Nonlinear Dynamic Modeling and Social Contagion: Reply to Stoolmiller (1998).
ERIC Educational Resources Information Center
Rodgers, Joseph Lee; Rowe, David C.; Buster, Maury
1998-01-01
Reviews and comments on Stoolmiller's (1998) criticisms of an epidemic model of the onset of social activities (EMOSA) and about nonlinear modeling in general. Discusses the idea of social contagion as a general theoretical tool. (Author)
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…
Social contagion, adolescent sexual behavior, and pregnancy: a nonlinear dynamic EMOSA model.
Rodgers, J L; Rowe, D C; Buster, M
1998-09-01
Nonlinear dynamic modeling has useful developmental applications. The authors introduce this class of models and contrast them with traditional linear models. Epidemic models of the onset of social activities (EMOSA models) are a special case, motivated by J. L. Rodgers and D. C. Rowe's (1993) social contagion theory, which predict the spread of adolescent behaviors like smoking, drinking, delinquency, and sexuality. In this article, a biological outcome, pregnancy, is added to an earlier EMOSA sexuality model. Parameters quantify likelihood of pregnancy for girls of different sexuality statuses. Five different sexuality/pregnancy models compete to explain variance in national prevalence curves. One finding was that, in the context of the authors' simplified model, adolescent girls have an approximately constant probability of pregnancy across age and time since virginity. PMID:9779754
Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.
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. PMID:26505473
Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks
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
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.
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)
Dynamics of social contagions with memory of nonredundant information.
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. PMID:26274238
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.
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…
Dynamics of social contagions with limited contact capacity.
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. PMID:26520068
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.
Low prevalence, quasi-stationarity and power-law behavior in a model of contagion spreading
NASA Astrophysics Data System (ADS)
Montakhab, Afshin; Manshour, Pouya
2012-09-01
While contagion (information, infection, etc.) spreading has been extensively studied recently, the role of active local agents has not been fully considered. Here, we propose and study a model of spreading which takes into account the strength or quality of contagions as well as the local probabilistic dynamics occurring at various nodes. Transmission occurs only after the quality-based fitness of the contagion has been evaluated by the local agent. We study such spreading dynamics on Erdös-Rényi as well as scale free networks. The model exhibits quality-dependent exponential time scales at early times leading to a slowly evolving quasi-stationary state. Low prevalence is seen for a wide range of contagion quality for arbitrary large networks. We also investigate the activity of nodes and find a power-law distribution with a robust exponent independent of network topology. These properties, while absent in standard theoretical models, are observed in recent empirical observations.
Emotional contagion and proto-organizing in human interaction dynamics.
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
Emotional contagion and proto-organizing in human interaction dynamics
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
Establishment of an animal model of depression contagion
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
The price of anarchy in mobility-driven contagion dynamics.
Nicolaides, Christos; Cueto-Felgueroso, Luis; Juanes, Ruben
2013-10-01
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
The price of anarchy in mobility-driven contagion dynamics
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
Social contagion and adolescent sexual behavior: a developmental EMOSA model.
Rodgers, J L; Rowe, D C
1993-07-01
Epidemic Models of the Onset of Social Activities (EMOSA models) describe the spread of adolescent transition behaviors (e.g., sexuality, smoking, and drinking) through an interacting adolescent network. A theory of social contagion is defined to explain how social influence affects sexual development. Contacts within a network can, with some transition rate or probability, result in an increase in level of sexual experience. Five stages of sexual development are posited. One submodel proposes a systematic progression through these stages; a competing submodel treats each as an independent process. These models are represented in sets of dynamically interacting recursive equations, which are fit to empirical prevalence data to estimate parameters. Model adjustments are substantively interpretable and can be used to test for and better understand social interaction processes that affect adolescent sexual behavior. PMID:8356187
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.
Contagion dynamics in time-varying metapopulation networks
NASA Astrophysics Data System (ADS)
Baronchelli, Andrea; Liu, Suyu; Perra, Nicola
2013-03-01
The metapopulation framework is adopted in a wide array of disciplines to describe systems of well separated yet connected subpopulations. The subgroups/patches are often represented as nodes in a network whose links represent the migration routes among them. The connections are usually considered as static, an approximation that is appropriate for the description of many systems, such as cities connected by human mobility, but it is obviously inadequate in those real systems where links evolve in time on a faster timescale. In the case of farmed animals, for example, the connections between each farm/node vary in time according to the different stages of production. Here we address this case by investigating simple contagion processes on temporal metapopulation networks. We focus on the SIR process, and we determine the mobility threshold for the onset of an epidemic spreading in the framework of activity-driven network models. Remarkably, we find profound differences from the case of static networks, determined by the crucial role played by the dynamical parameters defining the average number of instantaneously migrating individuals. Our results confirm the importance of addressing the time-varying properties of complex networks pointed out by the recent literature.
Dynamical influence processes on networks: general theory and applications to social contagion.
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. PMID:24032892
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.
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.
Thomas, A C
2013-02-20
I reflect on the statistical methods of the Christakis-Fowler studies on network-based contagion of traits by checking the sensitivity of these kinds of results to various alternate specifications and generative mechanisms. Despite the honest efforts of all involved, I remain pessimistic about establishing whether binary health outcomes or product adoptions are contagious if the evidence comes from simultaneously observed data. PMID:23341080
Multi-stage complex contagions.
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. PMID:23556961
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.
The karst contagion model: Synopsis and environmental implications
NASA Astrophysics Data System (ADS)
Kemmerly, Phillip R.
1989-03-01
The contagion model of karst terrane evolution focuses on the environmental implications for a large karst depression population on the Pennyroyal Plain (southern Kentucky) and the adjacent Western Highland Rim (Tennessee) immediately south of the Mammoth Cave Plateau. In karst terranes where the contagion model applies, there is a well-defined infrastructure comprised of hydrologic, structural geologic and geomorphic interacting elements that result in clustered depressions underlain by a radial conduit system. Clusters tend to be randomly distributed and typically contain a parent depression surrounded by numerous daughters. Groundwater flow is assumed to be turbulent and confined largely to conduits that are 3-dimensionally configured between clusters in a dendritic to trellis network. Parent depressions serve as conduit nodes for collecting groundwater migrating from beneath daughter depressions. Flow velocities in the 3-dimensional “cluster-cell” conduits exceed those in granular media by several orders of magnitude making pathogen and chemical contaminant migration rapid. Groundwater quality assessment in karst conduit hydrogeologic settings is difficult because monitoring wells are inappropriate. Monitoring wells may have a low probability of intercepting a major conduit and therefore the sampling regime must take into consideration the pulse discharge of pollutants in karst conduits. Representative water quality data must come from springs located near the local base level.
Exploring a contagion model for karst terrane evolution
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.
Dynamical influence processes on networks: General theory and applications to social contagion
NASA Astrophysics Data System (ADS)
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.
Coupled Contagion Dynamics of Fear and Disease: Mathematical and Computational Explorations
Epstein, Joshua M.; Parker, Jon; Cummings, Derek; Hammond, Ross A.
2008-01-01
Background In classical mathematical epidemiology, individuals do not adapt their contact behavior during epidemics. They do not endogenously engage, for example, in social distancing based on fear. Yet, adaptive behavior is well-documented in true epidemics. We explore the effect of including such behavior in models of epidemic dynamics. Methodology/Principal Findings Using both nonlinear dynamical systems and agent-based computation, we model two interacting contagion processes: one of disease and one of fear of the disease. Individuals can “contract” fear through contact with individuals who are infected with the disease (the sick), infected with fear only (the scared), and infected with both fear and disease (the sick and scared). Scared individuals–whether sick or not–may remove themselves from circulation with some probability, which affects the contact dynamic, and thus the disease epidemic proper. If we allow individuals to recover from fear and return to circulation, the coupled dynamics become quite rich, and can include multiple waves of infection. We also study flight as a behavioral response. Conclusions/Significance In a spatially extended setting, even relatively small levels of fear-inspired flight can have a dramatic impact on spatio-temporal epidemic dynamics. Self-isolation and spatial flight are only two of many possible actions that fear-infected individuals may take. Our main point is that behavioral adaptation of some sort must be considered. PMID:19079607
Social contagion theory: examining dynamic social networks and human behavior.
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. PMID:22711416
Social contagion theory: examining dynamic social networks and human behavior
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
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.
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.
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.
Phase transitions in contagion processes mediated by recurrent mobility patterns
NASA Astrophysics Data System (ADS)
Balcan, Duygu; Vespignani, Alessandro
2011-07-01
Human mobility and activity patterns mediate contagion on many levels, including the spatial spread of infectious diseases, diffusion of rumours, and emergence of consensus. These patterns however are often dominated by specific locations and recurrent flows and poorly modelled by the random diffusive dynamics generally used to study them. Here we develop a theoretical framework to analyse contagion within a network of locations where individuals recall their geographic origins. We find a phase transition between a regime in which the contagion affects a large fraction of the system and one in which only a small fraction is affected. This transition cannot be uncovered by continuous deterministic models because of the stochastic features of the contagion process and defines an invasion threshold that depends on mobility parameters, providing guidance for controlling contagion spread by constraining mobility processes. We recover the threshold behaviour by analysing diffusion processes mediated by real human commuting data.
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…
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.
Behavioral contagion in sibships.
Jones, D R; Jones, M B
1992-04-01
A behavior is "contagious" if one person is more likely to exhibit it when a relevant other person has already done so. In this sense, behavioral contagion is commonly thought to contribute to many social problems, such as drug abuse and teenage promiscuity. In this paper we focus on behavioral contagion in sibships. Borrowing a model from the theory of contagious diseases, we show that contagion will cause prevalence to increase with sibship size. This model also allows us to estimate the magnitude of the contagious factor relative to non-contagious factors. Finally, we develop two statistical tests for the presence of contagion. Results are presented for participation in a skill-development program and four child-psychiatric conditions: neurosis, hyperactivity, somatization, and conduct disorder. Evidence is presented that program participation is probably contagious and conduct disorder possibly so. The other three child-psychiatric conditions are shown not to be contagious. Implications for research and practice are discussed. PMID:1613681
Hutchinson, Marie
2013-04-01
Aim The aim of the present synthesis was to review the literature on bullying in the nursing workplace and develop an explanatory model for patterns of victimization and contagion within the workgroup. Background Although research has demonstrated that bullying can cause significant harm there has been little investigation or theorizing into the place of the workgroup as a vehicle for magnifying, transmitting or sustaining bullying. Evaluation Narrative synthesis of the literature on bullying in the nursing workplace. Key issues The putative model developed from a narrative synthesis of the available literature proposes four forms of bullying as workgroup manipulation. Conclusions The model provides insight into mechanisms for the contagion of bullying and victimization within workgroups and an explanatory mechanism for the way bullying can escalate to implicate patient care. Implications for Nurse Managers Recognizing workgroup manipulation processes and the patterns of victimization and contagion with the workgroup provides a deeper understanding of bullying and illustrates the place of intervention strategies which foster the emotional intelligence climate in nursing teams. PMID:23406069
Modeling colony collapse disorder in honeybees as a contagion.
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. PMID:25365602
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…
When is emotional contagion adaptive?
Nakahashi, Wataru; Ohtsuki, Hisashi
2015-09-01
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. PMID:26113192
NASA Astrophysics Data System (ADS)
Wang, Wei; Tang, Ming; Shu, Panpan; Wang, Zhen
2016-01-01
Heterogeneous adoption thresholds exist widely in social contagions, such as behavior spreading, but were always neglected in previous studies. To this end, we introduce heterogeneous adoption threshold distribution into a non-Markovian spreading threshold model, in which an individual adopts a behavior only when the received cumulative pieces of behavioral information from neighbors exceeds his adoption threshold. In order to understand the effects of heterogeneous adoption thresholds quantitatively, an edge-based compartmental theory is developed. A two-state spreading threshold model is taken as an example, in which some individuals have a low adoption threshold (i.e., activists) while the remaining ones hold a relatively higher adoption threshold (i.e., bigots). We find a hierarchical characteristic in adopting behavior, i.e., activists first adopt the behavior and then stimulate bigots to adopt the behavior. Interestingly, two types of crossover phenomena in phase transition occur: for a relatively low adoption threshold of bigots, a change from first-order to second-order phase transition can be triggered by increasing the fraction of activists; for a relatively higher adoption threshold of bigots, a change from hybrid to second-order phase transition can be induced by varying the fraction of activists, decreasing mean degree or enhancing network heterogeneity. The theoretical predictions based on the suggested theory agree very well with the simulation results.
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.
Structural diversity in social contagion.
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. PMID:22474360
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
Beyond Contagion: Reality Mining Reveals Complex Patterns of Social Influence.
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
Beyond Contagion: Reality Mining Reveals Complex Patterns of Social Influence
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
Seasonality and Dynamic Spatial Contagion of Air Pollution in 42 Chinese Cities
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
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.
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.
Explosive Contagion in Networks
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
Explosive Contagion in Networks.
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
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…
Measuring Emotional Contagion in Social Media.
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. PMID:26544688
Measuring Emotional Contagion in Social Media
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
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.
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.
Controlling Contagion Processes in Activity Driven Networks
NASA Astrophysics Data System (ADS)
Liu, Suyu; Perra, Nicola; Karsai, Márton; Vespignani, Alessandro
2014-03-01
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.
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.
The cultural contagion of conflict.
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
2012-03-01
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
The cultural contagion of conflict
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
Topological data analysis of contagion maps for examining spreading processes on networks
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
Topological data analysis of contagion maps for examining spreading processes on networks.
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 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. PMID:26194875
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.
Popularity Contagion among Adolescents
ERIC Educational Resources Information Center
Marks, Peter E. L.; Cillessen, Antonius H. N.; Crick, Nicki R.
2012-01-01
This study aimed to support the theory of popularity contagion, which posits that popularity spreads among friends spontaneously and regardless of behavioral changes. Peer nominations of status and behavior were collected annually between 6th and 12th grades from a total of 1062 adolescents. Longitudinal hypotheses were mostly supported using path…
NASA Astrophysics Data System (ADS)
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.
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.
A strategic interaction model of punishment favoring contagion of honest behavior.
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
A Strategic Interaction Model of Punishment Favoring Contagion of Honest Behavior
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
Contagion in Mass Killings and School Shootings
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
Hughey, Myra C; McCoy, Michael W; Vonesh, James R; Warkentin, Karen M
2012-10-23
Spatial contagion occurs when the perceived suitability of neighbouring habitat patches is not independent. As a result, organisms may colonize less-preferred patches near preferred patches and avoid preferred patches near non-preferred patches. Spatial contagion may thus alter colonization dynamics as well as the type and frequency of post-colonization interactions. Studies have only recently documented the phenomenon of spatial contagion and begun to examine its consequences for local recruitment. Here, we test for spatial contagion in the colonization of arboreal egg clutches of red-eyed treefrogs by a frogfly and examine the consequences of contagion for fly recruitment. In laboratory choice experiments, flies oviposit almost exclusively on clutches containing dead frog eggs. In nature, however, flies often colonize intact clutches without dead eggs. Consistent with predictions of contagion-induced oviposition, we found that flies more frequently colonize intact clutches near damaged clutches and rarely colonize intact clutches near other intact clutches. Moreover, contagion appears to benefit flies. Flies survived equally well and suffered less parasitism on clutches lacking dead eggs. This study demonstrates how reward contagion can influence colonization dynamics and suggests that colonization patterns caused by contagion may have important population- and community-level consequences. PMID:22832129
Spatial contagion drives colonization and recruitment of frogflies on clutches of red-eyed treefrogs
Hughey, Myra C.; McCoy, Michael W.; Vonesh, James R.; Warkentin, Karen M.
2012-01-01
Spatial contagion occurs when the perceived suitability of neighbouring habitat patches is not independent. As a result, organisms may colonize less-preferred patches near preferred patches and avoid preferred patches near non-preferred patches. Spatial contagion may thus alter colonization dynamics as well as the type and frequency of post-colonization interactions. Studies have only recently documented the phenomenon of spatial contagion and begun to examine its consequences for local recruitment. Here, we test for spatial contagion in the colonization of arboreal egg clutches of red-eyed treefrogs by a frogfly and examine the consequences of contagion for fly recruitment. In laboratory choice experiments, flies oviposit almost exclusively on clutches containing dead frog eggs. In nature, however, flies often colonize intact clutches without dead eggs. Consistent with predictions of contagion-induced oviposition, we found that flies more frequently colonize intact clutches near damaged clutches and rarely colonize intact clutches near other intact clutches. Moreover, contagion appears to benefit flies. Flies survived equally well and suffered less parasitism on clutches lacking dead eggs. This study demonstrates how reward contagion can influence colonization dynamics and suggests that colonization patterns caused by contagion may have important population- and community-level consequences. PMID:22832129
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.
Controlling Contagion Processes in Time-Varying Networks
NASA Astrophysics Data System (ADS)
Perra, Nicola; Liu, Suyu; Karsai, Marton; Vespignani, Alessandro
2014-03-01
The vast majority of strategies aimed at controlling contagion processes on networks considers the connectivity pattern of the system as either quenched or annealed. However, in the real world many networks are highly dynamical and evolve in time concurrently to the contagion process. Here, we derive an analytical framework for the study of control strategies specifically devised for time-varying networks. We consider the removal/immunization of individual nodes according the their activity in the network and develop a block variable mean-field approach that allows the derivation of the equations describing the evolution of the contagion process concurrently to the network dynamic. We derive the critical immunization threshold and assess the effectiveness of the control strategies. Finally, we validate the theoretical picture by simulating numerically the information spreading process and control strategies in both synthetic networks and a large-scale, real-world mobile telephone call dataset.
She more than he: gender bias supports the empathic nature of yawn contagion in Homo sapiens
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
She more than he: gender bias supports the empathic nature of yawn contagion in Homo sapiens.
Norscia, Ivan; Demuru, Elisa; Palagi, Elisabetta
2016-02-01
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
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.
ERIC Educational Resources Information Center
Hustinx, Lesley; Vanhove, Tim; Declercq, Anja; Hermans, Koen; Lammertyn, Frans
2005-01-01
In spite of a progressive institutionalisation of community-based learning into higher education, relatively little is known about the actual dynamics and correlates of volunteering by students. The study presented seeks a more in-depth understanding of the spontaneous, extracurricular involvement within a university student population. Data are…
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.
The modulation of motor contagion by intrapersonal sensorimotor experience.
Roberts, James W; Katayama, Orion; Lung, Tiffany; Constable, Merryn D; Elliott, Digby; Lyons, James L; Welsh, Timothy N
2016-06-15
Sensorimotor experiences can modify the internal models for action. These modifications can govern the discrepancies between predicted and actual sensory consequences, such as distinguishing self- and other-generated actions. This distinction may also contribute toward the inhibition of movement interference, which is strongly associated with the coupling of observed and executed actions. Therefore, movement interference could be mediated by the sensorimotor experiences underlying the self-other distinction. The present study examined the impact of sensorimotor experiences on involuntary movement interference (motor contagion). Participants were required to complete a motor contagion paradigm in which they executed horizontal arm movements while observing congruent (horizontal) or incongruent (vertical) arm movements of a model. This task was completed before and after a training protocol in which participants executed the same horizontal arm movements in the absence of the model stimuli. Different groups of participants trained with or without vision of their moving limb. Analysis of participants who were predisposed to motor contagion (involuntary movement interference during the observation of incongruent movements) revealed that the no vision group continued to demonstrate contagion at post-training, although the vision group did not. We propose that the vision group were able to integrate the visual afferent information with an internal model for action, which effectively refines the ability to match self-produced afferent and efferent sources of information during response-execution. This enhanced matching allows for a better distinction between self and other, which in turn, mediates the inhibition of motor contagion. PMID:27150073
In Bonobos Yawn Contagion Is Higher among Kin and Friends
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
How the contagion at links influences epidemic spreading
NASA Astrophysics Data System (ADS)
Ruan, Zhongyuan; Tang, Ming; Liu, Zonghua
2013-04-01
The reaction-diffusion (RD) model of epidemic spreading generally assume that contagion occurs only at the nodes of network, i.e., the links are used only for migration/diffusion of agents. However, in reality, we observe that contagion occurs also among the travelers staying in the same car, train or plane etc., which consist of the links of network. To reflect the contagious effect of links, we here present a traveling-contagion model where contagion occurs not only at nodes but also at links. Considering that the population density in transportation is generally much larger than that in districts, we introduce different infection rates for the nodes and links, respectively, whose two extreme cases correspond to the type-I and type-II reactions in the RD model [V. Colizza, R. Pastor-Satorras, A. Vespignani, Nat. Phys. 3, 276 (2007)]. Through studying three typical diffusion processes, we reveal both numerically and theoretically that the contagion at links can accelerate significantly the epidemic spreading. This finding is helpful in designing the controlling strategies of epidemic spreading.
Social contagion of risk perceptions in environmental management networks.
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. PMID:23231537
Stress, affiliation, and emotional contagion.
Gump, B B; Kulik, J A
1997-02-01
Female participants were exposed to high or low threat in the presence of another person believed to be facing either the same or a different situation. In Study 1, each dyad consisted of 2 actual participants, whereas in Study 2, each dyad consisted of 1 participant and 1 confederate, trained to convey either a calm or a nervous reaction to the situation. Affiliation patterns in both studies, defined in terms of the amount of time spent looking at the affiliate, were consistent with S. Schachter's (1959) "emotional similarity hypothesis"; threat increased affiliation and did so particularly with affiliates believed to be facing the same situation. The authors also found evidence of behavioral mimicry, in terms of facial expressions, and emotional contagion, in terms of self-reported anxiety. The behavioral mimicry and emotional contagion results are considered from both primitive emotional contagion and social comparison theory perspectives. PMID:9107002
Complex contagion process in spreading of online innovation.
Karsai, Márton; Iñiguez, Gerardo; Kaski, Kimmo; Kertész, János
2014-12-01
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
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…
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…
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.
Mass Media and the Contagion of Fear: The Case of Ebola in America
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
Complex Contagion of Campaign Donations.
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 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
Complex Contagion of Campaign Donations
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
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. PMID:26636878
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.
The impact of social contagion on non-suicidal self-injury: a review of the literature.
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. PMID:23387399
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.
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. PMID:18034325
Controlling Contagion Processes in Time Varying Networks
NASA Astrophysics Data System (ADS)
Liu, Suyu; Perra, Nicola; Karsai, Marton; Vespignani, Alessandro
2013-03-01
The vast majority of strategies aimed at controlling contagion and spreading processes on networks consider the connectivity pattern of the system as quenched. In this paper, we consider the class of activity driven networks to analytically evaluate how different control strategies perform in time-varying networks. We consider the limit in which the evolution of the structure of the network and the spreading process are simultaneous yet independent. We analyze three control strategies based on node's activity patterns to decide the removal/immunization of nodes. We find that targeted strategies aimed at the removal of active nodes outperform by orders of magnitude the widely used random strategies. In time-varying networks however any finite time observation of the network dynamics provides only incomplete information on the nodes' activity and does not allow the precise ranking of the most active nodes as needed to implement targeted strategies. Here we develop a control strategy that focuses on targeting the egocentric time-aggregated network of a small control group of nodes.The presented strategy allows the control of spreading processes by removing a fraction of nodes much smaller than the random strategy while at the same time limiting the observation time on the system.
Contagion on complex networks with persuasion.
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
Contagion on complex networks with persuasion
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
Inhibiting diffusion of complex contagions in social networks: theoretical and experimental results
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
The Social Contagion of Generosity
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
Motor contagion from gaze: the case of autism.
Becchio, Cristina; Pierno, Andrea; Mari, Morena; Lusher, Dean; Castiello, Umberto
2007-09-01
It has been proposed that motor contagion supplies the first step in mentalizing. Here, by using kinematic methods, we show that in contrast to normally developing children, children with autism seem to be immune to motor contagious processes. In the main experiment, involving twelve high-functioning autistic children (six males and six females, 10-13 years old, mean 11.1 years) and 12 normally developing controls (age and gender matched), two participants, a model and an observer, were seated facing each other at a table. The model was a normally developing child but the observer was either a normally developing or autistic child. The model was requested to grasp a stimulus or simply to gaze towards the target which could be presented alone or flanked by a distractor object. After watching the model, the observer was asked to grasp the object (always in the absence of the distractor). Despite the distractor being removed, the kinematics of normally developing children was affected by having observed an action performed in the presence of a distractor, thus revealing a transfer of interference from the model's action. Consistent with prior evidence, this transfer of interference effect was also present when the model simply looked at the target in the presence of the distractor object. In contrast, autistic children did not show any interference effect either from action or from gaze observation. A control experiment explored the importance of the information coming from the model's gaze pattern in eliciting the effects of motor contagion in normally developing children. In this case, the model was asked to fix their eyes on the target despite the presence of the distractor. Results highlight the importance of gaze direction in motor contagion, demonstrating that in normal children blocking the gaze prevented the transfer of interference. Altogether, these findings suggest that eye gaze plays a central role in eliciting motor contagion. We discuss these results in
NASA Astrophysics Data System (ADS)
Zhang, Yi-Qing; Li, Xiang
2014-10-01
Transmission of infectious diseases among populations can be modelled as contagion processes on contact networks. These contact networks are highly evolved in time and are represented by time-varying networks. The agents in contagion processes may have finite infectivity independently of their connectivity. Here we present an analytical framework of the susceptible-infectious-susceptible contagion process on time-varying networks, namely activity-driven networks with identical infectivity. We derive the critical epidemic thresholds and immunization thresholds as a function of infectivity, and prove that targeted immunizations are more efficient than random immunizations independently of the infectivity. We validate our conclusions in a large-scale human indoor interaction data set. Finally, we assess the effects of finite size.
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…
Suicide Contagion: A Systematic Review of Definitions and Research Utility
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
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.
Mishra, Arul; Mishra, Himanshu; Nayakankuppam, Dhananjay
2009-07-01
We used contagion theory as a framework for studying the influence of spread of qualities in a group. We found that people's preferences change depending on how objects are arranged in a group. They prefer to choose from a closely arranged group if one unidentified object in that group has a positive quality, but prefer to choose from a group in which objects are farther apart if one unidentified object in that group has a negative quality. We call this pattern of preference the group-contagion effect. We also found that the magnitude of the effect increases if the number of objects possessing the positive or negative quality increases. PMID:19493323
Dynamic Triggering Stress Modeling
NASA Astrophysics Data System (ADS)
Gonzalez-Huizar, H.; Velasco, A. A.
2008-12-01
It has been well established that static (permanent) stress changes can trigger nearby earthquakes, within a few fault lengths from the causative event, whereas triggering by dynamic (transient) stresses carried by seismic waves both nearby and at remote distances has not been as well documented nor understood. An analysis of the change in the local stress caused by the passing of surfaces waves is important for the understanding of this phenomenon. In this study, we modeled the change in the stress that the passing of Rayleigh and Loves waves causes on a fault plane of arbitrary orientation, and applied a Coulomb failure criteria to calculate the potential of these stress changes to trigger reverse, normal or strike-slip failure. We preliminarily test these model results with data from dynamically triggering earthquakes in the Australian Bowen Basin. In the Bowen region, the modeling predicts a maximum triggering potential for Rayleigh waves arriving perpendicularly to the strike of the reverse faults present in the region. The modeled potentials agree with our observations, and give us an understanding of the dynamic stress orientation needed to trigger different type of earthquakes.
NASA Astrophysics Data System (ADS)
Charpentier, Arthur; Durand, Marilou
2015-07-01
In this paper, we investigate questions arising in Parsons and Geist (Bull Seismol Soc Am 102:1-11, 2012). Pseudo causal models connecting magnitudes and waiting times are considered, through generalized regression. We do use conditional model (magnitude given previous waiting time, and conversely) as an extension to joint distribution model described in Nikoloulopoulos and Karlis (Environmetrics 19: 251-269, 2008). On the one hand, we fit a Pareto distribution for earthquake magnitudes, where the tail index is a function of waiting time following previous earthquake; on the other hand, waiting times are modeled using a Gamma or a Weibull distribution, where parameters are functions of the magnitude of the previous earthquake. We use those two models, alternatively, to generate the dynamics of earthquake occurrence, and to estimate the probability of occurrence of several earthquakes within a year or a decade.
Mesoscale ocean dynamics modeling
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.
Model for macroevolutionary dynamics
Maruvka, Yosef E.; Shnerb, Nadav M.; Kessler, David A.; Ricklefs, Robert E.
2013-01-01
The highly skewed distribution of species among genera, although challenging to macroevolutionists, provides an opportunity to understand the dynamics of diversification, including species formation, extinction, and morphological evolution. Early models were based on either the work by Yule [Yule GU (1925) Philos Trans R Soc Lond B Biol Sci 213:21–87], which neglects extinction, or a simple birth–death (speciation–extinction) process. Here, we extend the more recent development of a generic, neutral speciation–extinction (of species)–origination (of genera; SEO) model for macroevolutionary dynamics of taxon diversification. Simulations show that deviations from the homogeneity assumptions in the model can be detected in species-per-genus distributions. The SEO model fits observed species-per-genus distributions well for class-to-kingdom–sized taxonomic groups. The model’s predictions for the appearance times (the time of the first existing species) of the taxonomic groups also approximately match estimates based on molecular inference and fossil records. Unlike estimates based on analyses of phylogenetic reconstruction, fitted extinction rates for large clades are close to speciation rates, consistent with high rates of species turnover and the relatively slow change in diversity observed in the fossil record. Finally, the SEO model generally supports the consistency of generic boundaries based on morphological differences between species and provides a comparator for rates of lineage splitting and morphological evolution. PMID:23781101
Verbal social primes alter motor contagion during action observation.
Sparks, S; Douglas, T; Kritikos, A
2016-06-01
We investigated whether prosocial and nonsocial word primes prior to action observation modify subsequent initiation and execution of the observer's own reach-to-grasp actions. Participants observed a model performing exaggeratedly curved (vertical deviation) or natural straight reaches to a vertical dowel and always performed a straight reach to a dowel themselves. Observing curved movements slowed initiation times and increased the vertical deviation of the participants' movements. Observing curved movements enhanced vertical deviation only in the prosocial word primes condition. We suggest that social context priming can modulate initiation of movement as well as the extent of motor contagion (in this case, the extent of vertical deviation) between model and observer. PMID:26879285
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.
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.
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.
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.
Contact-based social contagion in multiplex networks
NASA Astrophysics Data System (ADS)
Cozzo, Emanuele; Baños, Raquel A.; Meloni, Sandro; Moreno, Yamir
2013-11-01
We develop a theoretical framework for the study of epidemiclike social contagion in large scale social systems. We consider the most general setting in which different communication platforms or categories form multiplex networks. Specifically, we propose a contact-based information spreading model, and show that the critical point of the multiplex system associated with the active phase is determined by the layer whose contact probability matrix has the largest eigenvalue. The framework is applied to a number of different situations, including a real multiplex system. Finally, we also show that when the system through which information is disseminating is inherently multiplex, working with the graph that results from the aggregation of the different layers is inaccurate.
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
Peer Contagion in Child and Adolescent Social and Emotional Development
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
Peer contagion in child and adolescent social and emotional development.
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. PMID:19575606
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.
Homophily and Contagion Are Generically Confounded in Observational Social Network Studies
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
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
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
Social contagion of mental health: evidence from college roommates.
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. PMID:23055446
Social contagion of mental health: Evidence from college roommates
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
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.
Thermal-dynamic modeling study
NASA Technical Reports Server (NTRS)
Ojalvo, I. U.
1973-01-01
Study provides basic information for designing models and conducting thermal-dynamic structural tests. Factors considered are development and interpretation of thermal-dynamic structural scaling laws; identification of major problem areas; and presentation of model fabrication, instrumentation, and test procedures.
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.
Dynamic modeling of power systems
Reed, M.; White, J.
1995-12-01
Morgantown Energy Technology Center`s (METC) Process and Project Engineering (P&PE) personnel continue to refine and modify dynamic modeling or simulations for advanced power systems. P&PE, supported by Gilbert/Commonwealth, Inc. (G/C), has adapted PC/TRAX commercial dynamic software to include equipment found in advanced power systems. PC/TRAX`s software contains the equations that describe the operation of standard power plant equipment such as gas turbines, feedwater pumps, and steam turbines. The METC team has incorporated customized dynamic models using Advanced Continuous Simulation Language (ACSL) code for pressurized circulating fluidized-bed combustors, carbonizers, and other components that are found in Advanced Pressurized Fluidized-Bed Combustion (APFBC) systems. A dynamic model of a commercial-size APFBC power plant was constructed in order to determine representative operating characteristics of the plant and to gain some insight into the best type of control system design. The dynamic model contains both process and control model components. This presentation covers development of a model used to describe the commercial APFBC power plant. Results of exercising the model to simulate plant performance are described and illustrated. Information gained during the APFBC study was applied to a dynamic model of a 1-1/2 generation PFBC system. Some initial results from this study are also presented.
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.
Motor contagion: the contribution of trajectory and end-points.
Roberts, James W; Hayes, Spencer J; Uji, Makoto; Bennett, Simon J
2015-07-01
Increased involuntary arm movement deviation when observing an incongruent human arm movement has been interpreted as a strong indicator of motor contagion. Here, we examined the contribution of trajectory and end-point information on motor contagion by altering congruence between the stimulus and arm movement. Participants performed cyclical horizontal arm movements whilst simultaneously observing a stimulus representing human arm movement. The stimuli comprised congruent horizontal movements or vertical movements featuring incongruent trajectory and end-points. A novel, third, stimulus comprised curvilinear movements featuring congruent end-points, but an incongruent trajectory. In Experiment 1, our dependent variables indicated increased motor contagion when observing the vertical compared to horizontal movement stimulus. There was even greater motor contagion in the curvilinear stimulus condition indicating an additive effect of an incongruent trajectory comprising congruent end-points. In Experiment 2, this additive effect was also present when facing perpendicular to the display, and thus with end-points represented as a product of the movement rather than an external spatial reference. Together, these findings support the theory of event coding (Hommel et al., Behav Brain Sci 24:849-878, 2001), and the prediction that increased motor contagion takes place when observed and executed actions share common features (i.e., movement end-points). PMID:24947759
NASA Astrophysics Data System (ADS)
Adams, Neil S.; Bollenbacher, Gary
1992-12-01
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.
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.
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.
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.
Model describes subsea control dynamics
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.
Dynamical models of happiness.
Sprott, J C
2005-01-01
A sequence of models for the time evolution of one's happiness in response to external events is described. These models with added nonlinearities can produce stable oscillations and chaos even without external events. Potential implications for psychotherapy and a personal approach to life are discussed. PMID:15629066
Fear of contagion and AIDS: nurses' perception of risk.
Gallop, R M; Lancee, W J; Taerk, G; Coates, R A; Fanning, M
1992-01-01
Nurses' fear of contagion when caring for persons with AIDS remains high despite increased levels of knowledge. This paper examines the multiple factors that contribute to nurses' perception of risk within the workplace. The authors suggests that constructs from theories such as decision making, psychoanalysis and cognitive psychology can provide insight into the assessment of risk. Findings from a recent survey of nurses are used to illustrate the complex nature of fear of contagion. Understanding this complexity may be an essential first step in order to provide opportunities for resolution of fears and modification of behaviors. PMID:1562626
Model of THz Magnetization Dynamics
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
Stochastic models of neuronal dynamics
Harrison, L.M; David, O; Friston, K.J
2005-01-01
Cortical activity is the product of interactions among neuronal populations. Macroscopic electrophysiological phenomena are generated by these interactions. In principle, the mechanisms of these interactions afford constraints on biologically plausible models of electrophysiological responses. In other words, the macroscopic features of cortical activity can be modelled in terms of the microscopic behaviour of neurons. An evoked response potential (ERP) is the mean electrical potential measured from an electrode on the scalp, in response to some event. The purpose of this paper is to outline a population density approach to modelling ERPs. We propose a biologically plausible model of neuronal activity that enables the estimation of physiologically meaningful parameters from electrophysiological data. The model encompasses four basic characteristics of neuronal activity and organization: (i) neurons are dynamic units, (ii) driven by stochastic forces, (iii) organized into populations with similar biophysical properties and response characteristics and (iv) multiple populations interact to form functional networks. This leads to a formulation of population dynamics in terms of the Fokker–Planck equation. The solution of this equation is the temporal evolution of a probability density over state-space, representing the distribution of an ensemble of trajectories. Each trajectory corresponds to the changing state of a neuron. Measurements can be modelled by taking expectations over this density, e.g. mean membrane potential, firing rate or energy consumption per neuron. The key motivation behind our approach is that ERPs represent an average response over many neurons. This means it is sufficient to model the probability density over neurons, because this implicitly models their average state. Although the dynamics of each neuron can be highly stochastic, the dynamics of the density is not. This means we can use Bayesian inference and estimation tools that have
Tree Modeling and Dynamics Simulation
NASA Astrophysics Data System (ADS)
Tian-shuang, Fu; Yi-bing, Li; Dong-xu, Shen
This paper introduces the theory about tree modeling and dynamic movements simulation in computer graphics. By comparing many methods we choose Geometry-based rendering as our method. The tree is decomposed into branches and leaves, under the rotation and quaternion methods we realize the tree animation and avoid the Gimbals Lock in Euler rotation. We take Orge 3D as render engine, which has good graphics programming ability. By the end we realize the tree modeling and dynamic movements simulation, achieve realistic visual quality with little computation cost.
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.
Modeling tumor evolutionary dynamics
Stransky, Beatriz; de Souza, Sandro J.
2013-01-01
Tumorigenesis can be seen as an evolutionary process, in which the transformation of a normal cell into a tumor cell involves a number of limiting genetic and epigenetic events, occurring in a series of discrete stages. However, not all mutations in a cell are directly involved in cancer development and it is likely that most of them (passenger mutations) do not contribute in any way to tumorigenesis. Moreover, the process of tumor evolution is punctuated by selection of advantageous (driver) mutations and clonal expansions. Regarding these driver mutations, it is uncertain how many limiting events are required and/or sufficient to promote a tumorigenic process or what are the values associated with the adaptive advantage of different driver mutations. In spite of the availability of high-quality cancer data, several assumptions about the mechanistic process of cancer initiation and development remain largely untested, both mathematically and statistically. Here we review the development of recent mathematical/computational models and discuss their impact in the field of tumor biology. PMID:23420281
Children's knowledge of contagion and contamination as causes of illness.
Siegal, M
1988-10-01
Children's knowledge of contagion and contamination as causes of illness was examined in 3 experiments. In Experiment 1, preschoolers and children in grades 1 and 3 were shown videotaped segments of puppets with colds and toothaches who explained their ailments in terms of contagion and immanent justice. The children were instructed to evaluate and correct the puppets' explanations and, in addition, to indicate the possible effects on health of drinking milk that had come into contact with objects such as a cockroach, used comb, and spoon. Even preschoolers displayed some knowledge of contagion and contamination. However, compared to the third graders, younger children were less likely to reject proximity to a sick person and naughty behavior as causes of toothaches. They were also more likely to indicate that to drink milk that had come into contact with a spoon was unhealthy. In Experiment 2, preschoolers rejected the proposition that an ailment caused by accident (i.e., a scraped knee) is contagious and, in Experiment 3, they generally accepted that contamination through contact with a dirty spoon can be prevented by washing. Altogether, preschoolers have a more substantial knowledge of contagion and contamination than has been estimated previously. The results are discussed in terms of children's ability to understand causal relations. PMID:3168645
Contagion Theory and the Communication of Public Speaking State Anxiety.
ERIC Educational Resources Information Center
Behnke, Ralph R.; And Others
1994-01-01
Reports on research into the communication of speech state anxiety between adjacent speakers in the speaking order in a public speaking setting. Finds, based on classical response contagion theory, that public speaking state anxiety in an educational setting is contagious. Discusses possible consequences, and advances suggestions for future…
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.…
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…
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…
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…
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…
Observability in dynamic evolutionary models.
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. PMID:15013222
High-performance biocomputing for simulating the spread of contagion over large contact networks
2012-01-01
Background Many important biological problems can be modeled as contagion diffusion processes over interaction networks. This article shows how the EpiSimdemics interaction-based simulation system can be applied to the general contagion diffusion problem. Two specific problems, computational epidemiology and human immune system modeling, are given as examples. We then show how the graphics processing unit (GPU) within each compute node of a cluster can effectively be used to speed-up the execution of these types of problems. Results We show that a single GPU can accelerate the EpiSimdemics computation kernel by a factor of 6 and the entire application by a factor of 3.3, compared to the execution time on a single core. When 8 CPU cores and 2 GPU devices are utilized, the speed-up of the computational kernel increases to 9.5. When combined with effective techniques for inter-node communication, excellent scalability can be achieved without significant loss of accuracy in the results. Conclusions We show that interaction-based simulation systems can be used to model disparate and highly relevant problems in biology. We also show that offloading some of the work to GPUs in distributed interaction-based simulations can be an effective way to achieve increased intra-node efficiency. PMID:22537298
Statistical fluctuations in pedestrian evacuation times and the effect of social contagion.
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. PMID:27627323
Conceptual dynamical models for turbulence.
Majda, Andrew J; Lee, Yoonsang
2014-05-01
Understanding the complexity of anisotropic turbulent processes in engineering and environmental fluid flows is a formidable challenge with practical significance because energy often flows intermittently from the smaller scales to impact the largest scales in these flows. Conceptual dynamical models for anisotropic turbulence are introduced and developed here which, despite their simplicity, capture key features of vastly more complicated turbulent systems. These conceptual models involve a large-scale mean flow and turbulent fluctuations on a variety of spatial scales with energy-conserving wave-mean-flow interactions as well as stochastic forcing of the fluctuations. Numerical experiments with a six-dimensional conceptual dynamical model confirm that these models capture key statistical features of vastly more complex anisotropic turbulent systems in a qualitative fashion. These features include chaotic statistical behavior of the mean flow with a sub-Gaussian probability distribution function (pdf) for its fluctuations whereas the turbulent fluctuations have decreasing energy and correlation times at smaller scales, with nearly Gaussian pdfs for the large-scale fluctuations and fat-tailed non-Gaussian pdfs for the smaller-scale fluctuations. This last feature is a manifestation of intermittency of the small-scale fluctuations where turbulent modes with small variance have relatively frequent extreme events which directly impact the mean flow. The dynamical models introduced here potentially provide a useful test bed for algorithms for prediction, uncertainty quantification, and data assimilation for anisotropic turbulent systems. PMID:24753605
Conceptual dynamical models for turbulence
Majda, Andrew J.; Lee, Yoonsang
2014-01-01
Understanding the complexity of anisotropic turbulent processes in engineering and environmental fluid flows is a formidable challenge with practical significance because energy often flows intermittently from the smaller scales to impact the largest scales in these flows. Conceptual dynamical models for anisotropic turbulence are introduced and developed here which, despite their simplicity, capture key features of vastly more complicated turbulent systems. These conceptual models involve a large-scale mean flow and turbulent fluctuations on a variety of spatial scales with energy-conserving wave–mean-flow interactions as well as stochastic forcing of the fluctuations. Numerical experiments with a six-dimensional conceptual dynamical model confirm that these models capture key statistical features of vastly more complex anisotropic turbulent systems in a qualitative fashion. These features include chaotic statistical behavior of the mean flow with a sub-Gaussian probability distribution function (pdf) for its fluctuations whereas the turbulent fluctuations have decreasing energy and correlation times at smaller scales, with nearly Gaussian pdfs for the large-scale fluctuations and fat-tailed non-Gaussian pdfs for the smaller-scale fluctuations. This last feature is a manifestation of intermittency of the small-scale fluctuations where turbulent modes with small variance have relatively frequent extreme events which directly impact the mean flow. The dynamical models introduced here potentially provide a useful test bed for algorithms for prediction, uncertainty quantification, and data assimilation for anisotropic turbulent systems. PMID:24753605
Modelling the mechanoreceptor's dynamic behaviour.
Song, Zhuoyi; Banks, Robert W; Bewick, Guy S
2015-08-01
All sensory receptors adapt, i.e. they constantly adjust their sensitivity to external stimuli to match the current demands of the natural environment. Electrophysiological responses of sensory receptors from widely different modalities seem to exhibit common features related to adaptation, and these features can be used to examine the underlying sensory transduction mechanisms. Among the principal senses, mechanosensation remains the least understood at the cellular level. To gain greater insights into mechanosensory signalling, we investigated if mechanosensation displayed adaptive dynamics that could be explained by similar biophysical mechanisms in other sensory modalities. To do this, we adapted a fly photoreceptor model to describe the primary transduction process for a stretch-sensitive mechanoreceptor, taking into account the viscoelastic properties of the accessory muscle fibres and the biophysical properties of known mechanosensitive channels (MSCs). The model's output is in remarkable agreement with the electrical properties of a primary ending in an isolated decapsulated spindle; ramp-and-hold stretch evokes a characteristic pattern of potential change, consisting of a large dynamic depolarization during the ramp phase and a smaller static depolarization during the hold phase. The initial dynamic component is likely to be caused by a combination of the mechanical properties of the muscle fibres and a refractory state in the MSCs. Consistent with the literature, the current model predicts that the dynamic component is due to a rapid stress increase during the ramp. More novel predictions from the model are the mechanisms to explain the initial peak in the dynamic component. At the onset of the ramp, all MSCs are sensitive to external stimuli, but as they become refractory (inactivated), fewer MSCs are able to respond to the continuous stretch, causing a sharp decrease after the peak response. The same mechanism could contribute a faster component in the
Modelling MIZ dynamics in a global model
NASA Astrophysics Data System (ADS)
Rynders, Stefanie; Aksenov, Yevgeny; Feltham, Daniel; Nurser, George; Naveira Garabato, Alberto
2016-04-01
Exposure of large, previously ice-covered areas of the Arctic Ocean to the wind and surface ocean waves results in the Arctic pack ice cover becoming more fragmented and mobile, with large regions of ice cover evolving into the Marginal Ice Zone (MIZ). The need for better climate predictions, along with growing economic activity in the Polar Oceans, necessitates climate and forecasting models that can simulate fragmented sea ice with a greater fidelity. Current models are not fully fit for the purpose, since they neither model surface ocean waves in the MIZ, nor account for the effect of floe fragmentation on drag, nor include sea ice rheology that represents both the now thinner pack ice and MIZ ice dynamics. All these processes affect the momentum transfer to the ocean. We present initial results from a global ocean model NEMO (Nucleus for European Modelling of the Ocean) coupled to the Los Alamos sea ice model CICE. The model setup implements a novel rheological formulation for sea ice dynamics, accounting for ice floe collisions, thus offering a seamless framework for pack ice and MIZ simulations. The effect of surface waves on ice motion is included through wave pressure and the turbulent kinetic energy of ice floes. In the multidecadal model integrations we examine MIZ and basin scale sea ice and oceanic responses to the changes in ice dynamics. We analyse model sensitivities and attribute them to key sea ice and ocean dynamical mechanisms. The results suggest that the effect of the new ice rheology is confined to the MIZ. However with the current increase in summer MIZ area, which is projected to continue and may become the dominant type of sea ice in the Arctic, we argue that the effects of the combined sea ice rheology will be noticeable in large areas of the Arctic Ocean, affecting sea ice and ocean. With this study we assert that to make more accurate sea ice predictions in the changing Arctic, models need to include MIZ dynamics and physics.
On whole Abelian model dynamics
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.
Evolution models with extremal dynamics.
Kärenlampi, Petri P
2016-08-01
The random-neighbor version of the Bak-Sneppen biological evolution model is reproduced, along with an analogous model of random replicators, the latter eventually experiencing topology changes. In the absence of topology changes, both types of models self-organize to a critical state. Species extinctions in the replicator system degenerates the self-organization to a random walk, as does vanishing of species interaction for the BS-model. A replicator model with speciation is introduced, experiencing dramatic topology changes. It produces a variety of features, but self-organizes to a possibly critical state only in a few special cases. Speciation-extinction dynamics interfering with self-organization, biological macroevolution probably is not a self-organized critical system. PMID:27626090
Dynamical model of brushite precipitation
NASA Astrophysics Data System (ADS)
Oliveira, Cristina; Georgieva, Petia; Rocha, Fernando; Ferreira, António; Feyo de Azevedo, Sebastião
2007-07-01
The objectives of this work are twofold. From academic point of view the aim is to build a dynamical macro model to fit the material balance and explain the main kinetic mechanisms that govern the transformation of the hydroxyapatite (HAP) into brushite and the growth of brushite, based on laboratory experiments and collected database. From practical point of view, the aim is to design a reliable process simulator that can be easily imbedded in industrial software for model driven monitoring, optimization and control purposes. Based upon a databank of laboratory measurements of the calcium concentration in solution (on-line) and the particle size distribution (off-line) a reliable dynamical model of the dual nature of brushite particle formation for a range of initial concentrations of the reagents was derived as a system of ordinary differential equations of time. The performance of the model is tested with respect to the predicted evolution of mass of calcium in solution and the average (in mass) particle size along time. Results obtained demonstrate a good agreement between the model time trajectories and the available experimental data for a number of different initial concentrations of reagents.
The Dynamics of Protest Recruitment through an Online Network
NASA Astrophysics Data System (ADS)
González-Bailón, Sandra; Borge-Holthoefer, Javier; Rivero, Alejandro; Moreno, Yamir
2011-12-01
The recent wave of mobilizations in the Arab world and across Western countries has generated much discussion on how digital media is connected to the diffusion of protests. We examine that connection using data from the surge of mobilizations that took place in Spain in May 2011. We study recruitment patterns in the Twitter network and find evidence of social influence and complex contagion. We identify the network position of early participants (i.e. the leaders of the recruitment process) and of the users who acted as seeds of message cascades (i.e. the spreaders of information). We find that early participants cannot be characterized by a typical topological position but spreaders tend to be more central in the network. These findings shed light on the connection between online networks, social contagion, and collective dynamics, and offer an empirical test to the recruitment mechanisms theorized in formal models of collective action.
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.
Rhodes, Michael Grant
2013-11-01
The instrumental use of social networks has become a central tenet of international health policy and advocacy since the Millennium project. In asking, 'How to facilitate social contagion?', Karl Blanchet of the London School of Hygiene and Tropical Medicine therefore reflects not only on the recent success, but also hints to growing challenges; the tactics of partnerships, alliances and platforms no longer seem to be delivering at the same rate and maybe reversing. A better understanding of how social networks work may therefore be needed to strengthen a tactical instrument that has been used to remarkable recent effect. But in focusing on the unbounded rhetoric and narrative options of Global Health, the danger will surely be on missing the fundamental factors constraining network growth. Future growth will depend on understanding these constraints, and Global Health may do well to think of social networks not only instrumentally, but also analytically in terms of the strategic contexts and environments in which such instruments are deployed. PMID:24596889
Modeling Wildfire Incident Complexity Dynamics
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
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.
Rapid mimicry and emotional contagion in domestic dogs.
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. PMID:27019737
Differences by degree: fatness, contagion and pre-emption.
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. PMID:23564448
[The contagion of adolescent suicide: cultural, ethical and psychosocial aspects].
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. PMID:22891588
Rapid mimicry and emotional contagion in domestic dogs
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
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.
COLD-SAT Dynamic Model Computer Code
NASA Technical Reports Server (NTRS)
Bollenbacher, G.; Adams, N. S.
1995-01-01
COLD-SAT Dynamic Model (CSDM) computer code implements six-degree-of-freedom, rigid-body mathematical model for simulation of spacecraft in orbit around Earth. Investigates flow dynamics and thermodynamics of subcritical cryogenic fluids in microgravity. Consists of three parts: translation model, rotation model, and slosh model. Written in FORTRAN 77.
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
Dynamics of the standard model
Donoghue, J.F.; Golowich, E.; Holstein, B.R.
1992-01-01
Given the remarkable successes of the standard model, it is appropriate that books in the field no longer dwell on the development of our current understanding of high-energy physics but rather present the world as we now know it. Dynamics of the Standard Model by Donoghue, Golowich, and Holstein takes just this approach. Instead of showing the confusion of the 60s and 70s, the authors present the enlightenment of the 80s. They start by describing the basic features and structure of the standard model and then concentrate on the techniques whereby the model can be applied to the physical world, connecting the theory to the experimental results that are the source of its success. Because they do not dwell on ancient (pre-1980) history, the authors of this book are able to go into much more depth in describing how the model can be tied to experiment, and much of the information presented has been accessible previously only in journal articles in a highly technical form. Though all of the authors are card-carrying theorists they go out of their way to stress applications and phenomenology and to show the reader how real-life calculations of use to experimentalists are done and can be applied to physical situations: what assumptions are made in doing them and how well they work. This is of great value both to the experimentalist seeking a deeper understanding of how the standard model can be connected to data and to the theorist wanting to see how detailed the phenomenological predictions of the standard model are and how well the model works. Furthermore, the authors constantly go beyond the lowest-order predictions of the standard model to discuss the corrections to it, as well as higher-order processes, some of which are now experimentally accessible and others of which will take well into the decade to uncover.
Fu, Rui; Gutfraind, Alexander; Brandeau, Margaret L
2016-03-01
Injection drug users (IDUs) are at high risk of acquiring and spreading various blood-borne infections including human immunodeficiency virus (HIV), hepatitis C virus (HCV), hepatitis B virus (HBV) and a number of sexually transmitted infections. These infections can spread among IDUs via risky sexual and needle-sharing contacts. To accurately model the spread of such contagions among IDUs, we build a bi-layer network that captures both types of risky contacts. We present methodology for inferring important model parameters, such as those governing network structure and dynamics, from readily available data sources (e.g., epidemiological surveys). Such a model can be used to evaluate the efficacy of various programs that aim to combat drug addiction and contain blood-borne diseases among IDUs. The model is especially useful for evaluating interventions that exploit the structure of the contact network. To illustrate, we instantiate a network model with data collected by a needle and syringe program in Chicago. We model sexual and needle-sharing contacts and the consequent spread of HIV and HCV. We use the model to evaluate the potential effects of a peer education (PE) program under different targeting strategies. We show that a targeted PE program would avert significantly more HIV and HCV infections than an untargeted program, highlighting the importance of reaching individuals who are centrally located in contact networks when instituting prevention programs. PMID:26775738
Dynamical modeling of tidal streams
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.
Dynamical Modeling of Tidal Streams
NASA Astrophysics Data System (ADS)
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.
Dynamically Evolving Models of Clusters
NASA Astrophysics Data System (ADS)
Bode, Paul W.; Berrington, Robert C.; Cohn, Haldan N.; Lugger, Phyllis M.
1993-12-01
An N-body method, with up to N=10(5) particles, is used to simulate the dynamical evolution of clusters of galaxies. Each galaxy is represented as an extended structure containing many particles, and the gravitational potential arises from the particles alone. The clusters initially contain 50 or 100 galaxies with masses distributed according to a Schechter function. Mass is apportioned between the galaxies and a smoothly distributed common group halo, or intra-cluster background. The fraction of the total cluster mass initially in this background is varied from 50% to 90%. The models begin in a virialized state. We will be presenting a videotape which contains animations of a number of these models. The animations show important physical processes, such as stripping, merging, and dynamical friction, as they take place, thus allowing one to observe the interplay of these processes in the global evolution of the system. When the galaxies have substantial dark halos (background mass fraction <=75%) a large, centrally located merger remnant is created. The galaxy number density profile around this dominant member becomes cusped, approaching an isothermal distribution. At the same time, the number of multiple nuclei increases. Comparing the 50-galaxy models to MKW/AWM clusters, the values of Delta M12 and the peculiar velocities of the first-ranked galaxies are best fit by a mix of model ages in the range 8--11 Gyr. The growth in luminosity of the first-ranked galaxy during this amount of time is consistent only with weak cannibalism.
Modeling sandhill crane population dynamics
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.
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,…
ERIC Educational Resources Information Center
Magen, Eran; Konasewich, Paul A.
2011-01-01
People in distress often turn to friends for emotional support. Ironically, although receiving emotional support contributes to emotional and physical health, providing emotional support may be distressing as a result of emotional contagion. Women have been found to be more susceptible than men to emotional contagion in certain contexts, but no…
ERIC Educational Resources Information Center
Prinstein, Mitchell J.
2007-01-01
This longitudinal study examined peer contagion of depressive symptoms over an 18-month interval within a sample of 100 11th-grade adolescents. Three types of peer contagion moderators were examined, including characteristics of adolescents (social anxiety, global self-worth), friends (level of friends' peer-perceived popularity), and the…
Terminal Model Of Newtonian Dynamics
NASA Technical Reports Server (NTRS)
Zak, Michail
1994-01-01
Paper presents study of theory of Newtonian dynamics of terminal attractors and repellers, focusing on issues of reversibility vs. irreversibility and deterministic evolution vs. probabilistic or chaotic evolution of dynamic systems. Theory developed called "terminal dynamics" emphasizes difference between it and classical Newtonian dynamics. Also holds promise for explaining irreversibility, unpredictability, probabilistic behavior, and chaos in turbulent flows, in thermodynamic phenomena, and in other dynamic phenomena and systems.
Foulk, Trevor; Woolum, Andrew; Erez, Amir
2016-01-01
In this article we offer a new perspective to the study of negative behavioral contagion in organizations. In 3 studies, we investigate the contagion effect of rudeness and the cognitive mechanism that explains this effect. Study 1 results show that low-intensity negative behaviors like rudeness can be contagious, and that this contagion effect can occur based on single episodes, that anybody can be a carrier, and that this contagion effect has second-order consequences for future interaction partners. In Studies 2 and 3 we explore in the laboratory the cognitive mechanism that underlies the negative behavioral contagion effect observed in Study 1. Specifically, we show that rudeness activates a semantic network of related concepts in individuals' minds, and that this activation influences individual's hostile behaviors. In sum, in these 3 studies we show that just like the common cold, common negative behaviors can spread easily and have significant consequences for people in organizations. PMID:26121091
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.
Emotional Contagion is not Altered in Mice Prenatally Exposed to Poly (I:C) on Gestational Day 9
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
Emotional Contagion is not Altered in Mice Prenatally Exposed to Poly (I:C) on Gestational Day 9.
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
Dynamic Models of Robots with Elastic Hinges
NASA Astrophysics Data System (ADS)
Krakhmalev, O. N.
2016-04-01
Two dynamic models of robots with elastic hinges are considered. Dynamic models are the implementation of the method based on the Lagrange equation using the transformation matrices of elastic coordinates. Dynamic models make it possible to determine the elastic deviations from programmed motion trajectories caused by elastic deformations in hinges, which are taken into account in directions of change of the corresponding generalized coordinates. One model is the exact implementation of the Lagrange method and makes it possible to determine the total elastic deviation of the robot from the programmed motion trajectory. Another dynamic model is approximated and makes it possible to determine small elastic quasi-static deviations and elastic vibrations. The results of modeling the dynamics by two models are compared to the example of a two-link manipulator system. The considered models can be used when performing investigations of the mathematical accuracy of the robots.
Exposure to externalizing peers in early childhood: homophily and peer contagion processes.
Hanish, Laura D; Martin, Carol Lynn; Fabes, Richard A; Leonard, Stacie; Herzog, Melissa
2005-06-01
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
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
Exposure to Externalizing Peers in Early Childhood: Homophily and Peer Contagion Processes
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
Modeling population dynamics: A quantile approach.
Chavas, Jean-Paul
2015-04-01
The paper investigates the modeling of population dynamics, both conceptually and empirically. It presents a reduced form representation that provides a flexible characterization of population dynamics. It leads to the specification of a threshold quantile autoregression (TQAR) model, which captures nonlinear dynamics by allowing lag effects to vary across quantiles of the distribution as well as with previous population levels. The usefulness of the model is illustrated in an application to the dynamics of lynx population. We find statistical evidence that the quantile autoregression parameters vary across quantiles (thus rejecting the AR model as well as the TAR model) as well as with past populations (thus rejecting the quantile autoregression QAR model). The results document the nature of dynamics and cycle in the lynx population over time. They show how both the period of the cycle and the speed of population adjustment vary with population level and environmental conditions. PMID:25661501
Multidimensional Langevin Modeling of Nonoverdamped Dynamics
NASA Astrophysics Data System (ADS)
Schaudinnus, Norbert; Bastian, Björn; Hegger, Rainer; Stock, Gerhard
2015-07-01
Based on a given time series, data-driven Langevin modeling aims to construct a low-dimensional dynamical model of the underlying system. When dealing with physical data as provided by, e.g., all-atom molecular dynamics simulations, effects due to small damping may be important to correctly describe the statistics (e.g., the energy landscape) and the dynamics (e.g., transition times). To include these effects in a dynamical model, an algorithm that propagates a second-order Langevin scheme is derived, which facilitates the treatment of multidimensional data. Adopting extensive molecular dynamics simulations of a peptide helix, a five-dimensional model is constructed that successfully forecasts the complex structural dynamics of the system. Neglect of small damping effects, on the other hand, is shown to lead to significant errors and inconsistencies.
Yawn contagion in humans and bonobos: emotional affinity matters more than species
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
Yawn contagion in humans and bonobos: emotional affinity matters more than species.
Palagi, Elisabetta; 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
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.
The Challenges to Coupling Dynamic Geospatial Models
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.
Magical contagion and AIDS risk perception in a college population.
Nemeroff, C J; Brinkman, A; Woodward, C K
1994-06-01
This study examined whether common reactions to AIDS are consistent with operation of the "magical law of contagion," a traditional belief that describes the transfer of properties, whether moral or physical, harmful or beneficial, through contact. Three features of magical contagion, explored in previous work, were re-examined. These features sometimes contrast with microbial contamination as described by modern germ theory. They are: permanence of effects; dose-insensitivity; and potential for effects to act backwards (i.e., from recipient back onto source). A fourth characteristic, previously unaddressed, was also explored: "moral-germ conflation," i.e., the tendency to incompletely distinguish illness from evil. Three hundred and ninety-nine college students completed a survey assessing each feature with regard to AIDS-related scenarios. Also assessed was general AIDS knowledge. Subjects were very well-informed about AIDS, yet a significant subset showed "magical" features of thinking. Consistent with moral-germ conflation, degree of worry about getting AIDS was better predicted by guilt than by risk behaviors and knowledge that they are risky. Implications are discussed. PMID:8080709
Hydration dynamics near a model protein surface
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.
Benchmarking of Planning Models Using Recorded Dynamics
Huang, Zhenyu; Yang, Bo; Kosterev, Dmitry
2009-03-15
Power system planning extensively uses model simulation to understand the dynamic behaviors and determine the operating limits of a power system. Model quality is key to the safety and reliability of electricity delivery. Planning model benchmarking, or model validation, has been one of the central topics in power engineering studies for years. As model validation aims at obtaining reasonable models to represent dynamic behavior of power system components, it has been essential to validate models against actual measurements. The development of phasor technology provides such measurements and represents a new opportunity for model validation as phasor measurements can capture power system dynamics with high-speed, time-synchronized data. Previously, methods for rigorous comparison of model simulation and recorded dynamics have been developed and applied to quantify model quality of power plants in the Western Electricity Coordinating Council (WECC). These methods can locate model components which need improvement. Recent work continues this effort and focuses on how model parameters may be calibrated to match recorded dynamics after the problematic model components are identified. A calibration method using Extended Kalman Filter technique is being developed. This paper provides an overview of prior work on model validation and presents new development on the calibration method and initial results of model parameter calibration.
Negative rumor: contagion of a psychiatric department.
Novac, Andrei; 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
Negative Rumor: Contagion of a Psychiatric Department
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
Map-based models in neuronal dynamics
NASA Astrophysics Data System (ADS)
Ibarz, B.; Casado, J. M.; Sanjuán, M. A. F.
2011-04-01
Ever since the pioneering work of Hodgkin and Huxley, biological neuron models have consisted of ODEs representing the evolution of the transmembrane voltage and the dynamics of ionic conductances. It is only recently that discrete dynamical systems-also known as maps-have begun to receive attention as valid phenomenological neuron models. The present review tries to provide a coherent perspective of map-based biological neuron models, describing their dynamical properties; stressing the similarities and differences, both among them and in relation to continuous-time models; exploring their behavior in networks; and examining their wide-ranging possibilities of application in computational neuroscience.
[Review of dynamic global vegetation models (DGVMs)].
Che, Ming-Liang; Chen, Bao-Zhang; Wang, Ying; Guo, Xiang-Yun
2014-01-01
Dynamic global vegetation model (DGVM) is an important and efficient tool for study on the terrestrial carbon circle processes and vegetation dynamics. This paper reviewed the development history of DGVMs, introduced the basic structure of DGVMs, and the outlines of several world-widely used DGVMs, including CLM-DGVM, LPJ, IBIS and SEIB. The shortages of the description of dynamic vegetation mechanisms in the current DGVMs were proposed, including plant functional types (PFT) scheme, vegetation competition, disturbance, and phenology. Then the future research directions of DGVMs were pointed out, i. e. improving the PFT scheme, refining the vegetation dynamic mechanism, and implementing a model inter-comparison project. PMID:24765870
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
Very Large System Dynamics Models - Lessons Learned
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.
Comparing models of Red Knot population dynamics
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.
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.
FRF based joint dynamics modeling and identification
NASA Astrophysics Data System (ADS)
Mehrpouya, Majid; Graham, Eldon; Park, Simon S.
2013-08-01
Complex structures, such as machine tools, are comprised of several substructures connected to each other through joints to form the assembled structures. Joints can have significant contributions on the behavior of the overall assembly and ignoring joint effects in the design stage may result in considerable deviations from the actual dynamic behavior. The identification of joint dynamics enables us to accurately predict overall assembled dynamics by mathematically combining substructure dynamics through the equilibrium and compatibility conditions at the joint. The essence of joint identification is the determination of the difference between the measured overall dynamics and the rigidly coupled substructure dynamics. In this study, we investigate the inverse receptance coupling (IRC) method and the point-mass joint model, which considers the joint as lumped mass, damping and stiffness elements. The dynamic properties of the joint are investigated using both methods through a finite element (FE) simulation and experimental tests. `100
Modeling microbial growth and dynamics.
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. PMID:26298697
Differential equation models for sharp threshold dynamics.
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. PMID:24184349
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.
Modeling dynamical geometry with lattice gas automata
Hasslacher, B.; Meyer, D.A.
1998-06-27
Conventional lattice gas automata consist of particles moving discretely on a fixed lattice. While such models have been quite successful for a variety of fluid flow problems, there are other systems, e.g., flow in a flexible membrane or chemical self-assembly, in which the geometry is dynamical and coupled to the particle flow. Systems of this type seem to call for lattice gas models with dynamical geometry. The authors construct such a model on one dimensional (periodic) lattices and describe some simulations illustrating its nonequilibrium dynamics.
Dynamics Modelling of Biolistic Gene Guns
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.
An Experimental Study of the Contagion of Leaving Behavior in Small Gatherings
ERIC Educational Resources Information Center
Stephenson, Geoffrey M.; Fielding, Geoffrey T.
1971-01-01
The results of these experiments strongly suggest that the occurrence of behavioral contagion depended on the relative advantage an initiator's action establishes over the other members of the group. (SD)
Markov state models of biomolecular conformational dynamics
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
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
A Microcomputer Dynamical Modelling System.
ERIC Educational Resources Information Center
Ogborn, Jon; Wong, Denis
1984-01-01
Presents a system that permits students to engage directly in the process of modelling and to learn some important lessons about models and classes of models. The system described currently runs on RML 380Z and 480Z, Apple II and IIe, and BBC model B microcomputers. (JN)
Dynamic modeling of emulsion polymerization reactors
Penlidis, A.; Hamielec, A.E.; MacGregor, J.F.
1985-06-01
This paper is a survey of recent published works on the dynamic and steady state modeling of emulsion homo- and copolymerization in batch, semicontinuous , and continuous latex reactors. Contributions to our understanding of diffusion-controlled termination and propagation reactions, molecular weight, long chain branching and crosslinking development, polymer particle nucleation, and of the dynamics of continuous emulsion polymerization are critically reviewed.
Flexible aircraft dynamic modeling for dynamic analysis and control synthesis
NASA Technical Reports Server (NTRS)
Schmidt, David K.
1989-01-01
The linearization and simplification of a nonlinear, literal model for flexible aircraft is highlighted. Areas of model fidelity that are critical if the model is to be used for control system synthesis are developed and several simplification techniques that can deliver the necessary model fidelity are discussed. These techniques include both numerical and analytical approaches. An analytical approach, based on first-order sensitivity theory is shown to lead not only to excellent numerical results, but also to closed-form analytical expressions for key system dynamic properties such as the pole/zero factors of the vehicle transfer-function matrix. The analytical results are expressed in terms of vehicle mass properties, vibrational characteristics, and rigid-body and aeroelastic stability derivatives, thus leading to the underlying causes for critical dynamic characteristics.
Automated adaptive inference of phenomenological dynamical models
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
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.
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.
Dynamic metabolic models in context: biomass backtracking.
Tummler, Katja; Kühn, Clemens; Klipp, Edda
2015-08-01
Mathematical modeling has proven to be a powerful tool to understand and predict functional and regulatory properties of metabolic processes. High accuracy dynamic modeling of individual pathways is thereby opposed by simplified but genome scale constraint based approaches. A method that links these two powerful techniques would greatly enhance predictive power but is so far lacking. We present biomass backtracking, a workflow that integrates the cellular context in existing dynamic metabolic models via stoichiometrically exact drain reactions based on a genome scale metabolic model. With comprehensive examples, for different species and environmental contexts, we show the importance and scope of applications and highlight the improvement compared to common boundary formulations in existing metabolic models. Our method allows for the contextualization of dynamic metabolic models based on all available information. We anticipate this to greatly increase their accuracy and predictive power for basic research and also for drug development and industrial applications. PMID:26189715
Single timepoint models of dynamic systems.
Sachs, K; Itani, S; Fitzgerald, J; Schoeberl, B; Nolan, G P; Tomlin, C J
2013-08-01
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
Single timepoint models of dynamic systems
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
Dynamics of two nonlinear oligopoly models
NASA Astrophysics Data System (ADS)
Ibrahim, Adyda
2014-06-01
This paper considers an n firms oligopoly model with isoelastic demand function and linear cost function. This model is introduced in two different dynamical systems. In the first system, firms are assumed have naive expectation, while in the second system, firms are assumed to have bounded rationality. We study the dynamics of both dynamical systems in the special case of firms behaving identically. The main result shows that as the number of firm increases, the equilibrium in the first system becomes unstable when the number of firms is greater than four, while in the second system, there is a change in the region of stability for the equilibrium.
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.
Swarm Intelligence for Urban Dynamics Modelling
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.
Battery electrochemical nonlinear/dynamic SPICE model
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.
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.
Dynamics of the Standard Model
NASA Astrophysics Data System (ADS)
Donoghue, John F.; Golowich, Eugene; Holstein, Barry R.
2014-04-01
Preface; 1. Inputs to the Standard Model; 2. Interactions of the Standard Model; 3. Symmetries and anomalies; 4. Introduction to effective field theory; 5. Charged leptons; 6. Neutrinos; 7. Effective field theory for low energy QCD; 8. Weak interactions of Kaons; 9. Mass mixing and CP violation; 10. The Nc-1 expansion; 11. Phenomenological models; 12. Baryon properties; 13. Hadron spectroscopy; 14. Weak interactions of heavy quarks; 15. The Higgs boson; 16. The electroweak sector; Appendixes; References; Index.
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.
Dynamical model for DNA sequences
NASA Astrophysics Data System (ADS)
Allegrini, P.; Barbi, M.; Grigolini, P.; West, B. J.
1995-11-01
We address the problem of DNA sequences, developing a ``dynamical'' method based on the assumption that the statistical properties of DNA paths are determined by the joint action of two processes, one deterministic with long-range correlations, and the other random and δ-function correlated. The generator of the deterministic evolution is a nonlinear map, belonging to a class of maps recently tailored to mimic the processes of weak chaos that are responsible for the birth of anomalous diffusion. It is assumed that the deterministic process corresponds to unknown biological rules that determine the DNA path, whereas the noise mimics the influence of an infinite-dimensional environment on the biological process under study. We prove that the resulting diffusion process, if the effect of the random process is neglected, is an α-stable Lévy process with 1<α<2. We also show that, if the diffusion process is determined by the joint action of the deterministic and the random process, the correlation effects of the ``deterministic dynamics'' are cancelled on the short-range scale, but show up in the long-range one. We denote our prescription to generate statistical sequences as the copying mistake map (CMM). We carry out our analysis of several DNA sequences and their CMM realizations with a variety of techniques, and we especially focus on a method of regression to equilibrium, which we call the Onsager analysis. With these techniques we establish the statistical equivalence of the real DNA sequences with their CMM realizations. We show that long-range correlations are present in exons as well as in introns, but are difficult to detect, since the exon ``dynamics'' is shown to be determined by the entanglement of three distinct and independent CMM's.
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].
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.
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.
Dynamic and Structural Gas Turbine Engine Modeling
NASA Technical Reports Server (NTRS)
Turso, James A.
2003-01-01
Model the interactions between the structural dynamics and the performance dynamics of a gas turbine engine. Generally these two aspects are considered separate, unrelated phenomena and are studied independently. For diagnostic purposes, it is desirable to bring together as much information as possible, and that involves understanding how performance is affected by structural dynamics (if it is) and vice versa. This can involve the relationship between thrust response and the excitation of structural modes, for instance. The job will involve investigating and characterizing these dynamical relationships, generating a model that incorporates them, and suggesting and/or developing diagnostic and prognostic techniques that can be incorporated in a data fusion system. If no coupling is found, at the least a vibration model should be generated that can be used for diagnostics and prognostics related to blade loss, for instance.
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.
The Immuno-Dynamics of Conflict Intervention in Social Systems
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
Haptics-based dynamic implicit solid modeling.
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. PMID:15794139
Synaptic dynamics: linear model and adaptation algorithm.
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
Global Civil Unrest: Contagion, Self-Organization, and Prediction
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
Modeling of Intracranial Pressure Dynamics
Griffith, Richard L.; Sullivan, Humbert G.; Miller, J. Douglas
1978-01-01
Digital computer simulation is utilized to test hypotheses regarding poorly understood mechanisms of intracranial pressure change. The simulation produces graphic output similar to records from polygraph recorders used in patient monitoring and in animal experimentation. The structure of the model is discussed. The mathematic model perfected by the comparison between simulation and experiment will constitute a formulation of medical information applicable to automated clinical monitoring and treatment of intracranial hypertension.
Modeling Dynamic Regulatory Processes in Stroke.
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.
Dynamics of internal models in game players
NASA Astrophysics Data System (ADS)
Taiji, Makoto; Ikegami, Takashi
1999-10-01
A new approach for the study of social games and communications is proposed. Games are simulated between cognitive players who build the opponent’s internal model and decide their next strategy from predictions based on the model. In this paper, internal models are constructed by the recurrent neural network (RNN), and the iterated prisoner’s dilemma game is performed. The RNN allows us to express the internal model in a geometrical shape. The complicated transients of actions are observed before the stable mutually defecting equilibrium is reached. During the transients, the model shape also becomes complicated and often experiences chaotic changes. These new chaotic dynamics of internal models reflect the dynamical and high-dimensional rugged landscape of the internal model space.
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.
Dynamical modeling of laser ablation processes
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.
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.
A dynamical model for the Utricularia trap
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
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
Modeling of Dynamic FRC Formation
NASA Astrophysics Data System (ADS)
Mok, Yung; Barnes, Dan; Dettrick, Sean
2010-11-01
We have developed a 2-D resistive MHD code, Lamy Ridge, to simulate the entire FRC formation process in Tri Alpha's C2 device, including initial formation, translation, merging and settling into equilibrium. Two FRC's can be created simultaneously, and then translated toward each other so that they merge into a single FRC. The code couples the external circuits around the formation tubes to the partially ionized plasma inside. Plasma and neutral gas are treated as two fluids. Dynamic and energetic equations, which take into account ionization and charge exchange, are solved in a time advance manner. The geometric shape of the vessel is specified by a set of inputs that defines the boundaries, which are handled by a cut-cell algorithm in the code. Multiple external circuits and field coils can be easily added, removed or relocated through individual inputs. The design of the code is modular and flexible so that it can be applied to future devices. The results of the code are in reasonable agreement with experimental measurements on the C2 device.
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.
Nonequilibrium dynamics in the antiferromagnetic Hubbard model
NASA Astrophysics Data System (ADS)
Sandri, Matteo; Fabrizio, Michele
2013-10-01
We investigate by means of the time-dependent Gutzwiller variational approach the out-of-equilibrium dynamics of an antiferromagnetic state evolved with the Hubbard model Hamiltonian after a sudden change of the repulsion strength U. We find that magnetic order survives more than what is expected on the basis of thermalization arguments, in agreement with recent dynamical mean field theory calculations. In addition, we find evidence of a dynamical transition for quenches to large values of U between a coherent antiferromagnet characterized by a finite quasiparticle residue to an incoherent one with vanishing residue, which finally turns into a paramagnet for even larger U.
Modeling the Dynamics of Compromised Networks
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.
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.
Dynamical model of bubble path instability.
Shew, Woodrow L; Pinton, Jean-François
2006-10-01
Millimeter-sized air bubbles rising through still water are known to exhibit zigzag and spiral oscillatory trajectories. We present a system of four ordinary differential equations which effectively model these dynamics. The model is based on Kirchhoff's equations and several physical arguments derived from our experimental observations. In the framework of this model, the zigzag and the spiral motions result from the same underlying bifurcation to wake instability. PMID:17155262
A dynamical model for multifragmentation of nuclei
NASA Astrophysics Data System (ADS)
Souza, S. R.; de Paula, L.; Leray, S.; Nemeth, J.; Ngô, C.; Ngô, H.
1994-04-01
A schematic model based on molecular dynamics and a restructured aggregation model is presented. We apply it to study the 16O+ 80Br system at several bombarding energies and compare some of the results to available emulsion data. We find that the model reproduces the experimental charge distributions rather well and the onset of multifragmentation for this system. Some general features of nuclear multifragmentation related to charged-particle production and intermediate-mass-fragments production are discussed.
Dynamic Model for Life History of Scyphozoa
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
Dynamic Model for Life History of Scyphozoa.
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
Modeling the dynamics of ant colony optimization.
Merkle, Daniel; Middendorf, Martin
2002-01-01
The dynamics of Ant Colony Optimization (ACO) algorithms is studied using a deterministic model that assumes an average expected behavior of the algorithms. The ACO optimization metaheuristic is an iterative approach, where in every iteration, artificial ants construct solutions randomly but guided by pheromone information stemming from former ants that found good solutions. The behavior of ACO algorithms and the ACO model are analyzed for certain types of permutation problems. It is shown analytically that the decisions of an ant are influenced in an intriguing way by the use of the pheromone information and the properties of the pheromone matrix. This explains why ACO algorithms can show a complex dynamic behavior even when there is only one ant per iteration and no competition occurs. The ACO model is used to describe the algorithm behavior as a combination of situations with different degrees of competition between the ants. This helps to better understand the dynamics of the algorithm when there are several ants per iteration as is always the case when using ACO algorithms for optimization. Simulations are done to compare the behavior of the ACO model with the ACO algorithm. Results show that the deterministic model describes essential features of the dynamics of ACO algorithms quite accurately, while other aspects of the algorithms behavior cannot be found in the model. PMID:12227995
Dynamic modeling of speed skiing
NASA Astrophysics Data System (ADS)
Catalfamo, R. S.
1997-12-01
The equations of motion that describe a skier descending a speed-skiing hill are solved both analytically and numerically. The model is shown to agree well with actual official results but only when the hill profile is considered. A sensitivity analysis reveals which parameters most affect the skier's exit speed. Other factors, such as scaling effects and wind gusts, are included to determine whether these need to be considered in official results. One surprising result is that, under certain conditions and hill profiles, maximum skier speed is attained prior to entry into the timing zone—thus bringing into question the optimum placement of the timing gates.
Dynamic modeling of solar dynamic components and systems. Final Report
Hochstein, J.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.
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.
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.
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.
Efficient dynamic models of tensegrity systems
NASA Astrophysics Data System (ADS)
Skelton, Robert
2009-03-01
The multi-body dynamics appear in a new form, as a matrix differential equation, rather than the traditional vector differential equation. The model has a constant mass matrix, and the equations are non-minimal. A specific focus of this paper is tensegrity systems. A tensegrity system requires prestress for stabilization of the configuration of rigid bodies and tensile members. This paper provides an efficient model for both static and dynamic behavior of such systems, specialized for the case when the rigid bodies are axi-symmetric rods.
You Turn Me Cold: Evidence for Temperature Contagion
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
Modeling emotional dynamics : currency versus field.
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.
Interest contagion in violation-of-expectation-based false-belief tasks.
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). PMID:24523706
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.
The Impact of Heterogeneous Thresholds on Social Contagion with Multiple Initiators
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
The Impact of Heterogeneous Thresholds on Social Contagion with Multiple Initiators.
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
Dynamic Radiation Environment Assimilation Model: DREAM
NASA Astrophysics Data System (ADS)
Reeves, G. D.; Chen, Y.; Cunningham, G. S.; Friedel, R. W. H.; Henderson, M. G.; Jordanova, V. K.; Koller, J.; Morley, S. K.; Thomsen, M. F.; Zaharia, S.
2012-03-01
The Dynamic Radiation Environment Assimilation Model (DREAM) was developed to provide accurate, global specification of the Earth's radiation belts and to better understand the physical processes that control radiation belt structure and dynamics. DREAM is designed using a modular software approach in order to provide a computational framework that makes it easy to change components such as the global magnetic field model, radiation belt dynamics model, boundary conditions, etc. This paper provides a broad overview of the DREAM model and a summary of some of the principal results to date. We describe the structure of the DREAM model, describe the five major components, and illustrate the various options that are available for each component. We discuss how the data assimilation is performed and the data preprocessing and postprocessing that are required for producing the final DREAM outputs. We describe how we apply global magnetic field models for conversion between flux and phase space density and, in particular, the benefits of using a self-consistent, coupled ring current-magnetic field model. We discuss some of the results from DREAM including testing of boundary condition assumptions and effects of adding a source term to radial diffusion models. We also describe some of the testing and validation of DREAM and prospects for future development.
Experimental evidence of massive-scale emotional contagion through social networks.
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. PMID:24889601
Optimal Empirical Prognostic Models of Climate Dynamics
NASA Astrophysics Data System (ADS)
Loskutov, E. M.; Mukhin, D.; Gavrilov, A.; Feigin, A. M.
2014-12-01
In this report the empirical methodology for prediction of climate dynamics is suggested. We construct the dynamical models of data patterns connected with climate indices, from observed spatially distributed time series. The models are based on artificial neural network (ANN) parameterization and have a form of discrete stochastic evolution operator mapping some sequence of systems state on the next one [1]. Different approaches to reconstruction of empirical basis (phase variables) for system's phase space representation, which is appropriate for forecasting the climate index of interest, are discussed in the report; for this purpose both linear and non-linear data expansions are considered. The most important point of the methodology is finding the optimal structural parameters of the model such as dimension of variable vector, i.e. number of principal components used for modeling, the time lag used for prediction, and number of neurons in ANN determining the quality of approximation. Actually, we need to solve the model selection problem, i.e. we want to obtain a model of optimal complexity in relation to analyzed time series. We use MDL approach [2] for this purpose: the model providing best data compression is chosen. The method is applied to space-distributed time-series of sea surface temperature and sea level pressure taken from IRI datasets [3]: the ability of proposed models to predict different climate indices (incl. Multivariate ENSO index, Pacific Decadal Oscillation index, North-Atlantic Oscillation index) is investigated. References:1. Molkov Ya. I., E. M. Loskutov, D. N. Mukhin, and A. M. Feigin, Random dynamical models from time series. Phys. Rev. E, 85, 036216, 2012.2. Molkov, Ya.I., D.N. Mukhin, E.M. Loskutov, A.M. Feigin, and G.A. Fidelin, Using the minimum description length principle for global reconstruction of dynamic systems from noisy time series. Phys. Rev. E, 80, 046207, 2009.3. IRI/LDEO Climate Data Library (http://iridl.ldeo.columbia.edu/)
A Novel Virus-Patch Dynamic Model.
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
A Novel Virus-Patch Dynamic Model
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
Modeling biological pathway dynamics with timed automata.
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. PMID:24808226
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.
System and mathematical modeling of quadrotor dynamics
NASA Astrophysics Data System (ADS)
Goodman, Jacob M.; Kim, Jinho; Gadsden, S. Andrew; Wilkerson, Stephen A.
2015-05-01
Unmanned aerial systems (UAS) are becoming increasingly visible in our daily lives; and range in operation from search and rescue, monitoring hazardous environments, and to the delivery of goods. One of the most popular UAS are based on a quad-rotor design. These are typically small devices that rely on four propellers for lift and movement. Quad-rotors are inherently unstable, and rely on advanced control methodologies to keep them operating safely and behaving in a predictable and desirable manner. The control of these devices can be enhanced and improved by making use of an accurate dynamic model. In this paper, we examine a simple quadrotor model, and note some of the additional dynamic considerations that were left out. We then compare simulation results of the simple model with that of another comprehensive model.
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.
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.
DYNAMIC LANDSCAPES, STABILITY AND ECOLOGICAL MODELING
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 ...
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.
Pupillary Contagion in Infancy: Evidence for Spontaneous Transfer of Arousal.
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. PMID:27207876
[Rayer's studies on the contagion of glanders (1837-1843)].
Richet, Gabriel
2002-01-01
P. Rayer (1795-1867) had never thoroughly published his experimental studies on the contagion of glanders. His recently un-earthed hand written papers allow us to depict his experimental approach and its results. He was not the first who transmitted glanders from a patient to horses or donkeys. But he did it systematically with glander secretions from acute and chronic cases. Whatever was the disease of the donors the transmitted forms were unpredictably either chronic or acute. His conclusion was that the two forms were two symptomatic aspects of a unique disease. Clinically dormant states were shown to be also contagious. He demonstrated it through deliberately altering healthy and sick horses inside the stable and by using saddles, bridles and brushes of sick horses on healthy ones. Moreover he excluded other causative factors tentatively proposed, peculiarly food products. The systematically logical and rigorous experimental approach used by Rayer for this research is a mile stone, 30 years before Pasteur. This methodology is still nowadays used to study the epidemiology of diseases such as Prion Diseases, Mad Cow for instance. PMID:12607548
The contagion indicator hypothesis for parasite-mediated sexual selection.
Able, D J
1996-03-01
Hamilton and Zuk [Hamilton, W. D. & Zuk, M. (1982) Science 218, 384-387] proposed that females choosing mates based on the degree of expression of male characters obtain heritable parasite resistance for their offspring. Alternatively, the "contagion indicator" hypothesis posits that females choose mates based on the degree of expression of male characters because the latter indicate a male's degree of infestation of parasites and thus the risk that choosing females and their offspring will acquire these parasites. I examined whether parasite transmittability affects the probability that parasite intensity and male mating success are negatively correlated in intraspecific studies of parasite-mediated sexual selection. When females risk infection of themselves or their future offspring as a result of mating with a parasitized male, negative relationships between parasite intensity and male mating success are significantly more likely to occur than when females do not risk such infection. The direct benefit to females of avoiding parasitic infection is proposed to lead to the linkage between variable secondary sexual characters and the intensity of transmittable parasites. The direct benefits of avoiding associatively transmittable parasites should be considered in future studies of parasite-mediated sexual selection. PMID:8700912
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.
Modeling of dynamical processes in laser ablation
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.
Feature extraction for structural dynamics model validation
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.
Dynamic models for the study of frailty.
Lipsitz, Lewis A
2008-11-01
Frailty can be viewed as resulting from the degradation of multiple interacting physiologic systems that are normally responsible for healthy adaptation to the daily demands of life. Mathematical models that can quantify alterations in the dynamics of physiologic systems and their interactions may help characterize the syndrome of frailty and enable investigators to test interventions to prevent its onset. One theoretical mathematical model reported by Varadhan et al. in this issue of the Journal represents one type of regulatory process that may become altered in frail individuals-the stimulus-response mechanism [Varadhan, R., Seplaki, C.S., Xue, Q.L., Bandeen-Roche, K., Fried, L.P. Stimulus-response paradigm for characterizing the loss of resilience in homeostatic regulation associated with frailty. Mech. Ageing Dev., this issue]. This model focuses on the timing of recovery from a single stimulus, rather than the full array of responses that might be altered in a complex dynamical system. Therefore, alternative models are needed to describe the wide variety of behaviors of physiologic systems over time and how they change with the onset of frailty. One such model, based on a simple signaling network composed of a lattice of nodes and the bi-directional connections between them, can reproduce the complex, fractal-like nature of healthy physiological processes. This model can be used to demonstrate how the degradation of signaling pathways within a physiologic system can result in the loss of complex dynamics that characterizes frailty. PMID:18930754
Rupture dynamics in model polymer systems.
Borah, Rupam; Debnath, Pallavi
2016-05-11
In this paper we explore the rupture dynamics of a model polymer system to capture the microscopic mechanism during relative motion of surfaces at the single polymer level. Our model is similar to the model for friction introduced by Filippov, Klafter, and Urbakh [Filippov et al., Phys. Rev. Lett., 2004, 92, 135503]; but with an important generalization to a flexible transducer (modelled as a bead spring polymer) which is attached to a fixed rigid planar substrate by interconnecting bonds (modelled as harmonic springs), and pulled by a constant force FT. Bonds are allowed to rupture stochastically. The model is simulated, and the results for a certain set of parameters exhibit a sequential rupture mechanism resulting in rupture fronts. A mean field formalism is developed to study these rupture fronts and the possible propagating solutions for the coupled bead and bond dynamics, where the coupling excludes an exact analytical treatment. Numerical solutions to mean field equations are obtained by standard numerical techniques, and they agree well with the simulation results which show sequential rupture. Within a travelling wave formalism based on the Tanh method, we show that the velocity of the rupture front can be obtained in closed form. The derived expression for the rupture front velocity gives good agreement with the stochastic and mean field results, when the rupture is sequential, while propagating solutions for bead and bond dynamics are shown to agree under certain conditions. PMID:27087684
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
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 PMID:26766766
Emotional contagion: dogs and humans show a similar physiological response to human infant crying.
Yong, Min Hooi; Ruffman, Ted
2014-10-01
Humans respond to an infant crying with an increase in cortisol level and heightened alertness, a response interpreted as emotional contagion, a primitive form of empathy. Previous results are mixed when examining whether dogs might respond similarly to human distress. We examined whether domestic dogs, which have a long history of affiliation with humans, show signs of emotional contagion, testing canine (n=75) and human (n=74) responses to one of three auditory stimuli: a human infant crying, a human infant babbling, and computer-generated "white noise", with the latter two stimuli acting as controls. Cortisol levels in both humans and dogs increased significantly from baseline only after listening to crying. In addition, dogs showed a unique behavioral response to crying, combining submissiveness with alertness. These findings suggest that dogs experience emotional contagion in response to human infant crying and provide the first clear evidence of a primitive form of cross-species empathy. PMID:25452080
Condensed Antenna Structural Models for Dynamics Analysis
NASA Technical Reports Server (NTRS)
Levy, R.
1985-01-01
Condensed degree-of-freedom models are compared with large degree-of-freedom finite-element models of a representative antenna-tipping and alidade structure, for both locked and free-rotor configurations. It is shown that: (1) the effective-mass models accurately reproduce the lower-mode natural frequencies of the finite element model; (2) frequency responses for the two types of models are in agreement up to at least 16 rad/s for specific points; and (3) transient responses computed for the same points are in good agreement. It is concluded that the effective-mass model, which best represents the five lower modes of the finite-element model, is a sufficient representation of the structure for future incorporation with a total servo control structure dynamic simulation.
Dynamic occupancy models for explicit colonization processes.
Broms, Kristin M; Hooten, Mevin B; Johnson, Devin S; Altwegg, Res; Conquest, Loveday L
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. PMID:27008788
Dynamic occupancy models for explicit colonization processes
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.
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
Dynamics of macroautophagy: Modeling and oscillatory behavior
NASA Astrophysics Data System (ADS)
Han, Kyungreem; Kwon, Hyun Woong; Kang, Hyuk; Kim, Jinwoong; Lee, Myung-Shik; Choi, M. Y.
2012-02-01
We propose a model for macroautophagy and study the resulting dynamics of autophagy in a system isolated from its extra-cellular environment. It is found that the intracellular concentrations of autophagosomes and autolysosomes display oscillations with their own natural frequencies. Such oscillatory behaviors, which are interrelated to the dynamics of intracellular ATP, amino acids, and proteins, are consistent with the very recent biological observations. Implications of this theoretical study of autophagy are discussed, with regard to the possibility of guiding molecular studies of autophagy.
SORD: A New Rupture Dynamics Modeling Code
NASA Astrophysics Data System (ADS)
Ely, G.; Minster, B.; Day, S.
2005-12-01
We report on our progress in validating our rupture dynamics modeling code, capable of dealing with nonplanar faults and surface topography. The method uses a "mimetic" approach to model spontaneous rupture on a fault within a 3D isotropic anelastic solid, wherein the equations of motion are approximated with a second order Support-Operator method on a logically rectangular mesh. Grid cells are not required to be parallelepipeds, however, so that non-rectangular meshes can be supported to model complex regions. However, for areas in the mesh which are in fact rectangular, the code uses a streamlined version of the algorithm that takes advantage of the simplifications of the operators in such areas. The fault itself is modeled using a double node technique, and the rheology on the fault surface is modeled through a slip-weakening, frictional, internal boundary condition. The Support Operator Rupture Dynamics (SORD) code, was prototyped in MATLAB, and all algorithms have been validated against known (including analytical solutions, eg Kostrov, 1964) solutions or previously validated solutions. This validation effort is conducted in the context of the SCEC Dynamic Rupture model validation effort led by R. Archuleta and R. Harris. Absorbing boundaries at the model edges are handled using the perfectly matched layers method (PML) (Olsen & Marcinkovich, 2003). PML is shown to work extremely well on rectangular meshes. We show that our implementation is also effective on non-rectangular meshes under the restriction that the boundary be planar. For validation of the model we use a variety of test cases using two types of meshes: a rectangular mesh and skewed mesh. The skewed mesh amplifies any biases caused by the Support-Operator method on non-rectangular elements. Wave propagation and absorbing boundaries are tested with a spherical wave source. Rupture dynamics on a planar fault are tested against (1) a Kostrov analytical solution, (2) data from foam rubber scale models
The dynamic modelling of a slotted test section
NASA Technical Reports Server (NTRS)
Gumas, G.
1979-01-01
A mathematical model of the wind tunnel dynamics was developed. The modelling techniques were restricted to the use of one dimensional unsteady flow. The dynamic characteristics of slotted test section incorporated into the model are presented.
Methodology for Uncertainty Analysis of Dynamic Computational Toxicology Models
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...
Collisional model for granular impact dynamics.
Clark, Abram H; Petersen, Alec J; Behringer, Robert P
2014-01-01
When an intruder strikes a granular material from above, the grains exert a stopping force which decelerates and stops the intruder. Many previous studies have used a macroscopic force law, including a drag force which is quadratic in velocity, to characterize the decelerating force on the intruder. However, the microscopic origins of the force-law terms are still a subject of debate. Here, drawing from previous experiments with photoelastic particles, we present a model which describes the velocity-squared force in terms of repeated collisions with clusters of grains. From our high speed photoelastic data, we infer that "clusters" correspond to segments of the strong force network that are excited by the advancing intruder. The model predicts a scaling relation for the velocity-squared drag force that accounts for the intruder shape. Additionally, we show that the collisional model predicts an instability to rotations, which depends on the intruder shape. To test this model, we perform a comprehensive experimental study of the dynamics of two-dimensional granular impacts on beds of photoelastic disks, with different profiles for the leading edge of the intruder. We particularly focus on a simple and useful case for testing shape effects by using triangular-nosed intruders. We show that the collisional model effectively captures the dynamics of intruder deceleration and rotation; i.e., these two dynamical effects can be described as two different manifestations of the same grain-scale physical processes. PMID:24580216
Electronic continuum model for molecular dynamics simulations.
Leontyev, I V; Stuchebrukhov, A A
2009-02-28
A simple model for accounting for electronic polarization in molecular dynamics (MD) simulations is discussed. In this model, called molecular dynamics electronic continuum (MDEC), the electronic polarization is treated explicitly in terms of the electronic continuum (EC) approximation, while the nuclear dynamics is described with a fixed-charge force field. In such a force-field all atomic charges are scaled to reflect the screening effect by the electronic continuum. The MDEC model is rather similar but not equivalent to the standard nonpolarizable force-fields; the differences are discussed. Of our particular interest is the calculation of the electrostatic part of solvation energy using standard nonpolarizable MD simulations. In a low-dielectric environment, such as protein, the standard MD approach produces qualitatively wrong results. The difficulty is in mistreatment of the electronic polarizability. We show how the results can be much improved using the MDEC approach. We also show how the dielectric constant of the medium obtained in a MD simulation with nonpolarizable force-field is related to the static (total) dielectric constant, which includes both the nuclear and electronic relaxation effects. Using the MDEC model, we discuss recent calculations of dielectric constants of alcohols and alkanes, and show that the MDEC results are comparable with those obtained with the polarizable Drude oscillator model. The applicability of the method to calculations of dielectric properties of proteins is discussed. PMID:19256627
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.
Global dynamic modeling of a transmission system
NASA Astrophysics Data System (ADS)
Choy, F. K.; Qian, W.
1993-04-01
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.
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.
Development of a dynamic thermal model process
Smith, F. R.
1996-04-01
A dynamic electrical-thermal modeling simulation technique was developed to allow up-front design of thermal and electronic packaging with a high degree of accuracy and confidence. We are developing a hybrid multichip module output driver which controls with power MOSFET driver circuits. These MOSFET circuits will dissipate from 13 to 26 watts per driver in a physical package less than two square inches. The power dissipation plus an operating temperature range of -55{degrees} C to 100{degrees} C makes an accurate thermal package design critical. The project goal was to develop a simulation process to dynamically model the electrical/thermal characteristics of the power MOSFETS using the SABER analog simulator and the ABAQUS finite element simulator. SABER would simulate the electrical characteristics of the multi-chip module design while co-simulation is being done with ABAQUS simulating the solid model thermal characteristics of the MOSFET package. The dynamic parameters, MOSFET power and chip temperature, would be actively passed between simulators to effect a coupled simulator modelling technique. The project required a development of a SABER late for the analog ASIC controller circuit, a dynamic electrical/thermal template for the IRF150 and IRF9130 power MOSFETs, a solid model of the multi-chip module package, FORTRAN code to handle I/Q between and HP755 workstation and SABER, and I/O between CRAY J90 computer and ABAQUS. The simulation model was certified by measured electrical characteristics of the circuits and real time thermal imaging of the output multichip module.
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.
Fluid-dynamical model for antisurfactants
NASA Astrophysics Data System (ADS)
Conn, Justin J. A.; Duffy, Brian R.; Pritchard, David; Wilson, Stephen K.; Halling, Peter J.; Sefiane, Khellil
2016-04-01
We construct a fluid-dynamical model for the flow of a solution with a free surface at which surface tension acts. This model can describe both classical surfactants, which decrease the surface tension of the solution relative to that of the pure solvent, and antisurfactants (such as many salts when added to water, and small amounts of water when added to alcohol) which increase it. We demonstrate the utility of the model by considering the linear stability of an infinitely deep layer of initially quiescent fluid. In particular, we predict the occurrence of an instability driven by surface-tension gradients, which occurs for antisurfactant, but not for surfactant, solutions.
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.
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.
Dynamical Field Model of Hand Preference
NASA Astrophysics Data System (ADS)
Franceschetti, Donald R.; Cantalupo, Claudio
2000-11-01
Dynamical field models of information processing in the nervous system are being developed by a number of groups of psychologists and physicists working together to explain The details of behaviors exhibited by a number of animal species. Here we adapt such a model to the expression of hand preference in a small primate, the bushbaby (Otolemur garnetti) . The model provides a theoretical foundation for the interpretation of an experiment currently underway in which a several of these animals are forced to extend either right or left hand to retrieve a food item from a rotating turntable.
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.
Structural system identification: Structural dynamics model validation
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.
Dynamic Multicriteria Evaluation of Conceptual Hydrological Models
NASA Astrophysics Data System (ADS)
de Vos, N. J.; Rientjes, T. H.; Fenicia, F.; Gupta, H. V.
2007-12-01
Accurate and precise forecasts of river streamflows are crucial for successful management of water resources and under the threat of hydrological extremes such as floods and droughts. Conceptual rainfall-runoff models are the most popular approach in flood forecasting. However, the calibration and evaluation of such models is often oversimplified by the use of performance statistics that largely ignore the dynamic character of a watershed system. This research aims to find novel ways of model evaluation by identifying periods of hydrologic similarity and customizing evaluation within each period using multiple criteria. A dynamic approach to hydrologic model identification, calibration and testing can be realized by applying clustering algorithms (e.g., Self-Organizing Map, Fuzzy C-means algorithm) to hydrological data. These algorithms are able to identify clusters in the data that represent periods of hydrological similarity. In this way, dynamic catchment system behavior can be simplified within the clusters that are identified. Although clustering requires a number of subjective choices, new insights into the hydrological functioning of a catchment can be obtained. Finally, separate model multi-criteria calibration and evaluation is performed for each of the clusters. Such a model evaluation procedure shows to be reliable and gives much-needed feedback on exactly where certain model structures fail. Several clustering algorithms were tested on two data sets of meso-scale and large-scale catchments. The results show that the clustering algorithms define categories that reflect hydrological process understanding: dry/wet seasons, rising/falling hydrograph limbs, precipitation-driven/ non-driven periods, etc. The results of various clustering algorithms are compared and validated using expert knowledge. Calibration results on a conceptual hydrological model show that the common practice of single-criteria calibration over the complete time series fails to perform
Dynamic alignment models for neural coding.
Kollmorgen, Sepp; Hahnloser, Richard H R
2014-03-01
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
Cellular automata modelling of biomolecular networks dynamics.
Bonchev, D; Thomas, S; Apte, A; Kier, L B
2010-01-01
The modelling of biological systems dynamics is traditionally performed by ordinary differential equations (ODEs). When dealing with intracellular networks of genes, proteins and metabolites, however, this approach is hindered by network complexity and the lack of experimental kinetic parameters. This opened the field for other modelling techniques, such as cellular automata (CA) and agent-based modelling (ABM). This article reviews this emerging field of studies on network dynamics in molecular biology. The basics of the CA technique are discussed along with an extensive list of related software and websites. The application of CA to networks of biochemical reactions is exemplified in detail by the case studies of the mitogen-activated protein kinase (MAPK) signalling pathway, the FAS-ligand (FASL)-induced and Bcl-2-related apoptosis. The potential of the CA method to model basic pathways patterns, to identify ways to control pathway dynamics and to help in generating strategies to fight with cancer is demonstrated. The different line of CA applications presented includes the search for the best-performing network motifs, an analysis of importance for effective intracellular signalling and pathway cross-talk. PMID:20373215
Efficient gradient computation for dynamical models
Sengupta, B.; Friston, K.J.; Penny, W.D.
2014-01-01
Data assimilation is a fundamental issue that arises across many scales in neuroscience — ranging from the study of single neurons using single electrode recordings to the interaction of thousands of neurons using fMRI. Data assimilation involves inverting a generative model that can not only explain observed data but also generate predictions. Typically, the model is inverted or fitted using conventional tools of (convex) optimization that invariably extremise some functional — norms, minimum descriptive length, variational free energy, etc. Generally, optimisation rests on evaluating the local gradients of the functional to be optimized. In this paper, we compare three different gradient estimation techniques that could be used for extremising any functional in time — (i) finite differences, (ii) forward sensitivities and a method based on (iii) the adjoint of the dynamical system. We demonstrate that the first-order gradients of a dynamical system, linear or non-linear, can be computed most efficiently using the adjoint method. This is particularly true for systems where the number of parameters is greater than the number of states. For such systems, integrating several sensitivity equations – as required with forward sensitivities – proves to be most expensive, while finite-difference approximations have an intermediate efficiency. In the context of neuroimaging, adjoint based inversion of dynamical causal models (DCMs) can, in principle, enable the study of models with large numbers of nodes and parameters. PMID:24769182
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.
Dynamic Modeling of an Evapotranspiration Cap
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.
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
Modelling the mechanoreceptor’s dynamic behaviour
Song, Zhuoyi; Banks, Robert W; Bewick, Guy S
2015-01-01
All sensory receptors adapt, i.e. they constantly adjust their sensitivity to external stimuli to match the current demands of the natural environment. Electrophysiological responses of sensory receptors from widely different modalities seem to exhibit common features related to adaptation, and these features can be used to examine the underlying sensory transduction mechanisms. Among the principal senses, mechanosensation remains the least understood at the cellular level. To gain greater insights into mechanosensory signalling, we investigated if mechanosensation displayed adaptive dynamics that could be explained by similar biophysical mechanisms in other sensory modalities. To do this, we adapted a fly photoreceptor model to describe the primary transduction process for a stretch-sensitive mechanoreceptor, taking into account the viscoelastic properties of the accessory muscle fibres and the biophysical properties of known mechanosensitive channels (MSCs). The model’s output is in remarkable agreement with the electrical properties of a primary ending in an isolated decapsulated spindle; ramp-and-hold stretch evokes a characteristic pattern of potential change, consisting of a large dynamic depolarization during the ramp phase and a smaller static depolarization during the hold phase. The initial dynamic component is likely to be caused by a combination of the mechanical properties of the muscle fibres and a refractory state in the MSCs. Consistent with the literature, the current model predicts that the dynamic component is due to a rapid stress increase during the ramp. More novel predictions from the model are the mechanisms to explain the initial peak in the dynamic component. At the onset of the ramp, all MSCs are sensitive to external stimuli, but as they become refractory (inactivated), fewer MSCs are able to respond to the continuous stretch, causing a sharp decrease after the peak response. The same mechanism could contribute a faster component in
Dynamical Causal Modeling from a Quantum Dynamical Perspective
NASA Astrophysics Data System (ADS)
Demiralp, Emre; Demiralp, Metin
2010-09-01
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.
Dynamical Causal Modeling from a Quantum Dynamical Perspective
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.
Part 2: Fear of contagion, fear of intimacy.
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
Identification of helicopter rotor dynamic models
NASA Technical Reports Server (NTRS)
Molusis, J. A.; Bar-Shalom, Y.; Warmbrodt, W.
1983-01-01
A recursive, extended Kalman-filter approach is applied to the identifiction of rotor damping levels of representative helicopter dynamic systems. The general formulation of the approach is presented in the context of a typically posed stochastic estimation problem, and the method is analytically applied to determining the damping levels of a coupled rotor-body system. The identified damping covergence characteristics are studied for sensitivity to both constant-coefficient and periodic-coefficient measurement models, process-noise covariance levels, and specified initial estimates of the rotor-system damping. A second application of the method to identifying the plant model for a highly damped, isolated flapping blade with a constant-coefficient state model (hover) and a periodic-coefficient state model (forward flight) is also investigated. The parameter-identification capability is evaluated for the effect of periodicity on the plant model coefficients and the influence of different measurement noise levels.
The dynamic radiation environment assimilation model (DREAM)
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.
Mathematical Models for HIV Transmission Dynamics
Cassels, Susan; Clark, Samuel J.; Morris, Martina
2012-01-01
Summary HIV researchers have long appreciated the need to understand the social and behavioral determinants of HIV-related risk behavior, but the cumulative impact of individual behaviors on population-level HIV outcomes can be subtle and counterintuitive, and the methods for studying this are rarely part of a traditional social science or epidemiology training program. Mathematical models provide a way to examine the potential effects of the proximate biologic and behavioral determinants of HIV transmission dynamics, alone and in combination. The purpose of this article is to show how mathematical modeling studies have contributed to our understanding of the dynamics and disparities in the global spread of HIV. Our aims are to demonstrate the value that these analytic tools have for social and behavioral sciences in HIV prevention research, to identify gaps in the current literature, and to suggest directions for future research. PMID:18301132
Dynamical models of hydrogenated amorphous silicon
NASA Astrophysics Data System (ADS)
Mousseau, Normand; Lewis, Laurent J.
1991-04-01
The results of our molecular-dynamics simulation of bulk hydrogenated amorphous silicon using empirical potentials are presented. More specifically, we discuss a dynamical procedure for incorporating hydrogen into a pure amorphous silicon matrix, which is derived from the concept of floating bonds put forward by Pantelides [Phys. Rev. Lett. 57, 2979 (1986)]. The structures resulting from this model are compared with those obtained with use of a static approach recently developed by us. This method exhibits considerable improvement over the previous one and, in particular, unambiguously reveals the strain-relieving role of hydrogen. While the former model leads to substantial overcoordination, the present one results in almost perfect tetrahedral bonding, with an average coordination number Z=4.03, the lowest value ever achieved using a Stillinger-Weber potential. The simulations are also used to calculate the vibrational densities of states, which are found to be in good accord with corresponding neutron-scattering measurements.
Dynamic plasmapause model based on THEMIS measurements
NASA Astrophysics Data System (ADS)
Liu, X.; Liu, W.; Cao, J. B.; Fu, H. S.; Yu, J.; Li, X.
2015-12-01
This paper presents a dynamic plasmapause location model established based on 5 years of Time History of Events and Macroscale Interactions during Substorms (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 5 min-averaged SYM-H, AL, and AU indices as well as hourly-averaged AE and Kp indices. two out-of-sample comparisons on the evolution of the plasmapause is shown during two magnetic storms, 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 the plasmapause on timescales as short as 5 min.
Emotional contagion in mice: the role of familiarity.
Gonzalez-Liencres, Cristina; Juckel, Georg; Tas, Cumhur; Friebe, Astrid; Brüne, Martin
2014-04-15
Empathy is a complex emotional process that involves sharing an emotional state with another organism. The extent to which nonhuman animals are capable of empathizing with others is still far from clear, partly due to a lack of empirical work in this domain, but also due to definitional confusion of empathy with emotional contagion and other related terms. In this study, an observer mouse witnessed a familiar cagemate or an unfamiliar non-cagemate receiving electric foot shocks in an experiment that consisted of three periods: baseline (no shocks), test (shocks) and recovery (no shocks). Freezing behavior in the observer was significantly increased in the cagemate, as opposed to the non-cagemate condition during the test period, but not during baseline or recovery, emphasizing the role of familiarity in empathy-like processes. In agreement with this, we also found a correlation that approached significance between the total number of fecal droppings of the observers, as an indication of distress, and those of the demonstrator in the cagemate, but not in the non-cagemate, condition. While the freezing behavior of the demonstrators increased with time, reaching a maximum at the recovery period, the observers froze the most during the test period while the demonstrators were receiving the electric foot shocks. The observation that the freezing response of the observers ceased when the shocks in the adjacent compartment stopped could be due to a decrease in saliency of the demonstrators' behavioral response. Finally, the presence of a cagemate, as compared to a stranger, possibly reduced the demonstrator's pain-induced behavior, suggesting an ameliorating effect of familiarity on stress responses. PMID:24480421
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.
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
Molecular dynamics modelling of solidification in metals
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.
Modeling the dynamics of nonlinear inductor circuits
NASA Astrophysics Data System (ADS)
Deane, Jonathan H. B.
1994-09-01
The Jiles-Atherton (J-A) model is applied to the problem of describing the dynamics of a nonlinear circuit driven by a square wave voltage source and comprising a linear resistor and capacitor in series with a nonlinear inductor, whose core displays saturation and hysteresis. The presence of hysteresis is shown to increase the order of the circuit by one. Period-multiplication and chaos are observed and excellent agreement is obtained between experiment and simulation.
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.
A dynamic model of thundercloud electric fields
NASA Technical Reports Server (NTRS)
Nisbet, J. S.
1983-01-01
A description is given of the first results obtained with a new type of dynamic electrical model of a thundercloud that allows the charge rearrangement produced in arc breakdown, as well as the conduction and displacement currents, to be calculated with realistic generator configurations. The model demonstrates the great complexity of behavior of thunderclouds owing to the interaction of the nonlinear breakdown mechanisms, the energy stored in the electric field, and a conductivity that varies with altitude. It is also seen that dynamic charge distributions and electric fields are quite different from static distributions. It is noted that these differences affect the initial conditions before and after lightning strokes. The conduction current density to the ionosphere is very much larger in the dynamic cases than in static simulations. Such basic properties of thunderclouds as the production of cloud-to-ground strokes are seen as compatible only with a very limited range of thundercloud models. Another finding is that coronal and convection currents cause the electric fields at the surface to be much smaller than they would be in their absence.
Bhandari, Poonam; Song, Moshi; Chen, Yun; Burelle, Yan; Dorn, Gerald W.
2015-01-01
Rationale Dysfunctional Parkin-mediated mitophagic culling of senescent or damaged mitochondria is a major pathological process underlying Parkinson disease and a potential genetic mechanism of cardiomyopathy. Despite epidemiological associations between Parkinson disease and heart failure, the role of Parkin and mitophagic quality control in maintaining normal cardiac homeostasis is poorly understood. Objective We used germline mutants and cardiac-specific RNA interference to interrogate Parkin regulation of cardiomyocyte mitochondria and examine functional crosstalk between mitophagy and mitochondrial dynamics in Drosophila heart tubes. Methods and Results Transcriptional profiling of Parkin knockout mouse hearts revealed compensatory upregulation of multiple related E3 ubiquitin ligases. Because Drosophila lack most of these redundant genes, we examined heart tubes of parkin knockout flies and observed accumulation of enlarged hollow donut mitochondria with dilated cardiomyopathy, which could be rescued by cardiomyocyte-specific Parkin expression. Identical abnormalities were induced by cardiomyocyte-specific Parkin suppression using 2 different inhibitory RNAs. Parkin-deficient cardiomyocyte mitochondria exhibited dysmorphology, depolarization, and reactive oxygen species generation without calcium cycling abnormalities, pointing to a primary mitochondrial defect. Suppressing cardiomyocyte mitochondrial fusion in Parkin-deficient fly heart tubes completely prevented the cardiomyopathy and corrected mitochondrial dysfunction without normalizing mitochondrial dysmorphology, demonstrating a central role for mitochondrial fusion in the cardiomyopathy provoked by impaired mitophagy. Conclusions Parkin deficiency and resulting mitophagic disruption produces cardiomyopathy in part by contamination of the cardiomyocyte mitochondrial pool through fusion between improperly retained dysfunctional/senescent and normal mitochondria. Limiting mitochondrial contagion by
Adaptive dynamics for physiologically structured population models.
Durinx, Michel; Metz, J A J Hans; Meszéna, Géza
2008-05-01
We develop a systematic toolbox for analyzing the adaptive dynamics of multidimensional traits in physiologically structured population models with point equilibria (sensu Dieckmann et al. in Theor. Popul. Biol. 63:309-338, 2003). Firstly, we show how the canonical equation of adaptive dynamics (Dieckmann and Law in J. Math. Biol. 34:579-612, 1996), an approximation for the rate of evolutionary change in characters under directional selection, can be extended so as to apply to general physiologically structured population models with multiple birth states. Secondly, we show that the invasion fitness function (up to and including second order terms, in the distances of the trait vectors to the singularity) for a community of N coexisting types near an evolutionarily singular point has a rational form, which is model-independent in the following sense: the form depends on the strategies of the residents and the invader, and on the second order partial derivatives of the one-resident fitness function at the singular point. This normal form holds for Lotka-Volterra models as well as for physiologically structured population models with multiple birth states, in discrete as well as continuous time and can thus be considered universal for the evolutionary dynamics in the neighbourhood of singular points. Only in the case of one-dimensional trait spaces or when N = 1 can the normal form be reduced to a Taylor polynomial. Lastly we show, in the form of a stylized recipe, how these results can be combined into a systematic approach for the analysis of the (large) class of evolutionary models that satisfy the above restrictions. PMID:17943289
DYNAMICAL MODELING OF GALAXY MERGERS USING IDENTIKIT
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.
Approaches for modeling magnetic nanoparticle dynamics
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
A dynamical model for bark beetle outbreaks.
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
Dynamic stall simulation including turbulence modeling
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.
New concepts for dynamic plant uptake models.
Rein, A; Legind, C N; Trapp, S
2011-03-01
Models for the prediction of chemical uptake into plants are widely applied tools for human and wildlife exposure assessment, pesticide design and for environmental biotechnology such as phytoremediation. Steady-state considerations are often applied, because they are simple and have a small data need. However, often the emission pattern is non-steady. Examples are pesticide spraying, or the application of manure and sewage sludge on agricultural fields. In these scenarios, steady-state solutions are not valid, and dynamic simulation is required. We compared different approaches for dynamic modelling of plant uptake in order to identify relevant processes and timescales of processes in the soil-plant-air system. Based on the outcome, a new model concept for plant uptake models was developed, approximating logistic growth and coupling transpiration to growing plant mass. The underlying system of differential equations was solved analytically for the inhomogenous case, i.e. for constant input. By superposition of the results of n periods, changes in emission and input data between periods are considered. This combination allows to mimic most input functions that are relevant in practice. The model was set up, parameterized and tested for uptake into growing crops. The outcome was compared with a numerical solution, to verify the mathematical structure. PMID:21391147
Restoration of the Potosi Dynamic Model 2010
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
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.
Transition matrix model for evolutionary game dynamics.
Ermentrout, G Bard; Griffin, Christopher; Belmonte, Andrew
2016-03-01
We study an evolutionary game model based on a transition matrix approach, in which the total change in the proportion of a population playing a given strategy is summed directly over contributions from all other strategies. This general approach combines aspects of the traditional replicator model, such as preserving unpopulated strategies, with mutation-type dynamics, which allow for nonzero switching to unpopulated strategies, in terms of a single transition function. Under certain conditions, this model yields an endemic population playing non-Nash-equilibrium strategies. In addition, a Hopf bifurcation with a limit cycle may occur in the generalized rock-scissors-paper game, unlike the replicator equation. Nonetheless, many of the Folk Theorem results are shown to hold for this model. PMID:27078323
Transition matrix model for evolutionary game dynamics
NASA Astrophysics Data System (ADS)
Ermentrout, G. Bard; Griffin, Christopher; Belmonte, Andrew
2016-03-01
We study an evolutionary game model based on a transition matrix approach, in which the total change in the proportion of a population playing a given strategy is summed directly over contributions from all other strategies. This general approach combines aspects of the traditional replicator model, such as preserving unpopulated strategies, with mutation-type dynamics, which allow for nonzero switching to unpopulated strategies, in terms of a single transition function. Under certain conditions, this model yields an endemic population playing non-Nash-equilibrium strategies. In addition, a Hopf bifurcation with a limit cycle may occur in the generalized rock-scissors-paper game, unlike the replicator equation. Nonetheless, many of the Folk Theorem results are shown to hold for this model.
AFDM: An Advanced Fluid-Dynamics Model
Bohl, W.R.; Parker, F.R. ); Wilhelm, D. . Inst. fuer Neutronenphysik und Reaktortechnik); Berthier, J. ); Goutagny, L. . Inst. de Protection et de Surete Nucleaire); Ninokata,
1990-09-01
AFDM, or the Advanced Fluid-Dynamics Model, is a computer code that investigates new approaches simulating the multiphase-flow fluid-dynamics aspects of severe accidents in fast reactors. The AFDM formalism starts with differential equations similar to those in the SIMMER-II code. These equations are modified to treat three velocity fields and supplemented with a variety of new models. The AFDM code has 12 topologies describing what material contacts are possible depending on the presence or absence of a given material in a computational cell, on the dominant liquid, and on the continuous phase. Single-phase, bubbly, churn-turbulent, cellular, and dispersed flow regimes are permitted for the pool situations modeled. Virtual mass terms are included for vapor in liquid-continuous flow. Interfacial areas between the continuous and discontinuous phases are convected to allow some tracking of phenomenological histories. Interfacial areas are also modified by models of nucleation, dynamic forces, turbulence, flashing, coalescence, and mass transfer. Heat transfer is generally treated using engineering correlations. Liquid-vapor phase transitions are handled with the nonequilibrium, heat-transfer-limited model, whereas melting and freezing processes are based on equilibrium considerations. Convection is treated using a fractional-step method of time integration, including a semi-implicit pressure iteration. A higher-order differencing option is provided to control numerical diffusion. The Los Alamos SESAME equation-of-state has been implemented using densities and temperatures as the independent variables. AFDM programming has vectorized all computational loops consistent with the objective of producing an exportable code. 24 refs., 4 figs.
An efficient model of drillstring dynamics
NASA Astrophysics Data System (ADS)
Butlin, T.; Langley, R. S.
2015-11-01
High amplitude vibration regimes can cause significant damage to oilwell drillstrings: torsional stick-slip oscillation, forward whirl and backward whirl are each associated with different kinds of damage. There is a need for models of drillstring dynamics that can predict this variety of phenomena that are: efficient enough to carry out parametric studies; simple enough to provide insight into the underlying physics, and which retain sufficient detail to correlate to real drillstrings. The modelling strategy presented in this paper attempts to balance these requirements. It includes the dynamics of the full length of the drillstring over a wide bandwidth but assumes that the main nonlinear effects are due to spatially localised regions of strong nonlinearity, for example at the drillbit cutting interface and at stabilisers where the borehole wall clearance is smallest. The equations of motion can be formed in terms of this reduced set of degrees of freedom, coupled to the nonlinear contact laws and solved by time-domain integration. Two implementations of this approach are presented, using (1) digital filters and (2) a finite element model to describe the linear dynamics. Choosing a sampling period that is less than the group delay between nonlinear degrees of freedom results in a decoupled set of equations that can be solved very efficiently. Several cases are presented which demonstrate a variety of phenomena, including stick-slip oscillation; forward whirl and backward whirl. Parametric studies are shown which reveal the conditions which lead to high amplitude vibration regimes, and an analytic regime boundary is derived for torsional stick-slip oscillation. The digital filter and finite element models are shown to be in good agreement and are similarly computationally efficient. The digital filter approach has the advantage of more intuitive interpretation, while the finite element model is more readily implemented using existing software packages.
Dynamic geometry, brain function modeling, and consciousness.
Roy, Sisir; Llinás, Rodolfo
2008-01-01
Pellionisz and Llinás proposed, years ago, a geometric interpretation towards understanding brain function. This interpretation assumes that the relation between the brain and the external world is determined by the ability of the central nervous system (CNS) to construct an internal model of the external world using an interactive geometrical relationship between sensory and motor expression. This approach opened new vistas not only in brain research but also in understanding the foundations of geometry itself. The approach named tensor network theory is sufficiently rich to allow specific computational modeling and addressed the issue of prediction, based on Taylor series expansion properties of the system, at the neuronal level, as a basic property of brain function. It was actually proposed that the evolutionary realm is the backbone for the development of an internal functional space that, while being purely representational, can interact successfully with the totally different world of the so-called "external reality". Now if the internal space or functional space is endowed with stochastic metric tensor properties, then there will be a dynamic correspondence between events in the external world and their specification in the internal space. We shall call this dynamic geometry since the minimal time resolution of the brain (10-15 ms), associated with 40 Hz oscillations of neurons and their network dynamics, is considered to be responsible for recognizing external events and generating the concept of simultaneity. The stochastic metric tensor in dynamic geometry can be written as five-dimensional space-time where the fifth dimension is a probability space as well as a metric space. This extra dimension is considered an imbedded degree of freedom. It is worth noticing that the above-mentioned 40 Hz oscillation is present both in awake and dream states where the central difference is the inability of phase resetting in the latter. This framework of dynamic
OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems.
Ogbunugafor, C Brandon; Robinson, Sean P
2016-01-01
Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs) by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of "ODEs and formalized flow diagrams" as OFFL.) Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative) abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler's behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features. PMID:27270918
Dynamic Modeling of the SMAP Rotating Flexible Antenna
NASA Technical Reports Server (NTRS)
Nayeri, Reza D.
2012-01-01
Dynamic model development in ADAMS for the SMAP project is explained: The main objective of the dynamic models are for pointing error assessment, and the control/stability margin requirement verifications
Dynamic modeling of hydrostatic guideway considering compressibility and inertia effect
NASA Astrophysics Data System (ADS)
Du, Yikang; Mao, Kuanmin; Zhu, Yaming; Wang, Fengyun; Mao, Xiaobo; Li, Bin
2015-03-01
Hydrostatic guideways are used as an alternative to contact bearings due to high stiffness and high damping in heavy machine tools. To improve the dynamic characteristic of bearing structure, the dynamic modeling of the hydrostatic guidway should be accurately known. This paper presents a "mass-spring-Maxwell" model considering the effects of inertia, squeeze, compressibility and static bearing. To determine the dynamic model coefficients, numerical simulation of different cases between displacement and dynamic force of oil film are performed with fluent code. Simulation results show that hydrostatic guidway can be taken as a linear system when it is subjected to a small oscillation amplitude. Based on a dynamic model and numerical simulation, every dynamic model's parameters are calculated by the Levenberg-Marquardt algorithm. Identification results show that "mass-spring-damper" model is the most appropriate dynamic model of the hydrostatic guidway. This paper provides a reference and preparation for the analysis of the dynamic model of the similar hydrostatic bearings.
Vanderweele, Tyler J; Tchetgen Tchetgen, Eric J; Halloran, M Elizabeth
2012-09-01
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
NASA Astrophysics Data System (ADS)
Dodds, Peter Sheridan; Harris, Kameron Decker; Payne, Joshua L.
2011-05-01
For a broad range of single-seed contagion processes acting on generalized random networks, we derive a unifying analytic expression for the possibility of global spreading events in a straightforward, physically intuitive fashion. Our reasoning lays bare a direct mechanical understanding of an archetypal spreading phenomena that is not evident in circuitous extant mathematical approaches.
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
ERIC Educational Resources Information Center
Lee, Bethany R.; Thompson, Ron
2009-01-01
Although concerns about peer contagion are often cited in critiques of group treatments for troubled youths, few studies have examined the effects of exposure to deviant peers in residential group care settings. This study used administrative data of youth served at Boys Town, a nationally-known group care provider. Using latent class growth…
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…
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.…
The Relative Importance of Socially Induced Tension and Behavioral Contagion for Smoking Behavior
ERIC Educational Resources Information Center
Glad, Wayne; Adesso, Vincent J.
1976-01-01
The purposes of this experiment were to determine (a) whether socially stimulated smoking (behavior contagion) occurs, (b) if evaluation by others is tension producing and if subjects smoke to reduce that tension, (c) if a relaxed social atmosphere would be conducive to smoking, and (d) if sex differences exist in smoking behavior. (Author)
ERIC Educational Resources Information Center
Hartman, Rosanne L.; Johnson, J. David
1989-01-01
Compares two contrasting perspectives of social contagion processes (structural equivalence and cohesion) associated with the organizational outcome variables of commitment and role ambiguity in organizations. Finds that structural equivalence was more associated with role ambiguity and that commitment was more associated with cohesion. (MS)
A Model of Canine Leukocyte Telomere Dynamics
Benetos, Athanase; Kimura, Masayuki; Labat, Carlos; Buchoff, Gerald M.; Huber, Shell; Labat, Laura; Lu, Xiaobin; Aviv, Abraham
2011-01-01
Summary Recent studies have found associations of leukocyte telomere length (TL) with diseases of aging and with longevity. However, it is unknown whether birth leukocyte TL or its age-dependent attrition— the two factors that determine leukocyte TL dynamics— explains these associations, since acquiring this information entails monitoring individuals over their entire life course. We tested in dogs a model of leukocyte TL dynamics, based on the following premises: (i) TL is synchronized among somatic tissues; (ii) TL in skeletal muscle, which is largely post-mitotic, is a measure of TL in early development; (iii) the difference between TL in leukocytes and muscle (ΔLMTL) is the extent of leukocyte TL shortening since early development. Using this model, we observed in 83 dogs (ages 4–42 months) no significant change with age in TLs of skeletal muscle and a shorter TL in leukocytes than in skeletal muscle (P<0.0001). Age explained 43% of the variation in ΔLMTL (P<0.00001) but only 6% of the variation in leukocyte TL (P=0.035) among dogs. Accordingly, muscle TL and ΔLMTL provide the two essential factors of leukocyte TL dynamics in the individual dog. When applied to humans, the partition of the contribution of leukocyte TL during early development versus telomere shortening afterward might provide information about whether the individual’s longevity is calibrated to either one or both factors that define leukocyte TL dynamics. PMID:21917112
Comet Gas and Dust Dynamics Modeling
NASA Technical Reports Server (NTRS)
Von Allmen, Paul A.; Lee, Seungwon
2010-01-01
This software models the gas and dust dynamics of comet coma (the head region of a comet) in order to support the Microwave Instrument for Rosetta Orbiter (MIRO) project. MIRO will study the evolution of the comet 67P/Churyumov-Gerasimenko's coma system. The instrument will measure surface temperature, gas-production rates and relative abundances, and velocity and excitation temperatures of each species along with their spatial temporal variability. This software will use these measurements to improve the understanding of coma dynamics. The modeling tool solves the equation of motion of a dust particle, the energy balance equation of the dust particle, the continuity equation for the dust and gas flow, and the dust and gas mixture energy equation. By solving these equations numerically, the software calculates the temperature and velocity of gas and dust as a function of time for a given initial gas and dust production rate, and a dust characteristic parameter that measures the ability of a dust particle to adjust its velocity to the local gas velocity. The software is written in a modular manner, thereby allowing the addition of more dynamics equations as needed. All of the numerical algorithms are added in-house and no third-party libraries are used.
Consequence modeling using the fire dynamics simulator.
Ryder, Noah L; Sutula, Jason A; Schemel, Christopher F; Hamer, Andrew J; Van Brunt, Vincent
2004-11-11
The use of Computational Fluid Dynamics (CFD) and in particular Large Eddy Simulation (LES) codes to model fires provides an efficient tool for the prediction of large-scale effects that include plume characteristics, combustion product dispersion, and heat effects to adjacent objects. This paper illustrates the strengths of the Fire Dynamics Simulator (FDS), an LES code developed by the National Institute of Standards and Technology (NIST), through several small and large-scale validation runs and process safety applications. The paper presents two fire experiments--a small room fire and a large (15 m diameter) pool fire. The model results are compared to experimental data and demonstrate good agreement between the models and data. The validation work is then extended to demonstrate applicability to process safety concerns by detailing a model of a tank farm fire and a model of the ignition of a gaseous fuel in a confined space. In this simulation, a room was filled with propane, given time to disperse, and was then ignited. The model yields accurate results of the dispersion of the gas throughout the space. This information can be used to determine flammability and explosive limits in a space and can be used in subsequent models to determine the pressure and temperature waves that would result from an explosion. The model dispersion results were compared to an experiment performed by Factory Mutual. Using the above examples, this paper will demonstrate that FDS is ideally suited to build realistic models of process geometries in which large scale explosion and fire failure risks can be evaluated with several distinct advantages over more traditional CFD codes. Namely transient solutions to fire and explosion growth can be produced with less sophisticated hardware (lower cost) than needed for traditional CFD codes (PC type computer verses UNIX workstation) and can be solved for longer time histories (on the order of hundreds of seconds of computed time) with
OFFl Models: Novel Schema for Dynamical Modeling of Biological Systems
2016-01-01
Flow diagrams are a common tool used to help build and interpret models of dynamical systems, often in biological contexts such as consumer-resource models and similar compartmental models. Typically, their usage is intuitive and informal. Here, we present a formalized version of flow diagrams as a kind of weighted directed graph which follow a strict grammar, which translate into a system of ordinary differential equations (ODEs) by a single unambiguous rule, and which have an equivalent representation as a relational database. (We abbreviate this schema of “ODEs and formalized flow diagrams” as OFFL.) Drawing a diagram within this strict grammar encourages a mental discipline on the part of the modeler in which all dynamical processes of a system are thought of as interactions between dynamical species that draw parcels from one or more source species and deposit them into target species according to a set of transformation rules. From these rules, the net rate of change for each species can be derived. The modeling schema can therefore be understood as both an epistemic and practical heuristic for modeling, serving both as an organizational framework for the model building process and as a mechanism for deriving ODEs. All steps of the schema beyond the initial scientific (intuitive, creative) abstraction of natural observations into model variables are algorithmic and easily carried out by a computer, thus enabling the future development of a dedicated software implementation. Such tools would empower the modeler to consider significantly more complex models than practical limitations might have otherwise proscribed, since the modeling framework itself manages that complexity on the modeler’s behalf. In this report, we describe the chief motivations for OFFL, carefully outline its implementation, and utilize a range of classic examples from ecology and epidemiology to showcase its features. PMID:27270918
Models of the Dynamic Deformations of Polymers
NASA Astrophysics Data System (ADS)
Merzhievsky, Lev; Voronin, Mihail; Korchagina, Anna
2013-06-01
In the process of deformation under the influence of external loading polymeric mediums show the complicated behavior connected with features of their structure. For amorphous polymers distinguish three physical conditions - glasslike, highlyelastic and viscoplastic. To each of the listed conditions there corresponds to mikro - meso- and macrostructural mechanisms of irreversible deformation. In the report the review of results of construction of models for the description of dynamic and shock-wave deformation of the polymers which are based on developed authors representations about mechanisms of irreversible deformation is made. Models include the formulation of the equations of conservation laws, considering effect of a relaxation of shear stresses in the process of deformation. For closing of models the equations of states with nonspherical tensor of deformations and relation for time of a relaxation of shear stresses are constructed. With using of the formulated models a number of problems of dynamic and shock wave deformations has been solved. The results are compared with corresponding experimental date. Development of the used approach are in summary discussed. To taking into account memory and fractal properties of real polymers is supposed of derivatives and integrals of a fractional order to use. Examples of constitutive equations with derivatives of a fractional order are presented. This work is supported by the Integration project of the Siberian Branch of the Russian Academy of Science 64 and grant RFBR 12-01-00726.
The Dynamical Sine-Gordon Model
NASA Astrophysics Data System (ADS)
Hairer, Martin; Shen, Hao
2016-02-01
We introduce the dynamical sine-Gordon equation in two space dimensions with parameter {β}, which is the natural dynamic associated to the usual quantum sine-Gordon model. It is shown that when {β2 in (0, 16π/3)} the Wick renormalised equation is well-posed. In the regime {β2 in (0, 4π)}, the Da Prato-Debussche method [J Funct Anal 196(1):180-210, 2002; Ann Probab 31(4):1900-1916, 2003] applies, while for {β2 in [4π, 16π/3)}, the solution theory is provided via the theory of regularity structures [Hairer, Invent Math 198(2):269-504, 2014]. We also show that this model arises naturally from a class of {2 + 1} -dimensional equilibrium interface fluctuation models with periodic nonlinearities. The main mathematical difficulty arises in the construction of the model for the associated regularity structure where the role of the noise is played by a non-Gaussian random distribution similar to the complex multiplicative Gaussian chaos recently analysed in Lacoin et al. [Commun Math Phys 337(2):569-632, 2015].
Stochastic dynamic models and Chebyshev splines
Fan, Ruzong; Zhu, Bin; Wang, Yuedong
2015-01-01
In this article, we establish a connection between a stochastic dynamic model (SDM) driven by a linear stochastic differential equation (SDE) and a Chebyshev spline, which enables researchers to borrow strength across fields both theoretically and numerically. We construct a differential operator for the penalty function and develop a reproducing kernel Hilbert space (RKHS) induced by the SDM and the Chebyshev spline. The general form of the linear SDE allows us to extend the well-known connection between an integrated Brownian motion and a polynomial spline to a connection between more complex diffusion processes and Chebyshev splines. One interesting special case is connection between an integrated Ornstein–Uhlenbeck process and an exponential spline. We use two real data sets to illustrate the integrated Ornstein–Uhlenbeck process model and exponential spline model and show their estimates are almost identical. PMID:26045632
Model-Free Dual Heuristic Dynamic Programming.
Ni, Zhen; He, Haibo; Zhong, Xiangnan; Prokhorov, Danil V
2015-08-01
Model-based dual heuristic dynamic programming (MB-DHP) is a popular approach in approximating optimal solutions in control problems. Yet, it usually requires offline training for the model network, and thus resulting in extra computational cost. In this brief, we propose a model-free DHP (MF-DHP) design based on finite-difference technique. In particular, we adopt multilayer perceptron with one hidden layer for both the action and the critic networks design, and use delayed objective functions to train both the action and the critic networks online over time. We test both the MF-DHP and MB-DHP approaches with a discrete time example and a continuous time example under the same parameter settings. Our simulation results demonstrate that the MF-DHP approach can obtain a control performance competitive with that of the traditional MB-DHP approach while requiring less computational resources. PMID:25955997
Dynamic survival models with spatial frailty.
Bastos, Leonardo Soares; Gamerman, Dani
2006-12-01
In many survival studies, covariates effects are time-varying and there is presence of spatial effects. Dynamic models can be used to cope with the variations of the effects and spatial components are introduced to handle spatial variation. This paper proposes a methodology to simultaneously introduce these components into the model. A number of specifications for the spatial components are considered. Estimation is performed via a Bayesian approach through Markov chain Monte Carlo methods. Models are compared to assess relevance of their components. Analysis of a real data set is performed, showing the relevance of both time-varying covariate effects and spatial components. Extensions to the methodology are proposed along with concluding remarks. PMID:17031498
Simulating aggregate dynamics in ocean biogeochemical models
NASA Astrophysics Data System (ADS)
Jackson, George A.; Burd, Adrian B.
2015-04-01
The dynamics of elements in the water column is complex, depending on multiple biological and physical processes operating at very different physical scales. Coagulation of particulate material is important for transforming particles and moving them in the water column. Mechanistic models of coagulation processes provide a means to predict these processes, help interpret observations, and provide insight into the processes occurring. However, most model applications have focused on describing simple marine systems and mechanisms. We argue that further model development, in close collaboration with field and experimental scientists, is required in order to extend the models to describe the large-scale elemental distributions and interactions being studied as part of GEOTRACES. Models that provide a fundamental description of trace element-particle interactions are required as are experimental tests of the mechanisms involved and the predictions arising from models. However, a comparison between simple and complicated models of aggregation and trace metal provides a means for understanding the implications of simplifying assumptions and providing guidance as to which simplifications are needed.
Flight Dynamic Model Exchange using XML
NASA Technical Reports Server (NTRS)
Jackson, E. Bruce; Hildreth, Bruce L.
2002-01-01
The AIAA Modeling and Simulation Technical Committee has worked for several years to develop a standard by which the information needed to develop physics-based models of aircraft can be specified. The purpose of this standard is to provide a well-defined set of information, definitions, data tables and axis systems so that cooperating organizations can transfer a model from one simulation facility to another with maximum efficiency. This paper proposes using an application of the eXtensible Markup Language (XML) to implement the AIAA simulation standard. The motivation and justification for using a standard such as XML is discussed. Necessary data elements to be supported are outlined. An example of an aerodynamic model as an XML file is given. This example includes definition of independent and dependent variables for function tables, definition of key variables used to define the model, and axis systems used. The final steps necessary for implementation of the standard are presented. Software to take an XML-defined model and import/export it to/from a given simulation facility is discussed, but not demonstrated. That would be the next step in final implementation of standards for physics-based aircraft dynamic models.
Dynamical Vertex Approximation for the Hubbard Model
NASA Astrophysics Data System (ADS)
Toschi, Alessandro
A full understanding of correlated electron systems in the physically relevant situations of three and two dimensions represents a challenge for the contemporary condensed matter theory. However, in the last years considerable progress has been achieved by means of increasingly more powerful quantum many-body algorithms, applied to the basic model for correlated electrons, the Hubbard Hamiltonian. Here, I will review the physics emerging from studies performed with the dynamical vertex approximation, which includes diagrammatic corrections to the local description of the dynamical mean field theory (DMFT). In particular, I will first discuss the phase diagram in three dimensions with a special focus on the commensurate and incommensurate magnetic phases, their (quantum) critical properties, and the impact of fluctuations on electronic lifetimes and spectral functions. In two dimensions, the effects of non-local fluctuations beyond DMFT grow enormously, determining the appearance of a low-temperature insulating behavior for all values of the interaction in the unfrustrated model: Here the prototypical features of the Mott-Hubbard metal-insulator transition, as well as the existence of magnetically ordered phases, are completely overwhelmed by antiferromagnetic fluctuations of exponentially large extension, in accordance with the Mermin-Wagner theorem. Eventually, by a fluctuation diagnostics analysis of cluster DMFT self-energies, the same magnetic fluctuations are identified as responsible for the pseudogap regime in the holed-doped frustrated case, with important implications for the theoretical modeling of the cuprate physics.
Modeling of dynamic bipolar plasma sheaths
NASA Astrophysics Data System (ADS)
Grossmann, J. M.; Swanekamp, S. B.; Ottinger, P. F.
1992-01-01
The behavior of a one-dimensional plasma sheath is described in regimes where the sheath is not in equilibrium because it carries current densities that are either time dependent, or larger than the bipolar Child-Langmuir level determined from the injected ion flux. Earlier models of dynamic bipolar sheaths assumed that ions and electrons evolve in a series of quasiequilibria. In addition, sheath growth was described by the equation Zen0ẋs=‖ ji‖-Zen0u0, where ẋs is the velocity of the sheath edge, ji is the ion current density, n0u0 is the injected ion flux density, and Ze is the ion charge. In this paper, a generalization of the bipolar electron-to-ion current density ratio formula is derived to study regimes where ions are not in equilibrium. A generalization of the above sheath growth equation is also developed, which is consistent with the ion continuity equation and which reveals new physics of sheath behavior associated with the emitted electrons and their evolution. Based on these findings, two new models of dynamic bipolar sheaths are developed. Larger sheath sizes and potentials than those of earlier models are found. In certain regimes, explosive sheath growth is predicted.
Dynamic displays of chemical process flowsheet models
Aull, J.E.
1996-11-01
This paper describes the algorithms used in constructing dynamic graphical displays of a process flowsheet. Movies are created which portray changes in the process over time using animation in the flowsheet such as individual streams that take on a color keyed to the current flow rate, tank levels that visibly rise and fall and {open_quotes}gauges{close_quotes} that move to display parameter values. Movies of this type can be a valuable tool for visualizing, analyzing, and communicating the behavior of a process model. This paper describes the algorithms used in constructing displays of this kind for dynamic models using the SPEEDUP{trademark} modeling package and the GMS{trademark} graphics package. It also tells how data is exported from the SPEEDUP{trademark} package to GMS{trademark} and describes how a user environment for running movies and editing flowsheets is set up. The algorithms are general enough to be applied to other processes and graphics packages. In fact the techniques described here can be used to create movies of any time-dependent data.
Numerical modeling of bubble dynamics in magmas
NASA Astrophysics Data System (ADS)
Huber, Christian; Su, Yanqing; Parmigiani, Andrea
2014-05-01
Understanding the complex non-linear physics that governs volcanic eruptions is contingent on our ability to characterize the dynamics of bubbles and its effect on the ascending magma. The exsolution and migration of bubbles has also a great impact on the heat and mass transport in and out of magma bodies stored at shallow depths in the crust. Multiphase systems like magmas are by definition heterogeneous at small scales. Although mixture theory or homogenization methods are convenient to represent multiphase systems as a homogeneous equivalent media, these approaches do not inform us on possible feedbacks at the pore-scale and can be significantly misleading. In this presentation, we discuss the development and application of bubble-scale multiphase flow modeling to address the following questions : How do bubbles impact heat and mass transport in magma chambers ? How efficient are chemical exchanges between the melt and bubbles during magma decompression? What is the role of hydrodynamic interactions on the deformation of bubbles while the magma is sheared? Addressing these questions requires powerful numerical methods that accurately model the balance between viscous, capillary and pressure stresses. We discuss how these bubble-scale models can provide important constraints on the dynamics of magmas stored at shallow depth or ascending to the surface during an eruption.
Mathematical modeling of infectious disease dynamics
Siettos, Constantinos I.; Russo, Lucia
2013-01-01
Over the last years, an intensive worldwide effort is speeding up the developments in the establishment of a global surveillance network for combating pandemics of emergent and re-emergent infectious diseases. Scientists from different fields extending from medicine and molecular biology to computer science and applied mathematics have teamed up for rapid assessment of potentially urgent situations. Toward this aim mathematical modeling plays an important role in efforts that focus on predicting, assessing, and controlling potential outbreaks. To better understand and model the contagious dynamics the impact of numerous variables ranging from the micro host–pathogen level to host-to-host interactions, as well as prevailing ecological, social, economic, and demographic factors across the globe have to be analyzed and thoroughly studied. Here, we present and discuss the main approaches that are used for the surveillance and modeling of infectious disease dynamics. We present the basic concepts underpinning their implementation and practice and for each category we give an annotated list of representative works. PMID:23552814
Aerodynamics modeling of towed-cable dynamics
Kang, S.W.; Latorre, V.R.
1991-01-17
The dynamics of a cable/drogue system being towed by an orbiting aircraft has been investigated as a part of an LTWA project for the Naval Air Systems Command. We present here a status report on the tasks performed under Phase 1. We have accomplished the following tasks under Phase 1: A literature survey on the towed-cable motion problem has been conducted. While both static (steady-state) and dynamic (transient) analyses exist in the literature, no single, comprehensive analysis exists that directly addresses the present problem. However, the survey also reveals that, when judiciously applied, these past analyses can serve as useful building blocks for approaching the present problem. A numerical model that addresses several aspects of the towed-cable dynamic problem has been adapted from a Canadian underwater code for the present aerodynamic situation. This modified code, called TOWDYN, analyzes the effects of gravity, tension, aerodynamic drag, and wind. Preliminary results from this code demonstrate that the wind effects alone CAN generate the drogue oscillation behavior, i.e., the yo-yo'' phenomenon. This code also will serve as a benchmark code for checking the accuracy of a more general and complete R D'' model code. We have initiated efforts to develop a general R D model supercomputer code that also takes into account other physical factors, such as induced oscillations and bending stiffness. This general code will be able to evaluate the relative impacts of the various physical parameters, which may become important under certain conditions. This R D code will also enable development of a simpler operational code that can be used by the Naval Air personnel in the field.
Computational fluid dynamics modelling in cardiovascular medicine
Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P
2016-01-01
This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards ‘digital patient’ or ‘virtual physiological human’ representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. PMID:26512019
Computational fluid dynamics modelling in cardiovascular medicine.
Morris, Paul D; Narracott, Andrew; von Tengg-Kobligk, Hendrik; Silva Soto, Daniel Alejandro; Hsiao, Sarah; Lungu, Angela; Evans, Paul; Bressloff, Neil W; Lawford, Patricia V; Hose, D Rodney; Gunn, Julian P
2016-01-01
This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges. PMID:26512019
Modeling coupled avulsion and earthquake timescale dynamics
NASA Astrophysics Data System (ADS)
Reitz, M. D.; Steckler, M. S.; Paola, C.; Seeber, L.
2014-12-01
River avulsions and earthquakes can be hazardous events, and many researchers work to better understand and predict their timescales. Improvements in the understanding of the intrinsic processes of deposition and strain accumulation that lead to these events have resulted in better constraints on the timescales of each process individually. There are however several mechanisms by which these two systems may plausibly become linked. River deposition and avulsion can affect the stress on underlying faults through differential loading by sediment or water. Conversely, earthquakes can affect river avulsion patterns through altering the topography. These interactions may alter the event recurrence timescales, but this dynamic has not yet been explored. We present results of a simple numerical model, in which two systems have intrinsic rates of approach to failure thresholds, but the state of one system contributes to the other's approach to failure through coupling functions. The model is first explored for the simplest case of two linear approaches to failure, and linearly proportional coupling terms. Intriguing coupling dynamics emerge: the system settles into cycles of repeating earthquake and avulsion timescales, which are approached at an exponential decay rate that depends on the coupling terms. The ratio of the number of events of each type and the timescale values also depend on the coupling coefficients and the threshold values. We then adapt the model to a more complex and realistic scenario, in which a river avulses between either side of a fault, with parameters corresponding to the Brahmaputra River / Dauki fault system in Bangladesh. Here the tectonic activity alters the topography by gradually subsiding during the interseismic time, and abruptly increasing during an earthquake. The river strengthens the fault by sediment loading when in one path, and weakens it when in the other. We show this coupling can significantly affect earthquake and avulsion
Modeling the dynamical systems on experimental data
Janson, N.B.; Anishchenko, V.S.
1996-06-01
An attempt is made in the work to create qualitative models of some real biological systems, i.e., isolated frog{close_quote}s heart, a human{close_quote}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{close_quote} attractors. The result of the work are the systems of ordinary differential equations which approximately describe the dynamics of the systems under investigation. {copyright} {ital 1996 American Institute of Physics.}
Dynamic Compaction Modeling of Porous Silica Powder
NASA Astrophysics Data System (ADS)
Borg, John P.; Schwalbe, Larry; Cogar, John; Chapman, D. J.; Tsembelis, K.; Ward, Aaron; Lloyd, Andrew
2006-07-01
A computational analysis of the dynamic compaction of porous silica is presented and compared with experimental measurements. The experiments were conducted at Cambridge University's one-dimensional flyer plate facility. The experiments shock loaded samples of silica dust of various initial porous densities up to a pressure of 2.25 GPa. The computational simulations utilized a linear Us-Up Hugoniot. The compaction events were modeled with CTH, a 3D Eulerian hydrocode developed at Sandia National Laboratory. Simulated pressures at two test locations are presented and compared with measurements.
Scalar model for frictional precursors dynamics.
Taloni, Alessandro; Benassi, Andrea; Sandfeld, Stefan; Zapperi, Stefano
2015-01-01
Recent experiments indicate that frictional sliding occurs by nucleation of detachment fronts at the contact interface that may appear well before the onset of global sliding. This intriguing precursory activity is not accounted for by traditional friction theories but is extremely important for friction dominated geophysical phenomena as earthquakes, landslides or avalanches. Here we simulate the onset of slip of a three dimensional elastic body resting on a surface and show that experimentally observed frictional precursors depend in a complex non-universal way on the sample geometry and loading conditions. Our model satisfies Archard's law and Amontons' first and second laws, reproducing with remarkable precision the real contact area dynamics, the precursors' envelope dynamics prior to sliding, and the normal and shear internal stress distributions close to the interfacial surface. Moreover, it allows to assess which features can be attributed to the elastic equilibrium, and which are attributed to the out-of-equilibrium dynamics, suggesting that precursory activity is an intrinsically quasi-static physical process. A direct calculation of the evolution of the Coulomb stress before and during precursors nucleation shows large variations across the sample, explaining why earthquake forecasting methods based only on accumulated slip and Coulomb stress monitoring are often ineffective. PMID:25640079
Unsteady aerodynamics modeling for flight dynamics application
NASA Astrophysics Data System (ADS)
Wang, Qing; He, Kai-Feng; Qian, Wei-Qi; Zhang, Tian-Jiao; Cheng, Yan-Qing; Wu, Kai-Yuan
2012-02-01
In view of engineering application, it is practicable to decompose the aerodynamics into three components: the static aerodynamics, the aerodynamic increment due to steady rotations, and the aerodynamic increment due to unsteady separated and vortical flow. The first and the second components can be presented in conventional forms, while the third is described using a one-order differential equation and a radial-basis-function (RBF) network. For an aircraft configuration, the mathematical models of 6-component aerodynamic coefficients are set up from the wind tunnel test data of pitch, yaw, roll, and coupled yawroll large-amplitude oscillations. The flight dynamics of an aircraft is studied by the bifurcation analysis technique in the case of quasi-steady aerodynamics and unsteady aerodynamics, respectively. The results show that: (1) unsteady aerodynamics has no effect upon the existence of trim points, but affects their stability; (2) unsteady aerodynamics has great effects upon the existence, stability, and amplitudes of periodic solutions; and (3) unsteady aerodynamics changes the stable regions of trim points obviously. Furthermore, the dynamic responses of the aircraft to elevator deflections are inspected. It is shown that the unsteady aerodynamics is beneficial to dynamic stability for the present aircraft. Finally, the effects of unsteady aerodynamics on the post-stall maneuverability are analyzed by numerical simulation.
Scalar model for frictional precursors dynamics
Taloni, Alessandro; Benassi, Andrea; Sandfeld, Stefan; Zapperi, Stefano
2015-01-01
Recent experiments indicate that frictional sliding occurs by nucleation of detachment fronts at the contact interface that may appear well before the onset of global sliding. This intriguing precursory activity is not accounted for by traditional friction theories but is extremely important for friction dominated geophysical phenomena as earthquakes, landslides or avalanches. Here we simulate the onset of slip of a three dimensional elastic body resting on a surface and show that experimentally observed frictional precursors depend in a complex non-universal way on the sample geometry and loading conditions. Our model satisfies Archard's law and Amontons' first and second laws, reproducing with remarkable precision the real contact area dynamics, the precursors' envelope dynamics prior to sliding, and the normal and shear internal stress distributions close to the interfacial surface. Moreover, it allows to assess which features can be attributed to the elastic equilibrium, and which are attributed to the out-of-equilibrium dynamics, suggesting that precursory activity is an intrinsically quasi-static physical process. A direct calculation of the evolution of the Coulomb stress before and during precursors nucleation shows large variations across the sample, explaining why earthquake forecasting methods based only on accumulated slip and Coulomb stress monitoring are often ineffective. PMID:25640079
Computational social dynamic modeling of group recruitment.
Berry, Nina M.; Lee, Marinna; Pickett, Marc; Turnley, Jessica Glicken; Smrcka, Julianne D.; Ko, Teresa H.; Moy, Timothy David; Wu, Benjamin C.
2004-01-01
The Seldon software toolkit combines concepts from agent-based modeling and social science to create a computationally social dynamic model for group recruitment. The underlying recruitment model is based on a unique three-level hybrid agent-based architecture that contains simple agents (level one), abstract agents (level two), and cognitive agents (level three). This uniqueness of this architecture begins with abstract agents that permit the model to include social concepts (gang) or institutional concepts (school) into a typical software simulation environment. The future addition of cognitive agents to the recruitment model will provide a unique entity that does not exist in any agent-based modeling toolkits to date. We use social networks to provide an integrated mesh within and between the different levels. This Java based toolkit is used to analyze different social concepts based on initialization input from the user. The input alters a set of parameters used to influence the values associated with the simple agents, abstract agents, and the interactions (simple agent-simple agent or simple agent-abstract agent) between these entities. The results of phase-1 Seldon toolkit provide insight into how certain social concepts apply to different scenario development for inner city gang recruitment.
A dynamic localization model with stochastic backscatter
NASA Astrophysics Data System (ADS)
Carati, Daniele; Ghosal, Sandip
1994-12-01
The modeling of subgrid scales in large-eddy simulation (LES) has been rationalized by the introduction of the dynamic localization procedure. This method allows one to compute rather than prescribe the unknown coefficients in the subgrid-scale model. Formally, the LES equations are supposed to be obtained by applying to the Navier-Stokes equations a 'grid filter' operation. Though the subgrid stress itself is unknown, an identity between subgrid stresses generated by different filters has been derived. Although preliminary tests of the Dynamic Localization Model (DLM) with k-equation have been satisfactory, the use of a negative eddy viscosity to describe backscatter is probably a crude representation of the physics of reverse transfer of energy. Indeed, the model is fully deterministic. Knowing the filtered velocity field and the subgrid-scale energy, the subgrid stress is automatically determined. We know that the LES equations cannot be fully deterministic since the small scales are not resolved. This stems from an important distinction between equilibrium hydrodynamics and turbulence. In equilibrium hydrodynamics, the molecular motions are also not resolved. However, there is a clear separation of scale between these unresolved motions and the relevant hydrodynamic scales. The result of molecular motions can then be separated into an average effect (the molecular viscosity) and some fluctuations. Due to the large number of molecules present in a box with size of the order of the hydrodynamic scale, the ratio between fluctuations and the average effect should be very small (as a result of the 'law of large numbers'). For that reason, the hydrodynamic balance equations are usually purely deterministic. In turbulence, however, there is no clear separation of scale between small and large eddies. In that case, the fluctuations around a deterministic eddy viscosity term could be significant. An eddy noise would then appear through a stochastic term in the subgrid
Modelling of snow avalanche dynamics: influence of model parameters
NASA Astrophysics Data System (ADS)
Bozhinskiy, A. N.
The three-parameter hydraulic model of snow avalanche dynamics including the coefficients of dry and turbulent friction and the coefficient of new-snow-mass entrainment was investigated. The 'Domestic' avalanche site in Elbrus region, Caucasus, Russia, was chosen as the model avalanche range. According to the model, the fixed avalanche run-out can be achieved with various combinations of model parameters. At the fixed value of the coefficient of entrainment me, we have a curve on a plane of the coefficients of dry and turbulent friction. It was found that the family of curves (me is a parameter) are crossed at the single point. The value of the coefficient of turbulent friction at the cross-point remained practically constant for the maximum and average avalanche run-outs. The conclusions obtained are confirmed by the results of modelling for six arbitrarily chosen avalanche sites: three in the Khibiny mountains, Kola Peninsula, Russia, two in the Elbrus region and one idealized site with an exponential longitudinal profile. The dependences of run-out on the coefficient of dry friction are constructed for all the investigated avalanche sites. The results are important for the statistical simulation of avalanche dynamics since they suggest the possibility of using only one random model parameter, namely, the coefficient of dry friction, in the model. The histograms and distribution functions of the coefficient of dry friction are constructed and presented for avalanche sites Nos 22 and 43 (Khibiny mountains) and 'Domestic', with the available series of field data.
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 Cu_{40}Zr_{51}Al_{9} 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 T_{x} ~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 (T_{m} ~ 900K), and the crossover temperature is roughly twice of the glass-transition temperature (T_{g}). Below T_{x}, 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 T_{x} 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.
The power of (Mis)perception: Rethinking suicide contagion in youth friendship networks.
Zimmerman, Gregory M; Rees, Carter; Posick, Chad; Zimmerman, Lori A
2016-05-01
Suicide is a leading cause of death among youth. In the wake of peer suicide, youth are vulnerable to suicide contagion. But, questions remain about the mechanisms through which suicide spreads and the accuracy of youths' estimates of friends' suicidal behaviors. This study addresses these questions within school-aged youths' friendship networks. Social network data were drawn from two schools in the National Longitudinal Study of Adolescent to Adult Health, from which 2180 youth in grades 7-12 nominated up to ten friends. A measure of "perceived" friends' attempted suicide was constructed based on respondents' reports of their friends' attempted suicide. This measure was broader than a "true" measure of friends' attempted suicide, constructed from self-reports of nominated friends who attended respondents' schools. Sociograms graphically represented the accuracy with which suicide attempters estimated friends' suicide attempts. Results from cross-tabulation with Chi-square analysis indicated that approximately 4% of youth (88/2180) attempted suicide, and these youth disproportionately misperceived (predominantly overestimated) friends' suicidal behaviors, compared to non-suicide-attempters. Penalized logistic regression models indicated that friends' self-reported attempted suicide was unrelated to respondent attempted suicide. But, the odds of respondent attempted suicide were 2.54 times higher (95% CI, 1.06-6.10) among youth who accurately perceived friends' attempted suicide, and 5.40 times higher (95% CI, 3.34-8.77) among youth who overestimated friends' attempted suicide. The results suggest that at-risk youth overestimate their friends' suicidal behaviors, which exacerbates their own risk of suicidal behavior. Methodologically, this suggests that a continued collaboration among network scientists, suicide researchers, and medical providers is necessary to further examine the mechanisms surrounding this phenomenon. Practically, it is important to screen at
Driven dynamics of simplified tribological models
NASA Astrophysics Data System (ADS)
Vanossi, A.; Braun, O. M.
2007-08-01
Over the last decade, remarkable developments in nanotechnology, notably the use of atomic and friction force microscopes (AFM/FFM), the surface-force apparatus (SFA) and the quartz-crystal microbalance (QCM), have provided the possibility to build experimental devices able to perform analysis on well-characterized materials at the nano- and microscale. Simultaneously, tremendous advances in computing hardware and methodology (molecular dynamics techniques and ab initio calculations) have dramatically increased the ability of theoreticians to simulate tribological processes, supplying very detailed information on the atomic scale for realistic sliding systems. This acceleration in experiments and computations, leading often to very detailed yet complex data, has deeply stimulated the search, rediscovery and implementation of simpler mathematical models such as the generalized Frenkel-Kontorova and Tomlinson models, capable of describing and interpreting, in a more immediate way, the essential physics involved in nonlinear sliding phenomena.
Microscopic model for ultrafast remagnetization dynamics.
Chimata, Raghuveer; Bergman, Anders; Bergqvist, Lars; Sanyal, Biplab; Eriksson, Olle
2012-10-12
In this Letter, we provide a microscopic model for the ultrafast remagnetization of atomic moments already quenched above the Stoner-Curie temperature by a strong laser fluence. Combining first-principles density functional theory, atomistic spin dynamics utilizing the Landau-Lifshitz-Gilbert equation, and a three-temperature model, we analyze the temporal evolution of atomic moments as well as the macroscopic magnetization of bcc Fe and hcp Co covering a broad time scale, ranging from femtoseconds to picoseconds. Our simulations show a variety of complex temporal behavior of the magnetic properties resulting from an interplay between electron, spin, and lattice subsystems, which causes an intricate time evolution of the atomic moment, where longitudinal and transversal fluctuations result in a macrospin moment that evolves highly nonmonotonically. PMID:23102359
A Simple General Model of Evolutionary Dynamics
NASA Astrophysics Data System (ADS)
Thurner, Stefan
Evolution is a process in which some variations that emerge within a population (of, e.g., biological species or industrial goods) get selected, survive, and proliferate, whereas others vanish. Survival probability, proliferation, or production rates are associated with the "fitness" of a particular variation. We argue that the notion of fitness is an a posteriori concept in the sense that one can assign higher fitness to species or goods that survive but one can generally not derive or predict fitness per se. Whereas proliferation rates can be measured, fitness landscapes, that is, the inter-dependence of proliferation rates, cannot. For this reason we think that in a physical theory of evolution such notions should be avoided. Here we review a recent quantitative formulation of evolutionary dynamics that provides a framework for the co-evolution of species and their fitness landscapes (Thurner et al., 2010, Physica A 389, 747; Thurner et al., 2010, New J. Phys. 12, 075029; Klimek et al., 2009, Phys. Rev. E 82, 011901 (2010). The corresponding model leads to a generic evolutionary dynamics characterized by phases of relative stability in terms of diversity, followed by phases of massive restructuring. These dynamical modes can be interpreted as punctuated equilibria in biology, or Schumpeterian business cycles (Schumpeter, 1939, Business Cycles, McGraw-Hill, London) in economics. We show that phase transitions that separate phases of high and low diversity can be approximated surprisingly well by mean-field methods. We demonstrate that the mathematical framework is suited to understand systemic properties of evolutionary systems, such as their proneness to collapse, or their potential for diversification. The framework suggests that evolutionary processes are naturally linked to self-organized criticality and to properties of production matrices, such as their eigenvalue spectra. Even though the model is phrased in general terms it is also practical in the sense
Dynamic causal models and autopoietic systems.
David, Olivier
2007-01-01
Dynamic Causal Modelling (DCM) and the theory of autopoietic systems are two important conceptual frameworks. In this review, we suggest that they can be combined to answer important questions about self-organising systems like the brain. DCM has been developed recently by the neuroimaging community to explain, using biophysical models, the non-invasive brain imaging data are caused by neural processes. It allows one to ask mechanistic questions about the implementation of cerebral processes. In DCM the parameters of biophysical models are estimated from measured data and the evidence for each model is evaluated. This enables one to test different functional hypotheses (i.e., models) for a given data set. Autopoiesis and related formal theories of biological systems as autonomous machines represent a body of concepts with many successful applications. However, autopoiesis has remained largely theoretical and has not penetrated the empiricism of cognitive neuroscience. In this review, we try to show the connections that exist between DCM and autopoiesis. In particular, we propose a simple modification to standard formulations of DCM that includes autonomous processes. The idea is to exploit the machinery of the system identification of DCMs in neuroimaging to test the face validity of the autopoietic theory applied to neural subsystems. We illustrate the theoretical concepts and their implications for interpreting electroencephalographic signals acquired during amygdala stimulation in an epileptic patient. The results suggest that DCM represents a relevant biophysical approach to brain functional organisation, with a potential that is yet to be fully evaluated. PMID:18575681
Dynamic Models for Templated Viral Capsid Assembly
NASA Astrophysics Data System (ADS)
Hagan, Michael
2008-03-01
The replication of many viruses with single-stranded genomes requires the simultaneous assembly of an ordered protein shell, or capsid, and encapsidation of the genome. In this talk, I will present coarse-grained computational and theoretical models that describe the assembly of viral capsid proteins around interior cores, such as polymers and rigid spheres. These models are motivated by two recently developed experimental model systems in which viral proteins dynamically encapsidate inorganic nanoparticles and polyelectrolytes. Model predictions suggest that some forms of cooperative interactions between subunits and cores can dramatically enhance rates and robustness of assembly, as compared to the spontaneous assembly of subunits into empty capsids. For large core-subunit interactions, subunits adsorb onto a core en masse in a disordered manner, and then undergo a cooperative rearrangement into an ordered capsid structure. These assembly pathways are unlike any seen for empty capsids formation. While model predictions suggest that cooperative interactions between disparate assembling components can overcome some limitations of spontaneous assembly, the complexity of multicomponent assembly introduces new forms of kinetic traps that can frustrate assembly, and hence introduces new limitations. These findings have implications for a mechanism in which viruses use interactions between proteins and genomic molecules to promote and control assembly, and thereby control the replication process.
Dynamic Elasticity Model of Resilin Biopolymers
NASA Astrophysics Data System (ADS)
Hu, Xiao; Duki, Solomon
2013-03-01
Resilin proteins are `super elastic rubbers' in the flight and jumping systems of most insects, and can extend and retract millions of times. Natural resilin exhibits high resilience (> 95%) under high-frequency conditions, and could be stretched to over 300% of its original length with a low elastic modulus of 0.1-3 MPa. However, insight into the underlying molecular mechanisms responsible for resilin elasticity remains undefined. We report on the dynamic structure transitions and functions of full length resilin from fruit fly (D. melanogaster CG15920) and its different functional domains. A dynamic computational model is proposed to explain the super elasticity and energy conversion mechanisms of resilin, providing important insight into structure-function relationships for resilins, as well as other elastomeric proteins. A strong beta-turn transition was experimentally identified in the full length resilin and its non-elastic domains (Exon III). Changes in periodic long-range order were demonstrated during this transition, induced either by thermal or mechanical inputs, to confirm the universality of proposed mechanism. Further, this model offers new options for designing protein-based biopolymers with tunable material applications.
Modeling quantum fluid dynamics at nonzero temperatures
Berloff, Natalia G.; Brachet, Marc; Proukakis, Nick P.
2014-01-01
The detailed understanding of the intricate dynamics of quantum fluids, in particular in the rapidly growing subfield of quantum turbulence which elucidates the evolution of a vortex tangle in a superfluid, requires an in-depth understanding of the role of finite temperature in such systems. The Landau two-fluid model is the most successful hydrodynamical theory of superfluid helium, but by the nature of the scale separations it cannot give an adequate description of the processes involving vortex dynamics and interactions. In our contribution we introduce a framework based on a nonlinear classical-field equation that is mathematically identical to the Landau model and provides a mechanism for severing and coalescence of vortex lines, so that the questions related to the behavior of quantized vortices can be addressed self-consistently. The correct equation of state as well as nonlocality of interactions that leads to the existence of the roton minimum can also be introduced in such description. We review and apply the ideas developed for finite-temperature description of weakly interacting Bose gases as possible extensions and numerical refinements of the proposed method. We apply this method to elucidate the behavior of the vortices during expansion and contraction following the change in applied pressure. We show that at low temperatures, during the contraction of the vortex core as the negative pressure grows back to positive values, the vortex line density grows through a mechanism of vortex multiplication. This mechanism is suppressed at high temperatures. PMID:24704874
Microscopic to Macroscopic Dynamical Models of Sociality
NASA Astrophysics Data System (ADS)
Solis Salas, Citlali; Woolley, Thomas; Pearce, Eiluned; Dunbar, Robin; Maini, Philip; Social; Evolutionary Neuroscience Research Group (Senrg) Collaboration
To help them survive, social animals, such as humans, need to share knowledge and responsibilities with other members of the species. The larger their social network, the bigger the pool of knowledge available to them. Since time is a limited resource, a way of optimising its use is meeting amongst individuals whilst fulfilling other necessities. In this sense it is useful to know how many, and how often, early humans could meet during a given period of time whilst performing other necessary tasks, such as food gathering. Using a simplified model of these dynamics, which comprehend encounter and memory, we aim at producing a lower-bound to the number of meetings hunter-gatherers could have during a year. We compare the stochastic agent-based model to its mean-field approximation and explore some of the features necessary for the difference between low population dynamics and its continuum limit. We observe an emergent property that could have an inference in the layered structure seen in each person's social organisation. This could give some insight into hunter-gatherer's lives and the development of the social layered structure we have today. With support from the Mexican Council for Science and Technology (CONACyT), the Public Education Secretariat (SEP), and the Mexican National Autonomous University's Foundation (Fundacion UNAM).
Modeling Insurgent Network Structure and Dynamics
NASA Astrophysics Data System (ADS)
Gabbay, Michael; Thirkill-Mackelprang, Ashley
2010-03-01
We present a methodology for mapping insurgent network structure based on their public rhetoric. Indicators of cooperative links between insurgent groups at both the leadership and rank-and-file levels are used, such as joint policy statements or joint operations claims. In addition, a targeting policy measure is constructed on the basis of insurgent targeting claims. Network diagrams which integrate these measures of insurgent cooperation and ideology are generated for different periods of the Iraqi and Afghan insurgencies. The network diagrams exhibit meaningful changes which track the evolution of the strategic environment faced by insurgent groups. Correlations between targeting policy and network structure indicate that insurgent targeting claims are aimed at establishing a group identity among the spectrum of rank-and-file insurgency supporters. A dynamical systems model of insurgent alliance formation and factionalism is presented which evolves the relationship between insurgent group dyads as a function of their ideological differences and their current relationships. The ability of the model to qualitatively and quantitatively capture insurgent network dynamics observed in the data is discussed.
Modeling habitat dynamics accounting for possible misclassification
Veran, Sophie; Kleiner, Kevin J.; Choquet, Remi; Collazo, Jaime; Nichols, James D.
2012-01-01
Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.
Dynamic models of lateritic bauxite formation
NASA Astrophysics Data System (ADS)
Zhukov, V. V.; Bogatyrev, B. A.
2012-09-01
2D dynamic models of bauxite formation in the weathering mantle covering denudation areas drained by river systems are discussed. The role of relief-forming factors (tectonic uplift, river erosion and denudation of drainage divides), the interrelation of hydrogeological and lithologic structure of the bauxitebearing weathering mantle, and the dynamics of zoning formation above and below groundwater level are described in the models. Creative and destructive epochs of lateritic bauxite formation differing in tectonic regime are distinguished. During the creative epochs, lateritic weathering develops against a background of decreasing denudation and an increase in areas of bauxite formation. The destructive epochs are characterized by intense denudation, cutting down the areas of lateritic bauxite formation and eventually leading to the complete removal of the weathering mantle. Different morphogenetic types and varieties of bauxite-bearing weathering mantles develop during creative and destructive epochs. The morphology of the weathering mantle sections at the deposits of Cenozoic lateritic bauxite in the present-day tropical zone of the Earth corresponds to the destructive epoch, which is characterized by declining areas of lateritic bauxite formation and will end with complete denudation of lateritic bauxite.
Multi-Scale Modeling of Magnetospheric Dynamics
NASA Technical Reports Server (NTRS)
Kuznetsova, M. M.; Hesse, M.; Toth, G.
2012-01-01
Magnetic reconnection is a key element in many phenomena in space plasma, e.g. Coronal mass Ejections, Magnetosphere substorms. One of the major challenges in modeling the dynamics of large-scale systems involving magnetic reconnection is to quantifY the interaction between global evolution of the magnetosphere and microphysical kinetic processes in diffusion regions near reconnection sites. Recent advances in small-scale kinetic modeling of magnetic reconnection significantly improved our understanding of physical mechanisms controlling the dissipation in the vicinity of the reconnection site in collisionless plasma. However the progress in studies of small-scale geometries was not very helpful for large scale simulations. Global magnetosphere simulations usually include non-ideal processes in terms of numerical dissipation and/or ad hoc anomalous resistivity. Comparative studies of magnetic reconnection in small scale geometries demonstrated that MHD simulations that included non-ideal processes in terms of a resistive term 11 J did not produce fast reconnection rates observed in kinetic simulations. In collisionless magnetospheric plasma, the primary mechanism controlling the dissipation in the vicinity of the reconnection site is nongyrotropic pressure effects with spatial scales comparable with the particle Larmor radius. We utilize the global MHD code BATSRUS and replace ad hoc parameters such as "critical current density" and "anomalous resistivity" with a physically motivated model of dissipation. The primary mechanism controlling the dissipation in the vicinity of the reconnection site in incorporated into MHD description in terms of non-gyrotropic corrections to the induction equation. We will demonstrate that kinetic nongyrotropic effects can significantly alter the global magnetosphere evolution. Our approach allowed for the first time to model loading/unloading cycle in response to steady southward IMF driving. The role of solar wind parameters and
Atypical viral dynamics from transport through popular places.
Manrique, Pedro D; Xu, Chen; Hui, Pak Ming; Johnson, Neil F
2016-08-01
The flux of visitors through popular places undoubtedly influences viral spreading-from H1N1 and Zika viruses spreading through physical spaces such as airports, to rumors and ideas spreading through online spaces such as chat rooms and social media. However, there is a lack of understanding of the types of viral dynamics that can result. Here we present a minimal dynamical model that focuses on the time-dependent interplay between the mobility through and the occupancy of such spaces. Our generic model permits analytic analysis while producing a rich diversity of infection profiles in terms of their shapes, durations, and intensities. The general features of these theoretical profiles compare well to real-world data of recent social contagion phenomena. PMID:27627314
Atypical viral dynamics from transport through popular places
NASA Astrophysics Data System (ADS)
Manrique, Pedro D.; Xu, Chen; Hui, Pak Ming; Johnson, Neil F.
2016-08-01
The flux of visitors through popular places undoubtedly influences viral spreading—from H1N1 and Zika viruses spreading through physical spaces such as airports, to rumors and ideas spreading through online spaces such as chat rooms and social media. However, there is a lack of understanding of the types of viral dynamics that can result. Here we present a minimal dynamical model that focuses on the time-dependent interplay between the mobility through and the occupancy of such spaces. Our generic model permits analytic analysis while producing a rich diversity of infection profiles in terms of their shapes, durations, and intensities. The general features of these theoretical profiles compare well to real-world data of recent social contagion phenomena.
Dynamic thermodiffusion model for binary liquid mixtures.
Eslamian, Morteza; Saghir, M Ziad
2009-07-01
Following the nonequilibrium thermodynamics approach, we develop a dynamic model to emulate thermo-diffusion process and propose expressions for estimating the thermal diffusion factor in binary nonassociating liquid mixtures. Here, we correlate the net heat of transport in thermodiffusion with parameters, such as the mixture temperature and pressure, the size and shape of the molecules, and mobility of the components, because the molecules have to become activated before they can move. Based on this interpretation, the net heat of transport of each component can be somehow related to the viscosity and the activation energy of viscous flow of the same component defined in Eyring's reaction-rate theory [S. Glasstone, K. J. Laidler, and H. Eyring, (McGraw-Hill, New York, 1941)]. This modeling approach is different from that of Haase and Kempers, in which thermodiffusion is considered as a function of the thermostatic properties of the mixture such as enthalpy. In simulating thermodiffusion, by correlating the net heat of transport with the activation energy of viscous flow, effects of the above mentioned parameters are accounted for, to some extent of course. The model developed here along with Haase-Kempers and Drickamer-Firoozabadi models linked with the Peng-Robinson equation of sate are evaluated against the experimental data for several recent nonassociating binary mixtures at various temperatures, pressures, and concentrations. Although the model prediction is still not perfect, the model is simple and easy to use, physically justified, and predicts the experimental data very good and much better than the existing models. PMID:19658691
Dynamic thermodiffusion model for binary liquid mixtures
NASA Astrophysics Data System (ADS)
Eslamian, Morteza; Saghir, M. Ziad
2009-07-01
Following the nonequilibrium thermodynamics approach, we develop a dynamic model to emulate thermo-diffusion process and propose expressions for estimating the thermal diffusion factor in binary nonassociating liquid mixtures. Here, we correlate the net heat of transport in thermodiffusion with parameters, such as the mixture temperature and pressure, the size and shape of the molecules, and mobility of the components, because the molecules have to become activated before they can move. Based on this interpretation, the net heat of transport of each component can be somehow related to the viscosity and the activation energy of viscous flow of the same component defined in Eyring’s reaction-rate theory [S. Glasstone, K. J. Laidler, and H. Eyring, The Theory of Rate Processes: The Kinetics of Chemical Reactions, Viscosity, Diffusion and Electrochemical Phenomena (McGraw-Hill, New York, 1941)]. This modeling approach is different from that of Haase and Kempers, in which thermodiffusion is considered as a function of the thermostatic properties of the mixture such as enthalpy. In simulating thermodiffusion, by correlating the net heat of transport with the activation energy of viscous flow, effects of the above mentioned parameters are accounted for, to some extent of course. The model developed here along with Haase-Kempers and Drickamer-Firoozabadi models linked with the Peng-Robinson equation of sate are evaluated against the experimental data for several recent nonassociating binary mixtures at various temperatures, pressures, and concentrations. Although the model prediction is still not perfect, the model is simple and easy to use, physically justified, and predicts the experimental data very good and much better than the existing models.
Dynamic hysteresis modeling including skin effect using diffusion equation model
NASA Astrophysics Data System (ADS)
Hamada, Souad; Louai, Fatima Zohra; Nait-Said, Nasreddine; Benabou, Abdelkader
2016-07-01
An improved dynamic hysteresis model is proposed for the prediction of hysteresis loop of electrical steel up to mean frequencies, taking into account the skin effect. In previous works, the analytical solution of the diffusion equation for low frequency (DELF) was coupled with the inverse static Jiles-Atherton (JA) model in order to represent the hysteresis behavior for a lamination. In the present paper, this approach is improved to ensure the reproducibility of measured hysteresis loops at mean frequency. The results of simulation are compared with the experimental ones. The selected results for frequencies 50 Hz, 100 Hz, 200 Hz and 400 Hz are presented and discussed.
Computational modeling of intraocular gas dynamics.
Noohi, P; Abdekhodaie, M J; Cheng, Y L
2015-01-01
The purpose of this study was to develop a computational model to simulate the dynamics of intraocular gas behavior in pneumatic retinopexy (PR) procedure. The presented model predicted intraocular gas volume at any time and determined the tolerance angle within which a patient can maneuver and still gas completely covers the tear(s). Computational fluid dynamics calculations were conducted to describe PR procedure. The geometrical model was constructed based on the rabbit and human eye dimensions. SF6 in the form of pure and diluted with air was considered as the injected gas. The presented results indicated that the composition of the injected gas affected the gas absorption rate and gas volume. After injection of pure SF6, the bubble expanded to 2.3 times of its initial volume during the first 23 h, but when diluted SF6 was used, no significant expansion was observed. Also, head positioning for the treatment of retinal tear influenced the rate of gas absorption. Moreover, the determined tolerance angle depended on the bubble and tear size. More bubble expansion and smaller retinal tear caused greater tolerance angle. For example, after 23 h, for the tear size of 2 mm the tolerance angle of using pure SF6 is 1.4 times more than that of using diluted SF6 with 80% air. Composition of the injected gas and conditions of the tear in PR may dramatically affect the gas absorption rate and gas volume. Quantifying these effects helps to predict the tolerance angle and improve treatment efficiency. PMID:26682529
Computational modeling of intraocular gas dynamics
NASA Astrophysics Data System (ADS)
Noohi, P.; Abdekhodaie, M. J.; Cheng, Y. L.
2015-12-01
The purpose of this study was to develop a computational model to simulate the dynamics of intraocular gas behavior in pneumatic retinopexy (PR) procedure. The presented model predicted intraocular gas volume at any time and determined the tolerance angle within which a patient can maneuver and still gas completely covers the tear(s). Computational fluid dynamics calculations were conducted to describe PR procedure. The geometrical model was constructed based on the rabbit and human eye dimensions. SF6 in the form of pure and diluted with air was considered as the injected gas. The presented results indicated that the composition of the injected gas affected the gas absorption rate and gas volume. After injection of pure SF6, the bubble expanded to 2.3 times of its initial volume during the first 23 h, but when diluted SF6 was used, no significant expansion was observed. Also, head positioning for the treatment of retinal tear influenced the rate of gas absorption. Moreover, the determined tolerance angle depended on the bubble and tear size. More bubble expansion and smaller retinal tear caused greater tolerance angle. For example, after 23 h, for the tear size of 2 mm the tolerance angle of using pure SF6 is 1.4 times more than that of using diluted SF6 with 80% air. Composition of the injected gas and conditions of the tear in PR may dramatically affect the gas absorption rate and gas volume. Quantifying these effects helps to predict the tolerance angle and improve treatment efficiency.
A dynamical model for mirror movements
NASA Astrophysics Data System (ADS)
Daffertshofer, A.; van den Berg, C.; Beek, P. J.
1999-07-01
In an experiment involving the unimanual performance of rhythmic movements about the elbow joint, mirror movements (MM) (i.e., unintended, associated movements) were observed in the arm not instructed to move. The amplitude of these movements was small relative to that of the intended movements (in the order of 0.5 to 5%). Complex patterns of relative phasing were observed between the intended movements and the MM that were characterized by the presence of higher harmonics in the oscillating units. The patterns in question depended on the frequency of the intended movements, which was varied from 0.5 to 3 Hz. At low frequencies, cases of both in- and anti-phase coordination were observed amidst various other instances of phase locking. MM were smaller in the anti-phase than in the in-phase coordination. At higher frequencies, the occurrence of in-phase coordination was most common while instances of anti-phase coordination were absent. To account for these properties, a dynamical model for the coordination between large-amplitude intended movements and small-amplitude MM was derived in the form of a model of nonlinearly coupled nonlinear oscillators with unequal amplitudes. The derived model was shown to correspond well with many quantitative and qualitative features of the observed dynamics of MM, including frequency locking, stable in-phase and anti-phase coordination, coordination-dependency of mirror movement amplitudes, and the presence of higher harmonics. The implications of the obtained experimental and analytical results and numerical parameter optimizations for the study of MM were discussed.
Behavioural Contagion Explains Group Cohesion in a Social Crustacean.
Broly, Pierre; Deneubourg, Jean-Louis
2015-06-01
In gregarious species, social interactions maintain group cohesion and the associated adaptive values of group living. The understanding of mechanisms leading to group cohesion is essential for understanding the collective dynamics of groups and the spatio-temporal distribution of organisms in environment. In this view, social aggregation in terrestrial isopods represents an interesting model due to its recurrence both in the field and in the laboratory. In this study, and under a perturbation context, we experimentally tested the stability of groups of woodlice according to group size and time spent in group. Our results indicate that the response to the disturbance of groups decreases with increases in these two variables. Models neglecting social effects cannot reproduce experimental data, attesting that cohesion of aggregation in terrestrial isopods is partly governed by a social effect. In particular, models involving calmed and excited individuals and a social transition between these two behavioural states more accurately reproduced our experimental data. Therefore, we concluded that group cohesion (and collective response to stimulus) in terrestrial isopods is governed by a transitory resting state under the influence of density of conspecifics and time spent in group. Lastly, we discuss the nature of direct or indirect interactions possibly implicated. PMID:26067565
Behavioural Contagion Explains Group Cohesion in a Social Crustacean
Broly, Pierre; Deneubourg, Jean-Louis
2015-01-01
In gregarious species, social interactions maintain group cohesion and the associated adaptive values of group living. The understanding of mechanisms leading to group cohesion is essential for understanding the collective dynamics of groups and the spatio-temporal distribution of organisms in environment. In this view, social aggregation in terrestrial isopods represents an interesting model due to its recurrence both in the field and in the laboratory. In this study, and under a perturbation context, we experimentally tested the stability of groups of woodlice according to group size and time spent in group. Our results indicate that the response to the disturbance of groups decreases with increases in these two variables. Models neglecting social effects cannot reproduce experimental data, attesting that cohesion of aggregation in terrestrial isopods is partly governed by a social effect. In particular, models involving calmed and excited individuals and a social transition between these two behavioural states more accurately reproduced our experimental data. Therefore, we concluded that group cohesion (and collective response to stimulus) in terrestrial isopods is governed by a transitory resting state under the influence of density of conspecifics and time spent in group. Lastly, we discuss the nature of direct or indirect interactions possibly implicated. PMID:26067565
Two numerical models for landslide dynamic analysis
NASA Astrophysics Data System (ADS)
Hungr, Oldrich; McDougall, Scott
2009-05-01
Two microcomputer-based numerical models (Dynamic ANalysis (DAN) and three-dimensional model DAN (DAN3D)) have been developed and extensively used for analysis of landslide runout, specifically for the purposes of practical landslide hazard and risk assessment. The theoretical basis of both models is a system of depth-averaged governing equations derived from the principles of continuum mechanics. Original features developed specifically during this work include: an open rheological kernel; explicit use of tangential strain to determine the tangential stress state within the flowing sheet, which is both more realistic and beneficial to the stability of the model; orientation of principal tangential stresses parallel with the direction of motion; inclusion of the centripetal forces corresponding to the true curvature of the path in the motion direction and; the use of very simple and highly efficient free surface interpolation methods. Both models yield similar results when applied to the same sets of input data. Both algorithms are designed to work within the semi-empirical framework of the "equivalent fluid" approach. This approach requires selection of material rheology and calibration of input parameters through back-analysis of real events. Although approximate, it facilitates simple and efficient operation while accounting for the most important characteristics of extremely rapid landslides. The two models have been verified against several controlled laboratory experiments with known physical basis. A large number of back-analyses of real landslides of various types have also been carried out. One example is presented. Calibration patterns are emerging, which give a promise of predictive capability.
Bio-Inspired Neural Model for Learning Dynamic Models
NASA Technical Reports Server (NTRS)
Duong, Tuan; Duong, Vu; Suri, Ronald
2009-01-01
A neural-network mathematical model that, relative to prior such models, places greater emphasis on some of the temporal aspects of real neural physical processes, has been proposed as a basis for massively parallel, distributed algorithms that learn dynamic models of possibly complex external processes by means of learning rules that are local in space and time. The algorithms could be made to perform such functions as recognition and prediction of words in speech and of objects depicted in video images. The approach embodied in this model is said to be "hardware-friendly" in the following sense: The algorithms would be amenable to execution by special-purpose computers implemented as very-large-scale integrated (VLSI) circuits that would operate at relatively high speeds and low power demands.
Multiscale modeling with smoothed dissipative particle dynamics.
Kulkarni, Pandurang M; Fu, Chia-Chun; Shell, M Scott; Leal, L Gary
2013-06-21
In this work, we consider two issues related to the use of Smoothed Dissipative Particle Dynamics (SDPD) as an intermediate mesoscale model in a multiscale scheme for solution of flow problems when there are local parts of a macroscopic domain that require molecular resolution. The first is to demonstrate that SDPD with different levels of resolution can accurately represent the fluid properties from the continuum scale all the way to the molecular scale. Specifically, while the thermodynamic quantities such as temperature, pressure, and average density remain scale-invariant, we demonstrate that the dynamic properties are quantitatively consistent with an all-atom Lennard-Jones reference system when the SDPD resolution approaches the atomistic scale. This supports the idea that SDPD can serve as a natural bridge between molecular and continuum descriptions. In the second part, a simple multiscale methodology is proposed within the SDPD framework that allows several levels of resolution within a single domain. Each particle is characterized by a unique physical length scale called the smoothing length, which is inversely related to the local number density and can change on-the-fly. This multiscale methodology is shown to accurately reproduce fluid properties for the simple problem of steady and transient shear flow. PMID:23802949
Models of dynamical R-parity violation
NASA Astrophysics Data System (ADS)
Csáki, Csaba; Kuflik, Eric; Slone, Oren; Volansky, Tomer
2015-06-01
The presence of R-parity violating interactions may relieve the tension between existing LHC constraints and natural supersymmetry. In this paper we lay down the theoretical framework and explore models of dynamical R-parity violation in which the breaking of R-parity is communicated to the visible sector by heavy messenger fields. We find that R-parity violation is often dominated by non-holomorphic operators that have so far been largely ignored, and might require a modification of the existing searches at the LHC. The dynamical origin implies that the effects of such operators are suppressed by the ratio of either the light fermion masses or the supersymmetry breaking scale to the mediation scale, thereby providing a natural explanation for the smallness of R-parity violation. We consider various scenarios, classified by whether R-parity violation, flavor breaking and/or supersymmetry breaking are mediated by the same messenger fields. The most compact case, corresponding to a deformation of the so called flavor mediation scenario, allows for the mediation of supersymmetry breaking, R-parity breaking, and flavor symmetry breaking in a unified manner.
Analytic wave model of Stark deceleration dynamics
Gubbels, Koos; Meijer, Gerard; Friedrich, Bretislav
2006-06-15
Stark deceleration relies on time-dependent inhomogeneous electric fields which repetitively exert a decelerating force on polar molecules. Fourier analysis reveals that such fields, generated by an array of field stages, consist of a superposition of partial waves with well-defined phase velocities. Molecules whose velocities come close to the phase velocity of a given wave get a ride from that wave. For a square-wave temporal dependence of the Stark field, the phase velocities of the waves are found to be odd-fraction multiples of a fundamental phase velocity {lambda}/{tau}, with {lambda} and {tau} the spatial and temporal periods of the field. Here we study explicitly the dynamics due to any of the waves as well as due to their mutual perturbations. We first solve the equations of motion for the case of single-wave interactions and exploit their isomorphism with those for the biased pendulum. Next we analyze the perturbations of the single-wave dynamics by other waves and find that these have no net effect on the phase stability of the acceleration or deceleration process. Finally, we find that a packet of molecules can also ride a wave which results from an interference of adjacent waves. In this case, small phase stability areas form around phase velocities that are even-fraction multiples of the fundamental velocity. A detailed comparison with classical trajectory simulations and with experiment demonstrates that the analytic 'wave model' encompasses all the longitudinal physics encountered in a Stark decelerator.
Monitoring and modeling growing season dynamics
NASA Astrophysics Data System (ADS)
White, Michael Aaron
Phenology, the study of recurring biological cycles and their connection to climate, is a growing field of global change research. Vegetation phenology exerts a strong control over carbon cycles, weather, and global radiation partitioning between sensible and latent heat fluxes. Phenological monitors of the timing and length of the growing season can also be used as barometers of vegetation responses to climatic variability. In the following chapters, I present research investigating the monitoring and interpretation of growing season dynamics. Ecological modeling is limited more by data availability than by model theory. In particular, the description of vegetation functional types (biomes) for distributed modeling has been lacking. In chapter 1, I present a documented description and sensitivity analysis of the 34 parameters used in the ecosystem model, BIOME-BGC, for major temperate biomes. I applied BIOME-BGC in the eastern U.S. deciduous broad leaf forest and found that minor phenological variation created large impacts on simulated net ecosystem exchange of carbon (chapter 2). In addition to simulating the effects of growing season variability, it is also important to develop accurate field monitoring techniques, both as a means of testing modeling activities and as a validation of satellite remote sensing estimates. I conducted an intercomparison of field techniques that could be used to monitor phenological dynamics in and ecosystems (chapter 3). I found that methodological barriers to rapid, low cost monitoring were severe, but that a digital camera with both visible and near-infrared channels was a viable option. Satellite remote sensing provides the only means of obtaining consistent estimates of phenological variation at a global scale, yet our understanding of these data has been limited by a lack of ground observations. To address this problem, I proposed, developed, and wrote a phenology measurement protocol for the Global Learning and Observations
Assessing Molecular Dynamics Simulations with Solvatochromism Modeling.
Schwabe, Tobias
2015-08-20
For the modeling of solvatochromism with an explicit representation of the solvent molecules, the quality of preceding molecular dynamics simulations is crucial. Therefore, the possibility to apply force fields which are derived with as little empiricism as possible seems desirable. Such an approach is tested here by exploiting the sensitive solvatochromism of p-nitroaniline, and the use of reliable excitation energies based on approximate second-order coupled cluster results within a polarizable embedding scheme. The quality of the various MD settings for four different solvents, water, methanol, ethanol, and dichloromethane, is assessed. In general, good agreement with the experiment is observed when polarizable force fields and special treatment of hydrogen bonding are applied. PMID:26220273
Modeling the dynamics of piano keys
NASA Astrophysics Data System (ADS)
Brenon, Celine; Boutillon, Xavier
2003-10-01
The models of piano keys available in the literature are crude: two degrees of freedom and a very few dynamical or geometrical parameters. Experiments on different piano mechanisms (upright, grand, one type of numerical keyboard) exhibit strong differences in the two successive phases of the key motion which are controlled by the finger. Understanding the controllability of the escapement velocity (typically a few percents for professional pianists), the differences between upright and grand pianos, the rationale for the numerous independent adjustments by technicians, and the feel by the pianist require sophisticated modeling. In addition to the inertia of the six independently moving parts of a grand piano mechanism, a careful modeling of friction at pivots and between the jack and the roll, of damping and nonlinearities in felts, and of internal springs will be presented. Simulations will be confronted to the measurements of the motions of the different parts. Currently, the first phase of the motion and the transition to the second phase are well understood while some progress must still be made in order to describe correctly this short but important phase before the escapement of the hammer. [Work done in part at the Laboratory for Musical Acoustics, Paris.
Persistent agents in Axelrod's social dynamics model
NASA Astrophysics Data System (ADS)
Reia, Sandro M.; Neves, Ubiraci P. C.
2016-01-01
Axelrod's model of social dynamics has been studied under the effect of external media. Here we study the formation of cultural domains in the model by introducing persistent agents. These are agents whose cultural traits are not allowed to change but may be spread through local neighborhood. In the absence of persistent agents, the system is known to present a transition from a monocultural to a multicultural regime at some critical Q (number of traits). Our results reveal a dependence of critical Q on the occupation probability p of persistent agents and we obtain the phase diagram of the model in the (p,Q) -plane. The critical locus is explained by the competition of two opposite forces named here barrier and bonding effects. Such forces are verified to be caused by non-persistent agents which adhere (adherent agents) to the set of traits of persistent ones. The adherence (concentration of adherent agents) as a function of p is found to decay for constant Q. Furthermore, adherence as a function of Q is found to decay as a power law with constant p.
CIDGA - Coupling of Interior Dynamic models with Global Atmosphere models
NASA Astrophysics Data System (ADS)
Noack, Lena; Plesa, Ana-Catalina; Breuer, Doris
2010-05-01
Atmosphere temperatures and in particular the surface temperatures mostly depend on the solar heat flux and the atmospheric composition. The latter can be influenced by interior processes of the planet, i.e. volcanism that releases greenhouse gases such as H2O, CO2 and methane into the atmosphere and plate tectonics through which atmospheric CO2 is recycled via carbonates into the mantle. An increasing concentration of greenhouse gases in the atmosphere results in an increase of the surface temperature. Changes in the surface temperature on the other hand may influence the cooling behaviour of the planet and hence influence its volcanic activity [Phillips et al., 2001]. This feedback relation between mantle convection and atmosphere is not very well understood, since until now mostly either the interior dynamic of a planet or its atmosphere was investigated separately. 2D or 3D mantle convection models to the authors' knowledge haven't been coupled to the atmosphere so far. We have used the 3D spherical simulation code GAIA [Hüttig et al., 2008] including partial melt production and coupled it with the atmosphere module CIDGA using a gray greenhouse model for varying H2O concentrations. This way, not only the influence of mantle dynamics on the atmosphere can be investigated, but also the recoupling effect, that the surface temperature has on the mantle dynamics. So far, we consider one-plate planets without crustal and thus volatile recycling. Phillips et al. [2001] already investigated the coupling effect of the surface temperature on mantle dynamics by using simple parameterized convection models for Venus. In their model a positive feedback mechanism has been observed, i.e., an increase of the surface temperature leads to an increase of partial melt and hence an increase of atmosphere density and surface temperature. Applying our model to Venus, we show that an increase of surface temperature leads not only to an increase of partial melt in the mantle; it also
Dynamical and Physical Models of Ecliptic Comets
NASA Astrophysics Data System (ADS)
Dones, L.; Boyce, D. C.; Levison, H. F.; Duncan, M. J.
2005-08-01
In most simulations of the dynamical evolution of the cometary reservoirs, a comet is removed from the computer only if it is thrown from the Solar System or strikes the Sun or a planet. However, ejection or collision is probably not the fate of most active comets. Some, like 3D/Biela, disintegrate for no apparent reason, and others, such as the Sun-grazers, 16P/Brooks 2, and D/1993 F2 Shoemaker-Levy 9, are pulled apart by the Sun or a planet. Still others, like 107P/Wilson Harrington and D/1819 W1 Blanpain, are lost and then rediscovered as asteroids. Historically, amateurs discovered most comets. However, robotic surveys now dominate the discovery of comets (http://www.comethunter.de/). These surveys include large numbers of comets observed in a standard way, so the process of discovery is amenable to modeling. Understanding the selection effects for discovery of comets is a key problem in constructing models of cometary origin. To address this issue, we are starting new orbital integrations that will provide the best model to date of the population of ecliptic comets as a function of location in the Solar System and the size of the cometary nucleus, which we expect will vary with location. The integrations include the gravitational effects of the terrestrial and giant planets and, in some cases, nongravitational jetting forces. We will incorporate simple parameterizations for mantling and mass loss based upon detailed physical models. This approach will enable us to estimate the fraction of comets in different states (active, extinct, dormant, or disintegrated) and to track how the cometary size distribution changes as a function of distance from the Sun. We will compare the results of these simulations with bias-corrected models of the orbital and absolute magnitude distributions of Jupiter-family comets and Centaurs.
Suicidal Disclosures among Friends: Using Social Network Data to Understand Suicide Contagion*
Mueller, Anna S.; Abrutyn, Seth
2015-01-01
A robust literature suggests that suicide is socially contagious; however, we know little about how and why suicide spreads. Using network data from the National Longitudinal Study of Adolescent to Adult Health, we examine the effects of alter’s (1) disclosed and (2) undisclosed suicide attempts, (3) suicide ideation and (4) emotional distress on ego’s mental health one year later to gain insights into the emotional and cultural mechanisms that underlie suicide contagion. We find that when egos know about alter’s suicide attempt, they report significantly higher levels of emotional distress and are more likely to report suicidality, net of extensive controls; however, alter’s undisclosed suicide attempts and ideation have no significant effect on ego’s mental health. Finally, we find evidence that emotional distress is contagious in adolescence, though it does not seem to promote suicidality. We discuss the implications of our findings for suicide contagion specifically and sociology more generally. PMID:25722129
ERIC Educational Resources Information Center
Kaplan, David
2005-01-01
This article considers the problem of estimating dynamic linear regression models when the data are generated from finite mixture probability density function where the mixture components are characterized by different dynamic regression model parameters. Specifically, conventional linear models assume that the data are generated by a single…
Modelling vegetation dynamics for Alpine meadows
NASA Astrophysics Data System (ADS)
Della Chiesa, Stefano; Bertoldi, Giacomo; Wohlfahrt, Georg; Rist, Armin; Niedrist, Georg; Albertson, John D.; Tappeiner, Ulrike
2010-05-01
Regional climate scenarios predict a temperature increase and a summer precipitation decrease for the European Alps. This is expected to lead to longer vegetation periods, but also to drought stress in Alpine meadows ecosystems. It is therefore uncertain if the predicted climatic changes will lead to an increase or decrease of biomass production in these grassland ecosystems. Understanding plant growth requires to consider the complex interactions between soil, atmosphere and climate via its physiological properties, in particular LAI, stomatal resistance, rooting depth, albedo, surface roughness and effects on soil moisture. Vegetation Dynamic Models (VDM) coupled with hydrological models take into account these interactions in order to study and estimate biomass production quantitatively. In this contribution, the VDM previously developed by Montaldo et al. (2005) for semi-arid environments is extended to Alpine meadows in the Stubai Valley (Eastern Austria) which are typically not subjected to water and nutrient stresses, but undergoing low temperature limitations. The aim is to assess the model robustness. Moreover, the effects of mowing practice during the season were taken into consideration. The VDM has then been implemented in the distributed hydrological model GEOtop (Rigon et al., 2006). The VDM performed well in the considered case study. The validation and calibration of the model is presented and then the effects of increased temperature and decreased precipitation are investigated numerically. In order to evaluate in the field the effects of climatic change on Alpine grassland biomass production, the inner Alpine continental Mazia Valley (South Tyrol, Italy) has been chosen in 2009 for Long-Term Ecological Research. These climatic changes will be simulated by manipulations along an altitudinal gradient comprising measuring stations at about 1000 m, 1500 m and 2000 m a.s.l.. Meadow monoliths will be transplanted downslope to simulate temperature
An Extension Dynamic Model Based on BDI Agent
NASA Astrophysics Data System (ADS)
Yu, Wang; Feng, Zhu; Hua, Geng; WangJing, Zhu
this paper's researching is based on the model of BDI Agent. Firstly, This paper analyze the deficiencies of the traditional BDI Agent model, Then propose an extension dynamic model of BDI Agent based on the traditional ones. It can quickly achieve the internal interaction of the tradition model of BDI Agent, deal with complex issues under dynamic and open environment and achieve quick reaction of the model. The new model is a natural and reasonable model by verifying the origin of civilization using the model of monkeys to eat sweet potato based on the design of the extension dynamic model. It is verified to be feasible by comparing the extended dynamic BDI Agent model with the traditional BDI Agent Model uses the SWARM, it has important theoretical significance.
Exploring the nonlinear dynamics of a physiologically viable model neuron
Lindner, J.F.; Ditto, W.L.
1996-06-01
We describe efforts underway to explore the nonlinear dynamics of the Pinsky-Rinzel model neuron. Via computer simulations, we seek to discover nonlinear phenomena in this physiologically accurate model, thereby complementing ongoing and future experiments. Here we describe the model in detail and analyze it using tools of nonlinear dynamics to demonstrate nontrivial behaviors. {copyright} {ital 1996 American Institute of Physics.}
Dynamics in Higher Education Politics: A Theoretical Model
ERIC Educational Resources Information Center
Kauko, Jaakko
2013-01-01
This article presents a model for analysing dynamics in higher education politics (DHEP). Theoretically the model draws on the conceptual history of political contingency, agenda-setting theories and previous research on higher education dynamics. According to the model, socio-historical complexity can best be analysed along two dimensions: the…
Stochastic-dynamic Modelling of Morphodynamics
NASA Astrophysics Data System (ADS)
Eppel, D. P.; Kapitza, H.
The numerical prediction of coastal sediment motion over time spans of years and decades is hampered by the sediment's ability, when stirred by waves and currents, to often react not uniquely to the external forcing but rather to show some kind of internal dynamics whose characteristics are not directly linked to the external forcing. Analytical stability analyses of the sediment-water system indicate that instabilities of tidally forced sediment layers in shallow seas can occur on spatial scales smaller than and not related to the scales of the tidal components. The finite growth of these un- stable amplitides can be described in terms of Ginzburg-Landau equations. Examples are the formation of ripples, sand waves and sand dunes or the formation of shore- face connected ridges. Among others, analyses of time series of coastal profiles from Duck, South Carolina extending over several decades gave evidence for self-organized behaviour suggesting that some important sediment-water systems can be perceived as dissipative dynamical structures. The consequences of such behaviour for predicting morphodynamics has been pointed out: one would expect that there exist time horizons beyond which predictions in the traditional deterministic sense are not possible. One would have to look for statistical quantities containing information of some relevance such as phase-space densities of solutions, attractor sets and the like. This contribution is part of an effort to address the prediction problem of morphody- namics through process-oriented models containing stochastic parameterizations for bottom shear stresses, critical shear stresses, etc.; process-based models because they are directly related to the physical processes but in a stochastic form because it is known that the physical processes contain strong stochastic components. The final outcome of such a program would be the generation of an ensemble of solutions by Monte Carlo integrations of the stochastic model
Supercomputer modeling of volcanic eruption dynamics
Kieffer, S.W.; Valentine, G.A.; Woo, Mahn-Ling
1995-06-01
Our specific goals are to: (1) provide a set of models based on well-defined assumptions about initial and boundary conditions to constrain interpretations of observations of active volcanic eruptions--including movies of flow front velocities, satellite observations of temperature in plumes vs. time, and still photographs of the dimensions of erupting plumes and flows on Earth and other planets; (2) to examine the influence of subsurface conditions on exit plane conditions and plume characteristics, and to compare the models of subsurface fluid flow with seismic constraints where possible; (3) to relate equations-of-state for magma-gas mixtures to flow dynamics; (4) to examine, in some detail, the interaction of the flowing fluid with the conduit walls and ground topography through boundary layer theory so that field observations of erosion and deposition can be related to fluid processes; and (5) to test the applicability of existing two-phase flow codes for problems related to the generation of volcanic long-period seismic signals; (6) to extend our understanding and simulation capability to problems associated with emplacement of fragmental ejecta from large meteorite impacts.
A dynamic model of Venus's gravity field
NASA Technical Reports Server (NTRS)
Kiefer, W. S.; Richards, M. A.; Hager, B. H.; Bills, B. G.
1984-01-01
Unlike Earth, long wavelength gravity anomalies and topography correlate well on Venus. Venus's admittance curve from spherical harmonic degree 2 to 18 is inconsistent with either Airy or Pratt isostasy, but is consistent with dynamic support from mantle convection. A model using whole mantle flow and a high viscosity near surface layer overlying a constant viscosity mantle reproduces this admittance curve. On Earth, the effective viscosity deduced from geoid modeling increases by a factor of 300 from the asthenosphere to the lower mantle. These viscosity estimates may be biased by the neglect of lateral variations in mantle viscosity associated with hot plumes and cold subducted slabs. The different effective viscosity profiles for Earth and Venus may reflect their convective styles, with tectonism and mantle heat transport dominated by hot plumes on Venus and by subducted slabs on Earth. Convection at degree 2 appears much stronger on Earth than on Venus. A degree 2 convective structure may be unstable on Venus, but may have been stabilized on Earth by the insulating effects of the Pangean supercontinental assemblage.
A dynamic model of Venus's gravity field
NASA Technical Reports Server (NTRS)
Kiefer, W. S.; Richards, M. A.; Hager, B. H.; Bills, B. G.
1986-01-01
Unlike Earth, long wavelength gravity anomalies and topography correlate well on Venus. Venus's admittance curve from spherical harmonic degree 2 to 18 is inconsistent with either Airy or Pratt isostasy, but is consistent with dynamic support from mantle convection. A model using whole mantle flow and a high viscosity near surface layer overlying a constant viscosity mantle reproduces this admittance curve. On Earth, the effective viscosity deduced from geoid modeling increases by a factor of 300 from the asthenosphere to the lower mantle. These viscosity estimates may be biased by the neglect of lateral variations in mantle viscosity associated with hot plumes and cold subducted slabs. The different effective viscosity profiles for Earth and Venus may reflect their convective styles, with tectonism and mantle heat transport dominated by hot plumes on Venus and by subducted slabs on Earth. Convection at degree 2 appears much stronger on Earth than on Venus. A degree 2 convective structure may be unstable on Venus, but may have been stabilized on Earth by the insulating effects of the Pangean supercontinental assemblage.
Research of cyclist's spine dynamical model.
Griskevicius, Julius; Linkel, Arturas; Pauk, Jolanta
2014-01-01
The purpose of the paper is to present a dynamic model of bicyclist's lumbar spine for the evaluation of linear and angular variation of intervertebral distance in sagittal plane. Ten degrees of freedom biomechanical model of the spine was solved numerically. Larger loads acting on a cyclist spine occur mostly while sitting in a sport position in comparison with recreation or middle sitting. The load on lumbar spine region is influenced by cycle's tire pressure, road bumps and wheeling speed. The biggest linear and angular displacements were found between L4-L5 vertebras. The biggest load protractile spine muscle experiences in the sport sitting position. Maximum vertebrae rotation and linear variation values in wheeling regime with 1.5 Bar tyres pressure and at a speed of 10 km/h are 0.46° and 0.46 mm. Maximum vertebrae rotation and linear variation values for a 23 year old, 1.74 m high and 73 kg of mass (bicycle mass~7 kg) man in wheeling regime with 3.5 Bar tyres pressure and at a speed of 30 km/h are 3.9° and 1.23 mm. The biggest variation of rotation in sagittal plane between two nearest lumbar spines is about 1°. Because of this displacement the frontal part of last mentioned disc is compressed with 530 N more and dorsal disc part as much less. PMID:24708161
Indicators of positive and negative emotions and emotional contagion in pigs.
Reimert, Inonge; Bolhuis, J Elizabeth; Kemp, Bas; Rodenburg, T Bas
2013-01-17
For the welfare of group-housed animals, such as pigs, the emotional state of an individual pig is relevant, but also the extent to which pen mates are affected by the distress or pleasure of other individuals, i.e. emotional contagion, a simple form of empathy. Therefore, indicators of positive and negative emotions were investigated in pigs during anticipation and experience of a rewarding (access in pairs to a compartment with straw, peat and chocolate raisins) or aversive (social isolation combined with negative, unpredictable interventions) event. Thereafter the same indicators were investigated in naive pigs during anticipation and experience of a rewarding or aversive event by their trained pen mates. Positive emotions could be indicated by play, barks and tail movements, while negative emotions could be indicated by freezing, defecating, urinating, escape attempts, high-pitched vocalizations (screams, squeals or grunt-squeals), tail low, ears back and ear movements. Salivary cortisol measurements supported these behavioral observations. During anticipation of the aversive event, naive pigs tended to show more tail low. During the aversive event, naive pigs tended to defecate more, while they played more during the rewarding event. These results suggest that pigs might be sensitive to emotional contagion, which could have implications for the welfare of group-housed pigs. Pig emotions and the process of emotional contagion merit, therefore, further research. PMID:23159725
Sympathetic magic and gambling: adherence to the law of contagion varies with gambling severity.
Teed, Moira; Finlay, Karen A; Marmurek, Harvey H C; Colwell, Scott R; Newby-Clark, Ian R
2012-12-01
This study assessed adherence to the law of contagion by 118 undergraduate students (39 males). Participants were students who played a slot machine game after viewing a prior player who seemed to be winning ("lucky" condition) or losing ("unlucky" condition). Adherence to the law of contagion was assessed by the selection of the coin holder used by a "lucky" prior player and the avoidance of the coin holder used by an "unlucky" prior player. Contagion varied directly with scores on the Problem Gambling Severity Index and scores on the Luck/Perseverance subscale of the Gamblers' Belief Questionnaire (Steenbergh et al. in Psychol Addict Behav 16(2):143-149, 2002). Gamblers high in problem severity chose the "lucky" coin holder and avoided the "unlucky" coin holder significantly more than gamblers low in problem severity. Problem gamblers, therefore, exhibit evidence of magical thinking related to the transfer of a "lucky" essence. The same was the case for individuals with a strong level of belief that sheer continuation in gambling (luck perseverance) results in success and for individuals who believe that luck is a personal rather than a situational characteristic. All three variables (problem gambling severity, luck perseverance and personal luck) had direct effects on behavior reflecting irrational magical thinking. A belief that knowledge or skill has a role in successful gaming was unrelated to magical thinking. These findings suggest potential foci for cognitive interventions with problem gamblers and those with non-skill based evidence of irrational thinking. PMID:22081162
Goumon, Sébastien; Špinka, Marek
2016-05-01
This study tested whether emotional contagion occurs when piglets directly observe a penmate in distress (restraint) and whether there is an effect of previous experience on the response to subsequent restraint or exposure to conspecific distress. Piglets (49.7 ± 0.7 days) were exposed in pairs to two stress phases (SP1 and SP2) in an arena divided into two pens by a wire mesh wall. During SP1, one of the pigs of a pair was either restrained (Stress treatment) or sham-restrained (Control treatment), while the other pig was considered observer. During SP2, the previous observer was restrained, while its penmate took the observer role. Heart rate variability, locomotion, vocalizations, body/head/ear and tail postures were monitored. During SP1, observer pigs responded to conspecific distress with increased indicators of attention (looking at, proximity to and snout contacts with the distressed pigs) and increased indicators of fear (reduced locomotion, increased freezing). During SP2, the observer pigs that had been restrained previously reacted more strongly (through higher proximity, decreased locomotion, increased freezing) to observing the penmate in restraint than pigs without the previous negative experience. This study suggests that young pigs are susceptible to emotional contagion and that this contagion is potentiated by previous exposure to the same stressor. These findings have implications for pig welfare in practical animal husbandry systems. PMID:26753689
Reducing social stress elicits emotional contagion of pain in mouse and human strangers.
Martin, Loren J; Hathaway, Georgia; Isbester, Kelsey; Mirali, Sara; Acland, Erinn L; Niederstrasser, Nils; Slepian, Peter M; Trost, Zina; Bartz, Jennifer A; Sapolsky, Robert M; Sternberg, Wendy F; Levitin, Daniel J; Mogil, Jeffrey S
2015-02-01
Empathy for another's physical pain has been demonstrated in humans [1] and mice [2]; in both species, empathy is stronger between familiars. Stress levels in stranger dyads are higher than in cagemate dyads or isolated mice [2, 3], suggesting that stress might be responsible for the absence of empathy for the pain of strangers. We show here that blockade of glucocorticoid synthesis or receptors for adrenal stress hormones elicits the expression of emotional contagion (a form of empathy) in strangers of both species. Mice and undergraduates were tested for sensitivity to noxious stimulation alone and/or together (dyads). In familiar, but not stranger, pairs, dyadic testing was associated with increased pain behaviors or ratings compared to isolated testing. Pharmacological blockade of glucocorticoid synthesis or glucocorticoid and mineralocorticoid receptors enabled the expression of emotional contagion of pain in mouse and human stranger dyads, as did a shared gaming experience (the video game Rock Band) in human strangers. Our results demonstrate that emotional contagion is prevented, in an evolutionarily conserved manner, by the stress of a social interaction with an unfamiliar conspecific and can be evoked by blocking the endocrine stress response. PMID:25601547
A dynamical stochastic coupled model for financial markets
NASA Astrophysics Data System (ADS)
Govindan, T. E.; Ibarra-Valdez, Carlos; Ruiz de Chávez, J.
2007-07-01
A model coupling a deterministic dynamical system which represents trading, with a stochastic one that represents asset prices evolution is presented. Both parts of the model have connections with well established dynamic models in mathematical economics and finance. The main objective is to represent the double feedback between trading dynamics (the demand/supply interaction) and price dynamics (assumed as largely random). We present the model, and address to some extent existence and uniqueness, continuity with respect to initial conditions and stability of solutions. The non-Lipschitz case is briefly considered as well.
AIR INGRESS ANALYSIS: COMPUTATIONAL FLUID DYNAMIC MODELS
Chang H. Oh; Eung S. Kim; Richard Schultz; Hans Gougar; David Petti; Hyung S. Kang
2010-08-01
The Idaho National Laboratory (INL), under the auspices of the U.S. Department of Energy, is performing research and development that focuses on key phenomena important during potential scenarios that may occur in very high temperature reactors (VHTRs). Phenomena Identification and Ranking Studies to date have ranked an air ingress event, following on the heels of a VHTR depressurization, as important with regard to core safety. Consequently, the development of advanced air ingress-related models and verification and validation data are a very high priority. Following a loss of coolant and system depressurization incident, air will enter the core of the High Temperature Gas Cooled Reactor through the break, possibly causing oxidation of the in-the core and reflector graphite structure. Simple core and plant models indicate that, under certain circumstances, the oxidation may proceed at an elevated rate with additional heat generated from the oxidation reaction itself. Under postulated conditions of fluid flow and temperature, excessive degradation of the lower plenum graphite can lead to a loss of structural support. Excessive oxidation of core graphite can also lead to the release of fission products into the confinement, which could be detrimental to a reactor safety. Computational fluid dynamic model developed in this study will improve our understanding of this phenomenon. This paper presents two-dimensional and three-dimensional CFD results for the quantitative assessment of the air ingress phenomena. A portion of results of the density-driven stratified flow in the inlet pipe will be compared with results of the experimental results.
Stochastic hybrid modeling of intracellular calcium dynamics
NASA Astrophysics Data System (ADS)
Choi, TaiJung; Maurya, Mano Ram; Tartakovsky, Daniel M.; Subramaniam, Shankar
2010-10-01
Deterministic models of biochemical processes at the subcellular level might become inadequate when a cascade of chemical reactions is induced by a few molecules. Inherent randomness of such phenomena calls for the use of stochastic simulations. However, being computationally intensive, such simulations become infeasible for large and complex reaction networks. To improve their computational efficiency in handling these networks, we present a hybrid approach, in which slow reactions and fluxes are handled through exact stochastic simulation and their fast counterparts are treated partially deterministically through chemical Langevin equation. The classification of reactions as fast or slow is accompanied by the assumption that in the time-scale of fast reactions, slow reactions do not occur and hence do not affect the probability of the state. Our new approach also handles reactions with complex rate expressions such as Michaelis-Menten kinetics. Fluxes which cannot be modeled explicitly through reactions, such as flux of Ca2+ from endoplasmic reticulum to the cytosol through inositol 1,4,5-trisphosphate receptor channels, are handled deterministically. The proposed hybrid algorithm is used to model the regulation of the dynamics of cytosolic calcium ions in mouse macrophage RAW 264.7 cells. At relatively large number of molecules, the response characteristics obtained with the stochastic and deterministic simulations coincide, which validates our approach in the limit of large numbers. At low doses, the response characteristics of some key chemical species, such as levels of cytosolic calcium, predicted with stochastic simulations, differ quantitatively from their deterministic counterparts. These observations are ubiquitous throughout dose response, sensitivity, and gene-knockdown response analyses. While the relative differences between the peak-heights of the cytosolic [Ca2+] time-courses obtained from stochastic (mean of 16 realizations) and deterministic
COMPUTATIONAL FLUID DYNAMICS MODELING ANALYSIS OF COMBUSTORS
Mathur, M.P.; Freeman, Mark; Gera, Dinesh
2001-11-06
In the current fiscal year FY01, several CFD simulations were conducted to investigate the effects of moisture in biomass/coal, particle injection locations, and flow parameters on carbon burnout and NO{sub x} inside a 150 MW GEEZER industrial boiler. Various simulations were designed to predict the suitability of biomass cofiring in coal combustors, and to explore the possibility of using biomass as a reburning fuel to reduce NO{sub x}. Some additional CFD simulations were also conducted on CERF combustor to examine the combustion characteristics of pulverized coal in enriched O{sub 2}/CO{sub 2} environments. Most of the CFD models available in the literature treat particles to be point masses with uniform temperature inside the particles. This isothermal condition may not be suitable for larger biomass particles. To this end, a stand alone program was developed from the first principles to account for heat conduction from the surface of the particle to its center. It is envisaged that the recently developed non-isothermal stand alone module will be integrated with the Fluent solver during next fiscal year to accurately predict the carbon burnout from larger biomass particles. Anisotropy in heat transfer in radial and axial will be explored using different conductivities in radial and axial directions. The above models will be validated/tested on various fullscale industrial boilers. The current NO{sub x} modules will be modified to account for local CH, CH{sub 2}, and CH{sub 3} radicals chemistry, currently it is based on global chemistry. It may also be worth exploring the effect of enriched O{sub 2}/CO{sub 2} environment on carbon burnout and NO{sub x} concentration. The research objective of this study is to develop a 3-Dimensional Combustor Model for Biomass Co-firing and reburning applications using the Fluent Computational Fluid Dynamics Code.
Dynamic modelling and analysis of space webs
NASA Astrophysics Data System (ADS)
Yu, Yang; Baoyin, HeXi; Li, JunFeng
2011-04-01
Future space missions demand operations on large flexible structures, for example, space webs, the lightweight cable nets deployable in space, which can serve as platforms for very large structures or be used to capture orbital objects. The interest in research on space webs is likely to increase in the future with the development of promising applications such as Furoshiki sat-ellite of JAXA, Robotic Geostationary Orbit Restorer (ROGER) of ESA and Grapple, Retrieve And Secure Payload (GRASP) of NASA. Unlike high-tensioned nets in civil engineering, space webs may be low-tensioned or tensionless, and extremely flexible, owing to the microgravity in the orbit and the lack of support components, which may cause computational difficulties. Mathematical models are necessary in the analysis of space webs, especially in the conceptual design and evaluation for prototypes. A full three-dimensional finite element (FE) model was developed in this work. Trivial truss elements were adopted to reduce the computational complexity. Considering cable is a compression-free material and its tensile stiffness is also variable, we introduced the cable material constitutive relationship to work out an accurate and feasible model for prototype analysis and design. In the static analysis, the stress distribution and global deformation of the webs were discussed to get access to the knowledge of strength of webs with different types of meshes. In the dynamic analysis, special attention was paid to the impact problem. The max stress and global deformation were investigated. The simulation results indicate the interesting phenomenon which may be worth further research.
Bayesian Estimation of Random Coefficient Dynamic Factor Models
ERIC Educational Resources Information Center
Song, Hairong; Ferrer, Emilio
2012-01-01
Dynamic factor models (DFMs) have typically been applied to multivariate time series data collected from a single unit of study, such as a single individual or dyad. The goal of DFMs application is to capture dynamics of multivariate systems. When multiple units are available, however, DFMs are not suited to capture variations in dynamics across…
A dynamic model for the Lagrangian stochastic dispersion coefficient
Pesmazoglou, I.; Navarro-Martinez, S.; Kempf, A. M.
2013-12-15
A stochastic sub-grid model is often used to accurately represent particle dispersion in turbulent flows using large eddy simulations. Models of this type have a free parameter, the dispersion coefficient, which is not universal and is strongly grid-dependent. In the present paper, a dynamic model for the evaluation of the coefficient is proposed and validated in decaying homogeneous isotropic turbulence. The grid dependence of the static coefficient is investigated in a turbulent mixing layer and compared to the dynamic model. The dynamic model accurately predicts dispersion statistics and resolves the grid-dependence. Dispersion statistics of the dynamically calculated constant are more accurate than any static coefficient choice for a number of grid spacings. Furthermore, the dynamic model produces less numerical artefacts than a static model and exhibits smaller sensitivity in the results predicted for different particle relaxation times.
Dynamic hysteretic sensing model of bending-mode Galfenol transducer
Cao, Shuying Zheng, Jiaju; Sang, Jie; Zhang, Pengfei; Wang, Bowen; Huang, Wenmei
2015-05-07
A dynamic hysteretic sensing model has been developed to predict the dynamic responses of the magnetic induction, the stress, and the output voltage for a bending-mode Galfenol unimorph transducer subjected simultaneously to acceleration and bias magnetic field. This model is obtained by coupling the hysteretic Armstrong model and the structural dynamic model of the Galfenol unimorph beam. The structural dynamic model of the beam is founded based on the Euler-Bernouli beam theory, the nonlinear constitutive equations, and the Faraday law of electromagnetic induction. Comparisons between the calculated and measured results show the model can describe dynamic nonlinear voltage characteristics of the device, and can predict hysteretic behaviors between the magnetic induction and the stress. Moreover, the model can effectively analyze the effects of the bias magnetic field, the acceleration amplitude, and frequency on the root mean square voltage of the device.
Spatiotemporal modelling of viral infection dynamics
NASA Astrophysics Data System (ADS)
Beauchemin, Catherine
Viral kinetics have been studied extensively in the past through the use of ordinary differential equations describing the time evolution of the diseased state in a spatially well-mixed medium. However, emerging spatial structures such as localized populations of dead cells might affect the spread of infection, similar to the manner in which a counter-fire can stop a forest fire from spreading. In the first phase of the project, a simple two-dimensional cellular automaton model of viral infections was developed. It was validated against clinical immunological data for uncomplicated influenza A infections and shown to be accurate enough to adequately model them. In the second phase of the project, the simple two-dimensional cellular automaton model was used to investigate the effects of relaxing the well-mixed assumption on viral infection dynamics. It was shown that grouping the initially infected cells into patches rather than distributing them uniformly on the grid reduced the infection rate as only cells on the perimeter of the patch have healthy neighbours to infect. Use of a local epithelial cell regeneration rule where dead cells are replaced by healthy cells when an immediate neighbour divides was found to result in more extensive damage of the epithelium and yielded a better fit to experimental influenza A infection data than a global regeneration rule based on division rate of healthy cell. Finally, the addition of immune cell at the site of infection was found to be a better strategy at low infection levels, while addition at random locations on the grid was the better strategy at high infection level. In the last project, the movement of T cells within lymph nodes in the absence of antigen, was investigated. Based on individual T cell track data captured by two-photon microscopy experiments in vivo, a simple model was proposed for the motion of T cells. This is the first step towards the implementation of a more realistic spatiotemporal model of HIV than
Davtyan, Aram; Dama, James F.; Voth, Gregory A.; Andersen, Hans C.
2015-04-21
Coarse-grained (CG) models of molecular systems, with fewer mechanical degrees of freedom than an all-atom model, are used extensively in chemical physics. It is generally accepted that a coarse-grained model that accurately describes equilibrium structural properties (as a result of having a well constructed CG potential energy function) does not necessarily exhibit appropriate dynamical behavior when simulated using conservative Hamiltonian dynamics for the CG degrees of freedom on the CG potential energy surface. Attempts to develop accurate CG dynamic models usually focus on replacing Hamiltonian motion by stochastic but Markovian dynamics on that surface, such as Langevin or Brownian dynamics. However, depending on the nature of the system and the extent of the coarse-graining, a Markovian dynamics for the CG degrees of freedom may not be appropriate. In this paper, we consider the problem of constructing dynamic CG models within the context of the Multi-Scale Coarse-graining (MS-CG) method of Voth and coworkers. We propose a method of converting a MS-CG model into a dynamic CG model by adding degrees of freedom to it in the form of a small number of fictitious particles that interact with the CG degrees of freedom in simple ways and that are subject to Langevin forces. The dynamic models are members of a class of nonlinear systems interacting with special heat baths that were studied by Zwanzig [J. Stat. Phys. 9, 215 (1973)]. The properties of the fictitious particles can be inferred from analysis of the dynamics of all-atom simulations of the system of interest. This is analogous to the fact that the MS-CG method generates the CG potential from analysis of equilibrium structures observed in all-atom simulation data. The dynamic models generate a non-Markovian dynamics for the CG degrees of freedom, but they can be easily simulated using standard molecular dynamics programs. We present tests of this method on a series of simple examples that demonstrate that
System Dynamics Modeling for Supply Chain Information Sharing
NASA Astrophysics Data System (ADS)
Feng, Yang
In this paper, we try to use the method of system dynamics to model supply chain information sharing. Firstly, we determine the model boundaries, establish system dynamics model of supply chain before information sharing, analyze the model's simulation results under different changed parameters and suggest improvement proposal. Then, we establish system dynamics model of supply chain information sharing and make comparison and analysis on the two model's simulation results, to show the importance of information sharing in supply chain management. We wish that all these simulations would provide scientific supports for enterprise decision-making.
A dynamic fault tree model of a propulsion system
NASA Technical Reports Server (NTRS)
Xu, Hong; Dugan, Joanne Bechta; Meshkat, Leila
2006-01-01
We present a dynamic fault tree model of the benchmark propulsion system, and solve it using Galileo. Dynamic fault trees (DFT) extend traditional static fault trees with special gates to model spares and other sequence dependencies. Galileo solves DFT models using a judicious combination of automatically generated Markov and Binary Decision Diagram models. Galileo easily handles the complexities exhibited by the benchmark problem. In particular, Galileo is designed to model phased mission systems.
Space Station Freedom solar dynamic modules structural modelling and analysis
Lawrence, C.; Morris, R.
1991-12-01
In support of the Space Station Freedom (SSF) Solar Dynamic Power Module effort, structural design studies were performed to investigate issues related to the design of the power module, its pointing capabilities, and the integration of the module into the SSF infrastructure. Of particular concern from a structural viewpoint are the dynamics of the power module, the impact of the power module on the Space Station dynamics and controls, and the required control effort for obtaining the specified Solar Dynamic Power Module pointing accuracy. Structural analyses were performed to determine the structural dynamics attributes of both the existing and the proposed structural dynamics module designs. The objectives of these analyses were to generate validated Solar Dynamic Power Module NASTRAN finite element models, combine Space Station and power module models into integrated system models, perform finite element modal analyses to assess the effect of the relocations of the power module center of mass, and provide modal data to controls designers for control systems design.
Modeling proteasome dynamics in Parkinson's disease.
Sneppen, Kim; Lizana, Ludvig; Jensen, Mogens H; Pigolotti, Simone; Otzen, Daniel
2009-01-01
In Parkinson's disease (PD), there is evidence that alpha-synuclein (alphaSN) aggregation is coupled to dysfunctional or overburdened protein quality control systems, in particular the ubiquitin-proteasome system. Here, we develop a simple dynamical model for the on-going conflict between alphaSN aggregation and the maintenance of a functional proteasome in the healthy cell, based on the premise that proteasomal activity can be titrated out by mature alphaSN fibrils and their protofilament precursors. In the presence of excess proteasomes the cell easily maintains homeostasis. However, when the ratio between the available proteasome and the alphaSN protofilaments is reduced below a threshold level, we predict a collapse of homeostasis and onset of oscillations in the proteasome concentration. Depleted proteasome opens for accumulation of oligomers. Our analysis suggests that the onset of PD is associated with a proteasome population that becomes occupied in periodic degradation of aggregates. This behavior is found to be the general state of a proteasome/chaperone system under pressure, and suggests new interpretations of other diseases where protein aggregation could stress elements of the protein quality control system. PMID:19411740
Modeling proteasome dynamics in Parkinson's disease
NASA Astrophysics Data System (ADS)
Sneppen, Kim; Lizana, Ludvig; Jensen, Mogens H.; Pigolotti, Simone; Otzen, Daniel
2009-09-01
In Parkinson's disease (PD), there is evidence that α-synuclein (αSN) aggregation is coupled to dysfunctional or overburdened protein quality control systems, in particular the ubiquitin-proteasome system. Here, we develop a simple dynamical model for the on-going conflict between αSN aggregation and the maintenance of a functional proteasome in the healthy cell, based on the premise that proteasomal activity can be titrated out by mature αSN fibrils and their protofilament precursors. In the presence of excess proteasomes the cell easily maintains homeostasis. However, when the ratio between the available proteasome and the αSN protofilaments is reduced below a threshold level, we predict a collapse of homeostasis and onset of oscillations in the proteasome concentration. Depleted proteasome opens for accumulation of oligomers. Our analysis suggests that the onset of PD is associated with a proteasome population that becomes occupied in periodic degradation of aggregates. This behavior is found to be the general state of a proteasome/chaperone system under pressure, and suggests new interpretations of other diseases where protein aggregation could stress elements of the protein quality control system.
An Individual-Based Model of Zebrafish Population Dynamics Accounting for Energy Dynamics
Beaudouin, Rémy; Goussen, Benoit; Piccini, Benjamin; Augustine, Starrlight; Devillers, James; Brion, François; Péry, Alexandre R. R.
2015-01-01
Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model) was coupled to an individual based model of zebrafish population dynamics (IBM model). Next, we fitted the DEB model to new experimental data on zebrafish growth and reproduction thus improving existing models. We further analysed the DEB-model and DEB-IBM using a sensitivity analysis. Finally, the predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics are realistic. While our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level. PMID:25938409
Validation of vehicle dynamics simulation models - a review
NASA Astrophysics Data System (ADS)
Kutluay, Emir; Winner, Hermann
2014-02-01
In this work, a literature survey on the validation of vehicle dynamics simulation models is presented. Estimating the dynamic responses of existing or proposed vehicles has a wide array of applications in the development of vehicle technologies, e.g. active suspensions, controller design, driver assistance systems, etc. Although simulation environments, measurement tools and mathematical theories on vehicle dynamics are well established, the methodical link between the experimental test data and validity analysis of the simulation model is still lacking. This report presents different views on the definition of validation, and its usage in vehicle dynamics simulation models.
Modelling multiphase dynamics during infiltration using a pore network model
NASA Astrophysics Data System (ADS)
Tzavaras, Jannis; Arns, Ji-Youns; Max, Koehne; Hans-Joerg, Vogel
2013-04-01
We present an implementation of water infiltration into a pore network model where the local water pressures is continuously updated during the transient process. The network geometry is designed to represent structured soil which is different from simple granular porous media in some respect: Pores are more elongated and less isometric and the pore size distribution is much wider and structured hierarchically. To reproduce these properties, the classical concept of pore-bodies and throats is replaced by direct measurements of pore topology and the pores below the minimal pore size of the network model are represented by a continuous network of water saturated micro pores. The latter ensures that the water phase is always continuous which affects the propagation of the water potential during infiltration. The network model is based on cylindrical pores and considers capillary and gravitational forces. The propagation of interfaces is calculated for each time step by repeatedly solving the complete set of linear equation arising from Kirchhoff's law based on mass balance at each node of the network. This is done using the public domain package ITPack. The successive overrelaxation (SOR) and the Jacobi conjugate gradient (JCG) method proved to be more robust and faster than other solvers tested for the complex topology. The model accounts for entrapped air which is assumed to be incompressible. We present first results demonstrating the impact of external forcing (i.e infiltration rate) and pore topology on the dynamics of water-gas interfaces, the volume of entrapped air and hysteresis.
Error Location in Structural Dynamic Model of a Rocket Structure
NASA Astrophysics Data System (ADS)
Sundararajan, T.; Sam, C.
2012-06-01
Structural dynamic characteristics of the aerospace structures are essential to obtain the structural responses due to dynamic loads during its mission. The structural dynamic parameters of the aerospace structures are frequencies, associated mode shape and damping. Usually finite element (FE) model of the aerospace structures are generated to estimate the frequencies and the associated mode shape. These FE models are validated by modal survey/ground resonance tests to ensure its completeness and correctness. The modeling deficiencies, if any, in these FE models have to be corrected. This paper describes the method to locate the FE modeling errors using residual force method.
A review of dynamics modelling of friction wedge suspensions
NASA Astrophysics Data System (ADS)
Wu, Qing; Cole, Colin; Spiryagin, Maksym; Sun, Yan Quan
2014-11-01
Three-piece bogies with friction wedge suspensions are the most widely used bogies in heavy haul trains. Fiction wedge suspensions play a key role in these wagon systems. This article reviews current techniques in dynamic modelling of friction wedge suspension with various motivations: to improve dynamic models of friction wedge suspensions so as to improve general wagon dynamics simulations; to seek better friction wedge suspension models for wagon stability assessments in complex train systems; to improve the modelling of other friction devices, such as friction draft gear. Relevant theories and friction wedge suspension models developed by using commercial simulation packages and in-house simulation packages are reviewed.
Fractional Relativistic Yamaleev Oscillator Model and Its Dynamical Behaviors
NASA Astrophysics Data System (ADS)
Luo, Shao-Kai; He, Jin-Man; Xu, Yan-Li; Zhang, Xiao-Tian
2016-07-01
In the paper we construct a new kind of fractional dynamical model, i.e. the fractional relativistic Yamaleev oscillator model, and explore its dynamical behaviors. We will find that the fractional relativistic Yamaleev oscillator model possesses Lie algebraic structure and satisfies generalized Poisson conservation law. We will also give the Poisson conserved quantities of the model. Further, the relation between conserved quantities and integral invariants of the model is studied and it is proved that, by using the Poisson conserved quantities, we can construct integral invariants of the model. Finally, the stability of the manifold of equilibrium states of the fractional relativistic Yamaleev oscillator model is studied. The paper provides a general method, i.e. fractional generalized Hamiltonian method, for constructing a family of fractional dynamical models of an actual dynamical system.
PC BEEPOP - A PERSONAL COMPUTER HONEY BEE POPULATION DYNAMICS MODEL
PC BEEPOP is a computer model that simulates honey bee (Apis mellifera L.) colony population dynamics. he model consists of a system of interdependent elements, including colony condition, environmental variability, colony energetics, and contaminant exposure. t includes a mortal...
Methods for modeling contact dynamics of capture mechanisms
NASA Technical Reports Server (NTRS)
Williams, Philip J.; Tobbe, Patrick A.; Glaese, John
1991-01-01
In this paper, an analytical approach for studying the contact dynamics of space-based vehicles during docking/berthing maneuvers is presented. Methods for modeling physical contact between docking/berthing mechanisms, examples of how these models have been used to evaluate the dynamic behavior of automated capture mechanisms, and experimental verification of predicted results are shown.
Estimation of Spatial Dynamic Nonparametric Durbin Models with Fixed Effects
ERIC Educational Resources Information Center
Qian, Minghui; Hu, Ridong; Chen, Jianwei
2016-01-01
Spatial panel data models have been widely studied and applied in both scientific and social science disciplines, especially in the analysis of spatial influence. In this paper, we consider the spatial dynamic nonparametric Durbin model (SDNDM) with fixed effects, which takes the nonlinear factors into account base on the spatial dynamic panel…
Pipes Conveying Fluid: A Model Dynamical Problem
NASA Astrophysics Data System (ADS)
Païdoussis, M. P.; Li, G. X.
1993-02-01
This paper reviews the dynamics of pipes conveying fluid and presents a selective review of the research undertaken on it. It is endeavoured to show that this system is fast becoming a new paradigm in dynamics, on a par with, for instance, the classical problem of the column subjected to compressive loading, but one capable of displaying much richer dynamical behaviour. The dynamics of pipes with supported ends, cantilevered pipes or with unusual boundary conditions; continuously flexible pipes or articulated ones; pipe conveying incompressible or compressible fluid, with steady or unsteady flow velocity; pipes thin enough to be treated as thin shells; linear, nonlinear and chaotic dynamics; these and many more are some of the aspects of the problem considered. An Appendix is provided for those unfamiliar with the modern methods of nonlinear analysis.
Modelling Seasonal Carbon Dynamics on Fen Peatlands
NASA Astrophysics Data System (ADS)
Giebels, Michael; Beyer, Madlen; Augustin, Jürgen; Roppel, Mario; Juszczak, Radoszlav; Serba, Tomasz
2010-05-01
In Germany more than 99 % of fens have lost their carbon and nutrient sink function due to heavy drainage and agricultural land use especially during the last decades and thus resulted in compression and heavy peat loss (CHARMAN 2002; JOOSTEN & CLARKE 2002; SUCCOW & JOOSTEN 2001; AUGUSTIN et al. 1996; KUNTZE 1993). Therefore fen peatlands play an important part (4-5 %) in the national anthropogenic trace gas budget. But only a small part of drained and agricultural used fens in NE Germany can be restored. Knowledge of the influence of land use to trace gas exchange is important for mitigation of the climate impact of the anthropogenic peatland use. We study carbon exchanges between soil and atmosphere on several fen peatland use areas at different sites in NE-Germany. Our research covers peatlands of supposed strongly climate forcing land use (cornfield and intensive pasture) and of probably less forcing, alternative types (meadow and extensive pasture) as well as rewetted (formerly drained) areas and near-natural sites like a low-degraded fen and a wetted alder woodland. We measured trace gas fluxes with manual and automatic chambers in periodic routines since spring 2007. The used chamber technique bases on DROESLER (2005). In total we now do research at 22 sites situated in 5 different locations covering agricultural, varying states of rewetted and near-natural treatments. We present results of at least 2 years of measurements on our site of varying types of agricultural land use. There we found significant differences in the annual carbon balances depending on the genesis of the observed sites and the seasonal dynamics. Annual balances were constructed by applying single respiration and photosynthesis CO2 models for each measurement campaign. These models were based on LLOYD-TAYLOR (1994) and Michaelis-Menten-Kinetics respectively. Crosswise comparison of different site treatments combined with the seasonal environmental observations give good hints for the
Dynamic Model Validation with Governor Deadband on the Eastern Interconnection
Kou, Gefei; Hadley, Stanton W; Liu, Yilu
2014-04-01
This report documents the efforts to perform dynamic model validation on the Eastern Interconnection (EI) by modeling governor deadband. An on-peak EI dynamic model is modified to represent governor deadband characteristics. Simulation results are compared with synchrophasor measurements collected by the Frequency Monitoring Network (FNET/GridEye). The comparison shows that by modeling governor deadband the simulated frequency response can closely align with the actual system response.
Dynamic battery cell model and state of charge estimation
NASA Astrophysics Data System (ADS)
Wijewardana, S.; Vepa, R.; Shaheed, M. H.
2016-03-01
Mathematical modelling and the dynamic simulation of battery storage systems can be challenging and demanding due to the nonlinear nature of the battery chemistry. This paper introduces a new dynamic battery model, with application to state of charge estimation, considering all possible aspects of environmental conditions and variables. The aim of this paper is to present a suitable convenient, generic dynamic representation of rechargeable battery dynamics that can be used to model any Lithium-ion rechargeable battery. The proposed representation is used to develop a dynamic model considering the thermal balance of heat generation mechanism of the battery cell and the ambient temperature effect including other variables such as storage effects, cyclic charging, battery internal resistance, state of charge etc. The results of the simulations have been used to study the characteristics of a Lithium-ion battery and the proposed battery model is shown to produce responses within 98% of known experimental measurements.
Benchmarking novel approaches for modelling species range dynamics
Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H.; Moore, Kara A.; Zimmermann, Niklaus E.
2016-01-01
Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species’ range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species’ response to climate change but also emphasise several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches
Benchmarking novel approaches for modelling species range dynamics.
Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E
2016-08-01
Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches
Modeling human spine using dynamic spline approach for vibrational simulation
NASA Astrophysics Data System (ADS)
Valentini, Pier Paolo
2012-12-01
This paper deals with the description of an innovative numerical dynamic model of the human spine for vibrational behavior assessment. The modeling approach is based on the use of the dynamic spline formalism in order to achieve a condensed description requiring a smaller set of variables but maintaining the nonlinear characteristic and the accuracy of a fully multibody dynamic model. The methodology has been validated by comparing the modal behavior of the spine sub-assembly to other models available in literature. Moreover, the proposed dynamic sub-system has been integrated into a two dimensional multibody model of a seated vehicle occupant in order to compute the seat-to-head transmissibility. This characteristic has been compared to those obtained using other spine sub-models. Both modal behavior and acceleration transmissibility computed with the proposed approach show a very good accordance with others coming from more complex models.
Multicomponent aerosol dynamics model UHMA: model development and validation
NASA Astrophysics Data System (ADS)
Korhonen, H.; Lehtinen, K. E. J.; Kulmala, M.
2004-05-01
A size-segregated aerosol dynamics model UHMA (University of Helsinki Multicomponent Aerosol model) was developed for studies of multicomponent tropospheric aerosol particles. The model includes major aerosol microphysical processes in the atmosphere with a focus on new particle formation and growth; thus it incorporates particle coagulation and multicomponent condensation, applying a revised treatment of condensation flux onto free molecular regime particles and the activation of nanosized clusters by organic vapours (Nano-Köhler theory), as well as recent parameterizations for binary H2SO4-H2O and ternary H2SO4-NH3-H2O homogeneous nucleation and dry deposition. The representation of particle size distribution can be chosen from three sectional methods: the hybrid method, the moving center method, and the retracking method in which moving sections are retracked to a fixed grid after a certain time interval. All these methods can treat particle emissions and atmospheric transport consistently, and are therefore suitable for use in large scale atmospheric models. In a test simulation against an accurate high resolution solution, all the methods showed reasonable treatment of new particle formation with 20 size sections although the hybrid and the retracking methods suffered from artificial widening of the distribution. The moving center approach, on the other hand, showed extra dents in the particle size distribution and failed to predict the onset of detectable particle formation. In a separate test simulation of an observed nucleation event, the model captured the key qualitative behaviour of the system well. Furthermore, its prediction of the organic volume fraction in newly formed particles, suggesting values as high as 0.5 for 3-4 nm particles and approximately 0.8 for 10 nm particles, agrees with recent indirect composition measurements.
Dynamics and kinetics of model biological systems
NASA Astrophysics Data System (ADS)
Mirigian, Stephen
In this work we study three systems of biological interest: the translocation of a heterogeneously charged polymer through an infinitely thin pore, the wrapped of a rigid particle by a soft vesicle and the modification of the dynamical properties of a gel due to the presence of rigid inclusions. We study the kinetics of translocation for a heterogeneously charged polyelectrolyte through an infinitely narrow pore using the Fokker-Planck formalism to compute mean first passage times, the probability of successful translocation, and the mean successful translocation time for a diblock copolymer. We find, in contrast to the homopolymer result, that details of the boundary conditions lead to qualitatively different behavior. Under experimentally relevant conditions for a diblock copolymer we find that there is a threshold length of the charged block, beyond which the probability of successful translocation is independent of charge fraction. Additionally, we find that mean successful translocation time exhibits non-monotonic behavior with increasing length of the charged fraction; there is an optimum length of the charged block where the mean successful translocation time is slowest and there can be a substantial range of charge fraction where it is slower than a minimally charged chain. For a fixed total charge on the chain, we find that finer distributions of the charge along the chain leads to a significant reduction in mean translocation time compared to the diblock distribution. Endocytosis is modeled using a simple geometrical model from the literature. We map the process of wrapping a rigid spherical bead onto a one-dimensional stochastic process described by the Fokker-Planck equation to compute uptake rates as a function of membrane properties and system geometry. We find that simple geometrical considerations pick an optimal particle size for uptake and a corresponding maximal uptake rate, which can be controlled by altering the material properties of the
A tribo-dynamic model of a spur gear pair
NASA Astrophysics Data System (ADS)
Li, S.; Kahraman, A.
2013-09-01
In this study, a tribo-dynamics model for spur gear pairs is proposed. The model couples a mixed elastohydrodynamic lubrication model of a spur gear pair with a transverse-torsional dynamic model. The lubrication model provides the dynamic model with friction forces and moments that couple the vibrations of the gears along the off-line-of-action direction to other gear vibrations. In addition, it predicts damping coefficient at the gear mesh in a physics-based manner from the energy loss associated with viscous shearing across the fluid film. In return, the dynamic model predicts the dynamic tooth forces and surface velocities to be used in the lubrication model. An iterative computational scheme is proposed to implement the lubrication and dynamics models simultaneously to couple tribological and dynamic behaviors of a spur gear pair fully. An example gear pair is analyzed using the proposed model to demonstrate this two-way relationship and quantify the impact of operating conditions, surface roughness and lubrication characteristics on the tribo-dynamics response. Dynamic gear mesh tooth forces predicted by the dynamic model are used in the EHL model as the loading. Surface velocity fluctuations due to gear vibrations are included in the EHL formulation in the definition of rolling and sliding velocities as well as non-Newtonian flow coefficients. A physics-based, time-varying, viscous gear mesh damping is defined from the EHL formulations to be used in the dynamic model along the OLOA direction. Since the EHL model considers rough surfaces, the roughness effects in addition to the operating speed, load and temperature effects are all included in the gear mesh damping. Time-varying friction forces acting in the OLOA direction and friction moments acting in torsional direction are computed from the EHL model to be used in the dynamic model to couple LOA and OLOA motions properly. Effects of surface roughness and operating speed, load and temperature conditions on
Embedding dynamical networks into distributed models
NASA Astrophysics Data System (ADS)
Innocenti, Giacomo; Paoletti, Paolo
2015-07-01
Large networks of interacting dynamical systems are well-known for the complex behaviours they are able to display, even when each node features a quite simple dynamics. Despite examples of such networks being widespread both in nature and in technological applications, the interplay between the local and the macroscopic behaviour, through the interconnection topology, is still not completely understood. Moreover, traditional analytical methods for dynamical response analysis fail because of the intrinsically large dimension of the phase space of the network which makes the general problem intractable. Therefore, in this paper we develop an approach aiming to condense all the information in a compact description based on partial differential equations. By focusing on propagative phenomena, rigorous conditions under which the original network dynamical properties can be successfully analysed within the proposed framework are derived as well. A network of Fitzhugh-Nagumo systems is finally used to illustrate the effectiveness of the proposed method.
Towse, John Nicholas; Towse, Andrea Sarah; Saito, Satoru; Maehara, Yukio; Miyake, Akira
2016-01-01
Generating random number sequences is a popular psychological task often used to measure executive functioning. We explore random generation under “joint cognition” instructions; pairs of participants take turns to compile a shared response sequence. Across three studies, we point to six key findings from this novel format. First, there are both costs and benefits from group performance. Second, repetition avoidance occurs in dyadic as well as individual production settings. Third, individuals modify their choices in a dyadic situation such that the pair becomes the unit of psychological function. Fourth, there is immediate contagion of sequence stereotypy amongst the pairs (i.e., each contributor “owns” their partner’s response). Fifth, dyad effects occur even when participants know their partner is not interacting with them (Experiment 2). Sixth, ironically, directing participants’ efforts away from their shared task responsibility can actually benefit conjoint performance (Experiment 3). These results both constrain models of random generation and illuminate processes of joint cognition. PMID:26977923
Dynamic Modeling in Solid-Oxide Fuel Cells Controller Design
Lu, Ning; Li, Qinghe; Sun, Xin; Khaleel, Mohammad A.
2007-06-28
In this paper, a dynamic model of the solid-oxide fuel cell (SOFC) power unit is developed for the purpose of designing a controller to regulate fuel flow rate, fuel temperature, air flow rate, and air temperature to maintain the SOFC stack temperature, fuel utilization rate, and voltage within operation limits. A lumped model is used to consider the thermal dynamics and the electro-chemial dynamics inside an SOFC power unit. The fluid dynamics at the fuel and air inlets are considered by using the in-flow ramp-rates.
The Rigid-Flexible System Dynamics Model of Highline Cable
NASA Astrophysics Data System (ADS)
Xing, Daoqi; Li, Nan; Zhang, Shiyun
The paper researches rigid flexible system dynamics model of the rope, and used it to simulate sealift Highline based on the multi-body dynamics theory. Meanwhile the paper simulated to the sea dry cargo replenishment of transverse process, then gain the conclusion that the rigid flexible dynamic model get in the paper is more close to the Caucasus, and the dynamic calculation results closer to the actual situation, through the analysis of simulation results, and combined with the actual situation in the Caucasus the structure of overhead cable.
Modelling and Analysis of a New Piezoelectric Dynamic Balance Regulator
Du, Zhe; Mei, Xue-Song; Xu, Mu-Xun
2012-01-01
In this paper, a new piezoelectric dynamic balance regulator, which can be used in motorised spindle systems, is presented. The dynamic balancing adjustment mechanism is driven by an in-plane bending vibration from an annular piezoelectric stator excited by a high-frequency sinusoidal input voltage. This device has different construction, characteristics and operating principles than a conventional balance regulator. In this work, a dynamic model of the regulator is first developed using a detailed analytical method. Thereafter, MATLAB is employed to numerically simulate the relations between the dominant parameters and the characteristics of the regulator based on thedynamic model. Finally, experimental measurements are used to certify the validity of the dynamic model. Consequently, the mathematical model presented and analysed in this paper can be used as a tool for optimising the design of a piezoelectric dynamic balance regulator during steady state operation. PMID:23202182
Developing a Dynamic Pharmacophore Model for HIV-1 Integrase
Carlson, Heather A.; Masukawa, Keven M.; Rubins, Kathleen; Bushman, Frederic; Jorgensen, William L.; Lins, Roberto; Briggs, James; Mccammon, Andy
2000-05-11
We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of ''dynamic'' pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is a multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a ''static'' pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors.
Developing a dynamic pharmacophore model for HIV-1 integrase.
Carlson, H A; Masukawa, K M; Rubins, K; Bushman, F D; Jorgensen, W L; Lins, R D; Briggs, J M; McCammon, J A
2000-06-01
We present the first receptor-based pharmacophore model for HIV-1 integrase. The development of "dynamic" pharmacophore models is a new method that accounts for the inherent flexibility of the active site and aims to reduce the entropic penalties associated with binding a ligand. Furthermore, this new drug discovery method overcomes the limitation of an incomplete crystal structure of the target protein. A molecular dynamics (MD) simulation describes the flexibility of the uncomplexed protein. Many conformational models of the protein are saved from the MD simulations and used in a series of multi-unit search for interacting conformers (MUSIC) simulations. MUSIC is a multiple-copy minimization method, available in the BOSS program; it is used to determine binding regions for probe molecules containing functional groups that complement the active site. All protein conformations from the MD are overlaid, and conserved binding regions for the probe molecules are identified. Those conserved binding regions define the dynamic pharmacophore model. Here, the dynamic model is compared to known inhibitors of the integrase as well as a three-point, ligand-based pharmacophore model from the literature. Also, a "static" pharmacophore model was determined in the standard fashion, using a single crystal structure. Inhibitors thought to bind in the active site of HIV-1 integrase fit the dynamic model but not the static model. Finally, we have identified a set of compounds from the Available Chemicals Directory that fit the dynamic pharmacophore model, and experimental testing of the compounds has confirmed several new inhibitors. PMID:10841789
Collision model for non-Markovian quantum dynamics
NASA Astrophysics Data System (ADS)
Kretschmer, Silvan; Luoma, Kimmo; Strunz, Walter T.
2016-07-01
We study the applicability of collisional models for non-Markovian dynamics of open quantum systems. By allowing interactions between the separate environmental degrees of freedom in between collisions we are able to construct a collision model that allows us to study quantum memory effects in open system dynamics. We also discuss the possibility to embed non-Markovian collision model dynamics into Markovian collision model dynamics in an extended state space. As a concrete example we show how, using the proposed class of collision models, we can discretely model non-Markovian amplitude damping of a qubit. In the time-continuous limit, we obtain the well-known results for spontaneous decay of a two-level system into a structured zero-temperature reservoir.
Comparisons of Four Methods for Estimating a Dynamic Factor Model
ERIC Educational Resources Information Center
Zhang, Zhiyong; Hamaker, Ellen L.; Nesselroade, John R.
2008-01-01
Four methods for estimating a dynamic factor model, the direct autoregressive factor score (DAFS) model, are evaluated and compared. The first method estimates the DAFS model using a Kalman filter algorithm based on its state space model representation. The second one employs the maximum likelihood estimation method based on the construction of a…
NASA Astrophysics Data System (ADS)
Dass, W.; Merkle, D. H.; Bratton, J. L.
1983-04-01
Constitutive modeling of cohesionless soil for both standard static test conditions and insitu impulsive dynamic load conditions is discussed in this annual report. Predicted laboratory response for several different types of models is evaluated using data from a coordinated testing program. The modeling of insitu soil response to explosive events (CIST and DISC Test) is considered, and the laboratory-derived models are tested for their convenience and accuracy in predicting ground motions. Several important laboratory and insitu phenomena which were not reflected by the model exercises are discussed. Based on the conclusions from this study, testing and modeling requirements for dynamic loading situations are proposed.
Model based control of dynamic atomic force microscope
Lee, Chibum; Salapaka, Srinivasa M.
2015-04-15
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H{sub ∞} control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments.
Model based control of dynamic atomic force microscope.
Lee, Chibum; Salapaka, Srinivasa M
2015-04-01
A model-based robust control approach is proposed that significantly improves imaging bandwidth for the dynamic mode atomic force microscopy. A model for cantilever oscillation amplitude and phase dynamics is derived and used for the control design. In particular, the control design is based on a linearized model and robust H(∞) control theory. This design yields a significant improvement when compared to the conventional proportional-integral designs and verified by experiments. PMID:25933864
Modeling river plume dynamics with the HYbrid Coordinate Ocean Model
NASA Astrophysics Data System (ADS)
Schiller, Rafael V.; Kourafalou, Vassiliki H.
The dynamics of large-scale river plumes are investigated in idealized numerical experiments using the HYbrid Coordinate Ocean Model (HYCOM). The focus of this study is to address how the development and structure of a buoyant plume are affected by the outflow properties, as impacted by processes within the estuary and at the point of discharge to the coastal basin. Changes in the outflow properties involved vertical and horizontal redistribution of the river inflow and enhanced vertical mixing inside an idealized estuary. The development of the buoyant plume was evaluated in a rectangular, f-plane basin with flat and sloping bottom conditions and in the absence of other external forcing. The general behavior of a mid-latitude river plume was reproduced, with the development of a surface anticyclonic bulge off the estuary mouth and a surface along-shore coastal current which flows in the direction of Kelvin wave propagation ("downstream"); the momentum balance was predominantly geostrophic. Conditions within the estuary and the outflow properties at the river mouth (where observed profiles may be available) greatly impacted the fate of riverine waters. In flat bottom conditions, larger mixing at the freshwater source enhanced the estuarine gravitational circulation, promoting larger upward entrainment and stronger outflow velocities. Although the overall geostrophic balance was maintained, estuarine mixing led to an asymmetry of the currents reaching the river mouth and to a sharp anticyclonic veering within the estuary, resulting in reduced upstream flow and enhanced downstream coastal current. These patterns were altered when the plumes evolved in the presence of a bottom slope. The anticyclonic veering of the buoyant outflow was suppressed, the offshore intrusion decreased and the recirculating bulge was displaced upstream. The sloping bottom impacts were accompanied by enhanced transport and increased downstream extent of the coastal current in most cases. No
A simplified dynamic model of the T700 turboshaft engine
NASA Technical Reports Server (NTRS)
Duyar, Ahmet; Gu, Zhen; Litt, Jonathan S.
1992-01-01
A simplified open-loop dynamic model of the T700 turboshaft engine, valid within the normal operating range of the engine, is developed. This model is obtained by linking linear state space models obtained at different engine operating points. Each linear model is developed from a detailed nonlinear engine simulation using a multivariable system identification and realization method. The simplified model may be used with a model-based real time diagnostic scheme for fault detection and diagnostics, as well as for open loop engine dynamics studies and closed loop control analysis utilizing a user generated control law.
Dynamical models of a sample of Population II stars
NASA Astrophysics Data System (ADS)
Levison, H. F.; Richstone, D. O.
1986-09-01
Dynamical models are constructed in order to investigate the implications of recent kinematic data of distant Population II stars on the emissivity distribution of those stars. Models are constructed using a modified Schwarzschild method in two extreme scale-free potentials, spherical and E6 elliptical. Both potentials produce flat rotation curves and velocity dispersion profiles. In all models, the distribution of stars in this sample is flat. Moreover, it is not possible to construct a model with a strictly spheroidal emissivity distribution. Most models have dimples at the poles. The dynamics of the models indicate that the system is supported by both the third integral and z angular momentum.
Branching dynamics of viral information spreading.
Iribarren, José Luis; Moro, Esteban
2011-10-01
Despite its importance for rumors or innovations propagation, peer-to-peer collaboration, social networking, or marketing, the dynamics of information spreading is not well understood. Since the diffusion depends on the heterogeneous patterns of human behavior and is driven by the participants' decisions, its propagation dynamics shows surprising properties not explained by traditional epidemic or contagion models. Here we present a detailed analysis of our study of real viral marketing campaigns where tracking the propagation of a controlled message allowed us to analyze the structure and dynamics of a diffusion graph involving over 31,000 individuals. We found that information spreading displays a non-Markovian branching dynamics that can be modeled by a two-step Bellman-Harris branching process that generalizes the static models known in the literature and incorporates the high variability of human behavior. It explains accurately all the features of information propagation under the "tipping point" and can be used for prediction and management of viral information spreading processes. PMID:22181236
Boxer, Paul; Guerra, Nancy G; Huesmann, L Rowell; Morales, Julie
2005-06-01
Examined peer contagion in small group, selected prevention programming over one school year. Participants were boys and girls in grades 3 (46 groups, 285 students) and 6 (36 groups, 219 students) attending school in low-resource, inner city communities or moderate resource urban communities. Three-level hierarchical linear modeling (observations within individuals within groups) indicated that individual change in aggression over time related to the average aggression of others in the intervention group. The individual child was "pulled" toward peers' mean level of aggression; so the intervention appeared to reduce aggression for those high on aggression, and to make those low on aggression more aggressive. Effects appeared to be magnified in either direction when the child was more discrepant from his or her peers. From these results we derive a principle of "discrepancy-proportional peer-influence" for small group intervention, and discuss the implications of this for aggregating aggressive children in small group programs. PMID:15957560
Subcycled dynamics in the Spectral Community Atmosphere Model, version 4
Taylor, Mark; Evans, Katherine J; Hack, James J; Worley, Patrick H
2010-01-01
To gain computational efficiency, a split explicit time integration scheme has been implemented in the CAM spectral Eulerian dynamical core. In this scheme, already present in other dynamical core options within the Community Atmosphere Model, version 4 (CAM), the fluid dynamics portion of the model is subcycled to allow a longer time step for the parameterization schemes. The physics parameterization of CAM is not subject to the stability restrictions of the fluid dynamics, and thus finer spatial resolutions of the model do not require the physics time step to be reduced. A brief outline of the subcycling algorithm implementation and resulting model efficiency improvement is presented. A discussion regarding the effect of the climate statistics derived from short model runs is provided.
Fractional-order in a macroeconomic dynamic model
NASA Astrophysics Data System (ADS)
David, S. A.; Quintino, D. D.; Soliani, J.
2013-10-01
In this paper, we applied the Riemann-Liouville approach in order to realize the numerical simulations to a set of equations that represent a fractional-order macroeconomic dynamic model. It is a generalization of a dynamic model recently reported in the literature. The aforementioned equations have been simulated for several cases involving integer and non-integer order analysis, with some different values to fractional order. The time histories and the phase diagrams have been plotted to visualize the effect of fractional order approach. The new contribution of this work arises from the fact that the macroeconomic dynamic model proposed here involves the public sector deficit equation, which renders the model more realistic and complete when compared with the ones encountered in the literature. The results reveal that the fractional-order macroeconomic model can exhibit a real reasonable behavior to macroeconomics systems and might offer greater insights towards the understanding of these complex dynamic systems.
Generic solar photovoltaic system dynamic simulation model specification.
Ellis, Abraham; Behnke, Michael Robert; Elliott, Ryan Thomas
2013-10-01
This document is intended to serve as a specification for generic solar photovoltaic (PV) system positive-sequence dynamic models to be implemented by software developers and approved by the WECC MVWG for use in bulk system dynamic simulations in accordance with NERC MOD standards. Two specific dynamic models are included in the scope of this document. The first, a Central Station PV System model, is intended to capture the most important dynamic characteristics of large scale (> 10 MW) PV systems with a central Point of Interconnection (POI) at the transmission level. The second, a Distributed PV System model, is intended to represent an aggregation of smaller, distribution-connected systems that comprise a portion of a composite load that might be modeled at a transmission load bus.