On the Substantial Spatial Spread of the Quadrantid Meteoroid Stream

Although the power of low-frequency oscillatory field potentials (FP) has been extensively applied previously, few studies have investigated the influence of conducting direction of deep-brain rhythm generator on the power distribution of low-frequency oscillatory FPs on the head surface. To address this issue, a simulation was designed based on the principle of electroencephalogram (EEG) generation of equivalent dipole current in deep brain, where a single oscillatory dipole current represented the rhythm generator, the dipole moment for the rhythm generator’s conducting direction (which was orthogonal and rotating every 30 degrees and at pointing to or parallel to the frontal lobe surface) and the (an)isotropic conduction medium for the 3D (a)symmetrical brain tissue. Both the power above average (significant power value, SP value) and its space (SP area) of low-frequency oscillatory FPs were employed to respectively evaluate the strength and the space of the influence. The computation was conducted using the finite element method (FEM) and Hilbert transform. The finding was that either the SP value or the SP area could be reduced or extended, depending on the conducting direction of deep-brain rhythm generator flowing in the (an)isotropic medium, suggesting that the 3D (a)symmetrical brain tissue could decay or strengthen the spatial spread of a rhythm generator conducting in a different direction.

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Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan

BMC Public Health ◽

10.1186/s12889-021-10260-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Meng-Chun Chang ◽

Rebecca Kahn ◽

Yu-An Li ◽

Cheng-Sheng Lee ◽

Caroline O. Buckee ◽

...

Keyword(s):

Disease Surveillance ◽

Initial Conditions ◽

Human Mobility ◽

Human Movement ◽

Disease Spread ◽

Spatial Spread ◽

Movement Data ◽

Intercity Travel ◽

Travel Restrictions ◽

The Impact

Abstract Background As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. Methods In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. Results We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. Conclusions To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions.

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Controlling the Spatial Spread of a Xylella Epidemic

Bulletin of Mathematical Biology ◽

10.1007/s11538-021-00861-z ◽

2021 ◽

Vol 83 (4) ◽

Author(s):

Sebastian Aniţa ◽

Vincenzo Capasso ◽

Simone Scacchi

Keyword(s):

Spatial Structure ◽

Numerical Simulations ◽

Control Strategies ◽

Xylella Fastidiosa ◽

Cost Effective ◽

Olive Tree ◽

Control Measures ◽

Weed Biomass ◽

Spatial Spread ◽

Olive Trees

AbstractIn a recent paper by one of the authors and collaborators, motivated by the Olive Quick Decline Syndrome (OQDS) outbreak, which has been ongoing in Southern Italy since 2013, a simple epidemiological model describing this epidemic was presented. Beside the bacterium Xylella fastidiosa, the main players considered in the model are its insect vectors, Philaenus spumarius, and the host plants (olive trees and weeds) of the insects and of the bacterium. The model was based on a system of ordinary differential equations, the analysis of which provided interesting results about possible equilibria of the epidemic system and guidelines for its numerical simulations. Although the model presented there was mathematically rather simplified, its analysis has highlighted threshold parameters that could be the target of control strategies within an integrated pest management framework, not requiring the removal of the productive resource represented by the olive trees. Indeed, numerical simulations support the outcomes of the mathematical analysis, according to which the removal of a suitable amount of weed biomass (reservoir of Xylella fastidiosa) from olive orchards and surrounding areas resulted in the most efficient strategy to control the spread of the OQDS. In addition, as expected, the adoption of more resistant olive tree cultivars has been shown to be a good strategy, though less cost-effective, in controlling the pathogen. In this paper for a more realistic description and a clearer interpretation of the proposed control measures, a spatial structure of the epidemic system has been included, but, in order to keep mathematical technicalities to a minimum, only two players have been described in a dynamical way, trees and insects, while the weed biomass is taken to be a given quantity. The control measures have been introduced only on a subregion of the whole habitat, in order to contain costs of intervention. We show that such a practice can lead to the eradication of an epidemic outbreak. Numerical simulations confirm both the results of the previous paper and the theoretical results of the model with a spatial structure, though subject to regional control only.

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Modeling and Optimizing the Multi-Objective Portfolio Optimization Problem with Trapezoidal Fuzzy Parameters

Mathematical and Computational Applications ◽

10.3390/mca26020036 ◽

2021 ◽

Vol 26 (2) ◽

pp. 36

Author(s):

Alejandro Estrada-Padilla ◽

Daniela Lopez-Garcia ◽

Claudia Gómez-Santillán ◽

Héctor Joaquín Fraire-Huacuja ◽

Laura Cruz-Reyes ◽

...

Keyword(s):

Steady State ◽

Portfolio Optimization ◽

Optimization Problem ◽

Solution Process ◽

Density Estimator ◽

Nsga Ii ◽

Spatial Spread ◽

Multi Objective ◽

Significant Difference ◽

Portfolio Optimization Problem

A common issue in the Multi-Objective Portfolio Optimization Problem (MOPOP) is the presence of uncertainty that affects individual decisions, e.g., variations on resources or benefits of projects. Fuzzy numbers are successful in dealing with imprecise numerical quantities, and they found numerous applications in optimization. However, so far, they have not been used to tackle uncertainty in MOPOP. Hence, this work proposes to tackle MOPOP’s uncertainty with a new optimization model based on fuzzy trapezoidal parameters. Additionally, it proposes three novel steady-state algorithms as the model’s solution process. One approach integrates the Fuzzy Adaptive Multi-objective Evolutionary (FAME) methodology; the other two apply the Non-Dominated Genetic Algorithm (NSGA-II) methodology. One steady-state algorithm uses the Spatial Spread Deviation as a density estimator to improve the Pareto fronts’ distribution. This research work’s final contribution is developing a new defuzzification mapping that allows measuring algorithms’ performance using widely known metrics. The results show a significant difference in performance favoring the proposed steady-state algorithm based on the FAME methodology.

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Implications of seasonal variations, host and vector migration on spatial spread of sleeping sickness: Insights from a mathematical model

Informatics in Medicine Unlocked ◽

10.1016/j.imu.2021.100570 ◽

2021 ◽

Vol 24 ◽

pp. 100570

Author(s):

Mlyashimbi Helikumi ◽

Paride O. Lolika ◽

Steady Mushayabasa

Keyword(s):

Mathematical Model ◽

Seasonal Variations ◽

Sleeping Sickness ◽

Spatial Spread

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The Spatial Spread of the AIDS Epidemic in Ohio: Empirical Analyses Using the Expansion Method

Environment and Planning A Economy and Space ◽

10.1068/a231589 ◽

1991 ◽

Vol 23 (11) ◽

pp. 1589-1608 ◽

Cited By ~ 21

Author(s):

E Casetti ◽

C C Fan

Keyword(s):

Expansion Method ◽

Spatial Spread ◽

Aids Epidemic ◽

Empirical Analyses

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LATTICE THREE-SPECIES MODELS OF THE SPATIAL SPREAD OF RABIES AMONG FOXES

International Journal of Modern Physics C ◽

10.1142/s0129183199000826 ◽

1999 ◽

Vol 10 (06) ◽

pp. 1025-1038 ◽

Cited By ~ 15

Author(s):

A. BENYOUSSEF ◽

N. BOCCARA ◽

H. CHAKIB ◽

H. EZ-ZAHRAOUY

Keyword(s):

Carrying Capacity ◽

Short Range ◽

Lattice Models ◽

Infection Process ◽

Spatial Spread ◽

One Dimensional ◽

Sense Of Direction ◽

Speed Of Propagation ◽

Automata Network ◽

And Diffusion

Lattice models describing the spatial spread of rabies among foxes are studied. In these models, the fox population is divided into three-species: susceptible (S), infected or incubating (I), and infectious or rabid (R). They are based on the fact that susceptible and incubating foxes are territorial while rabid foxes have lost their sense of direction and move erratically. Two different models are investigated: a one-dimensional coupled-map lattice model, and a two-dimensional automata network model. Both models take into account the short-range character of the infection process and the diffusive motion of rabid foxes. Numerical simulations show how the spatial distribution of rabies, and the speed of propagation of the epizootic front depend upon the carrying capacity of the environment and diffusion of rabid foxes out of their territory.

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