1
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Song R, Spadon G, Pelot R, Matwin S, Soares A. Enhancing global maritime traffic network forecasting with gravity-inspired deep learning models. Sci Rep 2024; 14:16665. [PMID: 39030401 PMCID: PMC11271636 DOI: 10.1038/s41598-024-67552-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 07/12/2024] [Indexed: 07/21/2024] Open
Abstract
Aquatic non-indigenous species (NIS) pose significant threats to biodiversity, disrupting ecosystems and inflicting substantial economic damages across agriculture, forestry, and fisheries. Due to the fast growth of global trade and transportation networks, NIS has been introduced and spread unintentionally in new environments. This study develops a new physics-informed model to forecast maritime shipping traffic between port regions worldwide. The predicted information provided by these models, in turn, is used as input for risk assessment of NIS spread through transportation networks to evaluate the capability of our solution. Inspired by the gravity model for international trades, our model considers various factors that influence the likelihood and impact of vessel activities, such as shipping flux density, distance between ports, trade flow, and centrality measures of transportation hubs. Accordingly, this paper introduces transformers to gravity models to rebuild the short- and long-term dependencies that make the risk analysis feasible. Thus, we introduce a physics-inspired framework that achieves an 89% binary accuracy for existing and non-existing trajectories and an 84.8% accuracy for the number of vessels flowing between key port areas, representing more than 10% improvement over the traditional deep-gravity model. Along these lines, this research contributes to a better understanding of NIS risk assessment. It allows policymakers, conservationists, and stakeholders to prioritize management actions by identifying high-risk invasion pathways. Besides, our model is versatile and can include new data sources, making it suitable for assessing international vessel traffic flow in a changing global landscape.
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Affiliation(s)
- Ruixin Song
- Department of Computer Science, Memorial University of Newfoundland, St. John's, NL, Canada
- Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada
- Industrial Engineering Department, Dalhousie University, Halifax, NS, Canada
| | - Gabriel Spadon
- Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada
- Industrial Engineering Department, Dalhousie University, Halifax, NS, Canada
| | - Ronald Pelot
- Industrial Engineering Department, Dalhousie University, Halifax, NS, Canada
| | - Stan Matwin
- Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada
- Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland
| | - Amilcar Soares
- Department of Computer Science and Media Technology, Linnaeus University, Växjö, Sweden.
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2
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Zhong Z, Takayasu H, Takayasu M. Human mobility description by physical analogy of electric circuit network based on GPS data. Sci Rep 2024; 14:13380. [PMID: 38862614 PMCID: PMC11167031 DOI: 10.1038/s41598-024-63719-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 05/31/2024] [Indexed: 06/13/2024] Open
Abstract
Human mobility in an urban area is complicated; the origins, destinations, and transportation modes of each person differ. The quantitative description of urban human mobility has recently attracted the attention of researchers, and it highly related to urban science problems. Herein, combined with physics inspiration, we introduce a revised electric circuit model (RECM) in which moving people are regarded as charged particles and analogical concepts of electromagnetism such as human conductivity and human potential enable us to capture the characteristics of urban human mobility. We introduce the unit system, ensure the uniqueness of the calculation result, and reduce the computation cost of the algorithm to 1/10,000 compared with the original ECM, making the model more universal and easier to use. We compared features including human conductivity and potential between different major cities in Japan to show our improvement of the universality and the application range of the model. Furthermore, based on inspiration of physics, we propose a route generation model (RGM) to simulate a human flow pattern that automatically determines suitable routes between a given origin and destination as a source and sink, respectively. These discoveries are expected to lead to new approaches to the solution of urban science problems.
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Affiliation(s)
- Zhihua Zhong
- School of Computing, Tokyo Institute of Technology, 4259, Nagatsutachō, Midori Ward, Yokohama, 226-8503, Japan
| | - Hideki Takayasu
- School of Computing, Tokyo Institute of Technology, 4259, Nagatsutachō, Midori Ward, Yokohama, 226-8503, Japan
- Sony Computer Science Laboratories, Tokyo, Japan
| | - Misako Takayasu
- School of Computing, Tokyo Institute of Technology, 4259, Nagatsutachō, Midori Ward, Yokohama, 226-8503, Japan.
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3
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Zhao P, Wang H, Liu Q, Yan XY, Li J. Unravelling the spatial directionality of urban mobility. Nat Commun 2024; 15:4507. [PMID: 38802395 PMCID: PMC11130278 DOI: 10.1038/s41467-024-48909-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 05/15/2024] [Indexed: 05/29/2024] Open
Abstract
As it is central to sustainable urban development, urban mobility has primarily been scrutinised for its scaling and hierarchical properties. However, traditional analyses frequently overlook spatial directionality, a critical factor in city centre congestion and suburban development. Here, we apply vector computation to unravel the spatial directionality of urban mobility, introducing a two-dimensional anisotropy-centripetality metric. Utilising travel data from 90 million mobile users across 60 Chinese cities, we effectively quantify mobility patterns through this metric, distinguishing between strong monocentric, weak monocentric, and polycentric patterns. Our findings highlight a notable difference: residents in monocentric cities face increasing commuting distances as cities expand, in contrast to the consistent commuting patterns observed in polycentric cities. Notably, mobility anisotropy intensifies in the outskirts of monocentric cities, whereas it remains uniform in polycentric settings. Additionally, centripetality wanes as one moves from the urban core, with a steeper decline observed in polycentric cities. Finally, we reveal that employment attraction strength and commuting distance scaling are key to explaining these divergent urban mobility patterns. These insights are important for shaping effective policies aimed at alleviating congestion and guiding suburban housing development.
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Affiliation(s)
- Pengjun Zhao
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China.
- School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China.
| | - Hao Wang
- School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China
| | - Qiyang Liu
- School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China.
| | - Xiao-Yong Yan
- School of Systems Science, Beijing Jiaotong University, Beijing, 100044, China.
| | - Jingzhong Li
- College of Urban and Environmental Sciences, Xuchang University, Xuchang, 461000, China
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4
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Patwardhan S, Barthelemy M, Erkol Ş, Fortunato S, Radicchi F. Symmetry breaking in optimal transport networks. Nat Commun 2024; 15:3758. [PMID: 38704371 PMCID: PMC11069546 DOI: 10.1038/s41467-024-48068-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 04/17/2024] [Indexed: 05/06/2024] Open
Abstract
Engineering multilayer networks that efficiently connect sets of points in space is a crucial task in all practical applications that concern the transport of people or the delivery of goods. Unfortunately, our current theoretical understanding of the shape of such optimal transport networks is quite limited. Not much is known about how the topology of the optimal network changes as a function of its size, the relative efficiency of its layers, and the cost of switching between layers. Here, we show that optimal networks undergo sharp transitions from symmetric to asymmetric shapes, indicating that it is sometimes better to avoid serving a whole area to save on switching costs. Also, we analyze the real transportation networks of the cities of Atlanta, Boston, and Toronto using our theoretical framework and find that they are farther away from their optimal shapes as traffic congestion increases.
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Affiliation(s)
- Siddharth Patwardhan
- Center for Complex Networks and Systems Research, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47408, USA
| | - Marc Barthelemy
- Université Paris-Saclay, CNRS, CEA, Institut de Physique Théorique, 91191, Gif-sur-Yvette, France.
- Centre d'Analyse et de Mathématique Sociales (CNRS/EHESS) 54 Avenue de Raspail, 75006, Paris, France.
| | - Şirag Erkol
- Center for Science of Science and Innovation, Kellogg School of Management, Northwestern University, Evanston, IL, 60208, USA
| | - Santo Fortunato
- Center for Complex Networks and Systems Research, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47408, USA.
| | - Filippo Radicchi
- Center for Complex Networks and Systems Research, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47408, USA.
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5
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Cogoni M, Busonera G. Predicting network congestion by extending betweenness centrality to interacting agents. Phys Rev E 2024; 109:044302. [PMID: 38755873 DOI: 10.1103/physreve.109.044302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 01/22/2024] [Indexed: 05/18/2024]
Abstract
We present a simple model to predict network activity at the edge level by extending a known approximation method to compute betweenness centrality with a repulsive mechanism to prevent unphysical densities. By taking into account the strong interaction effects often observed in real phenomena, we aim to obtain an improved measure of edge usage during rush hours as traffic congestion patterns emerge in urban networks. In this approach, the network is iteratively populated by agents following dynamically evolving fastest paths who are progressively attracted towards uncongested parts of the network as the global traffic volume increases. Following the transition of the network state from empty to saturated, we study the emergence of congestion and the progressive disruption of global connectivity due to a relatively small fraction of crowded edges. We assess the predictive power of our model by comparing the speed distribution against a large experimental data set for the London area with remarkable results, which also translate into a qualitative similarity of the congestion maps. Also, percolation analysis confirms the quantitative agreement of the model with the real data for London. We perform simulations for seven other topologically different cities to obtain the Fisher critical exponent τ that shows no common functional dependence on the traffic level. The critical exponent γ, studied to assess the power-law decay of spatial correlation, is found to be inversely proportional to the number of vehicles for both real and simulated traffic. This simulation approach seems particularly fit to describe qualitative and quantitative properties of the network loading process, culminating in peak-hour congestion, by using only topological and geographical network features.
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Affiliation(s)
- Marco Cogoni
- CRS4 Center for Advanced Studies, Research and Development in Sardinia - Via Ampere 2, 09134 Cagliari (CA) Italy
| | - Giovanni Busonera
- CRS4 Center for Advanced Studies, Research and Development in Sardinia - Via Ampere 2, 09134 Cagliari (CA) Italy
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6
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Yang S, Sun X, Jin L, Zhang M. Inferring language dispersal patterns with velocity field estimation. Nat Commun 2024; 15:190. [PMID: 38167834 PMCID: PMC10761963 DOI: 10.1038/s41467-023-44430-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
Reconstructing the spatial evolution of languages can deepen our understanding of the demic diffusion and cultural spread. However, the phylogeographic approach that is frequently used to infer language dispersal patterns has limitations, primarily because the phylogenetic tree cannot fully explain the language evolution induced by the horizontal contact among languages, such as borrowing and areal diffusion. Here, we introduce the language velocity field estimation, which does not rely on the phylogenetic tree, to infer language dispersal trajectories and centre. Its effectiveness and robustness are verified through both simulated and empirical validations. Using language velocity field estimation, we infer the dispersal patterns of four agricultural language families and groups, encompassing approximately 700 language samples. Our results show that the dispersal trajectories of these languages are primarily compatible with population movement routes inferred from ancient DNA and archaeological materials, and their dispersal centres are geographically proximate to ancient homelands of agricultural or Neolithic cultures. Our findings highlight that the agricultural languages dispersed alongside the demic diffusions and cultural spreads during the past 10,000 years. We expect that language velocity field estimation could aid the spatial analysis of language evolution and further branch out into the studies of demographic and cultural dynamics.
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Affiliation(s)
- Sizhe Yang
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, 200438, China
| | - Xiaoru Sun
- Human Phenome Institute, Fudan University, Shanghai, 200438, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai, 200438, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, 200438, China.
- Human Phenome Institute, Fudan University, Shanghai, 200438, China.
| | - Menghan Zhang
- Institute of Modern Languages and Linguistics, Fudan University, Shanghai, 200433, China.
- Research Institute of Intelligent Complex Systems, Fudan University, Shanghai, 200433, China.
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7
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Luca M, Campedelli GM, Centellegher S, Tizzoni M, Lepri B. Crime, inequality and public health: a survey of emerging trends in urban data science. Front Big Data 2023; 6:1124526. [PMID: 37303974 PMCID: PMC10248183 DOI: 10.3389/fdata.2023.1124526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 05/10/2023] [Indexed: 06/13/2023] Open
Abstract
Urban agglomerations are constantly and rapidly evolving ecosystems, with globalization and increasing urbanization posing new challenges in sustainable urban development well summarized in the United Nations' Sustainable Development Goals (SDGs). The advent of the digital age generated by modern alternative data sources provides new tools to tackle these challenges with spatio-temporal scales that were previously unavailable with census statistics. In this review, we present how new digital data sources are employed to provide data-driven insights to study and track (i) urban crime and public safety; (ii) socioeconomic inequalities and segregation; and (iii) public health, with a particular focus on the city scale.
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Affiliation(s)
- Massimiliano Luca
- Mobile and Social Computing Lab, Bruno Kessler Foundation, Trento, Italy
- Faculty of Computer Science, Free University of Bolzano, Bolzano, Italy
| | | | | | - Michele Tizzoni
- Department of Sociology and Social Research, University of Trento, Trento, Italy
| | - Bruno Lepri
- Mobile and Social Computing Lab, Bruno Kessler Foundation, Trento, Italy
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8
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Yang J, Shi Y, Zheng Y, Zhang Z. The spatiotemporal prediction method of urban population density distribution through behaviour environment interaction agent model. Sci Rep 2023; 13:5821. [PMID: 37037827 PMCID: PMC10086058 DOI: 10.1038/s41598-023-32529-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 03/29/2023] [Indexed: 04/12/2023] Open
Abstract
Based on the interrelationship between the built environment and spatial-temporal distribution of population density, this paper proposes a method to predict the spatial-temporal distribution of urban population density using the depth residual network model (ResNet) of neural network. This study used the time-sharing data of mobile phone users provided by the China Mobile Communications Corporation to predict the time-space sequence of the steady-state distribution of population density. Firstly, 40 prediction databases were constructed according to the characteristics of built environment and the spatial-temporal distribution of population density. Thereafter, the depth residual model ResNet was used as the basic framework to construct the behaviour-environment agent model (BEM) for model training and prediction. Finally, the average percentage error index was used to evaluate the prediction results. The results revealed that the accuracy rate of prediction results reached 76.92% in the central urban area of the verification case. The proposed method can be applied to prevent urban public safety incidents and alleviate pandemics. Moreover, this method can be practically applied to enable the construction of a "smart city" for improving the efficient allocation of urban resources and traffic mobility.
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Affiliation(s)
- Junyan Yang
- School of Architecture, Southeast University, 2nd Sipailou Street, Xuanwu District, Nanjing, 210096, China.
- Southeast University Smart City Institute, Nanjing, China.
| | - Yi Shi
- School of Architecture, Southeast University, 2nd Sipailou Street, Xuanwu District, Nanjing, 210096, China
| | - Yi Zheng
- School of Architecture, Southeast University, 2nd Sipailou Street, Xuanwu District, Nanjing, 210096, China
- Research Centre for Chinese Nation Visual Image, Southeast University, Nanjing, China
| | - Zhonghu Zhang
- School of Architecture, Southeast University, 2nd Sipailou Street, Xuanwu District, Nanjing, 210096, China
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9
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Cabrera-Arnau C, Zhong C, Batty M, Silva R, Kang SM. Inferring urban polycentricity from the variability in human mobility patterns. Sci Rep 2023; 13:5751. [PMID: 37029277 PMCID: PMC10082211 DOI: 10.1038/s41598-023-33003-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 04/05/2023] [Indexed: 04/09/2023] Open
Abstract
The polycentric city model has gained popularity in spatial planning policy, since it is believed to overcome some of the problems often present in monocentric metropolises, ranging from congestion to difficult accessibility to jobs and services. However, the concept 'polycentric city' has a fuzzy definition and as a result, the extent to which a city is polycentric cannot be easily determined. Here, we leverage the fine spatio-temporal resolution of smart travel card data to infer urban polycentricity by examining how a city departs from a well-defined monocentric model. In particular, we analyse the human movements that arise as a result of sophisticated forms of urban structure by introducing a novel probabilistic approach which captures the complexity of these human movements. We focus on London (UK) and Seoul (South Korea) as our two case studies, and we specifically find evidence that London displays a higher degree of monocentricity than Seoul, suggesting that Seoul is likely to be more polycentric than London.
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Affiliation(s)
- Carmen Cabrera-Arnau
- Department of Geography and Planning, University of Liverpool, Liverpool, UK.
- Centre for Advanced Spatial Analysis (CASA), University College London, London, UK.
| | - Chen Zhong
- Centre for Advanced Spatial Analysis (CASA), University College London, London, UK
| | - Michael Batty
- Centre for Advanced Spatial Analysis (CASA), University College London, London, UK
| | - Ricardo Silva
- Department of Statistical Science, University College London, London, UK
| | - Soong Moon Kang
- School of Management, University College London, London, WC1E 6BT, UK
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10
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Arcaute E, Ramasco JJ. Recent advances in urban system science: Models and data. PLoS One 2022; 17:e0272863. [PMID: 35976953 PMCID: PMC9384974 DOI: 10.1371/journal.pone.0272863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Cities are characterized by the presence of a dense population with a high potential for interactions between individuals of diverse backgrounds. They appear in parallel to the Neolithic revolution a few millennia ago. The advantages brought in terms of agglomeration for economy, innovation, social and cultural advancements have kept them as a major landmark in recent human history. There are many different aspects to study in urban systems from a scientific point of view, one can concentrate in demography and population evolution, mobility, economic output, land use and urban planning, home accessibility and real estate market, energy and water consumption, waste processing, health, education, integration of minorities, just to name a few. In the last decade, the introduction of communication and information technologies have enormously facilitated the collection of datasets on these and other questions, making possible a more quantitative approach to city science. All these topics have been addressed in many works in the literature, and we do not intend to offer here a systematic review. Instead, we will only provide a brief taste of some of these above-mentioned aspects, which could serve as an introduction to the collection ‘Cities as Complex Systems’. Such a non-systematic view will lead us to leave outside many relevant papers, and for this we must apologise.
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Affiliation(s)
- Elsa Arcaute
- Centre for Advanced Spatial Analysis, University College London, London, United Kingdom
- * E-mail: (EA); (JJR)
| | - José J. Ramasco
- Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), Campus UIB, Palma de Mallorca, Spain
- * E-mail: (EA); (JJR)
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11
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Urban spatial structures from human flow by Hodge-Kodaira decomposition. Sci Rep 2022; 12:11258. [PMID: 35789196 PMCID: PMC9252991 DOI: 10.1038/s41598-022-15512-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 06/24/2022] [Indexed: 11/10/2022] Open
Abstract
Human flow in cities indicates social activity and can reveal urban spatial structures based on human behaviours for relevant applications. Scalar potential is a mathematical concept that, when properly applied, can provide an intuitive view of human flow. However, the definition of such a potential in terms of the origin-destination flow matrix and its feasibility remain unresolved. In this case, we use Hodge–Kodaira decomposition, which uniquely decomposes a matrix into a potential-driven (gradient) flow and a curl flow. We depict the potential landscapes in cities resulting from commuting flow and reveal how the landscapes have either changed or remained unchanged by years or methods of transportation. We then determine how well the commuting flow is described by the potential, by evaluating the percentage of the gradient component for metropolitan areas in the USA and show that the gradient component is almost 100% in several areas; in other areas, however, the curl component is dominant, indicating the importance of circular flow along with triangles of places. The potential landscape provides an easy-to-use visualisation tool for showing the attractive places of human flow and will help in a variety of applications such as commerce, urban design, and epidemic spreading.
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12
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Shida Y, Ozaki J, Takayasu H, Takayasu M. Potential fields and fluctuation-dissipation relations derived from human flow in urban areas modeled by a network of electric circuits. Sci Rep 2022; 12:9918. [PMID: 35705582 PMCID: PMC9200729 DOI: 10.1038/s41598-022-13789-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 05/11/2022] [Indexed: 01/27/2023] Open
Abstract
Owing to the big data the extension of physical laws on nonmaterial has seen numerous successes, and human mobility is one of the scientific frontier topics. Recent GPS technology has made it possible to trace detailed trajectories of millions of people, macroscopic approaches such as the gravity law for human flow between cities and microscopic approaches of individual origin-destination distributions are attracting much attention. However, we need a more general basic model with wide applicability to realize traffic forecasting and urban planning of metropolis fully utilizing the GPS data. Here, based on a novel idea of treating moving people as charged particles, we introduce a method to map macroscopic human flows into currents on an imaginary electric circuit defined over a metropolitan area. Conductance is found to be nearly proportional to the maximum current in each location and synchronized human flows in the morning and evening are well described by the temporal changes of electric potential. Surprisingly, the famous fluctuation-dissipation theorem holds, namely, the variances of currents are proportional to the conductivities akin to an ordinary material.
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Affiliation(s)
- Yohei Shida
- grid.32197.3e0000 0001 2179 2105Department of Mathematical and Computing Science, School of Computing, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, 226-8503 Japan
| | - Jun’ichi Ozaki
- grid.32197.3e0000 0001 2179 2105Institute of Innovative Research, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, 226-8503 Japan
| | - Hideki Takayasu
- grid.32197.3e0000 0001 2179 2105Institute of Innovative Research, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, 226-8503 Japan ,grid.452725.30000 0004 1764 0071Sony Computer Science Laboratories, 3-14-13 Higashi-Gotanda, Shinagawa-ku, Tokyo, Japan
| | - Misako Takayasu
- grid.32197.3e0000 0001 2179 2105Department of Mathematical and Computing Science, School of Computing, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, 226-8503 Japan ,grid.32197.3e0000 0001 2179 2105Institute of Innovative Research, Tokyo Institute of Technology, 4259 Nagatsuta-cho, Midori-ku, Yokohama, 226-8503 Japan
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13
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Wolf H, Storch DM, Timme M, Schröder M. Spontaneous symmetry breaking in ride-sharing adoption dynamics. Phys Rev E 2022; 105:044309. [PMID: 35590645 DOI: 10.1103/physreve.105.044309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 03/16/2022] [Indexed: 06/15/2023]
Abstract
Symmetry breaking ubiquitously occurs across complex systems, from phase transition in statistical physics to self-organized lane formation in pedestrian dynamics. Here, we uncover spontaneous symmetry breaking in a simple model of ride-sharing adoption. We analyze how collective interactions among ride-sharing users to avoid detours in shared rides give rise to spontaneous symmetry breaking and pattern formation in the adoption dynamics. These dynamics result in bistability of high homogeneous and partial heterogeneous adoption states, potentially limiting the population-wide adoption of ride sharing. Our results provide a framework to understand real-world adoption patterns of ride sharing in complex urban settings and support the (re)design of ride-sharing services and incentives for sustainable shared mobility.
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Affiliation(s)
- Henrik Wolf
- Chair for Network Dynamics, Institute for Theoretical Physics and Center for Advancing Electronics Dresden (cfaed), Technische Universität Dresden, 01062 Dresden, Germany
| | - David-Maximilian Storch
- Chair for Network Dynamics, Institute for Theoretical Physics and Center for Advancing Electronics Dresden (cfaed), Technische Universität Dresden, 01062 Dresden, Germany
| | - Marc Timme
- Chair for Network Dynamics, Institute for Theoretical Physics and Center for Advancing Electronics Dresden (cfaed), Technische Universität Dresden, 01062 Dresden, Germany
| | - Malte Schröder
- Chair for Network Dynamics, Institute for Theoretical Physics and Center for Advancing Electronics Dresden (cfaed), Technische Universität Dresden, 01062 Dresden, Germany
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14
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Salazar Coariti AC, Fabien MS, Guzman J, McGuire JA, De Vita R, Toussaint KC. Fluid mechanics approach to analyzing collagen fiber organization. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:016503. [PMID: 35102730 PMCID: PMC8802803 DOI: 10.1117/1.jbo.27.1.016503] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 01/03/2022] [Indexed: 06/14/2023]
Abstract
SIGNIFICANCE The spatial organization of collagen fibers has been used as a biomarker for assessing injury and disease progression. However, quantifying this organization for complex structures is challenging. AIM To quantify and classify complex collagen fiber organizations. APPROACH Using quantitative second-harmonic generation (SHG) microscopy, we show that collagen-fiber orientation can be viewed as pseudovector fields. Subsequently, we analyze them using fluid mechanic metrics, such as energy U, enstrophy E, and tortuosity τ. RESULTS We show that metrics used in fluid mechanics for analyzing fluid flow can be adapted to analyze complex collagen fiber organization. As examples, we consider SHG images of collagenous tissue for straight, wavy, and circular fiber structures. CONCLUSIONS The results of this study show the utility of the chosen metrics to distinguish diverse and complex collagen organizations. We find that the distribution of values for E and U increases with collagen fiber disorganization, where they divide between low and high values corresponding to uniformly aligned fibers and disorganized collagen fibers, respectively. We also confirm that the values of τ cluster around 1 when the fibers are straight, and the range increases up to 1.5 when wavier fibers are present.
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Affiliation(s)
| | - Maurice S. Fabien
- Brown University, Division of Applied Mathematics, Providence, Rhode Island, United States
| | - Johnny Guzman
- Brown University, Division of Applied Mathematics, Providence, Rhode Island, United States
| | - Jeffrey A. McGuire
- Virginia Tech, Soft Tissue Research: Experiments, Theory, and Computations by Hokies (STRETCH) Lab, Department of Biomedical Engineering and Mechanics, Blacksburg, Virginia, United States
| | - Raffaella De Vita
- Virginia Tech, Soft Tissue Research: Experiments, Theory, and Computations by Hokies (STRETCH) Lab, Department of Biomedical Engineering and Mechanics, Blacksburg, Virginia, United States
| | - Kimani C. Toussaint
- Brown University, PROBE Lab, School of Engineering, Providence, Rhode Island, United States
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15
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Abstract
Human mobility impacts many aspects of a city, from its spatial structure1-3 to its response to an epidemic4-7. It is also ultimately key to social interactions8, innovation9,10 and productivity11. However, our quantitative understanding of the aggregate movements of individuals remains incomplete. Existing models-such as the gravity law12,13 or the radiation model14-concentrate on the purely spatial dependence of mobility flows and do not capture the varying frequencies of recurrent visits to the same locations. Here we reveal a simple and robust scaling law that captures the temporal and spatial spectrum of population movement on the basis of large-scale mobility data from diverse cities around the globe. According to this law, the number of visitors to any location decreases as the inverse square of the product of their visiting frequency and travel distance. We further show that the spatio-temporal flows to different locations give rise to prominent spatial clusters with an area distribution that follows Zipf's law15. Finally, we build an individual mobility model based on exploration and preferential return to provide a mechanistic explanation for the discovered scaling law and the emerging spatial structure. Our findings corroborate long-standing conjectures in human geography (such as central place theory16 and Weber's theory of emergent optimality10) and allow for predictions of recurrent flows, providing a basis for applications in urban planning, traffic engineering and the mitigation of epidemic diseases.
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16
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Li Q, Bessell L, Xiao X, Fan C, Gao X, Mostafavi A. Disparate patterns of movements and visits to points of interest located in urban hotspots across US metropolitan cities during COVID-19. ROYAL SOCIETY OPEN SCIENCE 2021; 8:201209. [PMID: 33614069 PMCID: PMC7890478 DOI: 10.1098/rsos.201209] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 11/25/2020] [Indexed: 05/08/2023]
Abstract
We examined the effect of social distancing on changes in visits to urban hotspot points of interest. In a pandemic situation, urban hotspots could be potential superspreader areas as visits to urban hotspots can increase the risk of contact and transmission of a disease among a population. We mapped census-block-group to point-of-interest (POI) movement networks in 16 cities in the United States. We adopted a modified coarse-grain approach to examine patterns of visits to POIs among hotspots and non-hotspots from January to May 2020. Also, we conducted chi-square tests to identify POIs with significant flux-in changes during the analysis period. The results showed disparate patterns across cities in terms of reduction in hotspot POI visitors. Sixteen cities were divided into two categories using a time series clustering method. In one category, which includes the cities of San Francisco, Seattle and Chicago, we observed a considerable decrease in hotspot POI visitors, while in another category, including the cities of Austin, Houston and San Diego, the visitors to hotspots did not greatly decrease. While all the cities exhibited overall decreased visitors to POIs, one category maintained the proportion of visitors to hotspot POIs. The proportion of visitors to some POIs (e.g. restaurants) remained stable during the social distancing period, while some POIs had an increased proportion of visitors (e.g. grocery stores). We also identified POIs with significant flux-in changes, indicating that related businesses were greatly affected by social distancing. The study was limited to 16 metropolitan cities in the United States. The proposed methodology could be applied to digital trace data in other cities and countries to study the patterns of movements to POIs during the COVID-19 pandemic.
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Affiliation(s)
- Qingchun Li
- Zachry Department of Civil and Environmental Engineering, Texas A&M University, 199 Spence Street, College Station, TX 77843-3112, USA
- Author for correspondence: Qingchun Li e-mail:
| | - Liam Bessell
- Department of Computer Science and Engineering, Texas A&M University, 199 Spence Street, College Station, TX 77843-3112, USA
| | - Xin Xiao
- Department of Computer Science and Engineering, Texas A&M University, 199 Spence Street, College Station, TX 77843-3112, USA
| | - Chao Fan
- Zachry Department of Civil and Environmental Engineering, Texas A&M University, 199 Spence Street, College Station, TX 77843-3112, USA
| | - Xinyu Gao
- Zachry Department of Civil and Environmental Engineering, Texas A&M University, 199 Spence Street, College Station, TX 77843-3112, USA
| | - Ali Mostafavi
- Zachry Department of Civil and Environmental Engineering, Texas A&M University, 199 Spence Street, College Station, TX 77843-3112, USA
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17
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Shida Y, Takayasu H, Havlin S, Takayasu M. Universal scaling laws of collective human flow patterns in urban regions. Sci Rep 2020; 10:21405. [PMID: 33293581 PMCID: PMC7722863 DOI: 10.1038/s41598-020-77163-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 10/29/2020] [Indexed: 11/09/2022] Open
Abstract
Detail observation of human locations became available recently by the development of information technology such as mobile phones with GPS (Global Positioning System). We analyzed temporal changes of global human flow patterns in urban regions based on mobile phones' GPS data in 9 large cities in Japan. By applying a new concept of drainage basins in analogous to river flow patterns, we discovered several universal scaling relations. These include, the number of moving people in a drainage basin of diameter L is proportional to [Formula: see text] in the morning rush hour, which is surprisingly different from reasonable intuition of proportionality to the 2 dimensional area, [Formula: see text]. We show that this unexpected 3 dimensional feature is related to the strong attraction of the city center to become a 3 dimensional structure due skyscrapers.
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Affiliation(s)
- Yohei Shida
- Department of Mathematical and Computing Science, School of Computing, Tokyo Institute of Technology, Yokohama, 226-8502, Japan
| | - Hideki Takayasu
- Sony Computer Science Laboratories, Tokyo, 141-0022, Japan.,Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, 226-8502, Japan
| | - Shlomo Havlin
- Department of Physics, Bar-Ilan University, Ramat-Gan, 52900, Israel.,Tokyo Tech World Research Hub Initiative (WRHI), Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, 226-8502, Japan
| | - Misako Takayasu
- Department of Mathematical and Computing Science, School of Computing, Tokyo Institute of Technology, Yokohama, 226-8502, Japan. .,Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, 226-8502, Japan.
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18
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Dong L, Huang Z, Zhang J, Liu Y. Understanding the mesoscopic scaling patterns within cities. Sci Rep 2020; 10:21201. [PMID: 33273607 PMCID: PMC7712915 DOI: 10.1038/s41598-020-78135-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Accepted: 11/20/2020] [Indexed: 11/10/2022] Open
Abstract
Understanding quantitative relationships between urban elements is crucial for a wide range of applications. The observation at the macroscopic level demonstrates that the aggregated urban quantities (e.g., gross domestic product) scale systematically with population sizes across cities, also known as urban scaling laws. However, at the mesoscopic level, we lack an understanding of whether the simple scaling relationship holds within cities, which is a fundamental question regarding the spatial origin of scaling in urban systems. Here, by analyzing four extensive datasets covering millions of mobile phone users and urban facilities, we investigate the scaling phenomena within cities. We find that the mesoscopic infrastructure volume and socioeconomic activity scale sub- and super-linearly with the active population, respectively. For a same scaling phenomenon, however, the exponents vary in cities of similar population sizes. To explain these empirical observations, we propose a conceptual framework by considering the heterogeneous distributions of population and facilities, and the spatial interactions between them. Analytical and numerical results suggest that, despite the large number of complexities that influence urban activities, the simple interaction rules can effectively explain the observed regularity and heterogeneity in scaling behaviors within cities.
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Affiliation(s)
- Lei Dong
- Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, 100871, China.,Senseable City Lab, Department of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Zhou Huang
- Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, 100871, China
| | - Jiang Zhang
- School of System Science, Beijing Normal University, Beijing, 100875, China
| | - Yu Liu
- Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, 100871, China.
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19
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Mazzoli M, Diechtiareff B, Tugores A, Wives W, Adler N, Colet P, Ramasco JJ. Migrant mobility flows characterized with digital data. PLoS One 2020; 15:e0230264. [PMID: 32203523 PMCID: PMC7089540 DOI: 10.1371/journal.pone.0230264] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 02/25/2020] [Indexed: 11/18/2022] Open
Abstract
Monitoring migration flows is crucial to respond to humanitarian crisis and to design efficient policies. This information usually comes from surveys and border controls, but timely accessibility and methodological concerns reduce its usefulness. Here, we propose a method to detect migration flows worldwide using geolocated Twitter data. We focus on the migration crisis in Venezuela and show that the calculated flows are consistent with official statistics at country level. Our method is versatile and far-reaching, as it can be used to study different features of migration as preferred routes, settlement areas, mobility through several countries, spatial integration in cities, etc. It provides finer geographical and temporal resolutions, allowing the exploration of issues not contemplated in official records. It is our hope that these new sources of information can complement official ones, helping authorities and humanitarian organizations to better assess when and where to intervene on the ground.
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Affiliation(s)
- Mattia Mazzoli
- Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), Campus UIB, Palma de Mallorca, Spain
- * E-mail: (MM); (JJR)
| | | | - Antònia Tugores
- Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), Campus UIB, Palma de Mallorca, Spain
| | - Willian Wives
- United Nations Children’s Fund -UNICEF Brasília, DF, Brazil
| | - Natalia Adler
- United Nations Children’s Fund -UNICEF 3 UN Plaza, New York, NY, United States of America
| | - Pere Colet
- Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), Campus UIB, Palma de Mallorca, Spain
| | - José J. Ramasco
- Instituto de Física Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB), Campus UIB, Palma de Mallorca, Spain
- * E-mail: (MM); (JJR)
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