Critical Behaviors in Contagion Dynamics
NASA Astrophysics Data System (ADS)
Böttcher, L.; Nagler, J.; Herrmann, H. J.
2017-02-01
We study the critical behavior of a general contagion model where nodes are either active (e.g., with opinion A , or functioning) or inactive (e.g., with opinion B , or damaged). The transitions between these two states are determined by (i) spontaneous transitions independent of the neighborhood, (ii) transitions induced by neighboring nodes, and (iii) spontaneous reverse transitions. The resulting dynamics is extremely rich including limit cycles and random phase switching. We derive a unifying mean-field theory. Specifically, we analytically show that the critical behavior of systems whose dynamics is governed by processes (i)-(iii) can only exhibit three distinct regimes: (a) uncorrelated spontaneous transition dynamics, (b) contact process dynamics, and (c) cusp catastrophes. This ends a long-standing debate on the universality classes of complex contagion dynamics in mean field and substantially deepens its mathematical understanding.
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…
Clustering determines the dynamics of complex contagions in multiplex networks
NASA Astrophysics Data System (ADS)
Zhuang, Yong; Arenas, Alex; Yaǧan, Osman
2017-01-01
We present the mathematical analysis of generalized complex contagions in a class of clustered multiplex networks. The model is intended to understand spread of influence, or any other spreading process implying a threshold dynamics, in setups of interconnected networks with significant clustering. The contagion is assumed to be general enough to account for a content-dependent linear threshold model, where each link type has a different weight (for spreading influence) that may depend on the content (e.g., product, rumor, political view) that is being spread. Using the generating functions formalism, we determine the conditions, probability, and expected size of the emergent global cascades. This analysis provides a generalization of previous approaches and is especially useful in problems related to spreading and percolation. The results present nontrivial dependencies between the clustering coefficient of the networks and its average degree. In particular, several phase transitions are shown to occur depending on these descriptors. Generally speaking, our findings reveal that increasing clustering decreases the probability of having global cascades and their size, however, this tendency changes with the average degree. There exists a certain average degree from which on clustering favors the probability and size of the contagion. By comparing the dynamics of complex contagions over multiplex networks and their monoplex projections, we demonstrate that ignoring link types and aggregating network layers may lead to inaccurate conclusions about contagion dynamics, particularly when the correlation of degrees between layers is high.
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.
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
Contagion spreading on complex networks with local deterministic dynamics
NASA Astrophysics Data System (ADS)
Manshour, Pouya; Montakhab, Afshin
2014-07-01
Typically, contagion strength is modeled by a transmission rate λ, whereby all nodes in a network are treated uniformly in a mean-field approximation. However, local agents react differently to the same contagion based on their local characteristics. Following our recent work (Montakhab and Manshour, 2012 [42]), we investigate contagion spreading models with local dynamics on complex networks. We therefore quantify contagions by their quality, 0⩽α⩽1, and follow their spreading as their transmission condition (fitness) is evaluated by local agents. Instead of considering stochastic dynamics, here we consider various deterministic local rules. We find that initial spreading with exponential quality-dependent time scales is followed by a stationary state with a prevalence depending on the quality of the contagion. We also observe various interesting phenomena, for example, high prevalence without the participation of the hubs. This special feature of our "threshold rule" provides a mechanism for high prevalence spreading without the participation of "super-spreaders", in sharp contrast with many standard mechanism of spreading where hubs are believed to play the central role. On the other hand, if local nodes act as agents who stop the transmission once a threshold is reached, we find that spreading is severely hindered in a heterogeneous population while in a homogeneous one significant spreading may occur. We further decouple local characteristics from underlying topology in order to study the role of network topology in various models and find that as long as small-world effect exists, the underlying topology does not contribute to the final stationary state but only affects the initial spreading velocity.
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.
A model for the contagion and herding
NASA Astrophysics Data System (ADS)
Caetano, Marco Antonio Leonel; Yoneyama, Takashi
2011-11-01
This work concerns the modeling of contagion and herding effects which can cause significant movements of prices and volatilities. The idea is to adapt some concepts borrowed from the Biological Sciences and that have emerged as useful analogies to model a variety of phenomena in a large variety of fields such as Engineering and Economics. In this work, the allegory of interacting particles is used to describe the contagion and emergence of herding behavior of financial agents leading to the formation of clusters. The main idea is to adapt the schemes originally employed in particle swarm optimization algorithms, together with the concepts of leaders and followers. As an illustration of the applicability of the proposed model, a case study is presented using data from the World Bank.
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…
NASA Astrophysics Data System (ADS)
Wang, Kuan-Min; Nguyen Thi, Thanh-Binh
2007-03-01
This article is an attempt to test, through the use of forward forecasting test on dynamic conditional correlation (DCC), for contagion between Taiwan and US stocks under asymmetry. The process includes three steps. The first step uses the iterated cumulative sums of squares (ICSS) algorithm to detect the structural breaks of market return. The second step creates dummy variables for breaks, estimates EGARCH model of conditional generalized error distribution, and computes dynamic conditional correlation coefficients of DCC multivariate GARCH model. The third step employs one-step and N-step forecast test to check for contagion effect. The evidences prove the asymmetric leverage effect of Taiwan weighted stock index and New York-NYSE Composite Index. Interestingly, we discovered that there are two kinds of contagion, “positive” and “negative”, between markets.
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
Contagion: epidemiological models and financial crises.
Peckham, Robert
2014-03-01
Since the 1990s, economists have drawn on the epidemiology of emerging infectious diseases to explain the diffusion of shock through an increasingly complex financial system. The successful coordination of public health responses to disease threats, and in particular the epidemiological modelling underpinning infection control, has influenced economists' understanding of the risks posed to the stability of the financial system by 'contagion'. While the exportation of analytic models and frames of reference can be fruitful, reinvigorating the destination domain, such analogizing can have a distorting effect. There are differences between biological and financial systems. Moreover, the migration of highly context-specific epidemiological models may undermine the basis of the analogy. Finally, there may be repercussions for the efficacy of public health in the way that its aims are misconstrued in financial analyses.
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
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.
Estimation of the Heteroskedastic Canonical Contagion Model with Instrumental Variables
2016-01-01
Knowledge of contagion among economies is a relevant issue in economics. The canonical model of contagion is an alternative in this case. Given the existence of endogenous variables in the model, instrumental variables can be used to decrease the bias of the OLS estimator. In the presence of heteroskedastic disturbances this paper proposes the use of conditional volatilities as instruments. Simulation is used to show that the homoscedastic and heteroskedastic estimators which use them as instruments have small bias. These estimators are preferable in comparison with the OLS estimator and their asymptotic distribution can be used to construct confidence intervals. PMID:28030628
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.
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.
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.
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.
Sentiment Contagion Based on the Modified SOSa-SPSa Model
Song, Zhijie; Jia, Jie; Wang, Jian
2016-01-01
Sentiment contagion is similar to an infectious disease that spreads in a crowd. In this study, we extend the proposed SOSa-SPSa model (susceptible-optimistic-susceptible and susceptible-pessimistic-susceptible) by considering the interaction between optimists and pessimists. Simulation results show that our model is reasonable and can better explain the entire contagion process by considering three groups of people. The recovery speed of pessimists has an obvious regulative effect on the number of pessimists and the possibility of optimists coming in contact with pessimists to be infected as pessimism plays a greater role than that of reverting to susceptibility. The number of pessimists is positively related to the possibility that optimists come in contact with pessimists to become pessimistic but is negatively related to the possibility of the other way around. When the speed of spontaneous generation is slow, the number of pessimists sharply increases. However, the increase is not so apparent when the speed of spontaneous generation reaches a certain number. PMID:27746827
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.
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
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.
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.
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.
Limitations of discrete-time approaches to continuous-time contagion dynamics
NASA Astrophysics Data System (ADS)
Fennell, Peter G.; Melnik, Sergey; Gleeson, James P.
2016-11-01
Continuous-time Markov process models of contagions are widely studied, not least because of their utility in predicting the evolution of real-world contagions and in formulating control measures. It is often the case, however, that discrete-time approaches are employed to analyze such models or to simulate them numerically. In such cases, time is discretized into uniform steps and transition rates between states are replaced by transition probabilities. In this paper, we illustrate potential limitations to this approach. We show how discretizing time leads to a restriction on the values of the model parameters that can accurately be studied. We examine numerical simulation schemes employed in the literature, showing how synchronous-type updating schemes can bias discrete-time formalisms when compared against continuous-time formalisms. Event-based simulations, such as the Gillespie algorithm, are proposed as optimal simulation schemes both in terms of replicating the continuous-time process and computational speed. Finally, we show how discretizing time can affect the value of the epidemic threshold for large values of the infection rate and the recovery rate, even if the ratio between the former and the latter is small.
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.
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…
Social contagions on interdependent lattice networks
NASA Astrophysics Data System (ADS)
Shu, Panpan; Gao, Lei; Zhao, Pengcheng; Wang, Wei; Stanley, H. Eugene
2017-03-01
Although an increasing amount of research is being done on the dynamical processes on interdependent spatial networks, knowledge of how interdependent spatial networks influence the dynamics of social contagion in them is sparse. Here we present a novel non-Markovian social contagion model on interdependent spatial networks composed of two identical two-dimensional lattices. We compare the dynamics of social contagion on networks with different fractions of dependency links and find that the density of final recovered nodes increases as the number of dependency links is increased. We use a finite-size analysis method to identify the type of phase transition in the giant connected components (GCC) of the final adopted nodes and find that as we increase the fraction of dependency links, the phase transition switches from second-order to first-order. In strong interdependent spatial networks with abundant dependency links, increasing the fraction of initial adopted nodes can induce the switch from a first-order to second-order phase transition associated with social contagion dynamics. In networks with a small number of dependency links, the phase transition remains second-order. In addition, both the second-order and first-order phase transition points can be decreased by increasing the fraction of dependency links or the number of initially-adopted nodes.
Social contagions on interdependent lattice networks.
Shu, Panpan; Gao, Lei; Zhao, Pengcheng; Wang, Wei; Stanley, H Eugene
2017-03-16
Although an increasing amount of research is being done on the dynamical processes on interdependent spatial networks, knowledge of how interdependent spatial networks influence the dynamics of social contagion in them is sparse. Here we present a novel non-Markovian social contagion model on interdependent spatial networks composed of two identical two-dimensional lattices. We compare the dynamics of social contagion on networks with different fractions of dependency links and find that the density of final recovered nodes increases as the number of dependency links is increased. We use a finite-size analysis method to identify the type of phase transition in the giant connected components (GCC) of the final adopted nodes and find that as we increase the fraction of dependency links, the phase transition switches from second-order to first-order. In strong interdependent spatial networks with abundant dependency links, increasing the fraction of initial adopted nodes can induce the switch from a first-order to second-order phase transition associated with social contagion dynamics. In networks with a small number of dependency links, the phase transition remains second-order. In addition, both the second-order and first-order phase transition points can be decreased by increasing the fraction of dependency links or the number of initially-adopted nodes.
Social contagions on interdependent lattice networks
Shu, Panpan; Gao, Lei; Zhao, Pengcheng; Wang, Wei; Stanley, H. Eugene
2017-01-01
Although an increasing amount of research is being done on the dynamical processes on interdependent spatial networks, knowledge of how interdependent spatial networks influence the dynamics of social contagion in them is sparse. Here we present a novel non-Markovian social contagion model on interdependent spatial networks composed of two identical two-dimensional lattices. We compare the dynamics of social contagion on networks with different fractions of dependency links and find that the density of final recovered nodes increases as the number of dependency links is increased. We use a finite-size analysis method to identify the type of phase transition in the giant connected components (GCC) of the final adopted nodes and find that as we increase the fraction of dependency links, the phase transition switches from second-order to first-order. In strong interdependent spatial networks with abundant dependency links, increasing the fraction of initial adopted nodes can induce the switch from a first-order to second-order phase transition associated with social contagion dynamics. In networks with a small number of dependency links, the phase transition remains second-order. In addition, both the second-order and first-order phase transition points can be decreased by increasing the fraction of dependency links or the number of initially-adopted nodes. PMID:28300198
An Information Perception-Based Emotion Contagion Model for Fire Evacuation
NASA Astrophysics Data System (ADS)
Liu, Ting Ting; Liu, Zhen; Ma, Minhua; Xuan, Rongrong; Chen, Tian; Lu, Tao; Yu, Lipeng
2017-03-01
In fires, people are easier to lose their mind. Panic will lead to irrational behavior and irreparable tragedy. It has great practical significance to make contingency plans for crowd evacuation in fires. However, existing studies about crowd simulation always paid much attention on the crowd density, but little attention on emotional contagion that may cause a panic. Based on settings about information space and information sharing, this paper proposes an emotional contagion model for crowd in panic situations. With the proposed model, a behavior mechanism is constructed for agents in the crowd and a prototype of system is developed for crowd simulation. Experiments are carried out to verify the proposed model. The results showed that the spread of panic not only related to the crowd density and the individual comfort level, but also related to people's prior knowledge of fire evacuation. The model provides a new way for safety education and evacuation management. It is possible to avoid and reduce unsafe factors in the crowd with the lowest cost.
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.
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
A model of contagion through competition in the aggressive behaviors of elementary school students.
Warren, Keith; Schoppelrey, Susan; Moberg, D Paul; McDonald, Marilyn
2005-06-01
This article extends the work of Kellam, Ling, Merisca, Brown and Ialongo (1998) by applying a mathematical model of competition between children to peer contagion in the aggressive behaviors of elementary school students. Nonlinearity in the relationship between group aggression and individual aggression at 2-year follow-up is present. Consistent with the findings of Kellam et al. (1998), hierarchical linear modeling indicates that the relationship is statistically significant for those students whose initial parental ratings of aggressive behavior were above the sample median. In the context of competition between students, the behavior of initially aggressive students may be negatively reinforced. Lowering aggression in the school environment may therefore be the most effective way to lower the level of these students' aggressive behavior.
Dueling biological and social contagions.
Fu, Feng; Christakis, Nicholas A; Fowler, James H
2017-03-02
Numerous models explore how a wide variety of biological and social phenomena spread in social networks. However, these models implicitly assume that the spread of one phenomenon is not affected by the spread of another. Here, we develop a model of "dueling contagions", with a particular illustration of a situation where one is biological (influenza) and the other is social (flu vaccination). We apply the model to unique time series data collected during the 2009 H1N1 epidemic that includes information about vaccination, flu, and face-to-face social networks. The results show that well-connected individuals are more likely to get vaccinated, as are people who are exposed to friends who get vaccinated or are exposed to friends who get the flu. Our dueling contagion model suggests that other epidemiological models may be dramatically underestimating the R0 of contagions. It also suggests that the rate of vaccination contagion may be even more important than the biological contagion in determining the course of the disease. These results suggest that real world and online platforms that make it easier to see when friends have been vaccinated (personalized vaccination campaigns) and when they get the flu (personalized flu warnings) could have a large impact on reducing the severity of epidemics. They also suggest possible benefits from understanding the coevolution of many kinds of dueling contagions.
Dueling biological and social contagions
Fu, Feng; Christakis, Nicholas A.; Fowler, James H.
2017-01-01
Numerous models explore how a wide variety of biological and social phenomena spread in social networks. However, these models implicitly assume that the spread of one phenomenon is not affected by the spread of another. Here, we develop a model of “dueling contagions”, with a particular illustration of a situation where one is biological (influenza) and the other is social (flu vaccination). We apply the model to unique time series data collected during the 2009 H1N1 epidemic that includes information about vaccination, flu, and face-to-face social networks. The results show that well-connected individuals are more likely to get vaccinated, as are people who are exposed to friends who get vaccinated or are exposed to friends who get the flu. Our dueling contagion model suggests that other epidemiological models may be dramatically underestimating the R0 of contagions. It also suggests that the rate of vaccination contagion may be even more important than the biological contagion in determining the course of the disease. These results suggest that real world and online platforms that make it easier to see when friends have been vaccinated (personalized vaccination campaigns) and when they get the flu (personalized flu warnings) could have a large impact on reducing the severity of epidemics. They also suggest possible benefits from understanding the coevolution of many kinds of dueling contagions. PMID:28252663
Dueling biological and social contagions
NASA Astrophysics Data System (ADS)
Fu, Feng; Christakis, Nicholas A.; Fowler, James H.
2017-03-01
Numerous models explore how a wide variety of biological and social phenomena spread in social networks. However, these models implicitly assume that the spread of one phenomenon is not affected by the spread of another. Here, we develop a model of “dueling contagions”, with a particular illustration of a situation where one is biological (influenza) and the other is social (flu vaccination). We apply the model to unique time series data collected during the 2009 H1N1 epidemic that includes information about vaccination, flu, and face-to-face social networks. The results show that well-connected individuals are more likely to get vaccinated, as are people who are exposed to friends who get vaccinated or are exposed to friends who get the flu. Our dueling contagion model suggests that other epidemiological models may be dramatically underestimating the R0 of contagions. It also suggests that the rate of vaccination contagion may be even more important than the biological contagion in determining the course of the disease. These results suggest that real world and online platforms that make it easier to see when friends have been vaccinated (personalized vaccination campaigns) and when they get the flu (personalized flu warnings) could have a large impact on reducing the severity of epidemics. They also suggest possible benefits from understanding the coevolution of many kinds of dueling contagions.
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.
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
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.
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
Choi, Jiye; Jeong, Yong
2017-01-01
Emotional contagion, a primitive form of empathy, is heightened in patients with Alzheimer’s disease (AD); however, the mechanism underlying this attribute has not been thoroughly elucidated. In this study, observational fear conditioning was performed to measure emotional contagion levels in a mouse model of AD. Simultaneous recording of local field potentials in the bilateral anterior insula, basolateral amygdala, anterior cingulate cortex, and retrosplenial cortex was also conducted to investigate related brain network changes. Consistent with the results obtained with AD patients, 11-month-old AD model mice exhibited significantly higher freezing levels in observational fear conditioning, indicating elevated emotional contagion compared to age-matched wild-type mice. Furthermore, the left anterior insula and right basolateral amygdala of 11-months-old AD model mice indicated sustained increases in synchronization when they observed the suffering of conspecifics. These changes did not appear in other age groups or wild-type controls. Additionally, the amyloid plaque burden within the anterior insula was significantly correlated with the freezing levels in observational fear conditioning. Taken together, this study reveals increased and sustained network synchrony between the anterior insula and basolateral amygdala, which comprise a salience network in humans, as a potential mechanism for elevated emotional contagion in a mouse model of AD. PMID:28387348
Mixed-order phase transition in a two-step contagion model with a single infectious seed
NASA Astrophysics Data System (ADS)
Choi, Wonjun; Lee, Deokjae; Kahng, B.
2017-02-01
Percolation is known as one of the most robust continuous transitions, because its occupation rule is intrinsically local. As one of the ways to break the robustness, occupation is allowed to more than one species of particles and they occupy cooperatively. This generalized percolation model undergoes a discontinuous transition. Here we investigate an epidemic model with two contagion steps and characterize its phase transition analytically and numerically. We find that even though the order parameter jumps at a transition point rc, then increases continuously, it does not exhibit any critical behavior: the fluctuations of the order parameter do not diverge at rc. However, critical behavior appears in mean outbreak size, which diverges at the transition point in a manner that the ordinary percolation shows. Such a type of phase transition is regarded as a mixed-order phase transition. We also obtain scaling relations of cascade outbreak statistics when the order parameter jumps at rc.
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
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.
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.
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.
Controlling contagion processes in activity driven networks.
Liu, Suyu; Perra, Nicola; Karsai, Márton; Vespignani, Alessandro
2014-03-21
The vast majority of strategies aimed at controlling contagion processes on networks consider the connectivity pattern of the system either quenched or annealed. However, in the real world, many networks are highly dynamical and evolve, in time, concurrently with the contagion process. Here, we derive an analytical framework for the study of control strategies specifically devised for a class of time-varying networks, namely activity-driven networks. We develop a block variable mean-field approach that allows the derivation of the equations describing the coevolution of the contagion process and the network dynamic. We derive the critical immunization threshold and assess the effectiveness of three different control strategies. Finally, we validate the theoretical picture by simulating numerically the spreading process and control strategies in both synthetic networks and a large-scale, real-world, mobile telephone call data set.
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.
Eye movements may cause motor contagion effects.
Constable, Merryn D; de Grosbois, John; Lung, Tiffany; Tremblay, Luc; Pratt, Jay; Welsh, Timothy N
2016-10-26
When a person executes a movement, the movement is more errorful while observing another person's actions that are incongruent rather than congruent with the executed action. This effect is known as "motor contagion". Accounts of this effect are often grounded in simulation mechanisms: increased movement error emerges because the motor codes associated with observed actions compete with motor codes of the goal action. It is also possible, however, that the increased movement error is linked to eye movements that are executed simultaneously with the hand movement because oculomotor and manual-motor systems are highly interconnected. In the present study, participants performed a motor contagion task in which they executed horizontal arm movements while observing a model making either vertical (incongruent) or horizontal (congruent) movements under three conditions: no instruction, maintain central fixation, or track the model's hand with the eyes. A significant motor contagion-like effect was only found in the 'track' condition. Thus, 'motor contagion' in the present task may be an artifact of simultaneously executed incongruent eye movements. These data are discussed in the context of stimulation and associative learning theories, and raise eye movements as a critical methodological consideration for future work on motor contagion.
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
2012-01-01
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
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.
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.
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
The simple rules of social contagion.
Hodas, Nathan O; Lerman, Kristina
2014-03-11
It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior.
The Simple Rules of Social Contagion
Hodas, Nathan O.; Lerman, Kristina
2014-01-01
It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior. PMID:24614301
Haak, Danielle M; Fath, Brian D; Forbes, Valery E; Martin, Dustin R; Pope, Kevin L
2017-04-01
Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensis alters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems.
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.
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.
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
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.
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…
Complex contagion process in spreading of online innovation.
Karsai, Márton; Iñiguez, Gerardo; Kaski, Kimmo; Kertész, János
2014-12-06
Diffusion of innovation can be interpreted as a social spreading phenomenon governed by the impact of media and social interactions. Although these mechanisms have been identified by quantitative theories, their role and relative importance are not entirely understood, as empirical verification has so far been hindered by the lack of appropriate data. Here we analyse a dataset recording the spreading dynamics of the world's largest Voice over Internet Protocol service to empirically support the assumptions behind models of social contagion. We show that the rate of spontaneous service adoption is constant, the probability of adoption via social influence is linearly proportional to the fraction of adopting neighbours, and the rate of service termination is time-invariant and independent of the behaviour of peers. By implementing the detected diffusion mechanisms into a dynamical agent-based model, we are able to emulate the adoption dynamics of the service in several countries worldwide. This approach enables us to make medium-term predictions of service adoption and disclose dependencies between the dynamics of innovation spreading and the socio-economic development of a country.
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.
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 50,000 elites and examine how connectivity among previous donors reinforces contagion. We find that the diffusion of donations is driven by independent reinforcement contagion: people are more likely to donate when exposed to donors from different social groups than when they are exposed to equally many donors from the same group. Counter-intuitively, being exposed to one side may increase donations to the other side. Although the effect is weak, simultaneous cross-cutting exposure makes donation somewhat less likely. Finally, the independence of donors in the beginning of a campaign predicts the amount of money that is raised throughout a campaign. We theorize that people infer population-wide estimates from their local observations, with elites assessing the viability of candidates, possibly opposing candidates in response to local support. Our findings suggest that theories of complex contagions need refinement and that political campaigns should target multiple communities.
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
Preferred pathways of behavioral contagion.
Jones, M B; Jones, D R
1995-01-01
A behavioral disorder is "contagious" if the risk to a given individual increases when someone in that person's vicinity, family, or social group develops the disorder. So understood, behavioral contagion may be involved in criminality, conduct disorder, drug abuse, suicide, and teenage pregnancy. Previous papers have shown that contagion generates highly distinctive result patterns, from which its presence may be inferred. The patterns concern prevalence in sibships of different size and, in case-control designs, the number of susceptible sibs that affected and unaffected individuals have. The present paper extends the analysis by allowing the likelihood of transmission from one sib to another to vary according as the two sibs are of the same or opposite gender, male or female, single borns or co-twins, fraternal or identical twins. The extension is illustrated by application to data on criminality in Danish twins previously reported by other workers. We will show that the distribution of criminality by gender and zygosity is better explained in terms of behavioral contagion than by previous analyses.
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
Contagion on complex networks with persuasion.
Huang, Wei-Min; Zhang, Li-Jie; Xu, Xin-Jian; Fu, Xinchu
2016-03-31
The threshold model has been widely adopted as a classic model for studying contagion processes on social networks. We consider asymmetric individual interactions in social networks and introduce a persuasion mechanism into the threshold model. Specifically, we study a combination of adoption and persuasion in cascading processes on complex networks. It is found that with the introduction of the persuasion mechanism, the system may become more vulnerable to global cascades, and the effects of persuasion tend to be more significant in heterogeneous networks than those in homogeneous networks: a comparison between heterogeneous and homogeneous networks shows that under weak persuasion, heterogeneous networks tend to be more robust against random shocks than homogeneous networks; whereas under strong persuasion, homogeneous networks are more stable. Finally, we study the effects of adoption and persuasion threshold heterogeneity on systemic stability. Though both heterogeneities give rise to global cascades, the adoption heterogeneity has an overwhelmingly stronger impact than the persuasion heterogeneity when the network connectivity is sufficiently dense.
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.
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.
Contagion of Cooperation in Static and Fluid Social Networks
Jordan, Jillian J.; Rand, David G.; Arbesman, Samuel; Fowler, James H.; Christakis, Nicholas A.
2013-01-01
Cooperation is essential for successful human societies. Thus, understanding how cooperative and selfish behaviors spread from person to person is a topic of theoretical and practical importance. Previous laboratory experiments provide clear evidence of social contagion in the domain of cooperation, both in fixed networks and in randomly shuffled networks, but leave open the possibility of asymmetries in the spread of cooperative and selfish behaviors. Additionally, many real human interaction structures are dynamic: we often have control over whom we interact with. Dynamic networks may differ importantly in the goals and strategic considerations they promote, and thus the question of how cooperative and selfish behaviors spread in dynamic networks remains open. Here, we address these questions with data from a social dilemma laboratory experiment. We measure the contagion of both cooperative and selfish behavior over time across three different network structures that vary in the extent to which they afford individuals control over their network ties. We find that in relatively fixed networks, both cooperative and selfish behaviors are contagious. In contrast, in more dynamic networks, selfish behavior is contagious, but cooperative behavior is not: subjects are fairly likely to switch to cooperation regardless of the behavior of their neighbors. We hypothesize that this insensitivity to the behavior of neighbors in dynamic networks is the result of subjects’ desire to attract new cooperative partners: even if many of one’s current neighbors are defectors, it may still make sense to switch to cooperation. We further hypothesize that selfishness remains contagious in dynamic networks because of the well-documented willingness of cooperators to retaliate against selfishness, even when doing so is costly. These results shed light on the contagion of cooperative behavior in fixed and fluid networks, and have implications for influence-based interventions aiming at
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.
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
A Multi-agent Simulation Tool for Micro-scale Contagion Spread Studies
Koch, Daniel B
2016-01-01
Within the disaster preparedness and emergency response community, there is interest in how contagions spread person-to-person at large gatherings and if mitigation strategies can be employed to reduce new infections. A contagion spread simulation module was developed for the Incident Management Preparedness and Coordination Toolkit that allows a user to see how a geographically accurate layout of the gathering space helps or hinders the spread of a contagion. The results can inform mitigation strategies based on changing the physical layout of an event space. A case study was conducted for a particular event to calibrate the underlying simulation model. This paper presents implementation details of the simulation code that incorporates agent movement and disease propagation. Elements of the case study are presented to show how the tool can be used.
Molenaar, Peter C M
2017-02-16
Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.
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
Thermal dynamic modeling study
NASA Technical Reports Server (NTRS)
Ojalvo, I. U.
1972-01-01
Some thermal dynamic requirements associated with the space shuttle vehicle are reviewed. Pertinent scaling laws are discussed and recommendations are offered regarding the need for conducting reduced-scale dynamic tests of major components at elevated temperatures. Items considered are the development and interpretation of thermal dynamic structural scaling laws, the identification of major related problem areas and a presentation of viable model fabrication, instrumentation, and test procedures.
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…
Paixão, Crysttian Arantes; da Costa, Antonio Tavares
2013-06-01
This paper reports the development of a simple dynamic microscopic model to describe the main features of the phenomenon known as dynamic speckle, or biospeckle. Biospeckle is an interference pattern formed when a biological surface is illuminated with coherent light. The dynamic characteristics of biospeckle have been investigated as possible tools for assessing the quality of biological products. Our model, despite its simplicity, was able to reproduce qualitatively the main features of biospeckle. We were able to correlate variations in a microscopic parameter associated with movement of the particles comprising the organic surface with changes in a macroscopic parameter that measures the change rate of a dynamic interference pattern. We showed that this correlation occurs only within a limited range of parameter microscope values. We also showed how our model was able to describe nonuniform surfaces composed of more than one type of particles.
Social contagion process in informal warning networks to understand evacuation timing behavior.
Hasan, Samiul; Ukkusuri, Satish V
2013-01-01
Individual evacuation decisions are often characterized by the influence of one's social network, referred to as informal warning network. In this article, a threshold model of social contagion, originally introduced in the network science literature, is proposed to characterize this social influence in the evacuation decision-making process, in particular the timing of evacuation decision. Simulation models are developed to investigate the effects of community mixing patterns and the strength of ties on timing of evacuation decision.
Pictures of you: Dot stimuli cause motor contagion in presence of a still human form.
Sparks, S; Sidari, M; Lyons, M; Kritikos, A
2016-10-01
In this study, we investigate which visual cues induce participants to encode a non-human motion stimulus in their motor system. Participants performed reach-to-grasp actions to a target after observing a dot moving in a direct or higher-arcing path across a screen. Dot motion occurred in the presence of a meaningless (scrambled human model) stimulus, a still human model, or a human model performing a direct or exaggeratedly curved reach to a target. Our results show that observing the dot displacement causes motor contagion (changes in the height of the observer's hand trajectory) when a human form was visually present in the background (either moving or still). No contagion was evident, however, when this human context was absent (i.e., human image scrambled and not identifiable). This indicates that visual cues suggestive of human agency can determine whether or not moving stimuli are encoded in the motor system.
Thrash, Todd M; Maruskin, Laura A; Moldovan, Emil G; Oleynick, Victoria C; Belzak, Will C
2016-04-28
A longstanding tradition in the humanities holds that a writer's inspiration is infectious, but this thesis has not been tested. We hypothesized that (a) inspiration is infectious, such that inspired writers are more inspiring to the average reader; (b) contagion is mediated by the insightfulness of the text; and (c) contagion is moderated by readers' openness to experience, such that open readers are more prone to contagion. To test these hypotheses, a sample of 195 student writers, each of whom wrote 1 poem, was crossed with a sample of 220 student readers, who read all poems. Data were available for 36,020 cells of the resulting Writer × Reader matrix. Our analytic approach integrated cross-classified multilevel modeling with conditional process analysis. As hypothesized, writers who were more inspired elicited higher levels of inspiration in the average reader. Inspiration contagion was mediated by the insightfulness and pleasantness of the text and was partially suppressed by originality. Inspiration contagion was moderated by reader openness. Moderated mediation analyses indicated that open readers were prone to contagion because they were tolerant of the originality and sublimity of inspired writing. Additional analyses differentiated contagion of inspiration from contagion of its covariates (awe, positive affect), documented effects of writer inspiration on reader enthrallment (awe, chills), and showed that writer effort is a poor predictor of reader states. The infectiousness of inspiration-through poetry, if not also through scripture and academic writing-suggests that a given instance of inspiration may have far-reaching cultural implications, including dissemination of innovations and ideologies. (PsycINFO Database Record
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.
Dynamic causal modelling revisited.
Friston, K J; Preller, Katrin H; Mathys, Chris; Cagnan, Hayriye; Heinzle, Jakob; Razi, Adeel; Zeidman, Peter
2017-02-17
This paper revisits the dynamic causal modelling of fMRI timeseries by replacing the usual (Taylor) approximation to neuronal dynamics with a neural mass model of the canonical microcircuit. This provides a generative or dynamic causal model of laminar specific responses that can generate haemodynamic and electrophysiological measurements. In principle, this allows the fusion of haemodynamic and (event related or induced) electrophysiological responses. Furthermore, it enables Bayesian model comparison of competing hypotheses about physiologically plausible synaptic effects; for example, does attentional modulation act on superficial or deep pyramidal cells - or both? In this technical note, we describe the resulting dynamic causal model and provide an illustrative application to the attention to visual motion dataset used in previous papers. Our focus here is on how to answer long-standing questions in fMRI; for example, do haemodynamic responses reflect extrinsic (afferent) input from distant cortical regions, or do they reflect intrinsic (recurrent) neuronal activity? To what extent do inhibitory interneurons contribute to neurovascular coupling? What is the relationship between haemodynamic responses and the frequency of induced neuronal activity? This paper does not pretend to answer these questions; rather it shows how they can be addressed using neural mass models of fMRI timeseries.
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.
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
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
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.
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.
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
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.
NASA Astrophysics Data System (ADS)
West, Bruce J.
The proper methodology for describing the dynamics of certain complex phenomena and fractal time series is the fractional calculus through the fractional Langevin equation discussed herein and applied in a biomedical context. We show that a fractional operator (derivative or integral) acting on a fractal function, yields another fractal function, allowing us to construct a fractional Langevin equation to describe the evolution of a fractal statistical process, for example, human gait and cerebral blood flow. The goal of this talk is to make clear how certain complex phenomena, such as those that are abundantly present in human physiology, can be faithfully described using dynamical models involving fractional differential stochastic equations. These models are tested against existing data sets and shown to describe time series from complex physiologic phenomena quite well.
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.
Motor contagion in young children: Exploring social influences on perception-action coupling.
Marshall, Peter J; Bouquet, Cédric A; Thomas, Amanda L; Shipley, Thomas F
2010-01-01
Human development occurs in a social environment in which learning is tightly coupled to the behavior of other supportive humans. One aspect of this coupling may occur through motor contagion, in which observing the actions of other people is associated with the activation of related motor representations. In order to explore the overlap between action observation and action execution in early childhood, a novel task was developed in which 4-year-old children were instructed to move a stylus on a graphics tablet in the presence of a background video which showed a model moving her arm in a direction that was either congruent or incongruent with the instructed axis of the child's stylus movements. The presence of incongruent background movements was associated with a significant interference effect on children's stylus movements. This interference effect was stronger when the background movements were performed by a same-age peer rather than by an adult. It is suggested that early childhood is a particularly interesting age period to study motor contagion, since the transition from infancy to childhood involves concurrent changes in cognitive control and in the ability to flexibly decouple perception and action. The examination of motor contagion provides an important consideration of social influences on cognitive control in early childhood--influences that have been somewhat neglected in the developmental literature on the related construct of executive functioning.
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.
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
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.
A framework for analyzing contagion in assortative banking networks
Hurd, Thomas R.; Gleeson, James P.; Melnik, Sergey
2017-01-01
We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections between banks, whereas our framework explicitly allows for (dis)assortative edge probabilities (i.e., a tendency for small banks to link to large banks). We analyze default cascades triggered by shocking the network and find that the cascade can be understood as an explicit iterated mapping on a set of edge probabilities that converges to a fixed point. We derive a cascade condition, analogous to the basic reproduction number R0 in epidemic modelling, that characterizes whether or not a single initially defaulted bank can trigger a cascade that extends to a finite fraction of the infinite network. This cascade condition is an easily computed measure of the systemic risk inherent in a given banking network topology. We use percolation theory for random networks to derive a formula for the frequency of global cascades. These analytical results are shown to provide limited quantitative agreement with Monte Carlo simulation studies of finite-sized networks. We show that edge-assortativity, the propensity of nodes to connect to similar nodes, can have a strong effect on the level of systemic risk as measured by the cascade condition. However, the effect of assortativity on systemic risk is subtle, and we propose a simple graph theoretic quantity, which we call the graph-assortativity coefficient, that can be used to assess systemic risk. PMID:28231324
[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.
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…
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…
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.…
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…
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…
Statistical fluctuations in pedestrian evacuation times and the effect of social contagion
NASA Astrophysics Data System (ADS)
Nicolas, Alexandre; Bouzat, Sebastián; Kuperman, Marcelo N.
2016-08-01
Mathematical models of pedestrian evacuation and the associated simulation software have become essential tools for the assessment of the safety of public facilities and buildings. While a variety of models is now available, their calibration and test against empirical data are generally restricted to global averaged quantities; the statistics compiled from the time series of individual escapes ("microscopic" statistics) measured in recent experiments are thus overlooked. In the same spirit, much research has primarily focused on the average global evacuation time, whereas the whole distribution of evacuation times over some set of realizations should matter. In the present paper we propose and discuss the validity of a simple relation between this distribution and the microscopic statistics, which is theoretically valid in the absence of correlations. To this purpose, we develop a minimal cellular automaton, with features that afford a semiquantitative reproduction of the experimental microscopic statistics. We then introduce a process of social contagion of impatient behavior in the model and show that the simple relation under test may dramatically fail at high contagion strengths, the latter being responsible for the emergence of strong correlations in the system. We conclude with comments on the potential practical relevance for safety science of calculations based on microscopic statistics.
Launch Vehicle Dynamics Demonstrator Model
NASA Technical Reports Server (NTRS)
1963-01-01
Launch Vehicle Dynamics Demonstrator Model. The effect of vibration on launch vehicle dynamics was studied. Conditions included three modes of instability. The film includes close up views of the simulator fuel tank with and without stability control. [Entire movie available on DVD from CASI as Doc ID 20070030984. Contact help@sti.nasa.gov
Generative models of conformational dynamics.
Langmead, Christopher James
2014-01-01
Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term 'generative' refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GRAPHICAL MODELS OF ENERGY LANDSCAPES), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc.) from long timescale simulation data.
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.
Predictive models of forest dynamics.
Purves, Drew; Pacala, Stephen
2008-06-13
Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.
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.
ERIC Educational Resources Information Center
Journal of Science and Mathematics Education in Southeast Asia, 1981
1981-01-01
Instructions (with diagrams and parts list) are provided for constructing an eye model with a pliable lens made from a plastic bottle which can vary its convexity to accommodate changing positions of an object being viewed. Also discusses concepts which the model can assist in developing. (Author/SK)
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.
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.
Respiratory Protection Provided by Five New Contagion Masks
Guyton, H. Gerald; Decker, Herbert M.
1963-01-01
The effectiveness of five recently developed contagion masks in filtering air-borne particles (1 to 5 μ diam) has been reported. One mask, available in four sizes, was 99% efficient. This mask can be reused after sterilization. The other four masks are available in only one size and are intended to be used one time only. Two of these four disposable types were more than 90% efficient but the variability of their respective test results was much greater than that for the reusable mask. The two remaining disposable types were less than 80% efficient. Two of these contagion-mask types were worn by hospital personnel for periods of up to 8 hr to determine the effect of such prolonged use on aerosol filtration efficiency. No significant decrease in filtration efficiency was noted. Physicians, nurses, and other hospital personnel who wear masks will benefit from the increased individual respiratory protection afforded by improved contagion masks. Concurrently, the incidence of hospital patient air-borne infections should be greatly reduced. Images FIG. 1 PMID:13951516
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
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
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.
Generative Models of Conformational Dynamics
Langmead, Christopher James
2014-01-01
Atomistic simulations of the conformational dynamics of proteins can be performed using either Molecular Dynamics or Monte Carlo procedures. The ensembles of three-dimensional structures produced during simulation can be analyzed in a number of ways to elucidate the thermodynamic and kinetic properties of the system. The goal of this chapter is to review both traditional and emerging methods for learning generative models from atomistic simulation data. Here, the term ‘generative’ refers to a model of the joint probability distribution over the behaviors of the constituent atoms. In the context of molecular modeling, generative models reveal the correlation structure between the atoms, and may be used to predict how the system will respond to structural perturbations. We begin by discussing traditional methods, which produce multivariate Gaussian models. We then discuss GAMELAN (GrAphical Models of Energy LANdscapes), which produces generative models of complex, non-Gaussian conformational dynamics (e.g., allostery, binding, folding, etc) from long timescale simulation data. PMID:24446358
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,…
9 CFR 85.2 - Notice relating to the existence of the contagion of pseudorabies.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Notice relating to the existence of the contagion of pseudorabies. 85.2 Section 85.2 Animals and Animal Products ANIMAL AND PLANT HEALTH... ANIMAL PRODUCTS PSEUDORABIES § 85.2 Notice relating to the existence of the contagion of...
The dynamics of coastal models
Hearn, Clifford J.
2008-01-01
Coastal basins are defined as estuaries, lagoons, and embayments. This book deals with the science of coastal basins using simple models, many of which are presented in either analytical form or Microsoft Excel or MATLAB. The book introduces simple hydrodynamics and its applications, from the use of simple box and one-dimensional models to flow over coral reefs. The book also emphasizes models as a scientific tool in our understanding of coasts, and introduces the value of the most modern flexible mesh combined wave-current models. Examples from shallow basins around the world illustrate the wonders of the scientific method and the power of simple dynamics. This book is ideal for use as an advanced textbook for graduate students and as an introduction to the topic for researchers, especially those from other fields of science needing a basic understanding of the basic ideas of the dynamics of coastal basins.
Predictive models of battle dynamics
NASA Astrophysics Data System (ADS)
Jelinek, Jan
2001-09-01
The application of control and game theories to improve battle planning and execution requires models, which allow military strategists and commanders to reliably predict the expected outcomes of various alternatives over a long horizon into the future. We have developed probabilistic battle dynamics models, whose building blocks in the form of Markov chains are derived from the first principles, and applied them successfully in the design of the Model Predictive Task Commander package. This paper introduces basic concepts of our modeling approach and explains the probability distributions needed to compute the transition probabilities of the Markov chains.
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.
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.
Dynamical Modelling of Meteoroid Streams
NASA Astrophysics Data System (ADS)
Clark, David; Wiegert, P. A.
2012-10-01
Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required questionable assumptions and significant simplifications. Extending on the approach of Vaubaillon et al. (2005)1, we model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of frequency based on model parameter changes. To assist in model analysis we are developing interactive software to permit the “turning of knobs” of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. With this tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform cometary surface attributes and temporal activity. The software uses a single model definition and implementation throughout model verification, sample particle bin generation and integration, and analysis. It supports the adjustment with feedback of both independent and independent model values, with the intent of providing an interface supporting multivariate analysis. Propagations of measurement uncertainties and model parameter precisions are tracked rigorously throughout. We maintain a separation of the model itself from the abstract concepts of model definition, parameter manipulation, and real-time analysis and visualization. Therefore we are able to quickly adapt to fundamental model changes. It is hoped the tool will also be of use in other solar system dynamics problems. 1 Vaubaillon, J.; Colas, F.; Jorda, L. (2005) A new method to predict meteor showers. I. Description of the model. Astronomy and
Dynamic Model of Mesoscale Eddies
NASA Astrophysics Data System (ADS)
Dubovikov, Mikhail S.
2003-04-01
Oceanic mesoscale eddies which are analogs of well known synoptic eddies (cyclones and anticyclones), are studied on the basis of the turbulence model originated by Dubovikov (Dubovikov, M.S., "Dynamical model of turbulent eddies", Int. J. Mod. Phys.B7, 4631-4645 (1993).) and further developed by Canuto and Dubovikov (Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: I. General formalism", Phys. Fluids8, 571-586 (1996a) (CD96a); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: II. Sheardriven flows", Phys. Fluids8, 587-598 (1996b) (CD96b); Canuto, V.M., Dubovikov, M.S., Cheng, Y. and Dienstfrey, A., "A dynamical model for turbulence: III. Numerical results", Phys. Fluids8, 599-613 (1996c)(CD96c); Canuto, V.M., Dubovikov, M.S. and Dienstfrey, A., "A dynamical model for turbulence: IV. Buoyancy-driven flows", Phys. Fluids9, 2118-2131 (1997a) (CD97a); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: V. The effect of rotation", Phys. Fluids9, 2132-2140 (1997b) (CD97b); Canuto, V.M., Dubovikov, M.S. and Wielaard, D.J., "A dynamical model for turbulence: VI. Two dimensional turbulence", Phys. Fluids9, 2141-2147 (1997c) (CD97c); Canuto, V.M. and Dubovikov, M.S., "Physical regimes and dimensional structure of rotating turbulence", Phys. Rev. Lett. 78, 666-669 (1997d) (CD97d); Canuto, V.M., Dubovikov, M.S. and Dienstfrey, A., "Turbulent convection in a spectral model", Phys. Rev. Lett. 78, 662-665 (1997e) (CD97e); Canuto, V.M. and Dubovikov, M.S., "A new approach to turbulence", Int. J. Mod. Phys.12, 3121-3152 (1997f) (CD97f); Canuto, V.M. and Dubovikov, M.S., "Two scaling regimes for rotating Raleigh-Benard convection", Phys. Rev. Letters78, 281-284, (1998) (CD98); Canuto, V.M. and Dubovikov, M.S., "A dynamical model for turbulence: VII. The five invariants for shear driven flows", Phys. Fluids11, 659-664 (1999a) (CD99a); Canuto, V.M., Dubovikov, M.S. and Yu, G., "A dynamical model for turbulence: VIII. IR and UV
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
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
Dynamical modelling of meteoroid streams
NASA Astrophysics Data System (ADS)
Clark, D. L.; Wiegert, P. A.
2014-07-01
Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required significant assumptions and simplifications. Extending on the approach of Vaubaillon et al. 2005, we model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of weights based on model parameter changes. To assist in model analysis we are developing interactive software to permit the "turning of knobs" of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. Using the tool, we will revisit prior assumptions made, and will observe the impact of introducing non-uniform and time-variant cometary surface attributes and processes.
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.
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
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
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
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.
Modeling Catastrophic Barrier Island Dynamics
NASA Astrophysics Data System (ADS)
Whitley, J. W.; McNamara, D.
2012-12-01
Barrier islands, thin strips of sand lying parallel to the mainland coastline, along the U.S. Atlantic and Gulf Coasts appear to have maintained their form for thousands of years in the face of rising sea level. The mechanisms that allow barrier islands to remain robust are transport of sediment from the ocean side of barriers to the top and backside during storms, termed island overwash, and the growth and alongshore propagation of tidal deltas near barrier island inlets. Dynamically these processes provide the necessary feedbacks to maintain a barrier island in an attractor that withstands rising sea level within a phase space of barrier island geometrical characteristics. Current barrier island configurations along the Atlantic and Gulf coasts exist among a wide range of storm climate and underlying geologic conditions and therefore the environment that forces overwash and tidal delta dynamics varies considerably. It has been suggested that barrier islands in certain locations such as those between Avon and Buxton (losing 76% of island width since 1852) and Chandeleur islands (losing 85% of its surface area since 2005) along the Atlantic and Gulf coasts, respectively, may be subject to a catastrophic shift in barrier island attractor states - more numerous inlets cutting barriers in some locations and the complete disappearance of barrier islands in other locations. In contrast to common models for barrier islands that neglect storm dynamics and often only consider cross-shore response, we use an alongshore extended model for barrier island dynamics including beach erosion, island overwash and inlet cutting during storms, and beach accretion, tidal delta growth and dune and vegetation growth between storms to explore the response of barrier islands to a wide range of environmental forcing. Results will be presented that show how barrier island attractor states are altered with variations in the rate of sea level rise, storminess, and underlying geology. We will
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.
Mathematical Modeling of Wildfire Dynamics
NASA Astrophysics Data System (ADS)
Del Bene, Kevin; Drew, Donald
2012-11-01
Wildfires have been a long-standing problem in today's society. In this paper, we derive and solve a fluid dynamics model to study a specific type of wildfire, namely, a two dimensional flow around a rising plume above a concentrated heat source, modeling a fire line. This flow assumes a narrow plume of hot gas rising and entraining the surrounding air. The surrounding air is assumed to have constant density and is irrotational far from the fire line. The flow outside the plume is described by a Biot-Savart integral with jump conditions across the position of the plume. The plume model describes the unsteady evolution of the mass, momentum, energy, and vorticity inside the plume, with sources derived to model mixing in the style of Morton, et al. 1956]. The fire is then modeled using a conservation derivation, allowing the fire to propagate, coupling back to the plume model. The results show that this model is capable of capturing the complex interaction of the plume with the surrounding air and fuel layer. Funded by NSF GRFP.
Contagions across networks: colds and markets
NASA Astrophysics Data System (ADS)
Berryman, Matthew J.; Johnson, Neil F.; Abbott, Derek
2005-12-01
We explore a variety of network models describing transmission across a network. In particular we focus on transmission across composite networks, or "networks of networks", in which a finite number of networked objects are then themselves connected together into a network. In a disease context we introduce two interrelated viruses to hosts on a network, to model the infection of hosts in a classroom situation, with high rates of infection within a classroom, and lower rates of infection between classrooms. The hosts can be either susceptible to infection, infected, or recovering from each virus. During the infection stage and recovery stage there is some level of cross-immunity to related viruses. We explore the effects of immunizing sections of the community on transmission through social networks. In a stock market context we introduce memes, or virus-like ideas into a virtual agent-based model of a stock exchange. By varying the parameters of the individual traders and the way in which they are connected we are able to show emergent behaviour, including boom and bust cycles.
Modeling the Dynamics of Snags.
Morrison, Michael L; Raphael, Martin G
1993-05-01
Many wildlife species required standing dead trees (i.e., snags) as part of their habitat. Therefore, the ability to predict future density, distribution, and condition of snags can assist resource managers in making land-use decisions. Here we present methods for modeling the dynamics of snags using data from a 10-yr study on the rates of decay, falling, and recruitment of snags on burned and unburned plots in the Sierra Nevada, California. Snags (all species) in advanced stages of decay usually fell within 5 yr, and snags created by fire decayed rapidly and fell quicker (within 10 yr) than those on unburned plots. Pine (Pinus spp.) snags decayed more rapidly than fir (Abies spp.). Although there was an overall net increase in snag density on unburned plots, most of this increase was in the smaller (>13-38 cm diameter at breast height [dbh]) size classes; there was a net decrease in the larger (>38 cm dbh) snags preferred by many birds for nesting and feeding. Overall, snags remained standing the longest that were larger in diameter, shorter in height, less decayed, fir rather than pine, and lacking tops. A Leslie matrix model of snag dynamics predicted changes in snag decay and density only when adjusted for the specific environmental factors(s) causing initial tree mortality. Many snags are created by episodic events, such as fire, disease, drought, and insects. Models of snag dynamics must include the species and condition of trees becoming snags, as well as the factor(s) causing the tree to die. Forest managers must consider this episodic creation of snags when developing snag-management guidelines, and when planning tree-salvage programs based on short-term inventories.
Bayesian Estimation of Categorical Dynamic Factor Models
ERIC Educational Resources Information Center
Zhang, Zhiyong; Nesselroade, John R.
2007-01-01
Dynamic factor models have been used to analyze continuous time series behavioral data. We extend 2 main dynamic factor model variations--the direct autoregressive factor score (DAFS) model and the white noise factor score (WNFS) model--to categorical DAFS and WNFS models in the framework of the underlying variable method and illustrate them with…
Characterizing and modeling citation dynamics.
Eom, Young-Ho; Fortunato, Santo
2011-01-01
Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well.
Characterizing and Modeling Citation Dynamics
Eom, Young-Ho; Fortunato, Santo
2011-01-01
Citation distributions are crucial for the analysis and modeling of the activity of scientists. We investigated bibliometric data of papers published in journals of the American Physical Society, searching for the type of function which best describes the observed citation distributions. We used the goodness of fit with Kolmogorov-Smirnov statistics for three classes of functions: log-normal, simple power law and shifted power law. The shifted power law turns out to be the most reliable hypothesis for all citation networks we derived, which correspond to different time spans. We find that citation dynamics is characterized by bursts, usually occurring within a few years since publication of a paper, and the burst size spans several orders of magnitude. We also investigated the microscopic mechanisms for the evolution of citation networks, by proposing a linear preferential attachment with time dependent initial attractiveness. The model successfully reproduces the empirical citation distributions and accounts for the presence of citation bursts as well. PMID:21966387
Dynamical model for competing opinions
NASA Astrophysics Data System (ADS)
Souza, S. R.; Gonçalves, S.
2012-05-01
We propose an opinion model based on agents located at the vertices of a regular lattice. Each agent has an independent opinion (among an arbitrary, but fixed, number of choices) and its own degree of conviction. The latter changes every time two agents which have different opinions interact with each other. The dynamics leads to size distributions of clusters (made up of agents which have the same opinion and are located at contiguous spatial positions) which follow a power law, as long as the range of the interaction between the agents is not too short; i.e., the system self-organizes into a critical state. Short range interactions lead to an exponential cutoff in the size distribution and to spatial correlations which cause agents which have the same opinion to be closely grouped. When the diversity of opinions is restricted to two, a nonconsensus dynamic is observed, with unequal population fractions, whereas consensus is reached if the agents are also allowed to interact with those located far from them. The individual agents' convictions, the preestablished interaction range, and the locality of the interaction between a pair of agents (their neighborhood has no effect on the interaction) are the main characteristics which distinguish our model from previous ones.
Discontinuous phase transitions via cooperative contagion
NASA Astrophysics Data System (ADS)
Ghanbarnejad, Fakhteh; Cai, Weiran; Chen, Li; Grassberger, Peter
2015-03-01
We study the spreading of two diseases that interact cooperatively (the presence of one helps the other one to spread) on different network topologies, and with two microscopic realizations, both of which are stochastic versions of an SIR type studied by us recently in mean field approximation. We had shown that cooperativity can lead to discontinuous transitions (DT). However, due to the rapid mixing implied by the mean field assumption, DTs were seen only when there were finite (non-zero) densities of sick individuals in the initial state.In this paper we find that the results for the stochastic model depend strongly on the underlying network. In particular, DTs are found when there are few short but many long loops: (i) No DTs exist on trees, due to the absence of loops; (ii) On 2-d lattices with local contacts there are no DTs either, but because of too many short loops; (iii) We do find DTs on Erdos-Renyi (ER) networks, on d-dimensional lattices with d >= 4 ,and on 2-d lattices with sufficiently long-ranged contacts; (iv) On 3-d lattices with local contacts the results depend on the microscopic details of the implementation. All found discontinuous transitions are of ``hybrid'' type, i.e. they display also scaling features usually associated with continuous transitions.
[Affective contagion at work. Causes and effects of collective moods and emotions].
Wróbel, Monika
2010-01-01
Affective contagion is a process of transferring of mood or emotions between individuals. The process often occurs among people who work together and leads to the activation of collective emotions and moods. In particular, it refers to the work teams whose members often cooperate, have positive relations with each other, and are interdependent. Collective affective states can also be shaped by a manager whose feelings spread over other members of the work team. The author discusses the stages of affective contagion and reviews the research on affective contagion at work. She also characterizes the consequences of the spread of collective states between workers for their functioning at work. Individual differences in susceptibility to affective contagion as well as in tendency to affect others with one's feelings are also discussed.
Dynamical model of surrogate reactions
Aritomo, Y.; Chiba, S.; Nishio, K.
2011-08-15
A new dynamical model is developed to describe the whole process of surrogate reactions: Transfer of several nucleons at an initial stage, thermal equilibration of residues leading to washing out of shell effects, and decay of populated compound nuclei are treated in a unified framework. Multidimensional Langevin equations are employed to describe time evolution of collective coordinates with a time-dependent potential energy surface corresponding to different stages of surrogate reactions. The new model is capable of calculating spin distributions of the compound nuclei, one of the most important quantities in the surrogate technique. Furthermore, various observables of surrogate reactions can be calculated, for example, energy and angular distribution of ejectile and mass distributions of fission fragments. These features are important to assess validity of the proposed model itself, to understand mechanisms of the surrogate reactions, and to determine unknown parameters of the model. It is found that spin distributions of compound nuclei produced in {sup 18}O+{sup 238}U{yields}{sup 16}O+{sup 240}*U and {sup 18}O+{sup 236}U{yields}{sup 16}O+{sup 238}*U reactions are equivalent and much less than 10({h_bar}/2{pi}) and therefore satisfy conditions proposed by Chiba and Iwamoto [Phys. Rev. C 81, 044604 (2010)] if they are used as a pair in the surrogate ratio method.
Dynamical Modeling of Mars' Paleoclimate
NASA Technical Reports Server (NTRS)
Richardson, Mark I.
2004-01-01
This report summarizes work undertaken under a one-year grant from the NASA Mars Fundamental Research Program. The goal of the project was to initiate studies of the response of the Martian climate to changes in planetary obliquity and orbital elements. This work was undertaken with a three-dimensional numerical climate model based on the Geophysical Fluid Dynamics Laboratory (GFDL) Skyhi General Circulation Model (GCM). The Mars GCM code was adapted to simulate various obliquity and orbital parameter states. Using a version of the model with a basic water cycle (ice caps, vapor, and clouds), we examined changes in atmospheric water abundances and in the distribution of water ice sheets on the surface. This work resulted in a paper published in the Journal of Geophysical Research - Planets. In addition, the project saw the initial incorporation of a regolith water transport and storage scheme into the model. This scheme allows for interaction between water in the pores of the near subsurface (<3m) and the atmosphere. This work was not complete by the end of the one-year grant, but is now continuing within the auspices of a three-year grant of the same title awarded by the Mars Fundamental Research Program in late 2003.
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.
SSME structural dynamic model development
NASA Technical Reports Server (NTRS)
Foley, Michael J.
1989-01-01
The high pressure fuel turbopump (HPFTP) is a major component of the Space Shuttle Main Engine (SSME) powerhead. The device is a three stage centrifugal pump that is directly driven by a two stage hot gas turbine. The purpose of the pump is to deliver fuel (liquid hydrogen) from the low pressure fuel turbopump (LPFTP) through the main fuel valve (MFV) to the thrust chamber coolant circuits. In doing so, the pump pressurizes the fuel from an inlet pressure of approximately 178 psi to a discharge pressure of over 6000 psi. At full power level (FPL), the pump rotates at a speed of over 37,000 rpm while generating approximately 77,000 horsepower. Obviously, a pump failure at these speeds and power levels could jeopardize the mission. Results are summarized for work in which the solutions obtained from analytical models of the fuel turbopump impellers are compared with the results obtained from dynamic tests.
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
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.
Preliminary shuttle structural dynamics modeling design study
NASA Technical Reports Server (NTRS)
1972-01-01
The design and development of a structural dynamics model of the space shuttle are discussed. The model provides for early study of structural dynamics problems, permits evaluation of the accuracy of the structural and hydroelastic analysis methods used on test vehicles, and provides for efficiently evaluating potential cost savings in structural dynamic testing techniques. The discussion is developed around the modes in which major input forces and responses occur and the significant structural details in these modes.
Comparative dynamics in a health investment model.
Eisenring, C
1999-10-01
The method of comparative dynamics fully exploits the inter-temporal structure of optimal control models. I derive comparative dynamic results in a simplified demand for health model. The effect of a change in the depreciation rate on the optimal paths for health capital and investment in health is studied by use of a phase diagram.
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.
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
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.
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.
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).
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
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.
Connecting micro dynamics and population distributions in system dynamics models.
Fallah-Fini, Saeideh; Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa
2013-01-01
Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model.
Connecting micro dynamics and population distributions in system dynamics models
Rahmandad, Hazhir; Chen, Hsin-Jen; Xue, Hong; Wang, Youfa
2014-01-01
Researchers use system dynamics models to capture the mean behavior of groups of indistinguishable population elements (e.g., people) aggregated in stock variables. Yet, many modeling problems require capturing the heterogeneity across elements with respect to some attribute(s) (e.g., body weight). This paper presents a new method to connect the micro-level dynamics associated with elements in a population with the macro-level population distribution along an attribute of interest without the need to explicitly model every element. We apply the proposed method to model the distribution of Body Mass Index and its changes over time in a sample population of American women obtained from the U.S. National Health and Nutrition Examination Survey. Comparing the results with those obtained from an individual-based model that captures the same phenomena shows that our proposed method delivers accurate results with less computation than the individual-based model. PMID:25620842
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.
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
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.
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.
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.
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.
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.
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.
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
Dynamic Modeling, Chaos, and Cognitive Development.
ERIC Educational Resources Information Center
Howe, Mark L.; Rabinowitz, F. Michael
1994-01-01
Introduces the essential constructs involved in dynamic modeling, in relation to issues in psychological development. Presents several instances of how the principles of dynamic systems can be translated into mathematical formalism. Concludes that transition is a key invariance in development and that single subject, longitudinal designs are…
Two-Stage Reduction Of Dynamical Models
NASA Technical Reports Server (NTRS)
Lee, Allan Y.; Tsuha, Walter S.
1993-01-01
No longer necessary to solve eigenvalue problems of high order. Component-mode projection-and-assembly model-reduction (COMPARE) method provides approximation of dynamics of vibrations of complicated, multiple flexible bodies by use of mathematical models of reduced order. Incorporates component-mode synthesis (CMS) method and enhanced projection-and-assembly (EP&A) method, described in "Enhanced Method of Reduction of Dynamical Models" (NPO-18402), providing for somewhat simplified two-stage process in which order of applicable mathematical models reduced. Reduced-order models used to design algorithms of control systems to suppress vibrations or otherwise control structure.
Model Verification of Mixed Dynamic Systems
NASA Technical Reports Server (NTRS)
Evensen, D. A.; Chrostowski, J. D.; Hasselman, T. K.
1982-01-01
MOVER uses experimental data to verify mathematical models of "mixed" dynamic systems. The term "mixed" refers to interactive mechanical, hydraulic, electrical, and other components. Program compares analytical transfer functions with experiment.
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.
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
MODELING MICROBUBBLE DYNAMICS IN BIOMEDICAL APPLICATIONS*
CHAHINE, Georges L.; HSIAO, Chao-Tsung
2012-01-01
Controlling microbubble dynamics to produce desirable biomedical outcomes when and where necessary and avoid deleterious effects requires advanced knowledge, which can be achieved only through a combination of experimental and numerical/analytical techniques. The present communication presents a multi-physics approach to study the dynamics combining viscous- in-viscid effects, liquid and structure dynamics, and multi bubble interaction. While complex numerical tools are developed and used, the study aims at identifying the key parameters influencing the dynamics, which need to be included in simpler models. PMID:22833696
Approximate dynamic model of a turbojet engine
NASA Technical Reports Server (NTRS)
Artemov, O. A.
1978-01-01
An approximate dynamic nonlinear model of a turbojet engine is elaborated on as a tool in studying the aircraft control loop, with the turbojet engine treated as an actuating component. Approximate relationships linking the basic engine parameters and shaft speed are derived to simplify the problem, and to aid in constructing an approximate nonlinear dynamic model of turbojet engine performance useful for predicting aircraft motion.
A dynamical model of color confinement
NASA Astrophysics Data System (ADS)
Loh, S.; Biró, T. S.; Mosel, U.; Thoma, M. H.
1996-02-01
A dynamical model of confinement based on a transport theoretical description of the Friedberg-Lee model is extended to explicit color degrees of freedom. The string tension is reproduced by an adiabatic string formation from the nucleon ground state. Color isovector oscillation modes of a qq¯-system are investigated for a wide range of relative qq¯-momenta and the dynamical impact of color confinement on the quark motion is shown.
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
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
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.
Discrete model for DNA-promoter dynamics
NASA Astrophysics Data System (ADS)
Salerno, Mario
1991-10-01
We introduce a discrete model for DNA that takes into account the information about specific base sequences along the double helix. We use this model to study nonlinear wave dynamics of the T7A1 DNA promoter. As results we show the existence in the promoter of a dynamically active region in which static solitons acquire finite velocities, which contrasts with regions where solitons simply remain static. Furthermore, when they pass through this region moving solitons are accelerated, decelerated, or reflected, depending on their initial velocities. The possibility that these dynamical effects play a role in the mechanism of genetic activation is suggested.
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.
Model systems for single molecule polymer dynamics.
Latinwo, Folarin; Schroeder, Charles M
2011-01-01
Double stranded DNA (dsDNA) has long served as a model system for single molecule polymer dynamics. However, dsDNA is a semiflexible polymer, and the structural rigidity of the DNA double helix gives rise to local molecular properties and chain dynamics that differ from flexible chains, including synthetic organic polymers. Recently, we developed single stranded DNA (ssDNA) as a new model system for single molecule studies of flexible polymer chains. In this work, we discuss model polymer systems in the context of "ideal" and "real" chain behavior considering thermal blobs, tension blobs, hydrodynamic drag and force-extension relations. In addition, we present monomer aspect ratio as a key parameter describing chain conformation and dynamics, and we derive dynamical scaling relations in terms of this molecular-level parameter. We show that asymmetric Kuhn segments can suppress monomer-monomer interactions, thereby altering global chain dynamics. Finally, we discuss ssDNA in the context of a new model system for single molecule polymer dynamics. Overall, we anticipate that future single polymer studies of flexible chains will reveal new insight into the dynamic behavior of "real" polymers, which will highlight the importance of molecular individualism and the prevalence of non-linear phenomena.
Model systems for single molecule polymer dynamics
Latinwo, Folarin
2012-01-01
Double stranded DNA (dsDNA) has long served as a model system for single molecule polymer dynamics. However, dsDNA is a semiflexible polymer, and the structural rigidity of the DNA double helix gives rise to local molecular properties and chain dynamics that differ from flexible chains, including synthetic organic polymers. Recently, we developed single stranded DNA (ssDNA) as a new model system for single molecule studies of flexible polymer chains. In this work, we discuss model polymer systems in the context of “ideal” and “real” chain behavior considering thermal blobs, tension blobs, hydrodynamic drag and force–extension relations. In addition, we present monomer aspect ratio as a key parameter describing chain conformation and dynamics, and we derive dynamical scaling relations in terms of this molecular-level parameter. We show that asymmetric Kuhn segments can suppress monomer–monomer interactions, thereby altering global chain dynamics. Finally, we discuss ssDNA in the context of a new model system for single molecule polymer dynamics. Overall, we anticipate that future single polymer studies of flexible chains will reveal new insight into the dynamic behavior of “real” polymers, which will highlight the importance of molecular individualism and the prevalence of non-linear phenomena. PMID:22956980
A stochastic model of human gait dynamics
NASA Astrophysics Data System (ADS)
Ashkenazy, Yosef; M. Hausdorff, Jeffrey; Ch. Ivanov, Plamen; Eugene Stanley, H.
2002-12-01
We present a stochastic model of gait rhythm dynamics, based on transitions between different “neural centers”, that reproduces distinctive statistical properties of normal human walking. By tuning one model parameter, the transition (hopping) range, the model can describe alterations in gait dynamics from childhood to adulthood-including a decrease in the correlation and volatility exponents with maturation. The model also generates time series with multifractal spectra whose broadness depends only on this parameter. Moreover, we find that the volatility exponent increases monotonically as a function of the width of the multifractal spectrum, suggesting the possibility of a change in multifractality with maturation.
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.
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 landscape models of coevolutionary games.
Richter, Hendrik
2017-02-24
Players of coevolutionary games may update not only their strategies but also their networks of interaction. Based on interpreting the payoff of players as fitness, dynamic landscape models are proposed. The modeling procedure is carried out for Prisoner's Dilemma (PD) and Snowdrift (SD) games that both use either birth-death (BD) or death-birth (DB) strategy updating. The main focus is on using dynamic fitness landscapes as a mathematical model of coevolutionary game dynamics. Hence, an alternative tool for analyzing coevolutionary games becomes available, and landscape measures such as modality, ruggedness and information content can be computed and analyzed. In addition, fixation properties of the games and quantifiers characterizing the interaction networks are calculated numerically. Relations are established between landscape properties expressed by landscape measures and quantifiers of coevolutionary game dynamics such as fixation probabilities, fixation times and network properties.
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.
Integrated dynamics modeling for supercavitating vehicle systems
NASA Astrophysics Data System (ADS)
Kim, Seonhong; Kim, Nakwan
2015-06-01
We have performed integrated dynamics modeling for a supercavitating vehicle. A 6-DOF equation of motion was constructed by defining the forces and moments acting on the supercavitating body surface that contacted water. The wetted area was obtained by calculating the cavity size and axis. Cavity dynamics were determined to obtain the cavity profile for calculating the wetted area. Subsequently, the forces and moments acting on each wetted part-the cavitator, fins, and vehicle body-were obtained by physical modeling. The planing force-the interaction force between the vehicle transom and cavity wall-was calculated using the apparent mass of the immersed vehicle transom. We integrated each model and constructed an equation of motion for the supercavitating system. We performed numerical simulations using the integrated dynamics model to analyze the characteristics of the supercavitating system and validate the modeling completeness. Our research enables the design of high-quality controllers and optimal supercavitating systems.
Modeling cell shape and dynamics on micropatterns
Albert, Philipp J.; Schwarz, Ulrich S.
2016-01-01
ABSTRACT Adhesive micropatterns have become a standard tool to study cells under defined conditions. Applications range from controlling the differentiation and fate of single cells to guiding the collective migration of cell sheets. In long-term experiments, single cell normalization is challenged by cell division. For all of these setups, mathematical models predicting cell shape and dynamics can guide pattern design. Here we review recent advances in predicting and explaining cell shape, traction forces and dynamics on micropatterns. Starting with contour models as the simplest approach to explain concave cell shapes, we move on to network and continuum descriptions as examples for static models. To describe dynamic processes, cellular Potts, vertex and phase field models can be used. Different types of model are appropriate to address different biological questions and together, they provide a versatile tool box to predict cell behavior on micropatterns. PMID:26838278
Dynamic stiffness model of spherical parallel robots
NASA Astrophysics Data System (ADS)
Cammarata, Alessandro; Caliò, Ivo; D`Urso, Domenico; Greco, Annalisa; Lacagnina, Michele; Fichera, Gabriele
2016-12-01
A novel approach to study the elastodynamics of Spherical Parallel Robots is described through an exact dynamic model. Timoshenko arches are used to simulate flexible curved links while the base and mobile platforms are modelled as rigid bodies. Spatial joints are inherently included into the model without Lagrangian multipliers. At first, the equivalent dynamic stiffness matrix of each leg, made up of curved links joined by spatial joints, is derived; then these matrices are assembled to obtain the Global Dynamic Stiffness Matrix of the robot at a given pose. Actuator stiffness is also included into the model to verify its influence on vibrations and modes. The latter are found by applying the Wittrick-Williams algorithm. Finally, numerical simulations and direct comparison to commercial FE results are used to validate the proposed model.
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.
Component testing for dynamic model verification
NASA Technical Reports Server (NTRS)
Hasselman, T. K.; Chrostowski, J. D.
1984-01-01
Dynamic model verification is the process whereby an analytical model of a dynamic system is compared with experimental data, adjusted if necessary to bring it into agreement with the data, and then qualified for future use in predicting system response in a different dynamic environment. These are various ways to conduct model verification. The approach taken here employs Bayesian statistical parameter estimation. Unlike curve fitting, whose objective is to minimize the difference between some analytical function and a given quantity of test data (or curve), Bayesian estimation attempts also to minimize the difference between the parameter values of that funciton (the model) and their initial estimates, in a least squares sense. The objectives of dynamic model verification, therefore, are to produce a model which: (1) is in agreement with test data; (2) will assist in the interpretation of test data; (3) can be used to help verify a design; (4) will reliably predict performance; and (5) in the case of space structures, will facilitate dynamic control.
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.
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.
Dynamical modelling of coordinated multiple robot systems
NASA Technical Reports Server (NTRS)
Hayati, Samad
1987-01-01
The state of the art in the modeling of the dynamics of coordinated multiple robot manipulators is summarized and various problems related to this subject are discussed. It is recognized that dynamics modeling is a component used in the design of controllers for multiple cooperating robots. As such, the discussion addresses some problems related to the control of multiple robots. The techniques used to date in the modeling of closed kinematic chains are summarized. Various efforts made to date for the control of coordinated multiple manipulators is summarized.
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.
A system dynamics model for communications networks
NASA Astrophysics Data System (ADS)
Awcock, A. J.; King, T. E. G.
1985-09-01
An abstract model of a communications network in system dynamics terminology is developed as implementation of this model by a FORTRAN program package developed at RSRE is discussed. The result of this work is a high-level simulation package in which the performance of adaptive routing algorithms and other network controls may be assessed for a network of arbitrary topology.
Dynamical effects of overparametrization in nonlinear models
NASA Astrophysics Data System (ADS)
Aguirre, Luis Antonio; Billings, S. A.
1995-01-01
This paper is concemed with dynamical reconstruction for nonlinear systems. The effects of the driving function and of the complexity of a given representation on the bifurcation patter are investigated. It is shown that the use of different driving functions to excite the system may yield models with different bifurcation patterns. The complexity of the reconstructions considered is quantified by the embedding dimension and the number of estimated parameters. In this respect it appears that models which reproduce the original bifurcation behaviour are of limited complexity and that excessively complex models tend to induce ghost bifurcations and spurious dynamical regimes. Moreover, some results suggest that the effects of overparametrization on the global dynamical behaviour of a nonlinear model may be more deleterious than the presence of moderate noise levels. In order to precisely quantify the complexity of the reconstructions, global polynomials are used although the results are believed to apply to a much wider class of representations including neural networks.
Magnetospheric dynamics from a low-dimensional nonlinear dynamics model
NASA Astrophysics Data System (ADS)
Doxas, I.; Horton, W.
1999-05-01
A physics based model for the coupled solar WIND-Magnetosphere-Ionosphere system (WINDMI) is described. The model is based on truncated descriptions of the collisionless microscopic energy transfer processes occurring in the quasineutral layer, and includes a thermal flux limit neglected in the Magnetohydrodynamic (MHD) closure of the moment equations. All dynamically relevant parameters of the model can be computed analytically. The system is both Kirchhoffian and Hamiltonian, ensuring that the power input from the solar wind is divided into physically realizable energy sub-components, a property not shared by data-based filters. The model provides a consistent mathematical formalism in which different models of the solar wind driver, ionospheric dissipation, global field configuration, and substorm trigger mechanism can be inserted, and the coupling between the different parts of the system investigated.
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.…
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
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…
Susceptibility to emotional contagion for negative emotions improves detection of smile authenticity
Manera, Valeria; Grandi, Elisa; Colle, Livia
2013-01-01
A smile is a context-dependent emotional expression. A smiling face can signal the experience of enjoyable emotions, but people can also smile to convince another person that enjoyment is occurring when it is not. For this reason, the ability to discriminate between felt and faked enjoyment expressions is a crucial social skill. Despite its importance, adults show remarkable individual variation in this ability. Revealing the factors responsible for these huge individual differences is a key challenge in this domain. Here we investigated, on a large sample of participants, whether individual differences in smile authenticity recognition are accounted for by differences in the predisposition to experience other people's emotions, i.e., by susceptibility to emotional contagion. Results showed that susceptibility to emotional contagion for negative emotions increased smile authenticity detection, while susceptibility to emotional contagion for positive emotions worsened detection performance, because it leaded to categorize most of the faked smiles as sincere. These findings suggest that susceptibility to emotional contagion plays a key role in complex emotion recognition, and point out the importance of analyzing the tendency to experience other people's positive and negative emotions as separate abilities. PMID:23508036
Omdahl, B L; O'Donnell, C
1999-06-01
Based on data gathered from registered nurses at two hospitals, this research examined the extent to which empathy variables contributed to nursing stress and occupational commitment. The empathy variables examined were emotional contagion (i.e. sharing the emotions of patients), empathic concern (i.e. being concerned for patients) and communicative effectiveness (i.e. effectively communicating with patients and their families). Nursing stress was explored through the variables of depersonalization, reduced personal accomplishment and emotional exhaustion. Multiple regression analyses revealed that the combination of the three emotional communication variables explained significant proportions of the variance in all three of the stress variables, as well as occupational commitment. The analyses further revealed that a lack of empathic concern and poor communicative responsiveness accounted for significant proportions of the variance in depersonalization. Lack of empathic concern, poor communicative responsiveness and high emotional contagion significantly contributed to reduced personal accomplishment. Emotional contagion explained a significant proportion of the variance in emotional exhaustion. Emotional contagion also significantly reduced occupational commitment. The findings are discussed in terms of nursing education and administration.
[Almeria faced by contagion: health practice in the 18th century].
Gómez Diaz, Donato; Gómez Diaz, Maria José
2003-01-01
Epidemics in Almeria during the 18th century and the beginnings of the 19th century are described, as well as the measures adopted to avoid them, regarding both internal contagion and the need for surveillance of incoming ships. The economic consequences of the prophylactic measures taken are also considered. Finally, the role of the Church in extreme situations is analyzed.
Cognitive bias in rats evoked by ultrasonic vocalizations suggests emotional contagion.
Saito, Yumi; Yuki, Shoko; Seki, Yoshimasa; Kagawa, Hiroko; Okanoya, Kazuo
2016-11-01
Emotional contagion occurs when an individual acquires the emotional state of another via social cues, and is an important component of empathy. Empathic responses seen in rodents are often explained by emotional contagion. Rats emit 50kHz ultrasonic vocalizations (USVs) in positive contexts, and emit 22kHz USVs in negative contexts. We tested whether rats show positive or negative emotional contagion after hearing conspecific USVs via a cognitive bias task. We hypothesized that animals in positive emotional states would perceive an ambiguous cue as being good (optimistic bias) whereas animals in negative states would perceive the same cue as being bad (pessimistic bias). Rats were trained to respond differently to two sounds with distinct pitches, each of which signaled either a positive or a negative outcome. An ambiguous cue with a frequency falling between the two stimuli tested whether rats interpreted it as positive or negative. Results showed that rats responded to ambiguous cues as positive when they heard the 50kHz USV (positive vocalizations) and negative when they heard the 22kHz USV (negative vocalizations). This suggests that conspecific USVs can evoke emotional contagion, both for positive and negative emotions, to change the affective states in receivers.
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
Adaptation dynamics of the quasispecies model
NASA Astrophysics Data System (ADS)
Jain, Kavita
2009-02-01
We study the adaptation dynamics of an initially maladapted population evolving via the elementary processes of mutation and selection. The evolution occurs on rugged fitness landscapes which are defined on the multi-dimensional genotypic space and have many local peaks separated by low fitness valleys. We mainly focus on the Eigen's model that describes the deterministic dynamics of an infinite number of self-replicating molecules. In the stationary state, for small mutation rates such a population forms a {\\it quasispecies} which consists of the fittest genotype and its closely related mutants. The quasispecies dynamics on rugged fitness landscape follow a punctuated (or step-like) pattern in which a population jumps from a low fitness peak to a higher one, stays there for a considerable time before shifting the peak again and eventually reaches the global maximum of the fitness landscape. We calculate exactly several properties of this dynamical process within a simplified version of the quasispecies model.
Modeling hybrid perovskites by molecular dynamics
NASA Astrophysics Data System (ADS)
Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia
2017-02-01
The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.
Modeling hybrid perovskites by molecular dynamics.
Mattoni, Alessandro; Filippetti, Alessio; Caddeo, Claudia
2017-02-01
The topical review describes the recent progress in the modeling of hybrid perovskites by molecular dynamics simulations. Hybrid perovskites and in particular methylammonium lead halide (MAPI) have a tremendous technological relevance representing the fastest-advancing solar material to date. They also represent the paradigm of an organic-inorganic crystalline material with some conceptual peculiarities: an inorganic semiconductor for what concerns the electronic and absorption properties with a hybrid and solution processable organic-inorganic body. After briefly explaining the basic concepts of ab initio and classical molecular dynamics, the model potential recently developed for hybrid perovskites is described together with its physical motivation as a simple ionic model able to reproduce the main dynamical properties of the material. Advantages and limits of the two strategies (either ab initio or classical) are discussed in comparison with the time and length scales (from pico to microsecond scale) necessary to comprehensively study the relevant properties of hybrid perovskites from molecular reorientations to electrocaloric effects. The state-of-the-art of the molecular dynamics modeling of hybrid perovskites is reviewed by focusing on a selection of showcase applications of methylammonium lead halide: molecular cations disorder; temperature evolution of vibrations; thermally activated defects diffusion; thermal transport. We finally discuss the perspectives in the modeling of hybrid perovskites by molecular dynamics.
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
Dispersive models describing mosquitoes’ population dynamics
NASA Astrophysics Data System (ADS)
Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.
2016-08-01
The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.
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.
Modelling Martian surface channel dynamics
NASA Astrophysics Data System (ADS)
Coulthard, T. J.; Skinner, C.; Kim, J.; Schumann, G.; Neal, J. C.; Bates, P. D.
2014-12-01
Extensive and large surface channel features found at Athabasca and Kasei have previously been attributed to the erosional power of flowing water with palaeoflood discharges being estimated from the surface channel dimensions. However, in order for these channels to be alluvial there are several basic questions to be answered. Are water flows under Martian conditions capable of eroding the amounts of sediment required to leave these channels? Are our present estimates of palaeoflood discharge of correct magnitude to carry out this erosion? And are the channels a product of one or many flood events? Here, we use a numerical model (CAESAR-Lisflood) that links a two-dimensional hydrodynamic flow scheme to a sediment transport model to simulate fluvial morphodynamics in the Athabasca and Kasei regions. CAESAR-Lisflood has been successfully applied to simulating flooding, erosion and deposition on Earth in a number of locations, and allows the development of channels, bars, braids and other fluvial features to be modelled. The numerical scheme of the model was adapted to Martian conditions by adjusting gravity, drag co-efficient, roughness and grainsize terms. Preliminary findings indicate that fluvial erosion and deposition is capable of creating mega channel features found at these sites and that existing palaeflood estimates are commensurate with channel forming discharges for these features.
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.
Alternative models for cyclic lemming dynamics.
Wang, Hao; Kuang, Yang
2007-01-01
Many natural population growths and interactions are affected by seasonal changes, suggesting that these natural population dynamics should be modeled by nonautonomous differential equations instead of autonomous differential equations. Through a series of carefully derived models of the well documented high-amplitude, large-period fluctuations of lemming populations, we argue that when appropriately formulated, autonomous differential equations may capture much of the desirable rich dynamics, such as the existence of a periodic solution with period and amplitude close to that of approximately periodic solutions produced by the more natural but mathematically daunt ing nonautonomous models. We start this series of models from the Barrow model, a well formulated model for the dynamics of food-lemming interaction at Point Barrow (Alaska, USA) with sufficient experimental data. Our work suggests that an autonomous system can indeed be a good approximation to the moss-lemming dynamics at Point Barrow. This, together with our bifurcation analysis, indicates that neither seasonal factors (expressed by time dependent moss growth rate and lemming death rate in the Barrow model) nor the moss growth rate and lemming death rate are the main culprits of the observed multi-year lemming cycles. We suspect that the main culprits may include high lemming predation rate, high lemming birth rate, and low lemming self-limitation rate.
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.
Flapping Wing Flight Dynamic Modeling
2011-08-22
Hummingbird [5]. This particular study focuses on the diculty of determining what models are most impor- tant to consider when trying to accurately...Projects Agency TTO Document, 1996. [5] Nano Hummingbird , Website, 2011. [6] Fry, S. N., Sayaman, R., and Dickinson, M. H., The Aerodynamics of Free...and Jategaonkar, R. V., Evolution of Flight Vehicle System Identication, Journal of Aircraft , Vol. 33, 1996, pp. 928. [40] Hedrick, T. L
Continuous Time Dynamic Topic Models
2008-06-20
called topics, can be used to explain the observed collection. LDA is a probabilistic extension of latent semantic indexing (LSI) [5] and probabilistic... latent semantic indexing (pLSI) [11]. Owing to its formal generative semantics, LDA has been extended and applied to authorship [19], email [15...Steyvers. Probabilistic topic models. In Latent Semantic Analysis: A Road to Meaning. 2006. [9] T. L. Griffiths and M. Steyvers. Finding scientific
Feature Extraction for Structural Dynamics Model Validation
Farrar, Charles; Nishio, Mayuko; Hemez, Francois; Stull, Chris; Park, Gyuhae; Cornwell, Phil; Figueiredo, Eloi; Luscher, D. J.; Worden, Keith
2016-01-13
As structural dynamics becomes increasingly non-modal, stochastic and nonlinear, finite element model-updating technology must adopt the broader notions of model validation and uncertainty quantification. For example, particular re-sampling procedures must be implemented to propagate uncertainty through a forward calculation, and non-modal features must be defined to analyze nonlinear data sets. The latter topic is the focus of this report, but first, some more general comments regarding the concept of model validation will be discussed.
The dynamic model of enterprise revenue management
NASA Astrophysics Data System (ADS)
Mitsel, A. A.; Kataev, M. Yu; Kozlov, S. V.; Korepanov, K. V.
2017-01-01
The article presents the dynamic model of enterprise revenue management. This model is based on the quadratic criterion and linear control law. The model is founded on multiple regression that links revenues with the financial performance of the enterprise. As a result, optimal management is obtained so as to provide the given enterprise revenue, namely, the values of financial indicators that ensure the planned profit of the organization are acquired.
Dynamic exponents for potts model cluster algorithms
NASA Astrophysics Data System (ADS)
Coddington, Paul D.; Baillie, Clive F.
We have studied the Swendsen-Wang and Wolff cluster update algorithms for the Ising model in 2, 3 and 4 dimensions. The data indicate simple relations between the specific heat and the Wolff autocorrelations, and between the magnetization and the Swendsen-Wang autocorrelations. This implies that the dynamic critical exponents are related to the static exponents of the Ising model. We also investigate the possibility of similar relationships for the Q-state Potts model.
A dynamic conceptual model of care planning.
Elf, Marie; Poutilova, Maria; Ohrn, Kerstin
2007-12-01
This article presents a conceptual model of the care planning process developed to identify the hypothetical links between structural, process and outcome factors important to the quality of the process. Based on existing literature, it was hypothesized that a thorough assessment of patients' health needs is an important prerequisite when making a rigorous diagnosis and preparing plans for various care interventions. Other important variables that are assumed to influence the quality of the process are the care culture and professional knowledge. The conceptual model was developed as a system dynamics causal loop diagram as a first essential step towards a computed model. System dynamics offers the potential to describe processes in a nonlinear, dynamic way and is suitable for exploring, comprehending, learning and communicating complex ideas about care processes.
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.
Dynamic reliability models with conditional proportional hazards.
Hollander, M; Peña, E A
1995-01-01
A dynamic approach to the stochastic modelling of reliability systems is further explored. This modelling approach is particularly appropriate for load-sharing, software reliability, and multivariate failure-time models, where component failure characteristics are affected by their degree of use, amount of load, or extent of stresses experienced. This approach incorporates the intuitive notion that when a set of components in a coherent system fail at a certain time, there is a 'jump' from one structure function to another which governs the residual lifetimes of the remaining functioning components, and since the component lifetimes are intrinsically affected by the structure function which they constitute, then at such a failure time there should also be a jump in the stochastic structure of the lifetimes of the remaining components. For such dynamically-modelled systems, the stochastic characteristics of their jump times are studied. These properties of the jump times allow us to obtain the properties of the lifetime of the system. In particular, for a Markov dynamic model, specific expressions for the exact distribution function of the jump times are obtained for a general coherent system, a parallel system, and a series-parallel system. We derive a new family of distribution functions which describes the distributions of the jump times for a dynamically-modelled system.
Dynamic modeling of solar dynamic components and systems
NASA Astrophysics Data System (ADS)
Hochstein, John I.; Korakianitis, T.
1992-09-01
The purpose of this grant was to support NASA in modeling efforts to predict the transient dynamic and thermodynamic response of the space station solar dynamic power generation system. In order to meet the initial schedule requirement of providing results in time to support installation of the system as part of the initial phase of space station, early efforts were executed with alacrity and often in parallel. Initially, methods to predict the transient response of a Rankine as well as a Brayton cycle were developed. Review of preliminary design concepts led NASA to select a regenerative gas-turbine cycle using a helium-xenon mixture as the working fluid and, from that point forward, the modeling effort focused exclusively on that system. Although initial project planning called for a three year period of performance, revised NASA schedules moved system installation to later and later phases of station deployment. Eventually, NASA selected to halt development of the solar dynamic power generation system for space station and to reduce support for this project to two-thirds of the original level.
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.
Echo Chambers: Emotional Contagion and Group Polarization on Facebook
NASA Astrophysics Data System (ADS)
Del Vicario, Michela; Vivaldo, Gianna; Bessi, Alessandro; Zollo, Fabiana; Scala, Antonio; Caldarelli, Guido; Quattrociocchi, Walter
2016-12-01
Recent findings showed that users on Facebook tend to select information that adhere to their system of beliefs and to form polarized groups – i.e., echo chambers. Such a tendency dominates information cascades and might affect public debates on social relevant issues. In this work we explore the structural evolution of communities of interest by accounting for users emotions and engagement. Focusing on the Facebook pages reporting on scientific and conspiracy content, we characterize the evolution of the size of the two communities by fitting daily resolution data with three growth models – i.e. the Gompertz model, the Logistic model, and the Log-logistic model. Although all the models appropriately describe the data structure, the Logistic one shows the best fit. Then, we explore the interplay between emotional state and engagement of users in the group dynamics. Our findings show that communities’ emotional behavior is affected by the users’ involvement inside the echo chamber. Indeed, to an higher involvement corresponds a more negative approach. Moreover, we observe that, on average, more active users show a faster shift towards the negativity than less active ones.
Echo Chambers: Emotional Contagion and Group Polarization on Facebook.
Del Vicario, Michela; Vivaldo, Gianna; Bessi, Alessandro; Zollo, Fabiana; Scala, Antonio; Caldarelli, Guido; Quattrociocchi, Walter
2016-12-01
Recent findings showed that users on Facebook tend to select information that adhere to their system of beliefs and to form polarized groups - i.e., echo chambers. Such a tendency dominates information cascades and might affect public debates on social relevant issues. In this work we explore the structural evolution of communities of interest by accounting for users emotions and engagement. Focusing on the Facebook pages reporting on scientific and conspiracy content, we characterize the evolution of the size of the two communities by fitting daily resolution data with three growth models - i.e. the Gompertz model, the Logistic model, and the Log-logistic model. Although all the models appropriately describe the data structure, the Logistic one shows the best fit. Then, we explore the interplay between emotional state and engagement of users in the group dynamics. Our findings show that communities' emotional behavior is affected by the users' involvement inside the echo chamber. Indeed, to an higher involvement corresponds a more negative approach. Moreover, we observe that, on average, more active users show a faster shift towards the negativity than less active ones.
Echo Chambers: Emotional Contagion and Group Polarization on Facebook
Del Vicario, Michela; Vivaldo, Gianna; Bessi, Alessandro; Zollo, Fabiana; Scala, Antonio; Caldarelli, Guido; Quattrociocchi, Walter
2016-01-01
Recent findings showed that users on Facebook tend to select information that adhere to their system of beliefs and to form polarized groups – i.e., echo chambers. Such a tendency dominates information cascades and might affect public debates on social relevant issues. In this work we explore the structural evolution of communities of interest by accounting for users emotions and engagement. Focusing on the Facebook pages reporting on scientific and conspiracy content, we characterize the evolution of the size of the two communities by fitting daily resolution data with three growth models – i.e. the Gompertz model, the Logistic model, and the Log-logistic model. Although all the models appropriately describe the data structure, the Logistic one shows the best fit. Then, we explore the interplay between emotional state and engagement of users in the group dynamics. Our findings show that communities’ emotional behavior is affected by the users’ involvement inside the echo chamber. Indeed, to an higher involvement corresponds a more negative approach. Moreover, we observe that, on average, more active users show a faster shift towards the negativity than less active ones. PMID:27905402
Dynamical properties of the Rabi model
NASA Astrophysics Data System (ADS)
Hu, Binglu; Zhou, Huili; Chen, Shujie; Xianlong, Gao; Wang, Kelin
2017-02-01
We study the dynamical properties of the quantum Rabi model using a systematic expansion method. Based on the observation that the parity symmetry of the Rabi model is kept during evolution of the states, we decompose the initial state and the time-dependent one into positive and negative parity parts expanded by superposition of the coherent states. The evolutions of the corresponding positive and the negative parities are obtained, in which the expansion coefficients in the dynamical equations are known from the derived recurrence relation.
Robot arm dynamic model reduction for control
NASA Technical Reports Server (NTRS)
Bejczy, A. K.; Lee, S.
1983-01-01
General methods are described by which the mathematical complexities of explicit and exact state equations of robot arms can be reduced to a simplified and compact state equation representation without introducing significant errors into the robot arm dynamic model. The model reduction methods are based on homogeneous coordinates and on the Langrangian algorithm for robot arm dynamics, and utilize matrix, vector and numeric analysis techniques. The derivation of differential vector representation of centripetal and Coriolis forces which has not yet been established in the literature is presented.
Dynamic models of Fabry-Perot interferometers.
Redding, David; Regehr, Martin; Sievers, Lisa
2002-05-20
Long-baseline, high-finesse Fabry-Perot interferometers can be used to make distance measurements that are precise enough to detect gravity waves. This level of sensitivity is achieved in part when the interferometer mirrors are isolated dynamically, with pendulum mounts and high-bandwidth cavity length control servos to reduce the effects of seismic noise. We present dynamical models of the cavity fields and signals of Fabry-Perot interferometers for use in the design and evaluation of length control systems for gravity-wave detectors. Models are described and compared with experimental data.
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.
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.
Dynamic model for the popularity of websites.
Lee, Chang-Yong; Kim, Seungwhan
2002-03-01
In this paper, we have studied a dynamic model to explain the observed characteristics of websites in the World Wide Web. The dynamic model consists of the self-growth term for each website and the external force term acting on the website. With simulations of the model, we can explain most of the important characteristics of websites. These characteristics include a power-law distribution of the number of visitors to websites, fluctuation in the fractional growth of individual websites, and the relationship between the age and the popularity of the websites. We also investigated a few variants of the model and showed that the ingredients included in the model adequately explain the behavior of the websites.
Dynamic model for the popularity of websites
NASA Astrophysics Data System (ADS)
Lee, Chang-Yong; Kim, Seungwhan
2002-03-01
In this paper, we have studied a dynamic model to explain the observed characteristics of websites in the World Wide Web. The dynamic model consists of the self-growth term for each website and the external force term acting on the website. With simulations of the model, we can explain most of the important characteristics of websites. These characteristics include a power-law distribution of the number of visitors to websites, fluctuation in the fractional growth of individual websites, and the relationship between the age and the popularity of the websites. We also investigated a few variants of the model and showed that the ingredients included in the model adequately explain the behavior of the websites.
BDI-modelling of complex intracellular dynamics.
Jonker, C M; Snoep, J L; Treur, J; Westerhoff, H V; Wijngaards, W C A
2008-03-07
A BDI-based continuous-time modelling approach for intracellular dynamics is presented. It is shown how temporalized BDI-models make it possible to model intracellular biochemical processes as decision processes. By abstracting from some of the details of the biochemical pathways, the model achieves understanding in nearly intuitive terms, without losing veracity: classical intentional state properties such as beliefs, desires and intentions are founded in reality through precise biochemical relations. In an extensive example, the complex regulation of Escherichia coli vis-à-vis lactose, glucose and oxygen is simulated as a discrete-state, continuous-time temporal decision manager. Thus a bridge is introduced between two different scientific areas: the area of BDI-modelling and the area of intracellular dynamics.
Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam’s Window*
Onorante, Luca; Raftery, Adrian E.
2015-01-01
Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and the number of possible models becomes too large for DMA to be applied in its original form. We propose a new method for this situation which allows us to perform DMA without considering the whole model space, but using a subset of models and dynamically optimizing the choice of models at each point in time. This yields a dynamic form of Occam’s window. We evaluate the method in the context of the problem of nowcasting GDP in the Euro area. We find that its forecasting performance compares well with that of other methods. PMID:26917859
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.
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.
Solvable model for polymorphic dynamics of biofilaments.
Mohrbach, Hervé; Kulić, Igor M
2012-03-01
We investigate an analytically tractable toy model for thermally induced polymorphic dynamics of cooperatively rearranging biofilaments-like microtubules. The proposed four-block model, which can be seen as a coarse-grained approximation of the full polymorphic tube model, permits a complete analytical treatment of all thermodynamic properties including correlation functions and angular Fourier mode distributions. Due to its mathematical tractability the model straightforwardly leads to some physical insights in recently discussed phenomena like the "length dependent persistence length." We show that a polymorphic filament can disguise itself as a classical worm-like chain on small and on large scales and yet display distinct anomalous tell-tale features indicating an inner switching dynamics on intermediate length scales.
The quantum Rabi model: solution and dynamics
NASA Astrophysics Data System (ADS)
Xie, Qiongtao; Zhong, Honghua; Batchelor, Murray T.; Lee, Chaohong
2017-03-01
This article presents a review of recent developments on various aspects of the quantum Rabi model. Particular emphasis is given on the exact analytic solution obtained in terms of confluent Heun functions. The analytic solutions for various generalisations of the quantum Rabi model are also discussed. Results are also reviewed on the level statistics and the dynamics of the quantum Rabi model. The article concludes with an introductory overview of several experimental realisations of the quantum Rabi model. An outlook towards future developments is also given.
Modeling of Reactor Kinetics and Dynamics
Matthew Johnson; Scott Lucas; Pavel Tsvetkov
2010-09-01
In order to model a full fuel cycle in a nuclear reactor, it is necessary to simulate the short time-scale kinetic behavior of the reactor as well as the long time-scale dynamics that occur with fuel burnup. The former is modeled using the point kinetics equations, while the latter is modeled by coupling fuel burnup equations with the kinetics equations. When the equations are solved simultaneously with a nonlinear equation solver, the end result is a code with the unique capability of modeling transients at any time during a fuel cycle.
Developmental Stages in Dynamic Plant Growth Models
NASA Astrophysics Data System (ADS)
Maclean, Heather; Dochain, Denis; Waters, Geoff; Stasiak, Michael; Dixon, Mike; Van Der Straeten, Dominique
2011-09-01
During the growth of red beet plants in a closed environment plant growth chamber, a change in metabolism was observed (decreasing photosynthetic quotient) which was not predicted by a previously developed simple dynamic model of photosynthesis and respiration reactions. The incorporation of developmental stages into the model allowed for the representation of this change in metabolism without adding unnecessary complexity. Developmental stages were implemented by dividing the model into two successive sub-models with independent yields. The transition between the phases was detected based on online measurements. Results showed an accurate prediction of carbon dioxide and oxygen fluxes.
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.
Modeling of tower relief dynamics: Part 2
Cassata, J.R.; Dasgupta, S.; Gandhi, S.L. )
1993-11-01
Dynamic simulations of individual towers or systems of distillations columns overcome limitations of steady-state models by rigorously determining dynamic responses. These will lead to a realistic quantification of relief header and flare system load and identify the design-setting relief scenario. Determination of distillation tower relief loads based on steady-state simulations or recognized methods of approximation can lead to over designing relief systems by large margins. This can result in unnecessary capital expenditure for relief headers and flare systems that can significantly alter the economics of a proposed project. Such overly conservative requirements may even cause potentially attractive projects to be unnecessarily canceled. In addition, approximate methods or analyses based on steady-state simulations sometimes do not identify the design-setting relief mode. Part 1 introduced the PRV and tower dynamic models. Different strategies were shown that can simplify these models. These strategies include tower segmentation, tray lumping and component lumping. Two case studies illustrate the advantages of dynamic models. The two studies are a depentanizer tower relief study and a delthanizer tower relief study.
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.
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.
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.
Modelling Subduction Dynamics: The South American Salsa
NASA Astrophysics Data System (ADS)
Hale, A. J.; Shephard, G.; Müller, D.; Liu, L.; Gurnis, M.
2009-12-01
Plate kinematic and seismic tomography models imply a gradual overriding of the Phoenix and Farallon slabs by the westward movement of the South American plate. This westward translation over the subducted slabs, and the currently subducting Nazca Plate, is expected to generate a dynamic surface topography effect, leading to time-progressive vertical motions and tilting of sedimentary basins and their hinterlands. We have set up a workflow to model these processes including ground-truthing with geological and geophysical data. A combination of geodynamic modelling software, CitcomS, GPlates (gplates.org) software and the Generic Mapping Tools (GMT) facilitates the modelling and visualisation of linked plate kinematics and mantle convection processes. The CitcomS software also allows us to alternatively use forward models, backward models, or combined forward and adjoint models. Forward models are driven by an imposed plate kinematic model and assumed initial subdution structure, whereas backwards models use mantle tomography as an input and run the model backwards by reversing the gravity field. Similarly, adjoint models use tomography as input, but iterate backwards and forwards in time to reach convergence upon present-day mantle structures. Model outputs include time-dependent mantle temperature, viscosity, and surface dynamic topography. Forward model results show that slab evolution under South America are strongly driven by the age of the subducting lithosphere. Hence, we can simulate flat-slab subduction and in regions close to the Chile triple junction we see a slab window developing, detaching older slab material from more recently subducted material. However, the forward model relies on an accurate description of the initial slab geometry at 140Ma to generate the initial slab pull. Forward and adjoint model results both suggest an alternative mechanism for major Miocene changes in paleo-Amazon river drainage. An eastward-sweeping negative dynamic
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.
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.
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
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
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
NASA Astrophysics Data System (ADS)
Davtyan, Aram; Voth, Gregory A.; Andersen, Hans C.
2016-12-01
We recently developed a dynamic force matching technique for converting a coarse-grained (CG) model of a molecular system, with a CG potential energy function, into a dynamic CG model with realistic dynamics [A. Davtyan et al., J. Chem. Phys. 142, 154104 (2015)]. This is done by supplementing the model with additional degrees of freedom, called "fictitious particles." In that paper, we tested the method on CG models in which each molecule is coarse-grained into one CG point particle, with very satisfactory results. When the method was applied to a CG model of methanol that has two CG point particles per molecule, the results were encouraging but clearly required improvement. In this paper, we introduce a new type (called type-3) of fictitious particle that exerts forces on the center of mass of two CG sites. A CG model constructed using type-3 fictitious particles (as well as type-2 particles previously used) gives a much more satisfactory dynamic model for liquid methanol. In particular, we were able to construct a CG model that has the same self-diffusion coefficient and the same rotational relaxation time as an all-atom model of liquid methanol. Type-3 particles and generalizations of it are likely to be useful in converting more complicated CG models into dynamic CG models.
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.
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...
Next Generation Carbon-Nitrogen Dynamics Model
NASA Astrophysics Data System (ADS)
Xu, C.; Fisher, R. A.; Vrugt, J. A.; Wullschleger, S. D.; McDowell, N. G.
2012-12-01
Nitrogen is a key regulator of vegetation dynamics, soil carbon release, and terrestrial carbon cycles. Thus, to assess energy impacts on the global carbon cycle and future climates, it is critical that we have a mechanism-based and data-calibrated nitrogen model that simulates nitrogen limitation upon both above and belowground carbon dynamics. In this study, we developed a next generation nitrogen-carbon dynamic model within the NCAR Community Earth System Model (CESM). This next generation nitrogen-carbon dynamic model utilized 1) a mechanistic model of nitrogen limitation on photosynthesis with nitrogen trade-offs among light absorption, electron transport, carboxylation, respiration and storage; 2) an optimal leaf nitrogen model that links soil nitrogen availability and leaf nitrogen content; and 3) an ecosystem demography (ED) model that simulates the growth and light competition of tree cohorts and is currently coupled to CLM. Our three test cases with changes in CO2 concentration, growing temperature and radiation demonstrate the model's ability to predict the impact of altered environmental conditions on nitrogen allocations. Currently, we are testing the model against different datasets including soil fertilization and Free Air CO2 enrichment (FACE) experiments across different forest types. We expect that our calibrated model will considerably improve our understanding and predictability of vegetation-climate interactions.itrogen allocation model evaluations. The figure shows the scatter plots of predicted and measured Vc,max and Jmax scaled to 25 oC (i.e.,Vc,max25 and Jmax25) at elevated CO2 (570 ppm, test case one), reduced radiation in canopy (0.1-0.9 of the radiation at the top of canopy, test case two) and reduced growing temperature (15oC, test case three). The model is first calibrated using control data under ambient CO2 (370 ppm), radiation at the top of the canopy (621 μmol photon/m2/s), the normal growing temperature (30oC). The fitted model
Dynamical modelling of galactic disc outskirts
NASA Astrophysics Data System (ADS)
Athanassoula, E.
2017-03-01
I review briefly some dynamical models of structures in the outer parts of disc galaxies, including models of polar rings, tidal tails and bridges. I then discuss the density distribution in the outer parts of discs. For this, I compare observations to results of a model in which the disc galaxy is in fact the remnant of a major merger, and find good agreement. This comparison includes radial profiles of the projected surface density and of stellar age, as well as time evolution of the break radius and of the inner and outer disc scale lengths. I also compare the radial projected surface density profiles of dynamically motivated mono-age populations and find that, compared to older populations, younger ones have flatter density profiles in the inner region and steeper in the outer one. The break radius, however, does not vary with stellar age, again in good agreement with observations.
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.
Learning generative models of molecular dynamics
2012-01-01
We introduce three algorithms for learning generative models of molecular structures from molecular dynamics simulations. The first algorithm learns a Bayesian-optimal undirected probabilistic model over user-specified covariates (e.g., fluctuations, distances, angles, etc). L1 reg-ularization is used to ensure sparse models and thus reduce the risk of over-fitting the data. The topology of the resulting model reveals important couplings between different parts of the protein, thus aiding in the analysis of molecular motions. The generative nature of the model makes it well-suited to making predictions about the global effects of local structural changes (e.g., the binding of an allosteric regulator). Additionally, the model can be used to sample new conformations. The second algorithm learns a time-varying graphical model where the topology and parameters change smoothly along the trajectory, revealing the conformational sub-states. The last algorithm learns a Markov Chain over undirected graphical models which can be used to study and simulate kinetics. We demonstrate our algorithms on multiple molecular dynamics trajectories. PMID:22369071
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.
Global Langevin model of multidimensional biomolecular dynamics
NASA Astrophysics Data System (ADS)
Schaudinnus, Norbert; Lickert, Benjamin; Biswas, Mithun; Stock, Gerhard
2016-11-01
Molecular dynamics simulations of biomolecular processes are often discussed in terms of diffusive motion on a low-dimensional free energy landscape F ( 𝒙 ) . To provide a theoretical basis for this interpretation, one may invoke the system-bath ansatz á la Zwanzig. That is, by assuming a time scale separation between the slow motion along the system coordinate x and the fast fluctuations of the bath, a memory-free Langevin equation can be derived that describes the system's motion on the free energy landscape F ( 𝒙 ) , which is damped by a friction field and driven by a stochastic force that is related to the friction via the fluctuation-dissipation theorem. While the theoretical formulation of Zwanzig typically assumes a highly idealized form of the bath Hamiltonian and the system-bath coupling, one would like to extend the approach to realistic data-based biomolecular systems. Here a practical method is proposed to construct an analytically defined global model of structural dynamics. Given a molecular dynamics simulation and adequate collective coordinates, the approach employs an "empirical valence bond"-type model which is suitable to represent multidimensional free energy landscapes as well as an approximate description of the friction field. Adopting alanine dipeptide and a three-dimensional model of heptaalanine as simple examples, the resulting Langevin model is shown to reproduce the results of the underlying all-atom simulations. Because the Langevin equation can also be shown to satisfy the underlying assumptions of the theory (such as a delta-correlated Gaussian-distributed noise), the global model provides a correct, albeit empirical, realization of Zwanzig's formulation. As an application, the model can be used to investigate the dependence of the system on parameter changes and to predict the effect of site-selective mutations on the dynamics.
Dynamic Modeling of Meandering Alluvial Channels
NASA Astrophysics Data System (ADS)
Lan, Yongqiang
1990-01-01
The migration of meandering alluvial channels is investigated theoretically, numerically, and experimentally. An equation for the rate of bank erosion is derived from a two-dimensional continuity equation for sediment transport linked with the depth-averaged dynamic flow equations. A simple one-dimensional theoretical analysis of meander migration leads to a relationship between the migration rate and the relative channel curvature and sediment properties. The simple model appropriately simulates the pattern and rate of meander expansion and migrations of the White River, Indiana and the East Nishnabotna River, Iowa. Application of the one-dimensional model to sine -generated alluvial channels indicates that meander migration reaches its maximum when the relative radius of curvature reaches about 4.8, or when the sinuosity of meander approaches 1.3. A two-dimensional numerical model, DYNAMIC, which predicts both lateral and longitudinal migration of alluvial channels is then developed, based on a system of quasi -steady depth-averaged flow dynamic equations, a sediment continuity equation, and a bank erosion equation. A linear analysis of the two-dimensional model leads to a convolutional relation between the rate of meander migration and flow and sediment properties. In the two-dimensional numerical analysis, a numerical algorithm called FLOWSOL is developed to solve the flow dynamic equations. The flow algorithm is then linked to the sediment continuity equation and bank erosion equation to simulate bed deformation and bank erosion. The developed two-dimensional model is applied to calculate the velocity profiles in Rozovskii's experiments and the bed deformation and shear stress in Hooke's experiments. Good agreement is obtained between the calculated and measured velocities, shear stresses and bed profiles in all experiments. Small scaled meandering rivers are developed successfully on a floodplain with or without cohesive materials (about 3%) in a wide
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.
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.
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.
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.
Suzuki, Shinsuke; Jensen, Emily L. S.; Bossaerts, Peter; O’Doherty, John P.
2016-01-01
Our attitude toward risk plays a crucial role in influencing our everyday decision-making. Despite its importance, little is known about how human risk-preference can be modulated by observing risky behavior in other agents at either the behavioral or the neural level. Using fMRI combined with computational modeling of behavioral data, we show that human risk-preference can be systematically altered by the act of observing and learning from others’ risk-related decisions. The contagion is driven specifically by brain regions involved in the assessment of risk: the behavioral shift is implemented via a neural representation of risk in the caudate nucleus, whereas the representations of other decision-related variables such as expected value are not affected. Furthermore, we uncover neural computations underlying learning about others’ risk-preferences and describe how these signals interact with the neural representation of risk in the caudate. Updating of the belief about others’ preferences is associated with neural activity in the dorsolateral prefrontal cortex (dlPFC). Functional coupling between the dlPFC and the caudate correlates with the degree of susceptibility to the contagion effect, suggesting that a frontal–subcortical loop, the so-called dorsolateral prefrontal–striatal circuit, underlies the modulation of risk-preference. Taken together, these findings provide a mechanistic account for how observation of others’ risky behavior can modulate an individual’s own risk-preference. PMID:27001826
Reduced Dynamic Models in Epithelial Transport
Hernández, Julio A.
2013-01-01
Most models developed to represent transport across epithelia assume that the cell interior constitutes a homogeneous compartment, characterized by a single concentration value of the transported species. This conception differs significantly from the current view, in which the cellular compartment is regarded as a highly crowded media of marked structural heterogeneity. Can the finding of relatively simple dynamic properties of transport processes in epithelia be compatible with this complex structural conception of the cell interior? The purpose of this work is to contribute with one simple theoretical approach to answer this question. For this, the techniques of model reduction are utilized to obtain a two-state reduced model from more complex linear models of transcellular transport with a larger number of intermediate states. In these complex models, each state corresponds to the solute concentration in an intermediate intracellular compartment. In addition, the numerical studies reveal that it is possible to approximate a general two-state model under conditions where strict reduction of the complex models cannot be performed. These results contribute with arguments to reconcile the current conception of the cell interior as a highly complex medium with the finding of relatively simple dynamic properties of transport across epithelial cells. PMID:23533397
Bioinactivation: Software for modelling dynamic microbial inactivation.
Garre, Alberto; Fernández, Pablo S; Lindqvist, Roland; Egea, Jose A
2017-03-01
This contribution presents the bioinactivation software, which implements functions for the modelling of isothermal and non-isothermal microbial inactivation. This software offers features such as user-friendliness, modelling of dynamic conditions, possibility to choose the fitting algorithm and generation of prediction intervals. The software is offered in two different formats: Bioinactivation core and Bioinactivation SE. Bioinactivation core is a package for the R programming language, which includes features for the generation of predictions and for the fitting of models to inactivation experiments using non-linear regression or a Markov Chain Monte Carlo algorithm (MCMC). The calculations are based on inactivation models common in academia and industry (Bigelow, Peleg, Mafart and Geeraerd). Bioinactivation SE supplies a user-friendly interface to selected functions of Bioinactivation core, namely the model fitting of non-isothermal experiments and the generation of prediction intervals. The capabilities of bioinactivation are presented in this paper through a case study, modelling the non-isothermal inactivation of Bacillus sporothermodurans. This study has provided a full characterization of the response of the bacteria to dynamic temperature conditions, including confidence intervals for the model parameters and a prediction interval of the survivor curve. We conclude that the MCMC algorithm produces a better characterization of the biological uncertainty and variability than non-linear regression. The bioinactivation software can be relevant to the food and pharmaceutical industry, as well as to regulatory agencies, as part of a (quantitative) microbial risk assessment.
Dynamic Alignment Models for Neural Coding
Kollmorgen, Sepp; Hahnloser, Richard H. R.
2014-01-01
Recently, there have been remarkable advances in modeling the relationships between the sensory environment, neuronal responses, and behavior. However, most models cannot encompass variable stimulus-response relationships such as varying response latencies and state or context dependence of the neural code. Here, we consider response modeling as a dynamic alignment problem and model stimulus and response jointly by a mixed pair hidden Markov model (MPH). In MPHs, multiple stimulus-response relationships (e.g., receptive fields) are represented by different states or groups of states in a Markov chain. Each stimulus-response relationship features temporal flexibility, allowing modeling of variable response latencies, including noisy ones. We derive algorithms for learning of MPH parameters and for inference of spike response probabilities. We show that some linear-nonlinear Poisson cascade (LNP) models are a special case of MPHs. We demonstrate the efficiency and usefulness of MPHs in simulations of both jittered and switching spike responses to white noise and natural stimuli. Furthermore, we apply MPHs to extracellular single and multi-unit data recorded in cortical brain areas of singing birds to showcase a novel method for estimating response lag distributions. MPHs allow simultaneous estimation of receptive fields, latency statistics, and hidden state dynamics and so can help to uncover complex stimulus response relationships that are subject to variable timing and involve diverse neural codes. PMID:24625448
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
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.
Modeling of intensified high dynamic star tracker.
Yan, Jinyun; Jiang, Jie; Zhang, Guangjun
2017-01-23
An intensified high dynamic star tracker (IHDST) is a photoelectric instrument and stably outputs three-axis attitude for a spacecraft at very high angular velocity. The IHDST uses an image intensifier to multiply the incident starlight. Thus, high sensitivity of the star detection is achieved under short exposure time such that extremely high dynamic performance is achieved. The IHDST differs from a traditional star tracker in terms of the imaging process. Therefore, we establish a quantum transfer model of IHDST based on stochastic process theory. By this model, the probability distribution of the output quantum number is obtained accurately. Then, we introduce two-dimensional Lorentz functions to describe the spatial spreading process of the IHDST. Considering the interaction of these two processes, a complete star imaging model of IHDST is provided. Using this model, the centroiding accuracy of the IHDST is analyzed in detail. Accordingly, a working parameter optimizing strategy is developed for high centroiding accuracy and improved dynamic performance. Finally, the laboratory tests and the night sky experiment support the conclusions.
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
Buck, David M; Plant, E Ashby; Ratcliff, Jennifer; Zielaskowski, Kate; Boerner, Patrick
2013-12-01
Membership in a valued group can provide an individual with a variety of benefits. As a result, people should be motivated to avoid being misidentified as a member of an outgroup, particularly a stigmatized outgroup. We argue that when group membership is not readily identifiable, concern over potentially being mistaken for a member of the outgroup (i.e., social contagion concerns) can be potent and can lead to avoidance of the outgroup. The current work shows that after controlling for negative attitudes toward homosexuality, social contagion concerns independently predict anxiety and avoidance in response to imagined, anticipated, and actual contact with a lesbian or gay individual. Results from these studies suggest that concern over misclassification of sexual orientation is an important and unique predictor of responses to contact with lesbian and gay people. Implications for intergroup contact and responses to other stigmatized groups are 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.
Culture and the Contagion of Conflict: Social Science and Computational Approaches
2015-08-05
WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Department of Psychology and Department of Computer Science, University of...outlets such as the Proceedings of the Royal Society B, Journal of Applied Psychology , Psychological Science, and Journal of Experimental Psychology ...Understanding the mechanisms that produce these contagion processes is critical for both psychological theory (which tends to look at conflict in isolated
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.
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
Dynamic plasmapause model based on THEMIS measurements
NASA Astrophysics Data System (ADS)
Liu, W.; Liu, X.
2015-12-01
We will present a dynamic plasmapause location model established based on five years of THEMIS measurements from 2009 to 2013. In total, 5878 plasmapause crossing events are identified, sufficiently covering all 24 Magnetic Local Time (MLT) sectors. Based on this plasmapause crossing database, we investigate the correlations between plasmapause locations with solar wind parameters and geomagnetic indices. Input parameters for the best fits are obtained for different MLT sectors and finally we choose five input parameters to build a plasmapause location model, including five-minute-averaged SYM-H, AL and AU indices as well as hourly-averaged AE and Kp indices. An out-of-sample comparison on the evolution of the plasmapause is shown during April 2001 magnetic storm, demonstrating good agreement between model results and observations. Two major advantages are achieved by this model. First, this model provides plasmapause locations at 24 MLT sectors, still providing good consistency with observations. Second, this model is able to reproduce dynamic variations of plasmapause in the time scale as short as five minutes.
Modeling the dynamical systems on experimental data
NASA Astrophysics Data System (ADS)
Janson, Natalie B.; Anishchenko, Vadim S.
1996-06-01
An attempt is made in the work to create qualitative models of some real biological systems, i.e., isolated frog's heart, a human's heart and a blood circulation system of a white rat. Sampled one-dimensional realizations of these systems were taken as the initial data. Correlation dimensions were calculated to evaluate the embedding dimensions of the systems' attractors. The result of the work are the systems of ordinary differential equations which approximately describe the dynamics of the systems under investigation.
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.
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.
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
2015-02-02
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.
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.
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.
Dynamic Factor Analysis Models with Time-Varying Parameters
ERIC Educational Resources Information Center
Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian
2011-01-01
Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…
Modeling the dynamics of bivalent histone modifications.
Ku, Wai Lim; Girvan, Michelle; Yuan, Guo-Cheng; Sorrentino, Francesco; Ott, Edward
2013-01-01
Epigenetic modifications to histones may promote either activation or repression of the transcription of nearby genes. Recent experimental studies show that the promoters of many lineage-control genes in stem cells have "bivalent domains" in which the nucleosomes contain both active (H3K4me3) and repressive (H3K27me3) marks. It is generally agreed that bivalent domains play an important role in stem cell differentiation, but the underlying mechanisms remain unclear. Here we formulate a mathematical model to investigate the dynamic properties of histone modification patterns. We then illustrate that our modeling framework can be used to capture key features of experimentally observed combinatorial chromatin states.
A dynamics model for fine coal flotation
Youjun, T.; Maixi, L.
1999-07-01
Through a large amount of experiments, this article studied the effect of the entrapment of water flow on the fine coal flotation during the flotation, and also investigated the relation between the constant of water flotation rate and different operation variables, and resulted in its equation. The water-recycling model is determined, and finally, the dynamics model on relation between the recovery of fine particle and the water recovery in concentration is established. The equation about ash of fine clean coal in any flotation time is derived by introduction of de-ashed coefficient.
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
Dynamical α -cluster model of 16O
NASA Astrophysics Data System (ADS)
Halcrow, C. J.; King, C.; Manton, N. S.
2017-03-01
We calculate the low-lying spectrum of the 16O nucleus using an α -cluster model which includes the important tetrahedral and square configurations. Our approach is motivated by the dynamics of α -particle scattering in the Skyrme model. We are able to replicate the large energy splitting that is observed between states of identical spin but opposite parities. We also provide a novel interpretation of the first excited state of 16O and make predictions for the energies of 6- states that have yet to be observed experimentally.
Simple models for biomembrane structure and dynamics
NASA Astrophysics Data System (ADS)
Brown, Frank L. H.
2007-07-01
Simulation of biomembranes over length and time scales relevant to cellular biology is not currently feasible with molecular dynamics including full atomic detail. Barring an unforeseen revolution in the computer industry, this situation will not change for many decades. We present two coarse grained simulation models for biomembranes that treat water implicitly (i.e. no water molecules appear in our simulations. The hydrophobic effect, hydrodynamics and related properties are approximately included without simulation of solvent). These models enable the study of systems and phenomena previously intractable to simulation. The influence of membrane bound proteins on lipid ordering and the diffusion of membrane bound proteins is discussed.
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
Directed network discovery with dynamic network modelling.
Anzellotti, Stefano; Kliemann, Dorit; Jacoby, Nir; Saxe, Rebecca
2017-02-16
Cognitive tasks recruit multiple brain regions. Understanding how these regions influence each other (the network structure) is an important step to characterize the neural basis of cognitive processes. Often, limited evidence is available to restrict the range of hypotheses a priori, and techniques that sift efficiently through a large number of possible network structures are needed (network discovery). This article introduces a novel modelling technique for network discovery (Dynamic Network Modelling or DNM) that builds on ideas from Granger Causality and Dynamic Causal Modelling introducing three key changes: (1) efficient network discovery is implemented with statistical tests on the consistency of model parameters across participants, (2) the tests take into account the magnitude and sign of each influence, and (3) variance explained in independent data is used as an absolute (rather than relative) measure of the quality of the network model. In this article, we outline the functioning of DNM, we validate DNM in simulated data for which the ground truth is known, and we report an example of its application to the investigation of influences between regions during emotion recognition, revealing top-down influences from brain regions encoding abstract representations of emotions (medial prefrontal cortex and superior temporal sulcus) onto regions engaged in the perceptual analysis of facial expressions (occipital face area and fusiform face area) when participants are asked to switch between reporting the emotional valence and the age of a face.
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
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.
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.
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.
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
A range extender hybrid electric vehicle dynamic model
Powell, B.K.; Pilutti, T.E.
1994-12-31
This paper describes a dynamic model possessing the key system components of a Range Extender Hybrid Electric Vehicle. The model is suitable for dynamic analysis, control law synthesis, and prototype simulation.
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
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.
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
Mathematical Model of Porous Medium Dynamics
NASA Astrophysics Data System (ADS)
Gerschuk, Peotr; Sapozhnikov, Anatoly
1999-06-01
Semiempirical model describing porous material strains under pulse mechanical and thermal loadings is proposed. Porous medium is considered as continuous one but with special form of pressure dependence upon strain. This model takes into account principal features of porous materials behavior which can be observed when the material is strained in dynamic and static experiments ( non-reversibility of large strains, nonconvexity of loading curve). Elastoplastic properties of porous medium, its damages when it is strained and dynamic fracture are also taken into account. Dispersion of unidirectional motion caused by medium heterogeneity (porousness) is taken into acount by introducing the physical viscosity depending upon pores size. It is supposed that at every moment of time pores are in equilibrium with pressure i.e. kinetic of pores collapse is not taken into account. The model is presented by the system of differential equations connecting pressure and energy of porous medium with its strain. These equations close system of equations of motion and continuity which then is integrated numerically. The proposed model has been tested on carbon materials and porous copper . Results of calculation of these materials shock compressing are in satisfactory agreement with experimental data. Results of calculation of thin plate with porous copper layer collision are given as an illustration.
Multiscale model approach for magnetization dynamics simulations
NASA Astrophysics Data System (ADS)
De Lucia, Andrea; Krüger, Benjamin; Tretiakov, Oleg A.; Kläui, Mathias
2016-11-01
Simulations of magnetization dynamics in a multiscale environment enable the rapid evaluation of the Landau-Lifshitz-Gilbert equation in a mesoscopic sample with nanoscopic accuracy in areas where such accuracy is required. We have developed a multiscale magnetization dynamics simulation approach that can be applied to large systems with spin structures that vary locally on small length scales. To implement this, the conventional micromagnetic simulation framework has been expanded to include a multiscale solving routine. The software selectively simulates different regions of a ferromagnetic sample according to the spin structures located within in order to employ a suitable discretization and use either a micromagnetic or an atomistic model. To demonstrate the validity of the multiscale approach, we simulate the spin wave transmission across the regions simulated with the two different models and different discretizations. We find that the interface between the regions is fully transparent for spin waves with frequency lower than a certain threshold set by the coarse scale micromagnetic model with no noticeable attenuation due to the interface between the models. As a comparison to exact analytical theory, we show that in a system with a Dzyaloshinskii-Moriya interaction leading to spin spirals, the simulated multiscale result is in good quantitative agreement with the analytical calculation.
A dynamical model of tumour immunotherapy.
Frascoli, Federico; Kim, Peter S; Hughes, Barry D; Landman, Kerry A
2014-07-01
A coupled ordinary differential equation model of tumour-immune dynamics is presented and analysed. The model accounts for biological and clinical factors which regulate the interaction rates of cytotoxic T lymphocytes on the surface of the tumour mass. A phase plane analysis demonstrates that competition between tumour cells and lymphocytes can result in tumour eradication, perpetual oscillations, or unbounded solutions. To investigate the dependence of the dynamic behaviour on model parameters, the equations are solved analytically and conditions for unbounded versus bounded solutions are discussed. An analytic characterisation of the basin of attraction for oscillatory orbits is given. It is also shown that the tumour shape, characterised by a surface area to volume scaling factor, influences the size of the basin, with significant consequences for therapy design. The findings reveal that the tumour volume must surpass a threshold size that depends on lymphocyte parameters for the cancer to be completely eliminated. A semi-analytic procedure to calculate oscillation periods and determine their sensitivity to model parameters is also presented. Numerical results show that the period of oscillations exhibits notable nonlinear dependence on biologically relevant conditions.
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
A dynamic network model for interbank market
NASA Astrophysics Data System (ADS)
Xu, Tao; He, Jianmin; Li, Shouwei
2016-12-01
In this paper, a dynamic network model based on agent behavior is introduced to explain the formation mechanism of interbank market network. We investigate the impact of credit lending preference on interbank market network topology, the evolution of interbank market network and stability of interbank market. Experimental results demonstrate that interbank market network is a small-world network and cumulative degree follows the power-law distribution. We find that the interbank network structure keeps dynamic stability in the network evolution process. With the increase of bank credit lending preference, network clustering coefficient increases and average shortest path length decreases monotonously, which improves the stability of the network structure. External shocks are main threats for the interbank market and the reduction of bank external investment yield rate and deposits fluctuations contribute to improve the resilience of the banking system.
Modeling of tower relief dynamics: Part 1
Cassata, J.R.; Dasgupta, S.; Gandhi, S.L. )
1993-10-01
In an environmentally responsible, safe and health-conscious design, a relief system must contain all relieving gases or vapors. The system must include treatment of these gases or vapors in a flare, scrubber or other appropriate device prior to discharge to the atmosphere. The benefit of a dynamic simulation is most significant in designing these systems. Dynamic modeling provides accurate answers to key questions which must be addressed. It identifies the design-setting relief scenario for any possible upset such as loss of reflux, power failure, loss of cooling water, fire, etc. It accurately quantifies the maximum relief rate and time dependency of the relief rates. This permits a safe relief system design that is not overly conservative.
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
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.
Models for inference in dynamic metacommunity systems
Dorazio, R.M.; Kery, M.; Royle, J. Andrew; Plattner, M.
2010-01-01
A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species-and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity. ?? 2010 by the Ecological Society of America.
Models for inference in dynamic metacommunity systems
Dorazio, Robert M.; Kery, Marc; Royle, J. Andrew; Plattner, Matthias
2010-01-01
A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species- and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity.
Dynamical model for light composite fermions
NASA Astrophysics Data System (ADS)
Derman, Emanuel
1981-04-01
A simple dynamical model for the internal structure of the three light lepton and quark generations (νe,e,u,d), (νμ,μ,c,s), and (ντ,τ,t,b) is proposed. Each generation is constructed of only one fundamental massive generation F=(L∘,L-,U,D) with the same (SU3)c×SU2×U1 quantum numbers as the light generations, bound to a core of one or more massive Higgs bosons H, where H is the single physical Higgs boson necessary for spontaneous symmetry breaking in the standard model. For example, e-=[L-H], μ-=[L-HH], τ-=[L-HHH]. It is shown that the known binding force due to H exchange is attractive and strong enough to produce light bound states. Dynamical calculations for the bound-state composite fermions using the Bethe-Salpeter equation, together with some phenomenological imput, suggest MH~16 TeV and MF~100 GeV. It is likely that such bound states can have properties compatible with the up to now apparently elementary appearance of known fermions, for example, their Dirac magnetic moments and absence of intergeneration radiative decays (such as μ-->eδ). Phenomenological consequences and tests of the model are discussed.
Dynamical model for light composite fermions
Derman, E.
1981-04-01
A simple dynamical model for the internal structure of the three light lepton and quark generations (..nu../sub e/,e,u,d), (..nu../sub ..mu../,..mu..,c,s), and (..nu../sub tau/,tau,t,b) is proposed. Each generation is constructed of only one fundamental massive generation F=(L-italic/sup 0/,L/sup -/,U,D) with the same (SU/sub 3/)/sub c/ x SU/sub 2/ x U/sub 1/ quantum numbers as the light generations, bound to a core of one or more massive Higgs bosons H, where H is the single physical Higgs boson necessary for spontaneous symmetry breaking in the standard model. For example, e/sup -/=L/sup -/H), ..mu../sup -/=L/sup -/HH), tau/sup -/=L/sup -/HHH). It is shown that the known binding force due to H exchange is attractive and strong enough to produce light bound states. Dynamical calculations for the bound-state composite fermions using the Bethe-Salpeter equation, together with some phenomenological imput, suggest M/sub H/approx.16 TeV and M/sub F/approx.100 GeV. It is likely that such bound states can have properties compatible with the up to now apparently elementary appearance of known fermions, for example, their Dirac magnetic moments and absence of intergeneration radiative decays (such as ..mu -->..e..gamma..). Phenomenological consequences and tests of the model are discussed.
Modeling cell dynamics under mobile phone radiation.
Minelli, Tullio Antonio; Balduzzo, Maurizio; Milone, Francesco Ferro; Nofrate, Valentina
2007-04-01
Perturbations by pulse-modulated microwave radiation from GSM mobile phones on neuron cell membrane gating and calcium oscillations have been suggested as a possible mechanism underlying activation of brain states and electroencephalographic epiphenomena. As the employ of UMTS phones seems to reveal other symptoms, a unified phenomenological framework is needed. In order to explain possible effects of mobile phone radiation on cell oscillations, GSM and UMTS low-frequency envelopes have been detected, recorded and used as input in cell models. Dynamical systems endowed with contiguous regular and chaotic regimes suitable to produce stochastic resonance can both account for the perturbation of the neuro-electrical activity and even for the low intensity of the signal perceived by high sensitive subjects. Neuron models of this kind can be employed as a reductionist hint for the mentioned phenomenology. The Hindmarsh-Rose model exhibits frequency enhancement and regularization phenomena induced by weak GSM and UMTS. More realistic simulations of cell membrane gating and calcium oscillations have been performed with the help of an adaptation of the Chay-Keizer dynamical system. This scheme can explain the suspected subjective sensitivity to mobile phone signals under the thermal threshold, in terms of cell calcium regularity mechanisms. Concerning the two kinds of emission, the stronger occupation of the ELF band of last generation UMTS phones is compensated by lower power emitted.
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
Oxygen and seizure dynamics: II. Computational modeling
Wei, Yina; Ullah, Ghanim; Ingram, Justin
2014-01-01
Electrophysiological recordings show intense neuronal firing during epileptic seizures leading to enhanced energy consumption. However, the relationship between oxygen metabolism and seizure patterns has not been well studied. Recent studies have developed fast and quantitative techniques to measure oxygen microdomain concentration during seizure events. In this article, we develop a biophysical model that accounts for these experimental observations. The model is an extension of the Hodgkin-Huxley formalism and includes the neuronal microenvironment dynamics of sodium, potassium, and oxygen concentrations. Our model accounts for metabolic energy consumption during and following seizure events. We can further account for the experimental observation that hypoxia can induce seizures, with seizures occurring only within a narrow range of tissue oxygen pressure. We also reproduce the interplay between excitatory and inhibitory neurons seen in experiments, accounting for the different oxygen levels observed during seizures in excitatory vs. inhibitory cell layers. Our findings offer a more comprehensive understanding of the complex interrelationship among seizures, ion dynamics, and energy metabolism. PMID:24671540
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.
Development of Improved Dynamic Failure Models.
1985-02-15
M 1.35 g/cm3 ) was used to produce a Chapman - Jouguet pressure of 16.3 GPa. The cylinder was surrounded by a PMHA tube of 1.15 cm thickness and a steel...3 mproved computational models were developed for dynamic material failure by Shear banding and ductile fracture. The research effort involved theory ...Cylinder at 56 ps After Detonation ..................... VI-41 ý,r I.4 I.P VI.2 Fragment (a) of 4340 Steel Cylinder (RC 40) and Photomicrographs (b and c) of
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 model of the threshold displacement energy
NASA Astrophysics Data System (ADS)
Kupchishin, A. I.; Kupchishin, A. A.
2017-01-01
A dynamic (cascade-probability) model for calculating the threshold displacement energy of knocked-out atoms (Ed) was proposed taking into account the influence of the instability zone (spontaneous recombination). General expression was recorded for Ed depending on the formation energy of interstitial atoms Ef and vacancies Ei, on the energy transfer coefficient α and the number of interactions i needed to move the atom out of the instability zone. The parameters of primary particles were calculated. Comparison of calculations with experimental data gives a satisfactory agreement.
Improved dynamical modelling of the Arches cluster
NASA Astrophysics Data System (ADS)
Lee, Joowon; Kim, Sungsoo S.
2014-05-01
Recently, Clarkson et al. (2012) measured the intrinsic velocity dispersion of the Arches cluster, a young and massive star cluster in the Galactic center. Using the observed velocity dispersion profile and the surface brightness profile of Espinoza et al. (2009), they estimate the cluster's present-day mass to be ˜ 1.5×104 M⊙ by fitting an isothermal King model. In this study, we trace the best-fit initial mass for the Arches cluster using the same observed data set and also the anisotropic Fokker-Planck calculations for the dynamical evolution.
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
Scalar model for frictional precursors dynamics.
Taloni, Alessandro; Benassi, Andrea; Sandfeld, Stefan; Zapperi, Stefano
2015-02-02
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.
AFDM: An Advanced Fluid-Dynamics Model
Wilhelm, D.
1990-09-01
This volume describes the Advanced Fluid-Dynamics Model (AFDM) for topologies, flow regimes, and interfacial areas. The objective of these models is to provide values for the interfacial areas between all components existing in a computational cell. The interfacial areas are then used to evaluate the mass, energy, and momentum transfer between the components. A new approach has been undertaken in the development of a model to convect the interfacial areas of the discontinuous velocity fields in the three-velocity-field environment of AFDM. These interfacial areas are called convectible surface areas. The continuous and discontinuous components are chosen using volume fraction and levitation criteria. This establishes so-called topologies for which the convectible surface areas can be determined. These areas are functions of space and time. Solid particulates that are limited to being discontinuous within the bulk fluid are assumed to have a constant size. The convectible surface areas are subdivided to model contacts between two discontinuous components or discontinuous components and the structure. The models have been written for the flow inside of large pools. Therefore, the structure is tracked only as a boundary to the fluid volume without having a direct influence on velocity or volume fraction distribution by means of flow regimes or boundary layer models. 17 refs., 7 tabs., 18 figs.
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.
Gradient navigation model for pedestrian dynamics
NASA Astrophysics Data System (ADS)
Dietrich, Felix; Köster, Gerta
2014-06-01
We present a microscopic ordinary differential equation (ODE)-based model for pedestrian dynamics: the gradient navigation model. The model uses a superposition of gradients of distance functions to directly change the direction of the velocity vector. The velocity is then integrated to obtain the location. The approach differs fundamentally from force-based models needing only three equations to derive the ODE system, as opposed to four in, e.g., the social force model. Also, as a result, pedestrians are no longer subject to inertia. Several other advantages ensue: Model-induced oscillations are avoided completely since no actual forces are present. The derivatives in the equations of motion are smooth and therefore allow the use of fast and accurate high-order numerical integrators. At the same time, the existence and uniqueness of the solution to the ODE system follow almost directly from the smoothness properties. In addition, we introduce a method to calibrate parameters by theoretical arguments based on empirically validated assumptions rather than by numerical tests. These parameters, combined with the accurate integration, yield simulation results with no collisions of pedestrians. Several empirically observed system phenomena emerge without the need to recalibrate the parameter set for each scenario: obstacle avoidance, lane formation, stop-and-go waves, and congestion at bottlenecks. The density evolution in the latter is shown to be quantitatively close to controlled experiments. Likewise, we observe a dependence of the crowd velocity on the local density that compares well with benchmark fundamental diagrams.
A dynamic localization model with stochastic backscatter
NASA Technical Reports Server (NTRS)
Carati, Daniele; Ghosal, Sandip
1994-01-01
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
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.
Absence of influential spreaders in rumor dynamics
NASA Astrophysics Data System (ADS)
Borge-Holthoefer, Javier; Moreno, Yamir
2012-02-01
Recent research [Kitsak, Gallos, Havlin, Liljeros, Muchnik, Stanley, and Makse, Nature Physics1745-247310.1038/nphys1746 6, 888 (2010)] has suggested that coreness, and not degree, constitutes a better topological descriptor to identify influential spreaders in complex networks. This hypothesis has been verified in the context of disease spreading. Here, we instead focus on rumor spreading models, which are more suited for social contagion and information propagation. To this end, we perform extensive computer simulations on top of several real-world networks and find opposite results. Namely, we show that the spreading capabilities of the nodes do not depend on their k-core index, which instead determines whether or not a given node prevents the diffusion of a rumor to a system-wide scale. Our findings are relevant both for sociological studies of contagious dynamics and for the design of efficient commercial viral processes.
Constructing Dynamic Event Trees from Markov Models
Paolo Bucci; Jason Kirschenbaum; Tunc Aldemir; Curtis Smith; Ted Wood
2006-05-01
In the probabilistic risk assessment (PRA) of process plants, Markov models can be used to model accurately the complex dynamic interactions between plant physical process variables (e.g., temperature, pressure, etc.) and the instrumentation and control system that monitors and manages the process. One limitation of this approach that has prevented its use in nuclear power plant PRAs is the difficulty of integrating the results of a Markov analysis into an existing PRA. In this paper, we explore a new approach to the generation of failure scenarios and their compilation into dynamic event trees from a Markov model of the system. These event trees can be integrated into an existing PRA using software tools such as SAPHIRE. To implement our approach, we first construct a discrete-time Markov chain modeling the system of interest by: a) partitioning the process variable state space into magnitude intervals (cells), b) using analytical equations or a system simulator to determine the transition probabilities between the cells through the cell-to-cell mapping technique, and, c) using given failure/repair data for all the components of interest. The Markov transition matrix thus generated can be thought of as a process model describing the stochastic dynamic behavior of the finite-state system. We can therefore search the state space starting from a set of initial states to explore all possible paths to failure (scenarios) with associated probabilities. We can also construct event trees of arbitrary depth by tracing paths from a chosen initiating event and recording the following events while keeping track of the probabilities associated with each branch in the tree. As an example of our approach, we use the simple level control system often used as benchmark in the literature with one process variable (liquid level in a tank), and three control units: a drain unit and two supply units. Each unit includes a separate level sensor to observe the liquid level in the tank
Modeling correlated human dynamics with temporal preference
NASA Astrophysics Data System (ADS)
Wang, Peng; Zhou, Tao; Han, Xiao-Pu; Wang, Bing-Hong
2014-03-01
We empirically study the activity pattern of individual blog-posting and observe the interevent time distributions decay as power-laws at both individual and population level. As different from previous studies, we find significant short-term memory in it. Moreover, the memory coefficient first decays in a power law and then turns to an exponential form. Our findings produce evidence for the strong short-term memory in human dynamics and challenge previous models. Accordingly, we propose a simple model based on temporal preference, which can well reproduce both the heavy-tailed nature and the strong memory effects. This work helps in understanding the temporal regularities of online human behaviors.
Dynamic modelling of packaging material flow systems.
Tsiliyannis, Christos A
2005-04-01
A dynamic model has been developed for reused and recycled packaging material flows. It allows a rigorous description of the flows and stocks during the transition to new targets imposed by legislation, product demand variations or even by variations in consumer discard behaviour. Given the annual reuse and recycle frequency and packaging lifetime, the model determines all packaging flows (e.g., consumption and reuse) and variables through which environmental policy is formulated, such as recycling, waste and reuse rates and it identifies the minimum number of variables to be surveyed for complete packaging flow monitoring. Simulation of the transition to the new flow conditions is given for flows of packaging materials in Greece, based on 1995--1998 field inventory and statistical data.
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.
Macroscopic model for solvated ion dynamics
NASA Astrophysics Data System (ADS)
Chen, J.-H.; Adelman, S. A.
1980-02-01
A macroscopic treatment of solvated ion dynamics is developed and applied to calculate the limiting (zero concentration) conductance of cations in several aprotic solvents. The theory is based on a coupled set of electrostatic and hydrodynamic equations for the density, flow, and polarization fields induced in the polar solvent by a moving ion. These equations, which are derived by the Mori projection technique, include crucial local solvent structure (ion solvation) effects through solvent compressibility, and local constitutive parameters. If solvent structure is suppressed, the equations reduce to those derived previously by Onsager and Hubbard [J. B. Hubbard and L. Onsager, J. Chem. Phys. 67, 4850 (1977)]. The macroscopic equations are approximately decoupled into electrostatic and hydrodynamic parts. The decoupled equations are solved assuming a step density, viscosity, and dielectric constant model for the local solvent structure and dynamics. This yields analytic expressions for the viscous, ζV, and dielectric ζD, contributions to the ion friction coefficient. These expressions generalize, respectively, the Stokes and Zwanzig results for the (slip) viscous and dielectric friction so as to account for ion solvation effects. The friction coefficients involve a desolvation function Δ which depends on the local structure (density) and dynamics of the solvent. The drag coefficient results reduce in form to those of Zwanzig (within a flow gradient correction factor of 2/3) and Stokes for both weak (Δ→1) and strong (Δ→0) ion-solvent interaction. For Δ→1 the true ionic radius Ri appears in the drag formulas while for Δ→0 a renormalized solvated ion radius σ=Ri+2Rs (where Rs=solvent molecule radius) appears. The theory is fit to experimental cation conductances in pyridine, acetone, and acetonitrile by representing Δ by a two parameter switching function. Agreement between the model and experiment is satisfactory for all three solvents. Moreover
Radiative and dynamical modeling of Jupiter's atmosphere
NASA Astrophysics Data System (ADS)
Guerlet, Sandrine; Spiga, Aymeric
2016-04-01
Jupiter's atmosphere harbours a rich meteorology, with alternate westward and eastward zonal jets, waves signatures and long-living storms. Recent ground-based and spacecraft measurements have also revealed a rich stratospheric dynamics, with the observation of thermal signatures of planetary waves, puzzling meridional distribution of hydrocarbons at odds with predictions of photochemical models, and a periodic equatorial oscillation analogous to the Earth's quasi-biennal oscillation and Saturn's equatorial oscillation. These recent observations, along with the many unanswered questions (What drives and maintain the equatorial oscillations? How important is the seasonal forcing compared to the influence of internal heat? What is the large-scale stratospheric circulation of these giant planets?) motivated us to develop a complete 3D General Circulation Model (GCM) of Saturn and Jupiter. We aim at exploring the large-scale circulation, seasonal variability, and wave activity from the troposphere to the stratosphere of these giant planets. We will briefly present how we adapted our existing Saturn GCM to Jupiter. One of the main change is the addition of a stratospheric haze layer made of fractal aggregates in the auroral regions (poleward of 45S and 30N). This haze layer has a significant radiative impact by modifying the temperature up to +/- 15K in the middle stratosphere. We will then describe the results of radiative-convective simulations and how they compare to recent Cassini and ground-based temperature measurements. These simulations reproduce surprisingly well some of the observed thermal vertical and meridional gradients, but several important mismatches at low and high latitudes suggest that dynamics also plays an important role in shaping the temperature field. Finally, we will present full GCM simulations and discuss the main resulting features (waves and instabilities). We will also and discuss the impact of the choice of spatial resolution and
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
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
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.
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.
Dynamic publication model for neurophysiology databases.
Gardner, D; Abato, M; Knuth, K H; DeBellis, R; Erde, S M
2001-08-29
We have implemented a pair of database projects, one serving cortical electrophysiology and the other invertebrate neurones and recordings. The design for each combines aspects of two proven schemes for information interchange. The journal article metaphor determined the type, scope, organization and quantity of data to comprise each submission. Sequence databases encouraged intuitive tools for data viewing, capture, and direct submission by authors. Neurophysiology required transcending these models with new datatypes. Time-series, histogram and bivariate datatypes, including illustration-like wrappers, were selected by their utility to the community of investigators. As interpretation of neurophysiological recordings depends on context supplied by metadata attributes, searches are via visual interfaces to sets of controlled-vocabulary metadata trees. Neurones, for example, can be specified by metadata describing functional and anatomical characteristics. Permanence is advanced by data model and data formats largely independent of contemporary technology or implementation, including Java and the XML standard. All user tools, including dynamic data viewers that serve as a virtual oscilloscope, are Java-based, free, multiplatform, and distributed by our application servers to any contemporary networked computer. Copyright is retained by submitters; viewer displays are dynamic and do not violate copyright of related journal figures. Panels of neurophysiologists view and test schemas and tools, enhancing community support.
Dynamics of Fst for the island model.
Rottenstreich, Sivan; Hamilton, Matthew B; Miller, Judith R
2007-12-01
F(st) is a measure of genetic differentiation in a subdivided population. Sewall Wright observed that F(st)=1/1+2Nm in a haploid diallelic infinite island model, where N is the effective population size of each deme and m is the migration rate. In demonstrating this result, Wright relied on the infinite size of the population. Natural populations are not infinite and therefore they change over time due to genetic drift. In a finite population, F(st) becomes a random variable that evolves over time. In this work we ask, given an initial population state, what are the dynamics of the mean and variance of F(st) under the finite island model? In application both of these quantities are critical in the evaluation of F(st) data. We show that after a time of order N generations the mean of F(st) is slightly biased below 1/1+2Nm. Further we show that the variance of F(st) is of order 1/d where d is the number of demes in the population. We introduce several new mathematical techniques to analyze coalescent genealogies in a dynamic setting.
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.
Aggregate Dynamics in AN Evolutionary Network Model
NASA Astrophysics Data System (ADS)
Seufert, Adrian M.; Schweitzer, Frank
We analyze a model of interacting agents (e.g. prebiotic chemical species) which are represented by nodes of a network, whereas their interactions are mapped onto directed links between these nodes. On a fast time scale, each agent follows an eigendynamics based on catalytic support from other nodes, whereas on a much slower time scale the network evolves through selection and mutation of its nodes-agent. In the first part of the paper, we explain the dynamics of the model by means of characteristic snapshots of the network evolution and confirm earlier findings on crashes and recoveries in the network structure. In the second part, we focus on the aggregate behavior of the network dynamics. We show that the disruptions in the network structure are smoothed out, so that the average evolution can be described by a growth regime followed by a saturation regime, without an initial random regime. For the saturation regime, we obtain a logarithmic scaling between the average connectivity per node
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.
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).
Coordinated supply chain dynamic production planning model
NASA Astrophysics Data System (ADS)
Chandra, Charu; Grabis, Janis
2001-10-01
Coordination of different and often contradicting interests of individual supply chain members is one of the important issues in supply chain management because the individual members can not succeed without success of the supply chain and vice versa. This paper investigates a supply chain dynamic production planning problem with emphasis on coordination. A planning problem is formally described using a supply chain kernel, which defines supply chain configuration, management policies, available resources and objectives both at supply chain or macro and supply chain member or micro levels. The coordinated model is solved in order to balance decisions made at the macro and micro levels and members' profitability is used as the coordination criterion. The coordinated model is used to determine inventory levels and production capacity across the supply chain. Application of the coordinated model distributes costs burden uniformly among supply chain members and preserves overall efficiency of the supply chain. Influence of the demand series uncertainty is investigated. The production planning model is a part of the integrated supply chain decision modeling system, which is shared among the supply chain members across the Internet.
Computational Fluid Dynamics Modeling of Bacillus anthracis ...
Journal Article Three-dimensional computational fluid dynamics and Lagrangian particle deposition models were developed to compare the deposition of aerosolized Bacillus anthracis spores in the respiratory airways of a human with that of the rabbit, a species commonly used in the study of anthrax disease. The respiratory airway geometries for each species were derived from computed tomography (CT) or µCT images. Both models encompassed airways that extended from the external nose to the lung with a total of 272 outlets in the human model and 2878 outlets in the rabbit model. All simulations of spore deposition were conducted under transient, inhalation-exhalation breathing conditions using average species-specific minute volumes. Four different exposure scenarios were modeled in the rabbit based upon experimental inhalation studies. For comparison, human simulations were conducted at the highest exposure concentration used during the rabbit experimental exposures. Results demonstrated that regional spore deposition patterns were sensitive to airway geometry and ventilation profiles. Despite the complex airway geometries in the rabbit nose, higher spore deposition efficiency was predicted in the upper conducting airways of the human at the same air concentration of anthrax spores. This greater deposition of spores in the upper airways in the human resulted in lower penetration and deposition in the tracheobronchial airways and the deep lung than that predict
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
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
NASA Astrophysics Data System (ADS)
Shahzad, Syed Jawad Hussain; Nor, Safwan Mohd; Kumar, Ronald Ravinesh; Mensi, Walid
2017-01-01
This study examines the interdependence and contagion among US industry-level credit markets. We use daily data of 11 industries from 17 December 2007 to 31 December 2014 for the time-frequency, namely, wavelet squared coherence analysis. The empirical analysis reveals that Basic Materials (Utilities) industry credit market has the highest (lowest) interdependence with other industries. Basic Materials credit market passes cyclical effect to all other industries. The little "shift-contagion" as defined by Forbes and Rigobon (2002) is examined using elliptical and Archimedean copulas on the short-run decomposed series obtained through Variational Mode Decomposition (VMD). The contagion effects between US industry-level credit markets mainly occurred during the global financial crisis of 2007-08.
Dynamical Models of Terrestrial Planet Formation
NASA Astrophysics Data System (ADS)
Lunine, Jonathan I.; O'brien, David P.; Raymond, Sean N.; Morbidelli, Alessandro; Quinn, Thomas; Graps, Amara L.
2011-02-01
We review the problem of the formation of terrestrial planets, with particular emphasis on the interaction of dynamical and geochemical models. The lifetime of gas around stars in the process of formation is limited to a few million years based on astronomical observations, while isotopic dating of meteorites and the Earth-Moon system suggest that perhaps 50-100 million years were required for the assembly of the Earth. Therefore, much of the growth of the terrestrial planets in our own system is presumed to have taken place under largely gas-free conditions, and the physics of terrestrial planet formation is dominated by gravitational interactions and collisions. The earliest phase of terrestrial-planet formation involve the growth of km-sized or larger planetesimals from dust grains, followed by the accumulations of these planetesimals into ∼100 lunar- to Mars-mass bodies that are initially gravitationally isolated from one-another in a swarm of smaller planetesimals, but eventually grow to the point of significantly perturbing one-another. The mutual perturbations between the embryos, combined with gravitational stirring by Jupiter, lead to orbital crossings and collisions that drive the growth to Earth-sized planets on a timescale of 107-108 years. Numerical treatment of this process has focussed on the use of symplectic integrators which can rapidy integrate the thousands of gravitationally-interacting bodies necessary to accurately model planetary growth. While the general nature of the terrestrial planets-their sizes and orbital parameters-seem to be broadly reproduced by the models, there are still some outstanding dynamical issues. One of these is the presence of an embryo-sized body, Mars, in our system in place of the more massive objects that simulations tend to yield. Another is the effect such impacts have on the geochemistry of the growing planets; re-equilibration of isotopic ratios of major elements during giant impacts (for example) must be
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 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.
A two-stage dynamic model for visual tracking.
Kristan, Matej; Kovacic, Stanislav; Leonardis, Aleš; Pers, Janez
2010-12-01
We propose a new dynamic model which can be used within blob trackers to track the target's center of gravity. A strong point of the model is that it is designed to track a variety of motions which are usually encountered in applications such as pedestrian tracking, hand tracking, and sports. We call the dynamic model a two-stage dynamic model due to its particular structure, which is a composition of two models: a liberal model and a conservative model. The liberal model allows larger perturbations in the target's dynamics and is able to account for motions in between the random-walk dynamics and the nearly constant-velocity dynamics. On the other hand, the conservative model assumes smaller perturbations and is used to further constrain the liberal model to the target's current dynamics. We implement the two-stage dynamic model in a two-stage probabilistic tracker based on the particle filter and apply it to two separate examples of blob tracking: 1) tracking entire persons and 2) tracking of a person's hands. Experiments show that, in comparison to the widely used models, the proposed two-stage dynamic model allows tracking with smaller number of particles in the particle filter (e.g., 25 particles), while achieving smaller errors in the state estimation and a smaller failure rate. The results suggest that the improved performance comes from the model's ability to actively adapt to the target's motion during tracking.
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.
A simple dynamic model of respiratory pump.
Calabrese, Pascale; Baconnier, Pierre; Laouani, Aicha; Fontecave-Jallon, Julie; Guméry, Pierre-Yves; Eberhard, André; Benchetrit, Gila
2010-09-01
To study the interaction of forces that produce chest wall motion, we propose a model based on the lever system of Hillman and Finucane (J Appl Physiol 63(3):951-961, 1987) and introduce some dynamic properties of the respiratory system. The passive elements (rib cage and abdomen) are considered as elastic compartments linked to the open air via a resistive tube, an image of airways. The respiratory muscles (active) force is applied to both compartments. Parameters of the model are identified in using experimental data of airflow signal measured by pneumotachography and rib cage and abdomen signals measured by respiratory inductive plethysmography on eleven healthy volunteers in five conditions: at rest and with four level of added loads. A breath by breath analysis showed, whatever the individual and the condition are, that there are several breaths on which the airflow simulated by our model is well fitted to the airflow measured by pneumotachography as estimated by a determination coefficient R(2) > or = 0.70. This very simple model may well represent the behaviour of the chest wall and thus may be useful to interpret the relative motion of rib cage and abdomen during quiet breathing.
A nonlinear dynamic analogue model of substorms
NASA Astrophysics Data System (ADS)
Klimas, A. J.; Baker, D. N.; Roberts, D. A.; Fairfield, D. H.; Büchner, J.
Linear prediction filter studies have shown that the magnetospheric response to energy transfer from the solar wind contains both directly driven and unloading components. These studies have also shown that the magnetospheric response is significantly nonlinear and, thus, the linear prediction filtering technique and other correlative techniques which assume a linear magnetospheric response cannot give a complete deacription of that response. Here, the solar wind-magnetosphere interaction is discussed within the framework of deterministic nonlinear dynamics. An earlier dripping faucet mechanical analogue to the magnetosphere is first reviewed and then the plasma physical counterpart to the mechanical model is constructed. A Faraday loop in the magnetotail is considered and the relationship of electric potentials on the loop to changes in the magnetic flux threading the loop is developed. This approach leads to a model of geomagnetic activity which is similar to the earlier mechanical model but described in terms of the geometry and plasma contents of the magnetotail. This Faraday loop response model contains analogues to both the directly driven and the storage-release magnetospheric responses and it includes, in a fundamental way, the inherent nonlinearity of the solar wind-magnetosphere system. It can be chancterized as a nonlinear, damped harmonic oscillator that is driven by the loading-unloading substorm cycle. The model is able to explain many of the features of the linear prediction filter results. In particular, at low geomagnetic activity levels the model exbibits the "regular dripping" response which provides an explanation for the unloading component at 1 hour lag in the linear prediction filters. Further, the model suggests that the disappearance of the unloading component in the linear prediction filters at high geomagnetic activity levels is due to a chaotic transition beyond which the loading-unloading mechanism becomes aperiodic. The model predicts
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 Dynamic Fountain Model for Lunar Dust
NASA Technical Reports Server (NTRS)
Stubbs, T. J.; Vondrak, R. R.; Farrell, W. M.
2005-01-01
During the Apollo era of exploration it was discovered that sunlight was scattered at the terminators giving rise to horizon glow and streamers above the lunar surface. This was observed from the dark side of the Moon during sunset and sunrise by both surface landers and astronauts in orbit. These observations were quite unexpected, as the Moon was thought to be a pristine environment with a negligible atmosphere or exosphere. Subsequent investigations have shown that the sunlight was most likely scattered by electrostatically charged dust grains originating from the surface. It has since been demonstrated that this dust population could have serious implications for astronomical observations from the lunar surface. The lunar surface is electrostatically charged by the Moon s large-scale interaction with the local plasma environment and the photoemission of electrons due to solar ultra-violet (UV) light and X-rays. The like-charged surface and dust grains then act to repel each other, such that under certain conditions the dust grains are lifted above the surface. We present a dynamic fountain model which can explain how sub-micron dust is able to reach altitudes of up to approximately 100 km above the lunar surface. Previous static dust levitation models are most applicable to the heavier micron-sized grains in close proximity proximity to the surface, but they cannot explain the presence of extremely light grains at high altitudes. If we relax the static constraint applied to previous models, and instead assume that the grains are in constant motion (under the action of dynamic forces), a new picture emerges for the behavior of sub-micron lunar dust.
Computational modeling of intraocular gas dynamics.
Noohi, P; Abdekhodaie, M J; Cheng, Y L
2015-12-18
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.
Emotions on the loose: emotional contagion and the role of oxytocin in pigs.
Reimert, Inonge; Bolhuis, J Elizabeth; Kemp, Bas; Rodenburg, T Bas
2015-03-01
We studied emotional contagion, a simple form of empathy, and the role of oxytocin herein in pigs. Two training pigs per pen (n = 16 pens) were subjected to a positive treatment (pairwise access to a large compartment filled with peat, straw and some chocolate raisins) and a negative treatment (social isolation in a small compartment) in a test room using a within-subjects design. Thereafter, two naive pen mates joined the training pigs in the test room, but were not given access to the treatments. This allowed testing for emotional contagion. Subsequently, the naive pigs, serving as their own controls, were given 24 IU of oxytocin or a placebo intranasally 30 min before accompanying the training pigs, which were exposed to either the negative or positive treatment, to the test room. Behavioral differences found between the positive and negative treatments (e.g., play and "tail wagging" vs. standing alert, urinating, defecating and ears backward) show that the treatments induced a positive and negative emotional state in the training pigs, respectively. Changes in behaviors of the training pigs with and without naive pigs present (e.g., in ears backwards) and of the naive pigs with and without training pigs present (e.g., in standing alert) indicated that emotional contagion occurred, especially during the negative treatment. Oxytocin did not seem to affect the behavior of the treated naive pigs, but did affect behaviors (e.g., defecating) of the training pigs which had not received oxytocin. This suggests a role for oxytocin in pig communication, which merits further research.
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.
Ilies, Remus; Wagner, David T; Morgeson, Frederick P
2007-07-01
To expand on the understanding of how affective states are linked within teams, the authors describe a longitudinal study examining the linkages between team members' affective states over time. In a naturalistic team performance setting, they found evidence that the average affective state of the other team members was related to an individual team member's affect over time, even after controlling for team performance. In addition, they found that these affective linkages were moderated by individual differences in susceptibility to emotional contagion and collectivistic tendencies such that the strength of the linkage was stronger for those high in susceptibility and those with collectivistic tendencies. Implications for research and practice are discussed.
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.
Modelling of the Pele Fragmentation Dynamics
NASA Astrophysics Data System (ADS)
Verreault, Jimmy
2013-06-01
The Penetrator with Enhanced Lateral Effect (PELE) is a type of explosive-free projectile that undergoes radial fragmentation upon an impact with a target plate. This type of projectile is composed of a brittle cylindrical shell (the jacket) filled in its core with a material characterized with a large Poisson's ratio. Upon an impact with a target, the axial compression causes the filling to expand in the radial direction. However, due to the brittleness of the jacket material, very little radial deformation can occur which creates a radial stress between the two materials and a hoop stress in the jacket. Fragmentation of the jacket occurs if the hoop stress exceeds the material's ultimate stress. The PELE fragmentation dynamics is explored via Finite-Element Method (FEM) simulations using the AUTODYN explicit dynamics hydrocode. The numerical results are compared with an analytical model based on wave interactions, as well as with the experimental investigation of Paulus and Schirm (1996). The comparison is based on the mechanical stress in the filling, the resulting radial velocity of the fragments, the number of fragments generated and their mass distribution.
Modelling of the PELE fragmentation dynamics
NASA Astrophysics Data System (ADS)
Verreault, J.
2014-05-01
The Penetrator with Enhanced Lateral Effect (PELE) is a type of explosive-free projectile that undergoes radial fragmentation upon an impact with a target plate. This type of projectile is composed of a brittle cylindrical shell (the jacket) filled in its core with a material characterized with a large Poisson's ratio. Upon an impact with a target, the axial compression causes the filling to expand in the radial direction. However, due to the brittleness of the jacket material, very little radial deformation can occur which creates a radial stress between the two materials and a hoop stress in the jacket. Fragmentation of the jacket occurs if the hoop stress exceeds the material's ultimate stress. The PELE fragmentation dynamics is explored via Finite-Element Method (FEM) simulations using the Autodyn explicit dynamics hydrocode. The numerical results are compared with an analytical model based on wave interactions, as well as with the experimental investigation of Paulus and Schirm (1996). The comparison is based on the mechanical stress in the filling and the qualitative fragmentation of the jacket.
Nonlinear dynamical model of human gait
NASA Astrophysics Data System (ADS)
West, Bruce J.; Scafetta, Nicola
2003-05-01
We present a nonlinear dynamical model of the human gait control system in a variety of gait regimes. The stride-interval time series in normal human gait is characterized by slightly multifractal fluctuations. The fractal nature of the fluctuations becomes more pronounced under both an increase and decrease in the average gait. Moreover, the long-range memory in these fluctuations is lost when the gait is keyed on a metronome. Human locomotion is controlled by a network of neurons capable of producing a correlated syncopated output. The central nervous system is coupled to the motocontrol system, and together they control the locomotion of the gait cycle itself. The metronomic gait is simulated by a forced nonlinear oscillator with a periodic external force associated with the conscious act of walking in a particular way.
Molecular modelling and molecular dynamics of CFTR.
Callebaut, Isabelle; Hoffmann, Brice; Lehn, Pierre; Mornon, Jean-Paul
2017-01-01
The cystic fibrosis transmembrane conductance regulator (CFTR) protein is a member of the ATP-binding cassette (ABC) transporter superfamily that functions as an ATP-gated channel. Considerable progress has been made over the last years in the understanding of the molecular basis of the CFTR functions, as well as dysfunctions causing the common genetic disease cystic fibrosis (CF). This review provides a global overview of the theoretical studies that have been performed so far, especially molecular modelling and molecular dynamics (MD) simulations. A special emphasis is placed on the CFTR-specific evolution of an ABC transporter framework towards a channel function, as well as on the understanding of the effects of disease-causing mutations and their specific modulation. This in silico work should help structure-based drug discovery and design, with a view to develop CFTR-specific pharmacotherapeutic approaches for the treatment of CF in the context of precision medicine.
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.
Dynamic model of flexible phytoplankton nutrient uptake
Bonachela, Juan A.; Raghib, Michael; Levin, Simon A.
2011-01-01
The metabolic machinery of marine microbes can be remarkably plastic, allowing organisms to persist under extreme nutrient limitation. With some exceptions, most theoretical approaches to nutrient uptake in phytoplankton are largely dominated by the classic Michaelis–Menten (MM) uptake functional form, whose constant parameters cannot account for the observed plasticity in the uptake apparatus. Following seminal ideas by earlier researchers, we propose a simple cell-level model based on a dynamic view of the uptake process whereby the cell can regulate the synthesis of uptake proteins in response to changes in both internal and external nutrient concentrations. In our flexible approach, the maximum uptake rate and nutrient affinity increase monotonically as the external nutrient concentration decreases. For low to medium nutrient availability, our model predicts uptake and growth rates larger than the classic MM counterparts, while matching the classic MM results for large nutrient concentrations. These results have important consequences for global coupled models of ocean circulation and biogeochemistry, which lack this regulatory mechanism and are thus likely to underestimate phytoplankton abundances and growth rates in oligotrophic regions of the ocean. PMID:22143781
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
A dynamic model of reasoning and memory.
Hawkins, Guy E; Hayes, Brett K; Heit, Evan
2016-02-01
Previous models of category-based induction have neglected how the process of induction unfolds over time. We conceive of induction as a dynamic process and provide the first fine-grained examination of the distribution of response times observed in inductive reasoning. We used these data to develop and empirically test the first major quantitative modeling scheme that simultaneously accounts for inductive decisions and their time course. The model assumes that knowledge of similarity relations among novel test probes and items stored in memory drive an accumulation-to-bound sequential sampling process: Test probes with high similarity to studied exemplars are more likely to trigger a generalization response, and more rapidly, than items with low exemplar similarity. We contrast data and model predictions for inductive decisions with a recognition memory task using a common stimulus set. Hierarchical Bayesian analyses across 2 experiments demonstrated that inductive reasoning and recognition memory primarily differ in the threshold to trigger a decision: Observers required less evidence to make a property generalization judgment (induction) than an identity statement about a previously studied item (recognition). Experiment 1 and a condition emphasizing decision speed in Experiment 2 also found evidence that inductive decisions use lower quality similarity-based information than recognition. The findings suggest that induction might represent a less cautious form of recognition. We conclude that sequential sampling models grounded in exemplar-based similarity, combined with hierarchical Bayesian analysis, provide a more fine-grained and informative analysis of the processes involved in inductive reasoning than is possible solely through examination of choice data.
Dynamic models in research and management of biological invasions.
Buchadas, Ana; Vaz, Ana Sofia; Honrado, João P; Alagador, Diogo; Bastos, Rita; Cabral, João A; Santos, Mário; Vicente, Joana R
2017-03-25
Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales.
Kinematical and Dynamical Modeling of Elliptical Galaxies
NASA Astrophysics Data System (ADS)
Mamon, G. A.; Łokas, E.; Dekel, A.; Stoehr, F.; Cox, T. J.
Elements of kinematical and dynamical modeling of elliptical galaxies are presented. In projection, NFW models resemble Sérsic models, but with a very narrow range of shapes (m=3±1). The total density profile of ellipticals cannot be NFW-like because the predicted local M/L and aperture velocity dispersion within an effective radius (R_e) are much lower than observed. Stars must then dominate ellipticals out to a few R_e. Fitting an NFW model to the total density profile of Sérsic+NFW (stars+dark matter [DM]) ellipticals results in very high concentration parameters, as found by X-ray observers. Kinematical modeling of ellipticals assuming an isotropic NFW DM model underestimates M/L at the virial radius by a factor of 1.6 to 2.4, because dissipationless ΛCDM halos have slightly different density profiles and slightly radial velocity anisotropy. In N-body+gas simulations of ellipticals as merger remnants of spirals embedded in DM halos, the slope of the DM density profile is steeper when the initial spiral galaxies are gas-rich. The Hansen & Moore (2006) relation between anisotropy and the slope of the density profile breaks down for gas and DM, but the stars follow an analogous relation with slightly less radial anisotropies for a given density slope. Using kurtosis (h_4) to infer anisotropy in ellipticals is dangerous, as h4 is also sensitive to small levels of rotation. The stationary Jeans equation provides accurate masses out to 8 R_e. The discrepancy between the modeling of Romanowsky et al. (2003), indicating a dearth of DM in ellipticals, and the simulations analyzed by Dekel et al. (2005), which match the spectroscopic observations of ellipticals, is partly due to radial anisotropy and to observing oblate ellipticals face-on. However, one of the 15 solutions to the orbit modeling of Romanowsky et al. is found to have an amount and concentration of DM consistent with ΛCDM predictions.
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…
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.
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…
Dynamical models of Saturn's Phoebe ring
NASA Astrophysics Data System (ADS)
Tamayo, Daniel; Markham, Stephen; Hedman, Matthew M.; Burns, Joseph A.
2014-05-01
Saturn has the distinction of hosting the largest observed ring system in the solar sytem, the Phoebe Ring. Its vertical extent implicates Saturn’s irregular and distant satellite Phoebe as the source, with material being liberated through collisions. Owing to radiation forces, dusty debris is then swept inward toward Saturn on long timescales, spreading into a disk two orders of magnitude larger than Saturn’s more famous main rings. Previous work indicates that Saturn’s moon Iapetus should sweep up the majority of this infalling dark material. This would explain its striking two-faced surface, with one hemisphere ten times darker than the other. However, there is yet no direct observational confirmation of this mass transfer process. An important prediction for this model of Iapetus’ hemispherical dichotomy is that Iapetus should carve out an inner edge to the Phoebe ring. While scattered light from Saturn thwarts all attempts to detect this inner edge from Earth, we have recently developed a technique for detecting the Phoebe ring using the Cassini spacecraft. Preliminary work suggests we have found such an inner edge.In order to meaningfully interpret our findings, we require a dynamical model for the debris decaying inward from Phoebe. We will present the results of our analytical and numerical investigations.
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.
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.
Supercomputer modeling of volcanic eruption dynamics
NASA Astrophysics Data System (ADS)
Kieffer, S. W.; Valentine, G. A.; Woo, Mahn-Ling
1995-04-01
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) 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) relate equations-of-state for magma-gas mixtures to flow dynamics; (4) 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; (5) test the applicability of existing two-phase flow codes for problems related to the generation of volcanic long-period seismic signals; and (6) to extend our understanding and simulation capability to problems associated with emplacement of fragmental ejecta from large meteorite impacts.
A general dynamic model of flexible robot arms for control
NASA Technical Reports Server (NTRS)
Ding, X.; Tarn, T. J.; Bejczy, A. K.
1989-01-01
Hamilton's principle is used to derive the dynamic model for a large class of flexible robot arms. The resultant dynamic model consists of a system of partial differential-integral equations and the dynamic boundary conditions associated with it. Some properties of the model are observed, and its application to control is discussed. This model represents an infinite-dimensional nonlinear dynamic system and yet can be turned into a finite-dimensional system that could be obtained by modal expansion, if it is desired. This provides more flexibility for control purposes as well as for the analysis of the system.
Hacker, Karen; Collins, Jessica; Gross-Young, Leni; Almeida, Stephanie; Burke, Noreen
2008-01-01
From 2000-2005, Somerville, MA, experienced a number of youth overdoses and suicides. The community response followed CDC recommendations for contagion containment. A community coalition, Somerville Cares About Prevention, became a pivotal convener of community partners and a local research organization, the Institute for Community Health, provided needed expertise in surveillance and analysis. Mayoral leadership provided the impetus for action while community activists connected those at risk with mental health resources. Using a variety of data sources (including death certificates, youth risk surveys, 911 call data, and hospital discharges) overdose and suicide activity were monitored. Rates of suicide and overdose for 10-24-year-olds were higher than in previous years. Using case investigation methods, the majority of suicide victims were found to be linked through common peer groups and substance abuse. Subsequent community action steps included: a community-based trauma response team, improved media relationships, focus groups for suicide survivors, and prevention trainings to community stakeholders. Youth suicide and overdose activity subsided in May of 2005. The community partnerships were critical elements for developing a response to this public health crisis. This collaborative approach to suicide contagion used existing resources and provides important lessons learned for other communities facing similar circumstances.
Motor contagion during human-human and human-robot interaction.
Bisio, Ambra; Sciutti, Alessandra; Nori, Francesco; Metta, Giorgio; Fadiga, Luciano; Sandini, Giulio; Pozzo, Thierry
2014-01-01
Motor resonance mechanisms are known to affect humans' ability to interact with others, yielding the kind of "mutual understanding" that is the basis of social interaction. However, it remains unclear how the partner's action features combine or compete to promote or prevent motor resonance during interaction. To clarify this point, the present study tested whether and how the nature of the visual stimulus and the properties of the observed actions influence observer's motor response, being motor contagion one of the behavioral manifestations of motor resonance. Participants observed a humanoid robot and a human agent move their hands into a pre-specified final position or put an object into a container at various velocities. Their movements, both in the object- and non-object- directed conditions, were characterized by either a smooth/curvilinear or a jerky/segmented trajectory. These trajectories were covered with biological or non-biological kinematics (the latter only by the humanoid robot). After action observation, participants were requested to either reach the indicated final position or to transport a similar object into another container. Results showed that motor contagion appeared for both the interactive partner except when the humanoid robot violated the biological laws of motion. These findings suggest that the observer may transiently match his/her own motor repertoire to that of the observed agent. This matching might mediate the activation of motor resonance, and modulate the spontaneity and the pleasantness of the interaction, whatever the nature of the communication partner.
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…
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.
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
NASA Astrophysics Data System (ADS)
Cao, Shuying; Zheng, Jiaju; Sang, Jie; Zhang, Pengfei; Wang, Bowen; Huang, Wenmei
2015-05-01
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.
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
NASA Astrophysics Data System (ADS)
Davtyan, Aram; Dama, James F.; Voth, Gregory A.; Andersen, Hans C.
2015-04-01
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
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.
ERIC Educational Resources Information Center
Houser, Marian L.; Waldbuesser, Caroline
2017-01-01
Teachers appreciate nonverbally responsive students, but what is missing is an understanding of the direct influence of teachers' self-perceptions on their perceptions of how engaged their students are in class. Using the emotional contagion theory as a lens, this study examines the premise that satisfied instructors expect students to mirror…
McCollum, Gin; Roberts, Patrick D
2004-12-01
Natural, everyday sensorimotor behaviors, such as rising from sitting, typically have an intrinsic organization of several levels of analysis. Taking this intrinsic organization as key to understanding neural dynamics is neither a top-down nor a bottom-up approach, but rather a meshing of multiple centers and levels of analysis. Motor control requires body dynamics that are consistent with physical dynamics, besides the more microscopic levels of neural dynamics. The dynamics of separate movements have been investigated as if the ends can be capped off, separated from the rest of the individual's life. Is this dynamically correct? Even chaotic behavior is deterministic. However, the mathematics of nonlinear oscillations is not all of dynamics. This paper relates Bloch's dynamical theorem to the modular, conditional approach to sensorimotor and other neural functioning. Bloch's dynamical theorem lays a foundation for the piecewise study of structurally accurate dynamics in theoretical neurobiology. Piecewise studies can be used as a modeling option complementary to the methods of nonlinear oscillator dynamics. By applying Bloch's theorem, dynamics of movements analyzed piecewise can be extended into a smooth flow on any manifold, either as a whole or conditionally. Conditional dynamics makes dynamical modeling options explicit, often depending on what variables the organism can control, and allows one to take different modeling options at different junctures in analyzing the same phenomenon. For example, this approach allows the study of complex motor control problems to be reduced to modular constructions using singularities and flow lines. Dynamical contingencies are expressed using the mathematics of ordered structures. This paper presents Bloch's dynamical theorem and its relevance to model construction in theoretical neurobiology. Specific examples, integrated into physiological and behavioral context, are cited from the literature.
Analysing the temporal dynamics of model performance for hydrological models
NASA Astrophysics Data System (ADS)
Reusser, D. E.; Blume, T.; Schaefli, B.; Zehe, E.
2009-07-01
The temporal dynamics of hydrological model performance gives insights into errors that cannot be obtained from global performance measures assigning a single number to the fit of a simulated time series to an observed reference series. These errors can include errors in data, model parameters, or model structure. Dealing with a set of performance measures evaluated at a high temporal resolution implies analyzing and interpreting a high dimensional data set. This paper presents a method for such a hydrological model performance assessment with a high temporal resolution and illustrates its application for two very different rainfall-runoff modeling case studies. The first is the Wilde Weisseritz case study, a headwater catchment in the eastern Ore Mountains, simulated with the conceptual model WaSiM-ETH. The second is the Malalcahuello case study, a headwater catchment in the Chilean Andes, simulated with the physics-based model Catflow. The proposed time-resolved performance assessment starts with the computation of a large set of classically used performance measures for a moving window. The key of the developed approach is a data-reduction method based on self-organizing maps (SOMs) and cluster analysis to classify the high-dimensional performance matrix. Synthetic peak errors are used to interpret the resulting error classes. The final outcome of the proposed method is a time series of the occurrence of dominant error types. For the two case studies analyzed here, 6 such error types have been identified. They show clear temporal patterns, which can lead to the identification of model structural errors.
Analysing the temporal dynamics of model performance for hydrological models
NASA Astrophysics Data System (ADS)
Reusser, D. E.; Blume, T.; Schaefli, B.; Zehe, E.
2008-11-01
The temporal dynamics of hydrological model performance gives insights into errors that cannot be obtained from global performance measures assigning a single number to the fit of a simulated time series to an observed reference series. These errors can include errors in data, model parameters, or model structure. Dealing with a set of performance measures evaluated at a high temporal resolution implies analyzing and interpreting a high dimensional data set. This paper presents a method for such a hydrological model performance assessment with a high temporal resolution and illustrates its application for two very different rainfall-runoff modeling case studies. The first is the Wilde Weisseritz case study, a headwater catchment in the eastern Ore Mountains, simulated with the conceptual model WaSiM-ETH. The second is the Malalcahuello case study, a headwater catchment in the Chilean Andes, simulated with the physics-based model Catflow. The proposed time-resolved performance assessment starts with the computation of a large set of classically used performance measures for a moving window. The key of the developed approach is a data-reduction method based on self-organizing maps (SOMs) and cluster analysis to classify the high-dimensional performance matrix. Synthetic peak errors are used to interpret the resulting error classes. The final outcome of the proposed method is a time series of the occurrence of dominant error types. For the two case studies analyzed here, 6 such error types have been identified. They show clear temporal patterns which can lead to the identification of model structural errors.
Modeling Statistical and Dynamic Features of Earthquakes
NASA Astrophysics Data System (ADS)
Rydelek, P. A.; Suyehiro, K.; Sacks, S. I.; Smith, D. E.; Takanami, T.; Hatano, T.
2015-12-01
The cellular automaton earthquake model by Sacks and Rydelek (1995) is extended to explain spatio-temporal change in seismicity with the regional tectonic stress buildup. Our approach is to apply a simple Coulomb failure law to our model space of discrete cells, which successfully reproduces empirical laws (e.g. Gutenberg-Richter law) and dynamic failure characteristics (e.g. stress drop vs. magnitude and asperities) of earthquakes. Once the stress condition supersedes the Coulomb threshold on a discrete cell, its accumulated stress is transferred to only neighboring cells, which cascades to more neighboring cells to create various size ruptures. A fundamental point here is the cellular view of the continuous earth. We suggest the cell size varies regionally with the maturity of the faults of the region. Seismic gaps (e.g. Mogi, 1979) and changes in seismicity such as indicated by b-values have been known but poorly understood. There have been reports of magnitude dependent seismic quiescence before large event at plate boundaries and intraplate (Smith et al., 2013). Recently, decreases in b-value for large earthquakes have been reported (Nanjo et al., 2012) as anticipated from lab experiments (Mogi, 1963). Our model reproduces the b-value decrease towards eventual large earthquake (increasing tectonic stress and its heterogeneous distribution). We succeeded in reproducing the cut-off of larger events above some threshold magnitude (M3-4) by slightly increasing the Coulomb failure level for only 2 % or more of the highly stressed cells. This is equivalent to reducing the pore pressure in these distributed cells. We are working on the model to introduce the recovery of pore pressure incorporating the observed orders of magnitude higher permeability fault zones than the surrounding rock (Lockner, 2009) allowing for a large earthquake to be generated. Our interpretation requires interactions of pores and fluids. We suggest heterogeneously distributed patches hardened
Protoplaneary Dynamics Uncovered through Synthetic Spectral Modeling
NASA Astrophysics Data System (ADS)
Kronberg, Martin
2010-01-01
One of the key problems in planetary formation research is to determine the properties and dynamics of protoplaneary accretion disks where all planetary formation occurs. An increasingly useful probe into these systems is near infrared spectroscopy of ro-vibrational CO emission. The goal of the study is to develop techniques that utilize synthetic spectra generated via a modeling algorithm fitted to actual spectral data gathered from protoplanetary systems to determine specific properties of the system. We currently have a working algorithm which generates synthetic spectra based upon a number of degenerate parameters. In order to generate the best fit given the degenerate nature of the parameters we are developing a Monte Carlo algorithm that will determine local as well as absolute minima in a ten dimensional surface plot. Once this is completed we will utilize two CONDOR clusters to generate fits for hundreds of known protoplanetary systems.The result will be the largest, most descriptive database of protoplanetary systems, an essential tool for planetary and stellar researchers. This project was funded by a partnership between the National Science Foundation (NSF AST-0552798), Research Experiences for Undergraduates (REU), and the Department of Defense (DoD) ASSURE (Awards to Stimulate and Support Undergraduate Research Experiences) programs.
Nonlinear dynamics of avian influenza epidemic models.
Liu, Sanhong; Ruan, Shigui; Zhang, Xinan
2017-01-01
Avian influenza is a zoonotic disease caused by the transmission of the avian influenza A virus, such as H5N1 and H7N9, from birds to humans. The avian influenza A H5N1 virus has caused more than 500 human infections worldwide with nearly a 60% death rate since it was first reported in Hong Kong in 1997. The four outbreaks of the avian influenza A H7N9 in China from March 2013 to June 2016 have resulted in 580 human cases including 202 deaths with a death rate of nearly 35%. In this paper, we construct two avian influenza bird-to-human transmission models with different growth laws of the avian population, one with logistic growth and the other with Allee effect, and analyze their dynamical behavior. We obtain a threshold value for the prevalence of avian influenza and investigate the local or global asymptotical stability of each equilibrium of these systems by using linear analysis technique or combining Liapunov function method and LaSalle's invariance principle, respectively. Moreover, we give necessary and sufficient conditions for the occurrence of periodic solutions in the avian influenza system with Allee effect of the avian population. Numerical simulations are also presented to illustrate the theoretical results.
Dynamical Properties of Polymers: Computational Modeling
CURRO, JOHN G.; ROTTACH, DANA; MCCOY, JOHN D.
2001-01-01
The free volume distribution has been a qualitatively useful concept by which dynamical properties of polymers, such as the penetrant diffusion constant, viscosity, and glass transition temperature, could be correlated with static properties. In an effort to put this on a more quantitative footing, we define the free volume distribution as the probability of finding a spherical cavity of radius R in a polymer liquid. This is identical to the insertion probability in scaled particle theory, and is related to the chemical potential of hard spheres of radius R in a polymer in the Henry's law limit. We used the Polymer Reference Interaction Site Model (PRISM) theory to compute the free volume distribution of semiflexible polymer melts as a function of chain stiffness. Good agreement was found with the corresponding free volume distributions obtained from MD simulations. Surprisingly, the free volume distribution was insensitive to the chain stiffness, even though the single chain structure and the intermolecular pair correlation functions showed a strong dependence on chain stiffness. We also calculated the free volume distributions of polyisobutylene (PIB) and polyethylene (PE) at 298K and at elevated temperatures from PRISM theory. We found that PIB has more of its free volume distributed in smaller size cavities than for PE at the same temperature.
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
Dynamical coarse grained models with realistic time dependence
NASA Astrophysics Data System (ADS)
Andersen, Hans
2015-03-01
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. 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 an 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 was studied by Zwanzig [R. Zwanzig, J. Stat. Phys. 9, 215 (1973)]. The dynamic models generate a non-Markovian dynamics for the CG degrees of freedom, but they can be easily simulated using standard molecular dynamics simulation programs. We present tests of this method on a series of simple examples that demonstrate that the method provides realistic dynamical CG models that have non-Markovian or close to Markovian behavior that is consistent with the actual dynamical behavior of the all-atom system used to construct the CG model. The dynamic CG models have computational requirements that are similar to
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.
An integrated dynamic model of a flexible wind turbine
NASA Astrophysics Data System (ADS)
Bongers, Peter M. M.; Bierbooms, Wim A. A.; Dijkstra, Sjoerd; Vanholten, Theo
1990-06-01
A model to study the dynamic behavior of flexible wind turbines was developed. The different subsystems of the wind turbine are individually modeled with about the same degree of accuracy. The aerodynamic part describes wind shear, gravity effects, unsteady effects, and dynamic inflow. The rotor blades are provided with degrees of freedom in lag and flap directions. The tower construction is modeled including the first bending mode. The first torsional mode of the transmission is included in the model. The model of synchronous generator with dc link consists of a nonlinear fourth order model, including saturation effects. The different models of the subsystems are coupled into one integrated dynamic model which is implemented as simulation code in the DUWECS (Delf University Wind Energy Converter Simulation Package) program. The DUWECS program is developed in such a manner that it is an easy to handle tool for the study of the dynamic features of wind turbine systems.
Dynamical Widom-Rowlinson Model and Its Mesoscopic Limit
NASA Astrophysics Data System (ADS)
Finkelshtein, Dmitri; Kondratiev, Yuri; Kutoviy, Oleksandr; Oliveira, Maria João
2015-01-01
We consider the non-equilibrium dynamics for the Widom-Rowlinson model (without hard-core) in the continuum. The Lebowitz-Penrose-type scaling of the dynamics is studied and the system of the corresponding kinetic equations is derived. In the space-homogeneous case, the equilibrium points of this system are described. Their structure corresponds to the dynamical phase transition in the model. The bifurcation of the system is shown.
Modeling Nanocomposites for Molecular Dynamics (MD) Simulations
2015-01-01
Maximum 200 Words) The minimum energy configuration for Molecular Dynamics (MD) simulations is found for a carbon nanotube (CNT)/polymer...Carbon Nanotubes (CNTs), Molecular Dynamics Simulations 15. NUMBER OF PAGES 18 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...fiber composites have shown success in improving mechanical properties. Carbon nanotube (CNT)-based nanocomposites have been studied for
Branching dynamics of viral information spreading
NASA Astrophysics Data System (ADS)
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.
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.
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…
A Dynamic Systems Model of Cognitive and Language Growth.
ERIC Educational Resources Information Center
van Geert, Paul
1991-01-01
A conceptual framework of cognitive growth is sketched and a mathematical model of cognitive growth is presented with the conclusion that the most plausible model is a model of logistic growth with delayed feedback. The model is transformed into a dynamic systems model based on the logistic-growth equation. (SLD)
Chowell, G; Shim, E; Brauer, F; Diaz-Dueñas, P; Hyman, J M; Castillo-Chavez, C
2006-06-15
We model an outbreak of acute haemorrhagic conjunctivitis (AHC) using a simple epidemic model that includes susceptible, infectious, reported, and recovered classes. The model's framework considers the impact of underreporting and behaviour changes on the transmission rate and is applied to a recent epidemic of AHC in Mexico, using a fit to the cumulative number of cases to estimate model parameters, which agree with those derived from clinical studies. The model predicts a 'mean time from symptomatic onset to diagnosis' of 1.43 days (95 per cent CI: 1-2.5) and that the final size of the Mexican epidemic was underreported by 39 per cent. We estimate that a primary infectious case generates approximately 3 secondary cases (R0* = 2.64, SD 0.65). We explore the impact of interventions on the final epidemic size, and estimate a 36 per cent reduction in the transmission rate due to behaviour changes. The effectiveness of the behaviour changes in slowing the epidemic is evident at 21.90 (SD 0.19) days after the first reported case. Results therefore support current public health policy including expeditious announcement of the outbreak and public health information press releases that instruct individuals on avoiding contagion and encourage them to seek diagnosis in hospital clinics.
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.
Heuristic Strategies for Persuader Selection in Contagions on Complex Networks
Wang, Peng; Zhang, Li-Jie; Xiao, Gaoxi
2017-01-01
Individual decision to accept a new idea or product is often driven by both self-adoption and others’ persuasion, which has been simulated using a double threshold model [Huang et al., Scientific Reports 6, 23766 (2016)]. We extend the study to consider the case with limited persuasion. That is, a set of individuals is chosen from the population to be equipped with persuasion capabilities, who may succeed in persuading their friends to take the new entity when certain conditions are satisfied. Network node centrality is adopted to characterize each node’s influence, based on which three heuristic strategies are applied to pick out persuaders. We compare these strategies for persuader selection on both homogeneous and heterogeneous networks. Two regimes of the underline networks are identified in which the system exhibits distinct behaviors: when networks are sufficiently sparse, selecting persuader nodes in descending order of node centrality achieves the best performance; when networks are sufficiently dense, however, selecting nodes with medium centralities to serve as the persuaders performs the best. Under respective optimal strategies for different types of networks, we further probe which centrality measure is most suitable for persuader selection. It turns out that for the first regime, degree centrality offers the best measure for picking out persuaders from homogeneous networks; while in heterogeneous networks, betweenness centrality takes its place. In the second regime, there is no significant difference caused by centrality measures in persuader selection for homogeneous network; while for heterogeneous networks, closeness centrality offers the best measure. PMID:28072847
Heuristic Strategies for Persuader Selection in Contagions on Complex Networks.
Wang, Peng; Zhang, Li-Jie; Xu, Xin-Jian; Xiao, Gaoxi
2017-01-01
Individual decision to accept a new idea or product is often driven by both self-adoption and others' persuasion, which has been simulated using a double threshold model [Huang et al., Scientific Reports 6, 23766 (2016)]. We extend the study to consider the case with limited persuasion. That is, a set of individuals is chosen from the population to be equipped with persuasion capabilities, who may succeed in persuading their friends to take the new entity when certain conditions are satisfied. Network node centrality is adopted to characterize each node's influence, based on which three heuristic strategies are applied to pick out persuaders. We compare these strategies for persuader selection on both homogeneous and heterogeneous networks. Two regimes of the underline networks are identified in which the system exhibits distinct behaviors: when networks are sufficiently sparse, selecting persuader nodes in descending order of node centrality achieves the best performance; when networks are sufficiently dense, however, selecting nodes with medium centralities to serve as the persuaders performs the best. Under respective optimal strategies for different types of networks, we further probe which centrality measure is most suitable for persuader selection. It turns out that for the first regime, degree centrality offers the best measure for picking out persuaders from homogeneous networks; while in heterogeneous networks, betweenness centrality takes its place. In the second regime, there is no significant difference caused by centrality measures in persuader selection for homogeneous network; while for heterogeneous networks, closeness centrality offers the best measure.
Dikou, Angela; Papapanagiotou, Evangelos; Troumbis, Andreas
2011-09-01
We used remote sensing and GIS in conjunction with multivariate statistical methods to: (i) quantify landscape composition (land cover types) and configuration (patch density, diversity, fractal dimension, contagion) for five coastal watersheds of Kalloni gulf, Lesvos Island, Greece, in 1945, 1960, 1971, 1990 and 2002/2003, (ii) evaluate the relative importance of physical (slope, geologic substrate, stream order) and human (road network, population density) variables on landscape composition and configuration, and (iii) characterize processes that led to land cover changes through land cover transitions between these five successive periods in time. Distributions of land cover types did not differ among the five time periods at the five watersheds studied because the largest cumulative changes between 1945 and 2002/2003 did not take place at dominant land cover types. Landscape composition related primarily to the physical attributes of the landscape. Nevertheless, increase in population density and the road network were found to increase heterogeneity of the landscape mosaic (patchiness), complexity of patch shape (fractal dimension), and patch disaggregation (contagion). Increase in road network was also found to increase landscape diversity due to the creation of new patches. The main processes involved in land cover changes were plough-land abandonment and ecological succession. Landscape dynamics during the last 50 years corroborate the ecotouristic-agrotouristic model for regional development to reverse trends in agricultural land abandonment and human population decline and when combined with hypothetical regulatory approaches could predict how this landscape could develop in the future, thus, providing a valuable tool to regional planning.
Multibody dynamics model building using graphical interfaces
NASA Technical Reports Server (NTRS)
Macala, Glenn A.
1989-01-01
In recent years, the extremely laborious task of manually deriving equations of motion for the simulation of multibody spacecraft dynamics has largely been eliminated. Instead, the dynamicist now works with commonly available general purpose dynamics simulation programs which generate the equations of motion either explicitly or implicitly via computer codes. The user interface to these programs has predominantly been via input data files, each with its own required format and peculiarities, causing errors and frustrations during program setup. Recent progress in a more natural method of data input for dynamics programs: the graphical interface, is described.
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
Modeling Dynamic Fracture of Cryogenic Pellets
Parks, Paul
2016-06-30
This work is part of an investigation with the long-range objective of predicting the size distribution function and velocity dispersion of shattered pellet fragments after a large cryogenic pellet impacts a solid surface at high velocity. The study is vitally important for the shattered pellet injection (SPI) technique, one of the leading technologies being implemented at ORNL for the mitigation of disruption damage on current tokamaks and ITER. The report contains three parts that are somewhat interwoven. In Part I we formulated a self-similar model for the expansion dynamics and velocity dispersion of the debris cloud following pellet impact against a thick (rigid) target plate. Also presented in Part I is an analytical fracture model that predicts the nominal or mean size of the fragments in the debris cloud and agrees well with known SPI data. The aim of Part II is to gain an understanding of the pellet fracturing process when a pellet is shattered inside a miter tube with a sharp bend. Because miter tubes have a thin stainless steel (SS) wall a permanent deformation (dishing) of the wall is produced at the site of the impact. A review of the literature indicates that most projectile impact on thin plates are those for which the target is deformed and the projectile is perfectly rigid. Such impacts result in “projectile embedding” where the projectile speed is reduced to zero during the interaction so that all the kinetic energy (KE) of the projectile goes into the energy stored in plastic deformation. Much of the literature deals with perforation of the target. The problem here is quite different; the softer pellet easily undergoes complete material failure causing only a small transfer of KE to stored energy of wall deformation. For the real miter tube, we derived a strain energy function for the wall deflection using a non-linear (plastic) stress-strain relation for 304 SS. Using a dishing profile identical to the linear Kirchkoff-Love profile (for lack
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.
Affecting others: social appraisal and emotion contagion in everyday decision making.
Parkinson, Brian; Simons, Gwenda
2009-08-01
In a diary study of interpersonal affect transfer, 41 participants reported on decisions involving other people over 3 weeks. Reported anxiety and excitement were reliably related to the perceived anxiety and excitement of another person who was present during decision making. Risk and importance appraisals partially mediated effects of other's anxiety on own anxiety as predicted by social appraisal theory. However, other's emotion remained a significant independent predictor of own emotion after controlling for appraisals, supporting the additional impact of more direct forms of affect transfer such as emotion contagion. Significant affect-transfer effects remained even after controlling for participants' perceptions of the other's emotion in addition to all measured appraisals, confirming that affect transfer does not require explicit registration of someone else's feelings. This research provides some of the clearest evidence for the operation of both social appraisal and automatic affect transfer in everyday social life.
Age and ethnic differences in cold weather and contagion theories of colds and flu.
Sigelman, Carol K
2012-02-01
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 other people causes disease were more causally sophisticated than explanations of how cold weather causes it. Finally, Mexican American and other minority children were more likely than European American children to subscribe to cold weather theories, a difference partially but not wholly attributable to ethnic group differences in parent education. Findings support the value of an intuitive or naïve theories perspective in understanding developmental and sociocultural differences in concepts of disease and in planning health education to help both children and their parents shed misconceptions so that they can focus on effective preventive actions.
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…
Model based control of dynamic atomic force microscope
NASA Astrophysics Data System (ADS)
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.
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.
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.
Size and complexity in model financial systems.
Arinaminpathy, Nimalan; Kapadia, Sujit; May, Robert M
2012-11-06
The global financial crisis has precipitated an increasing appreciation of the need for a systemic perspective toward financial stability. For example: What role do large banks play in systemic risk? How should capital adequacy standards recognize this role? How is stability shaped by concentration and diversification in the financial system? We explore these questions using a deliberately simplified, dynamic model of a banking system that combines three different channels for direct transmission of contagion from one bank to another: liquidity hoarding, asset price contagion, and the propagation of defaults via counterparty credit risk. Importantly, we also introduce a mechanism for capturing how swings in "confidence" in the system may contribute to instability. Our results highlight that the importance of relatively large, well-connected banks in system stability scales more than proportionately with their size: the impact of their collapse arises not only from their connectivity, but also from their effect on confidence in the system. Imposing tougher capital requirements on larger banks than smaller ones can thus enhance the resilience of the system. Moreover, these effects are more pronounced in more concentrated systems, and continue to apply, even when allowing for potential diversification benefits that may be realized by larger banks. We discuss some tentative implications for policy, as well as conceptual analogies in ecosystem stability and in the control of infectious diseases.
Size and complexity in model financial systems
Arinaminpathy, Nimalan; Kapadia, Sujit; May, Robert M.
2012-01-01
The global financial crisis has precipitated an increasing appreciation of the need for a systemic perspective toward financial stability. For example: What role do large banks play in systemic risk? How should capital adequacy standards recognize this role? How is stability shaped by concentration and diversification in the financial system? We explore these questions using a deliberately simplified, dynamic model of a banking system that combines three different channels for direct transmission of contagion from one bank to another: liquidity hoarding, asset price contagion, and the propagation of defaults via counterparty credit risk. Importantly, we also introduce a mechanism for capturing how swings in “confidence” in the system may contribute to instability. Our results highlight that the importance of relatively large, well-connected banks in system stability scales more than proportionately with their size: the impact of their collapse arises not only from their connectivity, but also from their effect on confidence in the system. Imposing tougher capital requirements on larger banks than smaller ones can thus enhance the resilience of the system. Moreover, these effects are more pronounced in more concentrated systems, and continue to apply, even when allowing for potential diversification benefits that may be realized by larger banks. We discuss some tentative implications for policy, as well as conceptual analogies in ecosystem stability and in the control of infectious diseases. PMID:23091020
NASA Astrophysics Data System (ADS)
González, Ramón E. R.; de Figueirêdo, Pedro Hugo; Coutinho, Sérgio
2013-10-01
We study a cellular automata model to test the timing of antiretroviral therapy strategies for the dynamics of infection with human immunodeficiency virus (HIV). We focus on the role of virus diffusion when its population is included in previous cellular automata model that describes the dynamics of the lymphocytes cells population during infection. This inclusion allows us to consider the spread of infection by the virus-cell interaction, beyond that which occurs by cell-cell contagion. The results show an acceleration of the infectious process in the absence of treatment, but show better efficiency in reducing the risk of the onset of AIDS when combined antiretroviral therapies are used even with drugs of low effectiveness. Comparison of results with clinical data supports the conclusions of this study.
Rosenthal, Sara Brin; Twomey, Colin R.; Hartnett, Andrew T.; Wu, Hai Shan; Couzin, Iain D.
2015-01-01
Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion. PMID:25825752
Rosenthal, Sara Brin; Twomey, Colin R; Hartnett, Andrew T; Wu, Hai Shan; Couzin, Iain D
2015-04-14
Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion.
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.
Failure dynamics of the global risk network.
Szymanski, Boleslaw K; Lin, Xin; Asztalos, Andrea; Sreenivasan, Sameet
2015-06-18
Risks threatening modern societies form an intricately interconnected network that often underlies crisis situations. Yet, little is known about how risk materializations in distinct domains influence each other. Here we present an approach in which expert assessments of likelihoods and influence of risks underlie a quantitative model of the global risk network dynamics. The modeled risks range from environmental to economic and technological, and include difficult to quantify risks, such as geo-political and social. Using the maximum likelihood estimation, we find the optimal model parameters and demonstrate that the model including network effects significantly outperforms the others, uncovering full value of the expert collected data. We analyze the model dynamics and study its resilience and stability. Our findings include such risk properties as contagion potential, persistence, roles in cascades of failures and the identity of risks most detrimental to system stability. The model provides quantitative means for measuring the adverse effects of risk interdependencies and the materialization of risks in the network.
Failure dynamics of the global risk network
NASA Astrophysics Data System (ADS)
Szymanski, Boleslaw K.; Lin, Xin; Asztalos, Andrea; Sreenivasan, Sameet
2015-06-01
Risks threatening modern societies form an intricately interconnected network that often underlies crisis situations. Yet, little is known about how risk materializations in distinct domains influence each other. Here we present an approach in which expert assessments of likelihoods and influence of risks underlie a quantitative model of the global risk network dynamics. The modeled risks range from environmental to economic and technological, and include difficult to quantify risks, such as geo-political and social. Using the maximum likelihood estimation, we find the optimal model parameters and demonstrate that the model including network effects significantly outperforms the others, uncovering full value of the expert collected data. We analyze the model dynamics and study its resilience and stability. Our findings include such risk properties as contagion potential, persistence, roles in cascades of failures and the identity of risks most detrimental to system stability. The model provides quantitative means for measuring the adverse effects of risk interdependencies and the materialization of risks in the network.
Failure dynamics of the global risk network
Szymanski, Boleslaw K.; Lin, Xin; Asztalos, Andrea; Sreenivasan, Sameet
2015-01-01
Risks threatening modern societies form an intricately interconnected network that often underlies crisis situations. Yet, little is known about how risk materializations in distinct domains influence each other. Here we present an approach in which expert assessments of likelihoods and influence of risks underlie a quantitative model of the global risk network dynamics. The modeled risks range from environmental to economic and technological, and include difficult to quantify risks, such as geo-political and social. Using the maximum likelihood estimation, we find the optimal model parameters and demonstrate that the model including network effects significantly outperforms the others, uncovering full value of the expert collected data. We analyze the model dynamics and study its resilience and stability. Our findings include such risk properties as contagion potential, persistence, roles in cascades of failures and the identity of risks most detrimental to system stability. The model provides quantitative means for measuring the adverse effects of risk interdependencies and the materialization of risks in the network. PMID:26087020
Exploiting Non-sequence Data in Dynamic Model Learning
2013-10-01
dynamic process of interest. For example, the Sloan Digital Sky Survey (SDSS)1 has collected images of millions of celestial objects, each of which may...function of Z and hence Z. Since we assume the true dynamics to be smooth, a natural way to reconstruct a temporal ordering would be to solve the...program (3.42) better captures the dynamic nature of the data. • The initial models learnt from ordered cluster centers already perform quite well
Stochastic models of cover class dynamics. [remote sensing of vegetation
NASA Technical Reports Server (NTRS)
Barringer, T. H.; Robinson, V. B.
1981-01-01
Investigations related to satellite remote sensing of vegetation have been concerned with questions of signature identification and extension, cover inventory accuracy, and change detection and monitoring. Attention is given to models of ecological succession, present directions in successional modeling and analysis, nondynamic spatial models, issues in the analysis of spatial data, and aspects of spatial modeling. Issues in time-series analysis are considered along with dynamic spatial models, and problems of model specification and identification.
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.
Mathematical modeling of microtubule dynamics: insights into physiology and disease.
Buxton, Gavin A; Siedlak, Sandra L; Perry, George; Smith, Mark A
2010-12-01
Computer models of microtubule dynamics have provided the basis for many of the theories on the cellular mechanics of the microtubules, their polymerization kinetics, and the diffusion of tubulin and tau. In the three-dimensional model presented here, we include the effects of tau concentration and the hydrolysis of GTP-tubulin to GDP-tubulin and observe the emergence of microtubule dynamic instability. This integrated approach simulates the essential physics of microtubule dynamics in a cellular environment. The model captures the structure of the microtubules as they undergo steady state dynamic instabilities in this simplified geometry, and also yields the average number, length, and cap size of the microtubules. The model achieves realistic geometries and simulates cellular structures found in degenerating neurons in disease states such as Alzheimer disease. Further, this model can be used to simulate microtubule changes following the addition of antimitotic drugs which have recently attracted attention as chemotherapeutic agents.
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.
NASA Technical Reports Server (NTRS)
Tan, C. M.; Carr, L. W.
1996-01-01
A variety of empirical and computational fluid dynamics two-dimensional (2-D) dynamic stall models were compared to recently obtained three-dimensional (3-D) dynamic stall data in a workshop on modeling of 3-D dynamic stall of an unswept, rectangular wing, of aspect ratio 10. Dynamic stall test data both below and above the static stall angle-of-attack were supplied to the participants, along with a 'blind' case where only the test conditions were supplied in advance, with results being compared to experimental data at the workshop itself. Detailed graphical comparisons are presented in the report, which also includes discussion of the methods and the results. The primary conclusion of the workshop was that the 3-D effects of dynamic stall on the oscillating wing studied in the workshop can be reasonably reproduced by existing semi-empirical models once 2-D dynamic stall data have been obtained. The participants also emphasized the need for improved quantification of 2-D dynamic stall.
Dynamic Evolution Model Based on Social Network Services
NASA Astrophysics Data System (ADS)
Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen
2013-11-01
Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.
Dynamic wake distortion model for helicopter maneuvering flight
NASA Astrophysics Data System (ADS)
Zhao, Jinggen
A new rotor dynamic wake distortion model, which can be used to account for the rotor transient wake distortion effect on inflow across the rotor disk during helicopter maneuvering and transitional flight in both hover and forward flight conditions, is developed. The dynamic growths of the induced inflow perturbation across rotor disk during different transient maneuvers, such as a step pitch or roll rate, a step climb rate and a step change of advance ratio are investigated by using a dynamic vortex tube analysis. Based on the vortex tube results, a rotor dynamic wake distortion model, which is expressed in terms of a set of ordinary differential equations, with rotor longitudinal and lateral wake curvatures, wake skew and wake spacing as states, is developed. Also, both the Pitt-Peters dynamic inflow model and the Peters-He finite state inflow model for axial or forward flight are augmented to account for rotor dynamic wake distortion effect during helicopter maneuvering flight. To model the aerodynamic interaction among main rotor, tail rotor and empennage caused by rotor wake curvature effect during helicopter maneuvering flight, a reduced order model based on a vortex tube analysis is developed. Both the augmented Pitt-Peters dynamic inflow model and the augmented Peters-He finite state inflow model, combined with the developed dynamic wake distortion model, together with the interaction model are implemented in a generic helicopter simulation program of UH-60 Black Hawk helicopter and the simulated vehicle control responses in both time domain and frequency domain are compared with flight test data of a UH-60 Black Hawk helicopter in both hover and low speed forward flight conditions.
Exploring the Components of Dynamic Modeling Techniques
ERIC Educational Resources Information Center
Turnitsa, Charles Daniel
2012-01-01
Upon defining the terms modeling and simulation, it becomes apparent that there is a wide variety of different models, using different techniques, appropriate for different levels of representation for any one system to be modeled. Selecting an appropriate conceptual modeling technique from those available is an open question for the practitioner.…
Modelling emergent patterns of dynamic desert ecosystems
Technology Transfer Automated Retrieval System (TEKTRAN)
In many desert ecosystems vegetation is both patchy and dynamic: vegetated areas are interspersed with patches of bare ground, and both the positioning and the species composition of the vegetated areas exhibit change through time. These characteristics lead to the emergence of multi-scale patterns ...
Modeling Academic Education Processes by Dynamic Storyboarding
ERIC Educational Resources Information Center
Sakurai, Yoshitaka; Dohi, Shinichi; Tsuruta, Setsuo; Knauf, Rainer
2009-01-01
In high-level education such as university studies, there is a flexible but complicated system of subject offerings and registration rules such as prerequisite subjects. Those offerings, connected with registration rules, should be matched to the students' learning needs and desires, which change dynamically. Students need assistance in such a…
Biomolecular Modeling in a Process Dynamics and Control Course
ERIC Educational Resources Information Center
Gray, Jeffrey J.
2006-01-01
I present modifications to the traditional course entitled, "Process dynamics and control," which I renamed "Modeling, dynamics, and control of chemical and biological processes." Additions include the central dogma of biology, pharmacokinetic systems, population balances, control of gene transcription, and large-scale…
Modelling the Structure and Dynamics of Biological Pathways
O’Hara, Laura; Livigni, Alessandra; Chen, Sz-Hau; Raza, Sobia; Digard, Paul; Smith, Lee B.; Freeman, Tom C.
2016-01-01
There is a need for formalised diagrams that both summarise current biological pathway knowledge and support modelling approaches that explain and predict their behaviour. Here, we present a new, freely available modelling framework that includes a biologist-friendly pathway modelling language (mEPN), a simple but sophisticated method to support model parameterisation using available biological information; a stochastic flow algorithm that simulates the dynamics of pathway activity; and a 3-D visualisation engine that aids understanding of the complexities of a system’s dynamics. We present example pathway models that illustrate of the power of approach to depict a diverse range of systems. PMID:27509052
A 4096 atom model of amorphous silicon: Structure and dynamics
NASA Astrophysics Data System (ADS)
Feldman, Joseph L.; Bickham, Scott R.; Davidson, Brian N.; Wooten, Frederick
1997-03-01
We present structural and lattice dynamical information for a 4096 atom model of amorphous silicon. The structural model was obtained, similarly to previously published smaller models, using periodic boundary conditions, the Wooten-Winer-Weaire bond-switching algorithm, and the Broughton-Li relaxation with respect to the Stillinger-Weber potential. The structure is dynamically stable and there is no evidence in the radial distribution function of medium range order. For examining this large model, we use a 1000 processor Connection Machine to compute all the eigenvalues and eigenvectors exactly. The phonon density of states and inverse participation ratio are compared with results for related 216, 432 and 1000-atom models.
Dynamic heat capacity of the east model and of a bead-spring polymer model.
McCoy, John Dwane; Brown, Jonathan R.; Adolf, Douglas Brian
2011-10-01
In this report we have presented a brief review of the glass transition and one means of characterizing glassy materials: linear and nonlinear thermodynamic oscillatory experiments to extract the dynamic heat capacity. We have applied these methods to the east model (a variation of the Ising model for glass forming systems) and a simple polymeric system via molecular dynamics simulation, and our results match what is seen in experiment. For the east model, since the dynamics are so simple, a mathematical model is developed that matches the simulated dynamics. For the polymeric system, since the system is a simulation, we can instantaneously 'quench' the system - removing all vibrational energy - to separate the vibrational dynamics from dynamics associated with particle rearrangements. This shows that the long-time glassy dynamics are due entirely to the particle rearrangements, i.e. basin jumping on the potential energy landscape. Finally, we present an extension of linear dynamic heat capacity to the nonlinear regime.
Physiology-based gap model of forest dynamics
Friend, A.D.; Schugart, H.H.; Running, S.W.
1993-01-01
A computer model of forest growth and ecosystem processes is presented. The model, HYBRID, is derived from a forest gap model, an ecosystem process model, and a photosynthesis model. In HYBRID individual trees fix and respire carbon, and lose water daily; carbon partitioning occurs at the end of each year. HYBRID obviates many of the limitations of both gap models and ecosystem process models. The growth equations of gap models are replaced with functionally realistic equations and processes for carbon fixation and partitioning, resulting in a dynamic model in which competition and physiology play important roles.
Equilibrium and Disequilibrium Dynamics in Cobweb Models with Time Delays
NASA Astrophysics Data System (ADS)
Gori, Luca; Guerrini, Luca; Sodini, Mauro
2015-06-01
This paper aims to study price dynamics in two different continuous time cobweb models with delays close to [Hommes, 1994]. In both cases, the stationary equilibrium may be not representative of the long-term dynamics of the model, since it is possible to observe endogenous and persistent fluctuations (supercritical Hopf bifurcations) even if a deterministic context without external shocks is considered. In the model in which markets are in equilibrium every time, we show that the existence of time delays in the expectations formation mechanism may cause chaotic dynamics similar to those obtained in [Hommes, 1994] in a discrete time context. From a mathematical point of view, we apply the Poincaré-Lindstedt perturbation method to study the local dynamic properties of the models. In addition, several numerical experiments are used to investigate global properties of the systems.