MS09 - ECOP-05 Part 4 of 4

Celebrating 60 Years of Excellence: Honoring Yang Kuang’s Contributions to Mathematical Biology (Part 4)

Friday, July 18 from 4:00pm - 5:40pm in Salon 9

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Organizers:

Tin Phan (Los Alamos National Laboratory), Yun Kang (Arizona State University); Tracy Stepien (University of Florida)

Description:

This session is organized to honor Professor Yang Kuang for his pioneering contributions to mathematical biology, his spirit of collaboration, and his dedication to mentoring 28 PhD students, as well as numerous postdoctoral, master's, and undergraduate researchers. Invited speakers will present cutting-edge research inspired by Dr. Kuang’s foundational work, spanning ecological stoichiometry, delay and partial differential equations, and data-driven modeling in biology. Together, we highlight Dr. Kuang’s achievements and the profound influence his work has on guiding the next generation of researchers in mathematical biology.

Room assignment: Salon 9



Yun Kang

Arizona State University
"Recognizing and Honoring Yang Kuang’s Contributions to Mathematical Biology"
This presentation is dedicated to celebrating the extraordinary career of Professor Yang Kuang, whose pioneering contributions have left a lasting impact on the field of mathematical biology. Professor Kuang's research, spanning ecological stoichiometry, delay differential equations, partial differential equations, and data-driven modeling, has shaped critical directions in both theoretical and applied biosciences. Beyond his influential scientific achievements, Dr. Kuang is widely recognized for his collaborative spirit and unwavering dedication to mentoring. Over the course of his career, he has guided 29 Ph.D. students and mentored numerous postdoctoral fellows, master’s students, and undergraduates, many of whom have gone on to make significant contributions to academia, industry, and government. In this talk, we will share personal reflections, quotes, and experiences collected from Dr. Kuang’s former students, postdoctoral scholars, and collaborators. Through their stories, we aim to highlight not only his profound academic influence but also his remarkable legacy as a mentor, role model, and community builder. This celebration honors both the depth of Dr. Kuang’s scholarship and the far-reaching impact he has had in shaping the next generation of mathematical biologists.



Jiaxu Li

University of Louisville
"The role of fatty acid in the progression of T2D"
Existing mathematical models investigating the progression of type 2 diabetes (T2D) over time often omitting fatty acids (FA) as an explicit variable, despite FA being a major energy source for the body. There exists a complex network of dynamical interactions among glucose, insulin, FA, and $beta$-cell mass, and the insulin sensitivity. To gain deeper insights into the metabolic dynamics and pathophysiology of T2D, it is essential to incorporate FA into such models. We extend the classic Topp’s $GIbeta$ model by explicitly incorporating FA and exploring its interactions with glucose, insulin, and $beta$-cell mass, and formulate a new formula for insulin sensitivity to better capture the impaired effect of FA on $S_I$, enabling the exploration of diabetes development pathways and strategies for prevention or onset delay. Our findings support the notion that glucotoxicity and lipotoxicity accelerate $beta$-cell decline, impair insulin secretion, and drive T2D progression. Elevated FA thus emerges not only as a contributing pathway but also as a potential biomarker for monitoring disease development. Furthermore, the observed relationship between glucose and FA levels seems to suggest a quantitative marker that could be used to track progression toward T2D. (Coauthors: R. Islam, J. Yang, M. Li, SP Mokshagundam, L. Cai)



Bingtuan Li

University of Louisville
"Forced Traveling Waves in a Reaction-Diffusion Equation with a Strong Allee Effect and Shifting Habitat"
Renewed interest in spatial ecology has emerged, largely due to the threats posed by global change. Shifts in habitat suitability for many species have already occurred and are expected to continue, profoundly affecting invasion dynamics. In this study, we consider a reaction-diffusion equation modeling the growth of a population subject to a strong Allee effect within a bounded habitat that shifts at a constant speed c. We demonstrate that the existence of forced positive traveling waves depends on the habitat size L and on c∗, the wave speed for the corresponding reaction-diffusion equation defined over an unbounded spatial domain with the same growth function. Specifically, we show that when c∗>c>0, there exists a positive threshold L∗(c) such that two positive traveling waves exist if L>L∗(c), while no positive traveling wave exists if Lc∗, then for any L>0, no positive traveling wave exists. These theoretical results are complemented by numerical simulations that explore the equation’s dynamics in greater detail.



Shigui Ruan

University of Miami
"On the geographic spread of chikungunya between Brazil and Florida: a multi-patch model with time delay"
Chikungunya (CHIK) is a viral disease transmitted to humans through the bites of Aedes mosquitoes infected with the chikungunya virus (CHIKV). CHIKV has been imported annually to Florida in the last decade due to Miami's crucial location as a hub for international travel, particularly from Central and South America including Brazil, where CHIK is endemic. This work addresses to the geographic spread of CHIK, incorporating factors such as human movement, temperature dependency, as well as vertical transmission, and incubation periods, for different patches. Central to the model is the integration of a multi-patch framework, and in the numerical analysis it is considered human movement between endemic Brazilian states and Florida. We establish crucial correlations between the mosquito reproduction number R_m and the disease reproduction number R_0 with the disease dynamics in a multi-patch environment, encompassing not only a numerical analysis but also from a theoretical perspective. Through numerical simulations, validated with real population and temperature data, it is possible to understand the disease dynamics under many different scenarios and make future projections, offering insights for potential effective control strategies, as well as addressing the timing for these strategies to be adopted.



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