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In complex dynamical networks, the resilience of the individual nodes against perturbation and their influence on the network dynamics are of great interest and have been actively investigated. We consider situations where the coupling dynamics are separable, which arise in certain classes of dynamical processes including epidemic spreading, population dynamics, and regulatory processes, and derive the algebraic scaling relations characterizing the nodal resilience and influence. Utilizing synthetic and empirical networks of different topologies, we numerically verify the scaling associated with the dynamical processes. Our results provide insights into the interplay between network topology and dynamics for the class of processes with separable coupling functions.
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http://dx.doi.org/10.1063/5.0254365 | DOI Listing |
Sci Rep
August 2025
School of Electrical and Electronic Engineering, Shandong University of Technology, Zhangdian District, Zibo, 255000, People's Republic of China.
This paper proposes a unified data-driven framework for topology identification, risk quantification, and reconfiguration optimization in power distribution networks under incomplete and fragmented observability. Motivated by real-world challenges where asset metadata, SCADA records, GIS layouts, and dispatcher logs are misaligned or incomplete, the proposed approach reconstructs network topology using a graph convolutional network (GCN) that fuses heterogeneous data attributes and learns structural representations from partial connectivity information. On the inferred topology, a scenario-based risk evaluation model is formulated to capture both local fragility and spatial risk propagation, integrating factors such as load stress, asset aging, and nodal redundancy into a unified zone-level risk index.
View Article and Find Full Text PDFFront Pharmacol
July 2025
Department of Community Medicine, Nodal Officer, Kerala One Health Centre for Nipah Research and Resilience, Kozhikode, Kerala, India.
Background: The and medicines at households are often disposed of improperly, which has harmful environmental impacts. Health hazards like antimicrobial resistance can occur. A home/household-based medicine reverse logistics system can avoid improper disposal of medicine waste, and it can recover any remaining value from end-of-use medicines.
View Article and Find Full Text PDFJ Particip Med
August 2025
Fordham University, 20 Grasmere Ave, Fairfield, CT, 06824, United States, (212) 280-1600.
Humanity stands at the threshold of a new era in biological understanding, disease treatment, and overall wellness. The convergence of evolving patient and caregiver (consumer) behaviors, increased data collection, advancements in health technology and standards, federal policies, and the rise of artificial intelligence (AI) is driving one of the most significant transformations in human history. To achieve transformative health care insights, AI must have access to comprehensive longitudinal health records (LHRs) that span clinical, genomic, nonclinical, wearable, and patient-generated data.
View Article and Find Full Text PDFTrans R Soc Trop Med Hyg
July 2025
School of Public Health, Kerala University of Health Sciences, Thiruvananthapuram, Kerala, India 695011.
Background: The world is witnessing the emergence of infections transmitted by Aedes mosquitoes. However, preventing large outbreaks challenges the health systems of endemic countries. Targeting infected adult Aedes mosquitoes may be a better means for resource-constrained health systems where integrated vector control may be less feasible.
View Article and Find Full Text PDFBrain Commun
June 2025
Stroke Research Group, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva 1205, Switzerland.
Strokes lead to widespread network changes that are associated with functional deficits and subsequent recovery. Beyond function, we hypothesize in this study that stroke-induced reorganization of brain connectivity increases network resilience against recurrent events, as an adaptive mechanism to limit the functional consequences of a new lesion. We used a dataset of 75 first-time stroke patients with resting-state functional connectivity assessed at 3 time-points within 1 year of stroke to determine whether brain networks of stroke patients become more resistant to recurrent lesions.
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