2026-10-10T14:19:30Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33967568 2026-09-22T17:34:03Z category_12 category_14 category_15 category_16 category_21 category_272 category_734 category_931 category_811 portal_5 item_type_3 month_year_09_2026

<p>Spearman and Pearson correlations between robustness index <i>R</i> and node-level indices in BA networks of varying sizes (<i>N</i> = 100, 1000, 10000, <i>m</i> = 2). Bold indicates the strongest (most negative) correlation for each network.</p> Masaki Chujyo (9964684) Shu Liu (160219) Fujio Toriumi (738862) Cell Biology Molecular Biology Neuroscience Physiology Biotechnology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified Mathematical Sciences not elsewhere classified standard centrality measures spatially localized failures pose significant threats capture key dynamics although previous studies topological position amplify world networks demonstrate evaluate average robustness single seed node network robustness degradation seed node position seed node network robustness structural position complex networks specific node node vulnerability study proposes severed links numerical experiments local connectivity level metric lavi provides lavi correlates lavi ), las ), la initiated generalizable indicator findings highlight cumulative number attack progression <p>Spearman and Pearson correlations between robustness index <i>R</i> and node-level indices in BA networks of varying sizes (<i>N</i> = 100, 1000, 10000, <i>m</i> = 2). Bold indicates the strongest (most negative) correlation for each network.</p> 2026-09-22T17:33:56Z Dataset Dataset 10.1371/journal.pone.0358769.t001 https://figshare.com/articles/dataset/_p_Spearman_and_Pearson_correlations_between_robustness_index_i_R_i_and_node-level_indices_in_BA_networks_of_varying_sizes_i_N_i_100_1000_10000_i_m_i_2_Bold_indicates_the_strongest_most_negative_correlation_for_each_network_p_/33967568 CC BY 4.0