{"id":"https://openalex.org/W4405649234","doi":"https://doi.org/10.3390/e26121113","title":"Sample Augmentation Using Enhanced Auxiliary Classifier Generative Adversarial Network by Transformer for Railway Freight Train Wheelset Bearing Fault Diagnosis","display_name":"Sample Augmentation Using Enhanced Auxiliary Classifier Generative Adversarial Network by Transformer for Railway Freight Train Wheelset Bearing Fault Diagnosis","publication_year":2024,"publication_date":"2024-12-20","ids":{"openalex":"https://openalex.org/W4405649234","doi":"https://doi.org/10.3390/e26121113","pmid":"https://pubmed.ncbi.nlm.nih.gov/39766742"},"language":"en","primary_location":{"id":"doi:10.3390/e26121113","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26121113","pdf_url":"https://www.mdpi.com/1099-4300/26/12/1113/pdf?version=1734677548","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/26/12/1113/pdf?version=1734677548","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065846668","display_name":"Jing Zhao","orcid":"https://orcid.org/0000-0003-0158-5330"},"institutions":[{"id":"https://openalex.org/I4210164386","display_name":"Hebei Science and Technology Department","ror":"https://ror.org/05k812a28","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210164386"]},{"id":"https://openalex.org/I90090648","display_name":"Shijiazhuang Tiedao University","ror":"https://ror.org/022e9e065","country_code":"CN","type":"education","lineage":["https://openalex.org/I90090648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Zhao","raw_affiliation_strings":["Hebei Province University Road Traffic Perception and Intelligent Application Technology Research and Development Center, Hebei Jiaotong Vocational and Technical College, Shijiazhuang 050011, China","School of Traffic and Transportation, Shijiazhuang Tiedao University, Shijiazhuang 050043, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei Province University Road Traffic Perception and Intelligent Application Technology Research and Development Center, Hebei Jiaotong Vocational and Technical College, Shijiazhuang 050011, China","institution_ids":["https://openalex.org/I4210164386"]},{"raw_affiliation_string":"School of Traffic and Transportation, Shijiazhuang Tiedao University, Shijiazhuang 050043, China","institution_ids":["https://openalex.org/I90090648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101930547","display_name":"Junfeng Li","orcid":"https://orcid.org/0000-0002-1207-3317"},"institutions":[{"id":"https://openalex.org/I186272606","display_name":"Guangdong University of Foreign Studies","ror":"https://ror.org/00fhc9y79","country_code":"CN","type":"education","lineage":["https://openalex.org/I186272606"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junfeng Li","raw_affiliation_strings":["School of Computer Science, South China Business College Guangdong University of Foreign Studies, Guangzhou 510545, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, South China Business College Guangdong University of Foreign Studies, Guangzhou 510545, China","institution_ids":["https://openalex.org/I186272606"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044127094","display_name":"Zonghao Yuan","orcid":"https://orcid.org/0000-0003-2600-5814"},"institutions":[{"id":"https://openalex.org/I94611258","display_name":"Hebei Normal University","ror":"https://ror.org/004rbbw49","country_code":"CN","type":"education","lineage":["https://openalex.org/I94611258"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zonghao Yuan","raw_affiliation_strings":["College of Career Technology, Hebei Normal University, Shijiazhuang 050043, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Career Technology, Hebei Normal University, Shijiazhuang 050043, China","institution_ids":["https://openalex.org/I94611258"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032019841","display_name":"Tianming Mu","orcid":"https://orcid.org/0009-0009-8319-1829"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tianming Mu","raw_affiliation_strings":["State Grid Shijiazhuang Electric Power Supply Company, Shijiazhuang 050021, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Grid Shijiazhuang Electric Power Supply Company, Shijiazhuang 050021, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008659742","display_name":"Zengqiang Ma","orcid":"https://orcid.org/0000-0002-2409-1977"},"institutions":[{"id":"https://openalex.org/I90090648","display_name":"Shijiazhuang Tiedao University","ror":"https://ror.org/022e9e065","country_code":"CN","type":"education","lineage":["https://openalex.org/I90090648"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zengqiang Ma","raw_affiliation_strings":["Hebei Provincial Collaborative Innovation Center of Transportation Power Grid Intelligent Integration Technology and Equipment, Shijiazhuang Tiedao University, Shijiazhuang 050043, China","School of Electrical and Electronic Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei Provincial Collaborative Innovation Center of Transportation Power Grid Intelligent Integration Technology and Equipment, Shijiazhuang Tiedao University, Shijiazhuang 050043, China","institution_ids":["https://openalex.org/I90090648"]},{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China","institution_ids":["https://openalex.org/I90090648"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034021327","display_name":"Suyan Liu","orcid":"https://orcid.org/0000-0003-0947-8222"},"institutions":[{"id":"https://openalex.org/I90090648","display_name":"Shijiazhuang Tiedao University","ror":"https://ror.org/022e9e065","country_code":"CN","type":"education","lineage":["https://openalex.org/I90090648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suyan Liu","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China","institution_ids":["https://openalex.org/I90090648"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5008659742"],"corresponding_institution_ids":["https://openalex.org/I90090648"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.3,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.60416,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"26","issue":"12","first_page":"1113","last_page":"1113"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11062","display_name":"Gear and Bearing Dynamics Analysis","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13213","display_name":"Mechanical Failure Analysis and Simulation","score":0.9613000154495239,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/computer-science","display_name":"Computer science","score":0.6813030242919922},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6592745184898376},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5527992844581604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.539379894733429},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.5141568183898926},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4959202706813812},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4955865144729614},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4366157054901123},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.41945287585258484},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41814109683036804},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1742652952671051}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6813030242919922},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6592745184898376},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5527992844581604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.539379894733429},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.5141568183898926},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4959202706813812},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4955865144729614},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4366157054901123},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.41945287585258484},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41814109683036804},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1742652952671051},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e26121113","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26121113","pdf_url":"https://www.mdpi.com/1099-4300/26/12/1113/pdf?version=1734677548","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:39766742","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39766742","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11675503","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11675503","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11675503/pdf/entropy-26-01113.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:60236d38b4434ed790278d827db09033","is_oa":true,"landing_page_url":"https://doaj.org/article/60236d38b4434ed790278d827db09033","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":"Entropy, Vol 26, Iss 12, p 1113 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/e26121113","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26121113","pdf_url":"https://www.mdpi.com/1099-4300/26/12/1113/pdf?version=1734677548","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6000000238418579,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G4964878788","display_name":null,"funder_award_id":"12393783","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7314785742","display_name":null,"funder_award_id":"12072207","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8237156517","display_name":null,"funder_award_id":"52205571","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405649234.pdf","grobid_xml":"https://content.openalex.org/works/W4405649234.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W2277064738","https://openalex.org/W2523408358","https://openalex.org/W2793164711","https://openalex.org/W2945520991","https://openalex.org/W2962907896","https://openalex.org/W2965875348","https://openalex.org/W2980902614","https://openalex.org/W2987480074","https://openalex.org/W3003598450","https://openalex.org/W3023920206","https://openalex.org/W3106914811","https://openalex.org/W3109842401","https://openalex.org/W3145770415","https://openalex.org/W3165603617","https://openalex.org/W3177031903","https://openalex.org/W3187725949","https://openalex.org/W3194185277","https://openalex.org/W3198999477","https://openalex.org/W3207531729","https://openalex.org/W3209564648","https://openalex.org/W4200049650","https://openalex.org/W4200069638","https://openalex.org/W4206612301","https://openalex.org/W4210741351","https://openalex.org/W4212861124","https://openalex.org/W4225016315","https://openalex.org/W4226454857","https://openalex.org/W4280516766","https://openalex.org/W4285064815","https://openalex.org/W4285195618","https://openalex.org/W4286377585","https://openalex.org/W4296473273","https://openalex.org/W4311734788","https://openalex.org/W4313612460","https://openalex.org/W4318035654","https://openalex.org/W4319990462","https://openalex.org/W4323050469","https://openalex.org/W4360994300","https://openalex.org/W4367146864","https://openalex.org/W4367663292","https://openalex.org/W4376491602","https://openalex.org/W4378637195","https://openalex.org/W4380740125","https://openalex.org/W4382197310","https://openalex.org/W4385819948","https://openalex.org/W4386317493","https://openalex.org/W4388107130","https://openalex.org/W4388692167","https://openalex.org/W4388734373","https://openalex.org/W4392355179","https://openalex.org/W4393346493","https://openalex.org/W4400457298"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W2387995142","https://openalex.org/W4380714744","https://openalex.org/W4319453655","https://openalex.org/W2596763562","https://openalex.org/W2964218010","https://openalex.org/W2808862658","https://openalex.org/W4324290231"],"abstract_inverted_index":{"Diagnosing":[0],"faults":[1],"in":[2,61,154,163],"wheelset":[3,44,179],"bearings":[4],"is":[5,13,139,149,161],"critical":[6],"for":[7,43],"train":[8,28,178],"safety.":[9],"The":[10,117],"main":[11],"challenge":[12],"that":[14,50],"only":[15],"a":[16],"limited":[17],"amount":[18],"of":[19,32,39,106,113,187],"fault":[20,46],"sample":[21],"data":[22],"can":[23],"be":[24],"obtained":[25],"during":[26],"high-speed":[27],"operations.":[29],"This":[30],"scarcity":[31],"samples":[33],"impacts":[34],"the":[35,51,90,101,111,114,143,147,155,158,164,177,183,188],"training":[36],"and":[37,79,92,104,109,128,152,171,185],"accuracy":[38,184],"deep":[40],"learning":[41],"models":[42,68],"bearing":[45,180],"diagnosis.":[47],"Studies":[48],"show":[49],"Auxiliary":[52,93],"Classifier":[53,94],"Generative":[54,95],"Adversarial":[55,96],"Network":[56,97],"(ACGAN)":[57],"demonstrates":[58],"promising":[59],"performance":[60],"addressing":[62],"this":[63,87],"issue.":[64],"However,":[65],"existing":[66],"ACGAN":[67],"have":[69],"drawbacks":[70],"such":[71],"as":[72],"complexity,":[73],"high":[74],"computational":[75,133],"expenses,":[76],"mode":[77,169],"collapse,":[78],"vanishing":[80,172],"gradients.":[81,173],"Aiming":[82],"to":[83,141,167],"address":[84],"these":[85],"issues,":[86],"paper":[88],"presents":[89],"Transformer":[91],"(TACGAN),":[98],"which":[99],"increases":[100],"diversity,":[102],"complexity":[103],"entropy":[105,112],"generated":[107,115],"samples,":[108],"maximizes":[110],"samples.":[116],"transformer":[118],"network":[119],"replaces":[120],"traditional":[121],"convolutional":[122,129],"neural":[123],"networks":[124],"(CNNs),":[125],"avoiding":[126],"iterative":[127],"structures,":[130],"thereby":[131],"reducing":[132],"expenses.":[134],"Moreover,":[135],"an":[136],"independent":[137],"classifier":[138],"integrated":[140],"prevent":[142],"coupling":[144],"problem,":[145],"where":[146],"discriminator":[148],"simultaneously":[150],"identified":[151],"classified":[153],"ACGAN.":[156],"Finally,":[157],"Wasserstein":[159],"distance":[160],"employed":[162],"loss":[165],"function":[166],"mitigate":[168],"collapse":[170],"Experimental":[174],"results":[175],"using":[176],"datasets":[181],"demonstrate":[182],"effectiveness":[186],"TACGAN.":[189]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}