{"id":"https://openalex.org/W4415221923","doi":"https://doi.org/10.1109/jstars.2025.3622117","title":"KDAD: Knowledge Distillation-Based Anomaly Detection for Thermal Infrared Hyperspectral Image","display_name":"KDAD: Knowledge Distillation-Based Anomaly Detection for Thermal Infrared Hyperspectral Image","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4415221923","doi":"https://doi.org/10.1109/jstars.2025.3622117"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2025.3622117","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3622117","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2025.3622117","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031035100","display_name":"Enyu Zhao","orcid":"https://orcid.org/0000-0001-7165-1861"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Enyu Zhao","raw_affiliation_strings":["Center for Hyperspectral Imaging in Remote Sensing, Information Science and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0001-7165-1861","affiliations":[{"raw_affiliation_string":"Center for Hyperspectral Imaging in Remote Sensing, Information Science and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100396859","display_name":"Hao Zhang","orcid":"https://orcid.org/0000-0002-1396-8745"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhang","raw_affiliation_strings":["Center for Hyperspectral Imaging in Remote Sensing, Information Science and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Hyperspectral Imaging in Remote Sensing, Information Science and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108915481","display_name":"Nianxin Qu","orcid":null},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nianxin Qu","raw_affiliation_strings":["Center for Hyperspectral Imaging in Remote Sensing, Information Science and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":"https://orcid.org/0009-0003-6491-8486","affiliations":[{"raw_affiliation_string":"Center for Hyperspectral Imaging in Remote Sensing, Information Science and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yulei Wang","orcid":"https://orcid.org/0000-0001-6436-5883"},"institutions":[{"id":"https://openalex.org/I43313876","display_name":"Dalian Maritime University","ror":"https://ror.org/002b7nr53","country_code":"CN","type":"education","lineage":["https://openalex.org/I43313876"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yulei Wang","raw_affiliation_strings":["Center for Hyperspectral Imaging in Remote Sensing, Information Science and Technology College, Dalian Maritime University, Dalian, China"],"raw_orcid":"https://orcid.org/0000-0001-6436-5883","affiliations":[{"raw_affiliation_string":"Center for Hyperspectral Imaging in Remote Sensing, Information Science and Technology College, Dalian Maritime University, Dalian, China","institution_ids":["https://openalex.org/I43313876"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yongguang Zhao","orcid":"https://orcid.org/0000-0001-9820-9678"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongguang Zhao","raw_affiliation_strings":["Key Laboratory of Quantitative Remote Sensing Information Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9820-9678","affiliations":[{"raw_affiliation_string":"Key Laboratory of Quantitative Remote Sensing Information Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5031035100"],"corresponding_institution_ids":["https://openalex.org/I43313876"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":0.99,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83225094,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"18","issue":null,"first_page":"26515","last_page":"26529"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9449999928474426,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9449999928474426,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.8065000176429749},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7791000008583069},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6556000113487244},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6230000257492065},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5672000050544739},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4814999997615814},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45669999718666077},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4113999903202057},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4081000089645386},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.3959999978542328}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8065000176429749},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7791000008583069},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6556000113487244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.645799994468689},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6381999850273132},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6230000257492065},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5672000050544739},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4814999997615814},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45669999718666077},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4113999903202057},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4081000089645386},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36309999227523804},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.35510000586509705},{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.33869999647140503},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3368000090122223},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.326200008392334},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.30300000309944153},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.26969999074935913},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2694999873638153},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.2676999866962433},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26019999384880066},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.25870001316070557},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.2556000053882599},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.25279998779296875}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2025.3622117","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3622117","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:a4880127d77847b2ad858a19c22b4419","is_oa":true,"landing_page_url":"https://doaj.org/article/a4880127d77847b2ad858a19c22b4419","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 26515-26529 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2025.3622117","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3622117","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2253421619","display_name":null,"funder_award_id":"3132025270","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7167985160","display_name":null,"funder_award_id":"42271355","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W1991190032","https://openalex.org/W1999621311","https://openalex.org/W2004491663","https://openalex.org/W2024288510","https://openalex.org/W2040078680","https://openalex.org/W2047870694","https://openalex.org/W2261059368","https://openalex.org/W2288987301","https://openalex.org/W2295576075","https://openalex.org/W2507498837","https://openalex.org/W2590856740","https://openalex.org/W2592141703","https://openalex.org/W2972480129","https://openalex.org/W2979897847","https://openalex.org/W2983563481","https://openalex.org/W2987228832","https://openalex.org/W3124606680","https://openalex.org/W3133744039","https://openalex.org/W3137199127","https://openalex.org/W3212209618","https://openalex.org/W4205183250","https://openalex.org/W4212800897","https://openalex.org/W4289823735","https://openalex.org/W4292980177","https://openalex.org/W4296209273","https://openalex.org/W4306168147","https://openalex.org/W4319866034","https://openalex.org/W4321380750","https://openalex.org/W4322576350","https://openalex.org/W4360993974","https://openalex.org/W4367031974","https://openalex.org/W4385872037","https://openalex.org/W4386230621","https://openalex.org/W4386473214","https://openalex.org/W4387164664","https://openalex.org/W4387803381","https://openalex.org/W4390097224","https://openalex.org/W4391759484","https://openalex.org/W4391956372","https://openalex.org/W4394938982","https://openalex.org/W4398757530","https://openalex.org/W4400489219","https://openalex.org/W4401705603","https://openalex.org/W4403447984","https://openalex.org/W4404293573","https://openalex.org/W4404563053","https://openalex.org/W4404788389","https://openalex.org/W4405778764","https://openalex.org/W4405811876","https://openalex.org/W4408443016","https://openalex.org/W4408520875","https://openalex.org/W4408697629","https://openalex.org/W4409155249","https://openalex.org/W4410427580","https://openalex.org/W4411055304","https://openalex.org/W4411725778","https://openalex.org/W4412024819"],"related_works":[],"abstract_inverted_index":{"Autoencoder":[0],"(AE)":[1],"is":[2,92,141],"extensively":[3],"utilized":[4],"in":[5,68,72,94,205,225],"Hyperspectral":[6],"anomaly":[7,26,88,215,221,235,256],"detection":[8,47,89,216,222,236,261],"(HAD)":[9],"tasks":[10],"owing":[11],"to":[12,33,148,207,232],"the":[13,29,34,46,62,114,214],"robust":[14],"feature":[15],"extraction":[16],"and":[17,64,125,163,185,188,228,254],"image":[18,79],"reconstruction":[19],"capabilities.":[20],"However,":[21],"AE":[22,132,156,162],"lacks":[23],"constraints":[24,210],"on":[25,144,211,241],"samples":[27],"during":[28],"training":[30],"process,":[31],"leading":[32],"reconstruct":[35],"part":[36],"of":[37,123,268],"some":[38],"anomalies":[39],"alongside":[40],"background":[41,150,251],"features,":[42],"which":[43],"ultimately":[44],"diminishes":[45],"accuracy;":[48],"additionally,":[49],"most":[50],"existing":[51,269],"HAD":[52],"algorithms":[53],"have":[54],"been":[55],"specifically":[56],"designed":[57],"for":[58,75],"data":[59],"captured":[60],"within":[61,237],"visible":[63],"near-infrared":[65],"bands,":[66],"resulting":[67],"a":[69,85,105,110,129,136,154,171,190],"notable":[70],"gap":[71],"methodologies":[73],"tailored":[74],"thermal":[76,99,242],"infrared":[77,100,243],"hyperspectral":[78,101,244],"(TIHSI).":[80],"To":[81],"address":[82],"these":[83],"issues,":[84],"knowledge":[86],"distillation-based":[87],"(KDAD)":[90],"model":[91,112,157],"proposed":[93],"this":[95],"study":[96],"aimed":[97],"at":[98],"data.":[102],"KDAD":[103,248],"constructs":[104,189],"spatial":[106,126],"information":[107],"map":[108],"utilizing":[109],"dual-window":[111],"through":[113,182],"spectral-spatial":[115],"fusion":[116,122],"module":[117,139,217],"(SSFM),":[118],"thereby":[119],"enabling":[120],"simultaneous":[121],"spectral":[124],"features":[127],"via":[128],"collaborative":[130],"stacked":[131],"with":[133,200],"dual":[134],"branches;":[135],"residual":[137],"enhancement":[138],"(REM)":[140],"introduced":[142],"based":[143],"transfer":[145],"learning":[146],"techniques":[147,227],"achieve":[149],"purification":[151],"while":[152],"forming":[153],"distillation":[155],"comprising":[158],"an":[159,164,220],"efficient":[160],"student":[161],"intricate":[165],"teacher":[166],"AE;":[167],"meanwhile,":[168],"REM":[169],"incorporates":[170],"clustering":[172,186,226],"weight":[173,192],"generation":[174],"mechanism":[175],"that":[176,247,267],"facilitates":[177],"pixel":[178],"density-aware":[179],"category":[180],"division":[181],"dimensionality":[183],"reduction":[184],"processes,":[187],"background-enhanced":[191],"matrix":[193],"by":[194],"integrating":[195],"Mahalanobis":[196],"distance":[197],"tensor":[198],"analysis":[199],"dynamic":[201],"threshold":[202],"adjustment":[203],"strategy":[204],"order":[206],"enforce":[208],"prior":[209],"anomalies;":[212],"finally,":[213],"(ADM)":[218],"formulates":[219],"process":[223],"grounded":[224],"cosine":[229],"similarity":[230],"metrics":[231],"facilitate":[233],"high-precision":[234],"TI_HSIs.":[238],"Experimental":[239],"results":[240],"datasets":[245],"indicate":[246],"markedly":[249],"enhances":[250],"suppression":[252],"capability":[253],"improves":[255],"localization":[257],"accuracy.":[258],"Furthermore,":[259],"its":[260],"performance":[262],"across":[263],"various":[264],"scenarios":[265],"outperforms":[266],"algorithms.":[270]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-16T00:00:00"}
