scholarly journals A dynamic power-law sexual network model of gonorrhoea outbreaks

2018 ◽  
Author(s):  
Lilith K Whittles ◽  
Peter J White ◽  
Xavier Didelot
Keyword(s):  
Network Model ◽  
Power Law ◽  
Dynamic Network ◽  
Great Promise ◽  
Model Parameters ◽  
Power Law Distribution ◽  
Time Model ◽  
Dynamic Network Model ◽  
The Impact ◽  
Over Time

AbstractHuman networks of sexual contacts are dynamic by nature, with partnerships forming and breaking continuously over time. Sexual behaviours are also highly heterogeneous, so that the number of partners reported by individuals over a given period of time is typically distributed as a power-law. Both the dynamism and heterogeneity of sexual partnerships are likely to have an effect in the patterns of spread of sexually transmitted diseases. To represent these two fundamental properties of sexual networks, we developed a stochastic process of dynamic partnership formation and dissolution, which results in power-law numbers of partners over time. Model parameters can be set to produce realistic conditions in terms of the exponent of the power-law distribution, of the number of individuals without relationships and of the average duration of relationships. Using an outbreak of antibiotic resistant gonorrhoea amongst men have sex with men as a case study, we show that our realistic dynamic network exhibits different properties compared to the frequently used static networks or homogeneous mixing models. We also consider an approximation to our dynamic network model in terms of a much simpler branching process. We estimate the parameters of the generation time distribution and offspring distribution which can be used for example in the context of outbreak reconstruction based on genomic data. Finally, we investigate the impact of a range of interventions against gonorrhoea, including increased condom use, more frequent screening and immunisation, concluding that the latter shows great promise to reduce the burden of gonorrhoea, even if the vaccine was only partially effective or applied to only a random subset of the population.

scholarly journals A dynamic network model for the action of low salinity on two-phase flow

2020 ◽  
Vol 137 ◽  
pp. 103520
Author(s):  
Z.M. Wilmott ◽  
C.J.W. Breward ◽  
S.J. Chapman
Keyword(s):  
Network Model ◽  
Two Phase Flow ◽  
Dynamic Network ◽  
Phase Flow ◽  
Two Phase ◽  
Low Salinity ◽  
Dynamic Network Model

The dynamic nature of depression: a new micro-level perspective of mental disorder that meets current challenges

2013 ◽  
Vol 44 (7) ◽  
pp. 1349-1360 ◽  
Author(s):  
M. Wichers
Keyword(s):  
Dynamic Network ◽  
Building Blocks ◽  
Major Depressive ◽  
Dynamic Network Model ◽  
Healthy State ◽  
Behavioural Patterns ◽  
Micro Level ◽  
Continuous Dynamic ◽  
Dynamic Interplay ◽  
Over Time

The examination of moment-to-moment, ‘micro-level’ patterns of experience and behaviour using experience sampling methodology has contributed to our understanding of the ‘macro-level’ development of full-blown symptoms and disorders. This paper argues that the micro-level perspective can be used to identify the smallest building blocks underlying the onset and course of mental ill-health. Psychopathology may be the result of the continuous dynamic interplay between micro-level moment-to-moment experiences and behavioural patterns over time. Reinforcing loops between momentary states may alter the course of mental health towards either a more or less healthy state. An example with observed data, from a population of individuals with depressive symptoms, supports the validity of a dynamic network model of psychopathology and shows that together and over time, this continuous interplay between momentary states may result in the cluster of symptoms we call major depressive disorder. This approach may help conceptualize the nature of mental disorders, and generate individualized insights useful for diagnosis and treatment in psychiatry.

Network model of deviation from power-law distribution in complex network

2010 ◽  
Vol 79 (1) ◽  
pp. 29-33 ◽  
Author(s):  
J. Jiang ◽  
R. Wang ◽  
Q. A. Wang
Keyword(s):  
Complex Network ◽  
Network Model ◽  
Power Law ◽  
Power Law Distribution

Dynamic Network Model Analysis Based on Communication Network

2014 ◽  
Vol 989-994 ◽  
pp. 2639-2642
Author(s):  
Nan Qi Yuan ◽  
Tian Jiang ◽  
Shi Bai ◽  
Hao Sun ◽  
Jing Mei Zhao
Keyword(s):  
Communication Network ◽  
Convergence Rate ◽  
Network Model ◽  
Dynamic Network ◽  
Model Analysis ◽  
Vicsek Model ◽  
Dynamic Network Model ◽  
Weighted Model

In order to research dynamic network astringency reaching uniformity, this paper perfects the Vicsek model and puts forward improving dynamic network astringency efficiency by weighted model. We prove that the convergence rate of weighted model is faster than the classic Vicsek model and it can optimize dynamic network.

Deterring the development and use of nuclear weapons: a multi-level modeling approach

2017 ◽  
Vol 15 (4) ◽  
pp. 483-493
Author(s):  
Kathleen M Carley ◽  
Geoffrey P Morgan ◽  
Michael J Lanham
Keyword(s):  
Nuclear Weapons ◽  
Dynamic Network ◽  
Pacific Rim ◽  
Country Level ◽  
Dynamic Network Model ◽  
The Pacific ◽  
Stakeholder Model ◽  
Using Data ◽  
Multi Stakeholder ◽  
The Impact

We describe a multi-country, multi-stakeholder model for the accrual and use of nuclear weapons and illustrate the model’s value for addressing nuclear weapon proliferation issues using a historic Pacific Rim scenario. We instantiate the agent-based dynamic network model for information and belief diffusion using data from subject matter experts and data mined from open source news documents. We present the techniques that supported model instantiation. A key feature of this model and these techniques is enabling rapid model re-use through the ability to instantiate at two levels: generically and for specific cases. We demonstrate these generic and specific cases using a scenario regarding North Korea’s interest in nuclear weapons and the resulting impact on the Pacific Rim circa 2014, that is, prior to the fourth and fifth nuclear weapons tests by the Democratic People’s Republic of Korea. A key feature of this model is that it uses two levels of network interaction, the country level and the stakeholder level, thus supporting the inclusion of non-state actors and the assessment of complex scenarios. Using this model, we conducted virtual experiments in which we assessed the impact of alternative courses of action on the overall force posture and desire to develop and use nuclear weapons.

scholarly journals Emerging, crystalizing, and changing psychological contracts over time: Introducing the iPC-network model

2019 ◽  
Author(s):  
Tim Vantilborgh
Keyword(s):  
Network Model ◽  
Psychological Contract ◽  
Dynamic Network ◽  
Network Models ◽  
Psychological Contracts ◽  
Exchange Relationships ◽  
Contract Breach ◽  
Alternative Approach ◽  
The Individual ◽  
Over Time

This chapter introduces the individual Psychological Contract (iPC) network model as an alternative approach to study psychological contracts. This model departs from the basic idea that a psychological contract forms a mental schema containing obligated inducements and contributions, which are exchanged for each other. This mental schema is captured by a dynamic network, in which the nodes represent the inducements and contributions and the ties represent the exchanges. Building on dynamic systems theory, I propose that these networks evolve over time towards attractor states, both at the level of the network structure and at the level of the nodes (i.e., breach and fulfilment attractor states). I highlight how the iPC-network model integrates recent theoretical developments in the psychological contract literature and explain how it may advance scholars understanding of exchange relationships. In particular, I illustrate how iPC-network models allow researchers to study the actual exchanges in the psychological contract over time, while acknowledging its idiosyncratic nature. This would allow for more precise predictions of psychological contract breach and fulfilment consequences and explains how content and process of the psychological contract continuously influence each other.

scholarly journals SIS dynamic network model based on product semantics from the perspective of infectious disease dynamics

2021 ◽  
Vol 235 ◽  
pp. 03035
Author(s):  
jiaojiao Lv ◽  
yingsi Zhao
Keyword(s):  
Network Model ◽  
Purchase Intention ◽  
Recommendation System ◽  
Optimal Algorithm ◽  
Dynamic Network ◽  
Distribution Model ◽  
Recommendation Algorithm ◽  
Model Based ◽  
Dynamic Network Model ◽  
Recommendation Algorithms

Recommendation system is unable to achive the optimal algorithm, recommendation system precision problem into bottleneck. Based on the perspective of product marketing, paper takes the inherent attribute as the classification standard and focuses on the core problem of “matching of product classification and recommendation algorithm of users’ purchase demand”. Three hypotheses are proposed: (1) inherent attributes of the product directly affect user demand; (2) classified product is suitable for different recommendation algorithms; (3) recommendation algorithm integration can achieve personalized customization. Based on empirical research on the relationship between characteristics of recommendation information (independent variable) and purchase intention (dependent variable), it is concluded that predictability and difference of recommendation information are not fully perceived and stimulation is insufficient. Therefore, SIS dynamic network model based on the distribution model of SIS virus is constructed. It discusses the spreading path of recommendation information and “infection” situation of consumers to enhance accurate matching of recommendation system.

A dynamic network model for interbank market

2016 ◽  
Vol 463 ◽  
pp. 131-138 ◽  
Author(s):  
Tao Xu ◽  
Jianmin He ◽  
Shouwei Li
Keyword(s):  
Network Model ◽  
Dynamic Network ◽  
Interbank Market ◽  
Dynamic Network Model

scholarly journals Oscillating epidemics in a dynamic network model: stochastic and mean-field analysis

2015 ◽  
Vol 72 (5) ◽  
pp. 1153-1176 ◽  
Author(s):  
András Szabó-Solticzky ◽  
Luc Berthouze ◽  
Istvan Z. Kiss ◽  
Péter L. Simon
Keyword(s):  
Network Model ◽  
Mean Field ◽  
Dynamic Network ◽  
Field Analysis ◽  
Dynamic Network Model
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