{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,5,28]],"date-time":"2024-05-28T00:14:50Z","timestamp":1716855290288},"reference-count":61,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,8,1]],"date-time":"2024-08-01T00:00:00Z","timestamp":1722470400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2024,8]]},"DOI":"10.1016\/j.neucom.2024.127790","type":"journal-article","created":{"date-parts":[[2024,5,4]],"date-time":"2024-05-04T09:42:02Z","timestamp":1714815722000},"page":"127790","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["CompleteDT: Point cloud completion with information-perception transformers"],"prefix":"10.1016","volume":"592","author":[{"given":"Jun","family":"Li","sequence":"first","affiliation":[]},{"given":"Shangwei","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Luhan","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Shaokun","family":"Han","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.neucom.2024.127790_b1","doi-asserted-by":"crossref","unstructured":"Z. Huang, Y. Yu, J. Xu, F. Ni, X. Le, PF-Net: Point fractal network for 3d point cloud completion, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 7662\u20137670.","DOI":"10.1109\/CVPR42600.2020.00768"},{"key":"10.1016\/j.neucom.2024.127790_b2","unstructured":"C.R. Qi, H. Su, K. Mo, L.J. Guibas, PointNet: Deep learning on point sets for 3d classification and segmentation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 652\u2013660."},{"key":"10.1016\/j.neucom.2024.127790_b3","article-title":"PointNet++: Deep hierarchical feature learning on point sets in a metric space","volume":"30","author":"Qi","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2024.127790_b4","doi-asserted-by":"crossref","unstructured":"H. Lei, N. Akhtar, A. Mian, Seggcn: Efficient 3d point cloud segmentation with fuzzy spherical kernel, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 11611\u201311620.","DOI":"10.1109\/CVPR42600.2020.01163"},{"key":"10.1016\/j.neucom.2024.127790_b5","doi-asserted-by":"crossref","unstructured":"X. Xu, G.H. Lee, Weakly supervised semantic point cloud segmentation: Towards 10x fewer labels, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 13706\u201313715.","DOI":"10.1109\/CVPR42600.2020.01372"},{"key":"10.1016\/j.neucom.2024.127790_b6","doi-asserted-by":"crossref","unstructured":"W. Ali, S. Abdelkarim, M. Zidan, M. Zahran, A. El Sallab, Yolo3d: End-to-end real-time 3d oriented object bounding box detection from lidar point cloud, in: Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 2018.","DOI":"10.1007\/978-3-030-11015-4_54"},{"key":"10.1016\/j.neucom.2024.127790_b7","doi-asserted-by":"crossref","unstructured":"X. Chen, H. Ma, J. Wan, B. Li, T. Xia, Multi-view 3d object detection network for autonomous driving, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 1907\u20131915.","DOI":"10.1109\/CVPR.2017.691"},{"key":"10.1016\/j.neucom.2024.127790_b8","doi-asserted-by":"crossref","unstructured":"A. Dai, C. Ruizhongtai Qi, M. Nie\u00dfner, Shape completion using 3d-encoder-predictor cnns and shape synthesis, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 5868\u20135877.","DOI":"10.1109\/CVPR.2017.693"},{"key":"10.1016\/j.neucom.2024.127790_b9","doi-asserted-by":"crossref","unstructured":"B. Yang, H. Wen, S. Wang, R. Clark, A. Markham, N. Trigoni, 3d object reconstruction from a single depth view with adversarial learning, in: Proceedings of the IEEE International Conference on Computer Vision Workshops, 2017, pp. 679\u2013688.","DOI":"10.1109\/ICCVW.2017.86"},{"key":"10.1016\/j.neucom.2024.127790_b10","series-title":"European Conference on Computer Vision","first-page":"365","article-title":"GRNet: Gridding residual network for dense point cloud completion","author":"Xie","year":"2020"},{"key":"10.1016\/j.neucom.2024.127790_b11","series-title":"Deep learning for 3D point clouds: A survey (IEEE TPAMI 2020)","author":"Guo","year":"2019"},{"key":"10.1016\/j.neucom.2024.127790_b12","series-title":"2018 International Conference on 3D Vision","first-page":"728","article-title":"PCN: Point completion network","author":"Yuan","year":"2018"},{"key":"10.1016\/j.neucom.2024.127790_b13","doi-asserted-by":"crossref","unstructured":"X. Wang, M.H. Ang, G.H. Lee, Cascaded refinement network for point cloud completion, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 790\u2013799.","DOI":"10.1109\/CVPR42600.2020.00087"},{"key":"10.1016\/j.neucom.2024.127790_b14","doi-asserted-by":"crossref","unstructured":"X. Wen, T. Li, Z. Han, Y.-S. Liu, Point cloud completion by skip-attention network with hierarchical folding, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 1939\u20131948.","DOI":"10.1109\/CVPR42600.2020.00201"},{"key":"10.1016\/j.neucom.2024.127790_b15","doi-asserted-by":"crossref","unstructured":"X. Wen, P. Xiang, Z. Han, Y.-P. Cao, P. Wan, W. Zheng, Y.-S. Liu, PMP-net: Point cloud completion by learning multi-step point moving paths, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 7443\u20137452.","DOI":"10.1109\/CVPR46437.2021.00736"},{"key":"10.1016\/j.neucom.2024.127790_b16","article-title":"PMP-net++: Point cloud completion by transformer-enhanced multi-step point moving paths","author":"Wen","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2024.127790_b17","doi-asserted-by":"crossref","unstructured":"L.P. Tchapmi, V. Kosaraju, H. Rezatofighi, I. Reid, S. Savarese, TopNet: Structural point cloud decoder, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 383\u2013392.","DOI":"10.1109\/CVPR.2019.00047"},{"key":"10.1016\/j.neucom.2024.127790_b18","doi-asserted-by":"crossref","unstructured":"L. Pan, X. Chen, Z. Cai, J. Zhang, H. Zhao, S. Yi, Z. Liu, Variational relational point completion network, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 8524\u20138533.","DOI":"10.1109\/CVPR46437.2021.00842"},{"key":"10.1016\/j.neucom.2024.127790_b19","doi-asserted-by":"crossref","unstructured":"K. Wang, K. Chen, K. Jia, Deep Cascade Generation on Point Sets, in: International Joint Conference on Artificial Intelligence, 2019.","DOI":"10.24963\/ijcai.2019\/517"},{"key":"10.1016\/j.neucom.2024.127790_b20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.neucom.2022.03.060","article-title":"DPG-Net: Densely progressive-growing network for point cloud completion","volume":"491","author":"Li","year":"2022","journal-title":"Neurocomputing"},{"issue":"3","key":"10.1016\/j.neucom.2024.127790_b21","doi-asserted-by":"crossref","first-page":"4392","DOI":"10.1109\/LRA.2020.2994483","article-title":"Ecg: Edge-aware point cloud completion with graph convolution","volume":"5","author":"Pan","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"10.1016\/j.neucom.2024.127790_b22","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"2","key":"10.1016\/j.neucom.2024.127790_b23","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/s41095-021-0229-5","article-title":"PCT: Point cloud transformer","volume":"7","author":"Guo","year":"2021","journal-title":"Comput. Vis. Media"},{"key":"10.1016\/j.neucom.2024.127790_b24","series-title":"Point transformer","author":"Zhao","year":"2020"},{"key":"10.1016\/j.neucom.2024.127790_b25","doi-asserted-by":"crossref","unstructured":"J. Rock, T. Gupta, J. Thorsen, J.Y. Gwak, D. Hoiem, Completing 3D object shape from one depth image, in: 2015 IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2015.","DOI":"10.1109\/CVPR.2015.7298863"},{"issue":"2","key":"10.1016\/j.neucom.2024.127790_b26","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1111\/cgf.12573","article-title":"Database-assisted object retrieval for real-time 3D reconstruction","volume":"34","author":"Li","year":"2015","journal-title":"Comput. Graph. Forum"},{"issue":"6cd","key":"10.1016\/j.neucom.2024.127790_b27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2816795.2818094","article-title":"Data-driven structural priors for shape completion","volume":"34","author":"Sung","year":"2015","journal-title":"ACM Trans. Graph."},{"key":"10.1016\/j.neucom.2024.127790_b28","doi-asserted-by":"crossref","unstructured":"Y. Wang, D.J. Tan, N. Navab, F. Tombari, Forknet: Multi-branch volumetric semantic completion from a single depth image, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2019, pp. 8608\u20138617.","DOI":"10.1109\/ICCV.2019.00870"},{"key":"10.1016\/j.neucom.2024.127790_b29","series-title":"Unpaired point cloud completion on real scans using adversarial training","author":"Chen","year":"2019"},{"key":"10.1016\/j.neucom.2024.127790_b30","series-title":"Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part V 16","first-page":"283","article-title":"Weakly-supervised 3D shape completion in the wild","author":"Gu","year":"2020"},{"key":"10.1016\/j.neucom.2024.127790_b31","article-title":"Unsupervised learning of shape and pose with differentiable point clouds","volume":"31","author":"Insafutdinov","year":"2018","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2024.127790_b32","series-title":"Self-supervised point cloud completion via inpainting","author":"Mittal","year":"2021"},{"key":"10.1016\/j.neucom.2024.127790_b33","doi-asserted-by":"crossref","unstructured":"J. Zhang, X. Chen, Z. Cai, L. Pan, H. Zhao, S. Yi, C.K. Yeo, B. Dai, C.C. Loy, Unsupervised 3d shape completion through gan inversion, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 1768\u20131777.","DOI":"10.1109\/CVPR46437.2021.00181"},{"key":"10.1016\/j.neucom.2024.127790_b34","doi-asserted-by":"crossref","unstructured":"X. Wen, Z. Han, Y.-P. Cao, P. Wan, W. Zheng, Y.-S. Liu, Cycle4completion: Unpaired point cloud completion using cycle transformation with missing region coding, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 13080\u201313089.","DOI":"10.1109\/CVPR46437.2021.01288"},{"key":"10.1016\/j.neucom.2024.127790_b35","series-title":"European Conference on Computer Vision","first-page":"517","article-title":"Optimization over disentangled encoding: Unsupervised cross-domain point cloud completion via occlusion factor manipulation","author":"Gong","year":"2022"},{"key":"10.1016\/j.neucom.2024.127790_b36","doi-asserted-by":"crossref","unstructured":"S. Hong, M. Yavartanoo, R. Neshatavar, K.M. Lee, ACL-SPC: Adaptive Closed-Loop system for Self-Supervised Point Cloud Completion, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 9435\u20139444.","DOI":"10.1109\/CVPR52729.2023.00910"},{"key":"10.1016\/j.neucom.2024.127790_b37","doi-asserted-by":"crossref","unstructured":"R. Cui, S. Qiu, S. Anwar, J. Liu, C. Xing, J. Zhang, N. Barnes, P2C: Self-supervised point cloud completion from single partial clouds, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2023, pp. 14351\u201314360.","DOI":"10.1109\/ICCV51070.2023.01320"},{"key":"10.1016\/j.neucom.2024.127790_b38","series-title":"Bert: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2018"},{"key":"10.1016\/j.neucom.2024.127790_b39","doi-asserted-by":"crossref","unstructured":"Z. Liu, Y. Lin, Y. Cao, H. Hu, Y. Wei, Z. Zhang, S. Lin, B. Guo, Swin transformer: Hierarchical vision transformer using shifted windows, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2021, pp. 10012\u201310022.","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"10.1016\/j.neucom.2024.127790_b40","article-title":"Dynamicvit: Efficient vision transformers with dynamic token sparsification","volume":"34","author":"Rao","year":"2021","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2024.127790_b41","series-title":"PU-transformer: Point cloud upsampling transformer","author":"Qiu","year":"2021"},{"key":"10.1016\/j.neucom.2024.127790_b42","series-title":"Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part XXV 16","first-page":"512","article-title":"Detail preserved point cloud completion via separated feature aggregation","author":"Zhang","year":"2020"},{"key":"10.1016\/j.neucom.2024.127790_b43","series-title":"MFM-Net: Unpaired shape completion network with multi-stage feature matching","first-page":"12","author":"Cao","year":"2021"},{"key":"10.1016\/j.neucom.2024.127790_b44","article-title":"Point cloud completion via skeleton-detail transformer","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Vis. Comput. Graphics"},{"key":"10.1016\/j.neucom.2024.127790_b45","doi-asserted-by":"crossref","unstructured":"Z. Zhu, H. Chen, X. He, W. Wang, J. Qin, M. Wei, SVDFormer: Complementing point cloud via self-view augmentation and self-structure dual-generator, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2023, pp. 14508\u201314518.","DOI":"10.1109\/ICCV51070.2023.01334"},{"key":"10.1016\/j.neucom.2024.127790_b46","doi-asserted-by":"crossref","DOI":"10.1016\/j.cagd.2020.101925","article-title":"Multi-stage point completion network with critical set supervision","volume":"82","author":"Zhang","year":"2020","journal-title":"Comput. Aided Geom. Design"},{"issue":"5","key":"10.1016\/j.neucom.2024.127790_b47","first-page":"6320","article-title":"Snowflake point deconvolution for point cloud completion and generation with skip-transformer","volume":"45","author":"Xiang","year":"2022","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2024.127790_b48","doi-asserted-by":"crossref","unstructured":"X. Yu, Y. Rao, Z. Wang, Z. Liu, J. Lu, J. Zhou, PoinTr: Diverse point cloud completion with geometry-aware transformers, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2021, pp. 12498\u201312507.","DOI":"10.1109\/ICCV48922.2021.01227"},{"key":"10.1016\/j.neucom.2024.127790_b49","series-title":"Densenet: Implementing efficient convnet descriptor pyramids","author":"Iandola","year":"2014"},{"key":"10.1016\/j.neucom.2024.127790_b50","doi-asserted-by":"crossref","unstructured":"H. Fan, H. Su, L.J. Guibas, A point set generation network for 3d object reconstruction from a single image, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 605\u2013613.","DOI":"10.1109\/CVPR.2017.264"},{"key":"10.1016\/j.neucom.2024.127790_b51","doi-asserted-by":"crossref","unstructured":"A. Dai, A.X. Chang, M. Savva, M. Halber, T. Funkhouser, M. Nie\u00dfner, ScanNet: Richly-annotated 3d reconstructions of indoor scenes, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 5828\u20135839.","DOI":"10.1109\/CVPR.2017.261"},{"key":"10.1016\/j.neucom.2024.127790_b52","series-title":"MatterPort3D: Learning from rgb-d data in indoor environments","author":"Chang","year":"2017"},{"key":"10.1016\/j.neucom.2024.127790_b53","article-title":"PyTorch: An imperative style, high-performance deep learning library","volume":"32","author":"Paszke","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2024.127790_b54","series-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014"},{"key":"10.1016\/j.neucom.2024.127790_b55","doi-asserted-by":"crossref","unstructured":"Y. Yang, F. Chen, Y. Shen, T. Dong, FoldingNet: Point Cloud Auto-Encoder via Deep Grid Deformation, in: 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2018.","DOI":"10.1109\/CVPR.2018.00029"},{"key":"10.1016\/j.neucom.2024.127790_b56","doi-asserted-by":"crossref","unstructured":"T. Groueix, M. Fisher, V.G. Kim, B.C. Russell, M. Aubry, A papier-m\u00e2ch\u00e9 approach to learning 3d surface generation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 216\u2013224.","DOI":"10.1109\/CVPR.2018.00030"},{"key":"10.1016\/j.neucom.2024.127790_b57","doi-asserted-by":"crossref","unstructured":"M. Liu, L. Sheng, S. Yang, J. Shao, S.-M. Hu, Morphing and sampling network for dense point cloud completion, in: Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 34, No. 07, 2020, pp. 11596\u201311603.","DOI":"10.1609\/aaai.v34i07.6827"},{"key":"10.1016\/j.neucom.2024.127790_b58","unstructured":"Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, J. Xiao, 3d shapenets: A deep representation for volumetric shapes, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015, pp. 1912\u20131920."},{"key":"10.1016\/j.neucom.2024.127790_b59","series-title":"European Conference on Computer Vision","first-page":"70","article-title":"Softpoolnet: Shape descriptor for point cloud completion and classification","author":"Wang","year":"2020"},{"issue":"11","key":"10.1016\/j.neucom.2024.127790_b60","doi-asserted-by":"crossref","first-page":"1231","DOI":"10.1177\/0278364913491297","article-title":"Vision meets robotics: The kitti dataset","volume":"32","author":"Geiger","year":"2013","journal-title":"Int. J. Robot. Res."},{"key":"10.1016\/j.neucom.2024.127790_b61","series-title":"2021 International Conference on 3D Vision","first-page":"1014","article-title":"PolyNet: Polynomial neural network for 3d shape recognition with polyshape representation","author":"Yavartanoo","year":"2021"}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231224005617?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231224005617?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,5,27]],"date-time":"2024-05-27T21:22:27Z","timestamp":1716844947000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231224005617"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8]]},"references-count":61,"alternative-id":["S0925231224005617"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2024.127790","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2024,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"CompleteDT: Point cloud completion with information-perception transformers","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2024.127790","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"127790"}}