{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T04:21:39Z","timestamp":1783052499264,"version":"3.54.6"},"reference-count":58,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing Municipality","doi-asserted-by":"publisher","award":["CSTB2024NSCQ-KJFZZDX0036"],"award-info":[{"award-number":["CSTB2024NSCQ-KJFZZDX0036"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012669","name":"Natural Science Foundation Project of Chongqing","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012669","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62376042"],"award-info":[{"award-number":["62376042"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Image and Vision Computing"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.imavis.2026.106012","type":"journal-article","created":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T21:59:22Z","timestamp":1777931962000},"page":"106012","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["GlowPrior-ADNet: A Bayesian variational dehazing framework with flow-based clean-image prior"],"prefix":"10.1016","volume":"171","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-0709-1714","authenticated-orcid":false,"given":"Fangtao","family":"Qin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Fang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pinjie","family":"You","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.imavis.2026.106012_b1","series-title":"Fog simulation on real lidar point clouds for 3d object detection in adverse weather","author":"Hahner","year":"2021"},{"key":"10.1016\/j.imavis.2026.106012_b2","series-title":"Seeing through fog without seeing fog: Deep sensor fusion in the absence of labeled training data","author":"Bijelic","year":"2019"},{"key":"10.1016\/j.imavis.2026.106012_b3","series-title":"Model adaptation with synthetic and real data for semantic dense foggy scene understanding","author":"Sakaridis","year":"2018"},{"key":"10.1016\/j.imavis.2026.106012_b4","series-title":"2019 IEEE\/CVF International Conference on Computer Vision, ICCV 2019, Seoul, Korea (South), October 27 - November 2, 2019","first-page":"9328","article-title":"Exploring the limitations of behavior cloning for autonomous driving","author":"Codevilla","year":"2019"},{"issue":"12","key":"10.1016\/j.imavis.2026.106012_b5","first-page":"2341","article-title":"Single image haze removal using dark channel prior","volume":"33","author":"He","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.imavis.2026.106012_b6","series-title":"Optics of the atmosphere: scattering by molecules and particles","author":"McCartney","year":"1976"},{"issue":"12","key":"10.1016\/j.imavis.2026.106012_b7","doi-asserted-by":"crossref","first-page":"4695","DOI":"10.1109\/TIP.2012.2214050","article-title":"No-reference image quality assessment in the spatial domain","volume":"21","author":"Mittal","year":"2012","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"10.1016\/j.imavis.2026.106012_b8","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1109\/LSP.2012.2227726","article-title":"Making a \u201ccompletely blind\u201d image quality analyzer","volume":"20","author":"Mittal","year":"2012","journal-title":"IEEE Signal Process. Lett."},{"key":"10.1016\/j.imavis.2026.106012_b9","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1023\/A:1016328200723","article-title":"Vision and the atmosphere","volume":"48","author":"Narasimhan","year":"2002","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.imavis.2026.106012_b10","doi-asserted-by":"crossref","first-page":"3391","DOI":"10.1109\/TIP.2021.3060873","article-title":"Refinednet: A weakly supervised refinement framework for single image dehazing","volume":"30","author":"Zhao","year":"2021","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.imavis.2026.106012_b11","doi-asserted-by":"crossref","unstructured":"H. Zhang, V.M. Patel, Densely connected pyramid dehazing network, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 3194\u20133203.","DOI":"10.1109\/CVPR.2018.00337"},{"key":"10.1016\/j.imavis.2026.106012_b12","doi-asserted-by":"crossref","unstructured":"Y. Pang, J. Nie, J. Xie, J. Han, X. Li, Bidnet: Binocular image dehazing without explicit disparity estimation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 5931\u20135940.","DOI":"10.1109\/CVPR42600.2020.00597"},{"key":"10.1016\/j.imavis.2026.106012_b13","doi-asserted-by":"crossref","first-page":"1754","DOI":"10.1007\/s11263-021-01431-5","article-title":"You only look yourself: Unsupervised and untrained single image dehazing neural network","volume":"129","author":"Li","year":"2021","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.imavis.2026.106012_b14","doi-asserted-by":"crossref","unstructured":"H. Dong, J. Pan, L. Xiang, Z. Hu, X. Zhang, F. Wang, M.-H. Yang, Multi-scale boosted dehazing network with dense feature fusion, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 2157\u20132167.","DOI":"10.1109\/CVPR42600.2020.00223"},{"key":"10.1016\/j.imavis.2026.106012_b15","doi-asserted-by":"crossref","unstructured":"X. Liu, Y. Ma, Z. Shi, J. Chen, Griddehazenet: Attention-based multi-scale network for image dehazing, in: Proceedings of the IEEE\/CVF International Conference on Computer Vision, 2019, pp. 7314\u20137323.","DOI":"10.1109\/ICCV.2019.00741"},{"key":"10.1016\/j.imavis.2026.106012_b16","series-title":"Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part II 14","first-page":"154","article-title":"Single image dehazing via multi-scale convolutional neural networks","author":"Ren","year":"2016"},{"key":"10.1016\/j.imavis.2026.106012_b17","doi-asserted-by":"crossref","unstructured":"Y. Yang, C. Wang, R. Liu, L. Zhang, X. Guo, D. Tao, Self-augmented unpaired image dehazing via density and depth decomposition, in: 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2022, pp. 2027\u20132036.","DOI":"10.1109\/CVPR52688.2022.00208"},{"key":"10.1016\/j.imavis.2026.106012_b18","doi-asserted-by":"crossref","first-page":"1927","DOI":"10.1109\/TIP.2023.3256763","article-title":"Vision transformers for single image dehazing","volume":"32","author":"Song","year":"2023","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.imavis.2026.106012_b19","doi-asserted-by":"crossref","first-page":"1361","DOI":"10.1109\/TIP.2024.3362153","article-title":"Ucl-dehaze: toward real-world image dehazing via unsupervised contrastive learning","volume":"33","author":"Wang","year":"2024","journal-title":"IEEE Trans. Image Process."},{"issue":"11","key":"10.1016\/j.imavis.2026.106012_b20","doi-asserted-by":"crossref","first-page":"3964","DOI":"10.1109\/TPAMI.2020.2992934","article-title":"Normalizing flows: An introduction and review of current methods","volume":"43","author":"Kobyzev","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"57","key":"10.1016\/j.imavis.2026.106012_b21","first-page":"1","article-title":"Normalizing flows for probabilistic modeling and inference","volume":"22","author":"Papamakarios","year":"2021","journal-title":"J. Mach. Learn. Res."},{"issue":"11","key":"10.1016\/j.imavis.2026.106012_b22","doi-asserted-by":"crossref","first-page":"3522","DOI":"10.1109\/TIP.2015.2446191","article-title":"A fast single image haze removal algorithm using color attenuation prior","volume":"24","author":"Zhu","year":"2015","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"10.1016\/j.imavis.2026.106012_b23","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2651362","article-title":"Dehazing using color-lines","volume":"34","author":"Fattal","year":"2014","journal-title":"ACM Trans. Graph."},{"issue":"1","key":"10.1016\/j.imavis.2026.106012_b24","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1109\/TIP.2018.2867951","article-title":"Benchmarking single-image dehazing and beyond","volume":"28","author":"Li","year":"2019","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.imavis.2026.106012_b25","doi-asserted-by":"crossref","unstructured":"M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, B. Schiele, The cityscapes dataset for semantic urban scene understanding, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2016.","DOI":"10.1109\/CVPR.2016.350"},{"key":"10.1016\/j.imavis.2026.106012_b26","doi-asserted-by":"crossref","unstructured":"R. Li, L.-F. Cheong, R.T. Tan, Heavy rain image restoration: Integrating physics model and conditional adversarial learning, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 1633\u20131642.","DOI":"10.1109\/CVPR.2019.00173"},{"key":"10.1016\/j.imavis.2026.106012_b27","first-page":"11908","article-title":"Ffa-net: Feature fusion attention network for single image dehazing","volume":"vol. 34","author":"Qin","year":"2020"},{"key":"10.1016\/j.imavis.2026.106012_b28","doi-asserted-by":"crossref","unstructured":"C.-L. Guo, Q. Yan, S. Anwar, R. Cong, W. Ren, C. Li, Image dehazing transformer with transmission-aware 3d position embedding, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 5812\u20135820.","DOI":"10.1109\/CVPR52688.2022.00572"},{"key":"10.1016\/j.imavis.2026.106012_b29","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2023.126535","article-title":"Visual transformer with stable prior and patch-level attention for single image dehazing","volume":"551","author":"Liu","year":"2023","journal-title":"Neurocomputing"},{"issue":"10","key":"10.1016\/j.imavis.2026.106012_b30","doi-asserted-by":"crossref","first-page":"5470","DOI":"10.1109\/TCSVT.2023.3256414","article-title":"Real-world non-homogeneous haze removal by sliding self-attention wavelet network","volume":"33","author":"Feng","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.imavis.2026.106012_b31","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110290","article-title":"Mcpnet: Multi-space color correction and features prior fusion for single-image dehazing in non-homogeneous haze scenarios","volume":"150","author":"Lyu","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.imavis.2026.106012_b32","doi-asserted-by":"crossref","unstructured":"D. Engin, A. Genc, H. Kemal Ekenel, Cycle-dehaze: Enhanced cyclegan for single image dehazing, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2018.","DOI":"10.1109\/CVPRW.2018.00127"},{"key":"10.1016\/j.imavis.2026.106012_b33","doi-asserted-by":"crossref","first-page":"7819","DOI":"10.1109\/TIP.2020.3007844","article-title":"End-to-end single image fog removal using enhanced cycle consistent adversarial networks","volume":"29","author":"Liu","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.imavis.2026.106012_b34","doi-asserted-by":"crossref","first-page":"8457","DOI":"10.1109\/TIP.2020.3016134","article-title":"Zero-shot image dehazing","volume":"29","author":"Li","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.imavis.2026.106012_b35","doi-asserted-by":"crossref","first-page":"2692","DOI":"10.1109\/TIP.2019.2952032","article-title":"Unsupervised single image dehazing using dark channel prior loss","volume":"29","author":"Golts","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.imavis.2026.106012_b36","doi-asserted-by":"crossref","unstructured":"Z. Chen, Y. Wang, Y. Yang, D. Liu, Psd: Principled synthetic-to-real dehazing guided by physical priors, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR, 2021, pp. 7180\u20137189.","DOI":"10.1109\/CVPR46437.2021.00710"},{"key":"10.1016\/j.imavis.2026.106012_b37","doi-asserted-by":"crossref","unstructured":"Y. Zheng, J. Zhan, S. He, J. Dong, Y. Du, Curricular contrastive regularization for physics-aware single image dehazing, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 5785\u20135794.","DOI":"10.1109\/CVPR52729.2023.00560"},{"key":"10.1016\/j.imavis.2026.106012_b38","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111596","article-title":"Real-world nighttime image dehazing using contrastive and adversarial learning","volume":"165","author":"Deng","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.imavis.2026.106012_b39","doi-asserted-by":"crossref","first-page":"9136","DOI":"10.1109\/TIP.2021.3122806","article-title":"Non-homogeneous haze removal via artificial scene prior and bidimensional graph reasoning","volume":"30","author":"Wei","year":"2021","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.imavis.2026.106012_b40","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106281","article-title":"Frequency compensated diffusion model for real-scene dehazing","volume":"175","author":"Wang","year":"2024","journal-title":"Neural Netw."},{"key":"10.1016\/j.imavis.2026.106012_b41","doi-asserted-by":"crossref","unstructured":"D. Bose, V. Sethu, E. Ambikairajah, Continuous emotion ambiguity prediction: Modeling with beta distributions, IEEE Trans. Affect. Comput. 2024.","DOI":"10.1109\/TAFFC.2024.3367371"},{"key":"10.1016\/j.imavis.2026.106012_b42","series-title":"Non-aligned supervision for real image dehazing","author":"Fan","year":"2023"},{"key":"10.1016\/j.imavis.2026.106012_b43","doi-asserted-by":"crossref","unstructured":"H. Dong, J. Pan, L. Xiang, Z. Hu, X. Zhang, F. Wang, M.-H. Yang, Multi-scale boosted dehazing network with dense feature fusion, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 2157\u20132167.","DOI":"10.1109\/CVPR42600.2020.00223"},{"key":"10.1016\/j.imavis.2026.106012_b44","series-title":"Gaussian Markov Random Fields: Theory and Applications","author":"Rue","year":"2005"},{"issue":"1","key":"10.1016\/j.imavis.2026.106012_b45","article-title":"Auto-encoding variational bayes","volume":"2","author":"Chen","year":"2024","journal-title":"Camb. Explor. Arts Sci."},{"issue":"1","key":"10.1016\/j.imavis.2026.106012_b46","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1214\/aoms\/1177729694","article-title":"On information and sufficiency","volume":"22","author":"Kullback","year":"1951","journal-title":"Ann. Math. Stat."},{"key":"10.1016\/j.imavis.2026.106012_b47","article-title":"Glow: Generative flow with invertible 1x1 convolutions","volume":"31","author":"Kingma","year":"2018","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"11","key":"10.1016\/j.imavis.2026.106012_b48","doi-asserted-by":"crossref","first-page":"3888","DOI":"10.1109\/TIP.2015.2456502","article-title":"Referenceless prediction of perceptual fog density and perceptual image defogging","volume":"24","author":"Choi","year":"2015","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.imavis.2026.106012_b49","series-title":"2010 20th International Conference on Pattern Recognition","first-page":"2366","article-title":"Image quality metrics: Psnr vs. ssim","author":"Hore","year":"2010"},{"issue":"4","key":"10.1016\/j.imavis.2026.106012_b50","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: from error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.imavis.2026.106012_b51","doi-asserted-by":"crossref","first-page":"1788","DOI":"10.1109\/TIP.2019.2942504","article-title":"Learning interleaved cascade of shrinkage fields for joint image dehazing and denoising","volume":"29","author":"Wu","year":"2019","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.imavis.2026.106012_b52","series-title":"2022 China Automation Congress","first-page":"1901","article-title":"An improved u-net model for astronomical images denoising","author":"Qi","year":"2022"},{"key":"10.1016\/j.imavis.2026.106012_b53","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.1109\/TIP.2024.3354108","article-title":"Dea-net: Single image dehazing based on detail-enhanced convolution and content-guided attention","volume":"33","author":"Chen","year":"2024","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.imavis.2026.106012_b54","first-page":"1426","article-title":"Omni-kernel network for image restoration","volume":"vol. 38","author":"Cui","year":"2024"},{"issue":"4","key":"10.1016\/j.imavis.2026.106012_b55","doi-asserted-by":"crossref","first-page":"2807","DOI":"10.1007\/s00371-023-02987-8","article-title":"Dfc-dehaze: an improved cycle-consistent generative adversarial network for unpaired image dehazing","volume":"40","author":"Wang","year":"2024","journal-title":"Vis. Comput."},{"key":"10.1016\/j.imavis.2026.106012_b56","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110763","article-title":"Unsupervised multi-branch network with high-frequency enhancement for image dehazing","volume":"156","author":"Sun","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.imavis.2026.106012_b57","first-page":"4455","article-title":"Exploiting diffusion prior for real-world image dehazing with unpaired training","volume":"vol. 39","author":"Lan","year":"2025"},{"issue":"6","key":"10.1016\/j.imavis.2026.106012_b58","doi-asserted-by":"crossref","first-page":"1452","DOI":"10.1109\/TPAMI.2017.2723009","article-title":"Places: A 10 million image database for scene recognition","volume":"40","author":"Zhou","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Image and Vision Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0262885626001198?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0262885626001198?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T04:01:52Z","timestamp":1783051312000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0262885626001198"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":58,"alternative-id":["S0262885626001198"],"URL":"https:\/\/doi.org\/10.1016\/j.imavis.2026.106012","relation":{},"ISSN":["0262-8856"],"issn-type":[{"value":"0262-8856","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"GlowPrior-ADNet: A Bayesian variational dehazing framework with flow-based clean-image prior","name":"articletitle","label":"Article Title"},{"value":"Image and Vision Computing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.imavis.2026.106012","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"106012"}}