scholarly journals Emergence of increased frequency and severity of multiple infections by viruses due to spatial clustering of hosts

2016 ◽  
Author(s):  
Bradford P Taylor ◽  
Catherine J Penington ◽  
Joshua S. Weitz
Keyword(s):  
Spatial Clustering ◽  
Mean Field ◽  
Multiple Infections ◽  
Mean Field Model ◽  
Virus Particles ◽  
Spatially Correlated ◽  
Multiple Virus ◽  
Key Driver ◽  
Evolutionary Consequences

AbstractMultiple virus particles can infect a target host cell. Such multiple infections (MIs) have significant and varied ecological and evolutionary consequences for both virus and host populations. Yet, the in situ rates and drivers of MIs in virusmicrobe systems remain largely unknown. Here, we develop an individual-based model (IBM) of virus-microbe dynamics to probe how spatial interactions drive the frequency and nature of MIs. In our IBMs, we identify increasingly spatially correlated clusters of viruses given sufficient decreases viral movement. We also identify increasingly spatially correlated clusters of viruses and clusters of hosts given sufficient increases in viral infectivity. The emergence of clusters is associated with an increase in multiply infected hosts as compared to expectations from an analogous mean-field model. We also observe longtails in the distribution of the multiplicity of infection (MOI) in contrast to mean-field expectations that such events are exponentially rare. We show that increases in both the frequency and severity of MIs occur when viruses invade a cluster of uninfected microbes. We contend that population-scale enhancement of MI arises from an aggregate of invasion dynamics over a distribution of microbe cluster sizes. Our work highlights the need to consider spatially explicit interactions as a potentially key driver underlying the ecology and evolution of virus-microbe communities.

scholarly journals On the Throughput Optimization in Large-Scale Batch-Processing Systems

2021 ◽  
Vol 48 (3) ◽  
pp. 128-129
Author(s):  
Sounak Kar ◽  
Robin Rehrmann ◽  
Arpan Mukhopadhyay ◽  
Bastian Alt ◽  
Florin Ciucu ◽  
...  
Keyword(s):  
Large Scale ◽  
Mean Field ◽  
Queueing Network ◽  
Processing System ◽  
Batch Size ◽  
System Throughput ◽  
Throughput Optimization ◽  
Mean Field Model ◽  
Optimal Batch Size ◽  
Globally Attractive

We analyze a data-processing system with n clients producing jobs which are processed in batches by m parallel servers; the system throughput critically depends on the batch size and a corresponding sub-additive speedup function that arises due to overhead amortization. In practice, throughput optimization relies on numerical searches for the optimal batch size which is computationally cumbersome. In this paper, we model this system in terms of a closed queueing network assuming certain forms of service speedup; a standard Markovian analysis yields the optimal throughput in w n4 time. Our main contribution is a mean-field model that has a unique, globally attractive stationary point, derivable in closed form. This point characterizes the asymptotic throughput as a function of the batch size that can be calculated in O(1) time. Numerical settings from a large commercial system reveal that this asymptotic optimum is accurate in practical finite regimes.

scholarly journals Mean-Field Models for EEG/MEG: From Oscillations to Waves

2021 ◽  
Author(s):  
Áine Byrne ◽  
James Ross ◽  
Rachel Nicks ◽  
Stephen Coombes
Keyword(s):  
Gap Junction ◽  
Large Scale ◽  
Mean Field ◽  
Coarse Grained ◽  
Neural Mass Model ◽  
Neuron Network ◽  
Mass Model ◽  
Mean Field Model ◽  
Neural Mass ◽  
The Rich

AbstractNeural mass models have been used since the 1970s to model the coarse-grained activity of large populations of neurons. They have proven especially fruitful for understanding brain rhythms. However, although motivated by neurobiological considerations they are phenomenological in nature, and cannot hope to recreate some of the rich repertoire of responses seen in real neuronal tissue. Here we consider a simple spiking neuron network model that has recently been shown to admit an exact mean-field description for both synaptic and gap-junction interactions. The mean-field model takes a similar form to a standard neural mass model, with an additional dynamical equation to describe the evolution of within-population synchrony. As well as reviewing the origins of this next generation mass model we discuss its extension to describe an idealised spatially extended planar cortex. To emphasise the usefulness of this model for EEG/MEG modelling we show how it can be used to uncover the role of local gap-junction coupling in shaping large scale synaptic waves.

scholarly journals Natural dimethyl sulfide gradients would lead marine predators to higher prey biomass

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Kylie Owen ◽  
Kentaro Saeki ◽  
Joseph D. Warren ◽  
Alessandro Bocconcelli ◽  
David N. Wiley ◽  
...  
Keyword(s):  
Laboratory Experiments ◽  
Dimethyl Sulfide ◽  
Zooplankton Biomass ◽  
Foraging Success ◽  
Spatially Correlated ◽  
Prey Biomass ◽  
Marine Predators ◽  
Predator Foraging ◽  
The Impact

AbstractFinding prey is essential to survival, with marine predators hypothesised to track chemicals such as dimethyl sulfide (DMS) while foraging. Many predators are attracted to artificially released DMS, and laboratory experiments have shown that zooplankton grazing on phytoplankton accelerates DMS release. However, whether natural DMS concentrations are useful for predators and correlated to areas of high prey biomass remains a fundamental knowledge gap. Here, we used concurrent hydroacoustic surveys and in situ DMS measurements to present evidence that zooplankton biomass is spatially correlated to natural DMS concentration in air and seawater. Using agent simulations, we also show that following gradients of DMS would lead zooplankton predators to areas of higher prey biomass than swimming randomly. Further understanding of the conditions and scales over which these gradients occur, and how they are used by predators, is essential to predicting the impact of future changes in the ocean on predator foraging success.

scholarly journals Quark mean-field model for single and double   and   hypernuclei

2014 ◽  
Vol 2014 (1) ◽  
pp. 13D02-0 ◽  
Author(s):  
J. N. Hu ◽  
A. Li ◽  
H. Shen ◽  
H. Toki
Keyword(s):  
Field Model ◽  
Mean Field ◽  
Mean Field Model

EVOLUTION OF SHELL STRUCTURE IN NUCLEI

2011 ◽  
Vol 20 (08) ◽  
pp. 1663-1675 ◽  
Author(s):  
A. BHAGWAT ◽  
Y. K. GAMBHIR
Keyword(s):  
Shell Structure ◽  
Crucial Role ◽  
Field Model ◽  
Mean Field ◽  
Mass Region ◽  
The Other ◽  
Mean Field Model ◽  
Relativistic Mean Field ◽  
Shell Closures ◽  
Low Mass

Systematic investigations of the pairing and two-neutron separation energies which play a crucial role in the evolution of shell structure in nuclei, are carried out within the framework of relativistic mean-field model. The shell closures are found to be robust, as expected, up to the lead region. New shell closures appear in low mass region. In the superheavy region, on the other hand, it is found that the shell closures are not as robust, and they depend on the particular combinations of neutron and proton numbers. Effect of deformation on the shell structure is found to be marginal.

Dynamic Mean-Field Model for the Mesoscale Morphologies of Liquid Crystalline Polymers

2001 ◽  
Vol 34 (23) ◽  
pp. 8378-8379 ◽  
Author(s):  
M. Hamm ◽  
G. Goldbeck-Wood ◽  
A. V. Zvelindovsky ◽  
G. J. A. Sevink ◽  
J. G. E. M. Fraaije
Keyword(s):  
Liquid Crystalline ◽  
Field Model ◽  
Mean Field ◽  
Liquid Crystalline Polymers ◽  
Mean Field Model ◽  
Crystalline Polymers
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