Article
Ecology
Jinbao Liao, Daniel Bearup, Giovanni Strona
Summary: The structure of interactions between species within a community is crucial for maintaining biodiversity. Previous studies have shown that the effects of these structures differ depending on the type of interaction. However, a new study using a patch-dynamic metacommunity framework found that the qualitative differences between antagonistic and mutualistic systems disappear, and nestedness and modularity interact to promote metacommunity persistence.
Article
Physics, Multidisciplinary
Emiliano Marchese, Guido Caldarelli, Tiziano Squartini
Summary: This study presents a unified, surprise-based framework for detecting mesoscale network structures. A general approach is provided by considering weighted cases and six variants of surprise. The performances are demonstrated using synthetic benchmarks and real-world configurations, and a Python code implementing all variants of surprise is provided.
COMMUNICATIONS PHYSICS
(2022)
Article
Automation & Control Systems
Li Lei, Degang Yang, Tao Liang, Wanli Zhang
Summary: Based on the framework of signed graphs, this paper investigates the finite-time bipartite synchronization of delayed complex-valued complex networks. Control strategies with quantizer are designed to save communication resources. Theoretical results are rigorously proved using 1-norm analytical techniques. FTBS criteria are established using multiple Lyapunov functions, and the settling time is estimated based on control parameters and initial values. Numerical simulations are conducted to verify the validity of the theoretical analysis.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Ecology
Lara Becker, Nico Bluethgen, Barbara Drossel
Summary: This study examines the assembly of species interaction networks and the influence of demographic noise on species and strategy diversity. The findings suggest that assembled communities show maximum species diversity and average generalization at intermediate assembly stages.
AMERICAN NATURALIST
(2022)
Article
Mathematics, Interdisciplinary Applications
C. T. Martinez-Martinez, J. A. Mendez-Bermudez, Thomas Peron, Yamir Moreno
Summary: Mutualistic networks are studied using a random matrix ensemble (RME) to analyze their spectral, eigenvector, and topological properties. The study shows that a statistical approach can reasonably predict the properties of real-world mutualistic networks, as the universal curves show good correspondence between theoretical and real-world networks.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Physics, Fluids & Plasmas
Hyun Woo Lee, Jae Woo Lee, Deok-Sun Lee
Summary: This study investigates species abundance in empirical plant-pollinator mutualistic networks using the Lotka-Volterra equation. By applying the annealed approximation and analyzing parameters, we identify different stable fixed points and obtain the phase diagram. The findings show that in the selective extinction phase, low-degree species go extinct, maintaining stability and supporting the theoretical predictions.
Article
Biochemistry & Molecular Biology
Isabel C. Kilian, Stephanie J. Swenson, Ximo Mengual, Birgit Gemeinholzer, Andree Hamm, J. Wolfgang Waegele, Ralph S. Peters
Summary: This study investigated the plant-pollinator network of caraway in a central European agricultural landscape, focusing on two potential pollinator taxa: Diptera and Hymenoptera. The results showed that both Diptera and Hymenoptera can carry caraway pollen, indicating a wide taxonomic breadth of potential pollinators and a higher network complexity than previously anticipated. The study also found that there are distinct qualitative differences between the networks of the two taxa, suggesting complementary roles of both taxa in pollination.
Article
Physics, Multidisciplinary
Simone Giansante, Sabato Manfredi, Sheri Markose
Summary: The aftermath of the recent financial crisis has highlighted the high cost and unfairness of stabilizing financial ecosystems. The complexity of financial interactions poses challenges for regulators. A framework is provided to decompose complex ecosystems and study their instability and the contribution of institutions to that instability. Immunization schemes can be used to penalize institutions based on their destabilizing contribution, promoting fairness and cost-efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Tao Liang, Degang Yang, Li Lei, Wanli Zhang, Ju Pan
Summary: This paper investigates the bipartite synchronization problem of complex networks with quantized couplings and stochastic perturbations using the preassigned-time control method. By designing a new controller and providing a PAT criterion, stochastic bipartite synchronization is achieved.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2022)
Article
Mathematics, Applied
Yu Meng, Celso Grebogi
Summary: The control method delays extinction and advances recovery by controlling the decay rate of pollinators in a complex network. Introducing pollinator species immune to environmental deterioration and in mutualistic relationship with collapsed species helps promote recovery.
Article
Biology
Agustin Vitali, Sofia Ruiz-Suarez, Diego P. Vazquez, Matthias Schleuning, Mariano A. Rodriguez-Cabal, Yamila Sasal, Shai Pilosof
Summary: The effects of invasive species on multitrophic networks were investigated in an ongoing invasion scenario in Patagonia, Argentina. Non-native ungulates disrupted a keystone interaction between hummingbirds, mistletoe, and marsupials, altering community composition. The connectivity between pollination and seed dispersal was reduced, and the network structure fragmented by the invasive species, leading to increased disturbance propagation and reduced network stability.
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
(2023)
Article
Mathematics, Applied
Shiju Yang, Chuandong Li, Xiping He, Wanli Zhang
Summary: This paper investigates the bipartite synchronization of coupled complex networks (CCNs) with signed graphs via variable-time impulsive (VTI) control. The VTI network models can be transformed into fixed-time impulsive CCNs using the B-equivalent technique. Assumptions are derived using 1-norm analytical techniques to ensure each solution of the coupled error nodes intersect each discontinuous impulsive surface exactly once. The paper presents sufficient conditions with theoretical demonstration to guarantee bipartite synchronization under mathematical induction, and simulation results show the effectiveness of the obtained results.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Automation & Control Systems
Shiju Yang, Wanli Zhang, Dongmei Ruan, Ting Yang, Yu Li
Summary: This dissertation discusses the FFDT-BS of TS FCNs with signed graphs under impulsive control. The control process includes impulsive control and fixed-time control, both designed as fuzzy logic systems. Novel criteria are presented to guarantee the FFDT-BS of the TS FCNs within bounded time, achieving faster convergence and demonstrating the correctness of the theoretical analysis.
NONLINEAR ANALYSIS-HYBRID SYSTEMS
(2023)
Article
Mathematics, Interdisciplinary Applications
Xiangrong Wang, Thomas Peron, Johan L. A. Dubbeldam, Sonia Kefi, Yamir Moreno
Summary: Mutualistic networks have gained attention in ecological literature due to their natural history and their role in maintaining biodiversity. However, there is a lack of theory exploring the interplay between the structures of competitive and mutualistic networks. In this study, we develop an analytical framework to study the structural stability of ecological communities with both competitive and mutualistic interactions. Our results show that the structure of the competitive network significantly affects the conditions for species coexistence in these communities. We also introduce a new metric that accurately links the network structures of competitive and mutualistic interactions to species coexistence.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Ecology
F. M. Windsor
Summary: Research in freshwater ecosystems has historically focused on trophic interactions and food webs, but there is a need to investigate a wider range of non-trophic interactions and the ecological networks they form. Understanding all potential interactions, from mutualistic to antagonistic, is crucial for understanding ecosystem assembly, structure, and function. To advance our understanding, we can learn from research in marine and terrestrial ecosystems and utilize emerging technologies to merge ecological interactions in freshwater ecosystems into networks.
JOURNAL OF ANIMAL ECOLOGY
(2023)
Article
Multidisciplinary Sciences
Yannick Leo, Eric Fleury, J. Ignacio Alvarez-Hamelin, Carlos Sarraute, Marton Karsai
JOURNAL OF THE ROYAL SOCIETY INTERFACE
(2016)
Article
Multidisciplinary Sciences
Laura Hernandez, Annick Vignes, Stephanie Saba
Article
Multidisciplinary Sciences
Carlos Gracia-Lazaro, Laura Hernandez, Avier Borge-Holthoefer, Yamir Moreno
SCIENTIFIC REPORTS
(2018)
Article
Computer Science, Information Systems
Esteban Carisimo, Carlos Selmo, J. Ignacio Alvarez-Hamelin, Amogh Dhamdhere
COMPUTER COMMUNICATIONS
(2019)
Article
Physics, Multidisciplinary
Claudia Payrato-Borras, Laura Hernandez, Yamir Moreno
Article
Computer Science, Information Systems
Esteban Carisimo, Julian M. Del Fiore, Diego Dujovne, Cristel Pelsser, J. Ignacio Alvarez-Hamelin
ACM SIGCOMM COMPUTER COMMUNICATION REVIEW
(2020)
Article
Multidisciplinary Sciences
Hendrik Schawe, Laura Hernandez
SCIENTIFIC REPORTS
(2020)
Article
Multidisciplinary Sciences
Hendrik Schawe, Laura Hernandez
SCIENTIFIC REPORTS
(2020)
Article
Ecology
Claudia Payrato-Borras, Laura Hernandez, Yamir Moreno
ECOLOGY AND EVOLUTION
(2020)
Article
Mathematics, Interdisciplinary Applications
Tomas Mussi Reyero, Mariano G. Beiro, J. Ignacio Alvarez-Hamelin, Laura Hernandez, Dimitris Kotzinos
Summary: This study examines the evolution of Argentina's political landscape during the 2015 and 2019 presidential elections using Twitter data, building a semantic network to detect societal topics. By assigning dynamic topic vectors to users, it reveals similarities and differences among groups of supporters of different candidates. The method can capture the reshaping of political opinions and the inversion of election results between the two rounds in 2015.
Article
Physics, Multidisciplinary
Hendrik Schawe, Sylvain Fontaine, Laura Hernandez
Summary: The study reveals the significant impact of network topology on the dynamics' steady states, and suggests that the consensus threshold may vanish in the thermodynamic limit with increasing system size.
PHYSICAL REVIEW RESEARCH
(2021)
Proceedings Paper
Computer Science, Hardware & Architecture
Diego Kiedanski, Eduardo Grampin, J. Ignacio Alvarez-Hamelin
PROCEEDINGS OF THE 10TH LATIN AMERICAN NETWORKING CONFERENCE (LANC 2018)
(2018)
Proceedings Paper
Computer Science, Hardware & Architecture
Esteban Carisimo, Carlos Selmo, J. Ignacio Alvarez-Hamelin, Amogh Dhamdhere
2018 NETWORK TRAFFIC MEASUREMENT AND ANALYSIS CONFERENCE (TMA)
(2018)
Proceedings Paper
Education, Scientific Disciplines
Pablo Etchepareborda, Marcos E. Bierzychudek, Leonardo Carducci, Francisco E. Veiras, Federico G. Zacchigna, Ernesto Corbellini, Sebastian Garcia Marra, Mariano Iglesias, Martin Mello Teggia, J. Ignacio Alvarez-Hamelin, Ricardo A. Veiga
2018 IEEE WORLD ENGINEERING EDUCATION CONFERENCE (EDUNINE)
(2018)
Article
Physics, Multidisciplinary
Xiaoyu Shi, Jian Zhang, Xia Jiang, Juan Chen, Wei Hao, Bo Wang
Summary: This study presents a novel framework using offline reinforcement learning to improve energy consumption in road transportation. By leveraging real-world human driving trajectories, the proposed method achieves significant improvements in energy consumption. The offline learning approach demonstrates generalizability across different scenarios.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Junhyuk Woo, Soon Ho Kim, Hyeongmo Kim, Kyungreem Han
Summary: Reservoir computing (RC) is a new machine-learning framework that uses an abstract neural network model to process information from complex dynamical systems. This study investigates the neuronal and network dynamics of liquid state machines (LSMs) using numerical simulations and classification tasks. The findings suggest that the computational performance of LSMs is closely related to the dynamic range, with a larger dynamic range resulting in higher performance.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Chengwei Dong, Min Yang, Lian Jia, Zirun Li
Summary: This work presents a novel three-dimensional system with multiple types of coexisting attractors, and investigates its dynamics using various methods. The mechanism of chaos emergence is explored, and the periodic orbits in the system are studied using the variational method. A symbolic coding method is successfully established to classify the short cycles. The flexibility and validity of the system are demonstrated through analogous circuit implementation. Various chaos-based applications are also presented to show the system's feasibility.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Viorel Badescu
Summary: This article discusses the maximum work extraction from confined particles energy, considering both reversible and irreversible processes. The results vary for different types of particles and conditions. The concept of exergy cannot be defined for particles that undergo spontaneous creation and annihilation. It is also noted that the Carnot efficiency is not applicable to the conversion of confined thermal radiation into work.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
P. M. Centres, D. J. Perez-Morelo, R. Guzman, L. Reinaudi, M. C. Gimenez
Summary: In this study, a phenomenological investigation of epidemic spread was conducted using a model of agent diffusion over a square region based on the SIR model. Two possible contagion mechanisms were considered, and it was observed that the number of secondary infections produced by an individual during its infectious period depended on various factors.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zuan Jin, Minghui Ma, Shidong Liang, Hongguang Yao
Summary: This study proposes a differential variable speed limit (DVSL) control strategy considering lane assignment, which sets dynamic speed limits for each lane to attract vehicle lane-changing behaviors before the bottleneck and reduce the impact of traffic capacity drop. Experimental results show that the proposed DVSL control strategy can alleviate traffic congestion and improve efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Matthew Dicks, Andrew Paskaramoorthy, Tim Gebbie
Summary: In this study, we investigate the learning dynamics of a single reinforcement learning optimal execution trading agent when it interacts with an event-driven agent-based financial market model. The results show that the agents with smaller state spaces converge faster and are able to intuitively learn to trade using spread and volume states. The introduction of the learning agent has a robust impact on the moments of the model, except for the Hurst exponent, which decreases, and it can increase the micro-price volatility as trading volumes increase.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Zhouzhou Yao, Xianyu Wu, Yang Yang, Ning Li
Summary: This paper developed a cooperative lane-changing decision system based on digital technology and indirect reciprocity. By introducing image scoring and a Q-learning based reinforcement learning algorithm, drivers can continuously evaluate gains and adjust their strategies. The study shows that this decision system can improve driver cooperation and traffic efficiency, achieving over 50% cooperation probability under any connected vehicles penetration and traffic density, and reaching 100% cooperation probability under high penetration and medium to high traffic density.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Josephine Nanyondo, Henry Kasumba
Summary: This paper presents a multi-class Aw-Rascle (AR) model with area occupancy expressed in terms of vehicle class proportions. The qualitative properties of the proposed equilibrium velocity and the stability conditions of the model are established. The numerical results show the effect of proportional densities on the flow of vehicle classes, indicating the realism of the proposed model.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Oliver Smirnov
Summary: This study proposes a new method for simultaneously estimating the parameters of the 2D Ising model. The method solves a constrained optimization problem, where the objective function is a pseudo-log-likelihood and the constraint is the Hamiltonian of the external field. Monte Carlo simulations were conducted using models of different shapes and sizes to evaluate the performance of the method with and without the Hamiltonian constraint. The results demonstrate that the proposed estimation method yields lower variance across all model shapes and sizes compared to a simple pseudo-maximum likelihood.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Przemyslaw Chelminiak
Summary: The study investigates the first-passage properties of a non-linear diffusion equation with diffusivity dependent on the concentration/probability density through a power-law relationship. The survival probability and first-passage time distribution are determined based on the power-law exponent, and both exact and approximate expressions are derived, along with their asymptotic representations. The results pertain to diffusing particles that are either freely or harmonically trapped. The mean first-passage time is finite for the harmonically trapped particle, while it is divergent for the freely diffusing particle.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Hidemaro Suwa
Summary: The choice of transition kernel is crucial for the performance of the Markov chain Monte Carlo method. A one-parameter rejection control transition kernel is proposed, and it is shown that the rejection process plays a significant role in determining the sampling efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Physics, Multidisciplinary
Xudong Wang, Yao Chen
Summary: This article investigates the joint influence of expanding medium and constant force on particle diffusion. By starting from the Langevin picture and introducing the effect of external force in two different ways, two models with different force terms are obtained. Detailed analysis and derivation yield the Fokker-Planck equations and moments for the two models. The sustained force behaves as a decoupled force, while the intermittent force changes the diffusion behavior with specific effects depending on the expanding rate of the medium.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
