{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T18:00:15Z","timestamp":1781632815162,"version":"3.54.5"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T00:00:00Z","timestamp":1770422400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:00:00Z","timestamp":1773187200000},"content-version":"vor","delay-in-days":32,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Natural Science Research Project of Anhui Universities","award":["2022AH040315"],"award-info":[{"award-number":["2022AH040315"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Cloud Comp"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Detecting risks promptly and accurately is vital for safeguarding the safety and longevity of road and bridge structures. That said, conventional monitoring systems centered on cloud computing often run into issues with bandwidth constraints, delays, and data privacy, especially across scattered networks designed for structural health assessment. Here, we introduce Edge-TimeLSH, an edge computing framework that leverages a time-sensitive version of Locality-Sensitive Hashing (LSH) for immediate, on-location risk identification. Our technique transforms unprocessed sensor data from various sources into hash codes that incorporate temporal factors, facilitating fast lookups of analogous past structural conditions right on the edge hardware. We then assemble a matrix highlighting temporal similarities to pinpoint repeating patterns in mechanical performance, which in turn support a non-parametric forecasting of structural behavior, weighted by those similarities. The system forwards just condensed hash codes and critical notifications to the cloud, thereby upholding privacy while minimizing bandwidth use. Evaluations using real-world datasets reveal that Edge-TimeLSH delivers precise, understandable risk evaluations even on resource-limited edge devices. Overall, these outcomes highlight the framework\u2019s potential as a feasible and adaptable approach for ongoing risk monitoring in road and bridge projects.<\/jats:p>","DOI":"10.1186\/s13677-026-00856-y","type":"journal-article","created":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T10:15:03Z","timestamp":1770459303000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Edge intelligence for on-site risk detection in road and bridge engineering"],"prefix":"10.1186","volume":"15","author":[{"given":"Feng","family":"Xu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hossein","family":"Khosravi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,7]]},"reference":[{"issue":"1851","key":"856_CR1","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1098\/rsta.2006.1928","volume":"365","author":"CR Farrar","year":"2007","unstructured":"Farrar CR, Worden K (2007) An introduction to structural health monitoring. Philosophical Trans Royal Soc A 365(1851):303\u2013315","journal-title":"Philosophical Trans Royal Soc A"},{"issue":"4","key":"856_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3620677","volume":"15","author":"Y Liu","year":"2024","unstructured":"Liu Y, Zhou X, Kou H, Zhao Y, Xu X, Zhang X, Qi L (2024) Privacy-preserving point-of-interest recommendation based on simplified graph convolutional network for geological traveling. ACM Trans Intell Syst Technol 15(4):1\u201317","journal-title":"ACM Trans Intell Syst Technol"},{"key":"856_CR3","doi-asserted-by":"publisher","first-page":"115741","DOI":"10.1016\/j.jsv.2020.115741","volume":"491","author":"R Hou","year":"2021","unstructured":"Hou R, Xia Y (2021) Review on the new development of vibration-based damage identification for civil engineering structures: 2010\u20132019. J Sound Vib 491:115741","journal-title":"J Sound Vib"},{"key":"856_CR4","first-page":"129","volume":"42","author":"XW Ye","year":"2014","unstructured":"Ye XW, Su YH, Han JP (2014) Structural health monitoring of civil infrastructure using optical fiber sensing technology. Autom Constr 42:129\u2013141","journal-title":"Autom Constr"},{"key":"856_CR5","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1186\/s13677-025-00768-3","volume":"14","author":"Y Zhang","year":"2025","unstructured":"Zhang Y, Yang L, Tan Y (2025) Energy-efficient adaptive routing in heterogeneous wireless sensor networks via hybrid PSO and dynamic clustering. J Cloud Comput 14:46","journal-title":"J Cloud Comput"},{"issue":"5","key":"856_CR6","doi-asserted-by":"crossref","first-page":"1618","DOI":"10.1088\/0964-1726\/16\/5\/013","volume":"16","author":"Y Wang","year":"2007","unstructured":"Wang Y, Lynch JP, Law KH (2007) A wireless structural health monitoring system with multithreaded sensing devices. Smart Mater Struct 16(5):1618\u20131629","journal-title":"Smart Mater Struct"},{"issue":"1","key":"856_CR7","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1193\/1.1461375","volume":"18","author":"M Celebi","year":"2002","unstructured":"Celebi M (2002) Seismic instrumentation of buildings (CISN testbed): A dense accelerometer array system for structural monitoring. Earthq Spectra 18(1):47\u201368","journal-title":"Earthq Spectra"},{"key":"856_CR8","first-page":"220","volume":"75","author":"T Tao","year":"2015","unstructured":"Tao T, Yi T (2015) Missing data Estimation for structural health monitoring using statistical models. Measurement 75:220\u2013234","journal-title":"Measurement"},{"issue":"5","key":"856_CR9","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1109\/JIOT.2016.2579198","volume":"3","author":"W Shi","year":"2016","unstructured":"Shi W, Cao J, Zhang Q, Li Y, Xu L (2016) Edge computing: vision and challenges. IEEE Internet Things J 3(5):637\u2013646","journal-title":"IEEE Internet Things J"},{"key":"856_CR10","first-page":"378","volume":"373","author":"M Aazam","year":"2015","unstructured":"Aazam M, N Huh E (2015) Fog computing and smart gateway-based communication for cloud of things. IEEE Int Conf Future Internet Things Cloud 373:378","journal-title":"IEEE Int Conf Future Internet Things Cloud"},{"issue":"4","key":"856_CR11","first-page":"425","volume":"22","author":"Y Gao","year":"2018","unstructured":"Gao Y, Mosalam KM (2018) Deep learning structural health monitoring with wireless sensor networks. Smart Struct Syst 22(4):425\u2013440","journal-title":"Smart Struct Syst"},{"key":"856_CR12","doi-asserted-by":"crossref","first-page":"111965","DOI":"10.1016\/j.engstruct.2021.111965","volume":"234","author":"R Santos","year":"2021","unstructured":"Santos R et al (2021) Temperature-induced effects on long-term SHM data of bridges: A review. Eng Struct 234:111965","journal-title":"Eng Struct"},{"key":"856_CR13","doi-asserted-by":"crossref","unstructured":"Indyk P, Motwani R (1998) Approximate nearest neighbors: towards removing the curse of dimensionality. STOC \u201998","DOI":"10.1145\/276698.276876"},{"key":"856_CR14","doi-asserted-by":"crossref","unstructured":"Charikar M (2002) Similarity estimation techniques from rounding algorithms. STOC \u201902","DOI":"10.1145\/509907.509965"},{"key":"856_CR15","unstructured":"https:\/\/wsdream.github.io\/"},{"key":"856_CR16","doi-asserted-by":"publisher","unstructured":"Xin Xin X, Liu H, Wang et al (2023) Improving implicit feedback-based recommendation through multi-behavior alignment. https:\/\/doi.org\/10.1145\/3539618.3591697","DOI":"10.1145\/3539618.3591697"},{"key":"856_CR17","doi-asserted-by":"publisher","first-page":"articlenumber12","DOI":"10.1007\/s44196-023-00299-2","volume":"16","author":"HI Abdalla","year":"2023","unstructured":"Abdalla HI, Amer AA, Amer YA et al (2023) Boosting the item-based collaborative filtering model with novel similarity measures. Int J Comput Intell Syst 16:articlenumber123","journal-title":"Int J Comput Intell Syst"},{"issue":"2","key":"856_CR18","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1109\/TCC.2015.2511764","volume":"8","author":"W Lianyong Qi","year":"2020","unstructured":"Lianyong Qi W, Dou C, Zhou HY, Yu J (2020) A Context-aware service evaluation approach over big data for cloud applications. IEEE Trans Cloud Comput 8(2):338\u2013348","journal-title":"IEEE Trans Cloud Comput"},{"key":"856_CR19","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1016\/j.ins.2018.11.030","volume":"480","author":"L Qi","year":"2019","unstructured":"Qi L, Wang R, Hu C, Li S, He Q, Xu X (2019) Time-aware distributed service recommendation with privacy-preservation. Inf Sci 480:354\u2013364","journal-title":"Inf Sci"},{"issue":"4","key":"856_CR20","doi-asserted-by":"publisher","first-page":"1031","DOI":"10.26599\/BDMA.2024.9020029","volume":"7","author":"C Liu","year":"2024","unstructured":"Liu C, Guo S, Dang F, Qiu X, Shao S (2024) Large-Scale model Meets federated learning: A hierarchical hybrid distributed training mechanism for intelligent intersection Large-Scale model. Big Data Min Analytics 7(4):1031\u20131049","journal-title":"Big Data Min Analytics"},{"key":"856_CR21","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2025.3617922","author":"L Qi","year":"2025","unstructured":"Qi L, Yan B, Wang W, Hu C, Dai F, Xu X, Dou W, Zhou X (2025) ST-BernT: a Spatiotemporal \u03bb-Bernstein graph convolutional network with transformer for multi-site air quality prediction in distributed unmanned agent systems. IEEE Internet Things J. https:\/\/doi.org\/10.1109\/JIOT.2025.3617922","journal-title":"IEEE Internet Things J"},{"key":"856_CR22","doi-asserted-by":"crossref","unstructured":"Wu S, Shen S, Xu X, Chen Y, Zhou X, Liu D et al (2022) Popularity-aware and diverse web APIs recommendation based on correlation graph. IEEE Trans Comput Soc Syst 10(2);771\u2013782.","DOI":"10.1109\/TCSS.2022.3168595"},{"key":"856_CR23","doi-asserted-by":"crossref","unstructured":"Zhong W, Zhai D, Fakhrabadi AK, Attar H, Yan Y, Jiang R, Wang S (2025) Exploring and mitigating the impact of popularity bias for dynamic API composition recommendations. Tsinghua Sci Technol","DOI":"10.26599\/TST.2024.9010212"},{"key":"856_CR24","doi-asserted-by":"publisher","first-page":"576","DOI":"10.1016\/j.ins.2018.12.051","volume":"527","author":"W Dou","year":"2020","unstructured":"Dou W, Tang W, Wu X, Qi L, Xu X, Zhang X, Hu C (2020) An insurance theory based optimal cyber-insurance contract against moral hazard. Inf Sci 527:576\u2013589","journal-title":"Inf Sci"},{"issue":"3","key":"856_CR25","doi-asserted-by":"publisher","first-page":"1294","DOI":"10.26599\/TST.2024.9010026","volume":"30","author":"B Yan","year":"2024","unstructured":"Yan B, Zhang Y, Gong W, Wan H, Wang W, Zhong W, Bu C (2024) MDGCN-Lt: fair web API classification with sparse and heterogeneous data based on deep GCN. Tsinghua Sci Technol 30(3):1294\u20131314","journal-title":"Tsinghua Sci Technol"},{"issue":"6","key":"856_CR26","first-page":"1","volume":"43","author":"F Wang","year":"2025","unstructured":"Wang F, Qi L, Liu W, Yu B, Chen J, Xu Y (2025) Inter-and intra-similarity preserved counterfactual incentive effect Estimation for recommendation systems. ACM Trans Inform Syst 43(6):1\u201324","journal-title":"ACM Trans Inform Syst"},{"key":"856_CR27","doi-asserted-by":"crossref","unstructured":"Zhao X, Lu S, Yan C, Zhang R, Huang W, Wang S, Jiang R (2025) Compatibility-aware web APIs recommendation via subgraph matching for multimedia mashup development. Tsinghua Sci Technol","DOI":"10.26599\/TST.2024.9010147"},{"issue":"6","key":"856_CR28","first-page":"5444","volume":"35","author":"L Qi","year":"2023","unstructured":"Qi L, Lin W, Zhang X, Dou W, Xu X, Chen J (2023) A correlation graph based approach for personalized and compatible web apis recommendation in mobile app development. IEEE Trans Knowl Data Eng 35(6):5444\u20135457","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"856_CR29","doi-asserted-by":"crossref","unstructured":"Gu R, Wang S, Dai H, Chen X, Wang Z, Bao W et al (2024) Fluid-shuttle: Efficient cloud data transmission based on serverless computing compression. IEEE\/ACM Trans Netw 32(6);4554\u20134569.","DOI":"10.1109\/TNET.2024.3402561"},{"issue":"3","key":"856_CR30","doi-asserted-by":"publisher","first-page":"661","DOI":"10.26599\/BDMA.2024.9020093","volume":"8","author":"Q Wang","year":"2025","unstructured":"Wang Q, Yu C, Chen S, Fang W, Xiong N (2025) Joint adaptive resolution selection and conditional early exiting for efficient video recognition on edge devices. Big Data Min Analytics 8(3):661\u2013677","journal-title":"Big Data Min Analytics"},{"issue":"4","key":"856_CR31","doi-asserted-by":"publisher","first-page":"1065","DOI":"10.26599\/BDMA.2024.9020022","volume":"7","author":"C Luo","year":"2024","unstructured":"Luo C, Zhang J, Guo J, Hong Y, Chen Z, Gu S (2024) Energy efficiency maximization in RISs-assisted UAVs-based edge computing network using deep reinforcement learning. Big Data Min Analytics 7(4):1065\u20131083","journal-title":"Big Data Min Analytics"},{"issue":"1","key":"856_CR32","doi-asserted-by":"publisher","first-page":"331","DOI":"10.26599\/TST.2023.9010106","volume":"30","author":"Y Guo","year":"2024","unstructured":"Guo Y, Xie W, Wang Q, Yan D, Zhang Y (2024) Betweenness approximation for edge computing with hypergraph neural networks. Tsinghua Sci Technol 30(1):331\u2013344","journal-title":"Tsinghua Sci Technol"},{"issue":"10","key":"856_CR33","doi-asserted-by":"publisher","first-page":"3161","DOI":"10.1109\/JSAC.2023.3310077","volume":"41","author":"L Qi","year":"2023","unstructured":"Qi L, Xu X, Wu X, Ni Q, Yuan Y, Zhang X (2023) Digital-twin-enabled 6\u00a0g mobile network video streaming using mobile crowdsourcing. IEEE J Sel Areas Commun 41(10):3161\u20133174","journal-title":"IEEE J Sel Areas Commun"},{"issue":"4","key":"856_CR34","doi-asserted-by":"publisher","first-page":"1050","DOI":"10.26599\/BDMA.2024.9020065","volume":"7","author":"R Liu","year":"2024","unstructured":"Liu R, Yu S, Lan L, Wang J, Kant K, Calleja N (2024) A remedy for heterogeneous data: clustered federated learning with gradient trajectory. Big Data Min Analytics 7(4):1050\u20131064","journal-title":"Big Data Min Analytics"},{"issue":"5s","key":"856_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/2983642","volume":"12","author":"T Wu","year":"2016","unstructured":"Wu T, Dou W, Wu F, Tang S, Hu C, Chen J (2016) A deployment optimization scheme over multimedia big data for large-scale media streaming application. ACM Trans Multimedia Comput Commun Appl (TOMM) 12(5s):1\u201323","journal-title":"ACM Trans Multimedia Comput Commun Appl (TOMM)"},{"key":"856_CR36","doi-asserted-by":"publisher","first-page":"118809","DOI":"10.1016\/j.engstruct.2024.118809","volume":"319","author":"Z Peng","year":"2024","unstructured":"Peng Z, Li J, Hao H, Zhong Y (2024) Smart structural health monitoring using computer vision and edge computing. Eng Struct 319:118809","journal-title":"Eng Struct"},{"issue":"2","key":"856_CR37","doi-asserted-by":"publisher","first-page":"469","DOI":"10.3390\/s24020469","volume":"24","author":"AR Al-Ali","year":"2024","unstructured":"Al-Ali AR, Beheiry S, Alnabulsi A, Obaid S, Mansoor N, Odeh N, Mostafa A (2024) An IoT-based road Bridge health monitoring and warning system. Sensors 24(2):469","journal-title":"Sensors"},{"key":"856_CR38","doi-asserted-by":"publisher","first-page":"13215","DOI":"10.1038\/s41598-023-40355-7","volume":"13","author":"M Fawad","year":"2023","unstructured":"Fawad M, Salamak M, Poprawa G, Koris K, Jasinski M, Lazinski P, Piotrowski D, Hasnain M, Gerges M (2023) Automation of structural health monitoring (SHM) system of a Bridge using bimification approach and BIM-based finite element model development. Sci Rep 13:13215","journal-title":"Sci Rep"},{"issue":"12","key":"856_CR39","doi-asserted-by":"publisher","first-page":"9410","DOI":"10.1109\/JIOT.2021.3111614","volume":"9","author":"W Sun","year":"2021","unstructured":"Sun W, Jiang J, Huang Y, Li J, Zhang M (2021) An integrated PCA-DAEGCN model for movie recommendation in the social internet of things. IEEE Internet Things J 9(12):9410\u20139418","journal-title":"IEEE Internet Things J"},{"key":"856_CR40","doi-asserted-by":"crossref","unstructured":"Chen ZS, Yang LL, Chin KS, Yang Y, Pedrycz W, Chang JP et al (2021) Sustainable building material selection: an integrated multi-criteria large group decision making framework. Appl Soft Comput 113;107903.","DOI":"10.1016\/j.asoc.2021.107903"},{"issue":"2","key":"856_CR41","doi-asserted-by":"publisher","first-page":"925","DOI":"10.1109\/TCYB.2020.2990319","volume":"52","author":"F Jiang","year":"2020","unstructured":"Jiang F, Dong L, Dai Q (2020) Designing a mixed multilayer wavelet neural network for solving ERI inversion problem with massive amounts of data: A hybrid STGWO-GD learning approach. IEEE Trans Cybernetics 52(2):925\u2013936","journal-title":"IEEE Trans Cybernetics"},{"issue":"2","key":"856_CR42","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1007\/s11554-020-01032-4","volume":"18","author":"W Sun","year":"2021","unstructured":"Sun W, Mo C (2021) High-speed real-time augmented reality tracking algorithm model of camera based on mixed feature points. J Real-Time Image Proc 18(2):249\u2013259","journal-title":"J Real-Time Image Proc"},{"key":"856_CR43","doi-asserted-by":"crossref","unstructured":"Xu X, Pan B, Yang Y (2018) Large-group risk dynamic emergency decision method based on the dual influence of preference transfer and risk preference. Soft Comput 22(22)","DOI":"10.1007\/s00500-018-3387-3"},{"issue":"7","key":"856_CR44","doi-asserted-by":"publisher","first-page":"2115","DOI":"10.3390\/s24072115","volume":"24","author":"A Armijo","year":"2024","unstructured":"Armijo A, Zamora-S\u00e1nchez D (2024) Integration of railway Bridge structural health monitoring into the internet of things with a digital twin: A case study. Sensors 24(7):2115","journal-title":"Sensors"},{"issue":"15","key":"856_CR45","doi-asserted-by":"publisher","first-page":"5078","DOI":"10.3390\/s24155078","volume":"24","author":"E Hidalgo-Fort","year":"2024","unstructured":"Hidalgo-Fort E, Blanco-Carmona P, Mu\u00f1oz-Chavero F, Torralba A, Castro-Triguero R (2024) Low-cost, low-power edge computing system for structural health monitoring in an IoT framework. Sensors 24(15):5078","journal-title":"Sensors"},{"key":"856_CR46","doi-asserted-by":"publisher","first-page":"105719","DOI":"10.1016\/j.autcon.2024.105719","volume":"167","author":"VM Di Mucci","year":"2024","unstructured":"Di Mucci VM, Cardellicchio A, Ruggieri S, Nettis A, Ren\u00f2 V, Uva G (2024) Artificial intelligence in structural health management of existing bridges. Autom Constr 167:105719","journal-title":"Autom Constr"},{"issue":"11","key":"856_CR47","doi-asserted-by":"publisher","first-page":"374","DOI":"10.55248\/gengpi.06.1125.3823","volume":"6","author":"VK Kella","year":"2025","unstructured":"Kella VK, Kotni L, Bura P, Alavilli H, Budumuru K (2025) Structural health monitoring of bridges using IoT and AI. Int J Res Publication Reviews 6(11):374\u2013377","journal-title":"Int J Res Publication Reviews"},{"key":"856_CR48","doi-asserted-by":"publisher","DOI":"10.1080\/15732479.2025.2547349","author":"H Qiao","year":"2025","unstructured":"Qiao H, Guan H, Zhu Y (2025) Footbridge structural health monitoring \u2013 A review of current research and future directions. Struct Infrastruct Eng. https:\/\/doi.org\/10.1080\/15732479.2025.2547349","journal-title":"Struct Infrastruct Eng"},{"issue":"17","key":"856_CR49","doi-asserted-by":"publisher","first-page":"5460","DOI":"10.3390\/s25175460","volume":"25","author":"X Kang","year":"2025","unstructured":"Kang X, Zhu B, Cai Y, Xiao Y, Liu N, Guo Z, Wang Q-A, Luo Y (2025) A concise review of state-of-the-art sensing technologies for Bridge structural health monitoring. Sensors 25(17):5460","journal-title":"Sensors"},{"key":"856_CR50","doi-asserted-by":"publisher","first-page":"109954","DOI":"10.1016\/j.istruc.2025.109954","volume":"80","author":"T Wang","year":"2025","unstructured":"Wang T, Li D, Li B, Zhang J (2025) Lightweight structural health monitoring method for bridges based on cloud-edge collaborative optimization. Structures 80:109954","journal-title":"Structures"},{"key":"856_CR51","doi-asserted-by":"publisher","unstructured":"Qi L, Xie J, Hu C, Xu X, Xiang H, Dai H et al (2025) Knowledge-Driven Reasoning for Compatible and Interpretable API Recommendation via Teacher LLM Distillation. ACM Trans Inf Syst. https:\/\/doi.org\/10.1145\/3771772","DOI":"10.1145\/3771772"},{"issue":"2","key":"856_CR52","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1109\/TSUSC.2017.2733018","volume":"4","author":"F Fei","year":"2019","unstructured":"Fei F, Li S, Dai H, Hu C, Dou W, Ni Q (2019) A K-anonymity based schema for location privacy preservation. IEEE Trans Sustainable Comput 4(2):156\u2013167","journal-title":"IEEE Trans Sustainable Comput"}],"container-title":["Journal of Cloud Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s13677-026-00856-y","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13677-026-00856-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s13677-026-00856-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T17:43:58Z","timestamp":1781631838000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s13677-026-00856-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,7]]},"references-count":52,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["856"],"URL":"https:\/\/doi.org\/10.1186\/s13677-026-00856-y","relation":{},"ISSN":["2192-113X"],"issn-type":[{"value":"2192-113X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,7]]},"assertion":[{"value":"17 November 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 January 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"We declare that there are no ethic issues.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Agree.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"36"}}