movement or differing levels of commitment to a certain product or idea-exert different amounts of influence on their neighbors. We demonstrate that the presence of even one additional stage introduces novel dynamical behavior, including interplay between multiple cascades, which cannot occur in single-stage contagion models. We find that cascades-and hence collective action-can be driven not only by high-stage influencers but also by low-stage influencers.

  13. Sentiment Contagion Based on the Modified SOSa-SPSa Model

    PubMed Central

    Song, Zhijie; Jia, Jie; Wang, Jian

    2016-01-01

    Sentiment contagion is similar to an infectious disease that spreads in a crowd. In this study, we extend the proposed SOSa-SPSa model (susceptible-optimistic-susceptible and susceptible-pessimistic-susceptible) by considering the interaction between optimists and pessimists. Simulation results show that our model is reasonable and can better explain the entire contagion process by considering three groups of people. The recovery speed of pessimists has an obvious regulative effect on the number of pessimists and the possibility of optimists coming in contact with pessimists to be infected as pessimism plays a greater role than that of reverting to susceptibility. The number of pessimists is positively related to the possibility that optimists come in contact with pessimists to become pessimistic but is negatively related to the possibility of the other way around. When the speed of spontaneous generation is slow, the number of pessimists sharply increases. However, the increase is not so apparent when the speed of spontaneous generation reaches a certain number. PMID:27746827

  14. Exploring a contagion model for karst terrane evolution

    SciTech Connect

    Kemmerly, P.R.

    1985-01-01

    The theoretical and geomorphic implications of a contagion model of karst depression and initiation are explored with particular emphasis on (1) identifying the parent versus daughter depression subpopulations; (2) analyzing the spatial characteristics of each subpopulation; and (3) defining the contagious karst mechanism and hot it is transmitted along solution-enlarged joints. The contagious karst mechanism suggests that the presence of one or more parent depressions does increase the the probability of daughter depressions developing along solution-enlarged joints that radiate outward from beneath parent depressions. In karst terranes where the contagious model applies, a well defined infrastructure exists with several important elements. The interaction of these elements in the infrastructure result in depressions occurring in clusters. The clusters tend to be randomly distributed and consist typically of a centrally located parent depression surrounded by numerous daughter depressions.

  15. Social contagion theory: examining dynamic social networks and human behavior

    PubMed Central

    Christakis, Nicholas A.; Fowler, James H.

    2013-01-01

    Here, we review the research we have conducted on social contagion. We describe the methods we have employed (and the assumptions they have entailed) to examine several datasets with complementary strengths and weaknesses, including the Framingham Heart Study, the National Longitudinal Study of Adolescent Health, and other observational and experimental datasets that we and others have collected. We describe the regularities that led us to propose that human social networks may exhibit a ‘three degrees of influence’ property, and we review statistical approaches we have used to characterize interpersonal influence with respect to phenomena as diverse as obesity, smoking, cooperation, and happiness. We do not claim that this work is the final word, but we do believe that it provides some novel, informative, and stimulating evidence regarding social contagion in longitudinally followed networks. Along with other scholars, we are working to develop new methods for identifying causal effects using social network data, and we believe that this area is ripe for statistical development as current methods have known and often unavoidable limitations. PMID:22711416

  16. Social contagion theory: examining dynamic social networks and human behavior.

    PubMed

    Christakis, Nicholas A; Fowler, James H

    2013-02-20

    Here, we review the research we have conducted on social contagion. We describe the methods we have employed (and the assumptions they have entailed) to examine several datasets with complementary strengths and weaknesses, including the Framingham Heart Study, the National Longitudinal Study of Adolescent Health, and other observational and experimental datasets that we and others have collected. We describe the regularities that led us to propose that human social networks may exhibit a 'three degrees of influence' property, and we review statistical approaches we have used to characterize interpersonal influence with respect to phenomena as diverse as obesity, smoking, cooperation, and happiness. We do not claim that this work is the final word, but we do believe that it provides some novel, informative, and stimulating evidence regarding social contagion in longitudinally followed networks. Along with other scholars, we are working to develop new methods for identifying causal effects using social network data, and we believe that this area is ripe for statistical development as current methods have known and often unavoidable limitations.

  17. Infectious Disease Modeling of Social Contagion in Networks

    PubMed Central

    Hill, Alison L.; Rand, David G.; Nowak, Martin A.; Christakis, Nicholas A.

    2010-01-01

    Many behavioral phenomena have been found to spread interpersonally through social networks, in a manner similar to infectious diseases. An important difference between social contagion and traditional infectious diseases, however, is that behavioral phenomena can be acquired by non-social mechanisms as well as through social transmission. We introduce a novel theoretical framework for studying these phenomena (the SISa model) by adapting a classic disease model to include the possibility for ‘automatic’ (or ‘spontaneous’) non-social infection. We provide an example of the use of this framework by examining the spread of obesity in the Framingham Heart Study Network. The interaction assumptions of the model are validated using longitudinal network transmission data. We find that the current rate of becoming obese is 2 per year and increases by 0.5 percentage points for each obese social contact. The rate of recovering from obesity is 4 per year, and does not depend on the number of non-obese contacts. The model predicts a long-term obesity prevalence of approximately 42, and can be used to evaluate the effect of different interventions on steady-state obesity. Model predictions quantitatively reproduce the actual historical time course for the prevalence of obesity. We find that since the 1970s, the rate of recovery from obesity has remained relatively constant, while the rates of both spontaneous infection and transmission have steadily increased over time. This suggests that the obesity epidemic may be driven by increasing rates of becoming obese, both spontaneously and transmissively, rather than by decreasing rates of losing weight. A key feature of the SISa model is its ability to characterize the relative importance of social transmission by quantitatively comparing rates of spontaneous versus contagious infection. It provides a theoretical framework for studying the interpersonal spread of any state that may also arise spontaneously, such as emotions

  18. Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks.

    PubMed

    Aral, Sinan; Muchnik, Lev; Sundararajan, Arun

    2009-12-22

    Node characteristics and behaviors are often correlated with the structure of social networks over time. While evidence of this type of assortative mixing and temporal clustering of behaviors among linked nodes is used to support claims of peer influence and social contagion in networks, homophily may also explain such evidence. Here we develop a dynamic matched sample estimation framework to distinguish influence and homophily effects in dynamic networks, and we apply this framework to a global instant messaging network of 27.4 million users, using data on the day-by-day adoption of a mobile service application and users' longitudinal behavioral, demographic, and geographic data. We find that previous methods overestimate peer influence in product adoption decisions in this network by 300-700%, and that homophily explains >50% of the perceived behavioral contagion. These findings and methods are essential to both our understanding of the mechanisms that drive contagions in networks and our knowledge of how to propagate or combat them in domains as diverse as epidemiology, marketing, development economics, and public health.

  19. Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks

    PubMed Central

    Aral, Sinan; Muchnik, Lev; Sundararajan, Arun

    2009-01-01

    Node characteristics and behaviors are often correlated with the structure of social networks over time. While evidence of this type of assortative mixing and temporal clustering of behaviors among linked nodes is used to support claims of peer influence and social contagion in networks, homophily may also explain such evidence. Here we develop a dynamic matched sample estimation framework to distinguish influence and homophily effects in dynamic networks, and we apply this framework to a global instant messaging network of 27.4 million users, using data on the day-by-day adoption of a mobile service application and users' longitudinal behavioral, demographic, and geographic data. We find that previous methods overestimate peer influence in product adoption decisions in this network by 300–700%, and that homophily explains >50% of the perceived behavioral contagion. These findings and methods are essential to both our understanding of the mechanisms that drive contagions in networks and our knowledge of how to propagate or combat them in domains as diverse as epidemiology, marketing, development economics, and public health. PMID:20007780

  20. A frailty-contagion model for multi-site hourly precipitation driven by atmospheric covariates

    NASA Astrophysics Data System (ADS)

    Koch, Erwan; Naveau, Philippe

    2015-04-01

    Accurate stochastic simulations of hourly precipitation are needed for impact studies at local spatial scales. Statistically, hourly precipitation data represent a difficult challenge. They are non-negative, skewed, heavy tailed, contain a lot of zeros (dry hours) and they have complex temporal structures (e.g., long persistence of dry episodes). Inspired by frailty-contagion approaches used in finance and insurance, we propose a multi-site precipitation simulator that, given appropriate regional atmospheric variables, can simultaneously handle dry events and heavy rainfall periods. One advantage of our model is its conceptual simplicity in its dynamical structure. In particular, the temporal variability is represented by a common factor based on a few classical atmospheric covariates like temperatures, pressures and others. Our inference approach is tested on simulated data and applied on measurements made in the northern part of French Brittany.

  1. Context-dependent colonization dynamics: Regional reward contagion drives local compression in aquatic beetles.

    PubMed

    Pintar, Matthew R; Resetarits, William J

    2017-09-01

    Habitat selection by colonizing organisms is an important factor in determining species abundance and community dynamics at multiple spatial scales. Many organisms select habitat patches based on intrinsic patch quality, but patches exist in complex landscapes linked by dispersal and colonization, forming metapopulations and metacommunities. Perceived patch quality can be influenced by neighbouring patches through spatial contagion, wherein perceived quality of one patch can extend beyond its borders and either increase or decrease the colonization of neighbouring patches and localities. These spatially explicit colonization dynamics can result in habitat compression, wherein more colonists occupy a patch or locality than in the absence of spatial context dependence. Previous work on contagion/compression focused primarily on the role of predators in driving colonization patterns. Our goal was to determine whether resource abundance can drive multi-scale colonization dynamics of aquatic beetles through the processes of contagion and compression in naturally colonized experimental pools. We established two levels (high/low quality) of within-patch resource abundances (leaf litter) using an experimental landscape of mesocosms, and assayed colonization by 35 species of aquatic beetles. Patches were arranged in localities (sets of two patches), which consisted of a combination of two patch-level resource levels in a 2 × 2 factorial design, allowing us to assay colonization at both locality and patch levels. We demonstrate that patterns of species abundance and richness of colonizing aquatic beetles are determined by patch quality and context-dependent processes at multiple spatial scales. Localities that consisted of at least one high-quality patch were colonized at equivalent rates that were higher than localities containing only low-quality patches, displaying regional reward contagion. In localities that consisted of one high- and one low-quality patch, reward

  2. Connectivity interplays with age in shaping contagion over networks with vital dynamics

    NASA Astrophysics Data System (ADS)

    Piccardi, Carlo; Colombo, Alessandro; Casagrandi, Renato

    2015-02-01

    The effects of network topology on the emergence and persistence of infectious diseases have been broadly explored in recent years. However, the influence of the vital dynamics of the hosts (i.e., birth-death processes) on the network structure, and their effects on the pattern of epidemics, have received less attention in the scientific community. Here, we study Susceptible-Infected-Recovered(-Susceptible) [SIR(S)] contact processes in standard networks (of Erdös-Rényi and Barabási-Albert type) that are subject to host demography. Accounting for the vital dynamics of hosts is far from trivial, and it causes the scale-free networks to lose their characteristic fat-tailed degree distribution. We introduce a broad class of models that integrate the birth and death of individuals (nodes) with the simplest mechanisms of infection and recovery, thus generating age-degree structured networks of hosts that interact in a complex manner. In our models, the epidemiological state of each individual may depend both on the number of contacts (which changes through time because of the birth-death process) and on its age, paving the way for a possible age-dependent description of contagion and recovery processes. We study how the proportion of infected individuals scales with the number of contacts among them. Rather unexpectedly, we discover that the result of highly connected individuals at the highest risk of infection is not as general as commonly believed. In infections that confer permanent immunity to individuals of vital populations (SIR processes), the nodes that are most likely to be infected are those with intermediate degrees. Our age-degree structured models allow such findings to be deeply analyzed and interpreted, and they may aid in the development of effective prevention policies.

  3. Connectivity interplays with age in shaping contagion over networks with vital dynamics.

    PubMed

    Piccardi, Carlo; Colombo, Alessandro; Casagrandi, Renato

    2015-02-01

    The effects of network topology on the emergence and persistence of infectious diseases have been broadly explored in recent years. However, the influence of the vital dynamics of the hosts (i.e., birth-death processes) on the network structure, and their effects on the pattern of epidemics, have received less attention in the scientific community. Here, we study Susceptible-Infected-Recovered(-Susceptible) [SIR(S)] contact processes in standard networks (of Erdös-Rényi and Barabási-Albert type) that are subject to host demography. Accounting for the vital dynamics of hosts is far from trivial, and it causes the scale-free networks to lose their characteristic fat-tailed degree distribution. We introduce a broad class of models that integrate the birth and death of individuals (nodes) with the simplest mechanisms of infection and recovery, thus generating age-degree structured networks of hosts that interact in a complex manner. In our models, the epidemiological state of each individual may depend both on the number of contacts (which changes through time because of the birth-death process) and on its age, paving the way for a possible age-dependent description of contagion and recovery processes. We study how the proportion of infected individuals scales with the number of contacts among them. Rather unexpectedly, we discover that the result of highly connected individuals at the highest risk of infection is not as general as commonly believed. In infections that confer permanent immunity to individuals of vital populations (SIR processes), the nodes that are most likely to be infected are those with intermediate degrees. Our age-degree structured models allow such findings to be deeply analyzed and interpreted, and they may aid in the development of effective prevention policies.

  4. Derivatives and credit contagion in interconnected networks

    NASA Astrophysics Data System (ADS)

    Heise, S.; Kühn, R.

    2012-04-01

    The importance of adequately modeling credit risk has once again been highlighted in the recent financial crisis. Defaults tend to cluster around times of economic stress due to poor macro-economic conditions, but also by directly triggering each other through contagion. Although credit default swaps have radically altered the dynamics of contagion for more than a decade, models quantifying their impact on systemic risk are still missing. Here, we examine contagion through credit default swaps in a stylized economic network of corporates and financial institutions. We analyse such a system using a stochastic setting, which allows us to exploit limit theorems to exactly solve the contagion dynamics for the entire system. Our analysis shows that, by creating additional contagion channels, CDS can actually lead to greater instability of the entire network in times of economic stress. This is particularly pronounced when CDS are used by banks to expand their loan books (arguing that CDS would offload the additional risks from their balance sheets). Thus, even with complete hedging through CDS, a significant loan book expansion can lead to considerably enhanced probabilities for the occurrence of very large losses and very high default rates in the system. Our approach adds a new dimension to research on credit contagion, and could feed into a rational underpinning of an improved regulatory framework for credit derivatives.

  5. A Model of Contagion through Competition in the Aggressive Behaviors of Elementary School Students.

    ERIC Educational Resources Information Center

    Warren, Keith; Schoppelrey, Susan; Moberg, D. Paul; McDonald, Marilyn

    2005-01-01

    This article extends the work of Kellam, Ling, Merisca, Brown and Ialongo (1998) by applying a mathematical model of competition between children to peer contagion in the aggressive behaviors of elementary school students. Nonlinearity in the relationship between group aggression and individual aggression at 2-year follow-up is present. Consistent…

  6. A Model of Contagion through Competition in the Aggressive Behaviors of Elementary School Students.

    ERIC Educational Resources Information Center

    Warren, Keith; Schoppelrey, Susan; Moberg, D. Paul; McDonald, Marilyn

    2005-01-01

    This article extends the work of Kellam, Ling, Merisca, Brown and Ialongo (1998) by applying a mathematical model of competition between children to peer contagion in the aggressive behaviors of elementary school students. Nonlinearity in the relationship between group aggression and individual aggression at 2-year follow-up is present. Consistent…

  7. Contagion effects in a chartist fundamentalist model with time delays

    NASA Astrophysics Data System (ADS)

    Dibeh, Ghassan

    2007-08-01

    In this paper two models of speculative markets are developed to study the effects of feedback mechanisms in financial markets. In the first model, a crash market model couples a linear chartist-fundamentalist model with time delays with a log-periodic market index I(t) through direct coupling. Numerical solutions to the model show that asset prices exhibit significant persistence as a result of the coupling to the log-periodic market index. An extension to include endogenous wealth dynamics shows that the chartists benefit from the persistent dynamics induced by the coupling. The second model is a two-asset model represented by a 2-dimensional delay-differential equation. Asset one price exhibits limit cycle dynamics while in the second market asset prices follow stable damped oscillations. The markets are coupled through a diffusive coupling term. Solutions to the coupled model show that the dynamics of asset two changes fundamentally with the price now exhibiting a limit cycle. The stable converging dynamics is replaced with limit cycle oscillations around the fundamental.

  8. Boolean network representation of contagion dynamics during a financial crisis

    NASA Astrophysics Data System (ADS)

    Caetano, Marco Antonio Leonel; Yoneyama, Takashi

    2015-01-01

    This work presents a network model for representation of the evolution of certain patterns of economic behavior. More specifically, after representing the agents as points in a space in which each dimension associated to a relevant economic variable, their relative "motions" that can be either stationary or discordant, are coded into a boolean network. Patterns with stationary averages indicate the maintenance of status quo, whereas discordant patterns represent aggregation of new agent into the cluster or departure from the former policies. The changing patterns can be embedded into a network representation, particularly using the concept of autocatalytic boolean networks. As a case study, the economic tendencies of the BRIC countries + Argentina were studied. Although Argentina is not included in the cluster formed by BRIC countries, it tends to follow the BRIC members because of strong commercial ties.

  9. Modeling Contagion Through Social Networks to Explain and Predict Gunshot Violence in Chicago, 2006 to 2014.

    PubMed

    Green, Ben; Horel, Thibaut; Papachristos, Andrew V

    2017-03-01

    Every day in the United States, more than 200 people are murdered or assaulted with a firearm. Little research has considered the role of interpersonal ties in the pathways through which gun violence spreads. To evaluate the extent to which the people who will become subjects of gun violence can be predicted by modeling gun violence as an epidemic that is transmitted between individuals through social interactions. This study was an epidemiological analysis of a social network of individuals who were arrested during an 8-year period in Chicago, Illinois, with connections between people who were arrested together for the same offense. Modeling of the spread of gunshot violence over the network was assessed using a probabilistic contagion model that assumed individuals were subject to risks associated with being arrested together, in addition to demographic factors, such as age, sex, and neighborhood residence. Participants represented a network of 138 163 individuals who were arrested between January 1, 2006, and March 31, 2014 (29.9% of all individuals arrested in Chicago during this period), 9773 of whom were subjects of gun violence. Individuals were on average 27 years old at the midpoint of the study, predominantly male (82.0%) and black (75.6%), and often members of a gang (26.2%). Explanation and prediction of becoming a subject of gun violence (fatal or nonfatal) using epidemic models based on person-to-person transmission through a social network. Social contagion accounted for 63.1% of the 11 123 gunshot violence episodes; subjects of gun violence were shot on average 125 days after their infector (the person most responsible for exposing the subject to gunshot violence). Some subjects of gun violence were shot more than once. Models based on both social contagion and demographics performed best; when determining the 1.0% of people (n = 1382) considered at highest risk to be shot each day, the combined model identified 728 subjects of gun violence

  10. Limitations of discrete-time approaches to continuous-time contagion dynamics

    NASA Astrophysics Data System (ADS)

    Fennell, Peter G.; Melnik, Sergey; Gleeson, James P.

    2016-11-01

    Continuous-time Markov process models of contagions are widely studied, not least because of their utility in predicting the evolution of real-world contagions and in formulating control measures. It is often the case, however, that discrete-time approaches are employed to analyze such models or to simulate them numerically. In such cases, time is discretized into uniform steps and transition rates between states are replaced by transition probabilities. In this paper, we illustrate potential limitations to this approach. We show how discretizing time leads to a restriction on the values of the model parameters that can accurately be studied. We examine numerical simulation schemes employed in the literature, showing how synchronous-type updating schemes can bias discrete-time formalisms when compared against continuous-time formalisms. Event-based simulations, such as the Gillespie algorithm, are proposed as optimal simulation schemes both in terms of replicating the continuous-time process and computational speed. Finally, we show how discretizing time can affect the value of the epidemic threshold for large values of the infection rate and the recovery rate, even if the ratio between the former and the latter is small.

  11. Modeling colony collapse disorder in honeybees as a contagion.

    PubMed

    Kribs-Zaleta, Christopher M; Mitchell, Christopher

    2014-12-01

    Honeybee pollination accounts annually for over $14 billion in United States agriculture alone. Within the past decade there has been a mysterious mass die-off of honeybees, an estimated 10 million beehives and sometimes as much as 90% of an apiary. There is still no consensus on what causes this phenomenon, called Colony Collapse Disorder, or CCD. Several mathematical models have studied CCD by only focusing on infection dynamics. We created a model to account for both healthy hive dynamics and hive extinction due to CCD, modeling CCD via a transmissible infection brought to the hive by foragers. The system of three ordinary differential equations accounts for multiple hive population behaviors including Allee effects and colony collapse. Numerical analysis leads to critical hive sizes for multiple scenarios and highlights the role of accelerated forager recruitment in emptying hives during colony collapse.

  12. Connecting minds and sharing emotions through mimicry: A neurocognitive model of emotional contagion.

    PubMed

    Prochazkova, Eliska; Kret, Mariska E

    2017-05-12

    During social interactions, people tend to automatically align with, or mimic their interactor's facial expressions, vocalizations, postures and other bodily states. Automatic mimicry might be implicated in empathy and affiliation and is impaired in several pathologies. Despite a growing body of literature on its phenomenology, the function and underlying mechanisms of mimicry remain poorly understood. The current review puts forward a new Neurocognitive Model of Emotional Contagion (NMEC), demonstrating how basic automatic mimicry can give rise to emotional contagion. We combine neurological, developmental and evolutionary insights to argue that automatic mimicry is a precursor to healthy social development. We show that (i) strong synchronization exists between people, (ii) that this resonates on different levels of processing and (iii) demonstrate how mimicry translates into emotional contagion. We conclude that our synthesized model, built upon integrative knowledge from various fields, provides a promising avenue for future research investigating the role of mimicry in human mental health and social development. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  13. The Contagion of Stress across Multiple Roles.

    ERIC Educational Resources Information Center

    Bolger, Niall; And Others

    1989-01-01

    Examined causal dynamics of stress contagion across work and home domains in married couples. Results revealed that husbands were more likely than wives to bring home stresses into workplace. Stress contagion from work to home was evident for both husbands and wives. Contagion of work stress into home appeared to set into motion process of dyadic…

  14. Social contagions on weighted networks

    NASA Astrophysics Data System (ADS)

    Zhu, Yu-Xiao; Wang, Wei; Tang, Ming; Ahn, Yong-Yeol

    2017-07-01

    We investigate critical behaviors of a social contagion model on weighted networks. An edge-weight compartmental approach is applied to analyze the weighted social contagion on strongly heterogenous networks with skewed degree and weight distributions. We find that degree heterogeneity cannot only alter the nature of contagion transition from discontinuous to continuous but also can enhance or hamper the size of adoption, depending on the unit transmission probability. We also show that the heterogeneity of weight distribution always hinders social contagions, and does not alter the transition type.

  15. Modeling the obesity epidemic: social contagion and its implications for control

    PubMed Central

    2013-01-01

    Background As an obesity epidemic has grown worldwide, a variety of intervention programs have been considered, but a scientific approach to comparatively assessing the control programs has still to be considered. The present study aims to describe an obesity epidemic by employing a simple mathematical model that accounts for both social contagion and non-contagious hazards of obesity, thereby comparing the effectiveness of different types of interventions. Methods An epidemiological model is devised to describe the time- and age-dependent risk of obesity, the hazard of which is dealt with as both dependent on and independent of obesity prevalence, and parameterizing the model using empirically observed data. The equilibrium prevalence is investigated as our epidemiological outcome, assessing its sensitivity to different parameters that regulate the impact of intervention programs and qualitatively comparing the effectiveness. We compare the effectiveness of different types of interventions, including those directed to never-obese individuals (i.e. primary prevention) and toward obese and ex-obese individuals (i.e. secondary prevention). Results The optimal choice of intervention programs considerably varies with the transmission coefficient of obesity, and a limited transmissibility led us to favour preventing weight gain among never-obese individuals. An abrupt decline in the prevalence is expected when the hazards of obesity through contagious and non-contagious routes fall into a particular parameter space, with a high sensitivity to the transmission potential of obesity from person to person. When a combination of two control strategies can be selected, primary and secondary preventions yielded similar population impacts and the superiority of the effectiveness depends on the strength of the interventions at an individual level. Conclusions The optimality of intervention programs depends on the contagiousness of obesity. Filling associated data gaps of obesity

  16. When is emotional contagion adaptive?

    PubMed

    Nakahashi, Wataru; Ohtsuki, Hisashi

    2015-09-07

    Empathy plays an important role in animal social behavior. Since emotional contagion forms one of the bases of empathy, here we study conditions for emotional contagion to be adaptive, compared with other behavioral rules such as behavioral mimicry. We consider the situation where the focal individual (=observer) reacts to a behavior of another individual (=demonstrator). By emotional contagion one spontaneously copies the emotional state of the demonstrator and takes a behavior driven by that emotion. By behavioral mimicry, in contrast, one copies the behavior of the demonstrator itself. Through mathematical models we show that emotional contagion is adaptive when the environmental similarity between the demonstrator and the observer is intermediate. The advantage of adopting emotional contagion over behavioral mimicry increases when observing others' behavior is difficult or cognitively demanding. We show that emotional contagion is often a more flexible strategy than behavioral mimicry in order to cope with the living environment. In other words, emotional contagion often works as a better social learning strategy. These results suggest some ecological conditions that would favor the evolution of emotional contagion, and give a part of the explanations of why emotional contagion is frequently observed in group-living animals. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Social contagions on interdependent lattice networks

    PubMed Central

    Shu, Panpan; Gao, Lei; Zhao, Pengcheng; Wang, Wei; Stanley, H. Eugene

    2017-01-01

    Although an increasing amount of research is being done on the dynamical processes on interdependent spatial networks, knowledge of how interdependent spatial networks influence the dynamics of social contagion in them is sparse. Here we present a novel non-Markovian social contagion model on interdependent spatial networks composed of two identical two-dimensional lattices. We compare the dynamics of social contagion on networks with different fractions of dependency links and find that the density of final recovered nodes increases as the number of dependency links is increased. We use a finite-size analysis method to identify the type of phase transition in the giant connected components (GCC) of the final adopted nodes and find that as we increase the fraction of dependency links, the phase transition switches from second-order to first-order. In strong interdependent spatial networks with abundant dependency links, increasing the fraction of initial adopted nodes can induce the switch from a first-order to second-order phase transition associated with social contagion dynamics. In networks with a small number of dependency links, the phase transition remains second-order. In addition, both the second-order and first-order phase transition points can be decreased by increasing the fraction of dependency links or the number of initially-adopted nodes. PMID:28300198

  18. Social contagions on interdependent lattice networks

    NASA Astrophysics Data System (ADS)

    Shu, Panpan; Gao, Lei; Zhao, Pengcheng; Wang, Wei; Stanley, H. Eugene

    2017-03-01

    Although an increasing amount of research is being done on the dynamical processes on interdependent spatial networks, knowledge of how interdependent spatial networks influence the dynamics of social contagion in them is sparse. Here we present a novel non-Markovian social contagion model on interdependent spatial networks composed of two identical two-dimensional lattices. We compare the dynamics of social contagion on networks with different fractions of dependency links and find that the density of final recovered nodes increases as the number of dependency links is increased. We use a finite-size analysis method to identify the type of phase transition in the giant connected components (GCC) of the final adopted nodes and find that as we increase the fraction of dependency links, the phase transition switches from second-order to first-order. In strong interdependent spatial networks with abundant dependency links, increasing the fraction of initial adopted nodes can induce the switch from a first-order to second-order phase transition associated with social contagion dynamics. In networks with a small number of dependency links, the phase transition remains second-order. In addition, both the second-order and first-order phase transition points can be decreased by increasing the fraction of dependency links or the number of initially-adopted nodes.

  19. Social contagions on interdependent lattice networks.

    PubMed

    Shu, Panpan; Gao, Lei; Zhao, Pengcheng; Wang, Wei; Stanley, H Eugene

    2017-03-16

    Although an increasing amount of research is being done on the dynamical processes on interdependent spatial networks, knowledge of how interdependent spatial networks influence the dynamics of social contagion in them is sparse. Here we present a novel non-Markovian social contagion model on interdependent spatial networks composed of two identical two-dimensional lattices. We compare the dynamics of social contagion on networks with different fractions of dependency links and find that the density of final recovered nodes increases as the number of dependency links is increased. We use a finite-size analysis method to identify the type of phase transition in the giant connected components (GCC) of the final adopted nodes and find that as we increase the fraction of dependency links, the phase transition switches from second-order to first-order. In strong interdependent spatial networks with abundant dependency links, increasing the fraction of initial adopted nodes can induce the switch from a first-order to second-order phase transition associated with social contagion dynamics. In networks with a small number of dependency links, the phase transition remains second-order. In addition, both the second-order and first-order phase transition points can be decreased by increasing the fraction of dependency links or the number of initially-adopted nodes.

  20. An Information Perception-Based Emotion Contagion Model for Fire Evacuation

    NASA Astrophysics Data System (ADS)

    Liu, Ting Ting; Liu, Zhen; Ma, Minhua; Xuan, Rongrong; Chen, Tian; Lu, Tao; Yu, Lipeng

    2017-03-01

    In fires, people are easier to lose their mind. Panic will lead to irrational behavior and irreparable tragedy. It has great practical significance to make contingency plans for crowd evacuation in fires. However, existing studies about crowd simulation always paid much attention on the crowd density, but little attention on emotional contagion that may cause a panic. Based on settings about information space and information sharing, this paper proposes an emotional contagion model for crowd in panic situations. With the proposed model, a behavior mechanism is constructed for agents in the crowd and a prototype of system is developed for crowd simulation. Experiments are carried out to verify the proposed model. The results showed that the spread of panic not only related to the crowd density and the individual comfort level, but also related to people's prior knowledge of fire evacuation. The model provides a new way for safety education and evacuation management. It is possible to avoid and reduce unsafe factors in the crowd with the lowest cost.

  1. Modeling the cooperative and competitive contagions in online social networks

    NASA Astrophysics Data System (ADS)

    Zhuang, Yun-Bei; Chen, J. J.; Li, Zhi-hong

    2017-10-01

    The wide adoption of social media has increased the interaction among different pieces of information, and this interaction includes cooperation and competition for our finite attention. While previous research focus on fully competition, this paper extends the interaction to be both ;cooperation; and ;competition;, by employing an IS1S2 R model. To explore how two different pieces of information interact with each other, the IS1S2 R model splits the agents into four parts-(Ignorant-Spreader I-Spreader II-Stifler), based on SIR epidemic spreading model. Using real data from Weibo.com, a social network site similar to Twitter, we find some parameters, like decaying rates, can both influence the cooperative diffusion process and the competitive process, while other parameters, like infectious rates only have influence on the competitive diffusion process. Besides, the parameters' effect are more significant in the competitive diffusion than in the cooperative diffusion.

  2. Contagion Shocks in One Dimension

    NASA Astrophysics Data System (ADS)

    Bertozzi, Andrea L.; Rosado, Jesus; Short, Martin B.; Wang, Li

    2015-02-01

    We consider an agent-based model of emotional contagion coupled with motion in one dimension that has recently been studied in the computer science community. The model involves movement with a speed proportional to a "fear" variable that undergoes a temporal consensus averaging based on distance to other agents. We study the effect of Riemann initial data for this problem, leading to shock dynamics that are studied both within the agent-based model as well as in a continuum limit. We examine the behavior of the model under distinguished limits as the characteristic contagion interaction distance and the interaction timescale both approach zero. The limiting behavior is related to a classical model for pressureless gas dynamics with "sticky" particles. In comparison, we observe a threshold for the interaction distance vs. interaction timescale that produce qualitatively different behavior for the system - in one case particle paths do not cross and there is a natural Eulerian limit involving nonlocal interactions and in the other case particle paths can cross and one may consider only a kinetic model in the continuum limit.

  3. The Nonverbal Transmission of Intergroup Bias: A Model of Bias Contagion with Implications for Social Policy

    PubMed Central

    Weisbuch, Max; Pauker, Kristin

    2013-01-01

    Social and policy interventions over the last half-century have achieved laudable reductions in blatant discrimination. Yet members of devalued social groups continue to face subtle discrimination. In this article, we argue that decades of anti-discrimination interventions have failed to eliminate intergroup bias because such bias is contagious. We present a model of bias contagion in which intergroup bias is subtly communicated through nonverbal behavior. Exposure to such nonverbal bias “infects” observers with intergroup bias. The model we present details two means by which nonverbal bias can be expressed—either as a veridical index of intergroup bias or as a symptom of worry about appearing biased. Exposure to this nonverbal bias can increase perceivers’ own intergroup biases through processes of implicit learning, informational influence, and normative influence. We identify critical moderators that may interfere with these processes and consequently propose several social and educational interventions based on these moderators. PMID:23997812

  4. A model of contagion through competition in the aggressive behaviors of elementary school students.

    PubMed

    Warren, Keith; Schoppelrey, Susan; Moberg, D Paul; McDonald, Marilyn

    2005-06-01

    This article extends the work of Kellam, Ling, Merisca, Brown and Ialongo (1998) by applying a mathematical model of competition between children to peer contagion in the aggressive behaviors of elementary school students. Nonlinearity in the relationship between group aggression and individual aggression at 2-year follow-up is present. Consistent with the findings of Kellam et al. (1998), hierarchical linear modeling indicates that the relationship is statistically significant for those students whose initial parental ratings of aggressive behavior were above the sample median. In the context of competition between students, the behavior of initially aggressive students may be negatively reinforced. Lowering aggression in the school environment may therefore be the most effective way to lower the level of these students' aggressive behavior.

  5. Structural diversity in social contagion.

    PubMed

    Ugander, Johan; Backstrom, Lars; Marlow, Cameron; Kleinberg, Jon

    2012-04-17

    The concept of contagion has steadily expanded from its original grounding in epidemic disease to describe a vast array of processes that spread across networks, notably social phenomena such as fads, political opinions, the adoption of new technologies, and financial decisions. Traditional models of social contagion have been based on physical analogies with biological contagion, in which the probability that an individual is affected by the contagion grows monotonically with the size of his or her "contact neighborhood"--the number of affected individuals with whom he or she is in contact. Whereas this contact neighborhood hypothesis has formed the underpinning of essentially all current models, it has been challenging to evaluate it due to the difficulty in obtaining detailed data on individual network neighborhoods during the course of a large-scale contagion process. Here we study this question by analyzing the growth of Facebook, a rare example of a social process with genuinely global adoption. We find that the probability of contagion is tightly controlled by the number of connected components in an individual's contact neighborhood, rather than by the actual size of the neighborhood. Surprisingly, once this "structural diversity" is controlled for, the size of the contact neighborhood is in fact generally a negative predictor of contagion. More broadly, our analysis shows how data at the size and resolution of the Facebook network make possible the identification of subtle structural signals that go undetected at smaller scales yet hold pivotal predictive roles for the outcomes of social processes.

  6. Dueling biological and social contagions.

    PubMed

    Fu, Feng; Christakis, Nicholas A; Fowler, James H

    2017-03-02

    Numerous models explore how a wide variety of biological and social phenomena spread in social networks. However, these models implicitly assume that the spread of one phenomenon is not affected by the spread of another. Here, we develop a model of "dueling contagions", with a particular illustration of a situation where one is biological (influenza) and the other is social (flu vaccination). We apply the model to unique time series data collected during the 2009 H1N1 epidemic that includes information about vaccination, flu, and face-to-face social networks. The results show that well-connected individuals are more likely to get vaccinated, as are people who are exposed to friends who get vaccinated or are exposed to friends who get the flu. Our dueling contagion model suggests that other epidemiological models may be dramatically underestimating the R0 of contagions. It also suggests that the rate of vaccination contagion may be even more important than the biological contagion in determining the course of the disease. These results suggest that real world and online platforms that make it easier to see when friends have been vaccinated (personalized vaccination campaigns) and when they get the flu (personalized flu warnings) could have a large impact on reducing the severity of epidemics. They also suggest possible benefits from understanding the coevolution of many kinds of dueling contagions.

  7. Dueling biological and social contagions

    PubMed Central

    Fu, Feng; Christakis, Nicholas A.; Fowler, James H.

    2017-01-01

    Numerous models explore how a wide variety of biological and social phenomena spread in social networks. However, these models implicitly assume that the spread of one phenomenon is not affected by the spread of another. Here, we develop a model of “dueling contagions”, with a particular illustration of a situation where one is biological (influenza) and the other is social (flu vaccination). We apply the model to unique time series data collected during the 2009 H1N1 epidemic that includes information about vaccination, flu, and face-to-face social networks. The results show that well-connected individuals are more likely to get vaccinated, as are people who are exposed to friends who get vaccinated or are exposed to friends who get the flu. Our dueling contagion model suggests that other epidemiological models may be dramatically underestimating the R0 of contagions. It also suggests that the rate of vaccination contagion may be even more important than the biological contagion in determining the course of the disease. These results suggest that real world and online platforms that make it easier to see when friends have been vaccinated (personalized vaccination campaigns) and when they get the flu (personalized flu warnings) could have a large impact on reducing the severity of epidemics. They also suggest possible benefits from understanding the coevolution of many kinds of dueling contagions. PMID:28252663

  8. Dueling biological and social contagions

    NASA Astrophysics Data System (ADS)

    Fu, Feng; Christakis, Nicholas A.; Fowler, James H.

    2017-03-01

    Numerous models explore how a wide variety of biological and social phenomena spread in social networks. However, these models implicitly assume that the spread of one phenomenon is not affected by the spread of another. Here, we develop a model of “dueling contagions”, with a particular illustration of a situation where one is biological (influenza) and the other is social (flu vaccination). We apply the model to unique time series data collected during the 2009 H1N1 epidemic that includes information about vaccination, flu, and face-to-face social networks. The results show that well-connected individuals are more likely to get vaccinated, as are people who are exposed to friends who get vaccinated or are exposed to friends who get the flu. Our dueling contagion model suggests that other epidemiological models may be dramatically underestimating the R0 of contagions. It also suggests that the rate of vaccination contagion may be even more important than the biological contagion in determining the course of the disease. These results suggest that real world and online platforms that make it easier to see when friends have been vaccinated (personalized vaccination campaigns) and when they get the flu (personalized flu warnings) could have a large impact on reducing the severity of epidemics. They also suggest possible benefits from understanding the coevolution of many kinds of dueling contagions.

  9. Beyond Contagion: Reality Mining Reveals Complex Patterns of Social Influence.

    PubMed

    Alshamsi, Aamena; Pianesi, Fabio; Lepri, Bruno; Pentland, Alex; Rahwan, Iyad

    2015-01-01

    Contagion, a concept from epidemiology, has long been used to characterize social influence on people's behavior and affective (emotional) states. While it has revealed many useful insights, it is not clear whether the contagion metaphor is sufficient to fully characterize the complex dynamics of psychological states in a social context. Using wearable sensors that capture daily face-to-face interaction, combined with three daily experience sampling surveys, we collected the most comprehensive data set of personality and emotion dynamics of an entire community of work. From this high-resolution data about actual (rather than self-reported) face-to-face interaction, a complex picture emerges where contagion (that can be seen as adaptation of behavioral responses to the behavior of other people) cannot fully capture the dynamics of transitory states. We found that social influence has two opposing effects on states: adaptation effects that go beyond mere contagion, and complementarity effects whereby individuals' behaviors tend to complement the behaviors of others. Surprisingly, these effects can exhibit completely different directions depending on the stable personality or emotional dispositions (stable traits) of target individuals. Our findings provide a foundation for richer models of social dynamics, and have implications on organizational engineering and workplace well-being.

  10. Beyond Contagion: Reality Mining Reveals Complex Patterns of Social Influence

    PubMed Central

    Alshamsi, Aamena; Pianesi, Fabio; Lepri, Bruno; Pentland, Alex; Rahwan, Iyad

    2015-01-01

    Contagion, a concept from epidemiology, has long been used to characterize social influence on people’s behavior and affective (emotional) states. While it has revealed many useful insights, it is not clear whether the contagion metaphor is sufficient to fully characterize the complex dynamics of psychological states in a social context. Using wearable sensors that capture daily face-to-face interaction, combined with three daily experience sampling surveys, we collected the most comprehensive data set of personality and emotion dynamics of an entire community of work. From this high-resolution data about actual (rather than self-reported) face-to-face interaction, a complex picture emerges where contagion (that can be seen as adaptation of behavioral responses to the behavior of other people) cannot fully capture the dynamics of transitory states. We found that social influence has two opposing effects on states: adaptation effects that go beyond mere contagion, and complementarity effects whereby individuals’ behaviors tend to complement the behaviors of others. Surprisingly, these effects can exhibit completely different directions depending on the stable personality or emotional dispositions (stable traits) of target individuals. Our findings provide a foundation for richer models of social dynamics, and have implications on organizational engineering and workplace well-being. PMID:26313449

  11. Structural diversity in social contagion

    PubMed Central

    Ugander, Johan; Backstrom, Lars; Marlow, Cameron; Kleinberg, Jon

    2012-01-01

    The concept of contagion has steadily expanded from its original grounding in epidemic disease to describe a vast array of processes that spread across networks, notably social phenomena such as fads, political opinions, the adoption of new technologies, and financial decisions. Traditional models of social contagion have been based on physical analogies with biological contagion, in which the probability that an individual is affected by the contagion grows monotonically with the size of his or her “contact neighborhood”—the number of affected individuals with whom he or she is in contact. Whereas this contact neighborhood hypothesis has formed the underpinning of essentially all current models, it has been challenging to evaluate it due to the difficulty in obtaining detailed data on individual network neighborhoods during the course of a large-scale contagion process. Here we study this question by analyzing the growth of Facebook, a rare example of a social process with genuinely global adoption. We find that the probability of contagion is tightly controlled by the number of connected components in an individual's contact neighborhood, rather than by the actual size of the neighborhood. Surprisingly, once this “structural diversity” is controlled for, the size of the contact neighborhood is in fact generally a negative predictor of contagion. More broadly, our analysis shows how data at the size and resolution of the Facebook network make possible the identification of subtle structural signals that go undetected at smaller scales yet hold pivotal predictive roles for the outcomes of social processes. PMID:22474360

  12. Seasonality and Dynamic Spatial Contagion of Air Pollution in 42 Chinese Cities

    PubMed Central

    He, Zhanqiong; Sriboonchita, Songsak; He, Min

    2013-01-01

    To monitor and improve the urban air quality, the Chinese government has begun to make many efforts, and the interregional cooperation to cut and improve air quality has been required. In this paper, we focus on the seasonality of the first and second moments of the daily air pollution indexes (APIs) of 42 Chinese sample cities over 10 years, from June 5, 2000 to March 4, 2010, and investigate the dynamic correlation of air pollution indexes (APIs) between 42 Chinese cities and their corresponding regional and national levels; comparison with the model without seasonal consideration is made. By adopting a DCC-GARCH model that accounts for the seasonality, we found that (i) the transformed DCC-GARCH model including seasonality dummies improves the estimation result in this study; (ii) the seasonality feature of the second moment follows that of the first moment, with the condition mean and variance of the second and autumn significantly lower than spring, whereas that of winter is higher than spring; (iii) the correlation between local APIs and their corresponding regional and national levels is dynamic; (iv) comparing with the DCC-GARCH model estimation, the transformed model does not change the feature of the dynamic correlations very much. PMID:23533348

  13. Seasonality and dynamic spatial contagion of air pollution in 42 Chinese cities.

    PubMed

    He, Zhanqiong; Sriboonchita, Songsak; He, Min

    2013-01-01

    To monitor and improve the urban air quality, the Chinese government has begun to make many efforts, and the interregional cooperation to cut and improve air quality has been required. In this paper, we focus on the seasonality of the first and second moments of the daily air pollution indexes (APIs) of 42 Chinese sample cities over 10 years, from June 5, 2000 to March 4, 2010, and investigate the dynamic correlation of air pollution indexes (APIs) between 42 Chinese cities and their corresponding regional and national levels; comparison with the model without seasonal consideration is made. By adopting a DCC-GARCH model that accounts for the seasonality, we found that (i) the transformed DCC-GARCH model including seasonality dummies improves the estimation result in this study; (ii) the seasonality feature of the second moment follows that of the first moment, with the condition mean and variance of the second and autumn significantly lower than spring, whereas that of winter is higher than spring; (iii) the correlation between local APIs and their corresponding regional and national levels is dynamic; (iv) comparing with the DCC-GARCH model estimation, the transformed model does not change the feature of the dynamic correlations very much.

  14. Social contagions on time-varying community networks.

    PubMed

    Liu, Mian-Xin; Wang, Wei; Liu, Ying; Tang, Ming; Cai, Shi-Min; Zhang, Hai-Feng

    2017-05-01

    Time-varying community structures exist widely in real-world networks. However, previous studies on the dynamics of spreading seldom took this characteristic into account, especially those on social contagions. To study the effects of time-varying community structures on social contagions, we propose a non-Markovian social contagion model on time-varying community networks based on the activity-driven network model. A mean-field theory is developed to analyze the proposed model. Through theoretical analyses and numerical simulations, two hierarchical features of the behavior adoption processes are found. That is, when community strength is relatively large, the behavior can easily spread in one of the communities, while in the other community the spreading only occurs at higher behavioral information transmission rates. Meanwhile, in spatial-temporal evolution processes, hierarchical orders are observed for the behavior adoption. Moreover, under different information transmission rates, three distinctive patterns are demonstrated in the change of the whole network's final adoption proportion along with the growing community strength. Within a suitable range of transmission rate, an optimal community strength can be found that can maximize the final adoption proportion. Finally, compared with the average activity potential, the promoting or inhibiting of social contagions is much more influenced by the number of edges generated by active nodes.

  15. Social contagions on time-varying community networks

    NASA Astrophysics Data System (ADS)

    Liu, Mian-Xin; Wang, Wei; Liu, Ying; Tang, Ming; Cai, Shi-Min; Zhang, Hai-Feng

    2017-05-01

    Time-varying community structures exist widely in real-world networks. However, previous studies on the dynamics of spreading seldom took this characteristic into account, especially those on social contagions. To study the effects of time-varying community structures on social contagions, we propose a non-Markovian social contagion model on time-varying community networks based on the activity-driven network model. A mean-field theory is developed to analyze the proposed model. Through theoretical analyses and numerical simulations, two hierarchical features of the behavior adoption processes are found. That is, when community strength is relatively large, the behavior can easily spread in one of the communities, while in the other community the spreading only occurs at higher behavioral information transmission rates. Meanwhile, in spatial-temporal evolution processes, hierarchical orders are observed for the behavior adoption. Moreover, under different information transmission rates, three distinctive patterns are demonstrated in the change of the whole network's final adoption proportion along with the growing community strength. Within a suitable range of transmission rate, an optimal community strength can be found that can maximize the final adoption proportion. Finally, compared with the average activity potential, the promoting or inhibiting of social contagions is much more influenced by the number of edges generated by active nodes.

  16. Default contagion risks in Russian interbank market

    NASA Astrophysics Data System (ADS)

    Leonidov, A. V.; Rumyantsev, E. L.

    2016-06-01

    Systemic risks of default contagion in the Russian interbank market are investigated. The analysis is based on considering the bow-tie structure of the weighted oriented graph describing the structure of the interbank loans. A probabilistic model of interbank contagion explicitly taking into account the empirical bow-tie structure reflecting functionality of the corresponding nodes (borrowers, lenders, borrowers and lenders simultaneously), degree distributions and disassortativity of the interbank network under consideration based on empirical data is developed. The characteristics of contagion-related systemic risk calculated with this model are shown to be in agreement with those of explicit stress tests.

  17. Evidence of complex contagion of information in social media: An experiment using Twitter bots

    PubMed Central

    2017-01-01

    It has recently become possible to study the dynamics of information diffusion in techno-social systems at scale, due to the emergence of online platforms, such as Twitter, with millions of users. One question that systematically recurs is whether information spreads according to simple or complex dynamics: does each exposure to a piece of information have an independent probability of a user adopting it (simple contagion), or does this probability depend instead on the number of sources of exposure, increasing above some threshold (complex contagion)? Most studies to date are observational and, therefore, unable to disentangle the effects of confounding factors such as social reinforcement, homophily, limited attention, or network community structure. Here we describe a novel controlled experiment that we performed on Twitter using ‘social bots’ deployed to carry out coordinated attempts at spreading information. We propose two Bayesian statistical models describing simple and complex contagion dynamics, and test the competing hypotheses. We provide experimental evidence that the complex contagion model describes the observed information diffusion behavior more accurately than simple contagion. Future applications of our results include more effective defenses against malicious propaganda campaigns on social media, improved marketing and advertisement strategies, and design of effective network intervention techniques. PMID:28937984

  18. Explosive Contagion in Networks

    PubMed Central

    Gómez-Gardeñes, J.; Lotero, L.; Taraskin, S. N.; Pérez-Reche, F. J.

    2016-01-01

    The spread of social phenomena such as behaviors, ideas or products is an ubiquitous but remarkably complex phenomenon. A successful avenue to study the spread of social phenomena relies on epidemic models by establishing analogies between the transmission of social phenomena and infectious diseases. Such models typically assume simple social interactions restricted to pairs of individuals; effects of the context are often neglected. Here we show that local synergistic effects associated with acquaintances of pairs of individuals can have striking consequences on the spread of social phenomena at large scales. The most interesting predictions are found for a scenario in which the contagion ability of a spreader decreases with the number of ignorant individuals surrounding the target ignorant. This mechanism mimics ubiquitous situations in which the willingness of individuals to adopt a new product depends not only on the intrinsic value of the product but also on whether his acquaintances will adopt this product or not. In these situations, we show that the typically smooth (second order) transitions towards large social contagion become explosive (first order). The proposed synergistic mechanisms therefore explain why ideas, rumours or products can suddenly and sometimes unexpectedly catch on. PMID:26819191

  19. Explosive Contagion in Networks

    NASA Astrophysics Data System (ADS)

    Gómez-Gardeñes, J.; Lotero, L.; Taraskin, S. N.; Pérez-Reche, F. J.

    2016-01-01

    The spread of social phenomena such as behaviors, ideas or products is an ubiquitous but remarkably complex phenomenon. A successful avenue to study the spread of social phenomena relies on epidemic models by establishing analogies between the transmission of social phenomena and infectious diseases. Such models typically assume simple social interactions restricted to pairs of individuals; effects of the context are often neglected. Here we show that local synergistic effects associated with acquaintances of pairs of individuals can have striking consequences on the spread of social phenomena at large scales. The most interesting predictions are found for a scenario in which the contagion ability of a spreader decreases with the number of ignorant individuals surrounding the target ignorant. This mechanism mimics ubiquitous situations in which the willingness of individuals to adopt a new product depends not only on the intrinsic value of the product but also on whether his acquaintances will adopt this product or not. In these situations, we show that the typically smooth (second order) transitions towards large social contagion become explosive (first order). The proposed synergistic mechanisms therefore explain why ideas, rumours or products can suddenly and sometimes unexpectedly catch on.

  20. Explosive Contagion in Networks.

    PubMed

    Gómez-Gardeñes, J; Lotero, L; Taraskin, S N; Pérez-Reche, F J

    2016-01-28

    The spread of social phenomena such as behaviors, ideas or products is an ubiquitous but remarkably complex phenomenon. A successful avenue to study the spread of social phenomena relies on epidemic models by establishing analogies between the transmission of social phenomena and infectious diseases. Such models typically assume simple social interactions restricted to pairs of individuals; effects of the context are often neglected. Here we show that local synergistic effects associated with acquaintances of pairs of individuals can have striking consequences on the spread of social phenomena at large scales. The most interesting predictions are found for a scenario in which the contagion ability of a spreader decreases with the number of ignorant individuals surrounding the target ignorant. This mechanism mimics ubiquitous situations in which the willingness of individuals to adopt a new product depends not only on the intrinsic value of the product but also on whether his acquaintances will adopt this product or not. In these situations, we show that the typically smooth (second order) transitions towards large social contagion become explosive (first order). The proposed synergistic mechanisms therefore explain why ideas, rumours or products can suddenly and sometimes unexpectedly catch on.

  1. Elevated emotional contagion in a mouse model of Alzheimer’s disease is associated with increased synchronization in the insula and amygdala

    PubMed Central

    Choi, Jiye; Jeong, Yong

    2017-01-01

    Emotional contagion, a primitive form of empathy, is heightened in patients with Alzheimer’s disease (AD); however, the mechanism underlying this attribute has not been thoroughly elucidated. In this study, observational fear conditioning was performed to measure emotional contagion levels in a mouse model of AD. Simultaneous recording of local field potentials in the bilateral anterior insula, basolateral amygdala, anterior cingulate cortex, and retrosplenial cortex was also conducted to investigate related brain network changes. Consistent with the results obtained with AD patients, 11-month-old AD model mice exhibited significantly higher freezing levels in observational fear conditioning, indicating elevated emotional contagion compared to age-matched wild-type mice. Furthermore, the left anterior insula and right basolateral amygdala of 11-months-old AD model mice indicated sustained increases in synchronization when they observed the suffering of conspecifics. These changes did not appear in other age groups or wild-type controls. Additionally, the amyloid plaque burden within the anterior insula was significantly correlated with the freezing levels in observational fear conditioning. Taken together, this study reveals increased and sustained network synchrony between the anterior insula and basolateral amygdala, which comprise a salience network in humans, as a potential mechanism for elevated emotional contagion in a mouse model of AD. PMID:28387348

  2. Yawn Contagion and Empathy in Homo sapiens

    PubMed Central

    Norscia, Ivan; Palagi, Elisabetta

    2011-01-01

    The ability to share others' emotions, or empathy, is crucial for complex social interactions. Clinical, psychological, and neurobiological clues suggest a link between yawn contagion and empathy in humans (Homo sapiens). However, no behavioral evidence has been provided so far. We tested the effect of different variables (e.g., country of origin, sex, yawn characteristics) on yawn contagion by running mixed models applied to observational data collected over 1 year on adult (>16 years old) human subjects. Only social bonding predicted the occurrence, frequency, and latency of yawn contagion. As with other measures of empathy, the rate of contagion was greatest in response to kin, then friends, then acquaintances, and lastly strangers. Related individuals (r≥0.25) showed the greatest contagion, in terms of both occurrence of yawning and frequency of yawns. Strangers and acquaintances showed a longer delay in the yawn response (latency) compared to friends and kin. This outcome suggests that the neuronal activation magnitude related to yawn contagion can differ as a function of subject familiarity. In conclusion, our results demonstrate that yawn contagion is primarily driven by the emotional closeness between individuals and not by other variables, such as gender and nationality. PMID:22163307

  3. Yawn contagion and empathy in Homo sapiens.

    PubMed

    Norscia, Ivan; Palagi, Elisabetta

    2011-01-01

    The ability to share others' emotions, or empathy, is crucial for complex social interactions. Clinical, psychological, and neurobiological clues suggest a link between yawn contagion and empathy in humans (Homo sapiens). However, no behavioral evidence has been provided so far. We tested the effect of different variables (e.g., country of origin, sex, yawn characteristics) on yawn contagion by running mixed models applied to observational data collected over 1 year on adult (>16 years old) human subjects. Only social bonding predicted the occurrence, frequency, and latency of yawn contagion. As with other measures of empathy, the rate of contagion was greatest in response to kin, then friends, then acquaintances, and lastly strangers. Related individuals (r≥0.25) showed the greatest contagion, in terms of both occurrence of yawning and frequency of yawns. Strangers and acquaintances showed a longer delay in the yawn response (latency) compared to friends and kin. This outcome suggests that the neuronal activation magnitude related to yawn contagion can differ as a function of subject familiarity. In conclusion, our results demonstrate that yawn contagion is primarily driven by the emotional closeness between individuals and not by other variables, such as gender and nationality.

  4. Mixed-order phase transition in a two-step contagion model with a single infectious seed

    NASA Astrophysics Data System (ADS)

    Choi, Wonjun; Lee, Deokjae; Kahng, B.

    2017-02-01

    Percolation is known as one of the most robust continuous transitions, because its occupation rule is intrinsically local. As one of the ways to break the robustness, occupation is allowed to more than one species of particles and they occupy cooperatively. This generalized percolation model undergoes a discontinuous transition. Here we investigate an epidemic model with two contagion steps and characterize its phase transition analytically and numerically. We find that even though the order parameter jumps at a transition point rc, then increases continuously, it does not exhibit any critical behavior: the fluctuations of the order parameter do not diverge at rc. However, critical behavior appears in mean outbreak size, which diverges at the transition point in a manner that the ordinary percolation shows. Such a type of phase transition is regarded as a mixed-order phase transition. We also obtain scaling relations of cascade outbreak statistics when the order parameter jumps at rc.

  5. Peer Contagion in Interventions for Children and Adolescents: Moving Towards an Understanding of the Ecology and Dynamics of Change.

    ERIC Educational Resources Information Center

    Dishion, Thomas J.; Dodge, Kenneth A.

    2005-01-01

    The influence of deviant peers on youth behavior is of growing concern, both in naturally occurring peer interactions and in interventions that might inadvertently exacerbate deviant development. The focus of this special issue is on understanding the moderating and mediating variables that account for peer contagion effects in interventions for…

  6. Measuring Emotional Contagion in Social Media.

    PubMed

    Ferrara, Emilio; Yang, Zeyao

    2015-01-01

    Social media are used as main discussion channels by millions of individuals every day. The content individuals produce in daily social-media-based micro-communications, and the emotions therein expressed, may impact the emotional states of others. A recent experiment performed on Facebook hypothesized that emotions spread online, even in absence of non-verbal cues typical of in-person interactions, and that individuals are more likely to adopt positive or negative emotions if these are over-expressed in their social network. Experiments of this type, however, raise ethical concerns, as they require massive-scale content manipulation with unknown consequences for the individuals therein involved. Here, we study the dynamics of emotional contagion using a random sample of Twitter users, whose activity (and the stimuli they were exposed to) was observed during a week of September 2014. Rather than manipulating content, we devise a null model that discounts some confounding factors (including the effect of emotional contagion). We measure the emotional valence of content the users are exposed to before posting their own tweets. We determine that on average a negative post follows an over-exposure to 4.34% more negative content than baseline, while positive posts occur after an average over-exposure to 4.50% more positive contents. We highlight the presence of a linear relationship between the average emotional valence of the stimuli users are exposed to, and that of the responses they produce. We also identify two different classes of individuals: highly and scarcely susceptible to emotional contagion. Highly susceptible users are significantly less inclined to adopt negative emotions than the scarcely susceptible ones, but equally likely to adopt positive emotions. In general, the likelihood of adopting positive emotions is much greater than that of negative emotions.

  7. Measuring Emotional Contagion in Social Media

    PubMed Central

    2015-01-01

    Social media are used as main discussion channels by millions of individuals every day. The content individuals produce in daily social-media-based micro-communications, and the emotions therein expressed, may impact the emotional states of others. A recent experiment performed on Facebook hypothesized that emotions spread online, even in absence of non-verbal cues typical of in-person interactions, and that individuals are more likely to adopt positive or negative emotions if these are over-expressed in their social network. Experiments of this type, however, raise ethical concerns, as they require massive-scale content manipulation with unknown consequences for the individuals therein involved. Here, we study the dynamics of emotional contagion using a random sample of Twitter users, whose activity (and the stimuli they were exposed to) was observed during a week of September 2014. Rather than manipulating content, we devise a null model that discounts some confounding factors (including the effect of emotional contagion). We measure the emotional valence of content the users are exposed to before posting their own tweets. We determine that on average a negative post follows an over-exposure to 4.34% more negative content than baseline, while positive posts occur after an average over-exposure to 4.50% more positive contents. We highlight the presence of a linear relationship between the average emotional valence of the stimuli users are exposed to, and that of the responses they produce. We also identify two different classes of individuals: highly and scarcely susceptible to emotional contagion. Highly susceptible users are significantly less inclined to adopt negative emotions than the scarcely susceptible ones, but equally likely to adopt positive emotions. In general, the likelihood of adopting positive emotions is much greater than that of negative emotions. PMID:26544688

  8. Insolvency and contagion in the Brazilian interbank market

    NASA Astrophysics Data System (ADS)

    Souza, Sergio R. S.; Tabak, Benjamin M.; Silva, Thiago C.; Guerra, Solange M.

    2015-08-01

    This paper proposes a new way to model and analyze contagion in interbank networks. We use a unique dataset from the Brazilian financial system and include all active financial intermediaries. We show that the contagion chain has a short propagation path. We find that first-round contagion is generated only by banks and that medium-sized banks can generate contagion, which implies that size is not the sole determinant of importance within networks. Most vulnerable financial institutions are not banks. Finally, we compute a lower bound for the financial system expected losses in a 1-year horizon. The results contribute to the development of a financial stability-monitoring toolkit.

  9. Controlling contagion processes in activity driven networks.

    PubMed

    Liu, Suyu; Perra, Nicola; Karsai, Márton; Vespignani, Alessandro

    2014-03-21

    The vast majority of strategies aimed at controlling contagion processes on networks consider the connectivity pattern of the system either quenched or annealed. However, in the real world, many networks are highly dynamical and evolve, in time, concurrently with the contagion process. Here, we derive an analytical framework for the study of control strategies specifically devised for a class of time-varying networks, namely activity-driven networks. We develop a block variable mean-field approach that allows the derivation of the equations describing the coevolution of the contagion process and the network dynamic. We derive the critical immunization threshold and assess the effectiveness of three different control strategies. Finally, we validate the theoretical picture by simulating numerically the spreading process and control strategies in both synthetic networks and a large-scale, real-world, mobile telephone call data set.

  10. Analysis of complex contagions in random multiplex networks

    NASA Astrophysics Data System (ADS)

    Yaǧan, Osman; Gligor, Virgil

    2012-09-01

    We study the diffusion of influence in random multiplex networks where links can be of r different types, and, for a given content (e.g., rumor, product, or political view), each link type is associated with a content-dependent parameter ci in [0,∞] that measures the relative bias type i links have in spreading this content. In this setting, we propose a linear threshold model of contagion where nodes switch state if their “perceived” proportion of active neighbors exceeds a threshold τ. Namely a node connected to mi active neighbors and ki-mi inactive neighbors via type i links will turn active if ∑cimi/∑ciki exceeds its threshold τ. Under this model, we obtain the condition, probability and expected size of global spreading events. Our results extend the existing work on complex contagions in several directions by (i) providing solutions for coupled random networks whose vertices are neither identical nor disjoint, (ii) highlighting the effect of content on the dynamics of complex contagions, and (iii) showing that content-dependent propagation over a multiplex network leads to a subtle relation between the giant vulnerable component of the graph and the global cascade condition that is not seen in the existing models in the literature.

  11. Eye movements may cause motor contagion effects.

    PubMed

    Constable, Merryn D; de Grosbois, John; Lung, Tiffany; Tremblay, Luc; Pratt, Jay; Welsh, Timothy N

    2016-10-26

    When a person executes a movement, the movement is more errorful while observing another person's actions that are incongruent rather than congruent with the executed action. This effect is known as "motor contagion". Accounts of this effect are often grounded in simulation mechanisms: increased movement error emerges because the motor codes associated with observed actions compete with motor codes of the goal action. It is also possible, however, that the increased movement error is linked to eye movements that are executed simultaneously with the hand movement because oculomotor and manual-motor systems are highly interconnected. In the present study, participants performed a motor contagion task in which they executed horizontal arm movements while observing a model making either vertical (incongruent) or horizontal (congruent) movements under three conditions: no instruction, maintain central fixation, or track the model's hand with the eyes. A significant motor contagion-like effect was only found in the 'track' condition. Thus, 'motor contagion' in the present task may be an artifact of simultaneously executed incongruent eye movements. These data are discussed in the context of stimulation and associative learning theories, and raise eye movements as a critical methodological consideration for future work on motor contagion.

  12. Quantitative measurement of the contagion effect between US and Chinese stock market during the financial crisis

    NASA Astrophysics Data System (ADS)

    Chen, Wang; Wei, Yu; Zhang, Bangzheng; Yu, Jiang

    2014-09-01

    In this paper, we study the quantitative measurement of contagion effect between US and Chinese stock market during the financial crisis by combining multifractal volatility (MFV) with the copula method. At first, we employ MFV to filter volatility of the two markets due to the existence of heteroskedasticity. Then we use an improved time-varying Clayton copula to estimate the dynamic lower tail dependence (lower Kendall's τ). After determining crisis and non-crisis periods by Markov regime switching model, we find that the statistical characteristics of lower Kendall's τ during crisis and non-crisis periods are obviously different. Time-varying lower Kendall's τ of the crisis period is about 1.87 times that of in non-crisis period on average, indicating that the contagion effect increased about 87% during the crisis period. It is very drastic that the fluctuations of lower tail dependence during crisis period, so the static measurement of contagion effect may not provide effective suggestions for investors. Thus, we propose a dynamic method to measure the strength of contagion effect.

  13. The cultural contagion of conflict

    PubMed Central

    Gelfand, Michele; Shteynberg, Garriy; Lee, Tiane; Lun, Janetta; Lyons, Sarah; Bell, Chris; Chiao, Joan Y.; Bruss, C. Bayan; Al Dabbagh, May; Aycan, Zeynep; Abdel-Latif, Abdel-Hamid; Dagher, Munqith; Khashan, Hilal; Soomro, Nazar

    2012-01-01

    Anecdotal evidence abounds that conflicts between two individuals can spread across networks to involve a multitude of others. We advance a cultural transmission model of intergroup conflict where conflict contagion is seen as a consequence of universal human traits (ingroup preference, outgroup hostility; i.e. parochial altruism) which give their strongest expression in particular cultural contexts. Qualitative interviews conducted in the Middle East, USA and Canada suggest that parochial altruism processes vary across cultural groups and are most likely to occur in collectivistic cultural contexts that have high ingroup loyalty. Implications for future neuroscience and computational research needed to understand the emergence of intergroup conflict are discussed. PMID:22271785

  14. Topological data analysis of contagion maps for examining spreading processes on networks

    PubMed Central

    Taylor, Dane; Klimm, Florian; Harrington, Heather A.; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A.; Mucha, Peter J.

    2015-01-01

    Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth’s surface; however, in modern contagions long-range edges—for example, due to airline transportation or communication media—allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct “contagion maps” that use multiple contagions on a network to map the nodes as a point cloud. By analyzing the topology, geometry, and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modeling, forecast, and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks. PMID:26194875

  15. Topological data analysis of contagion maps for examining spreading processes on networks

    NASA Astrophysics Data System (ADS)

    Taylor, Dane; Klimm, Florian; Harrington, Heather A.; Kramár, Miroslav; Mischaikow, Konstantin; Porter, Mason A.; Mucha, Peter J.

    2015-07-01

    Social and biological contagions are influenced by the spatial embeddedness of networks. Historically, many epidemics spread as a wave across part of the Earth's surface; however, in modern contagions long-range edges--for example, due to airline transportation or communication media--allow clusters of a contagion to appear in distant locations. Here we study the spread of contagions on networks through a methodology grounded in topological data analysis and nonlinear dimension reduction. We construct `contagion maps' that use multiple contagions on a network to map the nodes as a point cloud. By analysing the topology, geometry and dimensionality of manifold structure in such point clouds, we reveal insights to aid in the modelling, forecast and control of spreading processes. Our approach highlights contagion maps also as a viable tool for inferring low-dimensional structure in networks.

  16. Exact solutions for social and biological contagion models on mixed directed and undirected, degree-correlated random networks.

    PubMed

    Payne, Joshua L; Harris, Kameron Decker; Dodds, Peter Sheridan

    2011-07-01

    We derive analytic expressions for the possibility, probability, and expected size of global spreading events starting from a single infected seed for a broad collection of contagion processes acting on random networks with both directed and undirected edges and arbitrary degree-degree correlations. Our work extends previous theoretical developments for the undirected case, and we provide numerical support for our findings by investigating an example class of networks for which we are able to obtain closed-form expressions.

  17. A Strategic Interaction Model of Punishment Favoring Contagion of Honest Behavior

    PubMed Central

    Cremene, Marcel; Dumitrescu, D.; Cremene, Ligia

    2014-01-01

    The punishment effect on social behavior is analyzed within the strategic interaction framework of Cellular Automata and computational Evolutionary Game Theory. A new game, called Social Honesty (SH), is proposed. The SH game is analyzed in spatial configurations. Probabilistic punishment is used as a dishonesty deterrence mechanism. In order to capture the intrinsic uncertainty of social environments, payoffs are described as random variables. New dynamics, with a new relation between punishment probability and punishment severity, are revealed. Punishment probability proves to be more important than punishment severity in guiding convergence towards honesty as predominant behavior. This result is confirmed by empirical evidence and reported experiments. Critical values and transition intervals for punishment probability and severity are identified and analyzed. Clusters of honest or dishonest players emerge spontaneously from the very first rounds of interaction and are determinant for the future dynamics and outcomes. PMID:24489917

  18. A strategic interaction model of punishment favoring contagion of honest behavior.

    PubMed

    Cremene, Marcel; Dumitrescu, D; Cremene, Ligia

    2014-01-01

    The punishment effect on social behavior is analyzed within the strategic interaction framework of Cellular Automata and computational Evolutionary Game Theory. A new game, called Social Honesty (SH), is proposed. The SH game is analyzed in spatial configurations. Probabilistic punishment is used as a dishonesty deterrence mechanism. In order to capture the intrinsic uncertainty of social environments, payoffs are described as random variables. New dynamics, with a new relation between punishment probability and punishment severity, are revealed. Punishment probability proves to be more important than punishment severity in guiding convergence towards honesty as predominant behavior. This result is confirmed by empirical evidence and reported experiments. Critical values and transition intervals for punishment probability and severity are identified and analyzed. Clusters of honest or dishonest players emerge spontaneously from the very first rounds of interaction and are determinant for the future dynamics and outcomes.

  19. Complex Network for a Crisis Contagion on AN Interbank System

    NASA Astrophysics Data System (ADS)

    Tirado, Mariano

    2012-09-01

    The main focus of this research is the contagion of a financial crisis on an interbank debt network. In order to simulate the crisis propagation a weighted community complex network based on growth strategy has been created. The contagion is described by a new way of disease propagation perspective based on the concept of a financial virus. The model reproduces the existence of TBTF banks and shows the impact that an initial TBTF bank crash produces in the interbank network depending on the magnitude of the initial crash and on the resistance that the network offers against the contagion propagation.

  20. Modelling dwarf mistletoe at three scales: life history, ballistics and contagion

    Treesearch

    Donald C. E. Robinson; Brian W. Geils

    2006-01-01

    The epidemiology of dwarf mistletoe (Arceuthobium) is simulated for the reproduction, dispersal, and spatial patterns of these plant pathogens on conifer trees. A conceptual model for mistletoe spread and intensification is coded as sets of related subprograms that link to either of two individual-tree growth models (FVS and TASS) used by managers to develop...

  1. Cultural interpretations of contagion.

    PubMed

    Caprara, A

    1998-12-01

    Anthropological research in recent years has examined how single diseases such as Aids, tuberculosis, measles, malaria and leprosy are conceptualized by laypersons in non-Western societies. But how is disease transmission itself interpreted in other cultures? Data from ethnographical studies in Côte d'Ivoire and the Afro-Brazilian culture in Bahia, Brazil show that the interpretations of contagion and preventive practices cut across society involving five main relationships: empirical and analogical thinking, symbolic factors and social organization, the concept of person and body elements, natural and supernatural powers and individual and contextual factors. There is not a general theory, such as Pasteur's theory of germs. Instead, contagion presents itself as a transversal, multidimensional concept crossing and interconnecting society and culture. Public health programmes aimed at controlling infectious diseases need first to understand how contagion is conceptualized by laypersons, the extent to which diseases are considered infectious and the relation between perceptions and preventive practices. This would help in implementing infectious disease control programmes within local contexts based on meaningful community participation.

  2. Contagion in Mass Killings and School Shootings.

    PubMed

    Towers, Sherry; Gomez-Lievano, Andres; Khan, Maryam; Mubayi, Anuj; Castillo-Chavez, Carlos

    2015-01-01

    Several past studies have found that media reports of suicides and homicides appear to subsequently increase the incidence of similar events in the community, apparently due to the coverage planting the seeds of ideation in at-risk individuals to commit similar acts. Here we explore whether or not contagion is evident in more high-profile incidents, such as school shootings and mass killings (incidents with four or more people killed). We fit a contagion model to recent data sets related to such incidents in the US, with terms that take into account the fact that a school shooting or mass murder may temporarily increase the probability of a similar event in the immediate future, by assuming an exponential decay in contagiousness after an event. We find significant evidence that mass killings involving firearms are incented by similar events in the immediate past. On average, this temporary increase in probability lasts 13 days, and each incident incites at least 0.30 new incidents (p = 0.0015). We also find significant evidence of contagion in school shootings, for which an incident is contagious for an average of 13 days, and incites an average of at least 0.22 new incidents (p = 0.0001). All p-values are assessed based on a likelihood ratio test comparing the likelihood of a contagion model to that of a null model with no contagion. On average, mass killings involving firearms occur approximately every two weeks in the US, while school shootings occur on average monthly. We find that state prevalence of firearm ownership is significantly associated with the state incidence of mass killings with firearms, school shootings, and mass shootings.

  3. Contagion in Mass Killings and School Shootings

    PubMed Central

    Towers, Sherry; Gomez-Lievano, Andres; Khan, Maryam; Mubayi, Anuj; Castillo-Chavez, Carlos

    2015-01-01

    Background Several past studies have found that media reports of suicides and homicides appear to subsequently increase the incidence of similar events in the community, apparently due to the coverage planting the seeds of ideation in at-risk individuals to commit similar acts. Methods Here we explore whether or not contagion is evident in more high-profile incidents, such as school shootings and mass killings (incidents with four or more people killed). We fit a contagion model to recent data sets related to such incidents in the US, with terms that take into account the fact that a school shooting or mass murder may temporarily increase the probability of a similar event in the immediate future, by assuming an exponential decay in contagiousness after an event. Conclusions We find significant evidence that mass killings involving firearms are incented by similar events in the immediate past. On average, this temporary increase in probability lasts 13 days, and each incident incites at least 0.30 new incidents (p = 0.0015). We also find significant evidence of contagion in school shootings, for which an incident is contagious for an average of 13 days, and incites an average of at least 0.22 new incidents (p = 0.0001). All p-values are assessed based on a likelihood ratio test comparing the likelihood of a contagion model to that of a null model with no contagion. On average, mass killings involving firearms occur approximately every two weeks in the US, while school shootings occur on average monthly. We find that state prevalence of firearm ownership is significantly associated with the state incidence of mass killings with firearms, school shootings, and mass shootings. PMID:26135941

  4. Coupling ecological and social network models to assess "transmission" and "contagion" of an aquatic invasive species.

    PubMed

    Haak, Danielle M; Fath, Brian D; Forbes, Valery E; Martin, Dustin R; Pope, Kevin L

    2017-04-01

    Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensis alters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems.

  5. The Simple Rules of Social Contagion

    PubMed Central

    Hodas, Nathan O.; Lerman, Kristina

    2014-01-01

    It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior. PMID:24614301

  6. The simple rules of social contagion.

    PubMed

    Hodas, Nathan O; Lerman, Kristina

    2014-03-11

    It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior.

  7. Complex social contagion makes networks more vulnerable to disease outbreaks

    PubMed Central

    Campbell, Ellsworth; Salathé, Marcel

    2013-01-01

    Social network analysis is now widely used to investigate the dynamics of infectious disease spread. Vaccination dramatically disrupts disease transmission on a contact network, and indeed, high vaccination rates can potentially halt disease transmission altogether. Here, we build on mounting evidence that health behaviors - such as vaccination, and refusal thereof - can spread across social networks through a process of complex contagion that requires social reinforcement. Using network simulations that model health behavior and infectious disease spread, we find that under otherwise identical conditions, the process by which the health behavior spreads has a very strong effect on disease outbreak dynamics. This dynamic variability results from differences in the topology within susceptible communities that arise during the health behavior spreading process, which in turn depends on the topology of the overall social network. Our findings point to the importance of health behavior spread in predicting and controlling disease outbreaks. PMID:23712758

  8. The Inverse Contagion Problem (ICP) vs.. Predicting site contagion in real time, when network links are not observable

    NASA Astrophysics Data System (ADS)

    Mushkin, I.; Solomon, S.

    2017-10-01

    We study the inverse contagion problem (ICP). As opposed to the direct contagion problem, in which the network structure is known and the question is when each node will be contaminated, in the inverse problem the links of the network are unknown but a sequence of contagion histories (the times when each node was contaminated) is observed. We consider two versions of the ICP: The strong problem (SICP), which is the reconstruction of the network and has been studied before, and the weak problem (WICP), which requires ;only; the prediction (at each time step) of the nodes that will be contaminated at the next time step (this is often the real life situation in which a contagion is observed and predictions are made in real time). Moreover, our focus is on analyzing the increasing accuracy of the solution, as a function of the number of contagion histories already observed. For simplicity, we discuss the simplest (deterministic and synchronous) contagion dynamics and the simplest solution algorithm, which we have applied to different network types. The main result of this paper is that the complex problem of the convergence of the ICP for a network can be reduced to an individual property of pairs of nodes: the ;false link difficulty;. By definition, given a pair of unlinked nodes i and j, the difficulty of the false link (i,j) is the probability that in a random contagion history, the nodes i and j are not contaminated at the same time step (or at consecutive time steps). In other words, the ;false link difficulty; of a non-existing network link is the probability that the observations during a random contagion history would not rule out that link. This probability is relatively straightforward to calculate, and in most instances relies only on the relative positions of the two nodes (i,j) and not on the entire network structure. We have observed the distribution of false link difficulty for various network types, estimated it theoretically and confronted it

  9. Financial market volatility and contagion effect: A copula-multifractal volatility approach

    NASA Astrophysics Data System (ADS)

    Chen, Wang; Wei, Yu; Lang, Qiaoqi; Lin, Yu; Liu, Maojuan

    2014-03-01

    In this paper, we propose a new approach based on the multifractal volatility method (MFV) to study the contagion effect between the U.S. and Chinese stock markets. From recent studies, which reveal that multifractal characteristics exist in both developed and emerging financial markets, according to the econophysics literature we could draw conclusions as follows: Firstly, we estimate volatility using the multifractal volatility method, and find out that the MFV method performs best among other volatility models, such as GARCH-type and realized volatility models. Secondly, we analyze the tail dependence structure between the U.S. and Chinese stock market. The estimated static copula results for the entire period show that the SJC copula performs best, indicating asymmetric characteristics of the tail dependence structure. The estimated dynamic copula results show that the time-varying t copula achieves the best performance, which means the symmetry dynamic t copula is also a good choice, for it is easy to estimate and is able to depict both the upper and lower tail dependence structure. Finally, with the results of the previous two steps, we analyze the contagion effect between the U.S. and Chinese stock markets during the subprime mortgage crisis. The empirical results show that the subprime mortgage crisis started in the U.S. and that its stock market has had an obvious contagion effect on the Chinese stock market. Our empirical results should/might be useful for investors allocating their portfolios.

  10. A method of emotion contagion for crowd evacuation

    NASA Astrophysics Data System (ADS)

    Cao, Mengxiao; Zhang, Guijuan; Wang, Mengsi; Lu, Dianjie; Liu, Hong

    2017-10-01

    The current evacuation model does not consider the impact of emotion and personality on crowd evacuation. Thus, there is large difference between evacuation results and the real-life behavior of the crowd. In order to generate more realistic crowd evacuation results, we present a method of emotion contagion for crowd evacuation. First, we combine OCEAN (Openness, Extroversion, Agreeableness, Neuroticism, Conscientiousness) model and SIS (Susceptible Infected Susceptible) model to construct the P-SIS (Personalized SIS) emotional contagion model. The P-SIS model shows the diversity of individuals in crowd effectively. Second, we couple the P-SIS model with the social force model to simulate emotional contagion on crowd evacuation. Finally, the photo-realistic rendering method is employed to obtain the animation of crowd evacuation. Experimental results show that our method can simulate crowd evacuation realistically and has guiding significance for crowd evacuation in the emergency circumstances.

  11. She more than he: gender bias supports the empathic nature of yawn contagion in Homo sapiens

    PubMed Central

    Norscia, Ivan; Demuru, Elisa; Palagi, Elisabetta

    2016-01-01

    Psychological, clinical and neurobiological findings endorse that empathic abilities are more developed in women than in men. Because there is growing evidence that yawn contagion is an empathy-based phenomenon, we expect that the female bias in the empathic abilities reflects on a gender skew in the responsiveness to others’ yawns. We verified this assumption by applying a linear model on a dataset gathered during a 5 year period of naturalistic observations on humans. Gender, age and social bond were included in the analysis as fixed factors. The social bond and the receiver’s gender remained in the best model. The rates of contagion were significantly lower between acquaintances than between friends and family members, and significantly higher in women than in men. These results not only confirm that yawn contagion is sensitive to social closeness, but also that the phenomenon is affected by the same gender bias affecting empathy. The sex skew, also found in other non-human species, fits with the female social roles which are likely to require higher empathic abilities (e.g. parental care, group cohesion maintenance, social mediation). The fact that female influence in social dynamics also relies on face-to-face emotional exchange raises concerns on the negative repercussions of having women’s facial expressions forcibly concealed. PMID:26998318

  12. Avalanche outbreaks emerging in cooperative contagions

    NASA Astrophysics Data System (ADS)

    Cai, Weiran; Chen, Li; Ghanbarnejad, Fakhteh; Grassberger, Peter

    2015-11-01

    The spreading of contagions can exhibit a percolation transition, which separates transitory prevalence from outbreaks that reach a finite fraction of the population. Such transitions are commonly believed to be continuous, but empirical studies have shown more violent spreading modes when the participating agents are not limited to one type. Striking examples include the co-epidemic of the Spanish flu and pneumonia that occurred in 1918 (refs , ), and, more recently, the concurrent prevalence of HIV/AIDS and a host of diseases. It remains unclear to what extent an outbreak in the presence of interacting pathogens differs from that due to an ordinary single-agent process. Here we study a mechanistic model for understanding contagion processes involving inter-agent cooperation. Our stochastic simulations reveal the possible emergence of a massive avalanche-like outbreak right at the threshold, which is manifested as a discontinuous phase transition. Such an abrupt change arises only if the underlying network topology supports a bottleneck for cascaded mutual infections. Surprisingly, all these discontinuous transitions are accompanied by non-trivial critical behaviours, presenting a rare case of hybrid transition. The findings may imply the origin of catastrophic occurrences in many realistic systems, from co-epidemics to financial contagions.

  13. Limited Imitation Contagion on Random Networks: Chaos, Universality, and Unpredictability

    NASA Astrophysics Data System (ADS)

    Dodds, Peter Sheridan; Harris, Kameron Decker; Danforth, Christopher M.

    2013-04-01

    We study a family of binary state, socially inspired contagion models which incorporate imitation limited by an aversion to complete conformity. We uncover rich behavior in our models whether operating with either probabilistic or deterministic individual response functions on both dynamic and fixed random networks. In particular, we find significant variation in the limiting behavior of a population’s infected fraction, ranging from steady state to chaotic. We show that period doubling arises as we increase the average node degree, and that the universality class of this well-known route to chaos depends on the interaction structure of random networks rather than the microscopic behavior of individual nodes. We find that increasing the fixedness of the system tends to stabilize the infected fraction, yet disjoint, multiple equilibria are possible depending solely on the choice of the initially infected node.

  14. In Bonobos Yawn Contagion Is Higher among Kin and Friends

    PubMed Central

    Demuru, Elisa; Palagi, Elisabetta

    2012-01-01

    In humans, the distribution of yawn contagion is shaped by social closeness with strongly bonded pairs showing higher levels of contagion than weakly bonded pairs. This ethological finding led the authors to hypothesize that the phenomenon of yawn contagion may be the result of certain empathic abilities, although in their most basal form. Here, for the first time, we show the capacity of bonobos (Pan paniscus) to respond to yawns of conspecifics. Bonobos spontaneously yawned more frequently during resting/relaxing compared to social tension periods. The results show that yawn contagion was context independent suggesting that the probability of yawning after observing others' yawns is not affected by the propensity to engage in spontaneous yawns. As it occurs in humans, in bonobos the yawing response mostly occurred within the first minute after the perception of the stimulus. Finally, via a Linear Mixed Model we tested the effect of different variables (e.g., sex, rank, relationship quality) on yawn contagion, which increased when subjects were strongly bonded and when the triggering subject was a female. The importance of social bonding in shaping yawn contagion in bonobos, as it occurs in humans, is consistent with the hypothesis that empathy may play a role in the modulation of this phenomenon in both species. The higher frequency of yawn contagion in presence of a female as a triggering subject supports the hypothesis that adult females not only represent the relational and decisional nucleus of the bonobo society, but also that they play a key role in affecting the emotional states of others. PMID:23166729

  15. In bonobos yawn contagion is higher among kin and friends.

    PubMed

    Demuru, Elisa; Palagi, Elisabetta

    2012-01-01

    In humans, the distribution of yawn contagion is shaped by social closeness with strongly bonded pairs showing higher levels of contagion than weakly bonded pairs. This ethological finding led the authors to hypothesize that the phenomenon of yawn contagion may be the result of certain empathic abilities, although in their most basal form. Here, for the first time, we show the capacity of bonobos (Pan paniscus) to respond to yawns of conspecifics. Bonobos spontaneously yawned more frequently during resting/relaxing compared to social tension periods. The results show that yawn contagion was context independent suggesting that the probability of yawning after observing others' yawns is not affected by the propensity to engage in spontaneous yawns. As it occurs in humans, in bonobos the yawing response mostly occurred within the first minute after the perception of the stimulus. Finally, via a Linear Mixed Model we tested the effect of different variables (e.g., sex, rank, relationship quality) on yawn contagion, which increased when subjects were strongly bonded and when the triggering subject was a female. The importance of social bonding in shaping yawn contagion in bonobos, as it occurs in humans, is consistent with the hypothesis that empathy may play a role in the modulation of this phenomenon in both species. The higher frequency of yawn contagion in presence of a female as a triggering subject supports the hypothesis that adult females not only represent the relational and decisional nucleus of the bonobo society, but also that they play a key role in affecting the emotional states of others.

  16. Social contagion of risk perceptions in environmental management networks.

    PubMed

    Muter, Bret A; Gore, Meredith L; Riley, Shawn J

    2013-08-01

    An important requisite for improving risk communication practice related to contentious environmental issues is having a better theoretical understanding of how risk perceptions function in real-world social systems. Our study applied Scherer and Cho's social network contagion theory of risk perception (SNCTRP) to cormorant management (a contentious environmental management issue) in the Great Lakes Basin to: (1) assess contagion effects on cormorant-related risk perceptions and individual factors believed to influence those perceptions and (2) explore the extent of social contagion in a full network (consisting of interactions between and among experts and laypeople) and three "isolated" models separating different types of interactions from the full network (i.e., expert-to-expert, layperson-to-layperson, and expert-to-layperson). We conducted interviews and administered questionnaires with experts (e.g., natural resource professionals) and laypeople (e.g., recreational and commercial anglers, business owners, bird enthusiasts) engaged in cormorant management in northern Lake Huron (n = 115). Our findings generally support the SNCTRP; however, the scope and scale of social contagion varied considerably based on the variables (e.g., individual risk perception factors), actors (i.e., experts or laypeople), and interactions of interest. Contagion effects were identified more frequently, and were stronger, in the models containing interactions between experts and laypeople than in those models containing only interactions among experts or laypeople.

  17. Landscape patterns from mathematical morphology on maps with contagion

    Treesearch

    Kurt Riitters; Peter Vogt; Pierre Soille; Christine Estreguil

    2009-01-01

    The perceived realism of simulated maps with contagion (spatial autocorrelation) has led to their use for comparing landscape pattern metrics and as habitat maps for modeling organism movement across landscapes. The objective of this study was to conduct a neutral model analysis of pattern metrics defined by morphological spatial pattern analysis (MSPA) on maps with...

  18. Group Contagion: The Mailbox Melee

    ERIC Educational Resources Information Center

    Morse, William C.

    2010-01-01

    In a group situation, something goes wrong but no individual feels personal responsibility. This is called the "pie" phenomenon because everybody has a piece of the action, but all believe they are innocent. Each contributes to contagion and chaos but all say, "We didn't do nothing." In this article, the author, a pioneer in work with troubled…

  19. Group Contagion: The Mailbox Melee

    ERIC Educational Resources Information Center

    Morse, William C.

    2010-01-01

    In a group situation, something goes wrong but no individual feels personal responsibility. This is called the "pie" phenomenon because everybody has a piece of the action, but all believe they are innocent. Each contributes to contagion and chaos but all say, "We didn't do nothing." In this article, the author, a pioneer in work with troubled…

  20. Complex contagion process in spreading of online innovation

    PubMed Central

    Karsai, Márton; Iñiguez, Gerardo; Kaski, Kimmo; Kertész, János

    2014-01-01

    Diffusion of innovation can be interpreted as a social spreading phenomenon governed by the impact of media and social interactions. Although these mechanisms have been identified by quantitative theories, their role and relative importance are not entirely understood, as empirical verification has so far been hindered by the lack of appropriate data. Here we analyse a dataset recording the spreading dynamics of the world's largest Voice over Internet Protocol service to empirically support the assumptions behind models of social contagion. We show that the rate of spontaneous service adoption is constant, the probability of adoption via social influence is linearly proportional to the fraction of adopting neighbours, and the rate of service termination is time-invariant and independent of the behaviour of peers. By implementing the detected diffusion mechanisms into a dynamical agent-based model, we are able to emulate the adoption dynamics of the service in several countries worldwide. This approach enables us to make medium-term predictions of service adoption and disclose dependencies between the dynamics of innovation spreading and the socio-economic development of a country. PMID:25339685

  1. Complex contagion process in spreading of online innovation.

    PubMed

    Karsai, Márton; Iñiguez, Gerardo; Kaski, Kimmo; Kertész, János

    2014-12-06

    Diffusion of innovation can be interpreted as a social spreading phenomenon governed by the impact of media and social interactions. Although these mechanisms have been identified by quantitative theories, their role and relative importance are not entirely understood, as empirical verification has so far been hindered by the lack of appropriate data. Here we analyse a dataset recording the spreading dynamics of the world's largest Voice over Internet Protocol service to empirically support the assumptions behind models of social contagion. We show that the rate of spontaneous service adoption is constant, the probability of adoption via social influence is linearly proportional to the fraction of adopting neighbours, and the rate of service termination is time-invariant and independent of the behaviour of peers. By implementing the detected diffusion mechanisms into a dynamical agent-based model, we are able to emulate the adoption dynamics of the service in several countries worldwide. This approach enables us to make medium-term predictions of service adoption and disclose dependencies between the dynamics of innovation spreading and the socio-economic development of a country. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  2. Exploring the Relationships among Mirror Neurons, Theory of Mind, and Achievement Goals: Towards a Model of Achievement Goal Contagion in Educational Settings

    ERIC Educational Resources Information Center

    Eren, Altay

    2009-01-01

    This article aimed to examine the relationship between mirror neuron and theory of mind functions and to explore their possible roles in the emergence of an achievement goal contagion in educational settings such as classrooms. Based on the evidence from different lines of research such as neurobiology, neuropsychology, social psychology, and…

  3. Exploring the Relationships among Mirror Neurons, Theory of Mind, and Achievement Goals: Towards a Model of Achievement Goal Contagion in Educational Settings

    ERIC Educational Resources Information Center

    Eren, Altay

    2009-01-01

    This article aimed to examine the relationship between mirror neuron and theory of mind functions and to explore their possible roles in the emergence of an achievement goal contagion in educational settings such as classrooms. Based on the evidence from different lines of research such as neurobiology, neuropsychology, social psychology, and…

  4. Kinetics of Social Contagion.

    PubMed

    Ruan, Zhongyuan; Iñiguez, Gerardo; Karsai, Márton; Kertész, János

    2015-11-20

    Diffusion of information, behavioral patterns or innovations follows diverse pathways depending on a number of conditions, including the structure of the underlying social network, the sensitivity to peer pressure and the influence of media. Here we study analytically and by simulations a general model that incorporates threshold mechanism capturing sensitivity to peer pressure, the effect of "immune" nodes who never adopt, and a perpetual flow of external information. While any constant, nonzero rate of dynamically introduced spontaneous adopters leads to global spreading, the kinetics by which the asymptotic state is approached shows rich behavior. In particular, we find that, as a function of the immune node density, there is a transition from fast to slow spreading governed by entirely different mechanisms. This transition happens below the percolation threshold of network fragmentation, and has its origin in the competition between cascading behavior induced by adopters and blocking due to immune nodes. This change is accompanied by a percolation transition of the induced clusters.

  5. Kinetics of Social Contagion

    NASA Astrophysics Data System (ADS)

    Ruan, Zhongyuan; Iñiguez, Gerardo; Karsai, Márton; Kertész, János

    2015-11-01

    Diffusion of information, behavioral patterns or innovations follows diverse pathways depending on a number of conditions, including the structure of the underlying social network, the sensitivity to peer pressure and the influence of media. Here we study analytically and by simulations a general model that incorporates threshold mechanism capturing sensitivity to peer pressure, the effect of "immune" nodes who never adopt, and a perpetual flow of external information. While any constant, nonzero rate of dynamically introduced spontaneous adopters leads to global spreading, the kinetics by which the asymptotic state is approached shows rich behavior. In particular, we find that, as a function of the immune node density, there is a transition from fast to slow spreading governed by entirely different mechanisms. This transition happens below the percolation threshold of network fragmentation, and has its origin in the competition between cascading behavior induced by adopters and blocking due to immune nodes. This change is accompanied by a percolation transition of the induced clusters.

  6. Complex Contagion of Campaign Donations.

    PubMed

    Traag, Vincent A

    2016-01-01

    Money is central in US politics, and most campaign contributions stem from a tiny, wealthy elite. Like other political acts, campaign donations are known to be socially contagious. We study how campaign donations diffuse through a network of more than 50,000 elites and examine how connectivity among previous donors reinforces contagion. We find that the diffusion of donations is driven by independent reinforcement contagion: people are more likely to donate when exposed to donors from different social groups than when they are exposed to equally many donors from the same group. Counter-intuitively, being exposed to one side may increase donations to the other side. Although the effect is weak, simultaneous cross-cutting exposure makes donation somewhat less likely. Finally, the independence of donors in the beginning of a campaign predicts the amount of money that is raised throughout a campaign. We theorize that people infer population-wide estimates from their local observations, with elites assessing the viability of candidates, possibly opposing candidates in response to local support. Our findings suggest that theories of complex contagions need refinement and that political campaigns should target multiple communities.

  7. Complex Contagion of Campaign Donations

    PubMed Central

    2016-01-01

    Money is central in US politics, and most campaign contributions stem from a tiny, wealthy elite. Like other political acts, campaign donations are known to be socially contagious. We study how campaign donations diffuse through a network of more than 50000 elites and examine how connectivity among previous donors reinforces contagion. We find that the diffusion of donations is driven by independent reinforcement contagion: people are more likely to donate when exposed to donors from different social groups than when they are exposed to equally many donors from the same group. Counter-intuitively, being exposed to one side may increase donations to the other side. Although the effect is weak, simultaneous cross-cutting exposure makes donation somewhat less likely. Finally, the independence of donors in the beginning of a campaign predicts the amount of money that is raised throughout a campaign. We theorize that people infer population-wide estimates from their local observations, with elites assessing the viability of candidates, possibly opposing candidates in response to local support. Our findings suggest that theories of complex contagions need refinement and that political campaigns should target multiple communities. PMID:27077742

  8. Preferred pathways of behavioral contagion.

    PubMed

    Jones, M B; Jones, D R

    1995-01-01

    A behavioral disorder is "contagious" if the risk to a given individual increases when someone in that person's vicinity, family, or social group develops the disorder. So understood, behavioral contagion may be involved in criminality, conduct disorder, drug abuse, suicide, and teenage pregnancy. Previous papers have shown that contagion generates highly distinctive result patterns, from which its presence may be inferred. The patterns concern prevalence in sibships of different size and, in case-control designs, the number of susceptible sibs that affected and unaffected individuals have. The present paper extends the analysis by allowing the likelihood of transmission from one sib to another to vary according as the two sibs are of the same or opposite gender, male or female, single borns or co-twins, fraternal or identical twins. The extension is illustrated by application to data on criminality in Danish twins previously reported by other workers. We will show that the distribution of criminality by gender and zygosity is better explained in terms of behavioral contagion than by previous analyses.

  9. Derivation of two well-behaved theoretical contagion indices and their sampling properties and application for assessing forest landscape diversity

    Treesearch

    Bernard R. Parresol

    2011-01-01

    Studies of spatial patterns of landscapes are useful to quantify human impact, predict wildlife effects, or describe variability of landscape features. A common approach to identify and quantify landscape structure is with a landscape scale model known as a contagion index. A contagion index quantifies two distinct components of landscape diversity: composition and...

  10. Mass Media and the Contagion of Fear: The Case of Ebola in America.

    PubMed

    Towers, Sherry; Afzal, Shehzad; Bernal, Gilbert; Bliss, Nadya; Brown, Shala; Espinoza, Baltazar; Jackson, Jasmine; Judson-Garcia, Julia; Khan, Maryam; Lin, Michael; Mamada, Robert; Moreno, Victor M; Nazari, Fereshteh; Okuneye, Kamaldeen; Ross, Mary L; Rodriguez, Claudia; Medlock, Jan; Ebert, David; Castillo-Chavez, Carlos

    2015-01-01

    In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as "digital epidemiology"), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends. We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data. We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.

  11. Mass Media and the Contagion of Fear: The Case of Ebola in America

    PubMed Central

    Towers, Sherry; Afzal, Shehzad; Bernal, Gilbert; Bliss, Nadya; Brown, Shala; Espinoza, Baltazar; Jackson, Jasmine; Judson-Garcia, Julia; Khan, Maryam; Lin, Michael; Mamada, Robert; Moreno, Victor M.; Nazari, Fereshteh; Okuneye, Kamaldeen; Ross, Mary L.; Rodriguez, Claudia; Medlock, Jan; Ebert, David; Castillo-Chavez, Carlos

    2015-01-01

    Background In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends. Methodology We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data. Conclusions We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model. PMID:26067433

  12. Contagion on complex networks with persuasion.

    PubMed

    Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu

    2016-03-31

    The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense.

  13. Contagion on complex networks with persuasion

    NASA Astrophysics Data System (ADS)

    Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu

    2016-03-01

    The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense.

  14. Exercise contagion in a global social network

    PubMed Central

    Aral, Sinan; Nicolaides, Christos

    2017-01-01

    We leveraged exogenous variation in weather patterns across geographies to identify social contagion in exercise behaviours across a global social network. We estimated these contagion effects by combining daily global weather data, which creates exogenous variation in running among friends, with data on the network ties and daily exercise patterns of ∼1.1M individuals who ran over 350M km in a global social network over 5 years. Here we show that exercise is socially contagious and that its contagiousness varies with the relative activity of and gender relationships between friends. Less active runners influence more active runners, but not the reverse. Both men and women influence men, while only women influence other women. While the Embeddedness and Structural Diversity theories of social contagion explain the influence effects we observe, the Complex Contagion theory does not. These results suggest interventions that account for social contagion will spread behaviour change more effectively. PMID:28418379

  15. Exercise contagion in a global social network.

    PubMed

    Aral, Sinan; Nicolaides, Christos

    2017-04-18

    We leveraged exogenous variation in weather patterns across geographies to identify social contagion in exercise behaviours across a global social network. We estimated these contagion effects by combining daily global weather data, which creates exogenous variation in running among friends, with data on the network ties and daily exercise patterns of ∼1.1M individuals who ran over 350M km in a global social network over 5 years. Here we show that exercise is socially contagious and that its contagiousness varies with the relative activity of and gender relationships between friends. Less active runners influence more active runners, but not the reverse. Both men and women influence men, while only women influence other women. While the Embeddedness and Structural Diversity theories of social contagion explain the influence effects we observe, the Complex Contagion theory does not. These results suggest interventions that account for social contagion will spread behaviour change more effectively.

  16. The impact of social contagion on non-suicidal self-injury: a review of the literature.

    PubMed

    Jarvi, Stephanie; Jackson, Benita; Swenson, Lance; Crawford, Heather

    2013-01-01

    In this review, we explore social contagion as an understudied risk factor for non-suicidal self-injury (NSSI) among adolescents and young adults, populations with a high prevalence of NSSI. We review empirical studies reporting data on prevalence and risk factors that, through social contagion, may influence the transmission of NSSI. Findings in this literature are consistent with social modeling/learning of NSSI increasing risk of initial engagement in NSSI among individuals with certain individual and/or psychiatric characteristics. Preliminary research suggests iatrogenic effects of social contagion of NSSI through primary prevention are not likely. Thus, social contagion factors may warrant considerable empirical attention. Intervention efforts may be enhanced, and social contagion reduced, by implementation of psychoeducation and awareness about NSSI in schools, colleges, and treatment programs.

  17. Range of interaction in an opinion evolution model of ideological self-positioning: Contagion, hesitance and polarization

    NASA Astrophysics Data System (ADS)

    Gimenez, M. Cecilia; Paz García, Ana Pamela; Burgos Paci, Maxi A.; Reinaudi, Luis

    2016-04-01

    The evolution of public opinion using tools and concepts borrowed from Statistical Physics is an emerging area within the field of Sociophysics. In the present paper, a Statistical Physics model was developed to study the evolution of the ideological self-positioning of an ensemble of agents. The model consists of an array of L components, each one of which represents the ideology of an agent. The proposed mechanism is based on the ;voter model;, in which one agent can adopt the opinion of another one if the difference of their opinions lies within a certain range. The existence of ;undecided; agents (i.e. agents with no definite opinion) was implemented in the model. The possibility of radicalization of an agent's opinion upon interaction with another one was also implemented. The results of our simulations are compared to statistical data taken from the Latinobarómetro databank for the cases of Argentina, Chile, Brazil and Uruguay in the last decade. Among other results, the effect of taking into account the undecided agents is the formation of a single peak at the middle of the ideological spectrum (which corresponds to a centrist ideological position), in agreement with the real cases studied.

  18. Contagion of Cooperation in Static and Fluid Social Networks

    PubMed Central

    Jordan, Jillian J.; Rand, David G.; Arbesman, Samuel; Fowler, James H.; Christakis, Nicholas A.

    2013-01-01

    Cooperation is essential for successful human societies. Thus, understanding how cooperative and selfish behaviors spread from person to person is a topic of theoretical and practical importance. Previous laboratory experiments provide clear evidence of social contagion in the domain of cooperation, both in fixed networks and in randomly shuffled networks, but leave open the possibility of asymmetries in the spread of cooperative and selfish behaviors. Additionally, many real human interaction structures are dynamic: we often have control over whom we interact with. Dynamic networks may differ importantly in the goals and strategic considerations they promote, and thus the question of how cooperative and selfish behaviors spread in dynamic networks remains open. Here, we address these questions with data from a social dilemma laboratory experiment. We measure the contagion of both cooperative and selfish behavior over time across three different network structures that vary in the extent to which they afford individuals control over their network ties. We find that in relatively fixed networks, both cooperative and selfish behaviors are contagious. In contrast, in more dynamic networks, selfish behavior is contagious, but cooperative behavior is not: subjects are fairly likely to switch to cooperation regardless of the behavior of their neighbors. We hypothesize that this insensitivity to the behavior of neighbors in dynamic networks is the result of subjects’ desire to attract new cooperative partners: even if many of one’s current neighbors are defectors, it may still make sense to switch to cooperation. We further hypothesize that selfishness remains contagious in dynamic networks because of the well-documented willingness of cooperators to retaliate against selfishness, even when doing so is costly. These results shed light on the contagion of cooperative behavior in fixed and fluid networks, and have implications for influence-based interventions aiming at

  19. Can a violation of investor trust lead to financial contagion in the market for tax-exempt hospital bonds?

    PubMed

    Bernet, Patrick M; Getzen, Thomas E

    2008-03-01

    Not-for-profit hospitals rely heavily on tax-exempt debt. Investor confidence in such instruments was shaken by the 1998 bankruptcy of the Allegheny Health and Education Research Foundation (AHERF), which was the largest U.S. not-for-profit failure up to that date and whose default was accompanied by claims of accounting irregularities. Such shocks can result in contagion whereby all hospitals are viewed as riskier. We test for the significance and duration of resulting contagion using an industry-specific model of interest cost determinants. Empirical tests indicate that contagion does occur, resulting in higher interest on new debt issues from other hospitals.

  20. Contagion on complex networks with persuasion

    PubMed Central

    Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu

    2016-01-01

    The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense. PMID:27029498

  1. Regional Contagion: Social, Economic, Health and Population Crisis Diffusion

    DTIC Science & Technology

    2008-04-24

    crises have escalated and diffused through spatial , temporal and population networks, like a contagion . Many times a crisis in one dimension, like...history. In this environment, multiple crises have escalated and diffused through spatial , temporal and population networks, like a contagion . Many...and throughout history, crisis has escalated and diffused through spatial , temporal and population networks, like a contagion . With globalization and

  2. The Social Contagion of Generosity

    PubMed Central

    Tsvetkova, Milena; Macy, Michael W.

    2014-01-01

    Why do people help strangers when there is a low probability that help will be directly reciprocated or socially rewarded? A possible explanation is that these acts are contagious: those who receive or observe help from a stranger become more likely to help others. We test two mechanisms for the social contagion of generosity among strangers: generalized reciprocity (a recipient of generosity is more likely to pay it forward) and third-party influence (an observer of generous behavior is more likely to emulate it). We use an online experiment with randomized trials to test the two hypothesized mechanisms and their interaction by manipulating the extent to which participants receive and observe help. Results show that receiving help can increase the willingness to be generous towards others, but observing help can have the opposite effect, especially among those who have not received help. These results suggest that observing widespread generosity may attenuate the belief that one’s own efforts are needed. PMID:24551053

  3. Predicting the origin of contagion processes on complex, multi-scale networks

    NASA Astrophysics Data System (ADS)

    Brune, Rafael; Thiemann, Christian; Brockmann, Dirk

    2012-02-01

    Contagion phenomena in space often exhibit complex, multiscale spatio-temporal patterns driven by the interaction of non-local dispersal and nonlinear dynamics. A key challenge is the prediction of dynamic patterns based on information on human interactions, mobility and initial conditions. The development of computational models has thus received considerable attention. However, in many realistic situations, a process has already evolved for some period before detection and identifying the spatial origin is difficult. Surprisingly, this ``inverse problem'' has received little attention in the past. We show in a paradigmatic model for human disease dynamics that despite the spatial complexity of dynamic patterns, the origin of outbreak can be predicted with high fidelity. Based on the technique of shortest path trees in strongly heterogeneous, multi-scale human mobility networks we show that at any point in time the spatial origin can be reconstructed reliably. This novel perspective on complex spatio-temporal dynamics can be applied to systems beyond human disease dynamics for instance the reconstruction of neolithic diffusion of agriculture into Europe and related migration driven historic phenomena.

  4. Inhibiting diffusion of complex contagions in social networks: theoretical and experimental results

    PubMed Central

    Anil Kumar, V.S.; Marathe, Madhav V.; Ravi, S.S.; Rosenkrantz, Daniel J.

    2014-01-01

    We consider the problem of inhibiting undesirable contagions (e.g. rumors, spread of mob behavior) in social networks. Much of the work in this context has been carried out under the 1-threshold model, where diffusion occurs when a node has just one neighbor with the contagion. We study the problem of inhibiting more complex contagions in social networks where nodes may have thresholds larger than 1. The goal is to minimize the propagation of the contagion by removing a small number of nodes (called critical nodes) from the network. We study several versions of this problem and prove that, in general, they cannot even be efficiently approximated to within any factor ρ ≥ 1, unless P = NP. We develop efficient and practical heuristics for these problems and carry out an experimental study of their performance on three well known social networks, namely epinions, wikipedia and slashdot. Our results show that these heuristics perform significantly better than five other known methods. We also establish an efficiently computable upper bound on the number of nodes to which a contagion can spread and evaluate this bound on many real and synthetic networks. PMID:25750583

  5. Building an Intelligent Hospital to Fight Contagion.

    PubMed

    Bataille, Jérôme; Brouqui, Philippe

    2017-08-15

    The idea of building hospitals to fight contagion was born with the lazarettos. At the time when the microorganisms were not yet known, the mechanisms of transmission of contagion were already well apprehended. Based on the same knowledge but thanks to new technologies, such hospitals have now been built downtown, next to the most highly performing technological plateau. Regrouping patient care, diagnostics, research, and development, the University Hospital Institute Méditerranée Infection building offers a wonderful tool to contain and understand contagion, in a well-designed setting, creating excellent working conditions that are attractive for interested scientists. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

  6. A Multi-agent Simulation Tool for Micro-scale Contagion Spread Studies

    SciTech Connect

    Koch, Daniel B

    2016-01-01

    Within the disaster preparedness and emergency response community, there is interest in how contagions spread person-to-person at large gatherings and if mitigation strategies can be employed to reduce new infections. A contagion spread simulation module was developed for the Incident Management Preparedness and Coordination Toolkit that allows a user to see how a geographically accurate layout of the gathering space helps or hinders the spread of a contagion. The results can inform mitigation strategies based on changing the physical layout of an event space. A case study was conducted for a particular event to calibrate the underlying simulation model. This paper presents implementation details of the simulation code that incorporates agent movement and disease propagation. Elements of the case study are presented to show how the tool can be used.

  7. Equivalent Dynamic Models.

    PubMed

    Molenaar, Peter C M

    2017-02-16

    Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.

  8. Dissemination Of Opinions And Ideas Via Complex Contagion On Social Networks

    DTIC Science & Technology

    2016-09-23

    AFRL-AFOSR-JP-TR-2016-0076 Dissemination of opinions and ideas via complex contagion on social networks Yoshihisa Kashima UNIVERSITY OF MELBOURNE...contagion on social networks 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA2386-15-1-4020 5c.  PROGRAM ELEMENT NUMBER 61102F 6. AUTHOR(S) Yoshihisa Kashima 5d...cultural) and immutable features into a model of neighborhood segregation and social network formation, this research shows that under some

  9. Perception of behavioral contagion of adolescent suicide.

    PubMed

    Range, L M; Goggin, W C; Steede, K K

    1988-01-01

    In order to assess perceptions of behavioral contagion of suicide (what people thought a disturbed adolescent would do if the teen knew about a suicide in the community), and to assess actor-observer differences in such perceptions, 142 college students were asked to view a videotaped vignette of a distressed high school student, and then to assess her potential for committing suicide, running away, entering therapy, or abusing alcohol. Subjects who were told that the teenager knew of two recent suicides in the community (contagion group) rated the young woman as more likely to commit suicide or run away than did the subjects who were not told of the suicides (noncontagion group). Subjects who were instructed to imagine that they were the teenager (actors) blamed situational factors, and in particular the teen's parents, more for her distress than did subjects who were instructed just to rate the teenager on the videotape (observers). Contagion/actors rated suicide as more likely than did any other group. Apparently, people believe that behavioral contagion occurs when a suicide is reported, and they especially perceive themselves to be influenced by such information.

  10. Thermal dynamic modeling study

    NASA Technical Reports Server (NTRS)

    Ojalvo, I. U.

    1972-01-01

    Some thermal dynamic requirements associated with the space shuttle vehicle are reviewed. Pertinent scaling laws are discussed and recommendations are offered regarding the need for conducting reduced-scale dynamic tests of major components at elevated temperatures. Items considered are the development and interpretation of thermal dynamic structural scaling laws, the identification of major related problem areas and a presentation of viable model fabrication, instrumentation, and test procedures.

  11. Suicide contagion: a systematic review of definitions and research utility.

    PubMed

    Cheng, Qijin; Li, Hong; Silenzio, Vincent; Caine, Eric D

    2014-01-01

    Despite the common use of contagion to analogize the spread of suicide, there is a lack of rigorous assessment of the underlying concept or theory supporting the use of this term. The present study aims to examine the varied definitions and potential utility of the term contagion in suicide-related research. 100 initial records and 240 reference records in English were identified as relevant with our research objectives, through systematic literature screening. We then conducted narrative syntheses of various definitions and assessed their potential value for generating new research. 20.3% of the 340 records used contagion as equivalent to clustering (contagion-as-cluster); 68.5% used it to refer to various, often related mechanisms underlying the clustering phenomenon (contagion-as-mechanism); and 11.2% without clear definition. Under the category of contagion-as-mechanism, four mechanisms have been proposed to explain how suicide clusters occurred: transmission (contagion-as-transmission), imitation (contagion-as-imitation), contextual influence (contagion-as-context), and affiliation (contagion-as-affiliation). Contagion-as-cluster both confounds and constrains inquiry into suicide clustering by blending proposed mechanism with the phenomenon to be studied. Contagion-as-transmission is, in essence, a double or internally redundant metaphor. Contagion-as-affiliation and contagion-as-context involve mechanisms that are common mechanisms that often occur independently of apparent contagion, or may serve as a facilitating background. When used indiscriminately, these terms may create research blind spots. Contagion-as-imitation combines perspectives from psychology, sociology, and public health research and provides the greatest heuristic utility for examining whether and how suicide and suicidal behaviors may spread among persons at both individual and population levels. Clarifying the concept of "suicide contagion" is an essential step for more thoroughly

  12. Cholera, canals, and contagion: Rediscovering Dr. Beck's report.

    PubMed

    Tuite, Ashleigh R; Chan, Christina H; Fisman, David N

    2011-08-01

    Cholera first appeared in North America (in Montreal and Quebec) in 1832 and spread rapidly across the eastern half of the continent. The dispatch of American disease control experts to Lower Canada in anticipation of cholera's spread implies that medical professionals expected spread, possibly from contagion, even though the notion that cholera was contagious was disparaged in medical writings of the time, and would be until John Snow's landmark work in London in the 1850s. Snow's insights derived largely from his observations on spatial and temporal patterns of cholera cases. We discuss a document from the 1832 epidemic, the report of Dr. Lewis Beck to New York's Governor Throop, which anticipates Snow in presenting geospatial data that imply cholera's contagiousness. Beck shows that the movements of immigrants along the newly completed New York state canal system resulted in sequential cholera outbreaks along the canal's path. Although aware of the degree to which this suggested contagion, Beck argues strenuously against the contagiousness of cholera. We explore the social context of early nineteenth-century medicine that probably led Beck to disbelieve his own observations, and to favor a medical model inconsistent with his data. Themes that emerge from our inquiry include belief in disease as a physical manifestation of defective morality, stigmatization of the poor and immigrant groups, and reluctance to overturn prevailing medical models that themselves reflected the economic position of medical practitioners. We show that these themes continue to serve as obstacles to innovation in medical and public health practice today.

  13. Modeling Climate Dynamically

    ERIC Educational Resources Information Center

    Walsh, Jim; McGehee, Richard

    2013-01-01

    A dynamical systems approach to energy balance models of climate is presented, focusing on low order, or conceptual, models. Included are global average and latitude-dependent, surface temperature models. The development and analysis of the differential equations and corresponding bifurcation diagrams provides a host of appropriate material for…

  14. Modeling Climate Dynamically

    ERIC Educational Resources Information Center

    Walsh, Jim; McGehee, Richard

    2013-01-01

    A dynamical systems approach to energy balance models of climate is presented, focusing on low order, or conceptual, models. Included are global average and latitude-dependent, surface temperature models. The development and analysis of the differential equations and corresponding bifurcation diagrams provides a host of appropriate material for…

  15. Dynamic model for biospeckle.

    PubMed

    Paixão, Crysttian Arantes; da Costa, Antonio Tavares

    2013-06-01

    This paper reports the development of a simple dynamic microscopic model to describe the main features of the phenomenon known as dynamic speckle, or biospeckle. Biospeckle is an interference pattern formed when a biological surface is illuminated with coherent light. The dynamic characteristics of biospeckle have been investigated as possible tools for assessing the quality of biological products. Our model, despite its simplicity, was able to reproduce qualitatively the main features of biospeckle. We were able to correlate variations in a microscopic parameter associated with movement of the particles comprising the organic surface with changes in a macroscopic parameter that measures the change rate of a dynamic interference pattern. We showed that this correlation occurs only within a limited range of parameter microscope values. We also showed how our model was able to describe nonuniform surfaces composed of more than one type of particles.

  16. Suicide Contagion: A Systematic Review of Definitions and Research Utility

    PubMed Central

    Cheng, Qijin; Li, Hong; Silenzio, Vincent; Caine, Eric D.

    2014-01-01

    Objectives Despite the common use of contagion to analogize the spread of suicide, there is a lack of rigorous assessment of the underlying concept or theory supporting the use of this term. The present study aims to examine the varied definitions and potential utility of the term contagion in suicide-related research. Methods 100 initial records and 240 reference records in English were identified as relevant with our research objectives, through systematic literature screening. We then conducted narrative syntheses of various definitions and assessed their potential value for generating new research. Results 20.3% of the 340 records used contagion as equivalent to clustering (contagion-as-cluster); 68.5% used it to refer to various, often related mechanisms underlying the clustering phenomenon (contagion-as-mechanism); and 11.2% without clear definition. Under the category of contagion-as-mechanism, four mechanisms have been proposed to explain how suicide clusters occurred: transmission (contagion-as-transmission), imitation (contagion-as-imitation), contextual influence (contagion-as-context), and affiliation (contagion-as-affiliation). Contagion-as-cluster both confounds and constrains inquiry into suicide clustering by blending proposed mechanism with the phenomenon to be studied. Contagion-as-transmission is, in essence, a double or internally redundant metaphor. Contagion-as-affiliation and contagion-as-context involve mechanisms that are common mechanisms that often occur independently of apparent contagion, or may serve as a facilitating background. When used indiscriminately, these terms may create research blind spots. Contagion-as-imitation combines perspectives from psychology, sociology, and public health research and provides the greatest heuristic utility for examining whether and how suicide and suicidal behaviors may spread among persons at both individual and population levels. Conclusion Clarifying the concept of “suicide contagion” is an

  17. Systemic risk, maximum entropy and interbank contagion

    NASA Astrophysics Data System (ADS)

    Andrecut, M.

    2016-06-01

    We discuss the systemic risk implied by the interbank exposures reconstructed with the maximum entropy (ME) method. The ME method severely underestimates the risk of interbank contagion by assuming a fully connected network, while in reality the structure of the interbank network is sparsely connected. Here, we formulate an algorithm for sparse network reconstruction, and we show numerically that it provides a more reliable estimation of the systemic risk.

  18. Dynamic causal modelling revisited.

    PubMed

    Friston, K J; Preller, Katrin H; Mathys, Chris; Cagnan, Hayriye; Heinzle, Jakob; Razi, Adeel; Zeidman, Peter

    2017-02-17

    This paper revisits the dynamic causal modelling of fMRI timeseries by replacing the usual (Taylor) approximation to neuronal dynamics with a neural mass model of the canonical microcircuit. This provides a generative or dynamic causal model of laminar specific responses that can generate haemodynamic and electrophysiological measurements. In principle, this allows the fusion of haemodynamic and (event related or induced) electrophysiological responses. Furthermore, it enables Bayesian model comparison of competing hypotheses about physiologically plausible synaptic effects; for example, does attentional modulation act on superficial or deep pyramidal cells - or both? In this technical note, we describe the resulting dynamic causal model and provide an illustrative application to the attention to visual motion dataset used in previous papers. Our focus here is on how to answer long-standing questions in fMRI; for example, do haemodynamic responses reflect extrinsic (afferent) input from distant cortical regions, or do they reflect intrinsic (recurrent) neuronal activity? To what extent do inhibitory interneurons contribute to neurovascular coupling? What is the relationship between haemodynamic responses and the frequency of induced neuronal activity? This paper does not pretend to answer these questions; rather it shows how they can be addressed using neural mass models of fMRI timeseries.

  19. Corruption dynamics model

    NASA Astrophysics Data System (ADS)

    Malafeyev, O. A.; Nemnyugin, S. A.; Rylow, D.; Kolpak, E. P.; Awasthi, Achal

    2017-07-01

    The corruption dynamics is analyzed by means of the lattice model which is similar to the three-dimensional Ising model. Agents placed at nodes of the corrupt network periodically choose to perfom or not to perform the act of corruption at gain or loss while making decisions based on the process history. The gain value and its dynamics are defined by means of the Markov stochastic process modelling with parameters established in accordance with the influence of external and individual factors on the agent's gain. The model is formulated algorithmically and is studied by means of the computer simulation. Numerical results are obtained which demonstrate asymptotic behaviour of the corruption network under various conditions.

  20. Efficient target strategies for contagion in scale-free networks

    NASA Astrophysics Data System (ADS)

    Duan, Wenqi; Chen, Zhong; Liu, Zengrong; Jin, Wei

    2005-08-01

    Organizations or individuals often have an incentive to target a certain number of agents to launch a contagion process effectively and efficiently, for example, sampling consumers in the diffusion of new products. We present an effective strategy for contagion in scale-free networks. The proposed strategy, hub strategy, calls for targeting mostly the highly connected nodes. The biased level implemented in this strategy characterizes its ability to identify hub nodes. We demonstrate that hub strategy can improve the contagion effects evidently. We find that biased level increases first with heterogeneity level of contagion network but decreases with that after a certain value, and decreases with initial adopter rate all the time. Moreover, degree correlations in contagion networks may reduce biased level.

  1. Modelling sea ice dynamics

    NASA Astrophysics Data System (ADS)

    Murawski, Jens; Kleine, Eckhard

    2017-04-01

    Sea ice remains one of the frontiers of ocean modelling and is of vital importance for the correct forecasts of the northern oceans. At large scale, it is commonly considered a continuous medium whose dynamics is modelled in terms of continuum mechanics. Its specifics are a matter of constitutive behaviour which may be characterised as rigid-plastic. The new developed sea ice dynamic module bases on general principles and follows a systematic approach to the problem. Both drift field and stress field are modelled by a variational property. Rigidity is treated by Lagrangian relaxation. Thus one is led to a sensible numerical method. Modelling fast ice remains to be a challenge. It is understood that ridging and the formation of grounded ice keels plays a role in the process. The ice dynamic model includes a parameterisation of the stress associated with grounded ice keels. Shear against the grounded bottom contact might lead to plastic deformation and the loss of integrity. The numerical scheme involves a potentially large system of linear equations which is solved by pre-conditioned iteration. The entire algorithm consists of several components which result from decomposing the problem. The algorithm has been implemented and tested in practice.

  2. Dynamical model for thyroid

    NASA Astrophysics Data System (ADS)

    Rokni Lamooki, Gholam Reza; Shirazi, Amir H.; Mani, Ali R.

    2015-05-01

    Thyroid's main chemical reactions are employed to develop a mathematical model. The presented model is based on differential equations where their dynamics reflects many aspects of thyroid's behavior. Our main focus here is the well known, but not well understood, phenomenon so called as Wolff-Chaikoff effect. It is shown that the inhibitory effect of intake iodide on the rate of one single enzyme causes a similar effect as Wolff-Chaikoff. Besides this issue, the presented model is capable of revealing other complex phenomena of thyroid hormones homeostasis.

  3. Detecting Emotional Contagion in Massive Social Networks

    PubMed Central

    Coviello, Lorenzo; Sohn, Yunkyu; Kramer, Adam D. I.; Marlow, Cameron; Franceschetti, Massimo; Christakis, Nicholas A.; Fowler, James H.

    2014-01-01

    Happiness and other emotions spread between people in direct contact, but it is unclear whether massive online social networks also contribute to this spread. Here, we elaborate a novel method for measuring the contagion of emotional expression. With data from millions of Facebook users, we show that rainfall directly influences the emotional content of their status messages, and it also affects the status messages of friends in other cities who are not experiencing rainfall. For every one person affected directly, rainfall alters the emotional expression of about one to two other people, suggesting that online social networks may magnify the intensity of global emotional synchrony. PMID:24621792

  4. Social contagion process in informal warning networks to understand evacuation timing behavior.

    PubMed

    Hasan, Samiul; Ukkusuri, Satish V

    2013-01-01

    Individual evacuation decisions are often characterized by the influence of one's social network, referred to as informal warning network. In this article, a threshold model of social contagion, originally introduced in the network science literature, is proposed to characterize this social influence in the evacuation decision-making process, in particular the timing of evacuation decision. Simulation models are developed to investigate the effects of community mixing patterns and the strength of ties on timing of evacuation decision.

  5. Pictures of you: Dot stimuli cause motor contagion in presence of a still human form.

    PubMed

    Sparks, S; Sidari, M; Lyons, M; Kritikos, A

    2016-10-01

    In this study, we investigate which visual cues induce participants to encode a non-human motion stimulus in their motor system. Participants performed reach-to-grasp actions to a target after observing a dot moving in a direct or higher-arcing path across a screen. Dot motion occurred in the presence of a meaningless (scrambled human model) stimulus, a still human model, or a human model performing a direct or exaggeratedly curved reach to a target. Our results show that observing the dot displacement causes motor contagion (changes in the height of the observer's hand trajectory) when a human form was visually present in the background (either moving or still). No contagion was evident, however, when this human context was absent (i.e., human image scrambled and not identifiable). This indicates that visual cues suggestive of human agency can determine whether or not moving stimuli are encoded in the motor system.

  6. Modeling Fractal Dynamics

    NASA Astrophysics Data System (ADS)

    West, Bruce J.

    The proper methodology for describing the dynamics of certain complex phenomena and fractal time series is the fractional calculus through the fractional Langevin equation discussed herein and applied in a biomedical context. We show that a fractional operator (derivative or integral) acting on a fractal function, yields another fractal function, allowing us to construct a fractional Langevin equation to describe the evolution of a fractal statistical process, for example, human gait and cerebral blood flow. The goal of this talk is to make clear how certain complex phenomena, such as those that are abundantly present in human physiology, can be faithfully described using dynamical models involving fractional differential stochastic equations. These models are tested against existing data sets and shown to describe time series from complex physiologic phenomena quite well.

  7. Mesoscale ocean dynamics modeling

    SciTech Connect

    mHolm, D.; Alber, M.; Bayly, B.; Camassa, R.; Choi, W.; Cockburn, B.; Jones, D.; Lifschitz, A.; Margolin, L.; Marsden, L.; Nadiga, B.; Poje, A.; Smolarkiewicz, P.; Levermore, D.

    1996-05-01

    This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The ocean is a very complex nonlinear system that exhibits turbulence on essentially all scales, multiple equilibria, and significant intrinsic variability. Modeling the ocean`s dynamics at mesoscales is of fundamental importance for long-time-scale climate predictions. A major goal of this project has been to coordinate, strengthen, and focus the efforts of applied mathematicians, computer scientists, computational physicists and engineers (at LANL and a consortium of Universities) in a joint effort addressing the issues in mesoscale ocean dynamics. The project combines expertise in the core competencies of high performance computing and theory of complex systems in a new way that has great potential for improving ocean models now running on the Connection Machines CM-200 and CM-5 and on the Cray T3D.

  8. Writer-Reader Contagion of Inspiration and Related States: Conditional Process Analyses Within a Cross-Classified Writer × Reader Framework.

    PubMed

    Thrash, Todd M; Maruskin, Laura A; Moldovan, Emil G; Oleynick, Victoria C; Belzak, Will C

    2016-04-28

    A longstanding tradition in the humanities holds that a writer's inspiration is infectious, but this thesis has not been tested. We hypothesized that (a) inspiration is infectious, such that inspired writers are more inspiring to the average reader; (b) contagion is mediated by the insightfulness of the text; and (c) contagion is moderated by readers' openness to experience, such that open readers are more prone to contagion. To test these hypotheses, a sample of 195 student writers, each of whom wrote 1 poem, was crossed with a sample of 220 student readers, who read all poems. Data were available for 36,020 cells of the resulting Writer × Reader matrix. Our analytic approach integrated cross-classified multilevel modeling with conditional process analysis. As hypothesized, writers who were more inspired elicited higher levels of inspiration in the average reader. Inspiration contagion was mediated by the insightfulness and pleasantness of the text and was partially suppressed by originality. Inspiration contagion was moderated by reader openness. Moderated mediation analyses indicated that open readers were prone to contagion because they were tolerant of the originality and sublimity of inspired writing. Additional analyses differentiated contagion of inspiration from contagion of its covariates (awe, positive affect), documented effects of writer inspiration on reader enthrallment (awe, chills), and showed that writer effort is a poor predictor of reader states. The infectiousness of inspiration-through poetry, if not also through scripture and academic writing-suggests that a given instance of inspiration may have far-reaching cultural implications, including dissemination of innovations and ideologies. (PsycINFO Database Record

  9. Peer Contagion in Child and Adolescent Social and Emotional Development

    PubMed Central

    Dishion, Thomas J.; Tipsord, Jessica M.

    2012-01-01

    In this article, we examine the construct of peer contagion in childhood and adolescence and review studies of child and adolescent development that have identified peer contagion influences. Evidence suggests that children's interactions with peers are tied to increases in aggression in early and middle childhood and amplification of problem behaviors such as drug use, delinquency, and violence in early to late adolescence. Deviancy training is one mechanism that accounts for peer contagion effects on problem behaviors from age 5 through adolescence. In addition, we discuss peer contagion relevant to depression in adolescence, and corumination as an interactive process that may account for these effects. Social network analyses suggest that peer contagion underlies the influence of friendship on obesity, unhealthy body images, and expectations. Literature is reviewed that suggests how peer contagion effects can undermine the goals of public education from elementary school through college and impair the goals of juvenile corrections systems. In particular, programs that “select” adolescents at risk for aggregated preventive interventions are particularly vulnerable to peer contagion effects. It appears that a history of peer rejection is a vulnerability factor for influence by peers, and adult monitoring, supervision, positive parenting, structure, and self-regulation serve as protective factors. PMID:19575606

  10. Peer contagion in child and adolescent social and emotional development.

    PubMed

    Dishion, Thomas J; Tipsord, Jessica M

    2011-01-01

    In this article, we examine the construct of peer contagion in childhood and adolescence and review studies of child and adolescent development that have identified peer contagion influences. Evidence suggests that children's interactions with peers are tied to increases in aggression in early and middle childhood and amplification of problem behaviors such as drug use, delinquency, and violence in early to late adolescence. Deviancy training is one mechanism that accounts for peer contagion effects on problem behaviors from age 5 through adolescence. In addition, we discuss peer contagion relevant to depression in adolescence, and corumination as an interactive process that may account for these effects. Social network analyses suggest that peer contagion underlies the influence of friendship on obesity, unhealthy body images, and expectations. Literature is reviewed that suggests how peer contagion effects can undermine the goals of public education from elementary school through college and impair the goals of juvenile corrections systems. In particular, programs that "select" adolescents at risk for aggregated preventive interventions are particularly vulnerable to peer contagion effects. It appears that a history of peer rejection is a vulnerability factor for influence by peers, and adult monitoring, supervision, positive parenting, structure, and self-regulation serve as protective factors.

  11. Simple deterministic models and applications. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

    NASA Astrophysics Data System (ADS)

    Yang, Hyun Mo

    2015-12-01

    Currently, discrete modellings are largely accepted due to the access to computers with huge storage capacity and high performance processors and easy implementation of algorithms, allowing to develop and simulate increasingly sophisticated models. Wang et al. [7] present a review of dynamics in complex networks, focusing on the interaction between disease dynamics and human behavioral and social dynamics. By doing an extensive review regarding to the human behavior responding to disease dynamics, the authors briefly describe the complex dynamics found in the literature: well-mixed populations networks, where spatial structure can be neglected, and other networks considering heterogeneity on spatially distributed populations. As controlling mechanisms are implemented, such as social distancing due 'social contagion', quarantine, non-pharmaceutical interventions and vaccination, adaptive behavior can occur in human population, which can be easily taken into account in the dynamics formulated by networked populations.

  12. Yawning Detection Sensitivity and Yawning Contagion.

    PubMed

    Chan, Meingold H M; Tseng, Chia-Huei

    2017-01-01

    Contagious yawning-the urge to yawn when thinking about, listening to, or viewing yawning-is a well-documented phenomenon in humans and animals. The reduced yawn contagion observed in the autistic population suggested that it might be empathy related; however, it is unknown whether such a connection applies to nonclinical populations. We examined influences from both empathy (i.e., autistic traits) and nonempathy factors (i.e., individuals' perceptual detection sensitivity to yawning, happy, and angry faces) on 41 nonclinical adults. We induced contagious yawning with a 5-minute video and 20 yawning photo stimuli. In addition, we measured participants' autistic traits (with the autism-spectrum quotient questionnaire), eye gaze patterns, and their perceptual thresholds to detect yawning and emotion in human face photos. We found two factors associated with yawning contagion: (a) those more sensitive to detect yawning, but not other emotional expressions, displayed more contagious yawning than those less sensitive to yawning expressions, and (b) female participants exhibited significantly more contagious yawning than male participants. We did not find an association between autistic trait and contagious yawning. Our study offers a working hypothesis for future studies, in that perceptual encoding of yawning interacts with susceptibility to contagious yawning.

  13. Yawning Detection Sensitivity and Yawning Contagion

    PubMed Central

    Chan, Meingold H. M.

    2017-01-01

    Contagious yawning—the urge to yawn when thinking about, listening to, or viewing yawning—is a well-documented phenomenon in humans and animals. The reduced yawn contagion observed in the autistic population suggested that it might be empathy related; however, it is unknown whether such a connection applies to nonclinical populations. We examined influences from both empathy (i.e., autistic traits) and nonempathy factors (i.e., individuals’ perceptual detection sensitivity to yawning, happy, and angry faces) on 41 nonclinical adults. We induced contagious yawning with a 5-minute video and 20 yawning photo stimuli. In addition, we measured participants’ autistic traits (with the autism-spectrum quotient questionnaire), eye gaze patterns, and their perceptual thresholds to detect yawning and emotion in human face photos. We found two factors associated with yawning contagion: (a) those more sensitive to detect yawning, but not other emotional expressions, displayed more contagious yawning than those less sensitive to yawning expressions, and (b) female participants exhibited significantly more contagious yawning than male participants. We did not find an association between autistic trait and contagious yawning. Our study offers a working hypothesis for future studies, in that perceptual encoding of yawning interacts with susceptibility to contagious yawning. PMID:28890778

  14. Contagion in an interacting economy

    NASA Astrophysics Data System (ADS)

    Paga, Pierre; Kühn, Reimer

    2015-03-01

    We investigate the credit risk model defined in Hatchett and Kühn (2006 J. Phys. A: Math. Gen. 39 2231) under more general assumptions, in particular using a general degree distribution for sparse graphs. Expanding upon earlier results, we show that the model is exactly solvable in the N → ∞ limit and demonstrate that the exact solution is described by the message-passing approach outlined in Karrer and Newman (2010 Phys. Rev. E 82 016101), generalized to include heterogeneous agents and couplings. We provide comparisons with simulations of graph ensembles with power-law degree distributions.

  15. Contact dynamics math model

    NASA Technical Reports Server (NTRS)

    Glaese, John R.; Tobbe, Patrick A.

    1986-01-01

    The Space Station Mechanism Test Bed consists of a hydraulically driven, computer controlled six degree of freedom (DOF) motion system with which docking, berthing, and other mechanisms can be evaluated. Measured contact forces and moments are provided to the simulation host computer to enable representation of orbital contact dynamics. This report describes the development of a generalized math model which represents the relative motion between two rigid orbiting vehicles. The model allows motion in six DOF for each body, with no vehicle size limitation. The rotational and translational equations of motion are derived. The method used to transform the forces and moments from the sensor location to the vehicles' centers of mass is also explained. Two math models of docking mechanisms, a simple translational spring and the Remote Manipulator System end effector, are presented along with simulation results. The translational spring model is used in an attempt to verify the simulation with compensated hardware in the loop results.

  16. Heightened emotional contagion in mild cognitive impairment and Alzheimer’s disease is associated with temporal lobe degeneration

    PubMed Central

    Sturm, Virginia E.; Yokoyama, Jennifer S.; Seeley, William W.; Kramer, Joel H.; Miller, Bruce L.; Rankin, Katherine P.

    2013-01-01

    Emotional changes are common in mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Intrinsic connectivity imaging studies suggest that default mode network degradation in AD is accompanied by the release of an emotion-relevant salience network. We investigated whether emotional contagion, an evolutionarily conserved affect-sharing mechanism, is higher in MCI and AD secondary to biological alterations in neural networks that support emotion. We measured emotional contagion in 237 participants (111 healthy controls, 62 patients with MCI, and 64 patients with AD) with the Interpersonal Reactivity Index Personal Distress subscale. Depressive symptoms were evaluated with the Geriatric Depression Scale. Participants underwent structural MRI, and voxel-based morphometry was used to relate whole-brain maps to emotional contagion. Analyses of covariance found significantly higher emotional contagion at each stage of disease progression [controls < MCI (P < 0.01) and MCI < AD (P < 0.001)]. Depressive symptoms were also higher in patients compared with controls [controls < MCI (P < 0.01) and controls < AD (P < 0.0001)]. Higher emotional contagion (but not depressive symptoms) was associated with smaller volume in right inferior, middle, and superior temporal gyri (PFWE < 0.05); right temporal pole, anterior hippocampus, parahippocampal gyrus; and left middle temporal gyrus (all P < 0.001, uncorrected). These findings suggest that in MCI and AD, neurodegeneration of temporal lobe structures important for affective signal detection and emotion inhibition are associated with up-regulation of emotion-generating mechanisms. Emotional contagion, a quantifiable index of empathic reactivity that is present in other species, may be a useful tool with which to study emotional alterations in animal models of AD. PMID:23716653

  17. Relativistic dynamical collapse model

    NASA Astrophysics Data System (ADS)

    Pearle, Philip

    2015-05-01

    A model is discussed where all operators are constructed from a quantum scalar field whose energy spectrum takes on all real values. The Schrödinger picture wave function depends upon space and time coordinates for each particle, as well as an inexorably increasing evolution parameter s which labels a foliation of spacelike hypersurfaces. The model is constructed to be manifestly Lorentz invariant in the interaction picture. Free particle states and interactions are discussed in this framework. Then, the formalism of the continuous spontaneous localization (CSL) theory of dynamical collapse is applied. The collapse-generating operator is chosen to be the particle number space-time density. Unlike previous relativistically invariant models, the vacuum state is not excited. The collapse dynamics depends upon two parameters, a parameter Λ which represents the collapse rate/volume and a scale factor ℓ. A common example of collapse dynamics, involving a clump of matter in a superposition of two locations, is analyzed. The collapse rate is shown to be identical to that of nonrelativistic CSL when the GRW-CSL choice of ℓ=a =1 0-5 cm , is made, along with Λ =λ /a3 (GRW-CSL choice λ =1 0-16s-1). The collapse rate is also satisfactory with the choice ℓ as the size of the Universe, with Λ =λ /ℓa2. Because the collapse narrows wave functions in space and time, it increases a particle's momentum and energy, altering its mass. It is shown that, with ℓ=a , the change of mass of a nucleon is unacceptably large but, when ℓ is the size of the Universe, the change of mass over the age of the Universe is acceptably small.

  18. Homophily and Contagion Are Generically Confounded in Observational Social Network Studies

    PubMed Central

    Shalizi, Cosma Rohilla; Thomas, Andrew C.

    2012-01-01

    The authors consider processes on social networks that can potentially involve three factors: homophily, or the formation of social ties due to matching individual traits; social contagion, also known as social influence; and the causal effect of an individual’s covariates on his or her behavior or other measurable responses. The authors show that generically, all of these are confounded with each other. Distinguishing them from one another requires strong assumptions on the parametrization of the social process or on the adequacy of the covariates used (or both). In particular the authors demonstrate, with simple examples, that asymmetries in regression coefficients cannot identify causal effects and that very simple models of imitation (a form of social contagion) can produce substantial correlations between an individual’s enduring traits and his or her choices, even when there is no intrinsic affinity between them. The authors also suggest some possible constructive responses to these results. PMID:22523436

  19. Constructing a complex of contagion: the perceptions of AIDS among working prostitutes in Costa Rica.

    PubMed

    Downe, P J

    1997-05-01

    This paper explores the perceptions of HIV/AIDS held by a group of women working as prostitutes in San José, Costa Rica. Adopting the theoretical perspective of critical medical anthropology, the analysis of the prostitutes' constructions of HIV/AIDS is linked to the political and historical context of power that constitutes a medical cultural hegemony. The way in which the research participants associate threats of HIV/AIDS with violence to create a complex of contagion that both perpetuates and challenges the hegemonic model of disease is discussed. Specifically, biomedicine's designation of the prostitute as the "vector" of disease is contrasted with the position that the prostitutes create for themselves. Through a critical analysis of this complex of contagion, oppressive power structures come into sharp focus.

  20. Efficient immunization strategies to prevent financial contagion

    NASA Astrophysics Data System (ADS)

    Kobayashi, Teruyoshi; Hasui, Kohei

    2014-01-01

    Many immunization strategies have been proposed to prevent infectious viruses from spreading through a network. In this work, we study efficient immunization strategies to prevent a default contagion that might occur in a financial network. An essential difference from the previous studies on immunization strategy is that we take into account the possibility of serious side effects. Uniform immunization refers to a situation in which banks are ``vaccinated'' with a common low-risk asset. The riskiness of immunized banks will decrease significantly, but the level of systemic risk may increase due to the de-diversification effect. To overcome this side effect, we propose another immunization strategy, called counteractive immunization, which prevents pairs of banks from failing simultaneously. We find that counteractive immunization can efficiently reduce systemic risk without altering the riskiness of individual banks.

  1. Efficient immunization strategies to prevent financial contagion

    PubMed Central

    Kobayashi, Teruyoshi; Hasui, Kohei

    2014-01-01

    Many immunization strategies have been proposed to prevent infectious viruses from spreading through a network. In this work, we study efficient immunization strategies to prevent a default contagion that might occur in a financial network. An essential difference from the previous studies on immunization strategy is that we take into account the possibility of serious side effects. Uniform immunization refers to a situation in which banks are “vaccinated” with a common low-risk asset. The riskiness of immunized banks will decrease significantly, but the level of systemic risk may increase due to the de-diversification effect. To overcome this side effect, we propose another immunization strategy, called counteractive immunization, which prevents pairs of banks from failing simultaneously. We find that counteractive immunization can efficiently reduce systemic risk without altering the riskiness of individual banks. PMID:24452277

  2. Efficient immunization strategies to prevent financial contagion.

    PubMed

    Kobayashi, Teruyoshi; Hasui, Kohei

    2014-01-23

    Many immunization strategies have been proposed to prevent infectious viruses from spreading through a network. In this work, we study efficient immunization strategies to prevent a default contagion that might occur in a financial network. An essential difference from the previous studies on immunization strategy is that we take into account the possibility of serious side effects. Uniform immunization refers to a situation in which banks are "vaccinated" with a common low-risk asset. The riskiness of immunized banks will decrease significantly, but the level of systemic risk may increase due to the de-diversification effect. To overcome this side effect, we propose another immunization strategy, called counteractive immunization, which prevents pairs of banks from failing simultaneously. We find that counteractive immunization can efficiently reduce systemic risk without altering the riskiness of individual banks.

  3. Sensitivity analysis for contagion effects in social networks

    PubMed Central

    VanderWeele, Tyler J.

    2014-01-01

    Analyses of social network data have suggested that obesity, smoking, happiness and loneliness all travel through social networks. Individuals exert “contagion effects” on one another through social ties and association. These analyses have come under critique because of the possibility that homophily from unmeasured factors may explain these statistical associations and because similar findings can be obtained when the same methodology is applied to height, acne and head-aches, for which the conclusion of contagion effects seems somewhat less plausible. We use sensitivity analysis techniques to assess the extent to which supposed contagion effects for obesity, smoking, happiness and loneliness might be explained away by homophily or confounding and the extent to which the critique using analysis of data on height, acne and head-aches is relevant. Sensitivity analyses suggest that contagion effects for obesity and smoking cessation are reasonably robust to possible latent homophily or environmental confounding; those for happiness and loneliness are somewhat less so. Supposed effects for height, acne and head-aches are all easily explained away by latent homophily and confounding. The methodology that has been employed in past studies for contagion effects in social networks, when used in conjunction with sensitivity analysis, may prove useful in establishing social influence for various behaviors and states. The sensitivity analysis approach can be used to address the critique of latent homophily as a possible explanation of associations interpreted as contagion effects. PMID:25580037

  4. Social contagion of mental health: Evidence from college roommates

    PubMed Central

    Golberstein, Ezra; Whitlock, Janis L.; Downs, Marilyn F.

    2015-01-01

    From a policy standpoint the spread of health conditions in social networks is important to quantify, because it implies externalities and possible market failures in the consumption of health interventions. Recent studies conclude that happiness and depression may be highly contagious across social ties. The results may be biased, however, due to selection and common shocks. We provide unbiased estimates by using exogenous variation from college roommate assignments. Our findings are consistent with no significant overall contagion of mental health and no more than small contagion effects for specific mental health measures, with no evidence for happiness contagion and modest evidence for anxiety and depression contagion. The weakness of the contagion effects cannot be explained by avoidance of roommates with poor mental health or by generally low social contact among roommates. We also find that similarity of baseline mental health predicts the closeness of roommate relationships, which highlights the potential for selection biases in studies of peer effects that do not have a clearly exogenous source of variation. Overall our results suggest that mental health contagion is lower, or at least more context-specific, than implied by the recent studies in the medical literature. PMID:23055446

  5. Social contagion of mental health: evidence from college roommates.

    PubMed

    Eisenberg, Daniel; Golberstein, Ezra; Whitlock, Janis L; Downs, Marilyn F

    2013-08-01

    From a policy standpoint, the spread of health conditions in social networks is important to quantify, because it implies externalities and possible market failures in the consumption of health interventions. Recent studies conclude that happiness and depression may be highly contagious across social ties. The results may be biased, however, because of selection and common shocks. We provide unbiased estimates by using exogenous variation from college roommate assignments. Our findings are consistent with no significant overall contagion of mental health and no more than small contagion effects for specific mental health measures, with no evidence for happiness contagion and modest evidence for anxiety and depression contagion. The weakness of the contagion effects cannot be explained by avoidance of roommates with poor mental health or by generally low social contact among roommates. We also find that similarity of baseline mental health predicts the closeness of roommate relationships, which highlights the potential for selection biases in studies of peer effects that do not have a clearly exogenous source of variation. Overall, our results suggest that mental health contagion is lower, or at least more context specific, than implied by the recent studies in the medical literature. Copyright © 2012 John Wiley & Sons, Ltd.

  6. Motor contagion in young children: Exploring social influences on perception-action coupling.

    PubMed

    Marshall, Peter J; Bouquet, Cédric A; Thomas, Amanda L; Shipley, Thomas F

    2010-01-01

    Human development occurs in a social environment in which learning is tightly coupled to the behavior of other supportive humans. One aspect of this coupling may occur through motor contagion, in which observing the actions of other people is associated with the activation of related motor representations. In order to explore the overlap between action observation and action execution in early childhood, a novel task was developed in which 4-year-old children were instructed to move a stylus on a graphics tablet in the presence of a background video which showed a model moving her arm in a direction that was either congruent or incongruent with the instructed axis of the child's stylus movements. The presence of incongruent background movements was associated with a significant interference effect on children's stylus movements. This interference effect was stronger when the background movements were performed by a same-age peer rather than by an adult. It is suggested that early childhood is a particularly interesting age period to study motor contagion, since the transition from infancy to childhood involves concurrent changes in cognitive control and in the ability to flexibly decouple perception and action. The examination of motor contagion provides an important consideration of social influences on cognitive control in early childhood--influences that have been somewhat neglected in the developmental literature on the related construct of executive functioning.

  7. Chimpanzees Show a Developmental Increase in Susceptibility to Contagious Yawning: A Test of the Effect of Ontogeny and Emotional Closeness on Yawn Contagion

    PubMed Central

    Madsen, Elainie Alenkær; Persson, Tomas; Sayehli, Susan; Lenninger, Sara; Sonesson, Göran

    2013-01-01

    Contagious yawning has been reported for humans, dogs and several non-human primate species, and associated with empathy in humans and other primates. Still, the function, development and underlying mechanisms of contagious yawning remain unclear. Humans and dogs show a developmental increase in susceptibility to yawn contagion, with children showing an increase around the age of four, when also empathy-related behaviours and accurate identification of others’ emotions begin to clearly evince. Explicit tests of yawn contagion in non-human apes have only involved adult individuals and examined the existence of conspecific yawn contagion. Here we report the first study of heterospecific contagious yawning in primates, and the ontogeny of susceptibility thereto in chimpanzees, Pan troglodytes verus. We examined whether emotional closeness, defined as attachment history with the yawning model, affected the strength of contagion, and compared the contagiousness of yawning to nose-wiping. Thirty-three orphaned chimpanzees observed an unfamiliar and familiar human (their surrogate human mother) yawn, gape and nose-wipe. Yawning, but not nose-wiping, was contagious for juvenile chimpanzees, while infants were immune to contagion. Like humans and dogs, chimpanzees are subject to a developmental trend in susceptibility to contagious yawning, and respond to heterospecific yawn stimuli. Emotional closeness with the model did not affect contagion. The familiarity-biased social modulatory effect on yawn contagion previously found among some adult primates, seem to only emerge later in development, or be limited to interactions with conspecifics. The influence of the ‘chameleon effect’, targeted vs. generalised empathy, perspective-taking and visual attention on contagious yawning is discussed. PMID:24146848

  8. Chimpanzees show a developmental increase in susceptibility to contagious yawning: a test of the effect of ontogeny and emotional closeness on yawn contagion.

    PubMed

    Madsen, Elainie Alenkær; Persson, Tomas; Sayehli, Susan; Lenninger, Sara; Sonesson, Göran

    2013-01-01

    Contagious yawning has been reported for humans, dogs and several non-human primate species, and associated with empathy in humans and other primates. Still, the function, development and underlying mechanisms of contagious yawning remain unclear. Humans and dogs show a developmental increase in susceptibility to yawn contagion, with children showing an increase around the age of four, when also empathy-related behaviours and accurate identification of others' emotions begin to clearly evince. Explicit tests of yawn contagion in non-human apes have only involved adult individuals and examined the existence of conspecific yawn contagion. Here we report the first study of heterospecific contagious yawning in primates, and the ontogeny of susceptibility thereto in chimpanzees, Pan troglodytes verus. We examined whether emotional closeness, defined as attachment history with the yawning model, affected the strength of contagion, and compared the contagiousness of yawning to nose-wiping. Thirty-three orphaned chimpanzees observed an unfamiliar and familiar human (their surrogate human mother) yawn, gape and nose-wipe. Yawning, but not nose-wiping, was contagious for juvenile chimpanzees, while infants were immune to contagion. Like humans and dogs, chimpanzees are subject to a developmental trend in susceptibility to contagious yawning, and respond to heterospecific yawn stimuli. Emotional closeness with the model did not affect contagion. The familiarity-biased social modulatory effect on yawn contagion previously found among some adult primates, seem to only emerge later in development, or be limited to interactions with conspecifics. The influence of the 'chameleon effect', targeted vs. generalised empathy, perspective-taking and visual attention on contagious yawning is discussed.

  9. Natural ventilation for the prevention of airborne contagion.

    PubMed

    Escombe, A Roderick; Oeser, Clarissa C; Gilman, Robert H; Navincopa, Marcos; Ticona, Eduardo; Pan, William; Martínez, Carlos; Chacaltana, Jesus; Rodríguez, Richard; Moore, David A J; Friedland, Jon S; Evans, Carlton A

    2007-02-01

    Institutional transmission of airborne infections such as tuberculosis (TB) is an important public health problem, especially in resource-limited settings where protective measures such as negative-pressure isolation rooms are difficult to implement. Natural ventilation may offer a low-cost alternative. Our objective was to investigate the rates, determinants, and effects of natural ventilation in health care settings. The study was carried out in eight hospitals in Lima, Peru; five were hospitals of "old-fashioned" design built pre-1950, and three of "modern" design, built 1970-1990. In these hospitals 70 naturally ventilated clinical rooms where infectious patients are likely to be encountered were studied. These included respiratory isolation rooms, TB wards, respiratory wards, general medical wards, outpatient consulting rooms, waiting rooms, and emergency departments. These rooms were compared with 12 mechanically ventilated negative-pressure respiratory isolation rooms built post-2000. Ventilation was measured using a carbon dioxide tracer gas technique in 368 experiments. Architectural and environmental variables were measured. For each experiment, infection risk was estimated for TB exposure using the Wells-Riley model of airborne infection. We found that opening windows and doors provided median ventilation of 28 air changes/hour (ACH), more than double that of mechanically ventilated negative-pressure rooms ventilated at the 12 ACH recommended for high-risk areas, and 18 times that with windows and doors closed (p < 0.001). Facilities built more than 50 years ago, characterised by large windows and high ceilings, had greater ventilation than modern naturally ventilated rooms (40 versus 17 ACH; p < 0.001). Even within the lowest quartile of wind speeds, natural ventilation exceeded mechanical (p < 0.001). The Wells-Riley airborne infection model predicted that in mechanically ventilated rooms 39% of susceptible individuals would become infected following

  10. Self-Organized Criticality in a Model of Collective Bank Bankruptcies

    NASA Astrophysics Data System (ADS)

    Aleksiejuk, Agata; HoŁyst, Janusz A.; Kossinets, Gueorgi

    The question we address here is of whether phenomena of collective bankruptcies are related to self-organized criticality. In order to answer it we propose a simple model of banking networks based on the random directed percolation. We study effects of one bank failure on the nucleation of contagion phase in a financial market. We recognize the power law distribution of contagion sizes in 3d- and 4d-networks as an indicator of SOC behavior. The SOC dynamics was not detected in 2d-lattices. The difference between 2d- and 3d- or 4d-systems is explained due to the percolation theory.

  11. A framework for analyzing contagion in assortative banking networks.

    PubMed

    Hurd, Thomas R; Gleeson, James P; Melnik, Sergey

    2017-01-01

    We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections between banks, whereas our framework explicitly allows for (dis)assortative edge probabilities (i.e., a tendency for small banks to link to large banks). We analyze default cascades triggered by shocking the network and find that the cascade can be understood as an explicit iterated mapping on a set of edge probabilities that converges to a fixed point. We derive a cascade condition, analogous to the basic reproduction number R0 in epidemic modelling, that characterizes whether or not a single initially defaulted bank can trigger a cascade that extends to a finite fraction of the infinite network. This cascade condition is an easily computed measure of the systemic risk inherent in a given banking network topology. We use percolation theory for random networks to derive a formula for the frequency of global cascades. These analytical results are shown to provide limited quantitative agreement with Monte Carlo simulation studies of finite-sized networks. We show that edge-assortativity, the propensity of nodes to connect to similar nodes, can have a strong effect on the level of systemic risk as measured by the cascade condition. However, the effect of assortativity on systemic risk is subtle, and we propose a simple graph theoretic quantity, which we call the graph-assortativity coefficient, that can be used to assess systemic risk.

  12. A framework for analyzing contagion in assortative banking networks

    PubMed Central

    Hurd, Thomas R.; Gleeson, James P.; Melnik, Sergey

    2017-01-01

    We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections between banks, whereas our framework explicitly allows for (dis)assortative edge probabilities (i.e., a tendency for small banks to link to large banks). We analyze default cascades triggered by shocking the network and find that the cascade can be understood as an explicit iterated mapping on a set of edge probabilities that converges to a fixed point. We derive a cascade condition, analogous to the basic reproduction number R0 in epidemic modelling, that characterizes whether or not a single initially defaulted bank can trigger a cascade that extends to a finite fraction of the infinite network. This cascade condition is an easily computed measure of the systemic risk inherent in a given banking network topology. We use percolation theory for random networks to derive a formula for the frequency of global cascades. These analytical results are shown to provide limited quantitative agreement with Monte Carlo simulation studies of finite-sized networks. We show that edge-assortativity, the propensity of nodes to connect to similar nodes, can have a strong effect on the level of systemic risk as measured by the cascade condition. However, the effect of assortativity on systemic risk is subtle, and we propose a simple graph theoretic quantity, which we call the graph-assortativity coefficient, that can be used to assess systemic risk. PMID:28231324

  13. [The contagion of adolescent suicide: cultural, ethical and psychosocial aspects].

    PubMed

    Gérard, N; Delvenne, V; Nicolis, H

    2012-01-01

    Suicide is the second leading cause of death among adolescents. The risk factors are many and varied. The contagion of suicide was raised as a potential cause of youth suicide. In support of this argument, we did a review of the literature on the possible contagion of adolescent suicide. Several types of situations can support this hypothesis : when a youth is faced with the suicide of a relative or close friend, when he lived in a community, through the media or via the Internet. The way suicide is reported in the press shows a correlation with increased incidence of suicide among adolescents. In summary, there is evidence increasingly obvious that the contagion is the source of some youth suicides. For this reason, it seems important that preventive measures are in place. However, although this mechanism has been instrumental in initiating the act, it is important to note that suicide is always the result of several factors including the personal history of the subject.

  14. Human eyes with dilated pupils induce pupillary contagion in infants.

    PubMed

    Fawcett, Christine; Arslan, Melda; Falck-Ytter, Terje; Roeyers, Herbert; Gredebäck, Gustaf

    2017-08-29

    Being sensitive and responsive to others' internal states is critical for social life. One reliable cue to what others might be feeling is pupil dilation because it is linked to increases in arousal. When adults view an individual with dilated pupils, their pupils dilate in response, suggesting not only sensitivity to pupil size, but a corresponding response as well. However, little is known about the origins or mechanism underlying this phenomenon of pupillary contagion. Here we show that 4- to 6-month-old infants show pupillary contagion when viewing photographs of eyes with varying pupil sizes: their pupils dilate in response to others' large, but not small or medium pupils. The results suggest that pupillary contagion is likely driven by a transfer of arousal and that it is present very early in life in human infants, supporting the view that it could be an adaptation fundamental for social and emotional development.

  15. Launch Vehicle Dynamics Demonstrator Model

    NASA Technical Reports Server (NTRS)

    1963-01-01

    Launch Vehicle Dynamics Demonstrator Model. The effect of vibration on launch vehicle dynamics was studied. Conditions included three modes of instability. The film includes close up views of the simulator fuel tank with and without stability control. [Entire movie available on DVD from CASI as Doc ID 20070030984. Contact help@sti.nasa.gov

  16. Generative models of conformational dynamics.

    PubMed

    Langmead, Christopher James

    2014-01-01

    Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term 'generative' refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GRAPHICAL MODELS OF ENERGY LANDSCAPES), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc.) from long timescale simulation data.

  17. SSME structural dynamic model development

    NASA Technical Reports Server (NTRS)

    Foley, M. J.; Tilley, D. M.; Welch, C. T.

    1983-01-01

    A mathematical model of the Space Shuttle Main Engine (SSME) as a complete assembly, with detailed emphasis on LOX and High Fuel Turbopumps is developed. The advantages of both complete engine dynamics, and high fidelity modeling are incorporated. Development of this model, some results, and projected applications are discussed.

  18. Predictive models of forest dynamics.

    PubMed

    Purves, Drew; Pacala, Stephen

    2008-06-13

    Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.

  19. Dynamic Modeling of ALS Systems

    NASA Technical Reports Server (NTRS)

    Jones, Harry

    2002-01-01

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

  20. COLD-SAT dynamic model

    NASA Technical Reports Server (NTRS)

    Adams, Neil S.; Bollenbacher, Gary

    1992-01-01

    This report discusses the development and underlying mathematics of a rigid-body computer model of a proposed cryogenic on-orbit liquid depot storage, acquisition, and transfer spacecraft (COLD-SAT). This model, referred to in this report as the COLD-SAT dynamic model, consists of both a trajectory model and an attitudinal model. All disturbance forces and torques expected to be significant for the actual COLD-SAT spacecraft are modeled to the required degree of accuracy. Control and experimental thrusters are modeled, as well as fluid slosh. The model also computes microgravity disturbance accelerations at any specified point in the spacecraft. The model was developed by using the Boeing EASY5 dynamic analysis package and will run on Apollo, Cray, and other computing platforms.

  1. Aircraft Dynamic Modeling in Turbulence

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.; Cunninham, Kevin

    2012-01-01

    A method for accurately identifying aircraft dynamic models in turbulence was developed and demonstrated. The method uses orthogonal optimized multisine excitation inputs and an analytic method for enhancing signal-to-noise ratio for dynamic modeling in turbulence. A turbulence metric was developed to accurately characterize the turbulence level using flight measurements. The modeling technique was demonstrated in simulation, then applied to a subscale twin-engine jet transport aircraft in flight. Comparisons of modeling results obtained in turbulent air to results obtained in smooth air were used to demonstrate the effectiveness of the approach.

  2. Model describes subsea control dynamics

    SciTech Connect

    Not Available

    1988-02-01

    A mathematical model of the hydraulic control systems for subsea completions and their umbilicals has been developed and applied successfully to Jabiru and Challis field production projects in the Timor Sea. The model overcomes the limitations of conventional linear steady state models and yields for the hydraulic system an accurate description of its dynamic response, including the valve shut-in times and the pressure transients. Results of numerical simulations based on the model are in good agreement with measurements of the dynamic response of the tree valves and umbilicals made during land testing.

  3. Dynamic Eye Model.

    ERIC Educational Resources Information Center

    Journal of Science and Mathematics Education in Southeast Asia, 1981

    1981-01-01

    Instructions (with diagrams and parts list) are provided for constructing an eye model with a pliable lens made from a plastic bottle which can vary its convexity to accommodate changing positions of an object being viewed. Also discusses concepts which the model can assist in developing. (Author/SK)

  4. Examination of Negative Peer Contagion in a Residential Care Setting

    ERIC Educational Resources Information Center

    Huefner, Jonathan C.; Ringle, Jay L.

    2012-01-01

    There has been ongoing concern about the negative impact of residential treatment on youth in care. Research examining the impact of negative peer influence in juvenile justice, education, and residential care settings is reviewed. A study was conducted to examine the impact of negative peer contagion on the level of problem behavior in a…

  5. Emotional Contagion at Work: An In-Class Experiential Activity

    ERIC Educational Resources Information Center

    Schaefer, Rebecca A. Bull; Palanski, Michael E.

    2014-01-01

    This article describes an in-class exercise designed to demonstrate the concept of emotional contagion. Empirical research has found that leader emotional displays at work relate to various member work attitudes and performance. However, students may have a difficult time understanding how and why emotions can influence organizational outcomes.…

  6. Contagion and Repeat Offending among Urban Juvenile Delinquents

    ERIC Educational Resources Information Center

    Mennis, Jeremy; Harris, Philip

    2011-01-01

    This research investigates the role of repeat offending and spatial contagion in juvenile delinquency recidivism using a database of 7166 male juvenile offenders sent to community-based programs by the Family Court of Philadelphia. Results indicate evidence of repeat offending among juvenile delinquents, particularly for drug offenders. The…

  7. The Evolution of Epidemic Suicide on Guam: Context and Contagion

    ERIC Educational Resources Information Center

    Booth, Heather

    2010-01-01

    Thirty years of suicide rates for Guam were analyzed by age, sex, period, and cohort. Youth suicide increased rapidly in the 1990s; certain cohorts have higher rates. Four explanatory factors are discussed, including ecological factors and migration from the Federated States of Micronesia. Direct and indirect suicide contagion followed the death…

  8. The Evolution of Epidemic Suicide on Guam: Context and Contagion

    ERIC Educational Resources Information Center

    Booth, Heather

    2010-01-01

    Thirty years of suicide rates for Guam were analyzed by age, sex, period, and cohort. Youth suicide increased rapidly in the 1990s; certain cohorts have higher rates. Four explanatory factors are discussed, including ecological factors and migration from the Federated States of Micronesia. Direct and indirect suicide contagion followed the death…

  9. Peer Contagion and Adolescent Depression: The Role of Failure Anticipation

    ERIC Educational Resources Information Center

    van Zalk, Maarten Herman Walter; Kerr, Margaret; Branje, Susan J. T.; Stattin, Hakan; Meeus, Wim H. J.

    2010-01-01

    The current study investigated the mechanisms underlying peer contagion of depressive symptoms in adolescence. Five annual measurements of data were gathered from a large (N = 842) community-based network of adolescents (M = 14.3 years at first measurement). Results showed that, after controlling for selection and deselection of friends on the…

  10. Contagion and Repeat Offending among Urban Juvenile Delinquents

    ERIC Educational Resources Information Center

    Mennis, Jeremy; Harris, Philip

    2011-01-01

    This research investigates the role of repeat offending and spatial contagion in juvenile delinquency recidivism using a database of 7166 male juvenile offenders sent to community-based programs by the Family Court of Philadelphia. Results indicate evidence of repeat offending among juvenile delinquents, particularly for drug offenders. The…

  11. Modeling Molecular Dynamics from Simulations

    SciTech Connect

    Hinrichs, Nina Singhal

    2009-01-28

    Many important processes in biology occur at the molecular scale. A detailed understanding of these processes can lead to significant advances in the medical and life sciences. For example, many diseases are caused by protein aggregation or misfolding. One approach to studying these systems is to use physically-based computational simulations to model the interactions and movement of the molecules. While molecular simulations are computationally expensive, it is now possible to simulate many independent molecular dynamics trajectories in a parallel fashion by using super- or distributed- computing methods such as Folding@Home or Blue Gene. The analysis of these large, high-dimensional data sets presents new computational challenges. In this seminar, I will discuss a novel approach to analyzing large ensembles of molecular dynamics trajectories to generate a compact model of the dynamics. This model groups conformations into discrete states and describes the dynamics as Markovian, or history-independent, transitions between the states. I will discuss why the Markovian state model (MSM) is suitable for macromolecular dynamics, and how it can be used to answer many interesting and relevant questions about the molecular system. I will also discuss many of the computational and statistical challenges in building such a model, such as how to appropriately cluster conformations, determine the statistical reliability, and efficiently design new simulations.

  12. Flapping Wing Flight Dynamic Modeling

    DTIC Science & Technology

    2011-08-22

    against those of Theodorsen [16], Garrick [17], Loewy [18], Issacs [19, 20], Greenberg [21], Wagner [22], and von Karman [23] as well as experimental...kinematics and this data was used to generate the nal equations of motion (added to the nonlinear equations already derived from the Newton -Euler...wings). The ight dynamic model is a six-degree-of-freedom set of dynamic equations ( Newton -Euler scheme) with translation described in the inertial

  13. Model of THz Magnetization Dynamics

    PubMed Central

    Bocklage, Lars

    2016-01-01

    Magnetization dynamics can be coherently controlled by THz laser excitation, which can be applied in ultrafast magnetization control and switching. Here, transient magnetization dynamics are calculated for excitation with THz magnetic field pulses. We use the ansatz of Smit and Beljers, to formulate dynamic properties of the magnetization via partial derivatives of the samples free energy density, and extend it to solve the Landau-Lifshitz-equation to obtain the THz transients of the magnetization. The model is used to determine the magnetization response to ultrafast multi- and single-cycle THz pulses. Control of the magnetization trajectory by utilizing the THz pulse shape and polarization is demonstrated. PMID:26956997

  14. Structural dynamics system model reduction

    NASA Technical Reports Server (NTRS)

    Chen, J. C.; Rose, T. L.; Wada, B. K.

    1987-01-01

    Loads analysis for structural dynamic systems is usually performed by finite element models. Because of the complexity of the structural system, the model contains large number of degree-of-freedom. The large model is necessary since details of the stress, loads and responses due to mission environments are computed. However, a simplified model is needed for other tasks such as pre-test analysis for modal testing, and control-structural interaction studies. A systematic method of model reduction for modal test analysis is presented. Perhaps it will be of some help in developing a simplified model for the control studies.

  15. Statistical fluctuations in pedestrian evacuation times and the effect of social contagion

    NASA Astrophysics Data System (ADS)

    Nicolas, Alexandre; Bouzat, Sebastián; Kuperman, Marcelo N.

    2016-08-01

    Mathematical models of pedestrian evacuation and the associated simulation software have become essential tools for the assessment of the safety of public facilities and buildings. While a variety of models is now available, their calibration and test against empirical data are generally restricted to global averaged quantities; the statistics compiled from the time series of individual escapes ("microscopic" statistics) measured in recent experiments are thus overlooked. In the same spirit, much research has primarily focused on the average global evacuation time, whereas the whole distribution of evacuation times over some set of realizations should matter. In the present paper we propose and discuss the validity of a simple relation between this distribution and the microscopic statistics, which is theoretically valid in the absence of correlations. To this purpose, we develop a minimal cellular automaton, with features that afford a semiquantitative reproduction of the experimental microscopic statistics. We then introduce a process of social contagion of impatient behavior in the model and show that the simple relation under test may dramatically fail at high contagion strengths, the latter being responsible for the emergence of strong correlations in the system. We conclude with comments on the potential practical relevance for safety science of calculations based on microscopic statistics.

  16. Global/Local Dynamic Models

    SciTech Connect

    Pfeffer, A; Das, S; Lawless, D; Ng, B

    2006-10-10

    Many dynamic systems involve a number of entities that are largely independent of each other but interact with each other via a subset of state variables. We present global/local dynamic models (GLDMs) to capture these kinds of systems. In a GLDM, the state of an entity is decomposed into a globally influenced state that depends on other entities, and a locally influenced state that depends only on the entity itself. We present an inference algorithm for GLDMs called global/local particle filtering, that introduces the principle of reasoning globally about global dynamics and locally about local dynamics. We have applied GLDMs to an asymmetric urban warfare environment, in which enemy units form teams to attack important targets, and the task is to detect such teams as they form. Experimental results for this application show that global/local particle filtering outperforms ordinary particle filtering and factored particle filtering.

  17. Co-Rumination Mediates Contagion of Internalizing Symptoms within Youths’ Friendships

    PubMed Central

    Schwartz-Mette, Rebecca A.; Rose, Amanda J.

    2012-01-01

    Peer contagion of internalizing symptoms was examined within youths’ friendships over six months. Children (grades 3 and 5) and adolescents (grades 7 and 9) paired in 274 reciprocal same-sex friendship dyads completed measures of depressive and anxiety symptoms, co-rumination, and self-disclosure. Depression contagion was present for all youth, and anxiety contagion was found in the sample of girls and older boys. Although normative self-disclosure did not mediate the contagion effects, co-rumination mediated the depression contagion effect for adolescents and the anxiety contagion effect in the sample of girls and older boys. Implications for interventions with youth at risk for developing internalizing symptoms are discussed. PMID:22369336

  18. Dynamical models and Galaxy surveys

    NASA Astrophysics Data System (ADS)

    Binney, James; Sanders, Jason L.

    2014-01-01

    Equilibrium dynamical models are essential tools for extracting science from surveys of our Galaxy. We show how models can be tested with data from a survey before the survey's selection function has been determined. We illustrate the application of this method by presenting some results for the RAVE survey. We extend our published analytic distribution functions to include chemistry and fit the chosen functional form to a combination of the Geneva-Copenhagen survey (GCS) and a sample of G-dwarfs observed at z ~ 1.75 kpc by the SEGUE survey. By including solid dynamics we are able to predict the contribution that the thick disc/halo stars surveyed by SEGUE should make to the GCS survey. We show that the measured [Fe/H] distribution from the GCS includes many fewer stars at [Fe/H] < -0.6 than are predicted. The problem is more likely to lie in discordant abundance scales than with incorrect dynamics.

  19. Generative Models of Conformational Dynamics

    PubMed Central

    Langmead, Christopher James

    2014-01-01

    Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GrAphical Models of Energy LANdscapes), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc) from long timescale simulation data. PMID:24446358

  20. The dynamics of coastal models

    USGS Publications Warehouse

    Hearn, Clifford J.

    2008-01-01

    Coastal basins are defined as estuaries, lagoons, and embayments. This book deals with the science of coastal basins using simple models, many of which are presented in either analytical form or Microsoft Excel or MATLAB. The book introduces simple hydrodynamics and its applications, from the use of simple box and one-dimensional models to flow over coral reefs. The book also emphasizes models as a scientific tool in our understanding of coasts, and introduces the value of the most modern flexible mesh combined wave-current models. Examples from shallow basins around the world illustrate the wonders of the scientific method and the power of simple dynamics. This book is ideal for use as an advanced textbook for graduate students and as an introduction to the topic for researchers, especially those from other fields of science needing a basic understanding of the basic ideas of the dynamics of coastal basins.

  1. Observability in dynamic evolutionary models.

    PubMed

    López, I; Gámez, M; Carreño, R

    2004-02-01

    In the paper observability problems are considered in basic dynamic evolutionary models for sexual and asexual populations. Observability means that from the (partial) knowledge of certain phenotypic characteristics the whole evolutionary process can be uniquely recovered. Sufficient conditions are given to guarantee observability for both sexual and asexual populations near an evolutionarily stable state.

  2. Predictive models of battle dynamics

    NASA Astrophysics Data System (ADS)

    Jelinek, Jan

    2001-09-01

    The application of control and game theories to improve battle planning and execution requires models, which allow military strategists and commanders to reliably predict the expected outcomes of various alternatives over a long horizon into the future. We have developed probabilistic battle dynamics models, whose building blocks in the form of Markov chains are derived from the first principles, and applied them successfully in the design of the Model Predictive Task Commander package. This paper introduces basic concepts of our modeling approach and explains the probability distributions needed to compute the transition probabilities of the Markov chains.

  3. Stochastic Model of Microtubule Dynamics

    NASA Astrophysics Data System (ADS)

    Hryniv, Ostap; Martínez Esteban, Antonio

    2017-10-01

    We introduce a continuous time stochastic process on strings made of two types of particle, whose dynamics mimics that of microtubules in a living cell. The long term behaviour of the system is described in terms of the velocity v of the string end. We show that v is an analytic function of its parameters and study its monotonicity properties. We give a complete characterisation of the phase diagram of the model and derive several criteria of the growth (v>0) and the shrinking (v<0) regimes of the dynamics.

  4. Dynamical Modelling of Meteoroid Streams

    NASA Astrophysics Data System (ADS)

    Clark, David; Wiegert, P. A.

    2012-10-01

    Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required questionable assumptions and significant simplifications. Extending on the approach of Vaubaillon et al. (2005)1, we model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of frequency based on model parameter changes. To assist in model analysis we are developing interactive software to permit the “turning of knobs” of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. With this tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform cometary surface attributes and temporal activity. The software uses a single model definition and implementation throughout model verification, sample particle bin generation and integration, and analysis. It supports the adjustment with feedback of both independent and independent model values, with the intent of providing an interface supporting multivariate analysis. Propagations of measurement uncertainties and model parameter precisions are tracked rigorously throughout. We maintain a separation of the model itself from the abstract concepts of model definition, parameter manipulation, and real-time analysis and visualization. Therefore we are able to quickly adapt to fundamental model changes. It is hoped the tool will also be of use in other solar system dynamics problems. 1 Vaubaillon, J.; Colas, F.; Jorda, L. (2005) A new method to predict meteor showers. I. Description of the model. Astronomy and

  5. Dynamic Model of Mesoscale Eddies

    NASA Astrophysics Data System (ADS)

    Dubovikov, Mikhail S.

    2003-04-01

    Oceanic mesoscale eddies which are analogs of well known synoptic eddies (cyclones and anticyclones), are studied on the basis of the turbulence model originated by Dubovikov (Dubovikov, M.S., "Dynamical model of turbulent eddies", Int. J. Mod. Phys.B7, 4631-4645 (1993).) and further developed by Canuto and Dubovikov (Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: I. General formalism", Phys. Fluids8, 571-586 (1996a) (CD96a); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: II. Sheardriven flows", Phys. Fluids8, 587-598 (1996b) (CD96b); Canuto, V.M., Dubovikov, M.S., Cheng, Y. and Dienstfrey, A., "A dynamical model for turbulence: III. Numerical results", Phys. Fluids8, 599-613 (1996c)(CD96c); Canuto, V.M., Dubovikov, M.S. and Dienstfrey, A., "A dynamical model for turbulence: IV. Buoyancy-driven flows", Phys. Fluids9, 2118-2131 (1997a) (CD97a); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: V. The effect of rotation", Phys. Fluids9, 2132-2140 (1997b) (CD97b); Canuto, V.M., Dubovikov, M.S. and Wielaard, D.J., "A dynamical model for turbulence: VI. Two dimensional turbulence", Phys. Fluids9, 2141-2147 (1997c) (CD97c); Canuto, V.M. and Dubovikov, M.S., "Physical regimes and dimensional structure of rotating turbulence", Phys. Rev. Lett. 78, 666-669 (1997d) (CD97d); Canuto, V.M., Dubovikov, M.S. and Dienstfrey, A., "Turbulent convection in a spectral model", Phys. Rev. Lett. 78, 662-665 (1997e) (CD97e); Canuto, V.M. and Dubovikov, M.S., "A new approach to turbulence", Int. J. Mod. Phys.12, 3121-3152 (1997f) (CD97f); Canuto, V.M. and Dubovikov, M.S., "Two scaling regimes for rotating Raleigh-Benard convection", Phys. Rev. Letters78, 281-284, (1998) (CD98); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: VII. The five invariants for shear driven flows", Phys. Fluids11, 659-664 (1999a) (CD99a); Canuto, V.M., Dubovikov, M.S. and Yu, G., "A dynamical model for turbulence: VIII. IR and UV

  6. Respiratory Protection Provided by Five New Contagion Masks

    PubMed Central

    Guyton, H. Gerald; Decker, Herbert M.

    1963-01-01

    The effectiveness of five recently developed contagion masks in filtering air-borne particles (1 to 5 μ diam) has been reported. One mask, available in four sizes, was 99% efficient. This mask can be reused after sterilization. The other four masks are available in only one size and are intended to be used one time only. Two of these four disposable types were more than 90% efficient but the variability of their respective test results was much greater than that for the reusable mask. The two remaining disposable types were less than 80% efficient. Two of these contagion-mask types were worn by hospital personnel for periods of up to 8 hr to determine the effect of such prolonged use on aerosol filtration efficiency. No significant decrease in filtration efficiency was noted. Physicians, nurses, and other hospital personnel who wear masks will benefit from the increased individual respiratory protection afforded by improved contagion masks. Concurrently, the incidence of hospital patient air-borne infections should be greatly reduced. Images FIG. 1 PMID:13951516

  7. Differences by degree: fatness, contagion and pre-emption.

    PubMed

    Brown, Tim

    2014-03-01

    Drawing on evidence from the Framingham Heart Study, Christakis and Fowler in their 2007 article published in the New England Journal of Medicine make the claim that obesity spreads in social networks. Whether they are correct in this assertion is neither the concern nor focus of this article. Rather, what is of interest is the subsequent mobilisation of 'contagion' to describe this spread and to account for the emergence of an 'obesity epidemic' in contemporary society. Contrary to the argument that there is less stigma attached to obesity, the reporting of the Christakis and Fowler article suggests that being 'fat' remains a signifier of moral and physical decay; if we add to this the suggestion that obesity is spread within social networks, it is possible that the stigma associated with body size will begin to mirror that which is attached to other infectious bodies. In order to consider the potential implications of this, the article develops in three directions: it explores the application of contagion as a metaphor for understanding the spread of obesity; it sets this understanding within the context of scholarship on contagion and it draws on critical obesity studies literature to call for a more cautionary approach to be taken when deploying a term that when combined with pre-emptive public health discourse would add significantly to the pathologising of the corpulent, fat or obese body.

  8. Rapid mimicry and emotional contagion in domestic dogs.

    PubMed

    Palagi, Elisabetta; Nicotra, Velia; Cordoni, Giada

    2015-12-01

    Emotional contagion is a basic form of empathy that makes individuals able to experience others' emotions. In human and non-human primates, emotional contagion can be linked to facial mimicry, an automatic and fast response (less than 1 s) in which individuals involuntary mimic others' expressions. Here, we tested whether body (play bow, PBOW) and facial (relaxed open-mouth, ROM) rapid mimicry is present in domestic dogs (Canis lupus familiaris) during dyadic intraspecific play. During their free playful interactions, dogs showed a stronger and rapid mimicry response (less than 1 s) after perceiving PBOW and ROM (two signals typical of play in dogs) than after perceiving JUMP and BITE (two play patterns resembling PBOW and ROM in motor performance). Playful sessions punctuated by rapid mimicry lasted longer that those sessions punctuated only by signals. Moreover, the distribution of rapid mimicry was strongly affected by the familiarity linking the subjects involved: the stronger the social bonding, the higher the level of rapid mimicry. In conclusion, our results demonstrate the presence of rapid mimicry in dogs, the involvement of mimicry in sharing playful motivation and the social modulation of the phenomenon. All these findings concur in supporting the idea that a possible linkage between rapid mimicry and emotional contagion (a building-block of empathy) exists in dogs.

  9. Rapid mimicry and emotional contagion in domestic dogs

    PubMed Central

    Palagi, Elisabetta; Nicotra, Velia; Cordoni, Giada

    2015-01-01

    Emotional contagion is a basic form of empathy that makes individuals able to experience others’ emotions. In human and non-human primates, emotional contagion can be linked to facial mimicry, an automatic and fast response (less than 1 s) in which individuals involuntary mimic others’ expressions. Here, we tested whether body (play bow, PBOW) and facial (relaxed open-mouth, ROM) rapid mimicry is present in domestic dogs (Canis lupus familiaris) during dyadic intraspecific play. During their free playful interactions, dogs showed a stronger and rapid mimicry response (less than 1 s) after perceiving PBOW and ROM (two signals typical of play in dogs) than after perceiving JUMP and BITE (two play patterns resembling PBOW and ROM in motor performance). Playful sessions punctuated by rapid mimicry lasted longer that those sessions punctuated only by signals. Moreover, the distribution of rapid mimicry was strongly affected by the familiarity linking the subjects involved: the stronger the social bonding, the higher the level of rapid mimicry. In conclusion, our results demonstrate the presence of rapid mimicry in dogs, the involvement of mimicry in sharing playful motivation and the social modulation of the phenomenon. All these findings concur in supporting the idea that a possible linkage between rapid mimicry and emotional contagion (a building-block of empathy) exists in dogs. PMID:27019737

  10. On whole Abelian model dynamics

    SciTech Connect

    Chauca, J.; Doria, R.

    2012-09-24

    Physics challenge is to determine the objects dynamics. However, there are two ways for deciphering the part. The first one is to search for the ultimate constituents; the second one is to understand its behaviour in whole terms. Therefore, the parts can be defined either from elementary constituents or as whole functions. Historically, science has been moving through the first aspect, however, quarks confinement and complexity are interrupting this usual approach. These relevant facts are supporting for a systemic vision be introduced. Our effort here is to study on the whole meaning through gauge theory. Consider a systemic dynamics oriented through the U(1) - systemic gauge parameter which function is to collect a fields set {l_brace}A{sub {mu}I}{r_brace}. Derive the corresponding whole gauge invariant Lagrangian, equations of motion, Bianchi identities, Noether relationships, charges and Ward-Takahashi equations. Whole Lorentz force and BRST symmetry are also studied. These expressions bring new interpretations further than the usual abelian model. They are generating a systemic system governed by 2N+ 10 classical equations plus Ward-Takahashi identities. A whole dynamics based on the notions of directive and circumstance is producing a set determinism where the parts dynamics are inserted in the whole evolution. A dynamics based on state, collective and individual equations with a systemic interdependence.

  11. Modeling wildfire incident complexity dynamics.

    PubMed

    Thompson, Matthew P

    2013-01-01

    Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management.

  12. Dynamical modelling of meteoroid streams

    NASA Astrophysics Data System (ADS)

    Clark, D. L.; Wiegert, P. A.

    2014-07-01

    Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required significant assumptions and simplifications. Extending on the approach of Vaubaillon et al. 2005, we model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of weights based on model parameter changes. To assist in model analysis we are developing interactive software to permit the "turning of knobs" of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. Using the tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform and time-variant cometary surface attributes and processes.

  13. Towards a Dynamic DES model

    NASA Astrophysics Data System (ADS)

    Subbareddy, Pramod; Candler, Graham

    2009-11-01

    Hybrid RANS/LES methods are being increasingly used for turbulent flow simulations in complex geometries. Spalart's detached eddy simulation (DES) model is one of the more popular ones. We are interested in examining the behavior of the Spalart-Allmaras (S-A) Detached Eddy Simulation (DES) model in its ``LES mode.'' The role of the near-wall functions present in the equations is analyzed and an explicit analogy between the S-A and a one-equation LES model based on the sub-grid kinetic energy is presented. A dynamic version of the S-A DES model is proposed based on this connection. Validation studies and results from DES and LES applications will be presented and the effect of the proposed modification will be discussed.

  14. 9 CFR 85.2 - Notice relating to the existence of the contagion of pseudorabies.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 9 Animals and Animal Products 1 2013-01-01 2013-01-01 false Notice relating to the existence of the contagion of pseudorabies. 85.2 Section 85.2 Animals and Animal Products ANIMAL AND PLANT HEALTH... ANIMAL PRODUCTS PSEUDORABIES § 85.2 Notice relating to the existence of the contagion of pseudorabies...

  15. 9 CFR 85.2 - Notice relating to the existence of the contagion of pseudorabies.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 9 Animals and Animal Products 1 2012-01-01 2012-01-01 false Notice relating to the existence of the contagion of pseudorabies. 85.2 Section 85.2 Animals and Animal Products ANIMAL AND PLANT HEALTH... ANIMAL PRODUCTS PSEUDORABIES § 85.2 Notice relating to the existence of the contagion of pseudorabies...

  16. 9 CFR 85.2 - Notice relating to the existence of the contagion of pseudorabies.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 9 Animals and Animal Products 1 2011-01-01 2011-01-01 false Notice relating to the existence of the contagion of pseudorabies. 85.2 Section 85.2 Animals and Animal Products ANIMAL AND PLANT HEALTH... ANIMAL PRODUCTS PSEUDORABIES § 85.2 Notice relating to the existence of the contagion of pseudorabies...

  17. 9 CFR 85.2 - Notice relating to the existence of the contagion of pseudorabies.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Notice relating to the existence of the contagion of pseudorabies. 85.2 Section 85.2 Animals and Animal Products ANIMAL AND PLANT HEALTH... ANIMAL PRODUCTS PSEUDORABIES § 85.2 Notice relating to the existence of the contagion of pseudorabies...

  18. 9 CFR 85.2 - Notice relating to the existence of the contagion of pseudorabies.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 9 Animals and Animal Products 1 2014-01-01 2014-01-01 false Notice relating to the existence of the contagion of pseudorabies. 85.2 Section 85.2 Animals and Animal Products ANIMAL AND PLANT HEALTH... ANIMAL PRODUCTS PSEUDORABIES § 85.2 Notice relating to the existence of the contagion of pseudorabies...

  19. Emotional Contagion in the Classroom: An Examination of How Teacher and Student Emotions Are Related.

    ERIC Educational Resources Information Center

    Mottet, Timothy P.; Beebe, Steven A.

    The purpose of this study was to examine emotional contagion in the classroom. The theory of emotional contagion predicts that people automatically mimic and synchronize expressions, vocalizations, postures, and movements with others and consequently converge emotionally as a result of the activation and/or feedback from such mimicry (Hatfield,…

  20. Modeling Catastrophic Barrier Island Dynamics

    NASA Astrophysics Data System (ADS)

    Whitley, J. W.; McNamara, D.

    2012-12-01

    Barrier islands, thin strips of sand lying parallel to the mainland coastline, along the U.S. Atlantic and Gulf Coasts appear to have maintained their form for thousands of years in the face of rising sea level. The mechanisms that allow barrier islands to remain robust are transport of sediment from the ocean side of barriers to the top and backside during storms, termed island overwash, and the growth and alongshore propagation of tidal deltas near barrier island inlets. Dynamically these processes provide the necessary feedbacks to maintain a barrier island in an attractor that withstands rising sea level within a phase space of barrier island geometrical characteristics. Current barrier island configurations along the Atlantic and Gulf coasts exist among a wide range of storm climate and underlying geologic conditions and therefore the environment that forces overwash and tidal delta dynamics varies considerably. It has been suggested that barrier islands in certain locations such as those between Avon and Buxton (losing 76% of island width since 1852) and Chandeleur islands (losing 85% of its surface area since 2005) along the Atlantic and Gulf coasts, respectively, may be subject to a catastrophic shift in barrier island attractor states - more numerous inlets cutting barriers in some locations and the complete disappearance of barrier islands in other locations. In contrast to common models for barrier islands that neglect storm dynamics and often only consider cross-shore response, we use an alongshore extended model for barrier island dynamics including beach erosion, island overwash and inlet cutting during storms, and beach accretion, tidal delta growth and dune and vegetation growth between storms to explore the response of barrier islands to a wide range of environmental forcing. Results will be presented that show how barrier island attractor states are altered with variations in the rate of sea level rise, storminess, and underlying geology. We will

  1. Modeling Wildfire Incident Complexity Dynamics

    PubMed Central

    Thompson, Matthew P.

    2013-01-01

    Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management. PMID:23691014

  2. Data modeling of network dynamics

    NASA Astrophysics Data System (ADS)

    Jaenisch, Holger M.; Handley, James W.; Faucheux, Jeffery P.; Harris, Brad

    2004-01-01

    This paper highlights Data Modeling theory and its use for text data mining as a graphical network search engine. Data Modeling is then used to create a real-time filter capable of monitoring network traffic down to the port level for unusual dynamics and changes in business as usual. This is accomplished in an unsupervised fashion without a priori knowledge of abnormal characteristics. Two novel methods for converting streaming binary data into a form amenable to graphics based search and change detection are introduced. These techniques are then successfully applied to 1999 KDD Cup network attack data log-on sessions to demonstrate that Data Modeling can detect attacks without prior training on any form of attack behavior. Finally, two new methods for data encryption using these ideas are proposed.

  3. Mathematical Modeling of Wildfire Dynamics

    NASA Astrophysics Data System (ADS)

    Del Bene, Kevin; Drew, Donald

    2012-11-01

    Wildfires have been a long-standing problem in today's society. In this paper, we derive and solve a fluid dynamics model to study a specific type of wildfire, namely, a two dimensional flow around a rising plume above a concentrated heat source, modeling a fire line. This flow assumes a narrow plume of hot gas rising and entraining the surrounding air. The surrounding air is assumed to have constant density and is irrotational far from the fire line. The flow outside the plume is described by a Biot-Savart integral with jump conditions across the position of the plume. The plume model describes the unsteady evolution of the mass, momentum, energy, and vorticity inside the plume, with sources derived to model mixing in the style of Morton, et al. 1956]. The fire is then modeled using a conservation derivation, allowing the fire to propagate, coupling back to the plume model. The results show that this model is capable of capturing the complex interaction of the plume with the surrounding air and fuel layer. Funded by NSF GRFP.

  4. The global financial crisis: Is there any contagion between real estate and equity markets?

    NASA Astrophysics Data System (ADS)

    Hui, Eddie Chi-man; Chan, Ka Kwan Kevin

    2014-07-01

    This study examines contagion across equity and securitized real estate markets of Hong Kong, US and UK during the global financial crisis by the Forbes-Rigobon, coskewness and cokurtosis tests. In particular, this is the first study to use the cokurtosis test to examine contagion between real estate and equity markets. The results show that the cokurtosis test can detect additional channels of contagion, and hence is a more powerful test. In contrary to Fry et al. (2010), we find that the cokurtosis test shows a highly significant evidence of contagion between the equity and real estate markets in both directions. In particular, the contagion between US's equity and real estate markets is the most significant. This reflects that US is the centre of shock of the global financial crisis.

  5. Putting like a pro: the role of positive contagion in golf performance and perception.

    PubMed

    Lee, Charles; Linkenauger, Sally A; Bakdash, Jonathan Z; Joy-Gaba, Jennifer A; Profitt, Dennis R

    2011-01-01

    Many amateur athletes believe that using a professional athlete's equipment can improve their performance. Such equipment can be said to be affected with positive contagion, which refers to the belief of transference of beneficial properties between animate persons/objects to previously neutral objects. In this experiment, positive contagion was induced by telling participants in one group that a putter previously belonged to a professional golfer. The effect of positive contagion was examined for perception and performance in a golf putting task. Individuals who believed they were using the professional golfer's putter perceived the size of the golf hole to be larger than golfers without such a belief and also had better performance, sinking more putts. These results provide empirical support for anecdotes, which allege that using objects with positive contagion can improve performance, and further suggest perception can be modulated by positive contagion.

  6. Putting Like a Pro: The Role of Positive Contagion in Golf Performance and Perception

    PubMed Central

    Lee, Charles; Linkenauger, Sally A.; Bakdash, Jonathan Z.; Joy-Gaba, Jennifer A.; Profitt, Dennis R.

    2011-01-01

    Many amateur athletes believe that using a professional athlete's equipment can improve their performance. Such equipment can be said to be affected with positive contagion, which refers to the belief of transference of beneficial properties between animate persons/objects to previously neutral objects. In this experiment, positive contagion was induced by telling participants in one group that a putter previously belonged to a professional golfer. The effect of positive contagion was examined for perception and performance in a golf putting task. Individuals who believed they were using the professional golfer's putter perceived the size of the golf hole to be larger than golfers without such a belief and also had better performance, sinking more putts. These results provide empirical support for anecdotes, which allege that using objects with positive contagion can improve performance, and further suggest perception can be modulated by positive contagion. PMID:22028804

  7. Modeling the Dynamics of Snags.

    PubMed

    Morrison, Michael L; Raphael, Martin G

    1993-05-01

    Many wildlife species required standing dead trees (i.e., snags) as part of their habitat. Therefore, the ability to predict future density, distribution, and condition of snags can assist resource managers in making land-use decisions. Here we present methods for modeling the dynamics of snags using data from a 10-yr study on the rates of decay, falling, and recruitment of snags on burned and unburned plots in the Sierra Nevada, California. Snags (all species) in advanced stages of decay usually fell within 5 yr, and snags created by fire decayed rapidly and fell quicker (within 10 yr) than those on unburned plots. Pine (Pinus spp.) snags decayed more rapidly than fir (Abies spp.). Although there was an overall net increase in snag density on unburned plots, most of this increase was in the smaller (>13-38 cm diameter at breast height [dbh]) size classes; there was a net decrease in the larger (>38 cm dbh) snags preferred by many birds for nesting and feeding. Overall, snags remained standing the longest that were larger in diameter, shorter in height, less decayed, fir rather than pine, and lacking tops. A Leslie matrix model of snag dynamics predicted changes in snag decay and density only when adjusted for the specific environmental factors(s) causing initial tree mortality. Many snags are created by episodic events, such as fire, disease, drought, and insects. Models of snag dynamics must include the species and condition of trees becoming snags, as well as the factor(s) causing the tree to die. Forest managers must consider this episodic creation of snags when developing snag-management guidelines, and when planning tree-salvage programs based on short-term inventories.

  8. Opinion dynamics model with weighted influence: Exit probability and dynamics

    NASA Astrophysics Data System (ADS)

    Biswas, Soham; Sinha, Suman; Sen, Parongama

    2013-08-01

    We introduce a stochastic model of binary opinion dynamics in which the opinions are determined by the size of the neighboring domains. The exit probability here shows a step function behavior, indicating the existence of a separatrix distinguishing two different regions of basin of attraction. This behavior, in one dimension, is in contrast to other well known opinion dynamics models where no such behavior has been observed so far. The coarsening study of the model also yields novel exponent values. A lower value of persistence exponent is obtained in the present model, which involves stochastic dynamics, when compared to that in a similar type of model with deterministic dynamics. This apparently counterintuitive result is justified using further analysis. Based on these results, it is concluded that the proposed model belongs to a unique dynamical class.

  9. Eigenvalue dynamics for multimatrix models

    NASA Astrophysics Data System (ADS)

    de Mello Koch, Robert; Gossman, David; Nkumane, Lwazi; Tribelhorn, Laila

    2017-07-01

    By performing explicit computations of correlation functions, we find evidence that there is a sector of the two matrix model defined by the S U (2 ) sector of N =4 super Yang-Mills theory that can be reduced to eigenvalue dynamics. There is an interesting generalization of the usual Van der Monde determinant that plays a role. The observables we study are the Bogomol'nyi-Prasad-Sommerfield operators of the S U (2 ) sector and include traces of products of both matrices, which are genuine multimatrix observables. These operators are associated with supergravity solutions of string theory.

  10. Bayesian Estimation of Categorical Dynamic Factor Models

    ERIC Educational Resources Information Center

    Zhang, Zhiyong; Nesselroade, John R.

    2007-01-01

    Dynamic factor models have been used to analyze continuous time series behavioral data. We extend 2 main dynamic factor model variations--the direct autoregressive factor score (DAFS) model and the white noise factor score (WNFS) model--to categorical DAFS and WNFS models in the framework of the underlying variable method and illustrate them with…

  11. Bayesian Estimation of Categorical Dynamic Factor Models

    ERIC Educational Resources Information Center

    Zhang, Zhiyong; Nesselroade, John R.

    2007-01-01

    Dynamic factor models have been used to analyze continuous time series behavioral data. We extend 2 main dynamic factor model variations--the direct autoregressive factor score (DAFS) model and the white noise factor score (WNFS) model--to categorical DAFS and WNFS models in the framework of the underlying variable method and illustrate them with…

  12. Aperiodic dynamics in a deterministic adaptive network model of attitude formation in social groups

    NASA Astrophysics Data System (ADS)

    Ward, Jonathan A.; Grindrod, Peter

    2014-07-01

    Adaptive network models, in which node states and network topology coevolve, arise naturally in models of social dynamics that incorporate homophily and social influence. Homophily relates the similarity between pairs of nodes' states to their network coupling strength, whilst social influence causes coupled nodes' states to convergence. In this paper we propose a deterministic adaptive network model of attitude formation in social groups that includes these effects, and in which the attitudinal dynamics are represented by an activato-inhibitor process. We illustrate that consensus, corresponding to all nodes adopting the same attitudinal state and being fully connected, may destabilise via Turing instability, giving rise to aperiodic dynamics with sensitive dependence on initial conditions. These aperiodic dynamics correspond to the formation and dissolution of sub-groups that adopt contrasting attitudes. We discuss our findings in the context of cultural polarisation phenomena. Social influence. This reflects the fact that people tend to modify their behaviour and attitudes in response to the opinions of others [22-26]. We model social influence via diffusion: agents adjust their state according to a weighted sum (dictated by the evolving network) of the differences between their state and the states of their neighbours. Homophily. This relates the similarity of individuals' states to their frequency and strength of interaction [27]. Thus in our model, homophily drives the evolution of the weighted ‘social' network. A precise formulation of our model is given in Section 2. Social influence and homophily underpin models of social dynamics [21], which cover a wide range of sociological phenomena, including the diffusion of innovations [28-32], complex contagions [33-36], collective action [37-39], opinion dynamics [19,20,40,10,11,13,15,41,16], the emergence of social norms [42-44], group stability [45], social differentiation [46] and, of particular relevance

  13. Characterizing and modeling citation dynamics.

    PubMed

    Eom, Young-Ho; Fortunato, Santo

    2011-01-01

    Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well.

  14. Characterizing and Modeling Citation Dynamics

    PubMed Central

    Eom, Young-Ho; Fortunato, Santo

    2011-01-01

    Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well. PMID:21966387

  15. Dynamical model for competing opinions

    NASA Astrophysics Data System (ADS)

    Souza, S. R.; Gonçalves, S.

    2012-05-01

    We propose an opinion model based on agents located at the vertices of a regular lattice. Each agent has an independent opinion (among an arbitrary, but fixed, number of choices) and its own degree of conviction. The latter changes every time two agents which have different opinions interact with each other. The dynamics leads to size distributions of clusters (made up of agents which have the same opinion and are located at contiguous spatial positions) which follow a power law, as long as the range of the interaction between the agents is not too short; i.e., the system self-organizes into a critical state. Short range interactions lead to an exponential cutoff in the size distribution and to spatial correlations which cause agents which have the same opinion to be closely grouped. When the diversity of opinions is restricted to two, a nonconsensus dynamic is observed, with unequal population fractions, whereas consensus is reached if the agents are also allowed to interact with those located far from them. The individual agents' convictions, the preestablished interaction range, and the locality of the interaction between a pair of agents (their neighborhood has no effect on the interaction) are the main characteristics which distinguish our model from previous ones.

  16. Dynamical modeling of tidal streams

    SciTech Connect

    Bovy, Jo

    2014-11-01

    I present a new framework for modeling the dynamics of tidal streams. The framework consists of simple models for the initial action-angle distribution of tidal debris, which can be straightforwardly evolved forward in time. Taking advantage of the essentially one-dimensional nature of tidal streams, the transformation to position-velocity coordinates can be linearized and interpolated near a small number of points along the stream, thus allowing for efficient computations of a stream's properties in observable quantities. I illustrate how to calculate the stream's average location (its 'track') in different coordinate systems, how to quickly estimate the dispersion around its track, and how to draw mock stream data. As a generative model, this framework allows one to compute the full probability distribution function and marginalize over or condition it on certain phase-space dimensions as well as convolve it with observational uncertainties. This will be instrumental in proper data analysis of stream data. In addition to providing a computationally efficient practical tool for modeling the dynamics of tidal streams, the action-angle nature of the framework helps elucidate how the observed width of the stream relates to the velocity dispersion or mass of the progenitor, and how the progenitors of 'orphan' streams could be located. The practical usefulness of the proposed framework crucially depends on the ability to calculate action-angle variables for any orbit in any gravitational potential. A novel method for calculating actions, frequencies, and angles in any static potential using a single orbit integration is described in the Appendix.

  17. Emotional Contagion is not Altered in Mice Prenatally Exposed to Poly (I:C) on Gestational Day 9

    PubMed Central

    Gonzalez-Liencres, Cristina; Juckel, Georg; Esslinger, Manuela; Wachholz, Simone; Manitz, Marie-Pierre; Brüne, Martin; Friebe, Astrid

    2016-01-01

    Prenatal immune activation has been associated with increased risk of developing schizophrenia. The polyinosinic-polycytidylic acid (Poly(I:C)) mouse model replicates some of the endophenotype characteristic of this disorder but the social deficits observed in schizophrenia patients have not been well studied in this model. Therefore we aimed to investigate social behavior, in particular emotional contagion for pain, in this mouse model. We injected pregnant mouse dams with Poly(I:C) or saline (control) on gestation day 9 (GD9) and we evaluated their offspring in the pre-pulse inhibition (PPI) test at age 50–55 days old to confirm the reliability of our model. Mice were then evaluated in an emotional contagion test immediately followed by the light/dark test to explore post-test anxiety-like behavior at 10 weeks of age. In the emotional contagion test, an observer (prenatally exposed to Poly(I:C) or to saline) witnessed a familiar wild-type (WT) mouse (demonstrator) receiving electric foot shocks. Our results replicate the sensory gating impairments in the Poly(I:C) offspring but we only observed minor group differences in the social tasks. One of the differences we found was that demonstrators deposited fewer feces in the presence of control observers than of observers prenatally exposed to Poly(I:C), which we suggest could be due to the observers’ behavior. We discuss the findings in the context of age, sex and day of prenatal injection, suggesting that Poly(I:C) on GD9 may be a valuable tool to assess other symptoms or symptom clusters of schizophrenia but perhaps not comprising the social domain. PMID:27445729

  18. Exposure to Externalizing Peers in Early Childhood: Homophily and Peer Contagion Processes

    PubMed Central

    Hanish, Laura D.; Martin, Carol Lynn; Fabes, Richard A.; Leonard, Stacie; Herzog, Melissa

    2005-01-01

    Guided by a transactional model, we examined the predictors and effects of exposure to externalizing peers in a low-risk sample of preschoolers and kindergarteners. On the basis of daily observations of peer interactions, we calculated measures of total exposure to externalizing peers and measures of exposure to same- and other-sex externalizing peers. Analyses of predictors of externalizing peer exposure supported a homophily hypothesis for girls. Tests of peer contagion effects varied by sex, and exposure to externalizing peers predicted multiple problem behaviors for girls but not for boys. Sex differences were a function of children’s own sex, but not of peers’ sex. The study provides evidence of externalizing peer exposure effects in a low-risk sample of young children, notably for girls. PMID:15957556

  19. Work–family climate, organizational commitment, and turnover: Multilevel contagion effects of leaders ⋆

    PubMed Central

    O’Neill, John W.; Harrison, Michelle M.; Cleveland, Jeannette; Almeida, David; Stawski, Robert; Crouter, Anne C.

    2009-01-01

    This paper presents empirical research analyzing the relationship between work–family climate (operationalized in terms of three work–family climate sub-scales), organizational leadership (i.e., senior manager) characteristics, organizational commitment and turnover intent among 526 employees from 37 different hotels across the US. Using multilevel modeling, we found significant associations between work–family climate, and both organizational commitment and turnover intent, both within and between hotels. Findings underscored the importance of managerial support for employee work–family balance, the relevance of senior managers’ own work–family circumstances in relation to employees’ work outcomes, and the existence of possible contagion effects of leaders in relation to work–family climate. PMID:19412351

  20. Dynamical Modeling of Mars' Paleoclimate

    NASA Technical Reports Server (NTRS)

    Richardson, Mark I.

    2004-01-01

    This report summarizes work undertaken under a one-year grant from the NASA Mars Fundamental Research Program. The goal of the project was to initiate studies of the response of the Martian climate to changes in planetary obliquity and orbital elements. This work was undertaken with a three-dimensional numerical climate model based on the Geophysical Fluid Dynamics Laboratory (GFDL) Skyhi General Circulation Model (GCM). The Mars GCM code was adapted to simulate various obliquity and orbital parameter states. Using a version of the model with a basic water cycle (ice caps, vapor, and clouds), we examined changes in atmospheric water abundances and in the distribution of water ice sheets on the surface. This work resulted in a paper published in the Journal of Geophysical Research - Planets. In addition, the project saw the initial incorporation of a regolith water transport and storage scheme into the model. This scheme allows for interaction between water in the pores of the near subsurface (<3m) and the atmosphere. This work was not complete by the end of the one-year grant, but is now continuing within the auspices of a three-year grant of the same title awarded by the Mars Fundamental Research Program in late 2003.

  1. Dynamical model of surrogate reactions

    SciTech Connect

    Aritomo, Y.; Chiba, S.; Nishio, K.

    2011-08-15

    A new dynamical model is developed to describe the whole process of surrogate reactions: Transfer of several nucleons at an initial stage, thermal equilibration of residues leading to washing out of shell effects, and decay of populated compound nuclei are treated in a unified framework. Multidimensional Langevin equations are employed to describe time evolution of collective coordinates with a time-dependent potential energy surface corresponding to different stages of surrogate reactions. The new model is capable of calculating spin distributions of the compound nuclei, one of the most important quantities in the surrogate technique. Furthermore, various observables of surrogate reactions can be calculated, for example, energy and angular distribution of ejectile and mass distributions of fission fragments. These features are important to assess validity of the proposed model itself, to understand mechanisms of the surrogate reactions, and to determine unknown parameters of the model. It is found that spin distributions of compound nuclei produced in {sup 18}O+{sup 238}U{yields}{sup 16}O+{sup 240}*U and {sup 18}O+{sup 236}U{yields}{sup 16}O+{sup 238}*U reactions are equivalent and much less than 10({h_bar}/2{pi}) and therefore satisfy conditions proposed by Chiba and Iwamoto [Phys. Rev. C 81, 044604 (2010)] if they are used as a pair in the surrogate ratio method.

  2. Dynamical Modeling of Mars' Paleoclimate

    NASA Technical Reports Server (NTRS)

    Richardson, Mark I.

    2004-01-01

    This report summarizes work undertaken under a one-year grant from the NASA Mars Fundamental Research Program. The goal of the project was to initiate studies of the response of the Martian climate to changes in planetary obliquity and orbital elements. This work was undertaken with a three-dimensional numerical climate model based on the Geophysical Fluid Dynamics Laboratory (GFDL) Skyhi General Circulation Model (GCM). The Mars GCM code was adapted to simulate various obliquity and orbital parameter states. Using a version of the model with a basic water cycle (ice caps, vapor, and clouds), we examined changes in atmospheric water abundances and in the distribution of water ice sheets on the surface. This work resulted in a paper published in the Journal of Geophysical Research - Planets. In addition, the project saw the initial incorporation of a regolith water transport and storage scheme into the model. This scheme allows for interaction between water in the pores of the near subsurface (<3m) and the atmosphere. This work was not complete by the end of the one-year grant, but is now continuing within the auspices of a three-year grant of the same title awarded by the Mars Fundamental Research Program in late 2003.

  3. Modeling sandhill crane population dynamics

    USGS Publications Warehouse

    Johnson, D.H.

    1979-01-01

    The impact of sport hunting on the Central Flyway population of sandhill cranes (Grus canadensis) has been a subject of controversy for several years. A recent study (Buller 1979) presented new and important information on sandhill crane population dynamics. The present report is intended to incorporate that and other information into a mathematical model for the purpose of assessing the long-range impact of hunting on the population of sandhill cranes.The model is a simple deterministic system that embodies density-dependent rates of survival and recruitment. The model employs four kinds of data: (1) spring population size of sandhill cranes, estimated from aerial surveys to be between 250,000 and 400,000 birds; (2) age composition in fall, estimated for 1974-76 to be 11.3% young; (3) annual harvest of cranes, estimated from a variety of sources to be about 5 to 7% of the spring population; and (4) age composition of harvested cranes, which was difficult to estimate but suggests that immatures were 2 to 4 times as vulnerable to hunting as adults.Because the true nature of sandhill crane population dynamics remains so poorly understood, it was necessary to try numerous (768 in all) combinations of survival and recruitment functions, and focus on the relatively few (37) that yielded population sizes and age structures comparable to those extant in the real population. Hunting was then applied to those simulated populations. In all combinations, hunting resulted in a lower asymptotic crane population, the decline ranging from 5 to 54%. The median decline was 22%, which suggests that a hunted sandhill crane population might be about three-fourths as large as it would be if left unhunted. Results apply to the aggregate of the three subspecies in the Central Flyway; individual subspecies or populations could be affected to a greater or lesser degree.

  4. Negative Rumor: Contagion of a Psychiatric Department

    PubMed Central

    McEwan, Stephanie; Bota, Robert G.

    2014-01-01

    Over the past few decades, a sizable body of literature on the effects of rumors and gossip has emerged. Addressing rumors in the workplace is an important subject, as rumors have a direct impact on the quality of the work environment and also on the productivity and creativity of the employees. To date, little has been written on the effect of rumors and gossip in psychiatric hospitals. This article presents case vignettes of rumors spread in psychiatric hospitals and the impact on team cohesion and morale among the staff implicated in these, too often, neglected occurrences. Dynamic aspects with particular focus on rumors in psychiatric units and suggestions for remedy and treatment are presented. PMID:25133051

  5. SSME structural dynamic model development

    NASA Technical Reports Server (NTRS)

    Foley, Michael J.

    1989-01-01

    The high pressure fuel turbopump (HPFTP) is a major component of the Space Shuttle Main Engine (SSME) powerhead. The device is a three stage centrifugal pump that is directly driven by a two stage hot gas turbine. The purpose of the pump is to deliver fuel (liquid hydrogen) from the low pressure fuel turbopump (LPFTP) through the main fuel valve (MFV) to the thrust chamber coolant circuits. In doing so, the pump pressurizes the fuel from an inlet pressure of approximately 178 psi to a discharge pressure of over 6000 psi. At full power level (FPL), the pump rotates at a speed of over 37,000 rpm while generating approximately 77,000 horsepower. Obviously, a pump failure at these speeds and power levels could jeopardize the mission. Results are summarized for work in which the solutions obtained from analytical models of the fuel turbopump impellers are compared with the results obtained from dynamic tests.

  6. Yawn contagion in humans and bonobos: emotional affinity matters more than species

    PubMed Central

    Norscia, Ivan; Demuru, Elisa

    2014-01-01

    In humans and apes, yawn contagion echoes emotional contagion, the basal layer of empathy. Hence, yawn contagion is a unique tool to compare empathy across species. If humans are the most empathic animal species, they should show the highest empathic response also at the level of emotional contagion. We gathered data on yawn contagion in humans (Homo sapiens) and bonobos (Pan paniscus) by applying the same observational paradigm and identical operational definitions. We selected a naturalistic approach because experimental management practices can produce different psychological and behavioural biases in the two species, and differential attention to artificial stimuli. Within species, yawn contagion was highest between strongly bonded subjects. Between species, sensitivity to others’ yawns was higher in humans than in bonobos when involving kin and friends but was similar when considering weakly-bonded subjects. Thus, emotional contagion is not always highest in humans. The cognitive components concur in empowering emotional affinity between individuals. Yet, when they are not in play, humans climb down from the empathic podium to return to the “understory”, which our species shares with apes. PMID:25165630

  7. Teenage suicide cluster formation and contagion: implications for primary care

    PubMed Central

    Johansson, Lars; Lindqvist, Per; Eriksson, Anders

    2006-01-01

    Background We have previously studied unintentional as well as intentional injury deaths among teenagers living in the four northernmost counties, forming approximately 55% of Sweden with 908,000 inhabitants in 1991. During this work, we found what we suspected to be a suicide cluster among teenagers and we also suspected contagion since there were links between these cases. In this present study, we investigate the occurrence of suicide clustering among teenagers, analyze cluster definitions, and suggest preventive measures. Methods A retrospective study of teenager suicides autopsied at the Department of Forensic Medicine in Umeå, Sweden, during 1981 through 2000. Police reports, autopsy protocols, and medical records were studied in all cases, and the police officers that conducted the investigation at the scene were interviewed in all cluster cases. Parents of the suicide victims of the first cluster were also interviewed. Two aggregations of teenager suicides were detected and evaluated as possible suicide clusters using the US Centers for Disease Control definition of a suicide cluster. Results Two clusters including six teenagers were confirmed, and contagion was established within each cluster. Conclusion The general practitioner is identified as a key person in the aftermath of a teenage suicide since the general practitioner often meet the family, friends of the deceased, and other acquaintances early in the process after a suicide. This makes the general practitioner suitable to initiate contacts with others involved in the well-being of the young, in order to prevent suicide cluster formation and para-suicidal activities. PMID:16707009

  8. Effects of inspections in small world social networks with different contagion rules

    NASA Astrophysics Data System (ADS)

    Muñoz, Francisco; Nuño, Juan Carlos; Primicerio, Mario

    2015-08-01

    We study the way the structure of social links determines the effects of random inspections on a population formed by two types of individuals, e.g. tax-payers and tax-evaders (free riders). It is assumed that inspections occur in a larger scale than the population relaxation time and, therefore, a unique initial inspection is performed on a population that is completely formed by tax-evaders. Besides, the inspected tax-evaders become tax-payers forever. The social network is modeled as a Watts-Strogatz Small World whose topology can be tuned in terms of a parameter p ∈ [ 0 , 1 ] from regular (p = 0) to random (p = 1). Two local contagion rules are considered: (i) a continuous one that takes the proportion of neighbors to determine the next status of an individual (node) and (ii) a discontinuous (threshold rule) that assumes a minimum number of neighbors to modify the current state. In the former case, irrespective of the inspection intensity ν, the equilibrium population is always formed by tax-payers. In the mean field approach, we obtain the characteristic time of convergence as a function of ν and p. For the threshold contagion rule, we show that the response of the population to the intensity of inspections ν is a function of the structure of the social network p and the willingness of the individuals to change their state, r. It is shown that sharp transitions occur at critical values of ν that depends on p and r. We discuss these results within the context of tax evasion and fraud where the strategies of inspection could be of major relevance.

  9. Opinion dynamics model based on quantum formalism

    SciTech Connect

    Artawan, I. Nengah; Trisnawati, N. L. P.

    2016-03-11

    Opinion dynamics model based on quantum formalism is proposed. The core of the quantum formalism is on the half spin dynamics system. In this research the implicit time evolution operators are derived. The analogy between the model with Deffuant dan Sznajd models is discussed.

  10. Contagions across networks: colds and markets

    NASA Astrophysics Data System (ADS)

    Berryman, Matthew J.; Johnson, Neil F.; Abbott, Derek

    2005-12-01

    We explore a variety of network models describing transmission across a network. In particular we focus on transmission across composite networks, or "networks of networks", in which a finite number of networked objects are then themselves connected together into a network. In a disease context we introduce two interrelated viruses to hosts on a network, to model the infection of hosts in a classroom situation, with high rates of infection within a classroom, and lower rates of infection between classrooms. The hosts can be either susceptible to infection, infected, or recovering from each virus. During the infection stage and recovery stage there is some level of cross-immunity to related viruses. We explore the effects of immunizing sections of the community on transmission through social networks. In a stock market context we introduce memes, or virus-like ideas into a virtual agent-based model of a stock exchange. By varying the parameters of the individual traders and the way in which they are connected we are able to show emergent behaviour, including boom and bust cycles.

  11. Social contagion with degree-dependent thresholds

    NASA Astrophysics Data System (ADS)

    Lee, Eun; Holme, Petter

    2017-07-01

    We investigate opinion spreading by a threshold model in a situation in which the influence of people is heterogeneously distributed. We assume that there is a coupling between the influence of an individual (measured by the out-degree) and the threshold for accepting a new opinion or habit. We find that if the coupling is strongly positive, the final state of the system will be a mix of different opinions. Otherwise, it will converge to a consensus state. This phenomenon cannot simply be explained as a phase transition, but it is a combined effect of mechanisms and their relative dominance in different regions of parameter space.

  12. Discontinuous phase transitions via cooperative contagion

    NASA Astrophysics Data System (ADS)

    Ghanbarnejad, Fakhteh; Cai, Weiran; Chen, Li; Grassberger, Peter

    2015-03-01

    We study the spreading of two diseases that interact cooperatively (the presence of one helps the other one to spread) on different network topologies, and with two microscopic realizations, both of which are stochastic versions of an SIR type studied by us recently in mean field approximation. We had shown that cooperativity can lead to discontinuous transitions (DT). However, due to the rapid mixing implied by the mean field assumption, DTs were seen only when there were finite (non-zero) densities of sick individuals in the initial state.In this paper we find that the results for the stochastic model depend strongly on the underlying network. In particular, DTs are found when there are few short but many long loops: (i) No DTs exist on trees, due to the absence of loops; (ii) On 2-d lattices with local contacts there are no DTs either, but because of too many short loops; (iii) We do find DTs on Erdos-Renyi (ER) networks, on d-dimensional lattices with d >= 4 ,and on 2-d lattices with sufficiently long-ranged contacts; (iv) On 3-d lattices with local contacts the results depend on the microscopic details of the implementation. All found discontinuous transitions are of ``hybrid'' type, i.e. they display also scaling features usually associated with continuous transitions.

  13. Model dynamics for quantum computing

    NASA Astrophysics Data System (ADS)

    Tabakin, Frank

    2017-08-01

    A model master equation suitable for quantum computing dynamics is presented. In an ideal quantum computer (QC), a system of qubits evolves in time unitarily and, by virtue of their entanglement, interfere quantum mechanically to solve otherwise intractable problems. In the real situation, a QC is subject to decoherence and attenuation effects due to interaction with an environment and with possible short-term random disturbances and gate deficiencies. The stability of a QC under such attacks is a key issue for the development of realistic devices. We assume that the influence of the environment can be incorporated by a master equation that includes unitary evolution with gates, supplemented by a Lindblad term. Lindblad operators of various types are explored; namely, steady, pulsed, gate friction, and measurement operators. In the master equation, we use the Lindblad term to describe short time intrusions by random Lindblad pulses. The phenomenological master equation is then extended to include a nonlinear Beretta term that describes the evolution of a closed system with increasing entropy. An external Bath environment is stipulated by a fixed temperature in two different ways. Here we explore the case of a simple one-qubit system in preparation for generalization to multi-qubit, qutrit and hybrid qubit-qutrit systems. This model master equation can be used to test the stability of memory and the efficacy of quantum gates. The properties of such hybrid master equations are explored, with emphasis on the role of thermal equilibrium and entropy constraints. Several significant properties of time-dependent qubit evolution are revealed by this simple study.

  14. [Affective contagion at work. Causes and effects of collective moods and emotions].

    PubMed

    Wróbel, Monika

    2010-01-01

    Affective contagion is a process of transferring of mood or emotions between individuals. The process often occurs among people who work together and leads to the activation of collective emotions and moods. In particular, it refers to the work teams whose members often cooperate, have positive relations with each other, and are interdependent. Collective affective states can also be shaped by a manager whose feelings spread over other members of the work team. The author discusses the stages of affective contagion and reviews the research on affective contagion at work. She also characterizes the consequences of the spread of collective states between workers for their functioning at work. Individual differences in susceptibility to affective contagion as well as in tendency to affect others with one's feelings are also discussed.

  15. Preliminary shuttle structural dynamics modeling design study

    NASA Technical Reports Server (NTRS)

    1972-01-01

    The design and development of a structural dynamics model of the space shuttle are discussed. The model provides for early study of structural dynamics problems, permits evaluation of the accuracy of the structural and hydroelastic analysis methods used on test vehicles, and provides for efficiently evaluating potential cost savings in structural dynamic testing techniques. The discussion is developed around the modes in which major input forces and responses occur and the significant structural details in these modes.

  16. Comparative dynamics in a health investment model.

    PubMed

    Eisenring, C

    1999-10-01

    The method of comparative dynamics fully exploits the inter-temporal structure of optimal control models. I derive comparative dynamic results in a simplified demand for health model. The effect of a change in the depreciation rate on the optimal paths for health capital and investment in health is studied by use of a phase diagram.

  17. The Challenges to Coupling Dynamic Geospatial Models

    SciTech Connect

    Goldstein, N

    2006-06-23

    Many applications of modeling spatial dynamic systems focus on a single system and a single process, ignoring the geographic and systemic context of the processes being modeled. A solution to this problem is the coupled modeling of spatial dynamic systems. Coupled modeling is challenging for both technical reasons, as well as conceptual reasons. This paper explores the benefits and challenges to coupling or linking spatial dynamic models, from loose coupling, where information transfer between models is done by hand, to tight coupling, where two (or more) models are merged as one. To illustrate the challenges, a coupled model of Urbanization and Wildfire Risk is presented. This model, called Vesta, was applied to the Santa Barbara, California region (using real geospatial data), where Urbanization and Wildfires occur and recur, respectively. The preliminary results of the model coupling illustrate that coupled modeling can lead to insight into the consequences of processes acting on their own.

  18. "Mood contagion": the automatic transfer of mood between persons.

    PubMed

    Neumann, R; Strack, F

    2000-08-01

    The current studies aimed to find out whether a nonintentional form of mood contagion exists and which mechanisms can account for it. In these experiments participants who expected to be tested for text comprehension listened to an affectively neutral speech that was spoken in a slightly sad or happy voice. The authors found that (a) the emotional expression induced a congruent mood state in the listeners, (b) inferential accounts to emotional sharing were not easily reconciled with the findings, (c) different affective experiences emerged from intentional and nonintentional forms of emotional sharing, and (d) findings suggest that a perception-behavior link (T. L. Chartrand & J. A. Bargh, 1999) can account for these findings, because participants who were required to repeat the philosophical speech spontaneously imitated the target person's vocal expression of emotion.

  19. Pupillary contagion: central mechanisms engaged in sadness processing

    PubMed Central

    Harrison, Neil A.; Singer, Tania; Rotshtein, Pia; Dolan, Ray J.; Critchley, Hugo D.

    2006-01-01

    Empathic responses underlie our ability to share emotions and sensations with others. We investigated whether observed pupil size modulates our perception of other's emotional expressions and examined the central mechanisms modulated by incidental perception of pupil size in emotional facial expressions. We show that diminishing pupil size enhances ratings of emotional intensity and valence for sad, but not happy, angry or neutral facial expressions. This effect was associated with modulation of neural activity within cortical and subcortical regions implicated in social cognition. In an identical context, we show that the observed pupil size was mirrored by the observers’ own pupil size. This empathetic contagion engaged the brainstem pupillary control nuclei (Edinger–Westphal) in proportion to individual subject's sensitivity to this effect. These findings provide evidence that perception–action mechanisms extend to non-volitional operations of the autonomic nervous system. PMID:17186063

  20. Crisis Phones - Suicide Prevention Versus Suggestion/Contagion Effects.

    PubMed

    Stack, Steven

    2015-01-01

    There has been no systematic work on the short- or long-term impact of the installation of crisis phones on suicides from bridges. The present study addresses this issue. Data refer to 219 suicides from 1954 through 2013 on the Skyway Bridge in St. Petersburg, Florida. Six crisis phones with signs were installed in July 1999. In the first decade after installation, the phones were used by 27 suicidal persons and credited with preventing 26 or 2.6 suicides a year. However, the net suicide count increased from 48 in the 13 years before installation of phones to 106 the following 13 years or by 4.5 additional suicides/year (t =3.512, p < .001). Although the phones prevented some suicides, there was a net increase after installation. The findings are interpreted with reference to suggestion/contagion effects including the emergence of a controversial bridge suicide blog.

  1. Hydration dynamics near a model protein surface

    SciTech Connect

    Russo, Daniela; Hura, Greg; Head-Gordon, Teresa

    2003-09-01

    The evolution of water dynamics from dilute to very high concentration solutions of a prototypical hydrophobic amino acid with its polar backbone, N-acetyl-leucine-methylamide (NALMA), is studied by quasi-elastic neutron scattering and molecular dynamics simulation for both the completely deuterated and completely hydrogenated leucine monomer. We observe several unexpected features in the dynamics of these biological solutions under ambient conditions. The NALMA dynamics shows evidence of de Gennes narrowing, an indication of coherent long timescale structural relaxation dynamics. The translational water dynamics are analyzed in a first approximation with a jump diffusion model. At the highest solute concentrations, the hydration water dynamics is significantly suppressed and characterized by a long residential time and a slow diffusion coefficient. The analysis of the more dilute concentration solutions takes into account the results of the 2.0M solution as a model of the first hydration shell. Subtracting the first hydration layer based on the 2.0M spectra, the translational diffusion dynamics is still suppressed, although the rotational relaxation time and residential time are converged to bulk-water values. Molecular dynamics analysis shows spatially heterogeneous dynamics at high concentration that becomes homogeneous at more dilute concentrations. We discuss the hydration dynamics results of this model protein system in the context of glassy systems, protein function, and protein-protein interfaces.

  2. Addressing Dynamic Issues of Program Model Checking

    NASA Technical Reports Server (NTRS)

    Lerda, Flavio; Visser, Willem

    2001-01-01

    Model checking real programs has recently become an active research area. Programs however exhibit two characteristics that make model checking difficult: the complexity of their state and the dynamic nature of many programs. Here we address both these issues within the context of the Java PathFinder (JPF) model checker. Firstly, we will show how the state of a Java program can be encoded efficiently and how this encoding can be exploited to improve model checking. Next we show how to use symmetry reductions to alleviate some of the problems introduced by the dynamic nature of Java programs. Lastly, we show how distributed model checking of a dynamic program can be achieved, and furthermore, how dynamic partitions of the state space can improve model checking. We support all our findings with results from applying these techniques within the JPF model checker.

  3. Connecting micro dynamics and population distributions in system dynamics models.

    PubMed

    Fallah-Fini, Saeideh; Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa

    2013-01-01

    Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model.

  4. Connecting micro dynamics and population distributions in system dynamics models

    PubMed Central

    Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa

    2014-01-01

    Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model. PMID:25620842

  5. Stirling Convertor System Dynamic Model Developed

    NASA Technical Reports Server (NTRS)

    Lewandowski, Edward J.; Regan, Timothy F.

    2005-01-01

    Free-piston Stirling convertors are being developed for potential use on NASA exploration missions. In support of this effort, the NASA Glenn Research Center has developed the Stirling convertor System Dynamic Model (SDM). The SDM models the Stirling cycle thermodynamics; heat flow; gas, mechanical, and mounting dynamics; the linear alternator; and the controller. The SDM s scope extends from the thermal energy input to thermal, mechanical, and electrical energy output, allowing one to study complex system interactions among subsystems. Thermal, mechanical, fluid, magnetic, and electrical subsystems can be studied in one model. The SDM is a nonlinear time-domain model containing sub-cycle dynamics, which simulates transient and dynamic phenomena that other models cannot. The entire range of convertor operation is modeled, from startup to full-power conditions.

  6. Chaotic dynamics in a simple dynamical green ocean plankton model

    NASA Astrophysics Data System (ADS)

    Cropp, Roger; Moroz, Irene M.; Norbury, John

    2014-11-01

    The exchange of important greenhouse gases between the ocean and atmosphere is influenced by the dynamics of near-surface plankton ecosystems. Marine plankton ecosystems are modified by climate change creating a feedback mechanism that could have significant implications for predicting future climates. The collapse or extinction of a plankton population may push the climate system across a tipping point. Dynamic green ocean models (DGOMs) are currently being developed for inclusion into climate models to predict the future state of the climate. The appropriate complexity of the DGOMs used to represent plankton processes is an ongoing issue, with models tending to become more complex, with more complicated dynamics, and an increasing propensity for chaos. We consider a relatively simple (four-population) DGOM of phytoplankton, zooplankton, bacteria and zooflagellates where the interacting plankton populations are connected by a single limiting nutrient. Chaotic solutions are possible in this 4-dimensional model for plankton population dynamics, as well as in a reduced 3-dimensional model, as we vary two of the key mortality parameters. Our results show that chaos is robust to the variation of parameters as well as to the presence of environmental noise, where the attractor of the more complex system is more robust than the attractor of its simplified equivalent. We find robust chaotic dynamics in low trophic order ecological models, suggesting that chaotic dynamics might be ubiquitous in the more complex models, but this is rarely observed in DGOM simulations. The physical equations of DGOMs are well understood and are constrained by conservation principles, but the ecological equations are not well understood, and generally have no explicitly conserved quantities. This work, in the context of the paucity of the empirical and theoretical bases upon which DGOMs are constructed, raises the interesting question of whether DGOMs better represent reality if they include

  7. Global Civil Unrest: Contagion, Self-Organization, and Prediction

    PubMed Central

    Braha, Dan

    2012-01-01

    Civil unrest is a powerful form of collective human dynamics, which has led to major transitions of societies in modern history. The study of collective human dynamics, including collective aggression, has been the focus of much discussion in the context of modeling and identification of universal patterns of behavior. In contrast, the possibility that civil unrest activities, across countries and over long time periods, are governed by universal mechanisms has not been explored. Here, records of civil unrest of 170 countries during the period 1919–2008 are analyzed. It is demonstrated that the distributions of the number of unrest events per year are robustly reproduced by a nonlinear, spatially extended dynamical model, which reflects the spread of civil disorder between geographic regions connected through social and communication networks. The results also expose the similarity between global social instability and the dynamics of natural hazards and epidemics. PMID:23119067

  8. Global civil unrest: contagion, self-organization, and prediction.

    PubMed

    Braha, Dan

    2012-01-01

    Civil unrest is a powerful form of collective human dynamics, which has led to major transitions of societies in modern history. The study of collective human dynamics, including collective aggression, has been the focus of much discussion in the context of modeling and identification of universal patterns of behavior. In contrast, the possibility that civil unrest activities, across countries and over long time periods, are governed by universal mechanisms has not been explored. Here, records of civil unrest of 170 countries during the period 1919-2008 are analyzed. It is demonstrated that the distributions of the number of unrest events per year are robustly reproduced by a nonlinear, spatially extended dynamical model, which reflects the spread of civil disorder between geographic regions connected through social and communication networks. The results also expose the similarity between global social instability and the dynamics of natural hazards and epidemics.

  9. Behavioral contagion during learning about another agent's risk-preferences acts on the neural representation of decision-risk.

    PubMed

    Suzuki, Shinsuke; Jensen, Emily L S; Bossaerts, Peter; O'Doherty, John P

    2016-04-05

    Our attitude toward risk plays a crucial role in influencing our everyday decision-making. Despite its importance, little is known about how human risk-preference can be modulated by observing risky behavior in other agents at either the behavioral or the neural level. Using fMRI combined with computational modeling of behavioral data, we show that human risk-preference can be systematically altered by the act of observing and learning from others' risk-related decisions. The contagion is driven specifically by brain regions involved in the assessment of risk: the behavioral shift is implemented via a neural representation of risk in the caudate nucleus, whereas the representations of other decision-related variables such as expected value are not affected. Furthermore, we uncover neural computations underlying learning about others' risk-preferences and describe how these signals interact with the neural representation of risk in the caudate. Updating of the belief about others' preferences is associated with neural activity in the dorsolateral prefrontal cortex (dlPFC). Functional coupling between the dlPFC and the caudate correlates with the degree of susceptibility to the contagion effect, suggesting that a frontal-subcortical loop, the so-called dorsolateral prefrontal-striatal circuit, underlies the modulation of risk-preference. Taken together, these findings provide a mechanistic account for how observation of others' risky behavior can modulate an individual's own risk-preference.

  10. Stress contagion in the classroom? The link between classroom teacher burnout and morning cortisol in elementary school students.

    PubMed

    Oberle, Eva; Schonert-Reichl, Kimberly A

    2016-06-01

    The purpose of this study was to explore the link between classroom teachers' burnout levels and students' physiological stress response. Drawing from a stress-contagion framework, we expected higher levels of teacher burnout to be related to elevated cortisol levels in elementary school students (N = 406, 50% female, Mean age = 11.26, SD = .89). Classroom teacher burnout was assessed with the Maslach Burnout Inventory modified for teachers. Salivary cortisol was collected as an indicator of students' hypothalamic-pituitary-adrenal (HPA) functioning. We collected salivary cortisol in children at 9 a.m., 11:30 a.m., and 2 p.m. in the classroom setting. Using Multilevel Modeling, we found that children's morning cortisol levels significantly varied between classrooms (10% variability). Higher levels of classroom teacher burnout significantly predicted the variability in morning cortisol. Teacher burnout reduced the unexplained variability in cortisol at the classroom level to 4.6%. This is the first study to show that teachers' occupational stress is linked to students' physiological stress regulation. We discuss the present findings in the context of potential stress contagion in the classroom, considering empirical and practical relevance. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Very Large System Dynamics Models - Lessons Learned

    SciTech Connect

    Jacob J. Jacobson; Leonard Malczynski

    2008-10-01

    This paper provides lessons learned from developing several large system dynamics (SD) models. System dynamics modeling practice emphasize the need to keep models small so that they are manageable and understandable. This practice is generally reasonable and prudent; however, there are times that large SD models are necessary. This paper outlines two large SD projects that were done at two Department of Energy National Laboratories, the Idaho National Laboratory and Sandia National Laboratories. This paper summarizes the models and then discusses some of the valuable lessons learned during these two modeling efforts.

  12. Comparing models of Red Knot population dynamics

    USGS Publications Warehouse

    McGowan, Conor

    2015-01-01

    Predictive population modeling contributes to our basic scientific understanding of population dynamics, but can also inform management decisions by evaluating alternative actions in virtual environments. Quantitative models mathematically reflect scientific hypotheses about how a system functions. In Delaware Bay, mid-Atlantic Coast, USA, to more effectively manage horseshoe crab (Limulus polyphemus) harvests and protect Red Knot (Calidris canutus rufa) populations, models are used to compare harvest actions and predict the impacts on crab and knot populations. Management has been chiefly driven by the core hypothesis that horseshoe crab egg abundance governs the survival and reproduction of migrating Red Knots that stopover in the Bay during spring migration. However, recently, hypotheses proposing that knot dynamics are governed by cyclical lemming dynamics garnered some support in data analyses. In this paper, I present alternative models of Red Knot population dynamics to reflect alternative hypotheses. Using 2 models with different lemming population cycle lengths and 2 models with different horseshoe crab effects, I project the knot population into the future under environmental stochasticity and parametric uncertainty with each model. I then compare each model's predictions to 10 yr of population monitoring from Delaware Bay. Using Bayes' theorem and model weight updating, models can accrue weight or support for one or another hypothesis of population dynamics. With 4 models of Red Knot population dynamics and only 10 yr of data, no hypothesis clearly predicted population count data better than another. The collapsed lemming cycle model performed best, accruing ~35% of the model weight, followed closely by the horseshoe crab egg abundance model, which accrued ~30% of the weight. The models that predicted no decline or stable populations (i.e. the 4-yr lemming cycle model and the weak horseshoe crab effect model) were the most weakly supported.

  13. Human systems dynamics: Toward a computational model

    NASA Astrophysics Data System (ADS)

    Eoyang, Glenda H.

    2012-09-01

    A robust and reliable computational model of complex human systems dynamics could support advancements in theory and practice for social systems at all levels, from intrapersonal experience to global politics and economics. Models of human interactions have evolved from traditional, Newtonian systems assumptions, which served a variety of practical and theoretical needs of the past. Another class of models has been inspired and informed by models and methods from nonlinear dynamics, chaos, and complexity science. None of the existing models, however, is able to represent the open, high dimension, and nonlinear self-organizing dynamics of social systems. An effective model will represent interactions at multiple levels to generate emergent patterns of social and political life of individuals and groups. Existing models and modeling methods are considered and assessed against characteristic pattern-forming processes in observed and experienced phenomena of human systems. A conceptual model, CDE Model, based on the conditions for self-organizing in human systems, is explored as an alternative to existing models and methods. While the new model overcomes the limitations of previous models, it also provides an explanatory base and foundation for prospective analysis to inform real-time meaning making and action taking in response to complex conditions in the real world. An invitation is extended to readers to engage in developing a computational model that incorporates the assumptions, meta-variables, and relationships of this open, high dimension, and nonlinear conceptual model of the complex dynamics of human systems.

  14. Dynamics Modelling of Biolistic Gene Guns

    SciTech Connect

    Zhang, M.; Tao, W.; Pianetta, P.A.

    2009-06-04

    The gene transfer process using biolistic gene guns is a highly dynamic process. To achieve good performance, the process needs to be well understood and controlled. Unfortunately, no dynamic model is available in the open literature for analysing and controlling the process. This paper proposes such a model. Relationships of the penetration depth with the helium pressure, the penetration depth with the acceleration distance, and the penetration depth with the micro-carrier radius are presented. Simulations have also been conducted. The results agree well with experimental results in the open literature. The contribution of this paper includes a dynamic model for improving and manipulating performance of the biolistic gene gun.

  15. Differential equation models for sharp threshold dynamics.

    PubMed

    Schramm, Harrison C; Dimitrov, Nedialko B

    2014-01-01

    We develop an extension to differential equation models of dynamical systems to allow us to analyze probabilistic threshold dynamics that fundamentally and globally change system behavior. We apply our novel modeling approach to two cases of interest: a model of infectious disease modified for malware where a detection event drastically changes dynamics by introducing a new class in competition with the original infection; and the Lanchester model of armed conflict, where the loss of a key capability drastically changes the effectiveness of one of the sides. We derive and demonstrate a step-by-step, repeatable method for applying our novel modeling approach to an arbitrary system, and we compare the resulting differential equations to simulations of the system's random progression. Our work leads to a simple and easily implemented method for analyzing probabilistic threshold dynamics using differential equations.

  16. Equivalent dynamic model of DEMES rotary joint

    NASA Astrophysics Data System (ADS)

    Zhao, Jianwen; Wang, Shu; Xing, Zhiguang; McCoul, David; Niu, Junyang; Huang, Bo; Liu, Liwu; Leng, Jinsong

    2016-07-01

    The dielectric elastomer minimum energy structure (DEMES) can realize large angular deformations by a small voltage-induced strain of the dielectric elastomer (DE), so it is a suitable candidate to make a rotary joint for a soft robot. Dynamic analysis is necessary for some applications, but the dynamic response of DEMESs is difficult to model because of the complicated morphology and viscoelasticity of the DE film. In this paper, a method composed of theoretical analysis and experimental measurement is presented to model the dynamic response of a DEMES rotary joint under an alternating voltage. Based on measurements of equivalent driving force and damping of the DEMES, the model can be derived. Some experiments were carried out to validate the equivalent dynamic model. The maximum angle error between model and experiment is greater than ten degrees, but it is acceptable to predict angular velocity of the DEMES, therefore, it can be applied in feedforward-feedback compound control.

  17. Modeling microbial growth and dynamics.

    PubMed

    Esser, Daniel S; Leveau, Johan H J; Meyer, Katrin M

    2015-11-01

    Modeling has become an important tool for widening our understanding of microbial growth in the context of applied microbiology and related to such processes as safe food production, wastewater treatment, bioremediation, or microbe-mediated mining. Various modeling techniques, such as primary, secondary and tertiary mathematical models, phenomenological models, mechanistic or kinetic models, reactive transport models, Bayesian network models, artificial neural networks, as well as agent-, individual-, and particle-based models have been applied to model microbial growth and activity in many applied fields. In this mini-review, we summarize the basic concepts of these models using examples and applications from food safety and wastewater treatment systems. We further review recent developments in other applied fields focusing on models that explicitly include spatial relationships. Using these examples, we point out the conceptual similarities across fields of application and encourage the combined use of different modeling techniques in hybrid models as well as their cross-disciplinary exchange. For instance, pattern-oriented modeling has its origin in ecology but may be employed to parameterize microbial growth models when experimental data are scarce. Models could also be used as virtual laboratories to optimize experimental design analogous to the virtual ecologist approach. Future microbial growth models will likely become more complex to benefit from the rich toolbox that is now available to microbial growth modelers.

  18. Markov state models of biomolecular conformational dynamics

    PubMed Central

    Chodera, John D.; Noé, Frank

    2014-01-01

    It has recently become practical to construct Markov state models (MSMs) that reproduce the long-time statistical conformational dynamics of biomolecules using data from molecular dynamics simulations. MSMs can predict both stationary and kinetic quantities on long timescales (e.g. milliseconds) using a set of atomistic molecular dynamics simulations that are individually much shorter, thus addressing the well-known sampling problem in molecular dynamics simulation. In addition to providing predictive quantitative models, MSMs greatly facilitate both the extraction of insight into biomolecular mechanism (such as folding and functional dynamics) and quantitative comparison with single-molecule and ensemble kinetics experiments. A variety of methodological advances and software packages now bring the construction of these models closer to routine practice. Here, we review recent progress in this field, considering theoretical and methodological advances, new software tools, and recent applications of these approaches in several domains of biochemistry and biophysics, commenting on remaining challenges. PMID:24836551

  19. Dynamic coupling of three hydrodynamic models

    NASA Astrophysics Data System (ADS)

    Hartnack, J. N.; Philip, G. T.; Rungoe, M.; Smith, G.; Johann, G.; Larsen, O.; Gregersen, J.; Butts, M. B.

    2008-12-01

    The need for integrated modelling is evidently present within the field of flood management and flood forecasting. Engineers, modellers and managers are faced with flood problems which transcend the classical hydrodynamic fields of urban, river and coastal flooding. Historically the modeller has been faced with having to select one hydrodynamic model to cover all the aspects of the potentially complex dynamics occurring in a flooding situation. Such a single hydrodynamic model does not cover all dynamics of flood modelling equally well. Thus the ideal choice may in fact be a combination of models. Models combining two numerical/hydrodynamic models are becoming more standard, typically these models combine a 1D river model with a 2D overland flow model or alternatively a 1D sewer/collection system model with a 2D overland solver. In complex coastal/urban areas the flood dynamics may include rivers/streams, collection/storm water systems along with the overland flow. The dynamics within all three areas is of the same time scale and there is feedback in the system across the couplings. These two aspects dictate a fully dynamic three way coupling as opposed to running the models sequentially. It will be shown that the main challenges of the three way coupling are time step issues related to the difference in numerical schemes used in the three model components and numerical instabilities caused by the linking of the model components. MIKE FLOOD combines the models MIKE 11, MIKE 21 and MOUSE into one modelling framework which makes it possible to couple any combination of river, urban and overland flow fully dynamically. The MIKE FLOOD framework will be presented with an overview of the coupling possibilities. The flood modelling concept will be illustrated through real life cases in Australia and in Germany. The real life cases reflect dynamics and interactions across all three model components which are not possible to reproduce using a two-way coupling alone. The

  20. Dynamic Modeling, Chaos, and Cognitive Development.

    ERIC Educational Resources Information Center

    Howe, Mark L.; Rabinowitz, F. Michael

    1994-01-01

    Introduces the essential constructs involved in dynamic modeling, in relation to issues in psychological development. Presents several instances of how the principles of dynamic systems can be translated into mathematical formalism. Concludes that transition is a key invariance in development and that single subject, longitudinal designs are…

  1. Dynamic Modeling, Chaos, and Cognitive Development.

    ERIC Educational Resources Information Center

    Howe, Mark L.; Rabinowitz, F. Michael

    1994-01-01

    Introduces the essential constructs involved in dynamic modeling, in relation to issues in psychological development. Presents several instances of how the principles of dynamic systems can be translated into mathematical formalism. Concludes that transition is a key invariance in development and that single subject, longitudinal designs are…

  2. Biomolecular dynamics of DNA: statistical mechanics and dynamical models

    NASA Astrophysics Data System (ADS)

    Peyrard, M.; Dauxois, T.; Hoyet, H.; Willis, C. R.

    1993-09-01

    There is a growing feeling that biomolecular structure is not sufficient to determine biological activity which is also governed by large amplitude dynamics of the molecules. The transcription of DNA or its thermal denaturation are typical examples. Traditional approaches use Ising models to describe the denaturation transition of DNA. They have to introduce phenomenological “cooperativity factors” to explain the rather sharp “melting” of this quasi one-dimensional system. We present models which describe the full dynamics of the melting. Using molecular dynamics simulations and statistical analysis, we discuss the mechanism of the denaturation, including precursor effects that can be related to large amplitude localized nonlinear excitations of the molecule in which discreteness effects play a large role. We also show the microscopic origin of the cooperativity factors.

  3. Two-Stage Reduction Of Dynamical Models

    NASA Technical Reports Server (NTRS)

    Lee, Allan Y.; Tsuha, Walter S.

    1993-01-01

    No longer necessary to solve eigenvalue problems of high order. Component-mode projection-and-assembly model-reduction (COMPARE) method provides approximation of dynamics of vibrations of complicated, multiple flexible bodies by use of mathematical models of reduced order. Incorporates component-mode synthesis (CMS) method and enhanced projection-and-assembly (EP&A) method, described in "Enhanced Method of Reduction of Dynamical Models" (NPO-18402), providing for somewhat simplified two-stage process in which order of applicable mathematical models reduced. Reduced-order models used to design algorithms of control systems to suppress vibrations or otherwise control structure.

  4. MODELING MICROBUBBLE DYNAMICS IN BIOMEDICAL APPLICATIONS*

    PubMed Central

    CHAHINE, Georges L.; HSIAO, Chao-Tsung

    2012-01-01

    Controlling microbubble dynamics to produce desirable biomedical outcomes when and where necessary and avoid deleterious effects requires advanced knowledge, which can be achieved only through a combination of experimental and numerical/analytical techniques. The present communication presents a multi-physics approach to study the dynamics combining viscous- in-viscid effects, liquid and structure dynamics, and multi bubble interaction. While complex numerical tools are developed and used, the study aims at identifying the key parameters influencing the dynamics, which need to be included in simpler models. PMID:22833696

  5. Automated adaptive inference of phenomenological dynamical models

    PubMed Central

    Daniels, Bryan C.; Nemenman, Ilya

    2015-01-01

    Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved. PMID:26293508

  6. Automated adaptive inference of phenomenological dynamical models

    NASA Astrophysics Data System (ADS)

    Daniels, Bryan C.; Nemenman, Ilya

    2015-08-01

    Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved.

  7. Constructing minimal models for complex system dynamics

    NASA Astrophysics Data System (ADS)

    Barzel, Baruch; Liu, Yang-Yu; Barabási, Albert-László

    2015-05-01

    One of the strengths of statistical physics is the ability to reduce macroscopic observations into microscopic models, offering a mechanistic description of a system's dynamics. This paradigm, rooted in Boltzmann's gas theory, has found applications from magnetic phenomena to subcellular processes and epidemic spreading. Yet, each of these advances were the result of decades of meticulous model building and validation, which are impossible to replicate in most complex biological, social or technological systems that lack accurate microscopic models. Here we develop a method to infer the microscopic dynamics of a complex system from observations of its response to external perturbations, allowing us to construct the most general class of nonlinear pairwise dynamics that are guaranteed to recover the observed behaviour. The result, which we test against both numerical and empirical data, is an effective dynamic model that can predict the system's behaviour and provide crucial insights into its inner workings.

  8. Airship dynamics modeling: A literature review

    NASA Astrophysics Data System (ADS)

    Li, Yuwen; Nahon, Meyer; Sharf, Inna

    2011-04-01

    The resurgence of airships has created a need for dynamics models and simulation capabilities adapted to these lighter-than-air vehicles. However, the modeling techniques for airship dynamics have lagged behind and are less systematic than those for fixed-wing aircraft. A state-of-the-art literature review is presented on airship dynamics modeling, aiming to provide a comprehensive description of the main problems in this area and a useful source of references for researchers and engineers interested in modern airship applications. The references are categorized according to the major topics in this area: aerodynamics, flight dynamics, incorporation of structural flexibility, incorporation of atmospheric turbulence, and effects of ballonets. Relevant analytical, numerical, and semi-empirical techniques are discussed, with a particular focus on how the main differences between lighter-than-air and heavier-than-air aircraft have been addressed in the modeling. Directions are suggested for future research on each of these topics.

  9. Model Verification of Mixed Dynamic Systems

    NASA Technical Reports Server (NTRS)

    Evensen, D. A.; Chrostowski, J. D.; Hasselman, T. K.

    1982-01-01

    MOVER uses experimental data to verify mathematical models of "mixed" dynamic systems. The term "mixed" refers to interactive mechanical, hydraulic, electrical, and other components. Program compares analytical transfer functions with experiment.

  10. Stochastic population dynamic models as probability networks

    Treesearch

    M.E. and D.C. Lee. Borsuk

    2009-01-01

    The dynamics of a population and its response to environmental change depend on the balance of birth, death and age-at-maturity, and there have been many attempts to mathematically model populations based on these characteristics. Historically, most of these models were deterministic, meaning that the results were strictly determined by the equations of the model and...

  11. A dynamical model of color confinement

    NASA Astrophysics Data System (ADS)

    Loh, S.; Biró, T. S.; Mosel, U.; Thoma, M. H.

    1996-02-01

    A dynamical model of confinement based on a transport theoretical description of the Friedberg-Lee model is extended to explicit color degrees of freedom. The string tension is reproduced by an adiabatic string formation from the nucleon ground state. Color isovector oscillation modes of a qq¯-system are investigated for a wide range of relative qq¯-momenta and the dynamical impact of color confinement on the quark motion is shown.

  12. Approximate dynamic model of a turbojet engine

    NASA Technical Reports Server (NTRS)

    Artemov, O. A.

    1978-01-01

    An approximate dynamic nonlinear model of a turbojet engine is elaborated on as a tool in studying the aircraft control loop, with the turbojet engine treated as an actuating component. Approximate relationships linking the basic engine parameters and shaft speed are derived to simplify the problem, and to aid in constructing an approximate nonlinear dynamic model of turbojet engine performance useful for predicting aircraft motion.

  13. Single timepoint models of dynamic systems

    PubMed Central

    Sachs, K.; Itani, S.; Fitzgerald, J.; Schoeberl, B.; Nolan, G. P.; Tomlin, C. J.

    2013-01-01

    Many interesting studies aimed at elucidating the connectivity structure of biomolecular pathways make use of abundance measurements, and employ statistical and information theoretic approaches to assess connectivities. These studies often do not address the effects of the dynamics of the underlying biological system, yet dynamics give rise to impactful issues such as timepoint selection and its effect on structure recovery. In this work, we study conditions for reliable retrieval of the connectivity structure of a dynamic system, and the impact of dynamics on structure-learning efforts. We encounter an unexpected problem not previously described in elucidating connectivity structure from dynamic systems, show how this confounds structure learning of the system and discuss possible approaches to overcome the confounding effect. Finally, we test our hypotheses on an accurate dynamic model of the IGF signalling pathway. We use two structure-learning methods at four time points to contrast the performance and robustness of those methods in terms of recovering correct connectivity. PMID:24511382

  14. Swarm Intelligence for Urban Dynamics Modelling

    SciTech Connect

    Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.

    2009-04-16

    In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

  15. Swarm Intelligence for Urban Dynamics Modelling

    NASA Astrophysics Data System (ADS)

    Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.

    2009-04-01

    In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

  16. Discrete model for DNA-promoter dynamics

    NASA Astrophysics Data System (ADS)

    Salerno, Mario

    1991-10-01

    We introduce a discrete model for DNA that takes into account the information about specific base sequences along the double helix. We use this model to study nonlinear wave dynamics of the T7A1 DNA promoter. As results we show the existence in the promoter of a dynamically active region in which static solitons acquire finite velocities, which contrasts with regions where solitons simply remain static. Furthermore, when they pass through this region moving solitons are accelerated, decelerated, or reflected, depending on their initial velocities. The possibility that these dynamical effects play a role in the mechanism of genetic activation is suggested.

  17. You Turn Me Cold: Evidence for Temperature Contagion

    PubMed Central

    Featherstone, Eric; Voon, Valerie; Singer, Tania; Critchley, Hugo D.; Harrison, Neil A.

    2014-01-01

    Introduction During social interactions, our own physiological responses influence those of others. Synchronization of physiological (and behavioural) responses can facilitate emotional understanding and group coherence through inter-subjectivity. Here we investigate if observing cues indicating a change in another's body temperature results in a corresponding temperature change in the observer. Methods Thirty-six healthy participants (age; 22.9±3.1 yrs) each observed, then rated, eight purpose-made videos (3 min duration) that depicted actors with either their right or left hand in visibly warm (warm videos) or cold water (cold videos). Four control videos with the actors' hand in front of the water were also shown. Temperature of participant observers' right and left hands was concurrently measured using a thermistor within a Wheatstone bridge with a theoretical temperature sensitivity of <0.0001°C. Temperature data were analysed in a repeated measures ANOVA (temperature × actor's hand × observer's hand). Results Participants rated the videos showing hands immersed in cold water as being significantly cooler than hands immersed in warm water, F(1,34) = 256.67, p<0.001. Participants' own hands also showed a significant temperature-dependent effect: hands were significantly colder when observing cold vs. warm videos F(1,34) = 13.83, p = 0.001 with post-hoc t-test demonstrating a significant reduction in participants' own left (t(35) = −3.54, p = 0.001) and right (t(35) = −2.33, p = 0.026) hand temperature during observation of cold videos but no change to warm videos (p>0.1). There was however no evidence of left-right mirroring of these temperature effects p>0.1). Sensitivity to temperature contagion was also predicted by inter-individual differences in self-report empathy. Conclusions We illustrate physiological contagion of temperature in healthy individuals, suggesting that empathetic understanding for primary low

  18. You turn me cold: evidence for temperature contagion.

    PubMed

    Cooper, Ella A; Garlick, John; Featherstone, Eric; Voon, Valerie; Singer, Tania; Critchley, Hugo D; Harrison, Neil A

    2014-01-01

    During social interactions, our own physiological responses influence those of others. Synchronization of physiological (and behavioural) responses can facilitate emotional understanding and group coherence through inter-subjectivity. Here we investigate if observing cues indicating a change in another's body temperature results in a corresponding temperature change in the observer. Thirty-six healthy participants (age; 22.9±3.1 yrs) each observed, then rated, eight purpose-made videos (3 min duration) that depicted actors with either their right or left hand in visibly warm (warm videos) or cold water (cold videos). Four control videos with the actors' hand in front of the water were also shown. Temperature of participant observers' right and left hands was concurrently measured using a thermistor within a Wheatstone bridge with a theoretical temperature sensitivity of <0.0001°C. Temperature data were analysed in a repeated measures ANOVA (temperature × actor's hand × observer's hand). Participants rated the videos showing hands immersed in cold water as being significantly cooler than hands immersed in warm water, F(1,34) = 256.67, p<0.001. Participants' own hands also showed a significant temperature-dependent effect: hands were significantly colder when observing cold vs. warm videos F(1,34) = 13.83, p = 0.001 with post-hoc t-test demonstrating a significant reduction in participants' own left (t(35) = -3.54, p = 0.001) and right (t(35) = -2.33, p = 0.026) hand temperature during observation of cold videos but no change to warm videos (p>0.1). There was however no evidence of left-right mirroring of these temperature effects p>0.1). Sensitivity to temperature contagion was also predicted by inter-individual differences in self-report empathy. We illustrate physiological contagion of temperature in healthy individuals, suggesting that empathetic understanding for primary low-level physiological challenges (as well as more complex

  19. Model systems for single molecule polymer dynamics

    PubMed Central

    Latinwo, Folarin

    2012-01-01

    Double stranded DNA (dsDNA) has long served as a model system for single molecule polymer dynamics. However, dsDNA is a semiflexible polymer, and the structural rigidity of the DNA double helix gives rise to local molecular properties and chain dynamics that differ from flexible chains, including synthetic organic polymers. Recently, we developed single stranded DNA (ssDNA) as a new model system for single molecule studies of flexible polymer chains. In this work, we discuss model polymer systems in the context of “ideal” and “real” chain behavior considering thermal blobs, tension blobs, hydrodynamic drag and force–extension relations. In addition, we present monomer aspect ratio as a key parameter describing chain conformation and dynamics, and we derive dynamical scaling relations in terms of this molecular-level parameter. We show that asymmetric Kuhn segments can suppress monomer–monomer interactions, thereby altering global chain dynamics. Finally, we discuss ssDNA in the context of a new model system for single molecule polymer dynamics. Overall, we anticipate that future single polymer studies of flexible chains will reveal new insight into the dynamic behavior of “real” polymers, which will highlight the importance of molecular individualism and the prevalence of non-linear phenomena. PMID:22956980

  20. Understanding and Modeling Teams As Dynamical Systems

    PubMed Central

    Gorman, Jamie C.; Dunbar, Terri A.; Grimm, David; Gipson, Christina L.

    2017-01-01

    By its very nature, much of teamwork is distributed across, and not stored within, interdependent people working toward a common goal. In this light, we advocate a systems perspective on teamwork that is based on general coordination principles that are not limited to cognitive, motor, and physiological levels of explanation within the individual. In this article, we present a framework for understanding and modeling teams as dynamical systems and review our empirical findings on teams as dynamical systems. We proceed by (a) considering the question of why study teams as dynamical systems, (b) considering the meaning of dynamical systems concepts (attractors; perturbation; synchronization; fractals) in the context of teams, (c) describe empirical studies of team coordination dynamics at the perceptual-motor, cognitive-behavioral, and cognitive-neurophysiological levels of analysis, and (d) consider the theoretical and practical implications of this approach, including new kinds of explanations of human performance and real-time analysis and performance modeling. Throughout our discussion of the topics we consider how to describe teamwork using equations and/or modeling techniques that describe the dynamics. Finally, we consider what dynamical equations and models do and do not tell us about human performance in teams and suggest future research directions in this area. PMID:28744231

  1. Model systems for single molecule polymer dynamics.

    PubMed

    Latinwo, Folarin; Schroeder, Charles M

    2011-01-01

    Double stranded DNA (dsDNA) has long served as a model system for single molecule polymer dynamics. However, dsDNA is a semiflexible polymer, and the structural rigidity of the DNA double helix gives rise to local molecular properties and chain dynamics that differ from flexible chains, including synthetic organic polymers. Recently, we developed single stranded DNA (ssDNA) as a new model system for single molecule studies of flexible polymer chains. In this work, we discuss model polymer systems in the context of "ideal" and "real" chain behavior considering thermal blobs, tension blobs, hydrodynamic drag and force-extension relations. In addition, we present monomer aspect ratio as a key parameter describing chain conformation and dynamics, and we derive dynamical scaling relations in terms of this molecular-level parameter. We show that asymmetric Kuhn segments can suppress monomer-monomer interactions, thereby altering global chain dynamics. Finally, we discuss ssDNA in the context of a new model system for single molecule polymer dynamics. Overall, we anticipate that future single polymer studies of flexible chains will reveal new insight into the dynamic behavior of "real" polymers, which will highlight the importance of molecular individualism and the prevalence of non-linear phenomena.

  2. 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.

  3. Glassy dynamics of kinetically constrained models

    NASA Astrophysics Data System (ADS)

    Ritort, F.; Sollich, P.

    2003-06-01

    We review the use of kinetically constrained models (KCMs) for the study of dynamics in glassy systems. The characteristic feature of KCMs is that they have trivial, often non-interacting, equilibrium behaviour but interesting slow dynamics due to restrictions on the allowed transitions between configurations. The basic question which KCMs ask is therefore how much glassy physics can be understood without an underlying 'equilibrium glass transition'. After a brief review of glassy phenomenology, we describe the main model classes, which include spin-facilitated (Ising) models, constrained lattice gases, models inspired by cellular structures such as soap froths, models obtained via mappings from interacting systems without constraints, and finally related models such as urn, oscillator, tiling and needle models. We then describe the broad range of techniques that have been applied to KCMs, including exact solutions, adiabatic approximations, projection and mode-coupling techniques, diagrammatic approaches and mappings to quantum systems or effective models. Finally, we give a survey of the known results for the dynamics of KCMs both in and out of equilibrium, including topics such as relaxation time divergences and dynamical transitions, nonlinear relaxation, ageing and effective temperatures, cooperativity and dynamical heterogeneities, and finally non-equilibrium stationary states generated by external driving. We conclude with a discussion of open questions and possibilities for future work.

  4. Battery electrochemical nonlinear/dynamic SPICE model

    SciTech Connect

    Glass, M.C.

    1996-12-31

    An Integrated Battery Model has been produced which accurately represents DC nonlinear battery behavior together with transient dynamics. The NiH{sub 2} battery model begins with a given continuous-function electrochemical math model. The math model for the battery consists of the sum of two electrochemical process DC currents, which are a function of the battery terminal voltage. This paper describes procedures for realizing a voltage-source SPICE model which implements the electrochemical equations using behavioral sources. The model merges the essentially DC non-linear behavior of the electrochemical model, together with the empirical AC dynamic terminal impedance from measured data. Thus the model integrates the short-term linear impedance behavior, with the long-term nonlinear DC resistance behavior. The long-duration non-Faradaic capacitive behavior of the battery is represented by a time constant. Outputs of the model include battery voltage/current, state-of-charge, and charge-current efficiency.

  5. A stochastic model of human gait dynamics

    NASA Astrophysics Data System (ADS)

    Ashkenazy, Yosef; M. Hausdorff, Jeffrey; Ch. Ivanov, Plamen; Eugene Stanley, H.

    2002-12-01

    We present a stochastic model of gait rhythm dynamics, based on transitions between different “neural centers”, that reproduces distinctive statistical properties of normal human walking. By tuning one model parameter, the transition (hopping) range, the model can describe alterations in gait dynamics from childhood to adulthood-including a decrease in the correlation and volatility exponents with maturation. The model also generates time series with multifractal spectra whose broadness depends only on this parameter. Moreover, we find that the volatility exponent increases monotonically as a function of the width of the multifractal spectrum, suggesting the possibility of a change in multifractality with maturation.

  6. Integration of Dynamic Models in Range Operations

    NASA Technical Reports Server (NTRS)

    Bardina, Jorge; Thirumalainambi, Rajkumar

    2004-01-01

    This work addresses the various model interactions in real-time to make an efficient internet based decision making tool for Shuttle launch. The decision making tool depends on the launch commit criteria coupled with physical models. Dynamic interaction between a wide variety of simulation applications and techniques, embedded algorithms, and data visualizations are needed to exploit the full potential of modeling and simulation. This paper also discusses in depth details of web based 3-D graphics and applications to range safety. The advantages of this dynamic model integration are secure accessibility and distribution of real time information to other NASA centers.

  7. The Immuno-Dynamics of Conflict Intervention in Social Systems

    PubMed Central

    Krakauer, David C.; Page, Karen; Flack, Jessica

    2011-01-01

    We present statistical evidence and dynamical models for the management of conflict and a division of labor (task specialization) in a primate society. Two broad intervention strategy classes are observed– a dyadic strategy – pacifying interventions, and a triadic strategy –policing interventions. These strategies, their respective degrees of specialization, and their consequences for conflict dynamics can be captured through empirically-grounded mathematical models inspired by immuno-dynamics. The spread of aggression, analogous to the proliferation of pathogens, is an epidemiological problem. We show analytically and computationally that policing is an efficient strategy as it requires only a small proportion of a population to police to reduce conflict contagion. Policing, but not pacifying, is capable of effectively eliminating conflict. These results suggest that despite implementation differences there might be universal features of conflict management mechanisms for reducing contagion-like dynamics that apply across biological and social levels. Our analyses further suggest that it can be profitable to conceive of conflict management strategies at the behavioral level as mechanisms of social immunity. PMID:21887221

  8. Multi-scale modelling and dynamics

    NASA Astrophysics Data System (ADS)

    Müller-Plathe, Florian

    Moving from a fine-grained particle model to one of lower resolution leads, with few exceptions, to an acceleration of molecular mobility, higher diffusion coefficient, lower viscosities and more. On top of that, the level of acceleration is often different for different dynamical processes as well as for different state points. While the reasons are often understood, the fact that coarse-graining almost necessarily introduces unpredictable acceleration of the molecular dynamics severely limits its usefulness as a predictive tool. There are several attempts under way to remedy these shortcoming of coarse-grained models. On the one hand, we follow bottom-up approaches. They attempt already when the coarse-graining scheme is conceived to estimate their impact on the dynamics. This is done by excess-entropy scaling. On the other hand, we also pursue a top-down development. Here we start with a very coarse-grained model (dissipative particle dynamics) which in its native form produces qualitatively wrong polymer dynamics, as its molecules cannot entangle. This model is modified by additional temporary bonds, so-called slip springs, to repair this defect. As a result, polymer melts and solutions described by the slip-spring DPD model show correct dynamical behaviour. Read more: ``Excess entropy scaling for the segmental and global dynamics of polyethylene melts'', E. Voyiatzis, F. Müller-Plathe, and M.C. Böhm, Phys. Chem. Chem. Phys. 16, 24301-24311 (2014). [DOI: 10.1039/C4CP03559C] ``Recovering the Reptation Dynamics of Polymer Melts in Dissipative Particle Dynamics Simulations via Slip-Springs'', M. Langeloth, Y. Masubuchi, M. C. Böhm, and F. Müller-Plathe, J. Chem. Phys. 138, 104907 (2013). [DOI: 10.1063/1.4794156].

  9. Dynamic landscape models of coevolutionary games.

    PubMed

    Richter, Hendrik

    2017-02-24

    Players of coevolutionary games may update not only their strategies but also their networks of interaction. Based on interpreting the payoff of players as fitness, dynamic landscape models are proposed. The modeling procedure is carried out for Prisoner's Dilemma (PD) and Snowdrift (SD) games that both use either birth-death (BD) or death-birth (DB) strategy updating. The main focus is on using dynamic fitness landscapes as a mathematical model of coevolutionary game dynamics. Hence, an alternative tool for analyzing coevolutionary games becomes available, and landscape measures such as modality, ruggedness and information content can be computed and analyzed. In addition, fixation properties of the games and quantifiers characterizing the interaction networks are calculated numerically. Relations are established between landscape properties expressed by landscape measures and quantifiers of coevolutionary game dynamics such as fixation probabilities, fixation times and network properties.

  10. Uncertainty and Sensitivity in Surface Dynamics Modeling

    NASA Astrophysics Data System (ADS)

    Kettner, Albert J.; Syvitski, James P. M.

    2016-05-01

    Papers for this special issue on 'Uncertainty and Sensitivity in Surface Dynamics Modeling' heralds from papers submitted after the 2014 annual meeting of the Community Surface Dynamics Modeling System or CSDMS. CSDMS facilitates a diverse community of experts (now in 68 countries) that collectively investigate the Earth's surface-the dynamic interface between lithosphere, hydrosphere, cryosphere, and atmosphere, by promoting, developing, supporting and disseminating integrated open source software modules. By organizing more than 1500 researchers, CSDMS has the privilege of identifying community strengths and weaknesses in the practice of software development. We recognize, for example, that progress has been slow on identifying and quantifying uncertainty and sensitivity in numerical modeling of earth's surface dynamics. This special issue is meant to raise awareness for these important subjects and highlight state-of-the-art progress.

  11. Energy Balance Models and Planetary Dynamics

    NASA Technical Reports Server (NTRS)

    Domagal-Goldman, Shawn

    2012-01-01

    We know that planetary dynamics can have a significant affect on the climate of planets. Planetary dynamics dominate the glacial-interglacial periods on Earth, leaving a significant imprint on the geological record. They have also been demonstrated to have a driving influence on the climates of other planets in our solar system. We should therefore expect th.ere to be similar relationships on extrasolar planets. Here we describe a simple energy balance model that can predict the growth and thickness of glaciers, and their feedbacks on climate. We will also describe model changes that we have made to include planetary dynamics effects. This is the model we will use at the start of our collaboration to handle the influence of dynamics on climate.

  12. Dynamic stiffness model of spherical parallel robots

    NASA Astrophysics Data System (ADS)

    Cammarata, Alessandro; Caliò, Ivo; D`Urso, Domenico; Greco, Annalisa; Lacagnina, Michele; Fichera, Gabriele

    2016-12-01

    A novel approach to study the elastodynamics of Spherical Parallel Robots is described through an exact dynamic model. Timoshenko arches are used to simulate flexible curved links while the base and mobile platforms are modelled as rigid bodies. Spatial joints are inherently included into the model without Lagrangian multipliers. At first, the equivalent dynamic stiffness matrix of each leg, made up of curved links joined by spatial joints, is derived; then these matrices are assembled to obtain the Global Dynamic Stiffness Matrix of the robot at a given pose. Actuator stiffness is also included into the model to verify its influence on vibrations and modes. The latter are found by applying the Wittrick-Williams algorithm. Finally, numerical simulations and direct comparison to commercial FE results are used to validate the proposed model.

  13. Dynamic centrifugal compressor model for system simulation

    NASA Astrophysics Data System (ADS)

    Jiang, Wei; Khan, Jamil; Dougal, Roger A.

    A dynamic model of a centrifugal compressor capable of system simulation in the virtual test bed (VTB) computational environment is presented. The model is based on first principles, i.e. the dynamic performance including the losses is determined from the compressor geometry and not from the experimentally determined characteristic performance curves. In this study, the compressor losses, such as incidence and friction losses, etc., are mathematically modeled for developing compressor characteristics. For easy implementation in the VTB platform, the non-linear governing equations are discretized in resistive companion (RC) form. The developed simulation model can be applied to virtually any centrifugal compressor. By interfacing with a composite system, such as a Brayton cycle gas turbine, or a fuel cell, the compressor dynamic performance can be evaluated. The surge line for the compressor can also be determined from the simulation results. Furthermore, the model presented here provides a valuable tool for evaluating the system performance as a function of various operating parameters.

  14. Modeling cell shape and dynamics on micropatterns

    PubMed Central

    Albert, Philipp J.; Schwarz, Ulrich S.

    2016-01-01

    ABSTRACT Adhesive micropatterns have become a standard tool to study cells under defined conditions. Applications range from controlling the differentiation and fate of single cells to guiding the collective migration of cell sheets. In long-term experiments, single cell normalization is challenged by cell division. For all of these setups, mathematical models predicting cell shape and dynamics can guide pattern design. Here we review recent advances in predicting and explaining cell shape, traction forces and dynamics on micropatterns. Starting with contour models as the simplest approach to explain concave cell shapes, we move on to network and continuum descriptions as examples for static models. To describe dynamic processes, cellular Potts, vertex and phase field models can be used. Different types of model are appropriate to address different biological questions and together, they provide a versatile tool box to predict cell behavior on micropatterns. PMID:26838278

  15. Integrated dynamics modeling for supercavitating vehicle systems

    NASA Astrophysics Data System (ADS)

    Kim, Seonhong; Kim, Nakwan

    2015-06-01

    We have performed integrated dynamics modeling for a supercavitating vehicle. A 6-DOF equation of motion was constructed by defining the forces and moments acting on the supercavitating body surface that contacted water. The wetted area was obtained by calculating the cavity size and axis. Cavity dynamics were determined to obtain the cavity profile for calculating the wetted area. Subsequently, the forces and moments acting on each wetted part-the cavitator, fins, and vehicle body-were obtained by physical modeling. The planing force-the interaction force between the vehicle transom and cavity wall-was calculated using the apparent mass of the immersed vehicle transom. We integrated each model and constructed an equation of motion for the supercavitating system. We performed numerical simulations using the integrated dynamics model to analyze the characteristics of the supercavitating system and validate the modeling completeness. Our research enables the design of high-quality controllers and optimal supercavitating systems.

  16. Stirling Engine Dynamic System Modeling

    NASA Technical Reports Server (NTRS)

    Nakis, Christopher G.

    2004-01-01

    The Thermo-Mechanical systems branch at the Glenn Research Center focuses a large amount time on Stirling engines. These engines will be used on missions where solar power is inefficient, especially in deep space. I work with Tim Regan and Ed Lewandowski who are currently developing and validating a mathematical model for the Stirling engines. This model incorporates all aspects of the system including, mechanical, electrical and thermodynamic components. Modeling is done through Simplorer, a program capable of running simulations of the model. Once created and then proven to be accurate, a model is used for developing new ideas for engine design. My largest specific project involves varying key parameters in the model and quantifying the results. This can all be done relatively trouble-free with the help of Simplorer. Once the model is complete, Simplorer will do all the necessary calculations. The more complicated part of this project is determining which parameters to vary. Finding key parameters depends on the potential for a value to be independently altered in the design. For example, a change in one dimension may lead to a proportional change to the rest of the model, and no real progress is made. Also, the ability for a changed value to have a substantial impact on the outputs of the system is important. Results will be condensed into graphs and tables with the purpose of better communication and understanding of the data. With the changing of these parameters, a more optimal design can be created without having to purchase or build any models. Also, hours and hours of results can be simulated in minutes. In the long run, using mathematical models can save time and money. Along with this project, I have many other smaller assignments throughout the summer. My main goal is to assist in the processes of model development, validation and testing.

  17. Stirling Engine Dynamic System Modeling

    NASA Technical Reports Server (NTRS)

    Nakis, Christopher G.

    2004-01-01

    The Thermo-Mechanical systems branch at the Glenn Research Center focuses a large amount time on Stirling engines. These engines will be used on missions where solar power is inefficient, especially in deep space. I work with Tim Regan and Ed Lewandowski who are currently developing and validating a mathematical model for the Stirling engines. This model incorporates all aspects of the system including, mechanical, electrical and thermodynamic components. Modeling is done through Simplorer, a program capable of running simulations of the model. Once created and then proven to be accurate, a model is used for developing new ideas for engine design. My largest specific project involves varying key parameters in the model and quantifying the results. This can all be done relatively trouble-free with the help of Simplorer. Once the model is complete, Simplorer will do all the necessary calculations. The more complicated part of this project is determining which parameters to vary. Finding key parameters depends on the potential for a value to be independently altered in the design. For example, a change in one dimension may lead to a proportional change to the rest of the model, and no real progress is made. Also, the ability for a changed value to have a substantial impact on the outputs of the system is important. Results will be condensed into graphs and tables with the purpose of better communication and understanding of the data. With the changing of these parameters, a more optimal design can be created without having to purchase or build any models. Also, hours and hours of results can be simulated in minutes. In the long run, using mathematical models can save time and money. Along with this project, I have many other smaller assignments throughout the summer. My main goal is to assist in the processes of model development, validation and testing.

  18. Haptics-based dynamic implicit solid modeling.

    PubMed

    Hua, Jing; Qin, Hong

    2004-01-01

    This paper systematically presents a novel, interactive solid modeling framework, Haptics-based Dynamic Implicit Solid Modeling, which is founded upon volumetric implicit functions and powerful physics-based modeling. In particular, we augment our modeling framework with a haptic mechanism in order to take advantage of additional realism associated with a 3D haptic interface. Our dynamic implicit solids are semi-algebraic sets of volumetric implicit functions and are governed by the principles of dynamics, hence responding to sculpting forces in a natural and predictable manner. In order to directly manipulate existing volumetric data sets as well as point clouds, we develop a hierarchical fitting algorithm to reconstruct and represent discrete data sets using our continuous implicit functions, which permit users to further design and edit those existing 3D models in real-time using a large variety of haptic and geometric toolkits, and visualize their interactive deformation at arbitrary resolution. The additional geometric and physical constraints afford more sophisticated control of the dynamic implicit solids. The versatility of our dynamic implicit modeling enables the user to easily modify both the geometry and the topology of modeled objects, while the inherent physical properties can offer an intuitive haptic interface for direct manipulation with force feedback.

  19. Synaptic dynamics: linear model and adaptation algorithm.

    PubMed

    Yousefi, Ali; Dibazar, Alireza A; Berger, Theodore W

    2014-08-01

    In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neural stimuli. Temporal dynamics in neural models with dynamic synapses will be analyzed, and learning algorithms for synaptic adaptation of neural networks with hundreds of synaptic connections are proposed. The paper starts by introducing a linear approximate model for the temporal dynamics of synaptic transmission. The proposed linear model substantially simplifies the analysis and training of spiking neural networks. Furthermore, it is capable of replicating the synaptic response of the non-linear facilitation-depression model with an accuracy better than 92.5%. In the second part of the paper, a supervised spike-in-spike-out learning rule for synaptic adaptation in dynamic synapse neural networks (DSNN) is proposed. The proposed learning rule is a biologically plausible process, and it is capable of simultaneously adjusting both pre- and post-synaptic components of individual synapses. The last section of the paper starts with presenting the rigorous analysis of the learning algorithm in a system identification task with hundreds of synaptic connections which confirms the learning algorithm's accuracy, repeatability and scalability. The DSNN is utilized to predict the spiking activity of cortical neurons and pattern recognition tasks. The DSNN model is demonstrated to be a generative model capable of producing different cortical neuron spiking patterns and CA1 Pyramidal neurons recordings. A single-layer DSNN classifier on a benchmark pattern recognition task outperforms a 2-Layer Neural Network and GMM classifiers while having fewer numbers of free parameters and

  20. Dynamics modeling and simulation of flexible airships

    NASA Astrophysics Data System (ADS)

    Li, Yuwen

    The resurgence of airships has created a need for dynamics models and simulation capabilities of these lighter-than-air vehicles. The focus of this thesis is a theoretical framework that integrates the flight dynamics, structural dynamics, aerostatics and aerodynamics of flexible airships. The study begins with a dynamics model based on a rigid-body assumption. A comprehensive computation of aerodynamic effects is presented, where the aerodynamic forces and moments are categorized into various terms based on different physical effects. A series of prediction approaches for different aerodynamic effects are unified and applied to airships. The numerical results of aerodynamic derivatives and the simulated responses to control surface deflection inputs are verified by comparing to existing wind-tunnel and flight test data. With the validated aerodynamics and rigid-body modeling, the equations of motion of an elastic airship are derived by the Lagrangian formulation. The airship is modeled as a free-free Euler-Bernoulli beam and the bending deformations are represented by shape functions chosen as the free-free normal modes. In order to capture the coupling between the aerodynamic forces and the structural elasticity, local velocity on the deformed vehicle is used in the computation of aerodynamic forces. Finally, with the inertial, gravity, aerostatic and control forces incorporated, the dynamics model of a flexible airship is represented by a single set of nonlinear ordinary differential equations. The proposed model is implemented as a dynamics simulation program to analyze the dynamics characteristics of the Skyship-500 airship. Simulation results are presented to demonstrate the influence of structural deformation on the aerodynamic forces and the dynamics behavior of the airship. The nonlinear equations of motion are linearized numerically for the purpose of frequency domain analysis and for aeroelastic stability analysis. The results from the latter for the

  1. Agent-Based Crowd Simulation Considering Emotion Contagion for Emergency Evacuation Problem

    NASA Astrophysics Data System (ADS)

    Faroqi, H.; Mesgari, M.-S.

    2015-12-01

    During emergencies, emotions greatly affect human behaviour. For more realistic multi-agent systems in simulations of emergency evacuations, it is important to incorporate emotions and their effects on the agents. In few words, emotional contagion is a process in which a person or group influences the emotions or behavior of another person or group through the conscious or unconscious induction of emotion states and behavioral attitudes. In this study, we simulate an emergency situation in an open square area with three exits considering Adults and Children agents with different behavior. Also, Security agents are considered in order to guide Adults and Children for finding the exits and be calm. Six levels of emotion levels are considered for each agent in different scenarios and situations. The agent-based simulated model initialize with the random scattering of agent populations and then when an alarm occurs, each agent react to the situation based on its and neighbors current circumstances. The main goal of each agent is firstly to find the exit, and then help other agents to find their ways. Numbers of exited agents along with their emotion levels and damaged agents are compared in different scenarios with different initialization in order to evaluate the achieved results of the simulated model. NetLogo 5.2 is used as the multi-agent simulation framework with R language as the developing language.

  2. Homophily and contagion as explanations for weight similarities among adolescent friends.

    PubMed

    de la Haye, Kayla; Robins, Garry; Mohr, Philip; Wilson, Carlene

    2011-10-01

    To determine whether weight-based similarities among adolescent friends result from social influence processes, after controlling for the role of weight on friendship selection and other confounding influences. Four waves of data were collected from a grade 8 cohort of adolescents (N = 156, mean age = 13.6 years) over their initial 2 years of high school. At each wave, participants reported on their friendship relations with grade-mates and had their height and weight measured by researchers to calculate their body mass index (BMI). Newly developed stochastic actor-oriented models for social networks were used to simultaneously assess the role of weight on adolescents' friendship choices, and the effect of friends' BMIs on changes in adolescent BMI. Adolescents' BMIs were not significantly predicted by the BMI of their friends over the 16 months of this study. Similarities in the weights of friends were found to be driven predominantly by friendship selection, whereby adolescents, particularly those who were not overweight, preferred to initiate friendships with peers whose weight status (overweight/nonoverweight) was the same as their own. Weight-based similarities among friends were largely explained by the marginalization of overweight adolescents by their peers, rather than by the "contagion" of excess weight among friends. These findings highlight the importance of adequately modeling friendship selection processes when estimating social influence effects on adiposity. Copyright © 2011 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  3. Interest contagion in violation-of-expectation-based false-belief tasks.

    PubMed

    Falck, Andreas; Brinck, Ingar; Lindgren, Magnus

    2014-01-01

    In the debate about how to interpret Violation-of-Expectation (VoE) based false-belief experiments, it has been suggested that infants are predicting the actions of the agent based on more or less sophisticated cognitive means. We present an alternative, more parsimonious interpretation, exploring the possibility that the infants' reactions are not governed by rational expectation but rather of memory strength due to differences in the allocation of cognitive resources earlier in the experiment. Specifically, it is argued that (1) infants' have a tendency to find more interest in events that observed agents are attending to as opposed to unattended events ("interest contagion"), (2) the object-location configurations that result from such interesting events are remembered more strongly by the infants, and (3) the VoE contrast arises as a consequence of the difference in memory strength between more and less interesting object-location configurations. We discuss two published experiments, one which we argue that our model can explain (Kovács etal., 2010), and one which we argue cannot be readily explained by our model (Onishi and Baillargeon, 2005).

  4. The Impact of Heterogeneous Thresholds on Social Contagion with Multiple Initiators

    PubMed Central

    Karampourniotis, Panagiotis D.; Sreenivasan, Sameet; Szymanski, Boleslaw K.; Korniss, Gyorgy

    2015-01-01

    The threshold model is a simple but classic model of contagion spreading in complex social systems. To capture the complex nature of social influencing we investigate numerically and analytically the transition in the behavior of threshold-limited cascades in the presence of multiple initiators as the distribution of thresholds is varied between the two extreme cases of identical thresholds and a uniform distribution. We accomplish this by employing a truncated normal distribution of the nodes’ thresholds and observe a non-monotonic change in the cascade size as we vary the standard deviation. Further, for a sufficiently large spread in the threshold distribution, the tipping-point behavior of the social influencing process disappears and is replaced by a smooth crossover governed by the size of initiator set. We demonstrate that for a given size of the initiator set, there is a specific variance of the threshold distribution for which an opinion spreads optimally. Furthermore, in the case of synthetic graphs we show that the spread asymptotically becomes independent of the system size, and that global cascades can arise just by the addition of a single node to the initiator set. PMID:26571486

  5. Experimental evidence of massive-scale emotional contagion through social networks.

    PubMed

    Kramer, Adam D I; Guillory, Jamie E; Hancock, Jeffrey T

    2014-06-17

    Emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. Emotional contagion is well established in laboratory experiments, with people transferring positive and negative emotions to others. Data from a large real-world social network, collected over a 20-y period suggests that longer-lasting moods (e.g., depression, happiness) can be transferred through networks [Fowler JH, Christakis NA (2008) BMJ 337:a2338], although the results are controversial. In an experiment with people who use Facebook, we test whether emotional contagion occurs outside of in-person interaction between individuals by reducing the amount of emotional content in the News Feed. When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred. These results indicate that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale contagion via social networks. This work also suggests that, in contrast to prevailing assumptions, in-person interaction and nonverbal cues are not strictly necessary for emotional contagion, and that the observation of others' positive experiences constitutes a positive experience for people.

  6. Experimental evidence of massive-scale emotional contagion through social networks

    PubMed Central

    Kramer, Adam D. I.; Guillory, Jamie E.; Hancock, Jeffrey T.

    2014-01-01

    Emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. Emotional contagion is well established in laboratory experiments, with people transferring positive and negative emotions to others. Data from a large real-world social network, collected over a 20-y period suggests that longer-lasting moods (e.g., depression, happiness) can be transferred through networks [Fowler JH, Christakis NA (2008) BMJ 337:a2338], although the results are controversial. In an experiment with people who use Facebook, we test whether emotional contagion occurs outside of in-person interaction between individuals by reducing the amount of emotional content in the News Feed. When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred. These results indicate that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale contagion via social networks. This work also suggests that, in contrast to prevailing assumptions, in-person interaction and nonverbal cues are not strictly necessary for emotional contagion, and that the observation of others’ positive experiences constitutes a positive experience for people. PMID:24889601

  7. Emotional contagion for pain is intact in autism spectrum disorders

    PubMed Central

    Hadjikhani, N; Zürcher, N R; Rogier, O; Hippolyte, L; Lemonnier, E; Ruest, T; Ward, N; Lassalle, A; Gillberg, N; Billstedt, E; Helles, A; Gillberg, C; Solomon, P; Prkachin, K M; Gillberg, C

    2014-01-01

    Perceiving others in pain generally leads to empathic concern, consisting of both emotional and cognitive processes. Empathy deficits have been considered as an element contributing to social difficulties in individuals with autism spectrum disorders (ASD). Here, we used functional magnetic resonance imaging and short video clips of facial expressions of people experiencing pain to examine the neural substrates underlying the spontaneous empathic response to pain in autism. Thirty-eight adolescents and adults of normal intelligence diagnosed with ASD and 35 matched controls participated in the study. In contrast to general assumptions, we found no significant differences in brain activation between ASD individuals and controls during the perception of pain experienced by others. Both groups showed similar levels of activation in areas associated with pain sharing, evidencing the presence of emotional empathy and emotional contagion in participants with autism as well as in controls. Differences between groups could be observed at a more liberal statistical threshold, and revealed increased activations in areas involved in cognitive reappraisal in ASD participants compared with controls. Scores of emotional empathy were positively correlated with brain activation in areas involved in embodiment of pain in ASD group only. Our findings show that simulation mechanisms involved in emotional empathy are preserved in high-functioning individuals with autism, and suggest that increased reappraisal may have a role in their apparent lack of caring behavior. PMID:24424389

  8. Pupillary Contagion in Infancy: Evidence for Spontaneous Transfer of Arousal.

    PubMed

    Fawcett, Christine; Wesevich, Victoria; Gredebäck, Gustaf

    2016-07-01

    Pupillary contagion-responding to pupil size observed in other people with changes in one's own pupil-has been found in adults and suggests that arousal and other internal states could be transferred across individuals using a subtle physiological cue. Examining this phenomenon developmentally gives insight into its origins and underlying mechanisms, such as whether it is an automatic adaptation already present in infancy. In the current study, 6- and 9-month-olds viewed schematic depictions of eyes with smaller and larger pupils-pairs of concentric circles with smaller and larger black centers-while their own pupil sizes were recorded. Control stimuli were comparable squares. For both age groups, infants' pupil size was greater when they viewed large-center circles than when they viewed small-center circles, and no differences were found for large-center compared with small-center squares. The findings suggest that infants are sensitive and responsive to subtle cues to other people's internal states, a mechanism that would be beneficial for early social development. © The Author(s) 2016.

  9. Component testing for dynamic model verification

    NASA Technical Reports Server (NTRS)

    Hasselman, T. K.; Chrostowski, J. D.

    1984-01-01

    Dynamic model verification is the process whereby an analytical model of a dynamic system is compared with experimental data, adjusted if necessary to bring it into agreement with the data, and then qualified for future use in predicting system response in a different dynamic environment. These are various ways to conduct model verification. The approach taken here employs Bayesian statistical parameter estimation. Unlike curve fitting, whose objective is to minimize the difference between some analytical function and a given quantity of test data (or curve), Bayesian estimation attempts also to minimize the difference between the parameter values of that funciton (the model) and their initial estimates, in a least squares sense. The objectives of dynamic model verification, therefore, are to produce a model which: (1) is in agreement with test data; (2) will assist in the interpretation of test data; (3) can be used to help verify a design; (4) will reliably predict performance; and (5) in the case of space structures, will facilitate dynamic control.

  10. Modeling Dynamic Regulatory Processes in Stroke.

    SciTech Connect

    McDermott, Jason E.; Jarman, Kenneth D.; Taylor, Ronald C.; Lancaster, Mary J.; Shankaran, Harish; Vartanian, Keri B.; Stevens, S.L.; Stenzel-Poore, Mary; Sanfilippo, Antonio P.

    2012-10-11

    The ability to examine in silico the behavior of biological systems can greatly accelerate the pace of discovery in disease pathologies, such as stroke, where in vivo experimentation is lengthy and costly. In this paper we describe an approach to in silico examination of blood genomic responses to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) relating regulators and functional clusters from the data. These ODEs were used to develop dynamic models that simulate the expression of regulated functional clusters using system dynamics as the modeling paradigm. The dynamic model has the considerable advantage of only requiring an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. The manipulation of input model parameters, such as changing the magnitude of gene expression, made it possible to assess the behavior of the networks through time under varying conditions. We report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different preconditioning paradigms.

  11. Dynamical modeling of laser ablation processes

    SciTech Connect

    Leboeuf, J.N.; Chen, K.R.; Donato, J.M.; Geohegan, D.B.; Liu, C.L.; Puretzky, A.A.; Wood, R.F.

    1995-09-01

    Several physics and computational approaches have been developed to globally characterize phenomena important for film growth by pulsed laser deposition of materials. These include thermal models of laser-solid target interactions that initiate the vapor plume; plume ionization and heating through laser absorption beyond local thermodynamic equilibrium mechanisms; gas dynamic, hydrodynamic, and collisional descriptions of plume transport; and molecular dynamics models of the interaction of plume particles with the deposition substrate. The complexity of the phenomena involved in the laser ablation process is matched by the diversity of the modeling task, which combines materials science, atomic physics, and plasma physics.

  12. Dynamical modelling of coordinated multiple robot systems

    NASA Technical Reports Server (NTRS)

    Hayati, Samad

    1987-01-01

    The state of the art in the modeling of the dynamics of coordinated multiple robot manipulators is summarized and various problems related to this subject are discussed. It is recognized that dynamics modeling is a component used in the design of controllers for multiple cooperating robots. As such, the discussion addresses some problems related to the control of multiple robots. The techniques used to date in the modeling of closed kinematic chains are summarized. Various efforts made to date for the control of coordinated multiple manipulators is summarized.

  13. Dynamics Simulation Model for Space Tethers

    NASA Technical Reports Server (NTRS)

    Levin, E. M.; Pearson, J.; Oldson, J. C.

    2006-01-01

    This document describes the development of an accurate model for the dynamics of the Momentum Exchange Electrodynamic Reboost (MXER) system. The MXER is a rotating tether about 100-km long in elliptical Earth orbit designed to catch payloads in low Earth orbit and throw them to geosynchronous orbit or to Earth escape. To ensure successful rendezvous between the MXER tip catcher and a payload, a high-fidelity model of the system dynamics is required. The model developed here quantifies the major environmental perturbations, and can predict the MXER tip position to within meters over one orbit.

  14. A stochastic evolutionary model for survival dynamics

    NASA Astrophysics Data System (ADS)

    Fenner, Trevor; Levene, Mark; Loizou, George

    2014-09-01

    The recent interest in human dynamics has led researchers to investigate the stochastic processes that explain human behaviour in different contexts. Here we propose a generative model to capture the essential dynamics of survival analysis, traditionally employed in clinical trials and reliability analysis in engineering. In our model, the only implicit assumption made is that the longer an actor has been in the system, the more likely it is to have failed. We derive a power-law distribution for the process and provide preliminary empirical evidence for the validity of the model from two well-known survival analysis data sets.

  15. Dynamical effects of overparametrization in nonlinear models

    NASA Astrophysics Data System (ADS)

    Aguirre, Luis Antonio; Billings, S. A.

    1995-01-01

    This paper is concemed with dynamical reconstruction for nonlinear systems. The effects of the driving function and of the complexity of a given representation on the bifurcation patter are investigated. It is shown that the use of different driving functions to excite the system may yield models with different bifurcation patterns. The complexity of the reconstructions considered is quantified by the embedding dimension and the number of estimated parameters. In this respect it appears that models which reproduce the original bifurcation behaviour are of limited complexity and that excessively complex models tend to induce ghost bifurcations and spurious dynamical regimes. Moreover, some results suggest that the effects of overparametrization on the global dynamical behaviour of a nonlinear model may be more deleterious than the presence of moderate noise levels. In order to precisely quantify the complexity of the reconstructions, global polynomials are used although the results are believed to apply to a much wider class of representations including neural networks.

  16. A system dynamics model for communications networks

    NASA Astrophysics Data System (ADS)

    Awcock, A. J.; King, T. E. G.

    1985-09-01

    An abstract model of a communications network in system dynamics terminology is developed as implementation of this model by a FORTRAN program package developed at RSRE is discussed. The result of this work is a high-level simulation package in which the performance of adaptive routing algorithms and other network controls may be assessed for a network of arbitrary topology.

  17. Magnetospheric dynamics from a low-dimensional nonlinear dynamics model

    NASA Astrophysics Data System (ADS)

    Doxas, I.; Horton, W.

    1999-05-01

    A physics based model for the coupled solar WIND-Magnetosphere-Ionosphere system (WINDMI) is described. The model is based on truncated descriptions of the collisionless microscopic energy transfer processes occurring in the quasineutral layer, and includes a thermal flux limit neglected in the Magnetohydrodynamic (MHD) closure of the moment equations. All dynamically relevant parameters of the model can be computed analytically. The system is both Kirchhoffian and Hamiltonian, ensuring that the power input from the solar wind is divided into physically realizable energy sub-components, a property not shared by data-based filters. The model provides a consistent mathematical formalism in which different models of the solar wind driver, ionospheric dissipation, global field configuration, and substorm trigger mechanism can be inserted, and the coupling between the different parts of the system investigated.

  18. Adaptation dynamics of the quasispecies model

    NASA Astrophysics Data System (ADS)

    Jain, Kavita

    2009-02-01

    We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen's model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a {\\it quasispecies} which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.

  19. A dynamical model for the Utricularia trap

    PubMed Central

    Llorens, Coraline; Argentina, Médéric; Bouret, Yann; Marmottant, Philippe; Vincent, Olivier

    2012-01-01

    We propose a model that captures the dynamics of a carnivorous plant, Utricularia inflata. This plant possesses tiny traps for capturing small aquatic animals. Glands pump water out of the trap, yielding a negative pressure difference between the plant and its surroundings. The trap door is set into a meta-stable state and opens quickly as an extra pressure is generated by the displacement of a potential prey. As the door opens, the pressure difference sucks the animal into the trap. We write an ODE model that captures all the physics at play. We show that the dynamics of the plant is quite similar to neuronal dynamics and we analyse the effect of a white noise on the dynamics of the trap. PMID:22859569

  20. Automated dynamic analytical model improvement

    NASA Technical Reports Server (NTRS)

    Berman, A.

    1981-01-01

    A method is developed and illustrated which finds minimum changes in analytical mass and stiffness matrices to make them consistent with a set of measured normal modes and natural frequencies. The corrected model is an improved base for studies of physical changes, changes in boundary conditions, and for prediction of forced responses. Features of the method are: efficient procedures not requiring solutions of the eigenproblem; the model may have more degrees of freedom than the test data; modal displacements at all the analytical degrees of freedom are obtained; the frequency dependence of the coordinate transformations are properly treated.

  1. Session 6: Dynamic Modeling and Systems Analysis

    NASA Technical Reports Server (NTRS)

    Csank, Jeffrey; Chapman, Jeffryes; May, Ryan

    2013-01-01

    These presentations cover some of the ongoing work in dynamic modeling and dynamic systems analysis. The first presentation discusses dynamic systems analysis and how to integrate dynamic performance information into the systems analysis. The ability to evaluate the dynamic performance of an engine design may allow tradeoffs between the dynamic performance and operability of a design resulting in a more efficient engine design. The second presentation discusses the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a Simulation system with a library containing the basic building blocks that can be used to create dynamic Thermodynamic Systems. Some of the key features include Turbo machinery components, such as turbines, compressors, etc., and basic control system blocks. T-MAT is written in the Matlab-Simulink environment and is open source software. The third presentation focuses on getting additional performance from the engine by allowing the limit regulators only to be active when a limit is danger of being violated. Typical aircraft engine control architecture is based on MINMAX scheme, which is designed to keep engine operating within prescribed mechanical/operational safety limits. Using a conditionally active min-max limit regulator scheme, additional performance can be gained by disabling non-relevant limit regulators

  2. Modeling hybrid perovskites by molecular dynamics.

    PubMed

    Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia

    2017-02-01

    The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.

  3. Modeling hybrid perovskites by molecular dynamics

    NASA Astrophysics Data System (ADS)

    Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia

    2017-02-01

    The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.

  4. Dispersive models describing mosquitoes’ population dynamics

    NASA Astrophysics Data System (ADS)

    Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.

    2016-08-01

    The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.

  5. Dynamical Modeling of Surface Tension

    NASA Technical Reports Server (NTRS)

    Brackbill, Jeremiah U.; Kothe, Douglas B.

    1996-01-01

    In a recent review it is said that free-surface flows 'represent some of the difficult remaining challenges in computational fluid dynamics'. There has been progress with the development of new approaches to treating interfaces, such as the level-set method and the improvement of older methods such as the VOF method. A common theme of many of the new developments has been the regularization of discontinuities at the interface. One example of this approach is the continuum surface force (CSF) formulation for surface tension, which replaces the surface stress given by Laplace's equation by an equivalent volume force. Here, we describe how CSF formulation might be made more useful. Specifically, we consider a derivation of the CSF equations from a minimization of surface energy as outlined by Jacqmin (1996). This reformulation suggests that if one eliminates the computation of curvature in terms of a unit normal vector, parasitic currents may be eliminated. For this reformulation to work, it is necessary that transition region thickness be controlled. Various means for this, in addition to the one discussed by Jacqmin (1996), are discussed.

  6. Modelling Martian surface channel dynamics

    NASA Astrophysics Data System (ADS)

    Coulthard, T. J.; Skinner, C.; Kim, J.; Schumann, G.; Neal, J. C.; Bates, P. D.

    2014-12-01

    Extensive and large surface channel features found at Athabasca and Kasei have previously been attributed to the erosional power of flowing water with palaeoflood discharges being estimated from the surface channel dimensions. However, in order for these channels to be alluvial there are several basic questions to be answered. Are water flows under Martian conditions capable of eroding the amounts of sediment required to leave these channels? Are our present estimates of palaeoflood discharge of correct magnitude to carry out this erosion? And are the channels a product of one or many flood events? Here, we use a numerical model (CAESAR-Lisflood) that links a two-dimensional hydrodynamic flow scheme to a sediment transport model to simulate fluvial morphodynamics in the Athabasca and Kasei regions. CAESAR-Lisflood has been successfully applied to simulating flooding, erosion and deposition on Earth in a number of locations, and allows the development of channels, bars, braids and other fluvial features to be modelled. The numerical scheme of the model was adapted to Martian conditions by adjusting gravity, drag co-efficient, roughness and grainsize terms. Preliminary findings indicate that fluvial erosion and deposition is capable of creating mega channel features found at these sites and that existing palaeflood estimates are commensurate with channel forming discharges for these features.

  7. Predicting dynamic topography from mantle circulation models

    NASA Astrophysics Data System (ADS)

    Webb, Peter; Davies, J. Huw

    2013-04-01

    Dynamic topography is anomalous vertical motions of Earth's surface associated with viscous flow in the mantle. Deformable boundaries, such as the surface, CMB and phase transition boundaries, within a fluid (Earth's mantle) are deflected by viscous flow. Denser than average, sinking mantle creates inward deflections of Earth's surface. Equally, upwelling flow creates bulges in the surface; large plumes are commonly thought to produce superswells, such as the anomalously high elevation of Southern Africa. Dynamic topography appears to operate on a number of length scales. Mantle density anomalies estimated from seismic tomography indicate long wavelength dynamic topography at present day of around 2 km amplitude (e.g. Conrand & Husson, 2009) whilst continental scale studies suggest vertical motions of a few hundred metres. Furthermore, time scales must be an important factor to consider when assessing dynamic topography. Stable, dense lower mantle 'piles' may contribute to dynamic surface topography; as they appear stable over reasonably long time scales, long wavelength dynamic topography may be a fairly constant feature over the recent geological past. Shorter wavelength, smaller amplitude dynamic topography may be due to more transient features of mantle convection. Studies on a continental scale reveal shorter term changes in dynamic topography of the order of a few hundred metres (e.g. Roberts & White, 2010; Heine et al., 2010). Understanding dynamic topography is complicated by the fact it is difficult to observe as the signal is often masked by isostatic effects. We use forward mantle convection models with 300 million years of recent plate motion history as the surface boundary condition to generate a present day distribution of density anomalies associated with subducted lithosphere. From the modelled temperature and density fields we calculate the normal stress at or near the surface of the model. As the models generally have a free slip surface where no

  8. Modeling the Dynamics of Compromised Networks

    SciTech Connect

    Soper, B; Merl, D M

    2011-09-12

    Accurate predictive models of compromised networks would contribute greatly to improving the effectiveness and efficiency of the detection and control of network attacks. Compartmental epidemiological models have been applied to modeling attack vectors such as viruses and worms. We extend the application of these models to capture a wider class of dynamics applicable to cyber security. By making basic assumptions regarding network topology we use multi-group epidemiological models and reaction rate kinetics to model the stochastic evolution of a compromised network. The Gillespie Algorithm is used to run simulations under a worst case scenario in which the intruder follows the basic connection rates of network traffic as a method of obfuscation.

  9. Alternative models for cyclic lemming dynamics.

    PubMed

    Wang, Hao; Kuang, Yang

    2007-01-01

    Many natural population growths and interactions are affected by seasonal changes, suggesting that these natural population dynamics should be modeled by nonautonomous differential equations instead of autonomous differential equations. Through a series of carefully derived models of the well documented high-amplitude, large-period fluctuations of lemming populations, we argue that when appropriately formulated, autonomous differential equations may capture much of the desirable rich dynamics, such as the existence of a periodic solution with period and amplitude close to that of approximately periodic solutions produced by the more natural but mathematically daunt ing nonautonomous models. We start this series of models from the Barrow model, a well formulated model for the dynamics of food-lemming interaction at Point Barrow (Alaska, USA) with sufficient experimental data. Our work suggests that an autonomous system can indeed be a good approximation to the moss-lemming dynamics at Point Barrow. This, together with our bifurcation analysis, indicates that neither seasonal factors (expressed by time dependent moss growth rate and lemming death rate in the Barrow model) nor the moss growth rate and lemming death rate are the main culprits of the observed multi-year lemming cycles. We suspect that the main culprits may include high lemming predation rate, high lemming birth rate, and low lemming self-limitation rate.

  10. Translating psychological science: Highlighting the media's contribution to contagion in mass shootings: Comment on Kaslow (2015).

    PubMed

    Perrin, Paul B

    2016-01-01

    In her presidential address, N. J. Kaslow (see record 2015-33530-002) argued that psychologists have a responsibility to translate psychological science to the public and identifies various platforms for doing so. In this comment on her article, I advocate that psychology as a field immediately heed her call in the area of psychological science highlighting the media's contribution to contagion in mass shootings. I point out the psychological science documenting media contagion for suicide and mass shootings, the World Health Organization's (2008) guidelines for media in reporting suicide deaths to prevent that contagion, and discuss ways-based on Dr. Kaslow's suggestions-that psychologists can disseminate psychological science to prevent similar tragedies in the future. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  11. Nonlinear Dynamic Models in Advanced Life Support

    NASA Technical Reports Server (NTRS)

    Jones, Harry

    2002-01-01

    To facilitate analysis, ALS systems are often assumed to be linear and time invariant, but they usually have important nonlinear and dynamic aspects. Nonlinear dynamic behavior can be caused by time varying inputs, changes in system parameters, nonlinear system functions, closed loop feedback delays, and limits on buffer storage or processing rates. Dynamic models are usually cataloged according to the number of state variables. The simplest dynamic models are linear, using only integration, multiplication, addition, and subtraction of the state variables. A general linear model with only two state variables can produce all the possible dynamic behavior of linear systems with many state variables, including stability, oscillation, or exponential growth and decay. Linear systems can be described using mathematical analysis. Nonlinear dynamics can be fully explored only by computer simulations of models. Unexpected behavior is produced by simple models having only two or three state variables with simple mathematical relations between them. Closed loop feedback delays are a major source of system instability. Exceeding limits on buffer storage or processing rates forces systems to change operating mode. Different equilibrium points may be reached from different initial conditions. Instead of one stable equilibrium point, the system may have several equilibrium points, oscillate at different frequencies, or even behave chaotically, depending on the system inputs and initial conditions. The frequency spectrum of an output oscillation may contain harmonics and the sums and differences of input frequencies, but it may also contain a stable limit cycle oscillation not related to input frequencies. We must investigate the nonlinear dynamic aspects of advanced life support systems to understand and counter undesirable behavior.

  12. Continuous Time Dynamic Topic Models

    DTIC Science & Technology

    2008-06-20

    called topics, can be used to explain the observed collection. LDA is a probabilistic extension of latent semantic indexing (LSI) [5] and probabilistic... latent semantic indexing (pLSI) [11]. Owing to its formal generative semantics, LDA has been extended and applied to authorship [19], email [15...Steyvers. Probabilistic topic models. In Latent Semantic Analysis: A Road to Meaning. 2006. [9] T. L. Griffiths and M. Steyvers. Finding scientific

  13. Feature Extraction for Structural Dynamics Model Validation

    SciTech Connect

    Farrar, Charles; Nishio, Mayuko; Hemez, Francois; Stull, Chris; Park, Gyuhae; Cornwell, Phil; Figueiredo, Eloi; Luscher, D. J.; Worden, Keith

    2016-01-13

    As structural dynamics becomes increasingly non-modal, stochastic and nonlinear, finite element model-updating technology must adopt the broader notions of model validation and uncertainty quantification. For example, particular re-sampling procedures must be implemented to propagate uncertainty through a forward calculation, and non-modal features must be defined to analyze nonlinear data sets. The latter topic is the focus of this report, but first, some more general comments regarding the concept of model validation will be discussed.

  14. Information Dynamics in Networks: Models and Algorithms

    DTIC Science & Technology

    2016-09-13

    the economics and computer science communities . Such a model of externality is motivated by several factors: • The physical effect of the number of...Information Dynamics in Networks: Models and Algorithms In this project, we investigated how network structure interplays with higher level processes in...online social networks. We investigated the appropriateness of existing mathematical models for explaining the structure of retweet cascades on

  15. Dynamic river basin water quality model

    SciTech Connect

    Yearsley, J.

    1991-09-01

    RBM10 is a river basin model for simulating the dynamics of an aquatic ecosystem which has freely-flowing river reaches, river-run reservoirs, and vertically stratified reservoirs. An Eulerian viewpoint is adopted for solving the conservation equations for temperature, dissolved oxygen, nutrients, phytoplankton, bacteria and conservative constituents. The report describes the model development and the computer program which implements the mathematical model.

  16. Modelling and control of HIV dynamics.

    PubMed

    Landi, Alberto; Mazzoldi, Alberto; Andreoni, Chiara; Bianchi, Matteo; Cavallini, Andrea; Laurino, Marco; Ricotti, Leonardo; Iuliano, Rodolfo; Matteoli, Barbara; Ceccherini-Nelli, Luca

    2008-02-01

    Various models of HIV infection and evolution have been considered in the literature. This paper considers a variant of the Wodarz and Nowak mathematical model, adding "aggressiveness" as a new state variable in order to quantify the strength of the virus and its response to drugs. Although the model proposed is relatively simple, simulation results suggest that it may be useful in predicting the impact of the effectiveness of therapy on HIV dynamics.

  17. The dynamic model of enterprise revenue management

    NASA Astrophysics Data System (ADS)

    Mitsel, A. A.; Kataev, M. Yu; Kozlov, S. V.; Korepanov, K. V.

    2017-01-01

    The article presents the dynamic model of enterprise revenue management. This model is based on the quadratic criterion and linear control law. The model is founded on multiple regression that links revenues with the financial performance of the enterprise. As a result, optimal management is obtained so as to provide the given enterprise revenue, namely, the values of financial indicators that ensure the planned profit of the organization are acquired.

  18. Dynamic exponents for potts model cluster algorithms

    NASA Astrophysics Data System (ADS)

    Coddington, Paul D.; Baillie, Clive F.

    We have studied the Swendsen-Wang and Wolff cluster update algorithms for the Ising model in 2, 3 and 4 dimensions. The data indicate simple relations between the specific heat and the Wolff autocorrelations, and between the magnetization and the Swendsen-Wang autocorrelations. This implies that the dynamic critical exponents are related to the static exponents of the Ising model. We also investigate the possibility of similar relationships for the Q-state Potts model.

  19. Dynamic Model for Life History of Scyphozoa.

    PubMed

    Xie, Congbo; Fan, Meng; Wang, Xin; Chen, Ming

    2015-01-01

    A two-state life history model governed by ODEs is formulated to elucidate the population dynamics of jellyfish and to illuminate the triggering mechanism of its blooms. The polyp-medusa model admits trichotomous global dynamic scenarios: extinction, polyps survival only, and both survival. The population dynamics sensitively depend on several biotic and abiotic limiting factors such as substrate, temperature, and predation. The combination of temperature increase, substrate expansion, and predator diminishment acts synergistically to create a habitat that is more favorable for jellyfishes. Reducing artificial marine constructions, aiding predator populations, and directly controlling the jellyfish population would help to manage the jellyfish blooms. The theoretical analyses and numerical experiments yield several insights into the nature underlying the model and shed some new light on the general control strategy for jellyfish.

  20. Dynamic Model for Life History of Scyphozoa

    PubMed Central

    Xie, Congbo; Fan, Meng; Wang, Xin; Chen, Ming

    2015-01-01

    A two-state life history model governed by ODEs is formulated to elucidate the population dynamics of jellyfish and to illuminate the triggering mechanism of its blooms. The polyp-medusa model admits trichotomous global dynamic scenarios: extinction, polyps survival only, and both survival. The population dynamics sensitively depend on several biotic and abiotic limiting factors such as substrate, temperature, and predation. The combination of temperature increase, substrate expansion, and predator diminishment acts synergistically to create a habitat that is more favorable for jellyfishes. Reducing artificial marine constructions, aiding predator populations, and directly controlling the jellyfish population would help to manage the jellyfish blooms. The theoretical analyses and numerical experiments yield several insights into the nature underlying the model and shed some new light on the general control strategy for jellyfish. PMID:26114642

  1. A dynamic conceptual model of care planning.

    PubMed

    Elf, Marie; Poutilova, Maria; Ohrn, Kerstin

    2007-12-01

    This article presents a conceptual model of the care planning process developed to identify the hypothetical links between structural, process and outcome factors important to the quality of the process. Based on existing literature, it was hypothesized that a thorough assessment of patients' health needs is an important prerequisite when making a rigorous diagnosis and preparing plans for various care interventions. Other important variables that are assumed to influence the quality of the process are the care culture and professional knowledge. The conceptual model was developed as a system dynamics causal loop diagram as a first essential step towards a computed model. System dynamics offers the potential to describe processes in a nonlinear, dynamic way and is suitable for exploring, comprehending, learning and communicating complex ideas about care processes.

  2. Dynamic Smagorinsky model on anisotropic grids

    NASA Technical Reports Server (NTRS)

    Scotti, A.; Meneveau, C.; Fatica, M.

    1996-01-01

    Large Eddy Simulation (LES) of complex-geometry flows often involves highly anisotropic meshes. To examine the performance of the dynamic Smagorinsky model in a controlled fashion on such grids, simulations of forced isotropic turbulence are performed using highly anisotropic discretizations. The resulting model coefficients are compared with a theoretical prediction (Scotti et al., 1993). Two extreme cases are considered: pancake-like grids, for which two directions are poorly resolved compared to the third, and pencil-like grids, where one direction is poorly resolved when compared to the other two. For pancake-like grids the dynamic model yields the results expected from the theory (increasing coefficient with increasing aspect ratio), whereas for pencil-like grids the dynamic model does not agree with the theoretical prediction (with detrimental effects only on smallest resolved scales). A possible explanation of the departure is attempted, and it is shown that the problem may be circumvented by using an isotropic test-filter at larger scales. Overall, all models considered give good large-scale results, confirming the general robustness of the dynamic and eddy-viscosity models. But in all cases, the predictions were poor for scales smaller than that of the worst resolved direction.

  3. Dynamic reliability models with conditional proportional hazards.

    PubMed

    Hollander, M; Peña, E A

    1995-01-01

    A dynamic approach to the stochastic modelling of reliability systems is further explored. This modelling approach is particularly appropriate for load-sharing, software reliability, and multivariate failure-time models, where component failure characteristics are affected by their degree of use, amount of load, or extent of stresses experienced. This approach incorporates the intuitive notion that when a set of components in a coherent system fail at a certain time, there is a 'jump' from one structure function to another which governs the residual lifetimes of the remaining functioning components, and since the component lifetimes are intrinsically affected by the structure function which they constitute, then at such a failure time there should also be a jump in the stochastic structure of the lifetimes of the remaining components. For such dynamically-modelled systems, the stochastic characteristics of their jump times are studied. These properties of the jump times allow us to obtain the properties of the lifetime of the system. In particular, for a Markov dynamic model, specific expressions for the exact distribution function of the jump times are obtained for a general coherent system, a parallel system, and a series-parallel system. We derive a new family of distribution functions which describes the distributions of the jump times for a dynamically-modelled system.

  4. Record Dynamics and the Parking Lot Model for granular dynamics

    NASA Astrophysics Data System (ADS)

    Sibani, Paolo; Boettcher, Stefan

    Also known for its application to granular compaction (E. Ben-Naim et al., Physica D, 1998), the Parking Lot Model (PLM) describes the random parking of identical cars in a strip with no marked bays. In the thermally activated version considered, cars can be removed at an energy cost and, in thermal equilibrium, their average density increases as temperature decreases. However, equilibration at high density becomes exceedingly slow and the system enters an aging regime induced by a kinematic constraint, the fact that parked cars may not overlap. As parking an extra car reduces the available free space,the next parking event is even harder to achieve. Records in the number of parked cars mark the salient features of the dynamics and are shown to be well described by the log-Poisson statistics known from other glassy systems with record dynamics. Clusters of cars whose positions must be rearranged to make the next insertion possible have a length scale which grows logarithmically with age, while their life-time grows exponentially with size. The implications for a recent cluster model of colloidal dynamics,(S. Boettcher and P. Sibani, J. Phys.: Cond. Matter, 2011 N. Becker et al., J. Phys.: Cond. Matter, 2014) are discussed. Support rom the Villum Foundation is gratefully acknowledged.

  5. Dynamic modeling of solar dynamic components and systems

    NASA Astrophysics Data System (ADS)

    Hochstein, John I.; Korakianitis, T.

    1992-09-01

    The purpose of this grant was to support NASA in modeling efforts to predict the transient dynamic and thermodynamic response of the space station solar dynamic power generation system. In order to meet the initial schedule requirement of providing results in time to support installation of the system as part of the initial phase of space station, early efforts were executed with alacrity and often in parallel. Initially, methods to predict the transient response of a Rankine as well as a Brayton cycle were developed. Review of preliminary design concepts led NASA to select a regenerative gas-turbine cycle using a helium-xenon mixture as the working fluid and, from that point forward, the modeling effort focused exclusively on that system. Although initial project planning called for a three year period of performance, revised NASA schedules moved system installation to later and later phases of station deployment. Eventually, NASA selected to halt development of the solar dynamic power generation system for space station and to reduce support for this project to two-thirds of the original level.

  6. Dynamic Modeling of Solar Dynamic Components and Systems

    NASA Technical Reports Server (NTRS)

    Hochstein, John I.; Korakianitis, T.

    1992-01-01

    The purpose of this grant was to support NASA in modeling efforts to predict the transient dynamic and thermodynamic response of the space station solar dynamic power generation system. In order to meet the initial schedule requirement of providing results in time to support installation of the system as part of the initial phase of space station, early efforts were executed with alacrity and often in parallel. Initially, methods to predict the transient response of a Rankine as well as a Brayton cycle were developed. Review of preliminary design concepts led NASA to select a regenerative gas-turbine cycle using a helium-xenon mixture as the working fluid and, from that point forward, the modeling effort focused exclusively on that system. Although initial project planning called for a three year period of performance, revised NASA schedules moved system installation to later and later phases of station deployment. Eventually, NASA selected to halt development of the solar dynamic power generation system for space station and to reduce support for this project to two-thirds of the original level.

  7. The spatial Probit model-An application to the study of banking crises at the end of the 1990’s

    NASA Astrophysics Data System (ADS)

    Amaral, Andrea; Abreu, Margarida; Mendes, Victor

    2014-12-01

    We use a spatial Probit model to study the effect of contagion between banking systems of different countries. Applied to the late 1990s banking crisis in Asia we show that the phenomena of contagion is better seized using a spatial than a traditional Probit model. Unlike the latter, the spatial Probit model allows one to consider the cascade of cross and feedback effects of contagion that result from the outbreak of one initial crisis in one country or system. These contagion effects may result either from business connections between institutions of different countries or from institutional similarities between banking systems.

  8. Dynamic models of Fabry-Perot interferometers.

    PubMed

    Redding, David; Regehr, Martin; Sievers, Lisa

    2002-05-20

    Long-baseline, high-finesse Fabry-Perot interferometers can be used to make distance measurements that are precise enough to detect gravity waves. This level of sensitivity is achieved in part when the interferometer mirrors are isolated dynamically, with pendulum mounts and high-bandwidth cavity length control servos to reduce the effects of seismic noise. We present dynamical models of the cavity fields and signals of Fabry-Perot interferometers for use in the design and evaluation of length control systems for gravity-wave detectors. Models are described and compared with experimental data.

  9. Dynamical properties of the Rabi model

    NASA Astrophysics Data System (ADS)

    Hu, Binglu; Zhou, Huili; Chen, Shujie; Xianlong, Gao; Wang, Kelin

    2017-02-01

    We study the dynamical properties of the quantum Rabi model using a systematic expansion method. Based on the observation that the parity symmetry of the Rabi model is kept during evolution of the states, we decompose the initial state and the time-dependent one into positive and negative parity parts expanded by superposition of the coherent states. The evolutions of the corresponding positive and the negative parities are obtained, in which the expansion coefficients in the dynamical equations are known from the derived recurrence relation.

  10. Robot arm dynamic model reduction for control

    NASA Technical Reports Server (NTRS)

    Bejczy, A. K.; Lee, S.

    1983-01-01

    General methods are described by which the mathematical complexities of explicit and exact state equations of robot arms can be reduced to a simplified and compact state equation representation without introducing significant errors into the robot arm dynamic model. The model reduction methods are based on homogeneous coordinates and on the Langrangian algorithm for robot arm dynamics, and utilize matrix, vector and numeric analysis techniques. The derivation of differential vector representation of centripetal and Coriolis forces which has not yet been established in the literature is presented.

  11. Quantum model for the price dynamics

    NASA Astrophysics Data System (ADS)

    Choustova, Olga

    2008-10-01

    We apply methods of quantum mechanics to mathematical modelling of price dynamics in a financial market. We propose to describe behavioral financial factors (e.g., expectations of traders) by using the pilot wave (Bohmian) model of quantum mechanics. Our model is a quantum-like model of the financial market, cf. with works of W. Segal, I.E. Segal, E. Haven. In this paper we study the problem of smoothness of price-trajectories in the Bohmian financial model. We show that even the smooth evolution of the financial pilot wave [psi](t,x) (representing expectations of traders) can induce jumps of prices of shares.

  12. An integrated model of Plasmodium falciparum dynamics.

    PubMed

    McKenzie, F Ellis; Bossert, William H

    2005-02-07

    The within-host and between-host dynamics of malaria are linked in myriad ways, but most obviously by gametocytes, the parasite blood forms transmissible from human to mosquito. Gametocyte dynamics depend on those of non-transmissible blood forms, which stimulate immune responses, impeding transmission as well as within-host parasite densities. These dynamics can, in turn, influence antigenic diversity and recombination between genetically distinct parasites. Here, we embed a differential-equation model of parasite-immune system interactions within each of the individual humans represented in a discrete-event model of Plasmodium falciparum transmission, and examine the effects of human population turnover, parasite antigenic diversity, recombination, and gametocyte production on the dynamics of malaria. Our results indicate that the local persistence of P. falciparum increases with turnover in the human population and antigenic diversity in the parasite, particularly in combination, and that antigenic diversity arising from meiotic recombination in the parasite has complex differential effects on the persistence of founder and progeny genotypes. We also find that reductions in the duration of individual human infectivity to mosquitoes, even if universal, produce population-level effects only if near-absolute, and that, in competition, the persistence and prevalence of parasite genotypes with gametocyte production concordant with data exceed those of genotypes with higher gametocyte production. This new, integrated approach provides a framework for investigating relationships between pathogen dynamics within an individual host and pathogen dynamics within interacting host and vector populations.

  13. Particle dynamics modeling methods for colloid suspensions

    NASA Astrophysics Data System (ADS)

    Bolintineanu, Dan S.; Grest, Gary S.; Lechman, Jeremy B.; Pierce, Flint; Plimpton, Steven J.; Schunk, P. Randall

    2014-09-01

    We present a review and critique of several methods for the simulation of the dynamics of colloidal suspensions at the mesoscale. We focus particularly on simulation techniques for hydrodynamic interactions, including implicit solvents (Fast Lubrication Dynamics, an approximation to Stokesian Dynamics) and explicit/particle-based solvents (Multi-Particle Collision Dynamics and Dissipative Particle Dynamics). Several variants of each method are compared quantitatively for the canonical system of monodisperse hard spheres, with a particular focus on diffusion characteristics, as well as shear rheology and microstructure. In all cases, we attempt to match the relevant properties of a well-characterized solvent, which turns out to be challenging for the explicit solvent models. Reasonable quantitative agreement is observed among all methods, but overall the Fast Lubrication Dynamics technique shows the best accuracy and performance. We also devote significant discussion to the extension of these methods to more complex situations of interest in industrial applications, including models for non-Newtonian solvent rheology, non-spherical particles, drying and curing of solvent and flows in complex geometries. This work identifies research challenges and motivates future efforts to develop techniques for quantitative, predictive simulations of industrially relevant colloidal suspension processes.

  14. Modeling emotional dynamics : currency versus field.

    SciTech Connect

    Sallach, D .L.; Decision and Information Sciences; Univ. of Chicago

    2008-08-01

    Randall Collins has introduced a simplified model of emotional dynamics in which emotional energy, heightened and focused by interaction rituals, serves as a common denominator for social exchange: a generic form of currency, except that it is active in a far broader range of social transactions. While the scope of this theory is attractive, the specifics of the model remain unconvincing. After a critical assessment of the currency theory of emotion, a field model of emotion is introduced that adds expressiveness by locating emotional valence within its cognitive context, thereby creating an integrated orientation field. The result is a model which claims less in the way of motivational specificity, but is more satisfactory in modeling the dynamic interaction between cognitive and emotional orientations at both individual and social levels.

  15. Dynamic model for the popularity of websites.

    PubMed

    Lee, Chang-Yong; Kim, Seungwhan

    2002-03-01

    In this paper, we have studied a dynamic model to explain the observed characteristics of websites in the World Wide Web. The dynamic model consists of the self-growth term for each website and the external force term acting on the website. With simulations of the model, we can explain most of the important characteristics of websites. These characteristics include a power-law distribution of the number of visitors to websites, fluctuation in the fractional growth of individual websites, and the relationship between the age and the popularity of the websites. We also investigated a few variants of the model and showed that the ingredients included in the model adequately explain the behavior of the websites.

  16. Dynamic model for the popularity of websites

    NASA Astrophysics Data System (ADS)

    Lee, Chang-Yong; Kim, Seungwhan

    2002-03-01

    In this paper, we have studied a dynamic model to explain the observed characteristics of websites in the World Wide Web. The dynamic model consists of the self-growth term for each website and the external force term acting on the website. With simulations of the model, we can explain most of the important characteristics of websites. These characteristics include a power-law distribution of the number of visitors to websites, fluctuation in the fractional growth of individual websites, and the relationship between the age and the popularity of the websites. We also investigated a few variants of the model and showed that the ingredients included in the model adequately explain the behavior of the websites.

  17. BDI-modelling of complex intracellular dynamics.

    PubMed

    Jonker, C M; Snoep, J L; Treur, J; Westerhoff, H V; Wijngaards, W C A

    2008-03-07

    A BDI-based continuous-time modelling approach for intracellular dynamics is presented. It is shown how temporalized BDI-models make it possible to model intracellular biochemical processes as decision processes. By abstracting from some of the details of the biochemical pathways, the model achieves understanding in nearly intuitive terms, without losing veracity: classical intentional state properties such as beliefs, desires and intentions are founded in reality through precise biochemical relations. In an extensive example, the complex regulation of Escherichia coli vis-à-vis lactose, glucose and oxygen is simulated as a discrete-state, continuous-time temporal decision manager. Thus a bridge is introduced between two different scientific areas: the area of BDI-modelling and the area of intracellular dynamics.

  18. Part 2: Fear of contagion, fear of intimacy.

    PubMed

    Botnick, M R

    2000-01-01

    In this second part of the trilogy, I review the concepts of panic, the Theory of Cognitive Dissonance, and how internally inconsistent opinions and attitudes can be made consistent (or consonant). The theory explains, in some measure, how AIDS has been socialized into our thinking about identity, and goes beyond a medical condition. The pervasive identification of gay men with HIV and AIDS has resulted for many in an over-identification with fears of contagion and on a societal level in a fear of all gays as pools of contagion. The conversion of dissonance to consonance has taken many forms; within the gay community it has resulted in the rejection of the "100% safe-100% of the time" safe-sex message, and the adoption (for many) of a new form of deviant label-someone who is not in conformity with the social norm of gay community sexual behavior. However, we shall see that this so-called norm is a sham-that many gay men do not, as a rule, practice safe(r) sex on a consistent basis. This information indicates that the educational efforts of the last decade have at best lost their potency, and at worst were less than efficacious to begin with. The dissonant messages have also informed both the construction of the gay community and its interpretation of what it means to be gay. The result has been a tri-lateral perception of HIV and AIDS as either a medical, political or a social phenomenon. This fragmented understanding has exacerbated the already polarized ASOs and GSOs in that each has determined its ideology based on a particular interpretation of HIV and AIDS. This polarization has been operationalized by the GSOs and ASOs primarily in the manner by which they define their target markets, and more importantly, in the manner by which they exclude certain gays from participation. At the extreme, some gay men feel entirely left out of the community, and are consequently unable to convert their dissonance regarding being gay into consonance, if only by developing

  19. ODE models for oncolytic virus dynamics

    PubMed Central

    Komarova, Natalia L.; Wodarz, Dominik

    2010-01-01

    Replicating oncolytic viruses are able to infect and lyse cancer cells and spread through the tumor, while leaving normal cells largely unharmed. This makes them potentially useful in cancer therapy, and a variety of viruses have shown promising results in clinical trials. Nevertheless, consistent success remains elusive and the correlates of success have been the subject of investigation, both from an experimental and a mathematical point of view. Mathematical modeling of oncolytic virus therapy is often limited by the fact that the predicted dynamics depend strongly on particular mathematical terms in the model, the nature of which remain uncertain. We aim to address this issue in the context of ODE modeling, by formulating a general computational framework that is independent of particular mathematical expressions. By analyzing this framework, we find some new insights into the conditions for successful virus therapy. We find that depending on our assumptions about the virus spread, there can be two distinct types of dynamics. In models of the first type (the “fast spread” models), we predict that the viruses can eliminate the tumor if the viral replication rate is sufficiently high. The second type of models is characterized by a suboptimal spread (the “slow spread” models). For such models, the simulated treatment may fail, even for very high viral replication rates. Our methodology can be used to study the dynamics of many biological systems, and thus has implications beyond the study of virus therapy of cancers. PMID:20085772

  20. Dynamic causal modelling of distributed electromagnetic responses

    PubMed Central

    Daunizeau, Jean; Kiebel, Stefan J.; Friston, Karl J.

    2009-01-01

    In this note, we describe a variant of dynamic causal modelling for evoked responses as measured with electroencephalography or magnetoencephalography (EEG and MEG). We depart from equivalent current dipole formulations of DCM, and extend it to provide spatiotemporal source estimates that are spatially distributed. The spatial model is based upon neural-field equations that model neuronal activity on the cortical manifold. We approximate this description of electrocortical activity with a set of local standing-waves that are coupled though their temporal dynamics. The ensuing distributed DCM models source as a mixture of overlapping patches on the cortical mesh. Time-varying activity in this mixture, caused by activity in other sources and exogenous inputs, is propagated through appropriate lead-field or gain-matrices to generate observed sensor data. This spatial model has three key advantages. First, it is more appropriate than equivalent current dipole models, when real source activity is distributed locally within a cortical area. Second, the spatial degrees of freedom of the model can be specified and therefore optimised using model selection. Finally, the model is linear in the spatial parameters, which finesses model inversion. Here, we describe the distributed spatial model and present a comparative evaluation with conventional equivalent current dipole (ECD) models of auditory processing, as measured with EEG. PMID:19398015

  1. Pandemic obesity and the contagion of nutritional nonsense.

    PubMed

    Katz, David L

    2003-01-01

    The United States is the epicenter of an obesity pandemic. As more countries acculturate to a Western lifestyle, rates of obesity and its sequelae are rising steadily in both adults and children. In response, a variety of weight-loss diets emphasizing alternative distributions of macronutrient classes have been promoted with considerable success. Among the most popular is the so-called "Atkins Diet," in which carbohydrate restriction is touted as the key to weight loss. Despite claims, however, evidence that weight loss is enhanced by means other than caloric restriction is lacking. Also lacking is evidence that fad diets produce sustainable weight loss. Most important, fad diets generally ignore or refute what is known about fundamental associations between dietary pattern and human health. Cancer, cholera, and AIDS induce rapid weight loss, highlighting the potential incompatibility of weight loss by any means with health. Available data suggest that long-term weight loss is most consistently achieved by adherence to a fat-restricted diet abundant in grains, vegetables, and fruit, along with regular physical activity, a lifestyle notably conducive to the promotion of overall health. Fad diets, potential harms of which are well characterized, should be presumed "guilty" of incompatibility with human health until or unless proved otherwise; the burden of proof should reside with proponents. In the interim, the clinical and public health communities should work to empower individuals with knowledge needed to reconcile weight control with health promotion; support policies that mitigate obesogenic environmental conditions; and offer unified resistance to the contagion of dietary propaganda.

  2. Computational and dynamic models in neuroimaging

    PubMed Central

    Friston, Karl J.; Dolan, Raymond J.

    2010-01-01

    This article reviews the substantial impact computational neuroscience has had on neuroimaging over the past years. It builds on the distinction between models of the brain as a computational machine and computational models of neuronal dynamics per se; i.e., models of brain function and biophysics. Both sorts of model borrow heavily from computational neuroscience, and both have enriched the analysis of neuroimaging data and the type of questions we address. To illustrate the role of functional models in imaging neuroscience, we focus on optimal control and decision (game) theory; the models used here provide a mechanistic account of neuronal computations and the latent (mental) states represent by the brain. In terms of biophysical modelling, we focus on dynamic causal modelling, with a special emphasis on recent advances in neural-mass models for hemodynamic and electrophysiological time series. Each example emphasises the role of generative models, which embed our hypotheses or questions, and the importance of model comparison (i.e., hypothesis testing). We will refer to this theme, when trying to contextualise recent trends in relation to each other. PMID:20036335

  3. Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window.

    PubMed

    Onorante, Luca; Raftery, Adrian E

    2016-01-01

    Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam's window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods.

  4. Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam’s Window*

    PubMed Central

    Onorante, Luca; Raftery, Adrian E.

    2015-01-01

    Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam’s window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods. PMID:26917859

  5. A Novel Virus-Patch Dynamic Model

    PubMed Central

    Yang, Lu-Xing; Yang, Xiaofan

    2015-01-01

    The distributed patch dissemination strategies are a promising alternative to the conventional centralized patch dissemination strategies. This paper aims to establish a theoretical framework for evaluating the effectiveness of distributed patch dissemination mechanism. Assuming that the Internet offers P2P service for every pair of nodes on the network, a dynamic model capturing both the virus propagation mechanism and the distributed patch dissemination mechanism is proposed. This model takes into account the infected removable storage media and hence captures the interaction of patches with viruses better than the original SIPS model. Surprisingly, the proposed model exhibits much simpler dynamic properties than the original SIPS model. Specifically, our model admits only two potential (viral) equilibria and undergoes a fold bifurcation. The global stabilities of the two equilibria are determined. Consequently, the dynamical properties of the proposed model are fully understood. Furthermore, it is found that reducing the probability per unit time of disconnecting a node from the Internet benefits the containment of electronic viruses. PMID:26368556

  6. Modeling biological pathway dynamics with timed automata.

    PubMed

    Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

    2014-05-01

    Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

  7. Hidden process models for animal population dynamics.

    PubMed

    Newman, K B; Buckland, S T; Lindley, S T; Thomas, L; Fernández, C

    2006-02-01

    Hidden process models are a conceptually useful and practical way to simultaneously account for process variation in animal population dynamics and measurement errors in observations and estimates made on the population. Process variation, which can be both demographic and environmental, is modeled by linking a series of stochastic and deterministic subprocesses that characterize processes such as birth, survival, maturation, and movement. Observations of the population can be modeled as functions of true abundance with realistic probability distributions to describe observation or estimation error. Computer-intensive procedures, such as sequential Monte Carlo methods or Markov chain Monte Carlo, condition on the observed data to yield estimates of both the underlying true population abundances and the unknown population dynamics parameters. Formulation and fitting of a hidden process model are demonstrated for Sacramento River winter-run chinook salmon (Oncorhynchus tshawytsha).

  8. Solvable model for polymorphic dynamics of biofilaments.

    PubMed

    Mohrbach, Hervé; Kulić, Igor M

    2012-03-01

    We investigate an analytically tractable toy model for thermally induced polymorphic dynamics of cooperatively rearranging biofilaments-like microtubules. The proposed four-block model, which can be seen as a coarse-grained approximation of the full polymorphic tube model, permits a complete analytical treatment of all thermodynamic properties including correlation functions and angular Fourier mode distributions. Due to its mathematical tractability the model straightforwardly leads to some physical insights in recently discussed phenomena like the "length dependent persistence length." We show that a polymorphic filament can disguise itself as a classical worm-like chain on small and on large scales and yet display distinct anomalous tell-tale features indicating an inner switching dynamics on intermediate length scales.

  9. Polarizable protein model for Dissipative Particle Dynamics

    NASA Astrophysics Data System (ADS)

    Peter, Emanuel; Lykov, Kirill; Pivkin, Igor

    2015-11-01

    In this talk, we present a novel polarizable protein model for the Dissipative Particle Dynamics (DPD) simulation technique, a coarse-grained particle-based method widely used in modeling of fluid systems at the mesoscale. We employ long-range electrostatics and Drude oscillators in combination with a newly developed polarizable water model. The protein in our model is resembled by a polarizable backbone and a simplified representation of the sidechains. We define the model parameters using the experimental structures of 2 proteins: TrpZip2 and TrpCage. We validate the model on folding of five other proteins and demonstrate that it successfully predicts folding of these proteins into their native conformations. As a perspective of this model, we will give a short outlook on simulations of protein aggregation in the bulk and near a model membrane, a relevant process in several Amyloid diseases, e.g. Alzheimer's and Diabetes II.

  10. Modeling the Hydrogen Bond within Molecular Dynamics

    ERIC Educational Resources Information Center

    Lykos, Peter

    2004-01-01

    The structure of a hydrogen bond is elucidated within the framework of molecular dynamics based on the model of Rahman and Stillinger (R-S) liquid water treatment. Thus, undergraduates are exposed to the powerful but simple use of classical mechanics to solid objects from a molecular viewpoint.

  11. DYNAMIC LANDSCAPES, STABILITY AND ECOLOGICAL MODELING

    EPA Science Inventory

    The image of a ball rolling along a series of hills and valleys is an effective heuristic by which to communicate stability concepts in ecology. However, the dynamics of this landscape model have little to do with ecological systems. Other landscape representations, however, are ...

  12. A Flight Dynamic Model of Aircraft Spinning

    DTIC Science & Technology

    1990-06-01

    Australia, Library Australian Airlines, Library Qantas Airways Limited Hawker de Havilland Aust. Pty Ltd, Victoria, Library Hawker de Havilland Aust. Pty...3. MARTIN, C.A. ; Modelling Aircraft Dynamics. ARL-AERO-TECH- MEMO-400 July 1988 4. HULTBERG, R.S. ; Rotary Balance Data and Analysis for the

  13. Modeling of tower relief dynamics: Part 2

    SciTech Connect

    Cassata, J.R.; Dasgupta, S.; Gandhi, S.L. )

    1993-11-01

    Dynamic simulations of individual towers or systems of distillations columns overcome limitations of steady-state models by rigorously determining dynamic responses. These will lead to a realistic quantification of relief header and flare system load and identify the design-setting relief scenario. Determination of distillation tower relief loads based on steady-state simulations or recognized methods of approximation can lead to over designing relief systems by large margins. This can result in unnecessary capital expenditure for relief headers and flare systems that can significantly alter the economics of a proposed project. Such overly conservative requirements may even cause potentially attractive projects to be unnecessarily canceled. In addition, approximate methods or analyses based on steady-state simulations sometimes do not identify the design-setting relief mode. Part 1 introduced the PRV and tower dynamic models. Different strategies were shown that can simplify these models. These strategies include tower segmentation, tray lumping and component lumping. Two case studies illustrate the advantages of dynamic models. The two studies are a depentanizer tower relief study and a delthanizer tower relief study.

  14. Model Of Neural Network With Creative Dynamics

    NASA Technical Reports Server (NTRS)

    Zak, Michail; Barhen, Jacob

    1993-01-01

    Paper presents analysis of mathematical model of one-neuron/one-synapse neural network featuring coupled activation and learning dynamics and parametrical periodic excitation. Demonstrates self-programming, partly random behavior of suitable designed neural network; believed to be related to spontaneity and creativity of biological neural networks.

  15. Modeling the Hydrogen Bond within Molecular Dynamics

    ERIC Educational Resources Information Center

    Lykos, Peter

    2004-01-01

    The structure of a hydrogen bond is elucidated within the framework of molecular dynamics based on the model of Rahman and Stillinger (R-S) liquid water treatment. Thus, undergraduates are exposed to the powerful but simple use of classical mechanics to solid objects from a molecular viewpoint.

  16. Model Of Neural Network With Creative Dynamics

    NASA Technical Reports Server (NTRS)

    Zak, Michail; Barhen, Jacob

    1993-01-01

    Paper presents analysis of mathematical model of one-neuron/one-synapse neural network featuring coupled activation and learning dynamics and parametrical periodic excitation. Demonstrates self-programming, partly random behavior of suitable designed neural network; believed to be related to spontaneity and creativity of biological neural networks.

  17. DYNAMIC LANDSCAPES, STABILITY AND ECOLOGICAL MODELING

    EPA Science Inventory

    The image of a ball rolling along a series of hills and valleys is an effective heuristic by which to communicate stability concepts in ecology. However, the dynamics of this landscape model have little to do with ecological systems. Other landscape representations, however, are ...

  18. Modeling the population dynamics of Pacific yew.

    Treesearch

    Richard T. Busing; Thomas A. Spies

    1995-01-01

    A study of Pacific yew (Taxus brevifolia Nutt.) population dynamics in the mountains of western Oregon and Washington was based on a combination of long-term population data and computer modeling. Rates of growth and mortality were low in mature and old-growth forest stands. Diameter growth at breast height ranged from 0 to 3 centimeters per decade...

  19. Modeling of Reactor Kinetics and Dynamics

    SciTech Connect

    Matthew Johnson; Scott Lucas; Pavel Tsvetkov

    2010-09-01

    In order to model a full fuel cycle in a nuclear reactor, it is necessary to simulate the short time-scale kinetic behavior of the reactor as well as the long time-scale dynamics that occur with fuel burnup. The former is modeled using the point kinetics equations, while the latter is modeled by coupling fuel burnup equations with the kinetics equations. When the equations are solved simultaneously with a nonlinear equation solver, the end result is a code with the unique capability of modeling transients at any time during a fuel cycle.

  20. Constitutive Laws for Dynamic Modelling of Soils,

    DTIC Science & Technology

    1980-01-01

    AD-AO 733 DAMES AND MDORE LONDON (ENGLAND) F/ S/I3 CONSTITUTIVE LAWS FOR DYNAMIC MODELLING OF SOILS.(U) JAN 80 J MART1 P A CUNOALL F61708-79--087...shear history progresses. This is the type of approach followed in the endochronic models used by Bazant and co-workers ( Bazant and Krizeck, 1976...this improved model to soils (1978). Mean- while, Bazant and his co-workers have continued using the older model for 1describing concrete ( Bazant and

  1. The quantum Rabi model: solution and dynamics

    NASA Astrophysics Data System (ADS)

    Xie, Qiongtao; Zhong, Honghua; Batchelor, Murray T.; Lee, Chaohong

    2017-03-01

    This article presents a review of recent developments on various aspects of the quantum Rabi model. Particular emphasis is given on the exact analytic solution obtained in terms of confluent Heun functions. The analytic solutions for various generalisations of the quantum Rabi model are also discussed. Results are also reviewed on the level statistics and the dynamics of the quantum Rabi model. The article concludes with an introductory overview of several experimental realisations of the quantum Rabi model. An outlook towards future developments is also given.

  2. Developmental Stages in Dynamic Plant Growth Models

    NASA Astrophysics Data System (ADS)

    Maclean, Heather; Dochain, Denis; Waters, Geoff; Stasiak, Michael; Dixon, Mike; Van Der Straeten, Dominique

    2011-09-01

    During the growth of red beet plants in a closed environment plant growth chamber, a change in metabolism was observed (decreasing photosynthetic quotient) which was not predicted by a previously developed simple dynamic model of photosynthesis and respiration reactions. The incorporation of developmental stages into the model allowed for the representation of this change in metabolism without adding unnecessary complexity. Developmental stages were implemented by dividing the model into two successive sub-models with independent yields. The transition between the phases was detected based on online measurements. Results showed an accurate prediction of carbon dioxide and oxygen fluxes.

  3. Dynamic model of the Earth's upper atmosphere

    NASA Technical Reports Server (NTRS)

    Slowey, J. W.

    1984-01-01

    An initial modification to the MSF/J70 Thermospheric Model, in which the variations due to sudden geomagnetic disturbances upon the Earth's upper atmospheric density structure were modeled is presented. This dynamic model of the geomagnetic variation included is an improved version of one which SAO developed from the analysis of the ESRO 4 mass spectrometer data that was incorporated in the Jacchia 1977 model. The variation with geomagnetic local time as well as with geomagnetic latitude are included, and also the effects due to disturbance of the temperature profiles in the region of energy deposition.

  4. Population mixture model for nonlinear telomere dynamics

    NASA Astrophysics Data System (ADS)

    Itzkovitz, Shalev; Shlush, Liran I.; Gluck, Dan; Skorecki, Karl

    2008-12-01

    Telomeres are DNA repeats protecting chromosomal ends which shorten with each cell division, eventually leading to cessation of cell growth. We present a population mixture model that predicts an exponential decrease in telomere length with time. We analytically solve the dynamics of the telomere length distribution. The model provides an excellent fit to available telomere data and accounts for the previously unexplained observation of telomere elongation following stress and bone marrow transplantation, thereby providing insight into the nature of the telomere clock.

  5. Modeling joint friction in structural dynamics.

    SciTech Connect

    Segalman, Daniel Joseph

    2005-05-01

    The presence of mechanical joints--typified by the lap joint--in otherwise linear structures has been accommodated in structural dynamics via ad hoc methods for a century. The methods range from tuning linear models to approximate non-linear behavior in restricted load ranges to various methods which introduce joint dissipation in a post-processing stage. Other methods, employing constitutive models for the joints are being developed and their routine use is on the horizon.

  6. Modeling of dynamical processes in laser ablation

    SciTech Connect

    Leboeuf, J.N.; Chen, K.R.; Donato, J.M.; Geohegan, D.B.; Liu, C.L.; Puretzky, A.A.; Wood, R.F.

    1995-12-31

    Various physics and computational approaches have been developed to globally characterize phenomena important for film growth by pulsed-laser deposition of materials. These include thermal models of laser-solid target interactions that initiate the vapor plume, plume ionization and heating through laser absorption beyond local thermodynamic equilibrium mechanisms, hydrodynamic and collisional descriptions of plume transport, and molecular dynamics models of the interaction of plume particles with the deposition substrate.

  7. Modelling Subduction Dynamics: The South American Salsa

    NASA Astrophysics Data System (ADS)

    Hale, A. J.; Shephard, G.; Müller, D.; Liu, L.; Gurnis, M.

    2009-12-01

    Plate kinematic and seismic tomography models imply a gradual overriding of the Phoenix and Farallon slabs by the westward movement of the South American plate. This westward translation over the subducted slabs, and the currently subducting Nazca Plate, is expected to generate a dynamic surface topography effect, leading to time-progressive vertical motions and tilting of sedimentary basins and their hinterlands. We have set up a workflow to model these processes including ground-truthing with geological and geophysical data. A combination of geodynamic modelling software, CitcomS, GPlates (gplates.org) software and the Generic Mapping Tools (GMT) facilitates the modelling and visualisation of linked plate kinematics and mantle convection processes. The CitcomS software also allows us to alternatively use forward models, backward models, or combined forward and adjoint models. Forward models are driven by an imposed plate kinematic model and assumed initial subdution structure, whereas backwards models use mantle tomography as an input and run the model backwards by reversing the gravity field. Similarly, adjoint models use tomography as input, but iterate backwards and forwards in time to reach convergence upon present-day mantle structures. Model outputs include time-dependent mantle temperature, viscosity, and surface dynamic topography. Forward model results show that slab evolution under South America are strongly driven by the age of the subducting lithosphere. Hence, we can simulate flat-slab subduction and in regions close to the Chile triple junction we see a slab window developing, detaching older slab material from more recently subducted material. However, the forward model relies on an accurate description of the initial slab geometry at 140Ma to generate the initial slab pull. Forward and adjoint model results both suggest an alternative mechanism for major Miocene changes in paleo-Amazon river drainage. An eastward-sweeping negative dynamic

  8. Sepsis progression and outcome: a dynamical model

    PubMed Central

    Zuev, Sergey M; Kingsmore, Stephen F; Gessler, Damian DG

    2006-01-01

    Background Sepsis (bloodstream infection) is the leading cause of death in non-surgical intensive care units. It is diagnosed in 750,000 US patients per annum, and has high mortality. Current understanding of sepsis is predominately observational and correlational, with only a partial and incomplete understanding of the physiological dynamics underlying the syndrome. There exists a need for dynamical models of sepsis progression, based upon basic physiologic principles, which could eventually guide hourly treatment decisions. Results We present an initial mathematical model of sepsis, based on metabolic rate theory that links basic vascular and immunological dynamics. The model includes the rate of vascular circulation, a surrogate for the metabolic rate that is mechanistically associated with disease progression. We use the mass-specific rate of blood circulation (SRBC), a correlate of the body mass index, to build a differential equation model of circulation, infection, organ damage, and recovery. This introduces a vascular component into an infectious disease model that describes the interaction between a pathogen and the adaptive immune system. Conclusion The model predicts that deviations from normal SRBC correlate with disease progression and adverse outcome. We compare the predictions with population mortality data from cardiovascular disease and cancer and show that deviations from normal SRBC correlate with higher mortality rates. PMID:16480490

  9. Feature extraction for structural dynamics model validation

    SciTech Connect

    Hemez, Francois; Farrar, Charles; Park, Gyuhae; Nishio, Mayuko; Worden, Keith; Takeda, Nobuo

    2010-11-08

    This study focuses on defining and comparing response features that can be used for structural dynamics model validation studies. Features extracted from dynamic responses obtained analytically or experimentally, such as basic signal statistics, frequency spectra, and estimated time-series models, can be used to compare characteristics of structural system dynamics. By comparing those response features extracted from experimental data and numerical outputs, validation and uncertainty quantification of numerical model containing uncertain parameters can be realized. In this study, the applicability of some response features to model validation is first discussed using measured data from a simple test-bed structure and the associated numerical simulations of these experiments. issues that must be considered were sensitivity, dimensionality, type of response, and presence or absence of measurement noise in the response. Furthermore, we illustrate a comparison method of multivariate feature vectors for statistical model validation. Results show that the outlier detection technique using the Mahalanobis distance metric can be used as an effective and quantifiable technique for selecting appropriate model parameters. However, in this process, one must not only consider the sensitivity of the features being used, but also correlation of the parameters being compared.

  10. Data driven Langevin modeling of biomolecular dynamics

    NASA Astrophysics Data System (ADS)

    Schaudinnus, Norbert; Rzepiela, Andrzej J.; Hegger, Rainer; Stock, Gerhard

    2013-05-01

    Based on a given time series, the data-driven Langevin equation proposed by Hegger and Stock [J. Chem. Phys. 130, 034106 (2009), 10.1063/1.3058436] aims to construct a low-dimensional dynamical model of the system. Adopting various simple model problems of biomolecular dynamics, this work presents a systematic study of the theoretical virtues and limitations as well as of the practical applicability and performance of the method. As the method requires only local information, the input data need not to be Boltzmann weighted in order to warrant that the Langevin model yields correct Boltzmann-distributed results. Moreover, a delay embedding of the state vector allows for the treatment of memory effects. The robustness of the modeling with respect to wrongly chosen model parameters or low sampling is discussed, as well as the treatment of inertial effects. Given sufficiently sampled input data, the Langevin modeling is shown to successfully recover the correct statistics (such as the probability distribution) and the dynamics (such as the position autocorrelation function) of all considered problems.

  11. Nonsmooth dynamics in spiking neuron models

    NASA Astrophysics Data System (ADS)

    Coombes, S.; Thul, R.; Wedgwood, K. C. A.

    2012-11-01

    Large scale studies of spiking neural networks are a key part of modern approaches to understanding the dynamics of biological neural tissue. One approach in computational neuroscience has been to consider the detailed electrophysiological properties of neurons and build vast computational compartmental models. An alternative has been to develop minimal models of spiking neurons with a reduction in the dimensionality of both parameter and variable space that facilitates more effective simulation studies. In this latter case the single neuron model of choice is often a variant of the classic integrate-and-fire model, which is described by a nonsmooth dynamical system. In this paper we review some of the more popular spiking models of this class and describe the types of spiking pattern that they can generate (ranging from tonic to burst firing). We show that a number of techniques originally developed for the study of impact oscillators are directly relevant to their analysis, particularly those for treating grazing bifurcations. Importantly we highlight one particular single neuron model, capable of generating realistic spike trains, that is both computationally cheap and analytically tractable. This is a planar nonlinear integrate-and-fire model with a piecewise linear vector field and a state dependent reset upon spiking. We call this the PWL-IF model and analyse it at both the single neuron and network level. The techniques and terminology of nonsmooth dynamical systems are used to flesh out the bifurcation structure of the single neuron model, as well as to develop the notion of Lyapunov exponents. We also show how to construct the phase response curve for this system, emphasising that techniques in mathematical neuroscience may also translate back to the field of nonsmooth dynamical systems. The stability of periodic spiking orbits is assessed using a linear stability analysis of spiking times. At the network level we consider linear coupling between voltage

  12. Direct modeling for computational fluid dynamics

    NASA Astrophysics Data System (ADS)

    Xu, Kun

    2015-06-01

    All fluid dynamic equations are valid under their modeling scales, such as the particle mean free path and mean collision time scale of the Boltzmann equation and the hydrodynamic scale of the Navier-Stokes (NS) equations. The current computational fluid dynamics (CFD) focuses on the numerical solution of partial differential equations (PDEs), and its aim is to get the accurate solution of these governing equations. Under such a CFD practice, it is hard to develop a unified scheme that covers flow physics from kinetic to hydrodynamic scales continuously because there is no such governing equation which could make a smooth transition from the Boltzmann to the NS modeling. The study of fluid dynamics needs to go beyond the traditional numerical partial differential equations. The emerging engineering applications, such as air-vehicle design for near-space flight and flow and heat transfer in micro-devices, do require further expansion of the concept of gas dynamics to a larger domain of physical reality, rather than the traditional distinguishable governing equations. At the current stage, the non-equilibrium flow physics has not yet been well explored or clearly understood due to the lack of appropriate tools. Unfortunately, under the current numerical PDE approach, it is hard to develop such a meaningful tool due to the absence of valid PDEs. In order to construct multiscale and multiphysics simulation methods similar to the modeling process of constructing the Boltzmann or the NS governing equations, the development of a numerical algorithm should be based on the first principle of physical modeling. In this paper, instead of following the traditional numerical PDE path, we introduce direct modeling as a principle for CFD algorithm development. Since all computations are conducted in a discretized space with limited cell resolution, the flow physics to be modeled has to be done in the mesh size and time step scales. Here, the CFD is more or less a direct

  13. Dynamic occupancy models for explicit colonization processes

    USGS Publications Warehouse

    Broms, Kristin M.; Hooten, Mevin B.; Johnson, Devin S.; Altwegg, Res; Conquest, Loveday

    2016-01-01

    The dynamic, multi-season occupancy model framework has become a popular tool for modeling open populations with occupancies that change over time through local colonizations and extinctions. However, few versions of the model relate these probabilities to the occupancies of neighboring sites or patches. We present a modeling framework that incorporates this information and is capable of describing a wide variety of spatiotemporal colonization and extinction processes. A key feature of the model is that it is based on a simple set of small-scale rules describing how the process evolves. The result is a dynamic process that can account for complicated large-scale features. In our model, a site is more likely to be colonized if more of its neighbors were previously occupied and if it provides more appealing environmental characteristics than its neighboring sites. Additionally, a site without occupied neighbors may also become colonized through the inclusion of a long-distance dispersal process. Although similar model specifications have been developed for epidemiological applications, ours formally accounts for detectability using the well-known occupancy modeling framework. After demonstrating the viability and potential of this new form of dynamic occupancy model in a simulation study, we use it to obtain inference for the ongoing Common Myna (Acridotheres tristis) invasion in South Africa. Our results suggest that the Common Myna continues to enlarge its distribution and its spread via short distance movement, rather than long-distance dispersal. Overall, this new modeling framework provides a powerful tool for managers examining the drivers of colonization including short- vs. long-distance dispersal, habitat quality, and distance from source populations.

  14. Dynamic force matching: Construction of dynamic coarse-grained models with realistic short time dynamics and accurate long time dynamics

    NASA Astrophysics Data System (ADS)

    Davtyan, Aram; Voth, Gregory A.; Andersen, Hans C.

    2016-12-01

    We recently developed a dynamic force matching technique for converting a coarse-grained (CG) model of a molecular system, with a CG potential energy function, into a dynamic CG model with realistic dynamics [A. Davtyan et al., J. Chem. Phys. 142, 154104 (2015)]. This is done by supplementing the model with additional degrees of freedom, called "fictitious particles." In that paper, we tested the method on CG models in which each molecule is coarse-grained into one CG point particle, with very satisfactory results. When the method was applied to a CG model of methanol that has two CG point particles per molecule, the results were encouraging but clearly required improvement. In this paper, we introduce a new type (called type-3) of fictitious particle that exerts forces on the center of mass of two CG sites. A CG model constructed using type-3 fictitious particles (as well as type-2 particles previously used) gives a much more satisfactory dynamic model for liquid methanol. In particular, we were able to construct a CG model that has the same self-diffusion coefficient and the same rotational relaxation time as an all-atom model of liquid methanol. Type-3 particles and generalizations of it are likely to be useful in converting more complicated CG models into dynamic CG models.

  15. Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models

    EPA Science Inventory

    The task of quantifying the uncertainty in both parameter estimates and model predictions has become more important with the increased use of dynamic computational toxicology models by the EPA. Dynamic toxicological models include physiologically-based pharmacokinetic (PBPK) mode...

  16. Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models

    EPA Science Inventory

    The task of quantifying the uncertainty in both parameter estimates and model predictions has become more important with the increased use of dynamic computational toxicology models by the EPA. Dynamic toxicological models include physiologically-based pharmacokinetic (PBPK) mode...

  17. Indonesia’s Electricity Demand Dynamic Modelling

    NASA Astrophysics Data System (ADS)

    Sulistio, J.; Wirabhuana, A.; Wiratama, M. G.

    2017-06-01

    Electricity Systems modelling is one of the emerging area in the Global Energy policy studies recently. System Dynamics approach and Computer Simulation has become one the common methods used in energy systems planning and evaluation in many conditions. On the other hand, Indonesia experiencing several major issues in Electricity system such as fossil fuel domination, demand - supply imbalances, distribution inefficiency, and bio-devastation. This paper aims to explain the development of System Dynamics modelling approaches and computer simulation techniques in representing and predicting electricity demand in Indonesia. In addition, this paper also described the typical characteristics and relationship of commercial business sector, industrial sector, and family / domestic sector as electricity subsystems in Indonesia. Moreover, it will be also present direct structure, behavioural, and statistical test as model validation approach and ended by conclusions.

  18. Continuum modeling of cooperative traffic flow dynamics

    NASA Astrophysics Data System (ADS)

    Ngoduy, D.; Hoogendoorn, S. P.; Liu, R.

    2009-07-01

    This paper presents a continuum approach to model the dynamics of cooperative traffic flow. The cooperation is defined in our model in a way that the equipped vehicle can issue and receive a warning massage when there is downstream congestion. Upon receiving the warning massage, the (up-stream) equipped vehicle will adapt the current desired speed to the speed at the congested area in order to avoid sharp deceleration when approaching the congestion. To model the dynamics of such cooperative systems, a multi-class gas-kinetic theory is extended to capture the adaptation of the desired speed of the equipped vehicle to the speed at the downstream congested traffic. Numerical simulations are carried out to show the influence of the penetration rate of the equipped vehicles on traffic flow stability and capacity in a freeway.

  19. Dynamic modeling and simulation of planetary rovers

    NASA Technical Reports Server (NTRS)

    Lindemann, Randel A.

    1992-01-01

    This paper documents a preliminary study into the dynamic modeling and computer simulation of wheeled surface vehicles. The research centered on the feasibility of using commercially available multibody dynamics codes running on engineering workstations to perform the analysis. The results indicated that physically representative vehicle mechanics can be modeled and simulated in state-of-the-art Computer Aided Engineering environments, but at excessive cost in modeling and computation time. The results lead to the recommendation for the development of an efficient rover mobility-specific software system. This system would be used for vehicle design and simulation in planetary environments; controls prototyping, design, and testing; as well as local navigation simulation and expectation planning.

  20. Understanding Terrorist Organizations with a Dynamic Model

    NASA Astrophysics Data System (ADS)

    Gutfraind, Alexander

    Terrorist organizations change over time because of processes such as recruitment and training as well as counter-terrorism (CT) measures, but the effects of these processes are typically studied qualitatively and in separation from each other. Seeking a more quantitative and integrated understanding, we constructed a simple dynamic model where equations describe how these processes change an organization’s membership. Analysis of the model yields a number of intuitive as well as novel findings. Most importantly it becomes possible to predict whether counter-terrorism measures would be sufficient to defeat the organization. Furthermore, we can prove in general that an organization would collapse if its strength and its pool of foot soldiers decline simultaneously. In contrast, a simultaneous decline in its strength and its pool of leaders is often insufficient and short-termed. These results and other like them demonstrate the great potential of dynamic models for informing terrorism scholarship and counter-terrorism policy making.

  1. Dynamical modelling of galactic disc outskirts

    NASA Astrophysics Data System (ADS)

    Athanassoula, E.

    2017-03-01

    I review briefly some dynamical models of structures in the outer parts of disc galaxies, including models of polar rings, tidal tails and bridges. I then discuss the density distribution in the outer parts of discs. For this, I compare observations to results of a model in which the disc galaxy is in fact the remnant of a major merger, and find good agreement. This comparison includes radial profiles of the projected surface density and of stellar age, as well as time evolution of the break radius and of the inner and outer disc scale lengths. I also compare the radial projected surface density profiles of dynamically motivated mono-age populations and find that, compared to older populations, younger ones have flatter density profiles in the inner region and steeper in the outer one. The break radius, however, does not vary with stellar age, again in good agreement with observations.

  2. Building Markov state models with solvent dynamics.

    PubMed

    Gu, Chen; Chang, Huang-Wei; Maibaum, Lutz; Pande, Vijay S; Carlsson, Gunnar E; Guibas, Leonidas J

    2013-01-01

    Markov state models have been widely used to study conformational changes of biological macromolecules. These models are built from short timescale simulations and then propagated to extract long timescale dynamics. However, the solvent information in molecular simulations are often ignored in current methods, because of the large number of solvent molecules in a system and the indistinguishability of solvent molecules upon their exchange. We present a solvent signature that compactly summarizes the solvent distribution in the high-dimensional data, and then define a distance metric between different configurations using this signature. We next incorporate the solvent information into the construction of Markov state models and present a fast geometric clustering algorithm which combines both the solute-based and solvent-based distances. We have tested our method on several different molecular dynamical systems, including alanine dipeptide, carbon nanotube, and benzene rings. With the new solvent-based signatures, we are able to identify different solvent distributions near the solute. Furthermore, when the solute has a concave shape, we can also capture the water number inside the solute structure. Finally we have compared the performances of different Markov state models. The experiment results show that our approach improves the existing methods both in the computational running time and the metastability. In this paper we have initiated an study to build Markov state models for molecular dynamical systems with solvent degrees of freedom. The methods we described should also be broadly applicable to a wide range of biomolecular simulation analyses.

  3. Building Markov state models with solvent dynamics

    PubMed Central

    2013-01-01

    Background Markov state models have been widely used to study conformational changes of biological macromolecules. These models are built from short timescale simulations and then propagated to extract long timescale dynamics. However, the solvent information in molecular simulations are often ignored in current methods, because of the large number of solvent molecules in a system and the indistinguishability of solvent molecules upon their exchange. Methods We present a solvent signature that compactly summarizes the solvent distribution in the high-dimensional data, and then define a distance metric between different configurations using this signature. We next incorporate the solvent information into the construction of Markov state models and present a fast geometric clustering algorithm which combines both the solute-based and solvent-based distances. Results We have tested our method on several different molecular dynamical systems, including alanine dipeptide, carbon nanotube, and benzene rings. With the new solvent-based signatures, we are able to identify different solvent distributions near the solute. Furthermore, when the solute has a concave shape, we can also capture the water number inside the solute structure. Finally we have compared the performances of different Markov state models. The experiment results show that our approach improves the existing methods both in the computational running time and the metastability. Conclusions In this paper we have initiated an study to build Markov state models for molecular dynamical systems with solvent degrees of freedom. The methods we described should also be broadly applicable to a wide range of biomolecular simulation analyses. PMID:23368418

  4. Next Generation Carbon-Nitrogen Dynamics Model

    NASA Astrophysics Data System (ADS)

    Xu, C.; Fisher, R. A.; Vrugt, J. A.; Wullschleger, S. D.; McDowell, N. G.

    2012-12-01

    Nitrogen is a key regulator of vegetation dynamics, soil carbon release, and terrestrial carbon cycles. Thus, to assess energy impacts on the global carbon cycle and future climates, it is critical that we have a mechanism-based and data-calibrated nitrogen model that simulates nitrogen limitation upon both above and belowground carbon dynamics. In this study, we developed a next generation nitrogen-carbon dynamic model within the NCAR Community Earth System Model (CESM). This next generation nitrogen-carbon dynamic model utilized 1) a mechanistic model of nitrogen limitation on photosynthesis with nitrogen trade-offs among light absorption, electron transport, carboxylation, respiration and storage; 2) an optimal leaf nitrogen model that links soil nitrogen availability and leaf nitrogen content; and 3) an ecosystem demography (ED) model that simulates the growth and light competition of tree cohorts and is currently coupled to CLM. Our three test cases with changes in CO2 concentration, growing temperature and radiation demonstrate the model's ability to predict the impact of altered environmental conditions on nitrogen allocations. Currently, we are testing the model against different datasets including soil fertilization and Free Air CO2 enrichment (FACE) experiments across different forest types. We expect that our calibrated model will considerably improve our understanding and predictability of vegetation-climate interactions.itrogen allocation model evaluations. The figure shows the scatter plots of predicted and measured Vc,max and Jmax scaled to 25 oC (i.e.,Vc,max25 and Jmax25) at elevated CO2 (570 ppm, test case one), reduced radiation in canopy (0.1-0.9 of the radiation at the top of canopy, test case two) and reduced growing temperature (15oC, test case three). The model is first calibrated using control data under ambient CO2 (370 ppm), radiation at the top of the canopy (621 μmol photon/m2/s), the normal growing temperature (30oC). The fitted model

  5. Age and Ethnic Differences in Cold Weather and Contagion Theories of Colds and Flu

    ERIC Educational Resources Information Center

    Sigelman, Carol K.

    2012-01-01

    Age and ethnic group differences in cold weather and contagion or germ theories of infectious disease were explored in two studies. A cold weather theory was frequently invoked to explain colds and to a lesser extent flu but became less prominent with age as children gained command of a germ theory of disease. Explanations of how contact with…

  6. Susceptibility to emotional contagion for negative emotions improves detection of smile authenticity

    PubMed Central

    Manera, Valeria; Grandi, Elisa; Colle, Livia

    2013-01-01

    A smile is a context-dependent emotional expression. A smiling face can signal the experience of enjoyable emotions, but people can also smile to convince another person that enjoyment is occurring when it is not. For this reason, the ability to discriminate between felt and faked enjoyment expressions is a crucial social skill. Despite its importance, adults show remarkable individual variation in this ability. Revealing the factors responsible for these huge individual differences is a key challenge in this domain. Here we investigated, on a large sample of participants, whether individual differences in smile authenticity recognition are accounted for by differences in the predisposition to experience other people's emotions, i.e., by susceptibility to emotional contagion. Results showed that susceptibility to emotional contagion for negative emotions increased smile authenticity detection, while susceptibility to emotional contagion for positive emotions worsened detection performance, because it leaded to categorize most of the faked smiles as sincere. These findings suggest that susceptibility to emotional contagion plays a key role in complex emotion recognition, and point out the importance of analyzing the tendency to experience other people's positive and negative emotions as separate abilities. PMID:23508036

  7. Components of the indirect effect in vaccine trials: identification of contagion and infectiousness effects

    PubMed Central

    VanderWeele, Tyler J.; Tchetgen Tchetgen, Eric J.; Halloran, M. Elizabeth

    2012-01-01

    Vaccination of one person may prevent the infection of another either because the vaccine prevents the first from being infected and from infecting the second, or because, even if the first person is infected, the vaccine may render the infection less infectious. We might refer to the first of these mechanisms as a contagion effect and the second as an infectiousness effect. In the simple setting of a randomized vaccine trial with households of size two, we use counterfactual theory under interference to provide formal definitions of a contagion effect and an unconditional infectiousness effect. Using ideas analogous to mediation analysis, we show that the indirect effect (the effect of one person’s vaccine on another’s outcome) can be decomposed into a contagion effect and an unconditional infectiousness effect on the risk-difference, risk-ratio, odds-ratio and vaccine-efficacy scales. We provide identification assumptions for such contagion and unconditional infectiousness effects, and describe a simple statistical technique to estimate these effects when they are identified. We also give a sensitivity-analysis technique to assess how inferences would change under violations of the identification assumptions. The concepts and results of this paper are illustrated with hypothetical vaccine-trial data. PMID:22828661

  8. Predicting Role Conflict, Overload and Contagion in Adult Women University Students with Families and Jobs.

    ERIC Educational Resources Information Center

    Home, Alice M.

    1998-01-01

    Data from 443 women combining work, family, and schooling showed that lower income increased their vulnerability to role conflict. Perceived intensity of student demands was the strongest predictor of role conflict, overload, and contagion (preoccupation with one role while performing another). Conflict and overload were eased somewhat by distance…

  9. An investigation of the determinants of motor contagion in preschool children.

    PubMed

    Saby, Joni N; Marshall, Peter J; Smythe, Robert; Bouquet, Cedric A; Comalli, Christina E

    2011-09-01

    The influence of action perception on action execution has been demonstrated by studies of motor contagion in which the observation of an action interferes with the concurrent execution of a different action. The current study extends prior work on the extent of motor contagion in early childhood, a period of development when the effects of action observation on action execution may be particularly salient. During a classroom story reading, children (mean age 4.8 years) were familiarized with two different-colored bears, one of which was used as a seemingly animate hand puppet while the other bear remained lifeless and inanimate. Children then completed a task in which they were instructed to move a stylus on a graphics tablet in the presence of background videos of each bear making horizontal arm movements which had biological (human-moved) or non-biological (machine-moved) origins. Motor contagion was assessed as the variability of stylus movements in the horizontal axis when children were instructed to produce vertical stylus movements. Significant levels of motor contagion were seen when children observed the previously animate bear in the non-biological motion condition and when they observed the previously inanimate bear in the biological motion condition. For future studies of social perception, this finding points to the potential importance of examining mismatches between prior experience with (or knowledge about) a particular agent and the subsequent behavior of that agent in a different context. Published by Elsevier B.V.

  10. Cognitive bias in rats evoked by ultrasonic vocalizations suggests emotional contagion.

    PubMed

    Saito, Yumi; Yuki, Shoko; Seki, Yoshimasa; Kagawa, Hiroko; Okanoya, Kazuo

    2016-11-01

    Emotional contagion occurs when an individual acquires the emotional state of another via social cues, and is an important component of empathy. Empathic responses seen in rodents are often explained by emotional contagion. Rats emit 50kHz ultrasonic vocalizations (USVs) in positive contexts, and emit 22kHz USVs in negative contexts. We tested whether rats show positive or negative emotional contagion after hearing conspecific USVs via a cognitive bias task. We hypothesized that animals in positive emotional states would perceive an ambiguous cue as being good (optimistic bias) whereas animals in negative states would perceive the same cue as being bad (pessimistic bias). Rats were trained to respond differently to two sounds with distinct pitches, each of which signaled either a positive or a negative outcome. An ambiguous cue with a frequency falling between the two stimuli tested whether rats interpreted it as positive or negative. Results showed that rats responded to ambiguous cues as positive when they heard the 50kHz USV (positive vocalizations) and negative when they heard the 22kHz USV (negative vocalizations). This suggests that conspecific USVs can evoke emotional contagion, both for positive and negative emotions, to change the affective states in receivers.

  11. [Almeria faced by contagion: health practice in the 18th century].

    PubMed

    Gómez Diaz, Donato; Gómez Diaz, Maria José

    2003-01-01

    Epidemics in Almeria during the 18th century and the beginnings of the 19th century are described, as well as the measures adopted to avoid them, regarding both internal contagion and the need for surveillance of incoming ships. The economic consequences of the prophylactic measures taken are also considered. Finally, the role of the Church in extreme situations is analyzed.

  12. Age and Ethnic Differences in Cold Weather and Contagion Theories of Colds and Flu

    ERIC Educational Resources Information Center

    Sigelman, Carol K.

    2012-01-01

    Age and ethnic group differences in cold weather and contagion or germ theories of infectious disease were explored in two studies. A cold weather theory was frequently invoked to explain colds and to a lesser extent flu but became less prominent with age as children gained command of a germ theory of disease. Explanations of how contact with…

  13. Emotional contagion, empathic concern and communicative responsiveness as variables affecting nurses' stress and occupational commitment.

    PubMed

    Omdahl, B L; O'Donnell, C

    1999-06-01

    Based on data gathered from registered nurses at two hospitals, this research examined the extent to which empathy variables contributed to nursing stress and occupational commitment. The empathy variables examined were emotional contagion (i.e. sharing the emotions of patients), empathic concern (i.e. being concerned for patients) and communicative effectiveness (i.e. effectively communicating with patients and their families). Nursing stress was explored through the variables of depersonalization, reduced personal accomplishment and emotional exhaustion. Multiple regression analyses revealed that the combination of the three emotional communication variables explained significant proportions of the variance in all three of the stress variables, as well as occupational commitment. The analyses further revealed that a lack of empathic concern and poor communicative responsiveness accounted for significant proportions of the variance in depersonalization. Lack of empathic concern, poor communicative responsiveness and high emotional contagion significantly contributed to reduced personal accomplishment. Emotional contagion explained a significant proportion of the variance in emotional exhaustion. Emotional contagion also significantly reduced occupational commitment. The findings are discussed in terms of nursing education and administration.

  14. Behavioral Contagion and Manageability: Learning Disability and Regular Education Teachers' Perspectives.

    ERIC Educational Resources Information Center

    Safran, Stephen P.; Safran, Joan S.

    1987-01-01

    Statistical analyses of the Behavior Manageability and Behavioral Contagion Scales completed by 44 regular education teachers and 44 teachers of the learning disabled found that no significant group differences existed, that withdrawn behavior was most difficult to manage, and that acting-out behaviors were most disruptive to other students.…

  15. Global dynamic modeling of a transmission system

    NASA Technical Reports Server (NTRS)

    Choy, F. K.; Qian, W.

    1993-01-01

    The work performed on global dynamic simulation and noise correlation of gear transmission systems at the University of Akron is outlined. The objective is to develop a comprehensive procedure to simulate the dynamics of the gear transmission system coupled with the effects of gear box vibrations. The developed numerical model is benchmarked with results from experimental tests at NASA Lewis Research Center. The modal synthesis approach is used to develop the global transient vibration analysis procedure used in the model. Modal dynamic characteristics of the rotor-gear-bearing system are calculated by the matrix transfer method while those of the gear box are evaluated by the finite element method (NASTRAN). A three-dimensional, axial-lateral coupled bearing model is used to couple the rotor vibrations with the gear box motion. The vibrations between the individual rotor systems are coupled through the nonlinear gear mesh interactions. The global equations of motion are solved in modal coordinates and the transient vibration of the system is evaluated by a variable time-stepping integration scheme. The relationship between housing vibration and resulting noise of the gear transmission system is generated by linear transfer functions using experimental data. A nonlinear relationship of the noise components to the fundamental mesh frequency is developed using the hypercoherence function. The numerically simulated vibrations and predicted noise of the gear transmission system are compared with the experimental results from the gear noise test rig at NASA Lewis Research Center. Results of the comparison indicate that the global dynamic model developed can accurately simulate the dynamics of a gear transmission system.

  16. Learning generative models of molecular dynamics

    PubMed Central

    2012-01-01

    We introduce three algorithms for learning generative models of molecular structures from molecular dynamics simulations. The first algorithm learns a Bayesian-optimal undirected probabilistic model over user-specified covariates (e.g., fluctuations, distances, angles, etc). L1 reg-ularization is used to ensure sparse models and thus reduce the risk of over-fitting the data. The topology of the resulting model reveals important couplings between different parts of the protein, thus aiding in the analysis of molecular motions. The generative nature of the model makes it well-suited to making predictions about the global effects of local structural changes (e.g., the binding of an allosteric regulator). Additionally, the model can be used to sample new conformations. The second algorithm learns a time-varying graphical model where the topology and parameters change smoothly along the trajectory, revealing the conformational sub-states. The last algorithm learns a Markov Chain over undirected graphical models which can be used to study and simulate kinetics. We demonstrate our algorithms on multiple molecular dynamics trajectories. PMID:22369071

  17. Learning generative models of molecular dynamics.

    PubMed

    Razavian, Narges Sharif; Kamisetty, Hetunandan; Langmead, Christopher J

    2012-01-01

    We introduce three algorithms for learning generative models of molecular structures from molecular dynamics simulations. The first algorithm learns a Bayesian-optimal undirected probabilistic model over user-specified covariates (e.g., fluctuations, distances, angles, etc). L1 regularization is used to ensure sparse models and thus reduce the risk of over-fitting the data. The topology of the resulting model reveals important couplings between different parts of the protein, thus aiding in the analysis of molecular motions. The generative nature of the model makes it well-suited to making predictions about the global effects of local structural changes (e.g., the binding of an allosteric regulator). Additionally, the model can be used to sample new conformations. The second algorithm learns a time-varying graphical model where the topology and parameters change smoothly along the trajectory, revealing the conformational sub-states. The last algorithm learns a Markov Chain over undirected graphical models which can be used to study and simulate kinetics. We demonstrate our algorithms on multiple molecular dynamics trajectories.

  18. Global Langevin model of multidimensional biomolecular dynamics

    NASA Astrophysics Data System (ADS)

    Schaudinnus, Norbert; Lickert, Benjamin; Biswas, Mithun; Stock, Gerhard

    2016-11-01

    Molecular dynamics simulations of biomolecular processes are often discussed in terms of diffusive motion on a low-dimensional free energy landscape F ( 𝒙 ) . To provide a theoretical basis for this interpretation, one may invoke the system-bath ansatz á la Zwanzig. That is, by assuming a time scale separation between the slow motion along the system coordinate x and the fast fluctuations of the bath, a memory-free Langevin equation can be derived that describes the system's motion on the free energy landscape F ( 𝒙 ) , which is damped by a friction field and driven by a stochastic force that is related to the friction via the fluctuation-dissipation theorem. While the theoretical formulation of Zwanzig typically assumes a highly idealized form of the bath Hamiltonian and the system-bath coupling, one would like to extend the approach to realistic data-based biomolecular systems. Here a practical method is proposed to construct an analytically defined global model of structural dynamics. Given a molecular dynamics simulation and adequate collective coordinates, the approach employs an "empirical valence bond"-type model which is suitable to represent multidimensional free energy landscapes as well as an approximate description of the friction field. Adopting alanine dipeptide and a three-dimensional model of heptaalanine as simple examples, the resulting Langevin model is shown to reproduce the results of the underlying all-atom simulations. Because the Langevin equation can also be shown to satisfy the underlying assumptions of the theory (such as a delta-correlated Gaussian-distributed noise), the global model provides a correct, albeit empirical, realization of Zwanzig's formulation. As an application, the model can be used to investigate the dependence of the system on parameter changes and to predict the effect of site-selective mutations on the dynamics.

  19. Dynamic Modeling of Meandering Alluvial Channels

    NASA Astrophysics Data System (ADS)

    Lan, Yongqiang

    1990-01-01

    The migration of meandering alluvial channels is investigated theoretically, numerically, and experimentally. An equation for the rate of bank erosion is derived from a two-dimensional continuity equation for sediment transport linked with the depth-averaged dynamic flow equations. A simple one-dimensional theoretical analysis of meander migration leads to a relationship between the migration rate and the relative channel curvature and sediment properties. The simple model appropriately simulates the pattern and rate of meander expansion and migrations of the White River, Indiana and the East Nishnabotna River, Iowa. Application of the one-dimensional model to sine -generated alluvial channels indicates that meander migration reaches its maximum when the relative radius of curvature reaches about 4.8, or when the sinuosity of meander approaches 1.3. A two-dimensional numerical model, DYNAMIC, which predicts both lateral and longitudinal migration of alluvial channels is then developed, based on a system of quasi -steady depth-averaged flow dynamic equations, a sediment continuity equation, and a bank erosion equation. A linear analysis of the two-dimensional model leads to a convolutional relation between the rate of meander migration and flow and sediment properties. In the two-dimensional numerical analysis, a numerical algorithm called FLOWSOL is developed to solve the flow dynamic equations. The flow algorithm is then linked to the sediment continuity equation and bank erosion equation to simulate bed deformation and bank erosion. The developed two-dimensional model is applied to calculate the velocity profiles in Rozovskii's experiments and the bed deformation and shear stress in Hooke's experiments. Good agreement is obtained between the calculated and measured velocities, shear stresses and bed profiles in all experiments. Small scaled meandering rivers are developed successfully on a floodplain with or without cohesive materials (about 3%) in a wide

  20. Overview of the GRC Stirling Convertor System Dynamic Model

    NASA Technical Reports Server (NTRS)

    Lewandowski, Edward J.; Regan, Timothy F.

    2004-01-01

    A Stirling Convertor System Dynamic Model has been developed at the Glenn Research Center for controls, dynamics, and systems development of free-piston convertor power systems. It models the Stirling cycle thermodynamics, heat flow, gas, mechanical, and mounting dynamics, the linear alternator, and the controller. The model's scope extends from the thermal energy input to thermal, mechanical dynamics, and electrical energy out, allowing one to study complex system interactions among subsystems. The model is a non-linear time-domain model containing sub-cycle dynamics, allowing it to simulate transient and dynamic phenomena that other models cannot. The model details and capability are discussed.

  1. A computational model for dynamic vision

    NASA Technical Reports Server (NTRS)

    Moezzi, Saied; Weymouth, Terry E.

    1990-01-01

    This paper describes a novel computational model for dynamic vision which promises to be both powerful and robust. Furthermore the paradigm is ideal for an active vision system where camera vergence changes dynamically. Its basis is the retinotopically indexed object-centered encoding of the early visual information. Specifically, the relative distances of objects to a set of referents is encoded in image registered maps. To illustrate the efficacy of the method, it is applied to the problem of dynamic stereo vision. Integration of depth information over multiple frames obtained by a moving robot generally requires precise information about the relative camera position from frame to frame. Usually, this information can only be approximated. The method facilitates the integration of depth information without direct use or knowledge of camera motion.

  2. Polarizable water model for Dissipative Particle Dynamics

    NASA Astrophysics Data System (ADS)

    Pivkin, Igor; Peter, Emanuel

    2015-11-01

    Dissipative Particle Dynamics (DPD) is an efficient particle-based method for modeling mesoscopic behavior of fluid systems. DPD forces conserve the momentum resulting in a correct description of hydrodynamic interactions. Polarizability has been introduced into some coarse-grained particle-based simulation methods; however it has not been done with DPD before. We developed a new polarizable coarse-grained water model for DPD, which employs long-range electrostatics and Drude oscillators. In this talk, we will present the model and its applications in simulations of membrane systems, where polarization effects play an essential role.

  3. Informations in Models of Evolutionary Dynamics

    NASA Astrophysics Data System (ADS)

    Rivoire, Olivier

    2016-03-01

    Biological organisms adapt to changes by processing informations from different sources, most notably from their ancestors and from their environment. We review an approach to quantify these informations by analyzing mathematical models of evolutionary dynamics and show how explicit results are obtained for a solvable subclass of these models. In several limits, the results coincide with those obtained in studies of information processing for communication, gambling or thermodynamics. In the most general case, however, information processing by biological populations shows unique features that motivate the analysis of specific models.

  4. Structural system identification: Structural dynamics model validation

    SciTech Connect

    Red-Horse, J.R.

    1997-04-01

    Structural system identification is concerned with the development of systematic procedures and tools for developing predictive analytical models based on a physical structure`s dynamic response characteristics. It is a multidisciplinary process that involves the ability (1) to define high fidelity physics-based analysis models, (2) to acquire accurate test-derived information for physical specimens using diagnostic experiments, (3) to validate the numerical simulation model by reconciling differences that inevitably exist between the analysis model and the experimental data, and (4) to quantify uncertainties in the final system models and subsequent numerical simulations. The goal of this project was to develop structural system identification techniques and software suitable for both research and production applications in code and model validation.

  5. Dynamic Modeling of an Evapotranspiration Cap

    SciTech Connect

    Jacob J. Jacobson; Steven Piet; Rafael Soto; Gerald Sehlke; Harold Heydt; John Visser

    2005-10-01

    The U.S. Department of Energy is scheduled to design and install hundreds of landfill caps/barriers over the next several decades and these caps will have a design life expectancy of up to 1,000 years. Other landfill caps with 30 year design lifetimes are reaching the end of their original design life; the changes to these caps need to be understood to provide a basis for lifetime extension. Defining the attributes that make a successful cap (one that isolates the waste from the environment) is crucial to these efforts. Because cap systems such as landfill caps are dynamic in nature, it is impossible to understand, monitor, and update lifetime predictions without understanding the dynamics of cap degradation, which is most often due to multiple interdependent factors rather than isolated independent events. In an attempt to understand the dynamics of cap degradation, a computer model using system dynamics is being developed to capture the complex behavior of an evapotranspiration cap. The specific objectives of this project are to capture the dynamic, nonlinear feedback loop structures underlying an evapotranspiration cap and, through computer simulation, gain a better understanding of long-term behavior, influencing factors, and, ultimately, long-term cap performance.

  6. Activated Dynamics in Dense Model Nanocomposites

    NASA Astrophysics Data System (ADS)

    Xie, Shijie; Schweizer, Kenneth

    The nonlinear Langevin equation approach is applied to investigate the ensemble-averaged activated dynamics of small molecule liquids (or disconnected segments in a polymer melt) in dense nanocomposites under model isobaric conditions where the spherical nanoparticles are dynamically fixed. Fully thermalized and quenched-replica integral equation theory methods are employed to investigate the influence on matrix dynamics of the equilibrium and nonequilibrium nanocomposite structure, respectively. In equilibrium, the miscibility window can be narrow due to depletion and bridging attraction induced phase separation which limits the study of activated dynamics to regimes where the barriers are relatively low. In contrast, by using replica integral equation theory, macroscopic demixing is suppressed, and the addition of nanoparticles can induce much slower activated matrix dynamics which can be studied over a wide range of pure liquid alpha relaxation times, interfacial attraction strengths and ranges, particle sizes and loadings, and mixture microstructures. Numerical results for the mean activated relaxation time, transient localization length, matrix elasticity and kinetic vitrification in the nanocomposite will be presented.

  7. Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model

    NASA Astrophysics Data System (ADS)

    Chaudhary, Nitin; Miller, Paul A.; Smith, Benjamin

    2016-04-01

    Dynamic global vegetation models (DGVMs) are an important platform to study past, present and future vegetation patterns together with associated biogeochemical cycles and climate feedbacks (e.g. Sitch et al. 2008, Smith et al. 2001). However, very few attempts have been made to simulate peatlands using DGVMs (Kleinen et al. 2012, Tang et al. 2015, Wania et al. 2009a). In the present study, we have improved the peatland dynamics in the state-of-the-art dynamic vegetation model (LPJ-GUESS) in order to understand the long-term evolution of northern peatland ecosystems and to assess the effect of changing climate on peatland carbon balance. We combined a dynamic multi-layer approach (Frolking et al. 2010, Hilbert et al. 2000) with soil freezing-thawing functionality (Ekici et al. 2015, Wania et al. 2009a) in LPJ-GUESS. The new model is named LPJ-GUESS Peatland (LPJ-GUESS-P) (Chaudhary et al. in prep). The model was calibrated and tested at the sub-arctic mire in Stordalen, Sweden, and the model was able to capture the reported long-term vegetation dynamics and peat accumulation patterns in the mire (Kokfelt et al. 2010). For evaluation, the model was run at 13 grid points across a north to south transect in Europe. The modelled peat accumulation values were found to be consistent with the published data for each grid point (Loisel et al. 2014). Finally, a series of additional experiments were carried out to investigate the vulnerability of high-latitude peatlands to climate change. We find that the Stordalen mire will sequester more carbon in the future due to milder and wetter climate conditions, longer growing seasons, and the carbon fertilization effect. References: - Chaudhary et al. (in prep.). Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model - Ekici A, et al. 2015. Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes. The Cryosphere 9: 1343

  8. Dynamic Alignment Models for Neural Coding

    PubMed Central

    Kollmorgen, Sepp; Hahnloser, Richard H. R.

    2014-01-01

    Recently, there have been remarkable advances in modeling the relationships between the sensory environment, neuronal responses, and behavior. However, most models cannot encompass variable stimulus-response relationships such as varying response latencies and state or context dependence of the neural code. Here, we consider response modeling as a dynamic alignment problem and model stimulus and response jointly by a mixed pair hidden Markov model (MPH). In MPHs, multiple stimulus-response relationships (e.g., receptive fields) are represented by different states or groups of states in a Markov chain. Each stimulus-response relationship features temporal flexibility, allowing modeling of variable response latencies, including noisy ones. We derive algorithms for learning of MPH parameters and for inference of spike response probabilities. We show that some linear-nonlinear Poisson cascade (LNP) models are a special case of MPHs. We demonstrate the efficiency and usefulness of MPHs in simulations of both jittered and switching spike responses to white noise and natural stimuli. Furthermore, we apply MPHs to extracellular single and multi-unit data recorded in cortical brain areas of singing birds to showcase a novel method for estimating response lag distributions. MPHs allow simultaneous estimation of receptive fields, latency statistics, and hidden state dynamics and so can help to uncover complex stimulus response relationships that are subject to variable timing and involve diverse neural codes. PMID:24625448

  9. Reduced Dynamic Models in Epithelial Transport

    PubMed Central

    Hernández, Julio A.

    2013-01-01

    Most models developed to represent transport across epithelia assume that the cell interior constitutes a homogeneous compartment, characterized by a single concentration value of the transported species. This conception differs significantly from the current view, in which the cellular compartment is regarded as a highly crowded media of marked structural heterogeneity. Can the finding of relatively simple dynamic properties of transport processes in epithelia be compatible with this complex structural conception of the cell interior? The purpose of this work is to contribute with one simple theoretical approach to answer this question. For this, the techniques of model reduction are utilized to obtain a two-state reduced model from more complex linear models of transcellular transport with a larger number of intermediate states. In these complex models, each state corresponds to the solute concentration in an intermediate intracellular compartment. In addition, the numerical studies reveal that it is possible to approximate a general two-state model under conditions where strict reduction of the complex models cannot be performed. These results contribute with arguments to reconcile the current conception of the cell interior as a highly complex medium with the finding of relatively simple dynamic properties of transport across epithelial cells. PMID:23533397

  10. Bioinactivation: Software for modelling dynamic microbial inactivation.

    PubMed

    Garre, Alberto; Fernández, Pablo S; Lindqvist, Roland; Egea, Jose A

    2017-03-01

    This contribution presents the bioinactivation software, which implements functions for the modelling of isothermal and non-isothermal microbial inactivation. This software offers features such as user-friendliness, modelling of dynamic conditions, possibility to choose the fitting algorithm and generation of prediction intervals. The software is offered in two different formats: Bioinactivation core and Bioinactivation SE. Bioinactivation core is a package for the R programming language, which includes features for the generation of predictions and for the fitting of models to inactivation experiments using non-linear regression or a Markov Chain Monte Carlo algorithm (MCMC). The calculations are based on inactivation models common in academia and industry (Bigelow, Peleg, Mafart and Geeraerd). Bioinactivation SE supplies a user-friendly interface to selected functions of Bioinactivation core, namely the model fitting of non-isothermal experiments and the generation of prediction intervals. The capabilities of bioinactivation are presented in this paper through a case study, modelling the non-isothermal inactivation of Bacillus sporothermodurans. This study has provided a full characterization of the response of the bacteria to dynamic temperature conditions, including confidence intervals for the model parameters and a prediction interval of the survivor curve. We conclude that the MCMC algorithm produces a better characterization of the biological uncertainty and variability than non-linear regression. The bioinactivation software can be relevant to the food and pharmaceutical industry, as well as to regulatory agencies, as part of a (quantitative) microbial risk assessment.

  11. Composite model for DNA torsion dynamics.

    PubMed

    Cadoni, Mariano; De Leo, Roberto; Gaeta, Giuseppe

    2007-02-01

    DNA torsion dynamics is essential in the transcription process; a simple model for it, in reasonable agreement with experimental observations, has been proposed by Yakushevich (Y) and developed by several authors; in this, the nucleotides (the DNA subunits made of a sugar-phosphate group and the attached nitrogen base) are described by a single degree of freedom. In this paper we propose and investigate, both analytically and numerically, a "composite" version of the Y model, in which the sugar-phosphate group and the base are described by separate degrees of freedom. The model proposed here contains as a particular case the Y model and shares with it many features and results, but represents an improvement from both the conceptual and the phenomenological point of view. It provides a more realistic description of DNA and possibly a justification for the use of models which consider the DNA chain as uniform. It shows that the existence of solitons is a generic feature of the underlying nonlinear dynamics and is to a large extent independent of the detailed modeling of DNA. The model we consider supports solitonic solutions, qualitatively and quantitatively very similar to the Y solitons, in a fully realistic range of all the physical parameters characterizing the DNA.

  12. Modeling of intensified high dynamic star tracker.

    PubMed

    Yan, Jinyun; Jiang, Jie; Zhang, Guangjun

    2017-01-23

    An intensified high dynamic star tracker (IHDST) is a photoelectric instrument and stably outputs three-axis attitude for a spacecraft at very high angular velocity. The IHDST uses an image intensifier to multiply the incident starlight. Thus, high sensitivity of the star detection is achieved under short exposure time such that extremely high dynamic performance is achieved. The IHDST differs from a traditional star tracker in terms of the imaging process. Therefore, we establish a quantum transfer model of IHDST based on stochastic process theory. By this model, the probability distribution of the output quantum number is obtained accurately. Then, we introduce two-dimensional Lorentz functions to describe the spatial spreading process of the IHDST. Considering the interaction of these two processes, a complete star imaging model of IHDST is provided. Using this model, the centroiding accuracy of the IHDST is analyzed in detail. Accordingly, a working parameter optimizing strategy is developed for high centroiding accuracy and improved dynamic performance. Finally, the laboratory tests and the night sky experiment support the conclusions.

  13. Echo Chambers: Emotional Contagion and Group Polarization on Facebook

    NASA Astrophysics Data System (ADS)

    Del Vicario, Michela; Vivaldo, Gianna; Bessi, Alessandro; Zollo, Fabiana; Scala, Antonio; Caldarelli, Guido; Quattrociocchi, Walter

    2016-12-01

    Recent findings showed that users on Facebook tend to select information that adhere to their system of beliefs and to form polarized groups – i.e., echo chambers. Such a tendency dominates information cascades and might affect public debates on social relevant issues. In this work we explore the structural evolution of communities of interest by accounting for users emotions and engagement. Focusing on the Facebook pages reporting on scientific and conspiracy content, we characterize the evolution of the size of the two communities by fitting daily resolution data with three growth models – i.e. the Gompertz model, the Logistic model, and the Log-logistic model. Although all the models appropriately describe the data structure, the Logistic one shows the best fit. Then, we explore the interplay between emotional state and engagement of users in the group dynamics. Our findings show that communities’ emotional behavior is affected by the users’ involvement inside the echo chamber. Indeed, to an higher involvement corresponds a more negative approach. Moreover, we observe that, on average, more active users show a faster shift towards the negativity than less active ones.

  14. Echo Chambers: Emotional Contagion and Group Polarization on Facebook

    PubMed Central

    Del Vicario, Michela; Vivaldo, Gianna; Bessi, Alessandro; Zollo, Fabiana; Scala, Antonio; Caldarelli, Guido; Quattrociocchi, Walter

    2016-01-01

    Recent findings showed that users on Facebook tend to select information that adhere to their system of beliefs and to form polarized groups – i.e., echo chambers. Such a tendency dominates information cascades and might affect public debates on social relevant issues. In this work we explore the structural evolution of communities of interest by accounting for users emotions and engagement. Focusing on the Facebook pages reporting on scientific and conspiracy content, we characterize the evolution of the size of the two communities by fitting daily resolution data with three growth models – i.e. the Gompertz model, the Logistic model, and the Log-logistic model. Although all the models appropriately describe the data structure, the Logistic one shows the best fit. Then, we explore the interplay between emotional state and engagement of users in the group dynamics. Our findings show that communities’ emotional behavior is affected by the users’ involvement inside the echo chamber. Indeed, to an higher involvement corresponds a more negative approach. Moreover, we observe that, on average, more active users show a faster shift towards the negativity than less active ones. PMID:27905402

  15. Echo Chambers: Emotional Contagion and Group Polarization on Facebook.

    PubMed

    Del Vicario, Michela; Vivaldo, Gianna; Bessi, Alessandro; Zollo, Fabiana; Scala, Antonio; Caldarelli, Guido; Quattrociocchi, Walter

    2016-12-01

    Recent findings showed that users on Facebook tend to select information that adhere to their system of beliefs and to form polarized groups - i.e., echo chambers. Such a tendency dominates information cascades and might affect public debates on social relevant issues. In this work we explore the structural evolution of communities of interest by accounting for users emotions and engagement. Focusing on the Facebook pages reporting on scientific and conspiracy content, we characterize the evolution of the size of the two communities by fitting daily resolution data with three growth models - i.e. the Gompertz model, the Logistic model, and the Log-logistic model. Although all the models appropriately describe the data structure, the Logistic one shows the best fit. Then, we explore the interplay between emotional state and engagement of users in the group dynamics. Our findings show that communities' emotional behavior is affected by the users' involvement inside the echo chamber. Indeed, to an higher involvement corresponds a more negative approach. Moreover, we observe that, on average, more active users show a faster shift towards the negativity than less active ones.

  16. Dynamical Causal Modeling from a Quantum Dynamical Perspective

    SciTech Connect

    Demiralp, Emre; Demiralp, Metin

    2010-09-30

    Recent research suggests that any set of first order linear vector ODEs can be converted to a set of specific vector ODEs adhering to what we have called ''Quantum Harmonical Form (QHF)''. QHF has been developed using a virtual quantum multi harmonic oscillator system where mass and force constants are considered to be time variant and the Hamiltonian is defined as a conic structure over positions and momenta to conserve the Hermiticity. As described in previous works, the conversion to QHF requires the matrix coefficient of the first set of ODEs to be a normal matrix. In this paper, this limitation is circumvented using a space extension approach expanding the potential applicability of this method. Overall, conversion to QHF allows the investigation of a set of ODEs using mathematical tools available to the investigation of the physical concepts underlying quantum harmonic oscillators. The utility of QHF in the context of dynamical systems and dynamical causal modeling in behavioral and cognitive neuroscience is briefly discussed.

  17. Atomic-scale dynamics of a model glass-forming metallic liquid: Dynamical crossover, dynamical decoupling, and dynamical clustering

    DOE PAGES

    Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang

    2015-04-01

    The phase behavior of multi-component metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamic aspects of such a model ternary metallic liquid Cu40Zr51Al9 using molecular dynamics simulation with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (diffusion coefficient, relaxation times, and shear viscosity) bordered at Tx ~1300K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs in the equilibrium liquid state well above the melting temperature of the system (Tm ~ 900K), and the crossover temperature ismore » roughly twice of the glass-transition temperature (Tg). Below Tx, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a non-parametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below Tx and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter and the four-point correlation function.« less

  18. Atomic-scale dynamics of a model glass-forming metallic liquid: Dynamical crossover, dynamical decoupling, and dynamical clustering

    NASA Astrophysics Data System (ADS)

    Jaiswal, Abhishek; Egami, Takeshi; Zhang, Yang

    2015-04-01

    The phase behavior of multicomponent metallic liquids is exceedingly complex because of the convoluted many-body and many-elemental interactions. Herein, we present systematic studies of the dynamical aspects of a model ternary metallic liquid Cu40Zr51Al9 using molecular dynamics simulations with embedded atom method. We observed a dynamical crossover from Arrhenius to super-Arrhenius behavior in the transport properties (self diffusion coefficient, self relaxation time, and shear viscosity) bordered at Tx˜1300 K. Unlike in many molecular and macromolecular liquids, this crossover phenomenon occurs well above the melting point of the system (Tm˜900 K) in the equilibrium liquid state; and the crossover temperature Tx is roughly twice of the glass-transition temperature of the system (Tg). Below Tx, we found the elemental dynamics decoupled and the Stokes-Einstein relation broke down, indicating the onset of heterogeneous spatially correlated dynamics in the system mediated by dynamic communications among local configurational excitations. To directly characterize and visualize the correlated dynamics, we employed a nonparametric, unsupervised machine learning technique and identified dynamical clusters of atoms with similar atomic mobility. The revealed average dynamical cluster size shows an accelerated increase below Tx and mimics the trend observed in other ensemble averaged quantities that are commonly used to quantify the spatially heterogeneous dynamics such as the non-Gaussian parameter α2 and the four-point correlation function χ4.

  19. Dynamic material modeling in hot forging

    SciTech Connect

    El-Gizawy, A.S. )

    1992-03-01

    A dynamic material model that characterized flow behavior in the workpiece under forging conditions was required to optimize the process and produce defect-free product at minimum cost. Constitutive equations describe the relationship between stress, strain rate, and temperature under forging conditions. Using aluminum alloy 7050, numerous deformation experiments were conducted to fully characterize constitutive equation variables. A thorough description of the experimental arrangement was provided. Flow data and efficiency data were assembled into a three-dimensional plot of temperature vs. strain rate vs. deformation efficiency to produce an efficiency map. The efficiency map provided the information required for optimization of forging process design. The results of dynamic modeling of the material were used in simulating the isothermal forging of a particular part. Recommendations concerning optimum preform design and processing conditions were reported.

  20. The dynamic radiation environment assimilation model (DREAM)

    SciTech Connect

    Reeves, Geoffrey D; Koller, Josef; Tokar, Robert L; Chen, Yue; Henderson, Michael G; Friedel, Reiner H

    2010-01-01

    The Dynamic Radiation Environment Assimilation Model (DREAM) is a 3-year effort sponsored by the US Department of Energy to provide global, retrospective, or real-time specification of the natural and potential nuclear radiation environments. The DREAM model uses Kalman filtering techniques that combine the strengths of new physical models of the radiation belts with electron observations from long-term satellite systems such as GPS and geosynchronous systems. DREAM includes a physics model for the production and long-term evolution of artificial radiation belts from high altitude nuclear explosions. DREAM has been validated against satellites in arbitrary orbits and consistently produces more accurate results than existing models. Tools for user-specific applications and graphical displays are in beta testing and a real-time version of DREAM has been in continuous operation since November 2009.

  1. Dynamic plasmapause model based on THEMIS measurements

    NASA Astrophysics Data System (ADS)

    Liu, W.; Liu, X.

    2015-12-01

    We will present a dynamic plasmapause location model established based on five years of THEMIS measurements from 2009 to 2013. In total, 5878 plasmapause crossing events are identified, sufficiently covering all 24 Magnetic Local Time (MLT) sectors. Based on this plasmapause crossing database, we investigate the correlations between plasmapause locations with solar wind parameters and geomagnetic indices. Input parameters for the best fits are obtained for different MLT sectors and finally we choose five input parameters to build a plasmapause location model, including five-minute-averaged SYM-H, AL and AU indices as well as hourly-averaged AE and Kp indices. An out-of-sample comparison on the evolution of the plasmapause is shown during April 2001 magnetic storm, demonstrating good agreement between model results and observations. Two major advantages are achieved by this model. First, this model provides plasmapause locations at 24 MLT sectors, still providing good consistency with observations. Second, this model is able to reproduce dynamic variations of plasmapause in the time scale as short as five minutes.

  2. Molecular dynamics modelling of solidification in metals

    SciTech Connect

    Boercker, D.B.; Belak, J.; Glosli, J.

    1997-12-31

    Molecular dynamics modeling is used to study the solidification of metals at high pressure and temperature. Constant pressure MD is applied to a simulation cell initially filled with both solid and molten metal. The solid/liquid interface is tracked as a function of time, and the data are used to estimate growth rates of crystallites at high pressure and temperature in Ta and Mg.

  3. Modeling the dynamical systems on experimental data

    NASA Astrophysics Data System (ADS)

    Janson, Natalie B.; Anishchenko, Vadim S.

    1996-06-01

    An attempt is made in the work to create qualitative models of some real biological systems, i.e., isolated frog's heart, a human's heart and a blood circulation system of a white rat. Sampled one-dimensional realizations of these systems were taken as the initial data. Correlation dimensions were calculated to evaluate the embedding dimensions of the systems' attractors. The result of the work are the systems of ordinary differential equations which approximately describe the dynamics of the systems under investigation.

  4. Dynamic analysis of a parasite population model

    NASA Astrophysics Data System (ADS)

    Sibona, G. J.; Condat, C. A.

    2002-03-01

    We study the dynamics of a model that describes the competitive interaction between an invading species (a parasite) and its antibodies in an living being. This model was recently used to examine the dynamical competition between Tripanosoma cruzi and its antibodies during the acute phase of Chagas' disease. Depending on the antibody properties, the model yields three types of outcomes, corresponding, respectively, to healing, chronic disease, and host death. Here, we study the dynamics of the parasite-antibody interaction with the help of simulations, obtaining phase trajectories and phase diagrams for the system. We show that, under certain conditions, the size of the parasite inoculation can be crucial for the infection outcome and that a retardation in the stimulated production of an antibody species may result in the parasite gaining a definitive advantage. We also find a criterion for the relative sizes of the parameters that are required if parasite-generated decoys are indeed to help the invasion. Decoys may also induce a qualitatively different outcome: a limit cycle for the antibody-parasite population phase trajectories.

  5. Dynamical model of birdsong maintenance and control

    NASA Astrophysics Data System (ADS)

    Abarbanel, Henry D. I.; Talathi, Sachin S.; Mindlin, Gabriel; Rabinovich, Misha; Gibb, Leif

    2004-11-01

    The neuroethology of song learning, production, and maintenance in songbirds presents interesting similarities to human speech. We have developed a biophysical model of the manner in which song could be maintained in adult songbirds. This model may inform us about the human counterpart to these processes. In songbirds, signals generated in nucleus High Vocal center (HVc) follow a direct route along a premotor pathway to the robust nucleus of the archistriatum (RA) as well as an indirect route to RA through the anterior forebrain pathway (AFP): the neurons of RA are innervated from both sources. HVc expresses very sparse bursts of spikes having interspike intervals of about 2ms . The expressions of these bursts arrive at the RA with a time difference ΔT≈50±10ms between the two pathways. The observed combination of AMPA and NMDA receptors at RA projection neurons suggests that long-term potentiation and long-term depression can both be induced by spike timing plasticity through the pairing of the HVc and AFP signals. We present a dynamical model that stabilizes this synaptic plasticity through a feedback from the RA to the AFP using known connections. The stabilization occurs dynamically and is absent when the RA→AFP connection is removed. This requires a dynamical selection of ΔT . The model does this, and ΔT lies within the observed range. Our model represents an illustration of a functional consequence of activity-dependent plasticity directly connected with neuroethological observations. Within the model the parameters of the AFP, and thus the magnitude of ΔT , can also be tuned to an unstable regime. This means that destabilization might be induced by neuromodulation of the AFP.

  6. Dynamic Factor Analysis Models with Time-Varying Parameters

    ERIC Educational Resources Information Center

    Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian

    2011-01-01

    Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…

  7. Dynamic Factor Analysis Models with Time-Varying Parameters

    ERIC Educational Resources Information Center

    Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian

    2011-01-01

    Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…

  8. DYNAMICAL MODELING OF GALAXY MERGERS USING IDENTIKIT

    SciTech Connect

    Privon, G. C.; Evans, A. S.; Barnes, J. E.; Hibbard, J. E.; Yun, M. S.; Mazzarella, J. M.; Armus, L.; Surace, J.

    2013-07-10

    We present dynamical models of four interacting systems: NGC 5257/8, The Mice, the Antennae, and NGC 2623. The parameter space of the encounters are constrained using the Identikit model-matching and visualization tool. Identikit utilizes hybrid N-body and test particle simulations to enable rapid exploration of the parameter space of galaxy mergers. The Identikit-derived matches of these systems are reproduced with self-consistent collisionless simulations which show very similar results. The models generally reproduce the observed morphology and H I kinematics of the tidal tails in these systems with reasonable properties inferred for the progenitor galaxies. The models presented here are the first to appear in the literature for NGC 5257/8 and NGC 2623, and The Mice and the Antennae are compared with previously published models. Based on the assumed mass model and our derived initial conditions, the models indicate that the four systems are currently being viewed 175-260 Myr after first passage and cover a wide range of merger stages. In some instances there are mismatches between the models and the data (e.g., in the length of a tail); these are likely due to our adoption of a single mass model for all galaxies. Despite the use of a single mass model, these results demonstrate the utility of Identikit in constraining the parameter space for galaxy mergers when applied to real data.

  9. Simple models for biomembrane structure and dynamics

    NASA Astrophysics Data System (ADS)

    Brown, Frank L. H.

    2007-07-01

    Simulation of biomembranes over length and time scales relevant to cellular biology is not currently feasible with molecular dynamics including full atomic detail. Barring an unforeseen revolution in the computer industry, this situation will not change for many decades. We present two coarse grained simulation models for biomembranes that treat water implicitly (i.e. no water molecules appear in our simulations. The hydrophobic effect, hydrodynamics and related properties are approximately included without simulation of solvent). These models enable the study of systems and phenomena previously intractable to simulation. The influence of membrane bound proteins on lipid ordering and the diffusion of membrane bound proteins is discussed.

  10. Cytoskeleton Dynamics: A Continuum Cooperative Hydrolysis Model

    NASA Astrophysics Data System (ADS)

    Xu, Jian-Wei; Cheng, Bo; Feng, Yu-Yu; Wang, Zi-Qing; Wang, Guo-Dong

    2015-05-01

    Cytoskeleton is a network of filamentous proteins, such as actin filaments and microtubules. We propose a continuum cooperative hydrolysis model which possesses exactly analytical solution to describe the dynamics of filament. The results show that the cooperativity leads to non negative-exponential distribution of T (ATP or GTP) subunits. As an application, we investigate the treadmilling phenomenon using our model. It is shown that the cooperativity remarkably affects the length of filament. Supported by Chinese Universities Scientific Fund under Grant No. 2014YB029 and National Natural Science Foundation of China under Grant No. 11205123

  11. Population Model with a Dynamic Food Supply

    NASA Astrophysics Data System (ADS)

    Dickman, Ronald; da Silva Nascimento, Jonas

    2009-09-01

    We propose a simple population model including the food supply as a dynamic variable. In the model, survival of an organism depends on a certain minimum rate of food consumption; a higher rate of consumption is required for reproduction. We investigate the stationary behavior under steady food input, and the transient behavior of growth and decay when food is present initially but is not replenished. Under a periodic food supply, the system exhibits period-doubling bifurcations and chaos in certain ranges of the reproduction rate. Bifurcations and chaos are favored by a slow reproduction rate and a long period of food-supply oscillation.

  12. Approaches for modeling magnetic nanoparticle dynamics

    PubMed Central

    Reeves, Daniel B; Weaver, John B

    2014-01-01

    Magnetic nanoparticles are useful biological probes as well as therapeutic agents. There have been several approaches used to model nanoparticle magnetization dynamics for both Brownian as well as Néel rotation. The magnetizations are often of interest and can be compared with experimental results. Here we summarize these approaches including the Stoner-Wohlfarth approach, and stochastic approaches including thermal fluctuations. Non-equilibrium related temperature effects can be described by a distribution function approach (Fokker-Planck equation) or a stochastic differential equation (Langevin equation). Approximate models in several regimes can be derived from these general approaches to simplify implementation. PMID:25271360

  13. Dynamical α -cluster model of 16O

    NASA Astrophysics Data System (ADS)

    Halcrow, C. J.; King, C.; Manton, N. S.

    2017-03-01

    We calculate the low-lying spectrum of the 16O nucleus using an α -cluster model which includes the important tetrahedral and square configurations. Our approach is motivated by the dynamics of α -particle scattering in the Skyrme model. We are able to replicate the large energy splitting that is observed between states of identical spin but opposite parities. We also provide a novel interpretation of the first excited state of 16O and make predictions for the energies of 6- states that have yet to be observed experimentally.

  14. Modeling the dynamics of bivalent histone modifications.

    PubMed

    Ku, Wai Lim; Girvan, Michelle; Yuan, Guo-Cheng; Sorrentino, Francesco; Ott, Edward

    2013-01-01

    Epigenetic modifications to histones may promote either activation or repression of the transcription of nearby genes. Recent experimental studies show that the promoters of many lineage-control genes in stem cells have "bivalent domains" in which the nucleosomes contain both active (H3K4me3) and repressive (H3K27me3) marks. It is generally agreed that bivalent domains play an important role in stem cell differentiation, but the underlying mechanisms remain unclear. Here we formulate a mathematical model to investigate the dynamic properties of histone modification patterns. We then illustrate that our modeling framework can be used to capture key features of experimentally observed combinatorial chromatin states.

  15. A dynamical model for bark beetle outbreaks.

    PubMed

    Křivan, Vlastimil; Lewis, Mark; Bentz, Barbara J; Bewick, Sharon; Lenhart, Suzanne M; Liebhold, Andrew

    2016-10-21

    Tree-killing bark beetles are major disturbance agents affecting coniferous forest ecosystems. The role of environmental conditions on driving beetle outbreaks is becoming increasingly important as global climatic change alters environmental factors, such as drought stress, that, in turn, govern tree resistance. Furthermore, dynamics between beetles and trees are highly nonlinear, due to complex aggregation behaviors exhibited by beetles attacking trees. Models have a role to play in helping unravel the effects of variable tree resistance and beetle aggregation on bark beetle outbreaks. In this article we develop a new mathematical model for bark beetle outbreaks using an analogy with epidemiological models. Because the model operates on several distinct time scales, singular perturbation methods are used to simplify the model. The result is a dynamical system that tracks populations of uninfested and infested trees. A limiting case of the model is a discontinuous function of state variables, leading to solutions in the Filippov sense. The model assumes an extensive seed-bank so that tree recruitment is possible even if trees go extinct. Two scenarios are considered for immigration of new beetles. The first is a single tree stand with beetles immigrating from outside while the second considers two forest stands with beetle dispersal between them. For the seed-bank driven recruitment rate, when beetle immigration is low, the forest stand recovers to a beetle-free state. At high beetle immigration rates beetle populations approach an endemic equilibrium state. At intermediate immigration rates, the model predicts bistability as the forest can be in either of the two equilibrium states: a healthy forest, or a forest with an endemic beetle population. The model bistability leads to hysteresis. Interactions between two stands show how a less resistant stand of trees may provide an initial toe-hold for the invasion, which later leads to a regional beetle outbreak in the

  16. Dynamic stall simulation including turbulence modeling

    SciTech Connect

    Allet, A.; Halle, S.; Paraschivoiu, I.

    1995-09-01

    The objective of this study is to investigate the two-dimensional unsteady flow around an airfoil undergoing a Darrieus motion in dynamic stall conditions. For this purpose, a numerical solver based on the solution of the Reynolds-averaged Navier-Stokes equations expressed in a streamfunction-vorticity formulation in a non-inertial frame of reference was developed. The governing equations are solved by the streamline upwind Petrov-Galerkin finite element method (FEM). Temporal discretization is achieved by second-order-accurate finite differences. The resulting global matrix system is linearized by the Newton method and solved by the generalized minimum residual method (GMRES) with an incomplete triangular factorization preconditioning (ILU). Turbulence effects are introduced in the solver by an eddy viscosity model. The investigation centers on an evaluation of the possibilities of several turbulence models, including the algebraic Cebeci-Smith model (CSM) and the nonequilibrium Johnson-King model (JKM). In an effort to predict dynamic stall features on rotating airfoils, first the authors present some testing results concerning the performance of both turbulence models for the flat plate case. Then, computed flow structure together with aerodynamic coefficients for a NACA 0015 airfoil in Darrieus motion under stall conditions are presented.

  17. Directed network discovery with dynamic network modelling.

    PubMed

    Anzellotti, Stefano; Kliemann, Dorit; Jacoby, Nir; Saxe, Rebecca

    2017-05-01

    Cognitive tasks recruit multiple brain regions. Understanding how these regions influence each other (the network structure) is an important step to characterize the neural basis of cognitive processes. Often, limited evidence is available to restrict the range of hypotheses a priori, and techniques that sift efficiently through a large number of possible network structures are needed (network discovery). This article introduces a novel modelling technique for network discovery (Dynamic Network Modelling or DNM) that builds on ideas from Granger Causality and Dynamic Causal Modelling introducing three key changes: (1) efficient network discovery is implemented with statistical tests on the consistency of model parameters across participants, (2) the tests take into account the magnitude and sign of each influence, and (3) variance explained in independent data is used as an absolute (rather than relative) measure of the quality of the network model. In this article, we outline the functioning of DNM, we validate DNM in simulated data for which the ground truth is known, and we report an example of its application to the investigation of influences between regions during emotion recognition, revealing top-down influences from brain regions encoding abstract representations of emotions (medial prefrontal cortex and superior temporal sulcus) onto regions engaged in the perceptual analysis of facial expressions (occipital face area and fusiform face area) when participants are asked to switch between reporting the emotional valence and the age of a face. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Restoration of the Potosi Dynamic Model 2010

    SciTech Connect

    Adushita, Yasmin; Leetaru, Hannes

    2014-09-30

    In topical Report DOE/FE0002068-1 [2] technical performance evaluations on the Cambrian Potosi Formation were performed through reservoir modeling. The data included formation tops from mud logs, well logs from the VW1 and the CCS1 wells, structural and stratigraphic formation from three dimensional (3D) seismic data, and field data from several waste water injection wells for Potosi Formation. Intention was for two million tons per annum (MTPA) of CO2 to be injected for 20 years. In this Task the 2010 Potosi heterogeneous model (referred to as the "Potosi Dynamic Model 2010" in this report) was re-run using a new injection scenario; 3.2 MTPA for 30 years. The extent of the Potosi Dynamic Model 2010, however, appeared too small for the new injection target. It was not sufficiently large enough to accommodate the evolution of the plume. Also, it might have overestimated the injection capacity by enhancing too much the pressure relief due to the relatively close proximity between the injector and the infinite acting boundaries. The new model, Potosi Dynamic Model 2013a, was built by extending the Potosi Dynamic Model 2010 grid to 30 miles x 30 miles (48 km by 48 km), while preserving all property modeling workflows and layering. This model was retained as the base case. Potosi Dynamic Model 2013.a gives an average CO2 injection rate of 1.4 MTPA and cumulative injection of 43 Mt in 30 years, which corresponds to 45% of the injection target. This implies that according to this preliminary model, a minimum of three (3) wells could be required to achieve the injection target. The injectivity evaluation of the Potosi formation will be revisited in topical Report 15 during which more data will be integrated in the modeling exercise. A vertical flow performance evaluation could be considered for the succeeding task to determine the appropriate tubing size, the required injection tubing head pressure (THP) and to investigate whether the corresponding well injection rate

  19. A Multiscale Model for Virus Capsid Dynamics

    PubMed Central

    Chen, Changjun; Saxena, Rishu; Wei, Guo-Wei

    2010-01-01

    Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. PMID:20224756

  20. Dynamical models of happiness with fractional order

    NASA Astrophysics Data System (ADS)

    Song, Lei; Xu, Shiyun; Yang, Jianying

    2010-03-01

    This present study focuses on a dynamical model of happiness described through fractional-order differential equations. By categorizing people of different personality and different impact factor of memory (IFM) with different set of model parameters, it is demonstrated via numerical simulations that such fractional-order models could exhibit various behaviors with and without external circumstance. Moreover, control and synchronization problems of this model are discussed, which correspond to the control of emotion as well as emotion synchronization in real life. This study is an endeavor to combine the psychological knowledge with control problems and system theories, and some implications for psychotherapy as well as hints of a personal approach to life are both proposed.