arXiv subjects

Longmei Shu

Publications and source records attributed to Longmei Shu.

8 recordsLinked to original sources

arXiv2026

Modeling microbiome dynamics on social networks: how between-host transmission shapes within-host evolution

A social network perspective on the human microbiome is crucial for understanding how the interplay between within-host microbial dynamics and between-host transmission influences microbial community stability, host metabolism, and population health and nutrition. Here, we provide a mathematical and numerical analysis of human-associated microbial communities in dyadic social ties and within a small network. By utilizing a generalized Lotka-Volterra model, we simulate within-host dynamics while incorporating inter-host microbial sharing driven by social interactions. Furthermore, the study accounts for individual variability in microbial behavior across different hosts. Our work identifies the conditions under which microbial sharing can have long-lasting effects, offering insights into how social networks shape the human microbiome.

physics.soc-ph↗

arXiv2023

Determinants of successful mitigation in coupled social-climate dynamics

Understanding the impact of human behavior is crucial for successful mitigation of climate change across the globe. To shed light onto this issue, here we couple the forest dieback model with human behaviors. Using evolutionary game theory, we build a time-delay system where forest growth is impacted by both temperature and human mitigation choices, the latter being informed by temperature forecasts. Simulations of the coupled system over 200 years show us the varying outcomes: forest dies out and no one is a mitigator, forest dies out and everyone is a mitigator, or the forest survives and everyone is a mitigator. There exist rare cases where no one is a mitigator and yet the forest survives, but with a low coverage. We also find occasional oscillations where the proportion of mitigators vary between 0 and 1. Our results are based on simple models but have profound insights into determinants of behavior changes desired in social-climate dynamics.

physics.soc-ph↗

arXiv2023

Isospectral Reductions of Non-negative Matrices

Isospectral reduction is an important tool for network/matrix analysis as it reduces the dimension of a matrix/network while preserving its eigenvalues and eigenvectors. The main contribution of this manuscript is a proposed algorithmic scheme to approximate the stationary measure of a stochastic matrix based on isospectral reductions. We run numerical experiments that indicate this scheme is advantageous when there is more than one eigenvalue near 1, precisely the case where iterative methods perform poorly. We give a partial explanation why this scheme should work well, showing that in some situations isospectral reduction improves the spectral gap.

math.DS↗

arXiv2022

Eco-Evolutionary Dynamics of Bimatrix Games

Feedbacks between strategies and the environment are common in social-ecological, evolutionary-ecological, and even psychological-economic systems. Utilizing common resources is always a dilemma for community members, like tragedy of the commons. Here we consider replicator dynamics with feedback-evolving games, where the payoffs switch between two different matrices. Although each payoff matrix on its own represents an environment where cooperators and defectors can't coexist stably, we show that it's possible to design appropriate switching control laws and achieve persistent oscillations of strategy abundance. This result should help guide the widespread problem of population state control in microbial experiments and other social problems with eco-evolutionary feedback loops.

math.DS↗

arXiv2020

Local Immunodeficiency: Role of Neutral Viruses

This paper analyzes the role of neutral viruses in the phenomenon of local immunodeficiency. We show that, even in the absence of altruistic viruses, neutral viruses can support the existence of persistent viruses, and thus local immunodeficiency. However, in all such cases neutral viruses can maintain only bounded (relatively small) concentration of persistent viruses. Moreover, in all such cases the state of local immunodeficiency could only be marginally stable, while it is known that altruistic viruses can maintain stable local immunodeficiency. We also present an absolutely minimal cross-immunoreactivity network where a stable and robust state of local immunodeficiency can be maintained. It is now a challenge to synthetic biology to build such small networks with stable local immunodeficiency. Another important challenge for biology is to understand which types of viruses can play a role of persistent, altrustic and neutral ones, and whether a role which a given virus plays depends on the structure (topology) of a given cross-immunoreactivity network.

math.DS↗

arXiv2019

Local Immunodeficiency: Minimal Networks and Stability

Some basic aspects of the recently discovered phenomenon of local immunodeficiency \cite{pnas} generated by antigenic cooperation in cross-immunoreactivity (CR) networks are investigated. We prove that local immunodeficiency (LI) that's stable under perturbations already occurs in very small networks and under general conditions on their parameters. Therefore our results are applicable not only to Hepatitis C where CR networks are known to be large \cite{pnas}, but also to other diseases with CR. A major necessary feature of such networks is the non-homogeneity of their topology. It is also shown that one can construct larger CR networks with stable LI by using small networks with stable LI as their building blocks. Our results imply that stable LI occurs in networks with quite general topology. In particular, the scale-free property of a CR network, assumed in \cite{pnas}, is not required.

math.DS↗

arXiv2018

On Attractors of Isospectral Compressions of Networks

In the recently developed theory of isospectral transformations of networks isospectral compressions are performed with respect to some chosen characteristic (attribute) of nodes (or edges) of networks. Each isospectral compression (when a certain characteristic is fixed) defines a dynamical system on the space of all networks. It is shown that any orbit of such dynamical system which starts at any finite network (as the initial point of this orbit) converges to an attractor. Such attractor is a smaller network where a chosen characteristic has the same value for all nodes (or edges). We demonstrate that isospectral contractions of one and the same network defined by different characteristics of nodes (or edges) may converge to the same as well as to different attractors. It is also shown that spectrally equivalent with respect to some characteristic networks could be non-spectrally equivalent for another characteristic of nodes (edges). These results suggest a new constructive approach to analysis of networks structures and to comparison of topologies of different networks.

math.DS↗

arXiv2018

Generalized Eigenvectors of Isospectral Transformations,Spectral Equivalence and Reconstruction of Original Networks

Isospectral transformations (IT) of matrices and networks allow for compression of either object while keeping all the information about their eigenvalues and eigenvectors.We analyze here what happens to generalized eigenvectors under isospectral transformations and to what extent the initial network can be reconstructed from its compressed image under IT. We also generalize and essentially simplify the proof that eigenvectors are invariant under isospectral transformations and generalize and clarify the notion of spectral equivalence of networks.

math.DS↗