Rumor Diffusion and Convergence during the 3.11 Earthquake: A Twitter Case Study

We focus on Internet rumors and present an empirical analysis and simulation results of their diffusion and convergence during emergencies. In particular, we study one rumor that appeared in the immediate aftermath of the Great East Japan Earthquake on March 11, 2011, which later turned out to be misinformation. By investigating whole Japanese tweets that were sent one week after the quake, we show that one correction tweet, which originated from a city hall account, diffused enormously. We also demonstrate a stochastic agent-based model, which is inspired by contagion model of epidemics SIR, can reproduce observed rumor dynamics. Our model can estimate the rumor infection rate as well as the number of people who still believe in the rumor that cannot be observed directly. For applications, rumor diffusion sizes can be estimated in various scenarios by combining our model with the real data.     

The Africanized honey bee dispersal: A mathematical zoom

A general mathematical model for population dispersal featuring long range taxis is presented and exemplified by the dispersal episode of the Africanized honey bees (Apis mellifera adansonii) throughout the American Continent. The mathematical model is a discrete-time and nonlocal model represented by an integrodifference recursion. A newtaxis concept is defined and introduced into the mathematical model by an appropriate modification of the redistribution kernel. The model is capable of predicting the natural barrier for the expansion of the Africanized honey bees in the southern part of the Continent due to low winter temperatures. It also describes a sensitive expansion velocity with respect to the quality of resources, which can explain the AHB’s astounding spread rate, by using two different kinds of population dynamics strategies, one for a resourceful environment and the other for poor regions. An erratum to this article is available at .     

Immunization against the Spread of Rumors in Homogenous Networks

Since most rumors are harmful, how to control the spread of such rumors is important. In this paper, we studied the process of "immunization" against rumors by modeling the process of rumor spreading and changing the termination mechanism for the spread of rumors to make the model more realistic. We derived mean-field equations to describe the dynamics of the rumor spread. By carrying out steady-state analysis, we derived the spreading threshold value that must be exceeded for the rumor to spread. We further discuss a possible strategy for immunization against rumors and obtain an immunization threshold value that represents the minimum level required to stop the rumor from spreading. Numerical simulations revealed that the average degree of the network and parameters of transformation probability significantly influence the spread of rumors. More importantly, the simulations revealed that immunizing a higher proportion of individuals is not necessarily better because of the waste of resources and the generation of unnecessary information. So the optimal immunization rate should be the immunization threshold.     

Neutral evolution in spatially continuous populations

We introduce a general recursion for the probability of identity in state of two individuals sampled from a population subject to mutation, migration, and random drift in a two-dimensional continuum. The recursion allows for the interactions induced by density-dependent regulation of the population, which are inevitable in a continuous population. We give explicit series expansions for large neighbourhood size and for low mutation rates respectively and investigate the accuracy of the classical Malécot formula for these general models. When neighbourhood size is small, this formula does not give the identity even over large scales. However, for large neighbourhood size, it is an accurate approximation which summarises the local population structure in terms of three quantities: the effective dispersal rate, sigma(e); the effective population density, rho(e); and a local scale, kappa, at which local interactions become significant. The results are illustrated by simulations.     

Plant–pollinator population dynamics

We formulate and analyze a multi-generation population dynamics model for pollinators’ mutualism with plants. The centerpiece of our model is an analytical expression for population-level plant–pollinator interactions extrapolated from a model of individual-level flowers and bees interactions. We also show that this analytical expression can be productively approximated by the Beddington–DeAngelis formula—a function used to model trophic interactions in mathematical ecology.     

Plant–pollinator population dynamics

We formulate and analyze a multi-generation population dynamics model for pollinators’ mutualism with plants. The centerpiece of our model is an analytical expression for population-level plant–pollinator interactions extrapolated from a model of individual-level flowers and bees interactions. We also show that this analytical expression can be productively approximated by the Beddington–DeAngelis formula—a function used to model trophic interactions in mathematical ecology.     

Internet congestion control using nature population control tactics

In this paper we present a novel bio-inspired approach for congestion control in communication networks. This scheme is based on inspiration by natural population interactions: predator–prey and competition. We show that the relations of those Internet entities that are involved in congestion control mechanisms are similar to predator–prey and competition interactions. In order to apply these population control mechanisms to the Internet congestion control scheme, we combine the mathematical models of these interactions and obtain a hybrid mathematical model. The simulation results show that using appropriately defined parameters, this model leads to a scalable, stable, fair, and high-performance congestion control algorithm.     

Sterilizing vaccines or the politics of the womb: retrospective study of a rumor in Cameroon

In 1990 a rumor that public health workers were administering a vaccine to sterilize girls and women spread throughout Cameroon. Schoolgirls leapt from windows to escape the vaccination teams, and the vaccination campaign (part of the Year of Universal Child Immunization) was aborted. This article traces the origin and development of this rumor. Theories of rumor and ambiguous cultural response to new technologies shed some light on its genesis and spread, but explain neither its timing nor its content. For this task we need to examine the historical context of Cameroonian experience with colonial vaccination campaigns and the contemporary contexts of the turmoil of democratization movements and economic crisis, concurrent changes in contraceptive policy, and regional mistrust of the state and its "hegemonic project." Drawing on Bayart's politique du ventre and White's thoughts on gossip, we explore this rumor as diagnostic of local response to global and national projects. This response, expressed in this case through the idiom of threats to local reproductive capacity, reveals a feminine side to local-global relations, a politics of the womb.     

Modulation of acridine mutagen ICR191 intercalation to DNA by methylxanthines—Analysis with mathematical models

Caffeine (CAF) and other methylxanthines (MTX) may interact directly with several aromatic, intercalating ligands through mixed stacking aggregation. Formation of such stacking hetero-complexes may decrease their free form concentration and, in consequence, diminish their biological activity, which is often related to their direct interaction with DNA. In this paper interactions of acridine mutagen (ICR191) with DNA in the presence of three MTX: caffeine (CAF), pentoxifylline (PTX) and theophylline (TH) are investigated. Several mathematical models are used to calculate all association constant values and every component concentration in each analyzed mixture. Model McGhee–von Hippel is used to analyze ligand–DNA interaction, and model Zdunek et al.—to analyze ligand–MTX interactions. Finally, two distinct mathematical models are employed to analyze three-component mixture containing ligand, MTX and DNA molecules. The first model describes possible interactions of ligand with DNA and MTX, and rejects direct MTX interactions with DNA. The second model describes all interactions mentioned above and, additionally, allows MTX to interact directly with DNA. Results obtained using these models are similar. However, correspondence of theoretical results to experimental data is better for the first model than the second one. In this paper possible interactions of ICR191 with eukaryotic cell chromatin are also analyzed, showing that CAF reduces acridine mutagen potential to interact directly with cell chromatin. Additionally, it is demonstrated that MTX inhibit mutagenic activity of ICR191 in a dose-dependent manner. Furthermore, biological activity of ICR191–MTX mixtures corresponds with concentration of free mutagen form calculated using appropriate mathematical model.     

A mathematical synthesis of niche and neutral theories in community ecology

The debate between niche-based and neutral community theories centers around the question of which forces shape predominantly ecological communities. Niche theory attributes a central role to niche differences between species, which generate a difference between the strength of intra- and interspecific interactions. Neutral theory attributes a central role to migration processes and demographic stochasticity. One possibility to bridge these two theories is to combine them in a common mathematical framework. Here we propose a mathematical model that integrates the two perspectives. From a niche-based perspective, our model can be interpreted as a Lotka-Volterra model with symmetric interactions in which we introduce immigration and demographic stochasticity. From a neutral perspective, it can be interpreted as Hubbell's local community model in which we introduce a difference between intra- and interspecific interactions. We investigate the stationary species abundance distribution and other community properties as functions of the interaction coefficient, the immigration rate and the strength of demographic stochasticity.