研究者業績

安田 修悟

ヤスダ シユウゴ  (Shugo Yasuda)

基本情報

所属
兵庫県立大学 大学院 情報科学研究科 教授
学位
博士(工学)(2005年3月 京都大学)
修士(工学)(2002年3月 京都大学)

ORCID ID
 https://orcid.org/0000-0002-1824-0032
J-GLOBAL ID
201401009349676260
researchmap会員ID
B000238758

外部リンク

学歴

 3

委員歴

 2

論文

 31
  • Kotaro Oda, Shugo Yasuda
    Physical Review E 2024年6月3日  査読有り
  • Kenta Adachi, Shugo Yasuda
    Springer Proceedings in Mathematics & Statistics 235-248 2023年10月31日  査読有り
  • Shugo YASUDA
    Bulletin of Mathematical Biology 84(10) 113-113 2022年10月  査読有り
    Aggregation of chemotactic bacteria under a unimodal distribution of chemical cues was investigated by Monte Carlo (MC) simulation based on a kinetic transport equation, which considers an internal adaptation dynamics as well as a finite tumbling duration. It was found that there exist two different regimes of the adaptation time, between which the effect of the adaptation time on the aggregation behavior is reversed; that is, when the adaptation time is as small as the running duration, the aggregation becomes increasingly steeper as the adaptation time increases, while, when the adaptation time is as large as the diffusion time of the population density, the aggregation becomes more diffusive as the adaptation time increases. Moreover, the aggregation profile becomes bimodal (volcano) at the large adaptation-time regime when the tumbling duration is sufficiently large while it is always unimodal at the small adaptation-time regime. A remarkable result of this study is the identification of the parameter regime and scaling for the volcano effect. That is, by comparing the results of MC simulations to the continuum-limit models obtained at each of the small and large adaptation-time scalings, it is clarified that the volcano effect arises due to the coupling of diffusion, adaptation, and finite tumbling duration, which occurs at the large adaptation-time scaling.
  • Shugo Yasuda
    Physical Biology 18(6) 066001 2021年11月1日  査読有り
    The effects of internal adaptation dynamics on the self-organized aggregation of chemotactic bacteria are investigated by Monte Carlo (MC) simulations based on a two-stream kinetic transport equation coupled with a reaction-diffusion equation of the chemoattractant that bacteria produce. A remarkable finding is a nonmonotonic behavior of the peak aggregation density with respect to the adaptation time; more specifically, aggregation is the most enhanced when the adaptation time is comparable to or moderately larger than the mean run time of bacteria. Another curious observation is the formation of a trapezoidal aggregation profile occurring at a very large adaptation time, where the biased motion of individual cells is rather hindered at the plateau regimes due to the boundedness of the tumbling frequency modulation. Asymptotic analysis of the kinetic transport system is also carried out, and a novel asymptotic equation is obtained at the large adaptation-time regime while the Keller-Segel type equations are obtained when the adaptation time is moderate. Numerical comparison of the asymptotic equations with MC results clarifies that trapezoidal aggregation is well described by the novel asymptotic equation, and the nonmonotonic behavior of the peak aggregation density is interpreted as the transient of the asymptotic solutions between different adaptation time regimes.
  • Nicolas Vauchelet, Shugo Yasuda
    Multiscale Modeling & Simulation 19(1) 184-207 2021年1月  査読有り

MISC

 47

講演・口頭発表等

 85

共同研究・競争的資金等の研究課題

 7

学術貢献活動

 11

社会貢献活動

 7