2023年9月16日，数学科学学院在A413举办“2023年生物数学前沿问题学术研讨会”。报告内容和报告人如下：
报告题目：Mathematical Modeling and Analysis of Climate Changes
报告人：王稳地
报告时间：2023年9月16日 上午9:00-9:50
报告形式：线下会议
内容简介：In this talk, I start by talking about how climate changes affect population persistence. After that, I consider effects of a climate-induced range shift on outcomes of two competitive species. Finally, I show how plant behavior responses affect the spatial patterns.
报告人简介：王稳地：西南大学2级教授，博士生导师, 2005年获得重庆市名师称号, 2018年获得重庆市最美教师称号；从事生物数学的研究,在种群动力学和传染病动力学建模和分析方面发表论文100多篇，8次入选Elsevier数学类高引用论文作者；已经主持国家自然科学基金课题7项、教育部项目2项。
报告题目：Critical Bait Casting Threshold and Disease Transmission Dynamics of Fish in Passive Advective Environments
报告人：原三领
报告时间：2023年9月16日 上午10:10-11:00
报告形式：线下会议
内容简介：This talk is about the dynamics of fish population in passive advective environments which includes two parts. In the first part, we formulate a diffusive bait-fish model with advection term, aiming to determine the bait casting threshold that meets the demand for the breeding and causes less pollution to the water environment. The well-posedness, the net reproductive rate R0 determining the survival of the model and the relationship between R0 and the bait casting rate are fist discussed. Besides, we show that the model undergoes a forward supercritical transcritical bifurcation when the bait casting rate is equal to the critical value. In the second part, we propose a spatial eco-epidemiological system with disease spread within the predator population in open advective environments. The net reproductive rate Rp is first established for the disease-free subsystem to determine whether the predator can invade successfully. The impacts of advection rate on Rp are also discussed. For the scenario of successful invasion of the predator, sufficient conditions for the prevalence of disease and the local stability of disease-free attractor are obtained by dint of persistence theory and comparison theorem.
报告人简介：原三领，上海理工大学教授，博士生导师，中国数学会生物数学专业委员会副主任，国际学术期刊Mathematical Biosciences and Engineering编委。研究方向为：微分方程与动力系统、生物数学。先后主持多项国家和上海市基金项目的研究工作。研究内容涉及微分方程与动力系统、种群动力学、流行病动力学、海洋生态学以及生物化学工程等诸多领域，具有鲜明的多学科交叉特点。曾多次受邀到国内和国际多所高校进行合作研究和学术交流。已在Journal of Mathematical Biology、Journal of Differential Equations、Journal of Nonlinear Sciences等国内外重要学术刊物上发表SCI论文100余篇。
报告题目：Dynamical Analysis of Epidemics Based on Scale-free Networks and Higher-order Networks
报告人：刘茂省
报告时间：2023年9月16日 上午11:00-11:50
报告形式：线下会议
内容简介：In this talk, a new network-based SIR epidemic model, which incorporates the individual medical resource factor and public medical resource factor is proposed, and an epidemic model of the effect of media reports on higher-order networks is proposed, in which the simplicial complex is utilized to construct a social network that describes connections between nodes, where a single link can connect more than two individuals.
The theoretical results are illustrated by numerical simulations. Through theoretical analysis and numerical simulation, it has been found that analyzing the model on the network can lead to more complex dynamic phenomena.
报告人简介：刘茂省，男，北京建筑大学理学院教授，博士生导师，中国数学会生物数学专业委员会常务委员。2003年毕业于西安交通大学获得理学硕士学位，2009年毕业于复旦大学获得博士学位，2003-2022年工作于中北大学，曾在加拿大约克大学、匈牙利塞格德大学、美国亚利桑那州立大学访问。主要研究方向为网络传染病动力学，负责主持国家自然科学基金3项，参加国家自然科学基金5项，其中重点项目1项。曾主持山西省1331工程重点创新团队，主讲的《常微分方程》被评为山西省精品课程。曾获得山西省教学成果一等奖1项(第二完成人)，山西省科技奖自然类一等奖1项(第五完成人)，二等奖1项(第一完成人)等。
报告题目：Global Existence, Regularity, and Dissipativity of Retarded Reaction-diffusion Equations with Supercritical Nonliearities
报告人：李德生
报告时间：2023年9月16日 下午14:10-15:00
报告形式：线下会议
内容简介：In this talk I will discuss some recent results on the initial-boundary value problem of retarded reaction-diffusion equations in bounded domains with fast-growing nonlinearities. We allow the nonlinear terms to be supercritical, in which case even if local well-posedness is less well understood. We are particularly interested in how dissipative structures of the non-retarded terms can successfully control the retarded ones and produce nice analytic properties and determines the global dynamics of the problem. Specifically, we establish global existence and regularity results for solutions of the problem and prove the existence of global attractors. Although we are working in the context of retarded differential equations, to the best of our knowledge, part of our results are new even for non-retarded equations.
报告人简介：李德生，天津大学数学学院教授，博士生导师，主要从事动力系统和非线性微分方程方面的研究工作。1998 年研究了具有快速增长非线性项的 Cahn-Hilliard 系统的全局动力学行为，解决了著名数学家R.Temam的有关开问题，论文被全文录入J.W. Cholewa 和T.Dlotko的专著《Global attractor in abstract parabolic problems》(剑桥大学出版社, 2000), 同时被著名数学家G.R. Sell，Y.C. You和伍卓群等人的专著所收录。近期侧重于动力系统的Morse理论、Conley指标和大范围动态分支理论方面的研究，完整地建立了非光滑系统不变集和吸引子的Morse理论，由此给出了非线性系统链控制集的Morse刻划；建立了不变集的环绕定理和山路引理并证明了非自治共振热方程回复解的存在性；给出了非线性发展方程的全局不变集分支定理。作为主持人承担国家自然科学基金面上项目6项；在国内外著名数学期刊《Indiana Univ. Math. J.》、《J. Diff. Eqns.》、《SIAM J. Cont. Optim.》、《SIAM J. Appl. Dyna. Syst.》等杂志发表论文50余篇。成果曾获甘肃省自然科学一等奖、山东省自然科学二等奖各一项。
报告题目：Dynamical Data Science and AI
(动力学的数据科学与AI应用)
报告人：陈洛南
报告时间：2023年9月16日 下午17:00-17:50
报告形式：线下会议
内容简介：In this talk, I will present a new concept dynamics-based data science in AI applications of biology and medicine for studying dynamical processes and disease progressions, including dynamic network biomarkers (DNB) for early-warning signals of critical transitions, spatial-temporal information (STI) transformation for short-term time-series prediction, and partial cross-mapping (PCM) for causal inference among variables. These methods are all data-driven or model-free approaches but based on the theoretical frameworks of nonlinear dynamics. We show the principles and advantages of dynamics-based data-driven approaches as explicable, quantifiable, and generalizable. In particular, dynamics-based data science approaches exploit the essential features of dynamical systems in terms of data, e.g. strong fluctuations near a bifurcation point, low-dimensionality of a center manifold or an attractor, and phase-space reconstruction from a single variable by delay embedding theorem, and thus are able to provide different or additional information to the traditional approaches, i.e. statistics-based data science approaches. The dynamical-based data science approaches will further play an important role in the systematical research of various fields in biology and medicine as well as AI.
报告人简介：陈洛南，中国科学院分子细胞科学卓越创新中心研究员，国科大杭州高等研究院首席教授。现任中国生物化学与分子生物学会分子系统生物学专业分会主任委员，中国生物信息学会(筹)网络生物学专业分会主任委员，IEEE-SMC系统生物学委员会主席，中国运筹学会计算系统生物学分会名誉理事长。主要从事计算系统生物学、大数据分析和人工智能的研究工作，国家重点研发计划首席科学家，中国运筹学会首届会士。在系统生物学和复杂网络等研究领域发表了400余篇期刊论文及10余部编著书籍(H-index= 78; Elsevier高被引)。
（撰稿：裴永珍 审核：张国）
数学科学学院
2023年9月15日
