{"id":"https://openalex.org/W2487418985","doi":"https://doi.org/10.1109/tsipn.2017.2731051","title":"Network Topology Inference from Spectral Templates","display_name":"Network Topology Inference from Spectral Templates","publication_year":2017,"publication_date":"2017-07-24","ids":{"openalex":"https://openalex.org/W2487418985","doi":"https://doi.org/10.1109/tsipn.2017.2731051","mag":"2487418985"},"language":"en","primary_location":{"id":"doi:10.1109/tsipn.2017.2731051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2017.2731051","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal and Information Processing over Networks","raw_type":"journal-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1608.03008","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012007074","display_name":"Santiago Segarra","orcid":"https://orcid.org/0000-0002-8408-9633"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Santiago Segarra","raw_affiliation_strings":["Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA","[Institute for Data Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]},{"raw_affiliation_string":"[Institute for Data Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA]","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054312245","display_name":"Antonio G. Marqu\u00e9s","orcid":"https://orcid.org/0000-0002-4642-7718"},"institutions":[{"id":"https://openalex.org/I182083151","display_name":"Universidad Rey Juan Carlos","ror":"https://ror.org/01v5cv687","country_code":"ES","type":"education","lineage":["https://openalex.org/I182083151"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio G. Marques","raw_affiliation_strings":["Department of Signal Theory and Communications, King Juan Carlos University, Madrid, Spain","[Dept. of Signal Theory and Communications, King Juan Carlos University, Madrid, Spain]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Signal Theory and Communications, King Juan Carlos University, Madrid, Spain","institution_ids":["https://openalex.org/I182083151"]},{"raw_affiliation_string":"[Dept. of Signal Theory and Communications, King Juan Carlos University, Madrid, Spain]","institution_ids":["https://openalex.org/I182083151"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006078163","display_name":"Gonzalo Mateos","orcid":"https://orcid.org/0000-0002-9847-6298"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gonzalo Mateos","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA","Dept. of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]},{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078862959","display_name":"Alejandro Ribeiro","orcid":"https://orcid.org/0000-0003-4230-9906"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alejandro Ribeiro","raw_affiliation_strings":["Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0278,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.74032539,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"3","issue":"3","first_page":"467","last_page":"483"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.7146879434585571},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5695290565490723},{"id":"https://openalex.org/keywords/spectral-graph-theory","display_name":"Spectral graph theory","score":0.5152955055236816},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.5012197494506836},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4986231327056885},{"id":"https://openalex.org/keywords/graph-property","display_name":"Graph property","score":0.4929771423339844},{"id":"https://openalex.org/keywords/graph-energy","display_name":"Graph energy","score":0.4828932285308838},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4620612859725952},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.4600934386253357},{"id":"https://openalex.org/keywords/piecewise","display_name":"Piecewise","score":0.42914900183677673},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.41585880517959595},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.408669650554657},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40288323163986206},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.3863326609134674},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3719100058078766},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.28183627128601074},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.18775859475135803},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1742723286151886}],"concepts":[{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.7146879434585571},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5695290565490723},{"id":"https://openalex.org/C74003402","wikidata":"https://www.wikidata.org/wiki/Q3180727","display_name":"Spectral graph theory","level":5,"score":0.5152955055236816},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.5012197494506836},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4986231327056885},{"id":"https://openalex.org/C64339825","wikidata":"https://www.wikidata.org/wiki/Q722659","display_name":"Graph property","level":5,"score":0.4929771423339844},{"id":"https://openalex.org/C78913703","wikidata":"https://www.wikidata.org/wiki/Q5597087","display_name":"Graph energy","level":5,"score":0.4828932285308838},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4620612859725952},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.4600934386253357},{"id":"https://openalex.org/C164660894","wikidata":"https://www.wikidata.org/wiki/Q2037833","display_name":"Piecewise","level":2,"score":0.42914900183677673},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.41585880517959595},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.408669650554657},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40288323163986206},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.3863326609134674},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3719100058078766},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.28183627128601074},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.18775859475135803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1742723286151886},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/tsipn.2017.2731051","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2017.2731051","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal and Information Processing over Networks","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1608.03008","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1608.03008","pdf_url":"https://arxiv.org/pdf/1608.03008","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"mag:2487418985","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1608.03008.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1608.03008","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1608.03008","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"},{"id":"doi:10.17023/j7d9-3e61","is_oa":true,"landing_page_url":"https://doi.org/10.17023/j7d9-3e61","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Audiovisual"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1608.03008","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1608.03008","pdf_url":"https://arxiv.org/pdf/1608.03008","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5099999904632568}],"awards":[{"id":"https://openalex.org/G8148415091","display_name":null,"funder_award_id":"CCF-1217963","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W305292912","https://openalex.org/W356566955","https://openalex.org/W390146837","https://openalex.org/W587265912","https://openalex.org/W1532325895","https://openalex.org/W1541479357","https://openalex.org/W1578099820","https://openalex.org/W1627852934","https://openalex.org/W1671906456","https://openalex.org/W1684305122","https://openalex.org/W1698699930","https://openalex.org/W1774304772","https://openalex.org/W1848983290","https://openalex.org/W1945792210","https://openalex.org/W1991252559","https://openalex.org/W1997301483","https://openalex.org/W2010192956","https://openalex.org/W2010824638","https://openalex.org/W2015208937","https://openalex.org/W2023722580","https://openalex.org/W2028781966","https://openalex.org/W2055234679","https://openalex.org/W2061042699","https://openalex.org/W2078204800","https://openalex.org/W2093184664","https://openalex.org/W2101491865","https://openalex.org/W2107861471","https://openalex.org/W2132555912","https://openalex.org/W2133280087","https://openalex.org/W2159929956","https://openalex.org/W2161763921","https://openalex.org/W2188959515","https://openalex.org/W2213622371","https://openalex.org/W2235146554","https://openalex.org/W2271729023","https://openalex.org/W2299462150","https://openalex.org/W2389980101","https://openalex.org/W2399508263","https://openalex.org/W2403074563","https://openalex.org/W2486096428","https://openalex.org/W2501990301","https://openalex.org/W2549164117","https://openalex.org/W2592129227","https://openalex.org/W2593690739","https://openalex.org/W2616297073","https://openalex.org/W2796728297","https://openalex.org/W2905110430","https://openalex.org/W2959406683","https://openalex.org/W2963089591","https://openalex.org/W2964012239","https://openalex.org/W3098834468","https://openalex.org/W4213009331","https://openalex.org/W4248241950","https://openalex.org/W6689213722","https://openalex.org/W6697883479","https://openalex.org/W6704098073","https://openalex.org/W6729699061","https://openalex.org/W6729995155","https://openalex.org/W6734267277"],"related_works":["https://openalex.org/W2962759781","https://openalex.org/W2101491865","https://openalex.org/W2338083618","https://openalex.org/W3134247470","https://openalex.org/W2383526906","https://openalex.org/W2612384513","https://openalex.org/W2886820621","https://openalex.org/W3015230325","https://openalex.org/W2789969078","https://openalex.org/W2295709124","https://openalex.org/W3015304892","https://openalex.org/W2469576045","https://openalex.org/W3022025362","https://openalex.org/W3138963025","https://openalex.org/W3114408794","https://openalex.org/W2271729023","https://openalex.org/W2978752232","https://openalex.org/W2890444536","https://openalex.org/W2890261666","https://openalex.org/W2991281977"],"abstract_inverted_index":{"We":[0],"address":[1],"the":[2,6,13,22,46,67,75,89,98,115,120,148,153,157,170,178,194,197],"problem":[3],"of":[4,8,15,60,74,92,143,187,196],"identifying":[5],"structure":[7],"an":[9],"undirected":[10],"graph":[11,24,61,68,94,108],"from":[12,36,55,88,138],"observation":[14],"signals":[16,95],"defined":[17],"on":[18,45,97],"its":[19,79],"nodes.":[20],"Fundamentally,":[21],"unknown":[23],"encodes":[25],"direct":[26],"relationships":[27,39],"between":[28],"signal":[29],"elements,":[30],"which":[31],"we":[32,132],"aim":[33],"to":[34,65,105],"recover":[35],"observable":[37],"indirect":[38],"generated":[40],"by":[41],"a":[42,107,185],"diffusion":[43],"process":[44],"graph.":[47],"The":[48,101],"fresh":[49],"look":[50],"advocated":[51],"here":[52],"leverages":[53],"concepts":[54],"convex":[56,141],"optimization":[57],"and":[58,156,161,203],"stationarity":[59],"signals,":[62],"in":[63,200],"order":[64],"identify":[66],"shift":[69,109],"operator":[70],"(a":[71],"matrix":[72,155],"representation":[73],"graph)":[76],"given":[77],"only":[78,168,184],"eigenvectors.":[80],"These":[81],"spectral":[82,117],"templates":[83,171],"can":[84],"be":[85],"obtained,":[86],"e.g.,":[87],"sample":[90],"covariance":[91],"independent":[93],"diffused":[96],"sought":[99],"network.":[100],"novel":[102],"idea":[103],"is":[104],"find":[106],"that,":[110],"while":[111],"being":[112],"consistent":[113],"with":[114,122],"provided":[116],"information,":[118],"endows":[119],"network":[121],"certain":[123],"desired":[124],"properties":[125],"such":[126],"as":[127],"sparsity.":[128],"To":[129],"that":[130],"end,":[131],"develop":[133],"efficient":[134],"inference":[135],"algorithms":[136,199],"stemming":[137],"provably":[139],"tight":[140],"relaxations":[142],"natural":[144],"nonconvex":[145],"criteria,":[146],"particularizing":[147],"results":[149],"for":[150],"two":[151],"shifts:":[152],"adjacency":[154],"normalized":[158],"Laplacian.":[159],"Algorithms":[160],"theoretical":[162],"recovery":[163],"conditions":[164],"are":[165,172,180,189],"developed":[166],"not":[167],"when":[169,177,183],"perfectly":[173],"known,":[174],"but":[175],"also":[176],"eigenvectors":[179],"noisy":[181],"or":[182],"subset":[186],"them":[188],"given.":[190],"Numerical":[191],"tests":[192],"showcase":[193],"effectiveness":[195],"proposed":[198],"recovering":[201],"synthetic":[202],"real-world":[204],"networks.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
