{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T14:45:35Z","timestamp":1764859535754,"version":"3.37.3"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"16","license":[{"start":{"date-parts":[[2023,5,12]],"date-time":"2023-05-12T00:00:00Z","timestamp":1683849600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,5,12]],"date-time":"2023-05-12T00:00:00Z","timestamp":1683849600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61672338","61873160"],"award-info":[{"award-number":["61672338","61873160"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soft Comput"],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1007\/s00500-023-08220-x","type":"journal-article","created":{"date-parts":[[2023,5,12]],"date-time":"2023-05-12T13:02:44Z","timestamp":1683896564000},"page":"11647-11660","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["CTDM: cryptocurrency abnormal transaction detection method with spatio-temporal and global representation"],"prefix":"10.1007","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4165-5583","authenticated-orcid":false,"given":"Lijun","family":"Xiao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8861-5461","authenticated-orcid":false,"given":"Dezhi","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1986-7144","authenticated-orcid":false,"given":"Dun","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ce","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1381-4364","authenticated-orcid":false,"given":"Kuan-Ching","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arcangelo","family":"Castiglione","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,5,12]]},"reference":[{"key":"8220_CR1","doi-asserted-by":"crossref","unstructured":"Alarab I, Prakoonwit S, Nacer MI (2020) Competence of graph convolutional networks for anti-money laundering in bitcoin blockchain. In: Proceedings of the 2020 5th international conference on machine learning technologies, pp 23\u201327","DOI":"10.1145\/3409073.3409080"},{"key":"8220_CR2","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1016\/j.patrec.2019.11.036","volume":"131","author":"AS Ashour","year":"2020","unstructured":"Ashour AS, El-Attar A, Dey N, Abd El-Kader H, Abd El-Naby MM (2020) Long short term memory based patient-dependent model for fog detection in Parkinson\u2019s disease. Pattern Recognit Lett 131:23\u201329","journal-title":"Pattern Recognit Lett"},{"key":"8220_CR3","doi-asserted-by":"crossref","unstructured":"Attia O, Khoufi I., Laouiti A, Adjih C (2019) An iot-blockchain architecture based on hyperledger framework for health care monitoring application. In: NTMS 2019-10th IFIP international conference on new technologies, mobility and security. IEEE Computer Society, pp 1\u20135","DOI":"10.1109\/NTMS.2019.8763849"},{"key":"8220_CR4","doi-asserted-by":"crossref","unstructured":"Cai S, Han D, Yin X, Li D, Chang C-C (2022a) A hybrid parallel deep learning model for efficient intrusion detection based on metric learning. Connect Sci 34:551\u2013577","DOI":"10.1080\/09540091.2021.2024509"},{"key":"8220_CR5","doi-asserted-by":"crossref","unstructured":"Cai S, Han D, Li D, Zheng Z, Crespi N (2022b) An reinforcement learning-based speech censorship chatbot system. J Supercomput, 78:8751\u20138773","DOI":"10.1007\/s11227-021-04251-z"},{"key":"8220_CR6","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2021.3092204","author":"X Chen","year":"2017","unstructured":"Chen X, Liang W et al (2017) An efficient service recommendation algorithm for cyber-physical-social systems. Trans Netw Sci Eng. https:\/\/doi.org\/10.1109\/TNSE.2021.3092204","journal-title":"Trans Netw Sci Eng"},{"key":"8220_CR7","doi-asserted-by":"publisher","first-page":"1158","DOI":"10.1109\/JSYST.2022.3197447","volume":"17","author":"S Cai","year":"2023","unstructured":"Cai S, Han D, Li D (2023) A feedback semi-supervised learning with meta-gradient for intrusion detection. IEEE Syst J 17:1158\u20131169","journal-title":"IEEE Syst J"},{"key":"8220_CR8","unstructured":"Cheng Z, Hou X, Li R, Zhou Y, Luo X, Li J, Ren K (2019) Towards a first step to understand the cryptocurrency stealing attack on ethereum. In: 22nd international symposium on research in attacks, intrusions and defenses (RAID 2019), pp 47\u201360"},{"key":"8220_CR9","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3140229","author":"C Diao","year":"2022","unstructured":"Diao C, Zhang D et al (2022) A novel spatial-temporal multi-scale alignment graph neural network security model for vehicles prediction. IEEE Trans Intell Transp Syst. https:\/\/doi.org\/10.1109\/TITS.2022.3140229","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"3","key":"8220_CR10","doi-asserted-by":"publisher","first-page":"3231","DOI":"10.1007\/s11042-022-13240-0","volume":"82","author":"F Feng","year":"2023","unstructured":"Feng F, Yang E et al (2023) A novel oversampling and feature selection hybrid algorithm for imbalanced data classification. Multimed Tools Appl 82(3):3231\u20133267. https:\/\/doi.org\/10.1007\/s11042-022-13240-0","journal-title":"Multimed Tools Appl"},{"issue":"1","key":"8220_CR11","doi-asserted-by":"publisher","first-page":"1929","DOI":"10.1080\/09540091.2022.2088698","volume":"34","author":"J Fu","year":"2022","unstructured":"Fu J, Cao B, Wang X, Zeng P, Liang W, Liu Y (2022) BFS: a blockchain-based financing scheme for logistics company in supply chain finance. Connect Sci 34(1):1929\u20131955","journal-title":"Connect Sci"},{"key":"8220_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2022.108527","volume":"172","author":"N Gao","year":"2022","unstructured":"Gao N, Han D, Weng T-H, Xia B, Li D, Castiglione A, Li K-C (2022) Modeling and analysis of port supply chain system based on fabric blockchain. Comput Ind Eng 172:108527","journal-title":"Comput Ind Eng"},{"key":"8220_CR13","unstructured":"Gao H, Ji S (2019) Graph u-nets. In: International conference on machine learning, PMLR, pp 2083\u20132092"},{"key":"8220_CR14","doi-asserted-by":"crossref","unstructured":"Gao C, Zhu J, Zhang F, Wang Z, Li X (2022) A novel representation learning for dynamic graphs based on graph convolutional networks. IEEE Trans Cybern","DOI":"10.1109\/TCYB.2022.3159661"},{"key":"8220_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.06.024","volume":"187","author":"P Goyal","year":"2020","unstructured":"Goyal P, Chhetri SR, Canedo A (2020) dyngraph2vec: Capturing network dynamics using dynamic graph representation learning. Knowl-Based Syst 187:104816","journal-title":"Knowl-Based Syst"},{"key":"8220_CR16","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1016\/j.asoc.2019.03.057","volume":"79","author":"AM Grachev","year":"2019","unstructured":"Grachev AM, Ignatov DI, Savchenko AV (2019) Compression of recurrent neural networks for efficient language modeling. Appl Soft Comput 79:354\u2013362","journal-title":"Appl Soft Comput"},{"key":"8220_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2022.102775","author":"N Hu","year":"2022","unstructured":"Hu N, Zhang D, Xie K et al (2022) Multi-range bidirectional mask graph convolution based GRU networks for traffic prediction. J Syst Archit. https:\/\/doi.org\/10.1016\/j.sysarc.2022.102775","journal-title":"J Syst Archit"},{"key":"8220_CR18","doi-asserted-by":"crossref","unstructured":"James J, Hawthorne D, Duncan K, Leger ASt, Sagisi J, Collins (2019) An experimental framework for investigating hashgraph algorithm transaction speed. In: Proceedings of the 2nd workshop on blockchain-enabled networked sensor, pp 15\u201321","DOI":"10.1145\/3362744.3363342"},{"key":"8220_CR19","doi-asserted-by":"crossref","unstructured":"Jullum M, L\u00f8land A, Huseby RB, \u00c5nonsen G, Lorentzen J (2020) Detecting money laundering transactions with machine learning. J Money Laund Control 23(1):173\u2013186","DOI":"10.1108\/JMLC-07-2019-0055"},{"key":"8220_CR20","unstructured":"Kipf TN, Welling M (2016) Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907"},{"key":"8220_CR21","first-page":"1","volume":"2021","author":"M Li","year":"2021","unstructured":"Li M, Han D, Yin X, Liu H, Li D (2021) Design and implementation of an anomaly network traffic detection model integrating temporal and spatial features. Secur Commun Netw 2021:1\u201315","journal-title":"Secur Commun Netw"},{"key":"8220_CR22","first-page":"24","volume":"00","author":"D Li","year":"2022","unstructured":"Li D, Han D, Xia B, Weng T-H, Castiglione A, Li K-C (2022) Fabric-GC: a blockchain-based Gantt chart system for cross-organizational project management. Comput Sci Inf Syst 00:24\u201324","journal-title":"Comput Sci Inf Syst"},{"key":"8220_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2022.12.037","author":"J Li","year":"2022","unstructured":"Li J, Han D et al (2022) A novel system for medical equipment supply chain traceability based on alliance chain and attribute and role access control. Future Gener Comput Syst. https:\/\/doi.org\/10.1016\/j.future.2022.12.037","journal-title":"Future Gener Comput Syst"},{"issue":"9","key":"8220_CR24","doi-asserted-by":"publisher","first-page":"4423","DOI":"10.1007\/s00500-021-06496-5","volume":"26","author":"D Li","year":"2022","unstructured":"Li D, Han D et al (2022) Blockchain for federated learning toward secure distributed machine learning systems: a systemic survey. Soft Comput 26(9):4423\u20134440","journal-title":"Soft Comput"},{"key":"8220_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.csi.2021.103597","volume":"81","author":"D Li","year":"2022","unstructured":"Li D, Han D et al (2022) MOOCschain: a blockchain-based secure storage and sharing scheme for MOOCs learning. Comput Stand Interfaces 81:103597","journal-title":"Comput Stand Interfaces"},{"key":"8220_CR26","doi-asserted-by":"publisher","first-page":"14741","DOI":"10.1109\/JIOT.2021.3053842","volume":"9","author":"W Liang","year":"2021","unstructured":"Liang W, Xiao L, Zhang K, Tang M, He D, Li K (2021) Data fusion approach for collaborative anomaly intrusion detection in blockchain-based systems. IEEE Internet Things J 9:14741\u201314751","journal-title":"IEEE Internet Things J"},{"key":"8220_CR27","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2022.3156266","author":"W Liang","year":"2022","unstructured":"Liang W, Li Y, Xie K et al (2022) Spatial-temporal aware inductive graph neural network for C-ITS data recovery. IEEE Tran Intell Transp Syst. https:\/\/doi.org\/10.1109\/TITS.2022.3156266","journal-title":"IEEE Tran Intell Transp Syst"},{"key":"8220_CR28","doi-asserted-by":"publisher","unstructured":"Liang W,Yang Y (2020) Pdpchain: a consortium blockchain-based privacy protection scheme for personal data. IEEE Trans Reliab. https:\/\/doi.org\/10.1109\/TR.2022.3190932","DOI":"10.1109\/TR.2022.3190932"},{"key":"8220_CR29","doi-asserted-by":"crossref","unstructured":"Liang W, Yang Y, Yang C, Hu Y, Xie S, Li K-C, Cao J (2022) Pdpchain: a consortium blockchain-based privacy protection scheme for personal data. IEEE Trans Reliab","DOI":"10.1109\/TR.2022.3190932"},{"key":"8220_CR30","doi-asserted-by":"crossref","unstructured":"Li Y, Cai Y, Tian H, Xue G, Zheng Z (2020) Identifying illicit addresses in bitcoin network. In: International conference on blockchain and trustworthy systems, Springer, pp 99\u2013111","DOI":"10.1007\/978-981-15-9213-3_8"},{"key":"8220_CR31","doi-asserted-by":"crossref","unstructured":"Li X, Cao X, Qiu X, Zhao J, Zheng J (2017) Intelligent anti-money laundering solution based upon novel community detection in massive transaction networks on spark. In: Fifth international conference on advanced cloud and big data (CBD). IEEE, pp 176\u2013181","DOI":"10.1109\/CBD.2017.38"},{"key":"8220_CR32","doi-asserted-by":"crossref","unstructured":"Li D,Han D, Liu H (2020) Fabric-chain & chain: a blockchain-based electronic document system for supply chain finance. In: International conference on blockchain and trustworthy systems","DOI":"10.1007\/978-981-15-9213-3_46"},{"key":"8220_CR33","doi-asserted-by":"crossref","unstructured":"Li D, Han D, Zheng Z, Weng T, Li K, Li M, Cai S (2023) Does short-and-distort scheme really exist? a bitcoin futures audit scheme through birch and bpnn approach. Comput Econ 1\u201323","DOI":"10.1007\/s10614-023-10378-3"},{"key":"8220_CR34","doi-asserted-by":"publisher","unstructured":"Liu H, Han D et al (2023) IdenMultiSig: identity-based decentralized multisignature in internet of things. IEEE Transactions on Computational Social Systems. https:\/\/doi.org\/10.1109\/TCSS.2022.3232173","DOI":"10.1109\/TCSS.2022.3232173"},{"issue":"2","key":"8220_CR35","first-page":"2261","volume":"69","author":"Y Liu","year":"2021","unstructured":"Liu Y, Wang X, She X, Yi M, Li Y, Jiang F (2021) Design of intelligent mosquito nets based on deep learning algorithms. Comput Mater Contin 69(2):2261\u20132276","journal-title":"Comput Mater Contin"},{"key":"8220_CR36","doi-asserted-by":"crossref","unstructured":"Lorenz J, Silva MI, Apar\u00edcio D, Ascens\u00e3o JT, Bizarro P (2020) Machine learning methods to detect money laundering in the bitcoin blockchain in the presence of label scarcity. In: Proceedings of the first ACM international conference on AI in finance, pp 1\u20138","DOI":"10.1145\/3383455.3422549"},{"key":"8220_CR37","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13638-022-02180-w","volume":"2022","author":"X Lv","year":"2022","unstructured":"Lv X, Han D, Li D, Xiao L, Chang CC (2022) Network abnormal traffic detection method based on fusion of chord similarity and multiple loss encoder. EURASIP J Wirel Commun Netw 2022:1\u201321","journal-title":"EURASIP J Wirel Commun Netw"},{"key":"8220_CR38","doi-asserted-by":"crossref","unstructured":"Monamo PM, Marivate V, Twala B (2016) A multifaceted approach to bitcoin fraud detection: global and local outliers. In: 2016 15th IEEE international conference on machine learning and applications (ICMLA), IEEE, pp 188\u2013194","DOI":"10.1109\/ICMLA.2016.0039"},{"key":"8220_CR39","unstructured":"Nakamoto S (2008) Bitcoin: a peer-to-peer electronic cash system. Decentralized Bus Rev, p 21260"},{"key":"8220_CR40","doi-asserted-by":"crossref","unstructured":"Oh B, Jun TJ, Yoon W, Lee Y, Kim S, Kim D (2019) Enhancing trust of supply chain using blockchain platform with robust data model and verification mechanisms. In: 2019 IEEE international conference on systems, man and cybernetics (SMC), IEEE, pp 3504\u20133511","DOI":"10.1109\/SMC.2019.8913871"},{"key":"8220_CR41","doi-asserted-by":"crossref","unstructured":"Pareja A, Domeniconi G, Chen J, Ma T, Suzumura T, Kanezashi H, Kaler T, Schardl T, Leiserson C (2020) Evolvegcn: evolving graph convolutional networks for dynamic graphs. In: Proceedings of the AAAI conference on artificial intelligence, vol 34(04). pp 5363\u20135370","DOI":"10.1609\/aaai.v34i04.5984"},{"key":"8220_CR42","unstructured":"Qian W, Shao Q, Zhu Y, Jin C, Zhou A (2018) Research problems and methods in blockchain and trusted data management. J Softw 29(1):150\u2013159"},{"issue":"3","key":"8220_CR43","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1016\/j.eng.2019.12.012","volume":"6","author":"K Ren","year":"2020","unstructured":"Ren K, Zheng T, Qin Z, Liu X (2020) Adversarial attacks and defenses in deep learning. Engineering 6(3):346\u2013360","journal-title":"Engineering"},{"key":"8220_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.csi.2022.103674","volume":"84","author":"PK Roy","year":"2023","unstructured":"Roy PK, Tripathy AK et al (2023) Securing social platform from misinformation using deep learning. Comput Stand Interfaces 84:103674","journal-title":"Comput Stand Interfaces"},{"issue":"1","key":"8220_CR45","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1109\/TNN.2008.2005605","volume":"20","author":"F Scarselli","year":"2008","unstructured":"Scarselli F, Gori M, Tsoi AC, Hagenbuchner M, Monfardini G (2008) The graph neural network model. IEEE Trans Neural Networks 20(1):61\u201380","journal-title":"IEEE Trans Neural Networks"},{"issue":"1","key":"8220_CR46","doi-asserted-by":"publisher","first-page":"780","DOI":"10.1007\/s10489-021-02453-9","volume":"52","author":"X Sun","year":"2022","unstructured":"Sun X, Yang T, Hu B (2022) LSTM-TC: Bitcoin coin mixing detection method with a high recall. Appl Intell 52(1):780\u2013793","journal-title":"Appl Intell"},{"key":"8220_CR47","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13638-022-02122-6","volume":"2022","author":"Z Sun","year":"2022","unstructured":"Sun Z, Han D, Li D, Wang X, Chang CC, Wu Z (2022) A blockchain-based secure storage scheme for medical information. EURASIP J Wirel Commun Netw 2022:1\u201325","journal-title":"EURASIP J Wirel Commun Netw"},{"key":"8220_CR48","unstructured":"Weber M, Domeniconi G, Chen J, Weidele DKI, Bellei C, Robinson T, Leiserson CE (2019) Anti-money laundering in bitcoin: experimenting with graph convolutional networks for financial forensics. arXiv preprint arXiv:1908.02591,"},{"key":"8220_CR49","unstructured":"Wood KP (2014) Anti-money laundering in banking an enterprise-wide risk approach. Ph.D. dissertation, Utica College,"},{"issue":"2020","key":"8220_CR50","first-page":"1156","volume":"52","author":"J Wu","year":"2020","unstructured":"Wu J, Yuan Q, Lin D, You W, Chen W, Chen C, Zheng Z (2020) Who are the phishers? phishing scam detection on ethereum via network embedding. IEEE Tran Syst Man Cybern Syst 52(2020):1156\u20131166","journal-title":"IEEE Tran Syst Man Cybern Syst"},{"key":"8220_CR51","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2021.103139","volume":"190","author":"J Wu","year":"2021","unstructured":"Wu J, Liu J, Zhao Y, Zheng Z (2021) Analysis of cryptocurrency transactions from a network perspective: an overview. J Netw Comput Appl 190:103139","journal-title":"J Netw Comput Appl"},{"issue":"2021","key":"8220_CR52","first-page":"2237","volume":"52","author":"J Wu","year":"2021","unstructured":"Wu J, Liu J, Chen W, Huang H, Zheng Z, Zhang Y (2021) Detecting mixing services via mining bitcoin transaction network with hybrid motifs. IEEE Trans Syst Man Cybern Syst 52(2021):2237\u20132249","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"8220_CR53","unstructured":"Wu S, Wang D, He J, Zhou Y, Wu L, Yuan X, He Q, Ren K (2021) Defiranger: detecting price manipulation attacks on defi applications. arXiv preprint arXiv:2104.15068"},{"issue":"10","key":"8220_CR54","doi-asserted-by":"publisher","first-page":"7118","DOI":"10.1109\/TII.2021.3129631","volume":"18","author":"Z Xu","year":"2022","unstructured":"Xu Z, Liang W et al (2022) A time-sensitive token-based anonymous authentication and dynamic group key agreement scheme for industry 5.0. IEEE Trans Ind Inform 18(10):7118\u20137127. https:\/\/doi.org\/10.1109\/TII.2021.3129631","journal-title":"IEEE Trans Ind Inform"},{"key":"8220_CR55","doi-asserted-by":"publisher","first-page":"415","DOI":"10.1016\/j.neucom.2019.09.110","volume":"397","author":"Z Yang","year":"2020","unstructured":"Yang Z, Mourshed M, Liu K, Xu X, Feng S (2020) A novel competitive swarm optimized RBF neural network model for short-term solar power generation forecasting. Neurocomputing 397:415\u2013421","journal-title":"Neurocomputing"},{"key":"8220_CR56","doi-asserted-by":"publisher","first-page":"3147","DOI":"10.1109\/TCYB.2020.3005047","volume":"52","author":"Q Zhang","year":"2020","unstructured":"Zhang Q, Yang S, Liu M, Liu J, Jiang L (2020) A new crossover mechanism for genetic algorithms for Steiner tree optimization. IEEE Trans Cybern 52:3147\u20133158","journal-title":"IEEE Trans Cybern"},{"issue":"3","key":"8220_CR57","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1007\/s11633-016-1006-2","volume":"13","author":"G-B Zhou","year":"2016","unstructured":"Zhou G-B, Wu J, Zhang C-L, Zhou Z-H (2016) Minimal gated unit for recurrent neural networks. Int J Autom Comput 13(3):226\u2013234","journal-title":"Int J Autom Comput"}],"container-title":["Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-023-08220-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00500-023-08220-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-023-08220-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T17:06:11Z","timestamp":1687799171000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00500-023-08220-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,12]]},"references-count":57,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["8220"],"URL":"https:\/\/doi.org\/10.1007\/s00500-023-08220-x","relation":{},"ISSN":["1432-7643","1433-7479"],"issn-type":[{"type":"print","value":"1432-7643"},{"type":"electronic","value":"1433-7479"}],"subject":[],"published":{"date-parts":[[2023,5,12]]},"assertion":[{"value":"5 April 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 May 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The authors declare that their research has no involvement with human participants and\/or animals.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human participants and\/or animals"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}