Article
Computer Science, Artificial Intelligence
Xiaoze Ni, Shiping Wen, Huamin Wang, Zhenyuan Guo, Song Zhu, Tingwen Huang
Summary: This article focuses on the observer-based quasi-synchronization problem of delayed dynamical networks with parameter mismatch under impulsive effect. State estimation strategy is proposed, appropriate synchronization controller is designed, and analysis is done using Lyapunov function to prove the boundedness of the system trajectory. A numerical simulation is presented to illustrate the validity of the obtained results.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Yonggang Chen, Zidong Wang, Jun Hu, Qing-Long Han
Summary: This article addresses the synchronization control problem for discrete-time dynamical networks with mixed delays and switching topology. It specifically considers the saturation phenomenon of physical actuators and establishes conditions ensuring the stability of error dynamics and existence of desired controller gains. Three convex optimization problems are formulated for disturbance tolerance, performance constraints, and initial conditions. Two simulation examples demonstrate the effectiveness and merits of the proposed results.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Multidisciplinary Sciences
Yuanzhao Zhang, Maxime Lucas, Federico Battiston
Summary: Higher-order networks are a powerful framework for modeling complex systems and their collective behavior. The choice between simplicial complexes and hypergraphs has a significant impact on the dynamics of the system.
NATURE COMMUNICATIONS
(2023)
Article
Physics, Fluids & Plasmas
Mousumi Roy, Swarup Poria, Chittaranjan Hens
Summary: This study investigates the synchronization transition process in a scale-free network of nonidentical Chialvo neurons, focusing on the effect of the degree of assortativity. The research reveals that assortativity can lead to bistability between asymptotically stable states and transform the phase transition from second order to first order, with an expansion in the hysteresis loop area. Additionally, the study examines the simultaneous transitions of node frequencies to the synchronized state with phases and the impact of lower degree nodes on synchronization transition in positive assortative networks.
Article
Computer Science, Artificial Intelligence
Lijun Pan, Qiang Song, Jinde Cao, Minvydas Ragulskis
Summary: This article investigates the synchronization of stochastic delayed neural networks under pinning impulsive control, proposing new mean square decay results and analysis methods, discussing system behavior in different scenarios, and extending the flexibility of impulsive gains.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Automation & Control Systems
Jin-Liang Wang, Lu Wang, Huai-Ning Wu
Summary: This article investigates the synchronization problem for directed and undirected complex networks with multiple state or delayed state couplings, subject to recoverable attacks. Synchronization criteria are established using Lyapunov functional, inequality techniques, and state-feedback controller. The article also discusses the synchronization of networks with multiple delayed state couplings.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Jiejie Chen, Boshan Chen, Zhigang Zeng
Summary: This article proposes an event-triggering impulsive control strategy for synchronization of multiple neural networks, avoiding Zeno behavior. It discusses the synchronization problems of a MDNN with delay and a directed disconnected switching topology. The study also considers jointly connected and pure impulsive control protocol cases, providing theoretical analysis through a numerical example.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Physics, Fluids & Plasmas
Sayantan Nag Chowdhury, Sarbendu Rakshit, Javier M. Buldu, Dibakar Ghosh, Chittaranjan Hens
Summary: This article explores the synchronization properties of dynamical systems connected through multiplex architectures, showing the coexistence of intralayer synchronization and antiphase dynamics between coupled systems of different layers. The transition from interlayer antisynchronization to antiphase synchrony in bipartite multiplex architectures is demonstrated, along with the necessary conditions and local stability analysis of the interlayer antisynchronization state.
Article
Automation & Control Systems
Qian Xie, Duo Guo, Tong Wang, Xiaoping Yang
Summary: This paper focuses on finite-time synchronization and parameters identification in the Markovian switching complex delayed network with multiple weights. By adopting finite-time control technique and pinning control strategy, network synchronization and parameters identification can be achieved quickly while reducing energy consumption and control cost. Additionally, an Optimal Nodes Selection Control Strategy (ONSCS) is proposed to further enhance network performance and efficiency.
IET CONTROL THEORY AND APPLICATIONS
(2021)
Article
Automation & Control Systems
Xinrui Ji, Jianquan Lu, Bangxin Jiang, Jie Zhong
Summary: This paper investigates the synchronization of complex dynamical networks with both system delay and coupled delay using distributed delayed impulsive control. A new concept of average delayed impulsive weight is proposed to obtain more relaxed conditions. The criteria for global exponential synchronization are derived based on the impulsive control topology, Lyapunov theory, and linear matrix inequality (LMI) design. Simulation results demonstrate that the distributed delayed impulsive control can speed up the convergence rate for synchronized networks and facilitate synchronization for desynchronized networks.
NONLINEAR ANALYSIS-HYBRID SYSTEMS
(2022)
Article
Physics, Fluids & Plasmas
Srilena Kundu, Dibakar Ghosh
Summary: This letter reports the emergence of chimera states without phase lag in a nonlocally coupled identical Kuramoto network. The introduction of nonlinearity in the coupled system dynamics reduces the requirement for phase lag in chimera states.
Article
Automation & Control Systems
Mingzhu Wang, Shuchen Wu, Xiaodi Li
Summary: This paper investigates Lyapunov stability of general nonlinear systems using event-triggered impulsive control, considering delayed impulses. By excluding Zeno behavior, a set of sufficient conditions for uniform and asymptotic stability are obtained based on impulsive control theory in the framework of event triggering. The results depend on the event-triggering mechanism and time delays.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Automation & Control Systems
Ning Zhang, Shunjie Huang, Wenxue Li
Summary: This paper investigates the pth moment exponential stability of stochastic delayed systems, taking into account both semi-Markov jumps and stochastic mixed impulses. It establishes new impulsive differential inequalities with semi-Markov jumps and stochastic mixed impulses. By cleverly combining graph theory, stochastic analysis techniques, and the Lyapunov method, stability criteria for stochastic delayed semi-Markov jump systems with stochastic mixed impulses are proposed. Finally, the theoretical results are applied to oscillator systems, and the simulation results confirm the effectiveness of the theoretical findings.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Ziye Zhang, Xiaofeng Wei, Shuzhan Wang, Chong Lin, Jian Chen
Summary: This article focuses on fixed-time pinning common synchronization and adaptive synchronization for quaternion-valued neural networks with time-varying delays. By introducing fixed-time control theory and adaptive control gains, the corresponding synchronization criteria are established, and the effectiveness of these results is verified through simulation examples.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Mingyue Li, Xueyan Yang, Xiaodi Li
Summary: This article investigates the lag synchronization problem of neural networks involving partially unmeasurable states under impulsive control. It proposes a method to design impulsive controllers using measurable state information, and derives sufficient conditions for lag synchronization using linear matrix inequality and transition matrix methods. The results not only allow for the existence of unmeasurable states but also reduce the restrictions on the number of measurable states, demonstrating their generality and practical applicability.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Physics, Multidisciplinary
Anti Ingel, Abdullah Makkeh, Oriol Corcoll, Raul Vicente
Summary: In this study, we introduce an algorithm for computing the level of autonomy of an agent using an information-theoretic formulation. We use the partial information decomposition framework to monitor the autonomy level and environment internalization of reinforcement learning agents. Our experiments show strong correlations between specific PID terms and the obtained reward, as well as the agent's behavior in response to perturbations in the observations.
Article
Multidisciplinary Sciences
Joan Benach, Lucinda Cash-Gibson, Diego F. Rojas-Gualdron, Alvaro Padilla-Pozo, Juan Fernandez-Gracia, Victor M. Eguiluz
Summary: The COVID-19 pandemic has highlighted the urgent need for empirical research on health inequalities to effectively respond to global threats. A bibliometric and network analysis of COVID-19 associated inequalities research using the Scopus database reveals a highly collaborative field with both similarities and new dynamics compared to pre-COVID-19 global health inequalities research. It is crucial to invest in global health inequalities research capacities to address growing social inequalities and prepare for future crises.
Article
Multidisciplinary Sciences
Freya C. Womersley, Nicolas E. Humphries, Nuno Queiroz, Marisa Vedor, Ivo da Costa, Miguel Furtado, John P. Tyminski, Katya Abrantes, Gonzalo Araujo, Steffen S. Bach, Adam Barnett, Michael L. Berumen, Sandra Bessudo Lion, Camrin D. Braun, Elizabeth Clingham, Jesse E. M. Cochran, Rafael de la Parra, Stella Diamant, Alistair D. M. Dove, Christine L. Dudgeon, Mark Erdmann, Eduardo Espinoza, Richard Fitzpatrick, Jaime Gonzalez Cano, Jonathan R. Green, Hector M. Guzman, Royale Hardenstine, Abdi Hasan, Fabio H. Hazin, Alex R. Hearn, Robert E. Hueter, Mohammed Y. Jaidah, Jessica Labaja, Felipe Ladino, Bruno C. L. Macena, John J. Morris Jr, Bradley M. Norman, Cesar Penaherrera-Palma, Simon J. Pierce, Lina M. Quintero, Deni Ramirez-Macias, Samantha D. Reynolds, Anthony J. Richardson, David P. Robinson, Christoph A. Rohner, David R. L. Rowat, Marcus Sheaves, Mahmood S. Shivji, Abraham B. Sianipar, Gregory B. Skomal, German Soler, Ismail Syakurachman, Simon R. Thorrold, D. Harry Webb, Bradley M. Wetherbee, Timothy D. White, Tyler Clavelle, David A. Kroodsma, Michele Thums, Luciana C. Ferreira, Mark G. Meekan, Lucy M. Arrowsmith, Emily K. Lester, Megan M. Meyers, Lauren R. Peel, Ana M. M. Sequeira, Victor M. Eguiluz, Carlos M. Duarte, David W. Sims
Summary: Marine traffic is increasing globally, but collisions between ships and endangered megafauna are often undetected or unreported. By tracking the movements of whale sharks and vessel activity, it was found that there is a significant overlap between shark's space use and large vessel traffic. High collision risks were observed in major oceans, particularly with cargo and tanker vessels, concentrated in gulf regions where dense traffic coincides with shark movements. This study highlights the importance of mitigating ship-strike risks to protect species like whale sharks from the impact of growing global vessel traffic.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Multidisciplinary Sciences
Carlos M. Duarte, David Ketcheson, Victor M. Eguiluz, Susana Agusti, Juan Fernandez-Gracia, Tahira Jamil, Elisa Laiolo, Takashi Gojobori, Intikhab Alam
Summary: The competition between pathogens and hosts drives evolution, and the future evolutionary dynamics of SARS-CoV-2 can be predicted through real-time tracking of its population genomics worldwide. The evolution of SARS-CoV-2 is accelerating, with an average of 12 new effective RBD variants appearing daily. This challenges our defenses and calls for collaborative global sequencing and vaccination.
SCIENTIFIC REPORTS
(2022)
Article
Mathematics, Applied
David Sanchez, Luciano Zunino, Juan De Gregorio, Raul Toral, Claudio Mirasso
Summary: Words are fundamental linguistic units that are connected through meaning and syntactic rules. By analyzing the statistical connections between words using an ordinal pattern approach, we discovered unique pattern distributions for different languages. These pattern distributions can be used to determine the historical period and author of a text. Our findings highlight the significance of ordinal time series analysis in linguistic typology, historical linguistics, and stylometry.
Article
Mathematics, Applied
Jorge P. Rodriguez, Victor M. Eguiluz
Summary: Interactions between different diseases can alter their dynamics, posing uncertainty in modeling empirical data when the symptoms of both infections are indistinguishable. By extending previously proposed models to non-symmetric scenarios, we demonstrate that both cooperative and competitive interactions lead to synchronization of the maximum fraction of infected individuals. Using a model that combines the dynamics of COVID-19 and seasonal influenza, we show that the coupling synchronizes both infections, with a stronger influence on influenza dynamics.
Article
Biodiversity Conservation
Gian Marco Palamara, Alejandro Rozenfeld, Charles N. de Santana, Jan Klecka, Rodrigo Riera, Victor M. Eguiluz, Carlos J. Melian
Summary: This study examines the impact of fluctuations in landscape connectivity on biodiversity dynamics. The results show that local and regional species richness can increase together in dynamic landscapes, and fluctuations in connectivity can increase the overall number of coexisting species. This clarifies the empirical findings of high biodiversity in both low and high-connected landscapes.
Article
Multidisciplinary Sciences
Francesc Belvis, Alberto Aleta, Alvaro Padilla-Pozo, Juan-M. Pericas, Juan Fernandez-Gracia, Jorge P. Rodriguez, Victor M. Eguiluz, Charles Novaes De Santana, Mireia Julia, Joan Benach
Summary: This research examines the evolution of COVID-19 incidence rates and effective reproduction number R(t), as well as their relationship with spatial autocorrelation patterns in Catalonia, Spain. The study finds that there were five major outbreaks, all preceded by R(t) values greater than 1 in the previous two weeks. There is no clear pattern in the initial focus of each wave. Spatial autocorrelation follows a baseline pattern, but deviations occur in some waves, which can be reproduced through interventions to reduce mobility and virus transmissibility.
SCIENTIFIC REPORTS
(2023)
Article
Physiology
Guadalupe C. Garcia, Kavya Gupta, Thomas M. Bartol, Terrence J. Sejnowski, Padmini Rangamani
Summary: In this study, a thermodynamically consistent model for ATP production in mitochondria is presented. The model takes into account reaction rate constants and ensures detailed balance. Simulations and three-dimensional reconstructions of mitochondria show that ATP production is the limiting step and is linked to morphological features of the organelles.
JOURNAL OF GENERAL PHYSIOLOGY
(2023)
Article
Biotechnology & Applied Microbiology
Altynay Kaidarova, Nathan R. Geraldi, Rory P. Wilson, Juergen Kosel, Mark G. Meekan, Victor M. Eguiluz, Muhammad Mustafa Hussain, Atif Shamim, Hanguang Liao, Mani Srivastava, Swapnil Sayan Saha, Michael S. Strano, Xiangliang Zhang, Boon S. Ooi, Mark Holton, Lloyd W. Hopkins, Xiaojia Jin, Xun Gong, Flavio Quintana, Adylkhan Tovasarov, Assel Tasmagambetova, Carlos M. Duarte
Summary: Human societies rely on marine ecosystems, which are still experiencing degradation. This article discusses the adaptation of sensors and wearable technology developed for humans to improve marine monitoring. It highlights the barriers to transitioning this technology from land to sea, updates on sensor developments for ocean observation, and advocates for wider use of wearables on marine organisms. The authors propose that widespread use of wearables could contribute to an 'internet of marine life' and inform strategies for marine conservation and restoration.
NATURE BIOTECHNOLOGY
(2023)
Article
Physics, Fluids & Plasmas
Annalisa Caligiuri, Victor M. Eguiluz, Leonardo Di Gaetano, Tobias Galla, Lucas Lacasa
Summary: By interpreting a temporal network as a trajectory of a latent graph dynamical system, the concept of dynamical instability and a measure to estimate the network maximum Lyapunov exponent (nMLE) is introduced. Nonlinear time-series analysis algorithmic methods are extended to networks to quantify sensitive dependence on initial conditions and estimate the nMLE directly from a single network trajectory. The method is validated for synthetic generative network models displaying low- and high-dimensional chaos, and potential applications are discussed.
Article
Biochemistry & Molecular Biology
Kailash Venkatraman, Christopher T. Lee, Guadalupe C. Garcia, Arijit Mahapatra, Daniel Milshteyn, Guy Perkins, Keun-Young Kim, H. Amalia Pasolli, Sebastien Phan, Jennifer Lippincott-Schwartz, Mark H. Ellisman, Padmini Rangamani, Itay Budin
Summary: The architecture of the inner mitochondrial membrane is not only regulated by proteins, but also influenced by specific lipids. This study reveals the crucial role of cardiolipin in buffering the curvature loss and promoting cristae formation.
Article
Physics, Fluids & Plasmas
Mirko Goldmann, Claudio R. Mirasso, Ingo Fischer, Miguel C. Soriano
Summary: We propose scalable neural networks that can handle translational symmetries in dynamical systems and infer high-dimensional dynamics for different system sizes. By training the networks to predict dynamics for a single size and then driving them with their own predictions, we show that the complex dynamics for larger or smaller system sizes can be accurately predicted. The network learns from a single example and leverages symmetry properties to infer entire bifurcation diagrams.
Article
Physics, Multidisciplinary
Lucas Lacasa, Jorge P. Rodriguez, Victor M. Eguiluz
Summary: This study investigates the simulation of temporal networks, which model the evolution of interactions between elements in a complex system over time. It interprets temporal networks as trajectories of collective motion in graph space, following a latent graph dynamical system. The study proposes a way to measure how the network pulsates and collectively fluctuates over time and space, and demonstrates the measurement by constructing stochastic and deterministic graph dynamical systems.
PHYSICAL REVIEW RESEARCH
(2022)
Article
Multidisciplinary Sciences
Freya C. Womersley, Nicolas E. Humphries, Nuno Queiroz, Marisa Vedor, Ivo da Costa, Miguel Furtado, John P. Tyminski, Katya Abrantes, Gonzalo Araujo, Steffen S. Bach, Adam Barnett, Michael L. Berumen, Sandra Bessudo Lion, Camrin D. Braun, Elizabeth Clingham, Jesse E. M. Cochran, Rafael de la Parra, Stella Diamant, Alistair D. M. Dove, Christine L. Dudgeon, Mark V. Erdmann, Eduardo Espinoza, Richard Fitzpatrick, Jaime Gonzalez Cano, Jonathan R. Green, Hector M. Guzman, Royale Hardenstine, Abdi Hasan, Fabio H. V. Hazin, Alex R. Hearn, Robert E. Hueter, Mohammed Y. Jaidah, Jessica Labaja, Felipe Ladino, Bruno C. L. Macena, John J. Morris, Bradley M. Norman, Cesar Penaherrera-Palma, Simon J. Pierce, Lina M. Quintero, Deni Ramirez-Macias, Samantha D. Reynolds, Anthony J. Richardson, David P. Robinson, Christoph A. Rohner, David R. L. Rowat, Marcus Sheaves, Mahmood S. Shivji, Abraham B. Sianipar, Gregory B. Skomal, German Soler, Ismail Syakurachman, Simon R. Thorrold, D. Harry Webb, Bradley M. Wetherbee, Timothy D. White, Tyler Clavelle, David A. Kroodsma, Michele Thums, Luciana C. Ferreira, Mark G. Meekan, Lucy M. Arrowsmith, Emily K. Lester, Megan M. Meyers, Lauren R. Peel, Ana M. M. Sequeira, Victor M. Eguiluz, Carlos M. Duarte, David W. Sims
Summary: Global marine traffic is increasing, posing a risk to endangered megafauna such as whale sharks. Research shows significant overlap between whale shark movements and large vessel traffic, particularly in busy shipping routes and gulf regions, leading to predictable collision risk areas.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)