{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T00:56:23Z","timestamp":1760576183899,"version":"build-2065373602"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T00:00:00Z","timestamp":1750723200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T00:00:00Z","timestamp":1750723200000},"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":["62088101","62403060"],"award-info":[{"award-number":["62088101","62403060"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Natural Science Foundation of Beijing Municipality","doi-asserted-by":"publisher","award":["L243004"],"award-info":[{"award-number":["L243004"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1007\/s13042-025-02697-8","type":"journal-article","created":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T12:32:19Z","timestamp":1750768339000},"page":"7957-7971","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Robust humanoid vehicle ingress with regression and whole body control"],"prefix":"10.1007","volume":"16","author":[{"given":"Chenzheng","family":"Wang","sequence":"first","affiliation":[]},{"given":"Xuechao","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Zhangguo","family":"Yu","sequence":"additional","affiliation":[]},{"given":"Fei","family":"Meng","sequence":"additional","affiliation":[]},{"given":"Qiang","family":"Huang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,24]]},"reference":[{"key":"2697_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-74666-1","volume-title":"The DARPA robotics challenge finals: humanoid robots to the rescue,","author":"M Spenko","year":"2018","unstructured":"Spenko M, Buerger S, Iagnemma K (2018) The DARPA robotics challenge finals: humanoid robots to the rescue, vol 121. Springer"},{"issue":"3","key":"2697_CR2","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1109\/MRA.2020.2987805","volume":"27","author":"K Kawaharazuka","year":"2020","unstructured":"Kawaharazuka K, Tsuzuki K, Koga Y et al (2020) Toward autonomous driving by musculoskeletal humanoids: A study of developed hardware and learning-based software. IEEE Robotics & Automation Magazine 27(3):84\u201396","journal-title":"IEEE Robotics & Automation Magazine"},{"issue":"2","key":"2697_CR3","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1002\/rob.21731","volume":"35","author":"A Paolillo","year":"2018","unstructured":"Paolillo A, Gergondet P, Cherubini A et al (2018) Autonomous car driving by a humanoid robot. J. Field. Robotics 35(2):169\u2013186","journal-title":"J. Field. Robotics"},{"issue":"1","key":"2697_CR4","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1007\/s11370-015-0181-2","volume":"9","author":"K Sohn","year":"2016","unstructured":"Sohn K, Oh P (2016) Optimization of humanoid\u2019s motions under multiple constraints in vehicle ingress task. Intel Serv Robot 9(1):31\u201348","journal-title":"Intel Serv Robot"},{"issue":"1","key":"2697_CR5","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/s10846-018-0835-3","volume":"95","author":"K Sohn","year":"2019","unstructured":"Sohn K (2019) Optimization of vehicle mounting motions and its application to full-sized humanoid, drc-hubo. Journal of Intelligent & Robotic Systems 95(1):19\u201346","journal-title":"Journal of Intelligent & Robotic Systems"},{"key":"2697_CR6","doi-asserted-by":"crossref","unstructured":"Wang C, Chen X, Yu Z, et\u00a0al (2024) Robust humanoid robot vehicle ingress with a finite state machine integrated with deep reinforcement learning. International Journal of Machine Learning and Cybernetics pp 1\u201315","DOI":"10.21203\/rs.3.rs-3444385\/v1"},{"key":"2697_CR7","doi-asserted-by":"crossref","unstructured":"Maroger I, Stasse O, Watier B (2020) Walking human trajectory models and their application to humanoid robot locomotion. In: 2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, pp 3465\u20133472","DOI":"10.1109\/IROS45743.2020.9341118"},{"key":"2697_CR8","unstructured":"Quinlan JR, et\u00a0al (1992) Learning with continuous classes. In: 5th Australian joint conference on artificial intelligence, World Scientific, pp 343\u2013348"},{"issue":"1","key":"2697_CR9","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1109\/TIE.2016.2606358","volume":"64","author":"H Xiao","year":"2016","unstructured":"Xiao H, Li Z, Yang C et al (2016) Robust stabilization of a wheeled mobile robot using model predictive control based on neurodynamics optimization. IEEE Trans Industr Electron 64(1):505\u2013516","journal-title":"IEEE Trans Industr Electron"},{"key":"2697_CR10","doi-asserted-by":"crossref","unstructured":"Hedjar R (2022) Approximate quadratic programming algorithm for nonlinear model predictive tracking control of a wheeled mobile robot. IEEE Access 10:65,067\u201365,079","DOI":"10.1109\/ACCESS.2022.3178727"},{"issue":"3","key":"2697_CR11","doi-asserted-by":"publisher","first-page":"4463","DOI":"10.1109\/LRA.2020.3001471","volume":"5","author":"KA Hamed","year":"2020","unstructured":"Hamed KA, Kim J, Pandala A (2020) Quadrupedal locomotion via event-based predictive control and qp-based virtual constraints. IEEE Robotics and Automation Letters 5(3):4463\u20134470","journal-title":"IEEE Robotics and Automation Letters"},{"key":"2697_CR12","doi-asserted-by":"crossref","unstructured":"Ding Y, Pandala A, Park HW (2019) Real-time model predictive control for versatile dynamic motions in quadrupedal robots. In: 2019 International Conference on Robotics and Automation (ICRA), IEEE, pp 8484\u20138490","DOI":"10.1109\/ICRA.2019.8793669"},{"key":"2697_CR13","doi-asserted-by":"crossref","unstructured":"Brasseur C, Sherikov A, Collette C, et\u00a0al (2015) A robust linear mpc approach to online generation of 3d biped walking motion. In: 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids), IEEE, pp 595\u2013601","DOI":"10.1109\/HUMANOIDS.2015.7363423"},{"key":"2697_CR14","doi-asserted-by":"crossref","unstructured":"Caron S, Kheddar A, Tempier O (2019) Stair climbing stabilization of the hrp-4 humanoid robot using whole-body admittance control. In: 2019 International conference on robotics and automation (ICRA), IEEE, pp 277\u2013283","DOI":"10.1109\/ICRA.2019.8794348"},{"key":"2697_CR15","doi-asserted-by":"crossref","unstructured":"Chefchaouni S, Benallegue M, Escande A, et\u00a0al (2024) Motion accuracy and computational effort in qp-based robot control. In: 2024 IEEE-RAS 23rd International Conference on Humanoid Robots (Humanoids), IEEE, pp 129\u2013134","DOI":"10.1109\/Humanoids58906.2024.10769961"},{"key":"2697_CR16","doi-asserted-by":"crossref","unstructured":"Chappellet K, Murooka M, Caron G, et\u00a0al (2023) Humanoid loco-manipulations using combined fast dense 3d tracking and slam with wide-angle depth-images. IEEE Transactions on Automation Science and Engineering","DOI":"10.1109\/TASE.2023.3283497"},{"issue":"11","key":"2697_CR17","doi-asserted-by":"publisher","first-page":"8870","DOI":"10.1109\/TIE.2018.2875660","volume":"66","author":"T Dragi\u010devi\u0107","year":"2018","unstructured":"Dragi\u010devi\u0107 T, Novak M (2018) Weighting factor design in model predictive control of power electronic converters: An artificial neural network approach. IEEE Trans Industr Electron 66(11):8870\u20138880","journal-title":"IEEE Trans Industr Electron"},{"key":"2697_CR18","doi-asserted-by":"crossref","unstructured":"Park SC, Kim M, Park HM, et\u00a0al (2024) Optimal control gains optimization for mobile robot considering dynamic constraints. IEEE Access","DOI":"10.1109\/ACCESS.2024.3507739"},{"issue":"2","key":"2697_CR19","doi-asserted-by":"publisher","first-page":"A1221","DOI":"10.1137\/19M1288802","volume":"43","author":"T Nakamura-Zimmerer","year":"2021","unstructured":"Nakamura-Zimmerer T, Gong Q, Kang W (2021) Adaptive deep learning for high-dimensional hamilton-jacobi-bellman equations. SIAM J Sci Comput 43(2):A1221\u2013A1247","journal-title":"SIAM J Sci Comput"},{"key":"2697_CR20","unstructured":"Zang Y, Long J, Zhang X, et\u00a0al (2022) A machine learning enhanced algorithm for the optimal landing problem. In: Mathematical and Scientific Machine Learning, PMLR, pp 319\u2013334"},{"key":"2697_CR21","doi-asserted-by":"crossref","unstructured":"Zhang X, Bujarbaruah M, Borrelli F (2019) Safe and near-optimal policy learning for model predictive control using primal-dual neural networks. In: 2019 American Control Conference (ACC), IEEE, pp 354\u2013359","DOI":"10.23919\/ACC.2019.8814335"},{"issue":"3","key":"2697_CR22","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1109\/LCSYS.2018.2843682","volume":"2","author":"M Hertneck","year":"2018","unstructured":"Hertneck M, K\u00f6hler J, Trimpe S et al (2018) Learning an approximate model predictive controller with guarantees. IEEE Control Systems Letters 2(3):543\u2013548","journal-title":"IEEE Control Systems Letters"},{"issue":"4","key":"2697_CR23","doi-asserted-by":"publisher","first-page":"1303","DOI":"10.1109\/LCSYS.2020.3034415","volume":"5","author":"T Nakamura-Zimmerer","year":"2020","unstructured":"Nakamura-Zimmerer T, Gong Q, Kang W (2020) Qrnet: Optimal regulator design with lqr-augmented neural networks. IEEE Control Systems Letters 5(4):1303\u20131308","journal-title":"IEEE Control Systems Letters"},{"key":"2697_CR24","unstructured":"Sutton RS, Barto AG, et\u00a0al (1998) Reinforcement learning: An introduction, vol\u00a01. MIT press Cambridge"},{"issue":"4","key":"2697_CR25","first-page":"1","volume":"37","author":"XB Peng","year":"2018","unstructured":"Peng XB, Abbeel P, Levine S et al (2018) Deepmimic: Example-guided deep reinforcement learning of physics-based character skills. ACM Transactions On Graphics (TOG) 37(4):1\u201314","journal-title":"ACM Transactions On Graphics (TOG)"},{"key":"2697_CR26","doi-asserted-by":"crossref","unstructured":"Chitnis R, Tulsiani S, Gupta S, et\u00a0al (2020) Efficient bimanual manipulation using learned task schemas. In: 2020 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp 1149\u20131155","DOI":"10.1109\/ICRA40945.2020.9196958"},{"issue":"3","key":"2697_CR27","doi-asserted-by":"publisher","first-page":"4072","DOI":"10.1109\/TNNLS.2022.3201705","volume":"35","author":"G Wang","year":"2022","unstructured":"Wang G, Xin M, Wu W et al (2022) Learning of long-horizon sparse-reward robotic manipulator tasks with base controllers. IEEE Transactions on Neural Networks and Learning Systems 35(3):4072\u20134081","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"key":"2697_CR28","unstructured":"Schulman J, Levine S, Abbeel P, et\u00a0al (2015) Trust region policy optimization. In: International conference on machine learning, PMLR, pp 1889\u20131897"},{"key":"2697_CR29","unstructured":"Schulman J, Wolski F, Dhariwal P, et\u00a0al (2017) Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347"},{"key":"2697_CR30","unstructured":"Lillicrap TP, Hunt JJ, Pritzel A, et\u00a0al (2015) Continuous control with deep reinforcement learning. arXiv preprint arXiv:1509.02971"},{"issue":"2","key":"2697_CR31","doi-asserted-by":"publisher","first-page":"2610","DOI":"10.1109\/LRA.2020.2972879","volume":"5","author":"C Yang","year":"2020","unstructured":"Yang C, Yuan K, Heng S et al (2020) Learning natural locomotion behaviors for humanoid robots using human bias. IEEE Robotics and Automation Letters 5(2):2610\u20132617","journal-title":"IEEE Robotics and Automation Letters"},{"key":"2697_CR32","doi-asserted-by":"crossref","unstructured":"Rodriguez D, Behnke S (2021) Deepwalk: Omnidirectional bipedal gait by deep reinforcement learning. In: 2021 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp 3033\u20133039","DOI":"10.1109\/ICRA48506.2021.9561717"},{"key":"2697_CR33","doi-asserted-by":"publisher","DOI":"10.1002\/9780470182963","volume-title":"Approximate Dynamic Programming: Solving the curses of dimensionality,","author":"WB Powell","year":"2007","unstructured":"Powell WB (2007) Approximate Dynamic Programming: Solving the curses of dimensionality, vol 703. John Wiley & Sons"},{"issue":"11","key":"2697_CR34","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1177\/0142331216645176","volume":"39","author":"O Tutsoy","year":"2017","unstructured":"Tutsoy O, Erol Barkana D, Colak S (2017) Learning to balance an nao robot using reinforcement learning with symbolic inverse kinematic. Trans Inst Meas Control 39(11):1735\u20131748","journal-title":"Trans Inst Meas Control"},{"key":"2697_CR35","doi-asserted-by":"crossref","unstructured":"Johannink T, Bahl S, Nair A, et\u00a0al (2019) Residual reinforcement learning for robot control. In: 2019 International Conference on Robotics and Automation (ICRA), IEEE, pp 6023\u20136029","DOI":"10.1109\/ICRA.2019.8794127"},{"key":"2697_CR36","doi-asserted-by":"crossref","unstructured":"Li Z, Cheng X, Peng XB, et\u00a0al (2021) Reinforcement learning for robust parameterized locomotion control of bipedal robots. In: 2021 IEEE International Conference on Robotics and Automation (ICRA), IEEE, pp 2811\u20132817","DOI":"10.1109\/ICRA48506.2021.9560769"},{"issue":"1","key":"2697_CR37","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1007\/s10846-022-01619-y","volume":"105","author":"AF Muzio","year":"2022","unstructured":"Muzio AF, Maximo MR, Yoneyama T (2022) Deep reinforcement learning for humanoid robot behaviors. Journal of Intelligent & Robotic Systems 105(1):12","journal-title":"Journal of Intelligent & Robotic Systems"},{"key":"2697_CR38","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.neunet.2018.12.010","volume":"111","author":"M Fern\u00e1ndez-Delgado","year":"2019","unstructured":"Fern\u00e1ndez-Delgado M, Sirsat MS, Cernadas E et al (2019) An extensive experimental survey of regression methods. Neural Netw 111:11\u201334","journal-title":"Neural Netw"},{"issue":"3","key":"2697_CR39","doi-asserted-by":"publisher","first-page":"941","DOI":"10.1109\/TCST.2012.2191969","volume":"21","author":"JP Ferreira","year":"2012","unstructured":"Ferreira JP, Cris\u00f3stomo MM, Coimbra AP (2012) Adaptive pd controller modeled via support vector regression for a biped robot. IEEE Trans Control Syst Technol 21(3):941\u2013949","journal-title":"IEEE Trans Control Syst Technol"},{"issue":"1","key":"2697_CR40","doi-asserted-by":"publisher","first-page":"3877","DOI":"10.1016\/j.ifacol.2017.08.359","volume":"50","author":"T Beckers","year":"2017","unstructured":"Beckers T, Umlauft J, Hirche S (2017) Stable model-based control with gaussian process regression for robot manipulators. IFAC-PapersOnLine 50(1):3877\u20133884","journal-title":"IFAC-PapersOnLine"},{"key":"2697_CR41","unstructured":"JRL (2018) mc_rtc.github.com\/jrl-umi3218\/mc_rtc"},{"issue":"3","key":"2697_CR42","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1007\/s10514-016-9546-4","volume":"40","author":"J Vaillant","year":"2016","unstructured":"Vaillant J, Kheddar A, Audren H et al (2016) Multi-contact vertical ladder climbing with an hrp-2 humanoid. Auton Robot 40(3):561\u2013580","journal-title":"Auton Robot"},{"key":"2697_CR43","doi-asserted-by":"crossref","unstructured":"Bolotnikova A, Gergondet P, Tanguy A, et\u00a0al (2021) Task-space control interface for softbank humanoid robots and its human-robot interaction applications. In: 2021 IEEE\/SICE International Symposium on System Integration (SII), IEEE, pp 560\u2013565","DOI":"10.1109\/IEEECONF49454.2021.9382685"},{"issue":"4","key":"2697_CR44","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1109\/MRA.2019.2943395","volume":"26","author":"A Kheddar","year":"2019","unstructured":"Kheddar A, Caron S, Gergondet P et al (2019) Humanoid robots in aircraft manufacturing: The airbus use cases. IEEE Robotics & Automation Magazine 26(4):30\u201345","journal-title":"IEEE Robotics & Automation Magazine"},{"issue":"2","key":"2697_CR45","doi-asserted-by":"publisher","first-page":"1840","DOI":"10.1109\/LRA.2021.3060728","volume":"6","author":"M Murooka","year":"2021","unstructured":"Murooka M, Kumagai I, Morisawa M et al (2021) Humanoid loco-manipulation planning based on graph search and reachability maps. IEEE Robotics and Automation Letters 6(2):1840\u20131847","journal-title":"IEEE Robotics and Automation Letters"},{"key":"2697_CR46","doi-asserted-by":"crossref","unstructured":"Djeha M, Dallard A, Zermane A, et\u00a0al (2022) Human-robot handovers using task-space quadratic programming. In: 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), IEEE, pp 518\u2013523","DOI":"10.1109\/RO-MAN53752.2022.9900626"},{"key":"2697_CR47","doi-asserted-by":"crossref","unstructured":"Bouyarmane K, Kheddar A (2011) Using a multi-objective controller to synthesize simulated humanoid robot motion with changing contact configurations. In: 2011 IEEE\/RSJ International Conference on Intelligent Robots and Systems, IEEE, pp 4414\u20134419","DOI":"10.1109\/IROS.2011.6094483"},{"key":"2697_CR48","unstructured":"Wieber PB (2005) Some comments on the structure of the dynamics of articulated motion. In: Fast motions in biomechanics and robotics"},{"issue":"6","key":"2697_CR49","doi-asserted-by":"publisher","first-page":"1632","DOI":"10.1109\/TAC.2017.2752085","volume":"63","author":"K Bouyarmane","year":"2017","unstructured":"Bouyarmane K, Kheddar A (2017) On weight-prioritized multitask control of humanoid robots. IEEE Trans Autom Control 63(6):1632\u20131647","journal-title":"IEEE Trans Autom Control"},{"issue":"1","key":"2697_CR50","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1109\/TRO.2018.2876782","volume":"35","author":"K Bouyarmane","year":"2018","unstructured":"Bouyarmane K, Chappellet K, Vaillant J et al (2018) Quadratic programming for multirobot and task-space force control. IEEE Trans Rob 35(1):64\u201377","journal-title":"IEEE Trans Rob"},{"issue":"4","key":"2697_CR51","doi-asserted-by":"publisher","first-page":"3247","DOI":"10.1109\/LRA.2018.2851148","volume":"3","author":"K Lobos-Tsunekawa","year":"2018","unstructured":"Lobos-Tsunekawa K, Leiva F, Ruiz-del Solar J (2018) Visual navigation for biped humanoid robots using deep reinforcement learning. IEEE Robotics and Automation Letters 3(4):3247\u20133254","journal-title":"IEEE Robotics and Automation Letters"},{"key":"2697_CR52","unstructured":"Barth-Maron G, Hoffman MW, Budden D, et\u00a0al (2018) Distributed distributional deterministic policy gradients. arXiv preprint arXiv:1804.08617"},{"issue":"18","key":"2697_CR53","first-page":"480","volume":"00","author":"M Kuhn","year":"2012","unstructured":"Kuhn M, Weston S, Keefer C et al (2012) Cubist models for regression. R package Vignette R package version 00(18):480","journal-title":"R package Vignette R package version"},{"issue":"1","key":"2697_CR54","first-page":"2007","volume":"1","author":"G Ridgeway","year":"2007","unstructured":"Ridgeway G (2007) Generalized boosted models: A guide to the gbm package. Update 1(1):2007","journal-title":"Update"},{"key":"2697_CR55","first-page":"3","volume":"63","author":"P Geurts","year":"2006","unstructured":"Geurts P, Ernst D, Wehenkel L (2006) Extremely randomized trees. Machine learning 63:3\u201342","journal-title":"Extremely randomized trees. Machine learning"},{"key":"2697_CR56","doi-asserted-by":"crossref","unstructured":"Singh RP, Gergondet P, Kanehiro F (2022) mc-mujoco: Simulating articulated robots with fsm controllers in mujoco. arXiv preprint arXiv:2209.00274","DOI":"10.1109\/SII55687.2023.10039218"},{"key":"2697_CR57","doi-asserted-by":"publisher","unstructured":"Wang C, Chen X, Yu Z, et\u00a0al (2023) Robust humanoid robot vehicle ingress with a finite state machine integrated with deep reinforcement learning. https:\/\/doi.org\/10.21203\/rs.3.rs-3444385\/v1","DOI":"10.21203\/rs.3.rs-3444385\/v1"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-025-02697-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-025-02697-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-025-02697-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T17:01:34Z","timestamp":1760547694000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-025-02697-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,24]]},"references-count":57,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2025,10]]}},"alternative-id":["2697"],"URL":"https:\/\/doi.org\/10.1007\/s13042-025-02697-8","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"type":"print","value":"1868-8071"},{"type":"electronic","value":"1868-808X"}],"subject":[],"published":{"date-parts":[[2025,6,24]]},"assertion":[{"value":"25 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 May 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 June 2025","order":3,"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"}}]}}