The critical edges in complex networks are extraordinary edges which play more significant role than other edges on the structure and function of networks. The research on identifying critical edges in complex networks has attracted much attention because of its theoretical significance as well as wide range of applications. Considering the topological structure of networks and the ability to disseminate information, an edge ranking algorithm BCC based on cliques and paths in networks is proposed in this report. The effectiveness of the proposed method is evaluated by SIR model, susceptibility index S and the size of giant component σ and compared with well-known existing metrics such as Jaccard coefficient, Bridgeness index, Betweenness centrality and Reachability index in nine real networks. Experimental results show that the proposed method outperforms these well-known methods in identifying critical edges both in network connectivity and spreading dynamic.
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http://dx.doi.org/10.1038/s41598-018-32631-8 | DOI Listing |
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January 2025
Department of Chemistry, Indian Institute of Science Education and Research Bhopal, Bhopal, 462 066, India.
The structural and electronic changes are investigated in a 3D hybrid perovskite, methylhydrazinium lead chloride (MHyPbCl) from a host/guest perspective as it transitions from a highly polar to less polar phase upon cooling, using first-principles calculations. The two phases vary structurally in the guest (MHy) orientation and the two differently distorted host (lead halide) layers. These findings highlight the critical role of guest reorientation in reducing host distortion at high temperatures, making the former the primary order parameter for the transition, a notable contrast to the case of other hybrid perovskites.
View Article and Find Full Text PDFAtomic-scale changes can significantly impact heterogeneous catalysis, yet their atomic mechanisms are challenging to establish using conventional analysis methods. By using identical location scanning transmission electron microscopy (IL-STEM), which provides quantitative information at the single-particle level, we investigated the mechanisms of atomic evolution of Ru nanoclusters during the ammonia decomposition reaction. Nanometre-sized disordered nanoclusters transform into truncated nano-pyramids with stepped edges, leading to increased hydrogen production from ammonia.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Directorate for Railways, Nemanjina 6, 11000 Belgrade, Serbia.
The manuscript conducts a comparative analysis to assess the impact of noise on medical images using a proposed threshold value estimation approach. It applies an innovative method for edge detection on images of varying complexity, considering different noise types and concentrations of noise. Five edges are evaluated on images with low, medium, and high detail levels.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Biosciences and Bioinformatics, School of Science, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China.
Melatonin is a hormone released by the pineal gland that regulates the sleep-wake cycle. It has been widely studied for its therapeutic effects on Alzheimer's disease (AD), particularly through the amyloidosis, oxidative stress, and neuroinflammation pathways. Nevertheless, the mechanisms through which it exerts its neuroprotective effects in AD are still largely unknown.
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
The Institute of Cancer Research, London, United Kingdom.
Background: Deep learning (DL) has set new standards in cancer diagnosis, significantly enhancing the accuracy of automated classification of whole slide images (WSIs) derived from biopsied tissue samples. To enable DL models to process these large images, WSIs are typically divided into thousands of smaller tiles, each containing 10-50 cells. Multiple Instance Learning (MIL) is a commonly used approach, where WSIs are treated as bags comprising numerous tiles (instances) and only bag-level labels are provided during training.
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