We thoroughly study the robustness of partially interdependent networks when suffering attack combinations of random, targeted, and localized attacks. We compare analytically and numerically the robustness of partially interdependent networks with a broad range of parameters including coupling strength, attack strength, and network type. We observe the first and second order phase transition and accurately characterize the critical points for each combined attack. Generally, combined attacks show more efficient damage to interdependent networks. Besides, we find that, when robustness is measured by the critical removing ratio and the critical coupling strength, the conclusion drawn for a combined attack is not always consistent.
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http://dx.doi.org/10.1063/1.5085850 | DOI Listing |
Heliyon
December 2024
North China University of Water Resources and Electric Power, Zhengzhou, Henan, 450011, PR China.
In the domain of stock price prediction, the intricate interdependencies within multivariate time series data present significant challenges for accurate forecasting. This paper introduces a groundbreaking hybrid preprocessing technique to tackle this issue. By leveraging the Empirical Wavelet Transform (EWT), we adeptly extract both low-frequency and high-frequency components from the time series.
View Article and Find Full Text PDFFront Glob Womens Health
December 2024
Human Development and Family Science, Virginia Tech, Blacksburg, VA, United States.
Rationale: Over 11 million people in the United States provide care for an older family member with dementia, with this responsibility primarily falling on daughters and wives. In Appalachia, a mountainous region in the U.S characterized by close families, family members were crucial to ensuring that care needs were met for people living with dementia during the COVID-19 pandemic.
View Article and Find Full Text PDFBMC Nurs
December 2024
Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Background: Nurse burnout and turnover intention significantly impact global healthcare systems, especially intensified by the COVID-19 pandemic. This study employs network analysis to explore these phenomena, providing insights into the interdependencies and potential intervention points within the constructs of burnout and turnover intention among nurses.
Methods: A cross-sectional study was conducted with 560 nurses from three tertiary hospitals in Hangzhou, China.
Sensors (Basel)
November 2024
Graduate School of Information Science, University of Hyogo, Kobe 650-0047, Japan.
Early detection and precise characterization of brain tumors play a crucial role in improving patient outcomes and extending survival rates. Among neuroimaging modalities, magnetic resonance imaging (MRI) is the gold standard for brain tumor diagnostics due to its ability to produce high-contrast images across a variety of sequences, each highlighting distinct tissue characteristics. This study focuses on enabling multimodal MRI sequences to advance the automatic segmentation of low-grade astrocytomas, a challenging task due to their diffuse and irregular growth patterns.
View Article and Find Full Text PDFPsychotherapy (Chic)
December 2024
School of Family Life, Brigham Young University.
We investigated insecure attachment in relation to how actively romantic partners expect to participate in couple therapy (role expectations for self and partner) and, consequently, how much they expect to benefit from doing so (outcome expectations). Specifically, we used the mediated actor-partner interdependence model (Ledermann et al., 2011) with archived data from 297 heterosexual couples in a research-practice network (L.
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