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PLOS Complex Systems
Scopus
ISSN 2837-8830 · Public Library of Science · 118 artikel di indeks
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Group size and environmental obstacles drive acoustic call properties for gray bats in flight: A data-driven analysis
Unlike schools of fish or flocks of birds, social bats who use echolocation for navigation are faced with the complex challenge of signal processing while living and flying in groups. Interference between an individual’s calls and those of its conspecifics can be confused, making these signals…
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Assortativity in geometric and scale-free networks
The assortative behavior of a network is the tendency of similar (or dissimilar) nodes to connect to each other. This tendency can have an influence on various properties of the network, such as its robustness or the dynamics of spreading processes. In this paper, we study degree assortativity both…
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Characterization of monotone Boolean models supporting fixed points and multistability in balanced networks
Gene regulatory networks (GRN) control the expression levels of proteins in cells, and understanding their dynamics is key to potentially controlling disease processes. Steady states of GRNs are interpreted as cellular phenotypes, and the first step in understanding GRN dynamics is describing the…
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From atomic to global connectivity in the structure of the SARS-CoV2-human ACE2 receptor complex
We investigate connectivity properties of the SARS-CoV2 spike protein-human ACE2-receptor complex employing a protein side chain-based network method that allows us to span a range from atomic to global protein scales. We analyze network topology in terms of clusters and cliques obtained from…
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A typology of rules for knowledge exchange in higher-order interactions
Social learning is important to humans and other animals as they gather information about their environment. Information and behaviours can therefore spread rapidly through social networks as contagions. However, the way individuals acquire and use social information is highly variable and…
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A generalized Bayesian framework for maximizing information gain and model selection
Computational modelling of dynamical systems often involves many free parameters estimated from experimental data. The information gained from an experiment plays a crucial role in the goodness of predictions and parameter estimates. Optimal Experiment Design (OED) is typically used to choose an…
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Inference and training efficiency in pruned multilayer perceptron networks
This study explores how pruning strategies can improve the efficiency of deep neural networks (DNNs), which are widely used for tasks like image processing, medical diagnosis, etc. Although DNNs are powerful, they often contain weaker connections that can lead to increased energy consumption both…
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Bifurcation, sensitivity, and noise: Stochastic dynamics of cholera with vaccination and sanitation controls
This study develops the novel SVAITRS-B model, unifying deterministic and stochastic frameworks to capture cholera dynamics with vaccination, asymptomatic carriers, and environmental pathways. We demonstrate analytically that person-to-person transmission exhibits backward bifurcation, while…
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Algorithmic influence on conflict and cooperation in digital communities
This study focus on the contrasting dynamics of discussion and information dissemination on two influential platforms: X and Wikipedia. While X often serves as a battleground for contentious debates, where users engage in direct confrontation, Wikipedia fosters a collaborative environment aimed at…
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Research university assortativity conditions the integration of regional innovation systems
Substantial policy efforts to develop regional innovation systems (RIS) highlight the importance of understanding the institutional factors that promote integration and synergy at the regional scale. To this end, we analyzed historical patterns of research co-production within and across California…
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Weakly supervised contrastive representation learning to encode narrative viewpoint of COVID-19 tweets
Viewpoint detection is a crucial step for characterizing online narratives and understanding their diffusion and evolution across online social spaces. Existing methods for semantic understanding of online posts have shown strong progress towards grouping documents with similar topics but struggle…
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A green vehicle routing methodology for assessing optimal fleet mix and cost/emissions tradeoffs given environmental policy incentives
Transportation accounts for nearly one quarter of global greenhouse gas (GHG) emissions. A significant proportion of transportation emissions can be attributed to supply chain transport, which also represents the fastest-growing sector of emissions. As a way of addressing this challenge in the…
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Multiscale mobility: How the COVID-19 pandemic reshaped Mexico’s intermunicipal connectivity
Mobility networks are vital for economic activity, social interaction, and urban development, yet they remain highly vulnerable to external shocks. The COVID-19 pandemic profoundly disrupted human mobility, but most studies have focused on short-term responses or macroscopic patterns, leaving…
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A dynamic model of segregation and integration: Incorporating adaptive intolerance, media bias, and conformity into the Schelling framework
Thomas Schelling introduced his agent-based model of segregation in 1971 and concluded that even when there is a low amount of intolerance within society that segregation will develop if people follow their individual preferences. A large body of literature building of this framework has been built…
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Fast algorithms to improve fair information access in networks
We consider the problem of selecting k seed nodes in a network to maximize the minimum probability of activation under an independent cascade beginning at these seeds. The motivation is to promote fairness by ensuring that even the least advantaged members of the network have good access to…
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Can adversarial attacks by large language models be attributed?
Attributing outputs from Large Language Models (LLMs) in adversarial settings—such as cyberattacks and disinformation campaigns—presents significant challenges that are likely to grow in importance. We approach this attribution problem from both a theoretical and empirical perspective, drawing on…
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Cascades and convergence: Dynamic signal flow in a synapse-level brain network
Connectomes—maps of synaptic connectivity—constrain how signals flow through the nervous system, shaping the transmission of sensory information to downstream targets involved in perception, decision-making, and action. Here, we use a simple, network-based spreading model to simulate sensory signal…
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Towards a foundational platform for generative agents in simulated city environment
Urban environments, characterized by their complex, multi-layered networks encompassing physical, social, economic, and environmental dimensions, present significant challenges for sustainable urbanization. These challenges, ranging from traffic congestion and pollution to social inequality, call…
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Structural modeling of campaign finance decisions in the U.S. House of Representatives
Computational modeling and quantifying the drivers of modern political campaign finance is an emerging area of interest among researchers, policymakers, and the general public alike. In a federal legislative body like the U.S. House of Representatives, campaign finance decisions or “money flows”…