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Small inter-event times govern epidemic spreading on networks

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Physical Review Research 2020年第2期2卷 023163-023163页

作者： Naoki Masuda Petter Holme Department of Mathematics University at Buffalo State University of New York Buffalo New York 14260-2900 USA Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York Buffalo New York 14260-5030 USA Tokyo Tech World Research Hub Initiative (WRHI) Institute of Innovative Research Tokyo Institute of Technology Yokohama 226-8503 Japan

Many aspects of human and animal interaction, such as the frequency of contacts of an individual, the number of interaction partners, and the time between the contacts of two individuals, are characterized by heavy-tailed distributions. These distributions affect the spreading of, e.g., infectious diseases or rumors, often because of impacts of the right tail of the distributions (i.e., the large values). In this paper we show that when it comes to inter-event time distributions, it is not the tail but the small values that control spreading dynamics. We investigate this effect both analytically and numerically for different versions of the susceptible-infected-recovered model on different types of networks.

关键词： Epidemic Epidemic evolution Epidemic growth Epidemic prevalence

Small inter-event times govern epidemic spreading on temporal networks

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arXiv 2019年

作者： Masuda, Naoki Holme, Petter Department of Mathematics University at Buffalo State University of New York BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-5030 United States Institute of Innovative Research Tokyo Institute of Technology Yokohama226-8503 Japan

Just like the degrees of human and animal interaction networks, the distribution of the times between interactions is known to often be right-skewed and fat-tailed. Both these distributions affect epidemic dynamics strongly, but, as we show in this Letter, for very different reasons. Whereas the high degrees of the tail are critical for facilitating epidemics, it is the small interevent times that control the dynamics of epidemics. We investigate this effect both analytically and numerically for different versions of the Susceptible-Infected-Recovered model on different types of networks. Copyright © 2019, The Authors. All rights reserved.

关键词： Epidemiology

Generative models of simultaneously heavy-tailed distributions of interevent times on nodes and edges

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Physical Review E 2020年第5期102卷 052303-052303页

作者： Elohim Fonseca dos Reis Aming Li Naoki Masuda Department of Mathematics State University of New York at Buffalo Buffalo New York 14260 USA Department of Zoology University of Oxford Oxford OX1 3PS United Kingdom Department of Biochemistry University of Oxford Oxford OX1 3QU United Kingdom Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo Buffalo New York 14260 USA Faculty of Science and Engineering Waseda University 169-8555 Tokyo Japan

Intervals between discrete events representing human activities, as well as other types of events, often obey heavy-tailed distributions, and their impacts on collective dynamics on networks such as contagion processes have been intensively studied. The literature supports that such heavy-tailed distributions are present for interevent times associated with both individual nodes and individual edges in networks. However, the simultaneous presence of heavy-tailed distributions of interevent times for nodes and edges is a nontrivial phenomenon, and its origin has been elusive. In the present study, we propose a generative model and its variants to explain this phenomenon. We assume that each node independently transits between a high-activity and low-activity state according to a continuous-time two-state Markov process and that, for the main model, events on an edge occur at a high rate if and only if both end nodes of the edge are in the high-activity state. In other words, two nodes interact frequently only when both nodes prefer to interact with others. The model produces distributions of interevent times for both individual nodes and edges that resemble heavy-tailed distributions across some scales. It also produces positive correlation in consecutive interevent times, which is another stylized observation for empirical data of human activity. We expect that our modeling framework provides a useful benchmark for investigating dynamics on temporal networks driven by non-Poissonian event sequences.

关键词： Network structure Social networks Stochastic networks Network Models

Multilevel Particle Filters for Partially Observed McKean-Vlasov Stochastic Differential Equations

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arXiv 2024年

作者： Awadelkarim, Elsiddig Jasra, Ajay Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia School of Data Science The Chinese University of Hong Kong Shenzhen China

In this paper we consider the filtering problem associated to partially observed McKean-Vlasov stochastic differential equations (SDEs). The model consists of data that are observed at regular and discrete times and the objective is to compute the conditional expectation of (functionals) of the solutions of the SDE at the current time. This problem, even the ordinary SDE case is challenging and requires numerical approximations. Based upon the ideas in [3, 12] we develop a new particle filter (PF) and multilevel particle filter (MLPF) to approximate the afore-mentioned expectations. We prove under assumptions that, for ϵ > 0, to obtain a mean square error of O(ϵ2) the PF has a cost per-observation time of O(ϵ−5) and the MLPF costs O(ϵ−4) (best case) or O(ϵ−4 log(ϵ)2) (worst case). Our theoretical results are supported by numerical experiments. © 2024, CC BY.

关键词： Mean square error

Correction to: Mitigation strategies against cascading failures within a project activity network

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Journal of computational Social Science 2021年第1期5卷 1097-1098页

作者： Ellinas, Christos Nicolaides, Christos Masuda, Naoki Nodes and Links Ltd Cambridge UK Department of Business and Public Administration University of Cyprus Nicosia Cyprus Initiative on the Digital Economy Massachusetts Institute of Technology Cambridge USA Department of Mathematics State University of New York at Buffalo Buffalo USA Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo Buffalo USA Faculty of Management and Economics Dalian University of Technology Dalian China

Estimating international trade status of countries from global liner shipping networks

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arXiv 2020年

作者： Xu, Mengqiao Pan, Qian Xia, Haoxiang Masuda, Naoki School of Economics and Management Dalian University of Technology No. 2 Linggong Road Ganjingzi District Dalian City Liaoning Province116024 China Department of Mathematics University at Buffalo BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-5030 United States

Maritime shipping is a backbone of international trade and thus the world economy. Vessels travel from a port of one country to another on networks of ports to carry cargos, which contribute to countries’ international trade values. We hypothesize that ports that involve transshipment activities serve as a third-party middleman to mediate trade between two foreign countries and contribute to the corresponding country's status in international trade. We test this hypothesis using a port-level data set of global liner shipping services. We propose two indices that quantify the importance of countries in the global liner shipping network and show that they explain a large amount of variation in the international trade value and related measures of individual countries. These results support a long-standing view in maritime economics, which has yet been directly tested, that countries that are strongly integrated into the global maritime transportation network have enhanced access to global markets and trade opportunities. Copyright © 2020, The Authors. All rights reserved.

关键词： International trade

High-Throughput computational Studies in Catalysis and Materials Research, and their Impact on Rational Design

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arXiv 2019年

作者： Afzal, Mohammad Atif Faiz Hachmann, Johannes Schrödinger Inc. PortlandOR97204 United States Department of Chemical and Biological Engineering University at Buffalo State University of New York BuffaloNY14260 United States Computational and Data-Enabled Science and Engineering Graduate Program University at Buffalo The State University of New York BuffaloNY14260 United States New York State Center of Excellence in Materials Informatics BuffaloNY14203 United States

Efficient sampling of high-dimensional free energy landscapes using adaptive reinforced dynamics

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arXiv 2021年

作者： Wang, Dongdong Zhang, Linfeng Wang, Yanze Chang, Junhan Wang, Han Weinan, E. Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States DP Technology Beijing China College of Chemistry and Molecular Engineering Peking University Beijing100871 China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Fenghao East Road 2 Beijing100094 China School of Mathematical Sciences Peking University Beijing China Department of Mathematics Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Beijing Institute of Big Data Research Beijing100871 China

Enhanced sampling methods such as metadynamics and umbrella sampling have become essential tools for exploring the configuration space of molecules and materials. At the same time, they have long faced a number of issues such as the inefficiency when dealing with a large number of collective variables (CVs) or systems with high free energy barriers. In this work, we show that with the clustering and adaptive tuning techniques, the reinforced dynamics (RiD) scheme can be used to efficiently explore the configuration space and free energy landscapes with a large number of CVs or systems with high free energy barriers. We illustrate this by studying various representative and challenging examples. Firstly we demonstrate the efficiency of adaptive RiD compared with other methods, and construct the 9-dimensional free energy landscape of peptoid trimer which has energy barriers of more than 8 kcal/mol. We then study the folding of the protein chignolin using 18 CVs. In this case, both the folding and unfolding rates are observed to be equal to 4.30 µs−1. Finally, we propose a protein structure refinement protocol based on RiD. This protocol allows us to efficiently employ more than 100 CVs for exploring the landscape of protein structures and it gives rise to an overall improvement of 14.6 units over the initial Global Distance Test-High Accuracy (GDT-HA) score. © 2021, CC BY.

关键词： Wave functions

A growth model for water distribution networks with loops

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arXiv 2021年

作者： Sugishita, Kashin Abdel-Mottaleb, Noha Zhang, Qiong Masuda, Naoki Department of Mathematics State University of New York at Buffalo BuffaloNY14260-2900 United States Department of Transdisciplinary Science and Engineering Tokyo Institute of Technology Tokyo152-8550 Japan Department of Civil and Environmental Engineering University of South Florida TampaFL33620 United States Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY14260-5030 United States Faculty of Science and Engineering Waseda University Tokyo169-8555 Japan

Water distribution networks (WDNs) expand their service areas over time. These growth dynamics are poorly understood. One facet of WDNs is that they have loops in general, and closing loops may be a functionally important process for enhancing their robustness and efficiency. We propose a growth model for WDNs which generates networks with loops and is applicable to networks with multiple water sources. We apply the proposed model to four empirical WDNs to show that it produces networks whose structure is similar to that of the empirical WDNs. The comparison between the empirical and modeled WDNs suggests that the empirical WDNs may realize a reasonable balance between cost, efficiency, and robustness in terms of the network structure. We also study the design of pipe diameters based on a biological positive feedback mechanism. Specifically, we apply a model inspired by Physarum polycephalum to find moderate positive correlations between the empirical and modeled pipe diameters. The difference between the empirical and modeled pipe diameters suggests that we may be able to improve the performance of WDNs by following organizing principles of biological flow networks. Copyright © 2021, The Authors. All rights reserved.

关键词： Water distribution systems