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Han Z, Liu L, Wang X, Hao Y, Zheng H, Tang S, Zheng Z. Probabilistic activity driven model of temporal simplicial networks and its application on higher-order dynamics. CHAOS (WOODBURY, N.Y.) 2024; 34:023137. [PMID: 38407398 DOI: 10.1063/5.0167123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 01/27/2024] [Indexed: 02/27/2024]
Abstract
Network modeling characterizes the underlying principles of structural properties and is of vital significance for simulating dynamical processes in real world. However, bridging structure and dynamics is always challenging due to the multiple complexities in real systems. Here, through introducing the individual's activity rate and the possibility of group interaction, we propose a probabilistic activity-driven (PAD) model that could generate temporal higher-order networks with both power-law and high-clustering characteristics, which successfully links the two most critical structural features and a basic dynamical pattern in extensive complex systems. Surprisingly, the power-law exponents and the clustering coefficients of the aggregated PAD network could be tuned in a wide range by altering a set of model parameters. We further provide an approximation algorithm to select the proper parameters that can generate networks with given structural properties, the effectiveness of which is verified by fitting various real-world networks. Finally, we construct the co-evolution framework of the PAD model and higher-order contagion dynamics and derive the critical conditions for phase transition and bistable phenomenon using theoretical and numerical methods. Results show that tendency of participating in higher-order interactions can promote the emergence of bistability but delay the outbreak under heterogeneous activity rates. Our model provides a basic tool to reproduce complex structural properties and to study the widespread higher-order dynamics, which has great potential for applications across fields.
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Affiliation(s)
- Zhihao Han
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China
- Key laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing 100191, China
| | - Longzhao Liu
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China
- Key laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing 100191, China
- State Key Lab of Software Development Environment (NLSDE), Beihang University, Beijing 100191, China
- Zhongguancun Laboratory, Beijing 100094, People's Republic of China
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China
- PengCheng Laboratory, Shenzhen 518055, China
| | - Xin Wang
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China
- Key laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing 100191, China
- State Key Lab of Software Development Environment (NLSDE), Beihang University, Beijing 100191, China
- Zhongguancun Laboratory, Beijing 100094, People's Republic of China
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China
- PengCheng Laboratory, Shenzhen 518055, China
| | - Yajing Hao
- Key laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing 100191, China
- School of Mathematical Sciences, Beihang University, Beijing 100191, China
| | - Hongwei Zheng
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China
- Beijing Academy of Blockchain and Edge Computing (BABEC), Beijing 100085, China
| | - Shaoting Tang
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China
- Key laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing 100191, China
- State Key Lab of Software Development Environment (NLSDE), Beihang University, Beijing 100191, China
- Zhongguancun Laboratory, Beijing 100094, People's Republic of China
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China
- PengCheng Laboratory, Shenzhen 518055, China
- Institute of Medical Artificial Intelligence, Binzhou Medical University, Yantai 264003, China
- School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China
| | - Zhiming Zheng
- Institute of Artificial Intelligence, Beihang University, Beijing 100191, China
- Key laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing 100191, China
- State Key Lab of Software Development Environment (NLSDE), Beihang University, Beijing 100191, China
- Zhongguancun Laboratory, Beijing 100094, People's Republic of China
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing 100191, China
- PengCheng Laboratory, Shenzhen 518055, China
- Institute of Medical Artificial Intelligence, Binzhou Medical University, Yantai 264003, China
- School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China
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2
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Dutta S, Verma UK, Jalan S. Solitary death in coupled limit cycle oscillators with higher-order interactions. Phys Rev E 2023; 108:L062201. [PMID: 38243514 DOI: 10.1103/physreve.108.l062201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 11/16/2023] [Indexed: 01/21/2024]
Abstract
Coupled limit cycle oscillators with pairwise interactions are known to depict phase transitions from an oscillatory state to amplitude or oscillation death. This Research Letter introduces a scheme to incorporate higher-order interactions which cannot be decomposed into pairwise interactions and investigates the dynamical evolution of Stuart-Landau oscillators under the impression of such a coupling. We discover an oscillator death state through a first-order (explosive) phase transition in which a single, coupling-dependent stable death state away from the origin exists in isolation without being accompanied by any other stable state usually existing for pairwise couplings. We call such a state a solitary death state. Contrary to widespread subcritical Hopf bifurcation, here we report homoclinic bifurcation as an origin of the explosive death state. Moreover, this explosive transition to the death state is preceded by a surge in amplitude and followed by a revival of the oscillations. The analytical value of the critical coupling strength for the solitary death state agrees with the simulation results. Finally, we point out the resemblance of the results with different dynamical states associated with epileptic seizures.
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Affiliation(s)
- Subhasanket Dutta
- Complex Systems Lab, Department of Physics, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore-453552, India
| | - Umesh Kumar Verma
- Complex Systems Lab, Department of Physics, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore-453552, India
| | - Sarika Jalan
- Complex Systems Lab, Department of Physics, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore-453552, India
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Guo Y, Wu F, Yang F, Ma J. Physical approach of a neuron model with memristive membranes. CHAOS (WOODBURY, N.Y.) 2023; 33:113106. [PMID: 37909904 DOI: 10.1063/5.0170121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 10/13/2023] [Indexed: 11/03/2023]
Abstract
The membrane potential of a neuron is mainly controlled by the gradient distribution of electromagnetic field and concentration diversity between intracellular and extracellular ions. Without considering the thickness and material property, the electric characteristic of cell membrane is described by a capacitive variable and output voltage in an equivalent neural circuit. The flexible property of cell membrane enables controllability of endomembrane and outer membrane, and the capacitive properties and gradient field can be approached by double membranes connected by a memristor in an equivalent neural circuit. In this work, two capacitors connected by a memristor are used to mimic the physical property of two-layer membranes, and an inductive channel is added to the neural circuit. A biophysical neuron is obtained and the energy characteristic, dynamics, self-adaption is discussed, respectively. Coherence resonance and mode selection in adaptive way are detected under noisy excitation. The distribution of average energy function is effective to predict the appearance of coherence resonance. An adaptive law is proposed to control the capacitive parameters, and the controllability of cell membrane under external stimulus can be explained in theoretical way. The neuron with memristive membranes explains the self-adaptive mechanism of parameter changes and mode transition from energy viewpoint.
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Affiliation(s)
- Yitong Guo
- College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China
| | - Fuqiang Wu
- School of Mathematics and Statistics, Ningxia University, Yinchuan 750021, China
| | - Feifei Yang
- College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China
| | - Jun Ma
- College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China
- Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China
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4
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Ren X, Lei Y, Grebogi C, Baptista MS. The complementary contribution of each order topology into the synchronization of multi-order networks. CHAOS (WOODBURY, N.Y.) 2023; 33:111101. [PMID: 37909900 DOI: 10.1063/5.0177687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 10/12/2023] [Indexed: 11/03/2023]
Abstract
Higher-order interactions improve our capability to model real-world complex systems ranging from physics and neuroscience to economics and social sciences. There is great interest nowadays in understanding the contribution of higher-order terms to the collective behavior of the network. In this work, we investigate the stability of complete synchronization of complex networks with higher-order structures. We demonstrate that the synchronization level of a network composed of nodes interacting simultaneously via multiple orders is maintained regardless of the intensity of coupling strength across different orders. We articulate that lower-order and higher-order topologies work together complementarily to provide the optimal stable configuration, challenging previous conclusions that higher-order interactions promote the stability of synchronization. Furthermore, we find that simply adding higher-order interactions based on existing connections, as in simple complexes, does not have a significant impact on synchronization. The universal applicability of our work lies in the comprehensive analysis of different network topologies, including hypergraphs and simplicial complexes, and the utilization of appropriate rescaling to assess the impact of higher-order interactions on synchronization stability.
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Affiliation(s)
- Xiaomin Ren
- School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Youming Lei
- School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an 710072, China
| | - Celso Grebogi
- Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen AB24 3UE, United Kingdom
| | - Murilo S Baptista
- Institute for Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen AB24 3UE, United Kingdom
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5
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Rathore V, Suman A, Jalan S. Synchronization onset for contrarians with higher-order interactions in multilayer systems. CHAOS (WOODBURY, N.Y.) 2023; 33:091105. [PMID: 37729103 DOI: 10.1063/5.0166627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 08/28/2023] [Indexed: 09/22/2023]
Abstract
We investigate the impact of contrarians (via negative coupling) in multilayer networks of phase oscillators having higher-order interactions. We report that the multilayer framework facilitates synchronization onset in the negative pairwise coupling regime. The multilayering strength governs the onset of synchronization and the nature of the phase transition, whereas the higher-order interactions dictate the backward critical coupling. Specifically, the system does not synchronize below a critical value of the multilayering strength. The analytical calculations using the mean-field Ott-Antonsen approach agree with the simulations. The results presented here may be useful for understanding emergent behaviors in real-world complex systems with contrarians and higher-order interactions, such as the brain and social system.
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Affiliation(s)
- Vasundhara Rathore
- Department of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore 453552, India
| | - Ayushi Suman
- Department of Physics, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore 453552, India
| | - Sarika Jalan
- Department of Biosciences and Biomedical Engineering, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore 453552, India
- Department of Physics, Indian Institute of Technology Indore, Khandwa Road, Simrol, Indore 453552, India
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6
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Dutta S, Mondal A, Kundu P, Khanra P, Pal P, Hens C. Impact of phase lag on synchronization in frustrated Kuramoto model with higher-order interactions. Phys Rev E 2023; 108:034208. [PMID: 37849147 DOI: 10.1103/physreve.108.034208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 08/25/2023] [Indexed: 10/19/2023]
Abstract
The study of first order transition (explosive synchronization) in an ensemble (network) of coupled oscillators has been the topic of paramount interest among the researchers for more than one decade. Several frameworks have been proposed to induce explosive synchronization in a network and it has been reported that phase frustration in a network usually suppresses first order transition in the presence of pairwise interactions among the oscillators. However, on the contrary, by considering networks of phase frustrated coupled oscillators in the presence of higher-order interactions (up to 2-simplexes) we show here, under certain conditions, phase frustration can promote explosive synchronization in a network. A low-dimensional model of the network in the thermodynamic limit is derived using the Ott-Antonsen ansatz to explain this surprising result. Analytical treatment of the low-dimensional model, including bifurcation analysis, explains the apparent counter intuitive result quite clearly.
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Affiliation(s)
- Sangita Dutta
- Department of Mathematics, National Institute of Technology, Durgapur 713209, India
| | - Abhijit Mondal
- Department of Mathematics, National Institute of Technology, Durgapur 713209, India
| | - Prosenjit Kundu
- Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, Gujarat 382007, India
| | - Pitambar Khanra
- Department of Mathematics, State University of New York at Buffalo, Buffalo 14260, USA
| | - Pinaki Pal
- Department of Mathematics, National Institute of Technology, Durgapur 713209, India
| | - Chittaranjan Hens
- Center for Computational Natural Science and Bioinformatics, International Institute of Informational Technology, Gachibowli, Hyderabad 500032, India
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7
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Jaros P, Ghosh S, Dudkowski D, Dana SK, Kapitaniak T. Higher-order interactions in Kuramoto oscillators with inertia. Phys Rev E 2023; 108:024215. [PMID: 37723775 DOI: 10.1103/physreve.108.024215] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 08/01/2023] [Indexed: 09/20/2023]
Abstract
How do higher-order interactions influence the dynamical landscape of a network of the second-order phase oscillators? We address this question using three coupled Kuramoto phase oscillators with inertia under pairwise and higher-order interactions, in search of various collective states, and new states, if any, that show marginal presence or absence under pairwise interactions. We explore this small network for varying phase lag in the coupling and over a range of negative to positive coupling strength of pairwise as well as higher-order or group interactions. In the extended coupling parameter plane of the network we record several well-known states such as synchronization, frequency chimera states, and rotating waves that appear with distinct boundaries. In the parameter space, we also find states generated by the influence of higher-order interactions: The 2+1 antipodal point and the 2+1 phase-locked states. Our results demonstrate the importantance of the choices of the phase lag and the sign of the higher-order coupling strength for the emergent dynamics of the network. We provide analytical support to our numerical results.
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Affiliation(s)
- Patrycja Jaros
- Division of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924 Lodz, Poland
| | - Subrata Ghosh
- Division of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924 Lodz, Poland
- Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Gachibowli, Hyderabad 500032, India
| | - Dawid Dudkowski
- Division of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924 Lodz, Poland
| | - Syamal K Dana
- Division of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924 Lodz, Poland
- Department of Mathematics, National Institute of Technology, Durgapur 713209, India
| | - Tomasz Kapitaniak
- Division of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924 Lodz, Poland
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8
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Ren C, Chen B, Xie F. Identifying Key Factors of Hazardous Materials Transportation Accidents Based on Higher-Order and Multilayer Networks. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1036. [PMID: 37509983 PMCID: PMC10378565 DOI: 10.3390/e25071036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 06/26/2023] [Accepted: 07/07/2023] [Indexed: 07/30/2023]
Abstract
This paper focuses on the application of higher-order and multilayer networks in identifying critical causes and relationships contributing to hazardous materials transportation accidents. There were 792 accidents of hazardous materials transportation that occurred on the road from 2017 to 2021 which have been investigated. By considering time sequence and dependency of causes, the hazardous materials transportation accidents causation network (HMTACN) was described using the higher-order model. To investigate the structure of HMTACN such as the importance of causes and links, HMTACN was divided into three layers using the weighted k-core decomposition: the core layer, the bridge layer and the peripheral layer. Then causes and links were analyzed in detail. It was found that the core layer was tightly connected and supported most of the causal flows of HMTACN. The results showed that causes should be given hierarchical attention. This study provides an innovative method to analyze complicated accidents, which can be used in identifying major causes and links. And this paper brings new ideas about safety network study and extends the applications of complex network theory.
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Affiliation(s)
- Cuiping Ren
- School of Modern Post, Xi'an University of Posts and Telecommunications, Xi'an 710061, China
| | - Bianbian Chen
- School of Modern Post, Xi'an University of Posts and Telecommunications, Xi'an 710061, China
| | - Fengjie Xie
- School of Modern Post, Xi'an University of Posts and Telecommunications, Xi'an 710061, China
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9
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Kaiser D, Patwardhan S, Radicchi F. Multiplex reconstruction with partial information. Phys Rev E 2023; 107:024309. [PMID: 36932554 DOI: 10.1103/physreve.107.024309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 01/26/2023] [Indexed: 06/18/2023]
Abstract
A multiplex is a collection of network layers, each representing a specific type of edges. This appears to be a genuine representation of many real-world systems. However, due to a variety of potential factors, such as limited budget and equipment, or physical impossibility, multiplex data can be difficult to observe directly. Often, only partial information on the layer structure of the system is available, whereas the remaining information is in the form of a single-layer network. In this work we face the problem of reconstructing the hidden multiplex structure of an aggregated network from partial information. We propose an algorithm that leverages the layerwise community structure that can be learned from partial observations to reconstruct the ground-truth topology of the unobserved part of the multiplex. The algorithm is characterized by a computational time that grows linearly with the network size. We perform a systematic study of reconstruction problems for both synthetic and real-world multiplex networks. We show that the ability of the proposed method to solve the reconstruction problem is affected by the heterogeneity of the individual layers and the similarity among the layers. On real-world networks, we observe that the accuracy of the reconstruction saturates quickly as the amount of available information increases. In genetic interaction and scientific collaboration multiplexes, for example, we find that 10% of ground-truth information yields 70% accuracy, while 30% information allows for more than 90% accuracy.
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Affiliation(s)
- Daniel Kaiser
- Center for Complex Networks and Systems Research, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, Indiana 47408, USA
| | - Siddharth Patwardhan
- Center for Complex Networks and Systems Research, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, Indiana 47408, USA
| | - Filippo Radicchi
- Center for Complex Networks and Systems Research, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, Indiana 47408, USA
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10
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Vazquez A. Complex hypergraphs. Phys Rev E 2023; 107:024316. [PMID: 36932522 DOI: 10.1103/physreve.107.024316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 02/15/2023] [Indexed: 06/18/2023]
Abstract
Providing an abstract representation of natural and human complex structures is a challenging problem. Accounting for the system heterogenous components while allowing for analytical tractability is a difficult balance. Here I introduce complex hypergraphs (chygraphs), bringing together concepts from hypergraphs, multilayer networks, simplicial complexes, and hyperstructures. To illustrate the applicability of this combinatorial structure I calculate the component sizes statistics and identify the transition to a giant component. To this end I introduce a vectorization technique that tackles the multilevel nature of chygraphs. I conclude that chygraphs are a unifying representation of complex systems allowing for analytical insight.
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Affiliation(s)
- Alexei Vazquez
- Nodes & Links Ltd, Salisbury House, Station Road, Cambridge CB1 2LA, United Kingdom
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11
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Marra M, Alfano V, Celentano RM. Assessing university-business collaborations for moderate innovators: Implications for university-led innovation policy evaluation. EVALUATION AND PROGRAM PLANNING 2022; 95:102170. [PMID: 36202045 DOI: 10.1016/j.evalprogplan.2022.102170] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Revised: 09/22/2022] [Accepted: 09/22/2022] [Indexed: 06/16/2023]
Abstract
The growing literature on University-Industry Collaborations (UICs) highlights how learning processes get unevenly located in space, within centers of innovative activity, where the local presence of research-oriented universities plays a crucial role. Through a mixed-methods approach, this article explores the firm-level drivers of innovation and the interactions between a sample of companies and the local university in a moderate innovation EU region. Findings highlight that firms' size, sector, leadership's commitment to digitalization, and collaborations with the university explain companies' innovative performance. The article contributes to the university's societal impact assessment and discusses the implications for university-led innovation for Smart Specialization.
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Affiliation(s)
- Mita Marra
- University of Naples "Federico II", Italy.
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12
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Ren C, Chen B, Xie F, Zhao X, Zhang J, Zhou X. Understanding Hazardous Materials Transportation Accidents Based on Higher-Order Network Theory. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:13337. [PMID: 36293920 PMCID: PMC9603339 DOI: 10.3390/ijerph192013337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 10/11/2022] [Accepted: 10/12/2022] [Indexed: 06/16/2023]
Abstract
In hazardous materials transportation systems, accident causation analysis is important to transportation safety. Complex network theory can be effectively used to understand the causal factors of and their relationships within accidents. In this paper, a higher-order network method is proposed to establish a hazardous materials transportation accident causation network (HMTACN), which considers the sequences and dependences of causal factors. The HMTACN is composed of 125 first- and 118 higher-order nodes that represent causes, and 545 directed edges that denote complex relationships among causes. By analyzing topological properties, the results show that the HMTACN has the characteristics of small-world networks and displays the properties of scale-free networks. Additionally, critical causal factors and key relationships of the HMTACN are discovered. Moreover, unsafe tank or valve states are important causal factors; and leakage, roll-over, collision, and fire are most likely to trigger chain reactions. Important higher-order nodes are discovered, which can represent key relationships in the HMTACN. For example, unsafe distance and improper operation usually lead to collision and roll-over. These results of higher-order nodes cannot be found by the traditional Markov network model. This study provides a practical way to extract and construct an accident causation network from numerous accident investigation reports. It also provides insights into safety management of hazardous materials transportation.
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Affiliation(s)
- Cuiping Ren
- School of Modern Posts, Xi’an University of Posts and Telecommunications, Xi’an 710061, China
| | - Bianbian Chen
- School of Modern Posts, Xi’an University of Posts and Telecommunications, Xi’an 710061, China
| | - Fengjie Xie
- School of Modern Posts, Xi’an University of Posts and Telecommunications, Xi’an 710061, China
| | - Xuan Zhao
- Key Laboratory of Transportation Industry of Automotive Transportation Safety Enhancement Technology, Chang’an University, Xi’an 710064, China
| | - Jiaqian Zhang
- School of Modern Posts, Xi’an University of Posts and Telecommunications, Xi’an 710061, China
| | - Xueyan Zhou
- School of Modern Posts, Xi’an University of Posts and Telecommunications, Xi’an 710061, China
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13
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Anwar MS, Ghosh D. Stability of synchronization in simplicial complexes with multiple interaction layers. Phys Rev E 2022; 106:034314. [PMID: 36266849 DOI: 10.1103/physreve.106.034314] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 09/01/2022] [Indexed: 06/16/2023]
Abstract
Understanding how the interplay between higher-order and multilayer structures of interconnections influences the synchronization behaviors of dynamical systems is a feasible problem of interest, with possible application in essential topics such as neuronal dynamics. Here, we provide a comprehensive approach for analyzing the stability of the complete synchronization state in simplicial complexes with numerous interaction layers. We show that the synchronization state exists as an invariant solution and derive the necessary condition for a stable synchronization state in the presence of general coupling functions. It generalizes the well-known master stability function scheme to the higher-order structures with multiple interaction layers. We verify our theoretical results by employing them on networks of paradigmatic Rössler oscillators and Sherman neuronal models, and we demonstrate that the presence of group interactions considerably improves the synchronization phenomenon in the multilayer framework.
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Affiliation(s)
- Md Sayeed Anwar
- Physics and Applied Mathematics Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata 700108, India
| | - Dibakar Ghosh
- Physics and Applied Mathematics Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata 700108, India
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14
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Bibliometric Analysis of Network Pharmacology in Traditional Chinese Medicine. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2022:1583773. [PMID: 35754692 PMCID: PMC9217600 DOI: 10.1155/2022/1583773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 03/06/2022] [Accepted: 04/09/2022] [Indexed: 11/17/2022]
Abstract
Aim We evaluated the developmental process, research status, and existing challenges of network pharmacology. Moreover, we elucidated the corresponding solutions to improve and develop network pharmacology. Methods Research data for the current study were retrieved from the Web of Science. The developmental process of network pharmacology was analyzed using HisCite, whereas cooccurrence analysis of countries, institutions, keywords, and references in literature was conducted using CiteSpace. Results In literature, there was a trend of annual increase of studies on network pharmacology and China was found to be the country with the most published literature on network pharmacology. The main publishing research institutions were universities of traditional Chinese medicine (TCM). The keywords with more research frequency were TCM, mechanisms, molecular docking, and quercetin, among others. Conclusion Currently, studies on network pharmacology are mainly associated with the exploration of action mechanisms of TCM. The main active ingredient in many Chinese medicines is quercetin. This ingredient may lead to deviation of research results, inability to truly analyze active ingredients, and even mislead the research direction of TCM. Such deviation may be because the database fails to reflect the content and composition changes of Chinese medicinal components. The database does not account for interactions among components, targets, and diseases, and it ignores the different pathological states of the disease. Therefore, network pharmacology should be improved from the databases and research methods.
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15
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Anwar MS, Ghosh D. Intralayer and interlayer synchronization in multiplex network with higher-order interactions. CHAOS (WOODBURY, N.Y.) 2022; 32:033125. [PMID: 35364852 DOI: 10.1063/5.0074641] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Accepted: 03/03/2022] [Indexed: 06/14/2023]
Abstract
Recent developments in complex systems have witnessed that many real-world scenarios, successfully represented as networks, are not always restricted to binary interactions but often include higher-order interactions among the nodes. These beyond pairwise interactions are preferably modeled by hypergraphs, where hyperedges represent higher-order interactions between a set of nodes. In this work, we consider a multiplex network where the intralayer connections are represented by hypergraphs, called the multiplex hypergraph. The hypergraph is constructed by mapping the maximal cliques of a scale-free network to hyperedges of suitable sizes. We investigate the intralayer and interlayer synchronizations of such multiplex structures. Our study unveils that the intralayer synchronization appreciably enhances when a higher-order structure is taken into consideration in spite of only pairwise connections. We derive the necessary condition for stable synchronization states by the master stability function approach, which perfectly agrees with the numerical results. We also explore the robustness of interlayer synchronization and find that for the multiplex structures with many-body interaction, the interlayer synchronization is more persistent than the multiplex networks with solely pairwise interaction.
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Affiliation(s)
- Md Sayeed Anwar
- Physics and Applied Mathematics Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata 700108, India
| | - Dibakar Ghosh
- Physics and Applied Mathematics Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata 700108, India
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16
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Majhi S, Perc M, Ghosh D. Dynamics on higher-order networks: a review. J R Soc Interface 2022; 19:20220043. [PMID: 35317647 PMCID: PMC8941407 DOI: 10.1098/rsif.2022.0043] [Citation(s) in RCA: 70] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 02/18/2022] [Indexed: 12/25/2022] Open
Abstract
Network science has evolved into an indispensable platform for studying complex systems. But recent research has identified limits of classical networks, where links connect pairs of nodes, to comprehensively describe group interactions. Higher-order networks, where a link can connect more than two nodes, have therefore emerged as a new frontier in network science. Since group interactions are common in social, biological and technological systems, higher-order networks have recently led to important new discoveries across many fields of research. Here, we review these works, focusing in particular on the novel aspects of the dynamics that emerges on higher-order networks. We cover a variety of dynamical processes that have thus far been studied, including different synchronization phenomena, contagion processes, the evolution of cooperation and consensus formation. We also outline open challenges and promising directions for future research.
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Affiliation(s)
- Soumen Majhi
- Department of Mathematics, Bar-Ilan University, Ramat-Gan 5290002, Israel
| | - Matjaž Perc
- Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000 Maribor, Slovenia
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan
- Complexity Science Hub Vienna, Josefstödter Straße 39, 1080 Vienna, Austria
- Alma Mater Europaea, Slovenska ulica 17, 2000 Maribor, Slovenia
| | - Dibakar Ghosh
- Physics and Applied Mathematics Unit, Indian Statistical Institute, 203 B. T. Road, Kolkata 700108, India
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17
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Shang Y. A system model of three-body interactions in complex networks: consensus and conservation. Proc Math Phys Eng Sci 2022. [DOI: 10.1098/rspa.2021.0564] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Networked complex systems in a wide range of physics, biology and social sciences involve synergy among multiple agents beyond pairwise interactions. Higher-order mathematical structures such as hypergraphs have been increasingly popular in modelling and analysis of complex dynamical behaviours. Here, we study a simple three-body consensus model, which favourably incorporates higher-order network interactions, higher-order dimensional states, the group reinforcement effect and the social homophily principle. The model features asymmetric roles of acting agents using modulating functions. We analytically establish sufficient conditions for nonlinear consensus and conservation of states for agents with both discrete-time and continuous-time dynamics. We show that higher-order interactions encoded in three-body edges give rise to consensus and conservation for systems with gravity-like and Heaviside-like modulating functions. Furthermore, we illustrate our theoretical results with numerical simulations and examine the system convergence time through a network depreciation process.
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Affiliation(s)
- Yilun Shang
- Department of Computer and Information Sciences, Northumbria University, Newcastle, UK
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18
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Tsouchnika M, Smolyak A, Argyrakis P, Havlin S. Patent collaborations: From segregation to globalization. J Informetr 2022. [DOI: 10.1016/j.joi.2021.101238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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19
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Zhu N, Liu C, Yang Z. Team Size, Research Variety, and Research Performance: Do Coauthors’ Coauthors Matter? J Informetr 2021. [DOI: 10.1016/j.joi.2021.101205] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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20
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Lüschow A. Application of graph theory in the library domain—Building a faceted framework based on a literature review. JOURNAL OF LIBRARIANSHIP AND INFORMATION SCIENCE 2021. [DOI: 10.1177/09610006211036734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Based on a literature review, we present a framework for structuring the application of graph theory in the library domain. Our goal is to provide both researchers and libraries with a standard tool to classify scientific work, at the same time allowing for the identification of previously underrepresented areas where future research might be productive. To achieve this, we compile graph theoretical approaches from the literature to consolidate the components of our framework on a solid basis. The extendable framework consists of multiple facets grouped into five categories whose elements can be arbitrarily combined. Libraries can benefit from these facets by using them as a point of reference for the (meta)data they offer. Further work on formally defining the framework’s categories as well as on integration of other graph-related research areas not discussed in this article (e.g. knowledge graphs) would be desirable and helpful in the future.
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21
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Sagan A, Brzezińska J, Rybicka A, Sztemberg-Lewandowska M, Pełka M. Item response theory network analysis of European universities. COMMUN STAT-SIMUL C 2021. [DOI: 10.1080/03610918.2021.1941109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Adam Sagan
- University of Cracow, Department of Market Analysis and Marketing Research, Cracow, Poland
| | - Justyna Brzezińska
- University of Economics in Katowice, Department of Economic and Financial Analysis, Katowice, Poland
| | - Aneta Rybicka
- Wroclaw University of Economics and Business, Department of Econometrics and Informatics, Wroclaw, Poland
| | | | - Marcin Pełka
- Wroclaw University of Economics and Business, Department of Econometrics and Informatics, Wroclaw, Poland
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