{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T05:40:49Z","timestamp":1771047649554,"version":"3.50.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2025,5,22]],"date-time":"2025-05-22T00:00:00Z","timestamp":1747872000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,5,22]],"date-time":"2025-05-22T00:00:00Z","timestamp":1747872000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"crossref","award":["RS-2024-00336077"],"award-info":[{"award-number":["RS-2024-00336077"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"crossref","award":["RS-2022-00166699"],"award-info":[{"award-number":["RS-2022-00166699"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"crossref","award":["RS-2023-NR076676"],"award-info":[{"award-number":["RS-2023-NR076676"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Glob Optim"],"published-print":{"date-parts":[[2025,7]]},"DOI":"10.1007\/s10898-025-01506-4","type":"journal-article","created":{"date-parts":[[2025,5,22]],"date-time":"2025-05-22T02:21:16Z","timestamp":1747880476000},"page":"713-736","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["On the convergence result of the gradient-push algorithm on directed graphs with constant stepsize"],"prefix":"10.1007","volume":"92","author":[{"given":"Woocheol","family":"Choi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4996-0200","authenticated-orcid":false,"given":"Doheon","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seok-Bae","family":"Yun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,5,22]]},"reference":[{"issue":"3","key":"1506_CR1","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1109\/TCNS.2015.2505149","volume":"4","author":"M Akbari","year":"2017","unstructured":"Akbari, M., Gharesifard, B., Linder, T.: Distributed Online Convex Optimization on Time-Varying Directed Graphs. IEEE Transactions on Control of Network Systems 4(3), 417\u2013428 (2017)","journal-title":"IEEE Transactions on Control of Network Systems"},{"key":"1506_CR2","first-page":"344","volume":"97","author":"M Assran","year":"2019","unstructured":"Assran, M., Loizou, N., Ballas, N., Rabbat, M.: Stochastic gradient push for distributed deep learning. in 36th International Conference on Machine Learning. 97, 344\u2013353 (2019). (PMLR)","journal-title":"in 36th International Conference on Machine Learning."},{"issue":"3","key":"1506_CR3","doi-asserted-by":"publisher","first-page":"1847","DOI":"10.1109\/TSP.2009.2038417","volume":"58","author":"JA Bazerque","year":"2010","unstructured":"Bazerque, J.A., Giannakis, G.B.: Distributed spectrum sensing for cognitive radio networks by exploiting sparsity. IEEE Trans. Signal Process. 58(3), 1847\u20131862 (2010)","journal-title":"IEEE Trans. Signal Process."},{"issue":"8","key":"1506_CR4","doi-asserted-by":"publisher","first-page":"3141","DOI":"10.1109\/TAC.2018.2880407","volume":"64","author":"AS Berahas","year":"2018","unstructured":"Berahas, A.S., Bollapragada, R., Keskar, N.S., Wei, E.: Balancing communication and computation in distributed optimization. IEEE Trans. Autom. Control 64(8), 3141\u20133155 (2018)","journal-title":"IEEE Trans. Autom. Control"},{"issue":"2","key":"1506_CR5","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1137\/16M1080173","volume":"60","author":"L Bottou","year":"2018","unstructured":"Bottou, L., Curtis, F.E., Nocedal, J.: Optimization methods for large-scale machine learning. SIAM Review 60(2), 223\u2013311 (2018)","journal-title":"SIAM Review"},{"issue":"3\u20134","key":"1506_CR6","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1561\/2200000050","volume":"8","author":"S Bubeck","year":"2015","unstructured":"Bubeck, S.: Convex optimization: Algorithms and complexity. Foundations and Trends in Machine Learning 8(3\u20134), 231\u2013357 (2015)","journal-title":"Foundations and Trends in Machine Learning"},{"key":"1506_CR7","doi-asserted-by":"publisher","DOI":"10.1515\/9781400831470","volume-title":"Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms","author":"F Bullo","year":"2009","unstructured":"Bullo, F., Cortes, J., Martinez, S.: Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms, vol. 27. Princeton University Press, Princeton (2009)"},{"key":"1506_CR8","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1109\/TII.2012.2219061","volume":"9","author":"Y Cao","year":"2013","unstructured":"Cao, Y., Yu, W., Ren, W., Chen, G.: An overview of recent progress in the study of distributed multi-agent coordination. IEEE Trans Ind. Informat. 9, 427\u2013438 (2013)","journal-title":"IEEE Trans Ind. Informat."},{"key":"1506_CR9","doi-asserted-by":"crossref","unstructured":"Chen, A.I., Ozdaglar, A.: A fast distributed proximal-gradient method, in Communication, Control, and Computing (Allerton), 2012 50th Annual Allerton Conference on. IEEE, pp. 601-608 (2012)","DOI":"10.1109\/Allerton.2012.6483273"},{"key":"1506_CR10","unstructured":"Choi, H., Choi, W., Kim, G.: Convergence result for the gradient-push algorithm and its application to boost up the Push-DIGing algorithm, arXiv:2407.13564"},{"issue":"1","key":"1506_CR11","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1007\/s10957-022-02069-0","volume":"195","author":"W Choi","year":"2022","unstructured":"Choi, W., Kim, D., Yun, S.: Convergence results of a nested decentralized gradient method for non-strongly convex problems. J. Optim. Theory Appl. 195(1), 172\u2013204 (2022)","journal-title":"J. Optim. Theory Appl."},{"key":"1506_CR12","unstructured":"Choi, W., Kim, J.: On the convergence of decentralized gradient descent with diminishing stepsize, revisited, arXiv:2203.09079"},{"key":"1506_CR13","first-page":"1663","volume":"11","author":"PA Forero","year":"2010","unstructured":"Forero, P.A., Cano, A., Giannakis, G.B.: Consensus-based distributed support vector machines. Journal of Machine Learning Research 11, 1663\u20131707 (2010)","journal-title":"Journal of Machine Learning Research"},{"key":"1506_CR14","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1109\/MSP.2013.2245726","volume":"30","author":"GB Giannakis","year":"2013","unstructured":"Giannakis, G.B., Kekatos, V., Gatsis, N., Kim, S.-J., Zhu, H., Wollenberg, B.: Mon-itoring and optimization for power grids: A signal processing perspective. IEEE Signal Processing Mag. 30, 107\u2013128 (2013)","journal-title":"IEEE Signal Processing Mag."},{"issue":"5","key":"1506_CR15","doi-asserted-by":"publisher","first-page":"1131","DOI":"10.1109\/TAC.2014.2298712","volume":"59","author":"D Jakovetic","year":"2014","unstructured":"Jakovetic, D., Xavier, J., Moura, J.M.F.: Fast Distributed Gradient Methods. IEEE Transactions on Automatic Control 59(5), 1131\u20131146 (2014)","journal-title":"IEEE Transactions on Automatic Control"},{"key":"1506_CR16","doi-asserted-by":"publisher","first-page":"1617","DOI":"10.1109\/TPWRS.2012.2219629","volume":"28","author":"V Kekatos","year":"2013","unstructured":"Kekatos, V., Giannakis, G.B.: Distributed robust power system state estimation. IEEE Trans. Power Syst. 28, 1617\u20131626 (2013)","journal-title":"IEEE Trans. Power Syst."},{"key":"1506_CR17","first-page":"482","volume-title":"Gossip-based computation of aggregate information\u201d,\" in Proc","author":"D Kempe","year":"2003","unstructured":"Kempe, D., Dobra, A., Gehrke, J.: Gossip-based computation of aggregate information\u201d,\" in Proc, pp. 482\u2013491. Washington, DC, USA, IEEE Symp. Found. Comput. Sci. (2003)"},{"key":"1506_CR18","doi-asserted-by":"publisher","first-page":"517","DOI":"10.1109\/ACCESS.2022.3233233","volume":"11","author":"J Kim","year":"2023","unstructured":"Kim, J., Choi, W.: Gradient-push algorithm for distributed optimization with event-triggered communications. IEEE Access 11, 517\u2013534 (2023)","journal-title":"IEEE Access"},{"key":"1506_CR19","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.neucom.2019.03.094","volume":"416","author":"J Li","year":"2020","unstructured":"Li, J., Gu, C., Wu, Z.: Online distributed stochastic learning algorithm for convex optimization in time-varying directed networks. Neurocomputing 416, 85\u201394 (2020)","journal-title":"Neurocomputing"},{"key":"1506_CR20","first-page":"4649","volume":"2022","author":"Q Lin","year":"2022","unstructured":"Lin, Q., Ling, Q., Graphs, Decentralized Multi-Agent Policy Evaluation Over Directed.: 41st Chinese Control Conference (CCC). Hefei, China 2022, 4649\u20134654 (2022)","journal-title":"Hefei, China"},{"issue":"1","key":"1506_CR21","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1109\/TAC.2008.2009515","volume":"54","author":"A Nedi\u0107","year":"2009","unstructured":"Nedi\u0107, A., Ozdaglar, A.: Distributed subgradient methods for multi-agent optimization. IEEE Transactions on Automatic Control 54(1), 48 (2009)","journal-title":"IEEE Transactions on Automatic Control"},{"issue":"12","key":"1506_CR22","doi-asserted-by":"publisher","first-page":"3936","DOI":"10.1109\/TAC.2016.2529285","volume":"61","author":"A Nedi\u0107","year":"2016","unstructured":"Nedi\u0107, A., Olshevsky, A.: Stochastic gradient-push for strongly convex functions on time-varying directed graphs. IEEE Transactions on Automatic Control 61(12), 3936\u20133947 (2016)","journal-title":"IEEE Transactions on Automatic Control"},{"issue":"3","key":"1506_CR23","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1109\/TAC.2014.2364096","volume":"60","author":"A Nedi\u0107","year":"2014","unstructured":"Nedi\u0107, A., Olshevsky, A.: Distributed optimization over time-varying directed graphs. IEEE Transactions on Automatic Control 60(3), 601\u2013615 (2014)","journal-title":"IEEE Transactions on Automatic Control"},{"issue":"4","key":"1506_CR24","doi-asserted-by":"publisher","first-page":"2597","DOI":"10.1137\/16M1084316","volume":"27","author":"A Nedi\u0107","year":"2017","unstructured":"Nedi\u0107, A., Olshevsky, A., Shi, W.: Achieving geometric convergence for distributed optimization over time-varying graphs. SIAM Journal on Optimization 27(4), 2597\u20132633 (2017)","journal-title":"SIAM Journal on Optimization"},{"issue":"1","key":"1506_CR25","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TAC.2020.2972824","volume":"66","author":"S Pu","year":"2021","unstructured":"Pu, S., Shi, W., Xu, J., Nedi\u0107, A.: Push-pull gradient methods for distributed optimization in networks. IEEE Trans. Autom. Control 66(1), 1\u201316 (2021)","journal-title":"IEEE Trans. Autom. Control"},{"issue":"3","key":"1506_CR26","doi-asserted-by":"publisher","first-page":"1245","DOI":"10.1109\/TCNS.2017.2698261","volume":"5","author":"G Qu","year":"2018","unstructured":"Qu, G., Li, N.: Harnessing smoothness to accelerate distributed optimization. IEEE Transactions on Control of Network Systems 5(3), 1245\u20131260 (2018)","journal-title":"IEEE Transactions on Control of Network Systems"},{"issue":"1","key":"1506_CR27","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1109\/TSP.2015.2472372","volume":"64","author":"H Raja","year":"2016","unstructured":"Raja, H., Bajwa, W.U.: Cloud K-SVD: A collaborative dictionary learning algorithm for big, distributed data. IEEE Transactions on Signal Processing 64(1), 173\u2013188 (2016)","journal-title":"IEEE Transactions on Signal Processing"},{"key":"1506_CR28","unstructured":"Ren, W.: Consensus Based Formation Control Strategies for Multi-Vehicle Systems, in Proceedings of the Amer-ican Control Conference, pp. 4237\u20134242 (2006)"},{"key":"1506_CR29","doi-asserted-by":"crossref","unstructured":"Sayed, A.H.: Diffusion adaptation over networks. Academic Press Library in Signal Processing, vol. 3 (2013)","DOI":"10.1016\/B978-0-12-411597-2.00009-6"},{"issue":"4","key":"1506_CR30","doi-asserted-by":"publisher","first-page":"1650","DOI":"10.1109\/TSP.2007.908943","volume":"56","author":"ID Schizas","year":"2008","unstructured":"Schizas, I.D., Giannakis, G.B., Roumeliotis, S.I., Ribeiro, A.: Consensus in ad hoc WSNs with noisy links-part II: distributed estimation and smoothing of random signals. IEEE Trans. Signal Process. 56(4), 1650\u20131666 (2008)","journal-title":"IEEE Trans. Signal Process."},{"key":"1506_CR31","doi-asserted-by":"publisher","DOI":"10.1007\/0-387-32792-4","volume-title":"Non-negative matrices and Markov chains","author":"E Seneta","year":"1981","unstructured":"Seneta, E.: Non-negative matrices and Markov chains, 2nd edn. Springer-Verlag, New York (1981)","edition":"2"},{"issue":"2","key":"1506_CR32","doi-asserted-by":"publisher","first-page":"944","DOI":"10.1137\/14096668X","volume":"25","author":"W Shi","year":"2015","unstructured":"Shi, W., Ling, Q., Wu, G., Yin, W.: Extra: an exact first-order algorithm for decentralized consensus optimization. SIAM J. Optim. 25(2), 944\u2013966 (2015)","journal-title":"SIAM J. Optim."},{"issue":"7","key":"1506_CR33","doi-asserted-by":"publisher","first-page":"1750","DOI":"10.1109\/TSP.2014.2304432","volume":"62","author":"W Shi","year":"2014","unstructured":"Shi, W., Ling, Q., Yuan, K., Wu, G., Yin, W.: On the linear convergence of theADMMin decentralized consensus optimization. IEEE Trans. Signal Process. 62(7), 1750\u20131761 (2014)","journal-title":"IEEE Trans. Signal Process."},{"key":"1506_CR34","unstructured":"Taheri, H., Mokhtari, A., Hassani, H., Pedarsani, R.: Quantized decentralized stochastic learning over directed graphs. In International Conference on Machine Learning, (2020)"},{"issue":"8","key":"1506_CR35","doi-asserted-by":"publisher","first-page":"3744","DOI":"10.1109\/TAC.2017.2648041","volume":"62","author":"T Tatarenko","year":"2017","unstructured":"Tatarenko, T., Touri, B.: Non-convex distributed optimization. IEEE Trans. Automat. Control 62(8), 3744\u20133757 (2017)","journal-title":"IEEE Trans. Automat. Control"},{"key":"1506_CR36","unstructured":"Tsianos, K., Lawlor, S., Rabbat, M.G.: Communication\/computation tradeoffs in consensus-based distributed optimization, in Proc. Adv. Neural Inf. Process. Syst., pp. 1943-1951 (2012)"},{"key":"1506_CR37","doi-asserted-by":"crossref","unstructured":"Tsianos, K.I., Lawlor, S., Rabbat, M.G.: Consensus-based distributed optimization: Practical issues and applications in large-scale machine learning, in Proceedings of the IEEE Allerton Conference on Communication, Control, and Computing, IEEE, New York, pp. 1543\u20131550, (2012)","DOI":"10.1109\/Allerton.2012.6483403"},{"key":"1506_CR38","doi-asserted-by":"crossref","unstructured":"Tsianos, K.I., Lawlor, S., Rabbat, M.G.: Push-sum distributed dual averaging for convex optimization, in Proc. IEEE Conf. Dec. Control pp. 5453\u20135458. Maui, HI, USA, IEEE Conf. Dec. Control (2012)","DOI":"10.1109\/CDC.2012.6426375"},{"issue":"4","key":"1506_CR39","doi-asserted-by":"publisher","first-page":"2263","DOI":"10.1109\/TCYB.2020.2999309","volume":"52","author":"C Wang","year":"2022","unstructured":"Wang, C., Xu, S., Yuan, D., Zhang, B., Zhang, Z.: Push-Sum Distributed Online Optimization With Bandit Feedback. IEEE Transactions on Cybernetics 52(4), 2263\u20132273 (2022)","journal-title":"IEEE Transactions on Cybernetics"},{"issue":"10","key":"1506_CR40","doi-asserted-by":"publisher","first-page":"4980","DOI":"10.1109\/TAC.2017.2672698","volume":"62","author":"C Xi","year":"2017","unstructured":"Xi, C., Khan, U.A.: DEXTRA: A fast algorithm for optimization over directed graphs. IEEE Transactions on Automatic Control 62(10), 4980\u20134993 (2017)","journal-title":"IEEE Transactions on Automatic Control"},{"issue":"3","key":"1506_CR41","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1109\/LCSYS.2018.2834316","volume":"2","author":"R Xin","year":"2018","unstructured":"Xin, R., Khan, U.A.: A linear algorithm for optimization over directed graphs with geometric convergence. IEEE Control Syst. Lett. 2(3), 315\u2013320 (2018)","journal-title":"IEEE Control Syst. Lett."},{"key":"1506_CR42","doi-asserted-by":"crossref","unstructured":"Xin, R., Sahu, A.K., Khan, U.A., Kar, S.: Distributed stochastic optimization with gradient tracking over strongly-connected networks, in 58th IEEE Conference on Decision and Control, pp. 8353-8358 (2019)","DOI":"10.1109\/CDC40024.2019.9029217"},{"key":"1506_CR43","doi-asserted-by":"publisher","first-page":"1329","DOI":"10.1109\/TAC.2017.2737582","volume":"63","author":"C Xi","year":"2018","unstructured":"Xi, C., Xin, R., Khan, U.: ADD-OPT: Accelerated Distributed Directed Optimization. IEEE Transactions on Automatic Control 63, 1329\u20131339 (2018)","journal-title":"IEEE Transactions on Automatic Control"},{"key":"1506_CR44","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1016\/j.arcontrol.2019.05.006","volume":"47","author":"T Yang","year":"2019","unstructured":"Yang, T., Yi, X., Wu, J., Yuan, Y., Wu, D., Meng, Z., Hong, Y., Wang, H., Lin, Z., Johansson, K.H.: A survey of distributed optimization. Annual Reviews in Control 47, 278\u2013305 (2019)","journal-title":"Annual Reviews in Control"},{"issue":"3","key":"1506_CR45","doi-asserted-by":"publisher","first-page":"1835","DOI":"10.1137\/130943170","volume":"26","author":"K Yuan","year":"2016","unstructured":"Yuan, K., Ling, Q., Yin, W.: On the convergence of decentralized gradient descent. SIAM Journal on Optimization 26(3), 1835\u20131854 (2016)","journal-title":"SIAM Journal on Optimization"},{"issue":"10","key":"1506_CR46","doi-asserted-by":"publisher","first-page":"1569","DOI":"10.1002\/rnc.3164","volume":"25","author":"D Yuan","year":"2015","unstructured":"Yuan, D., Xu, S., Lu, J.: Gradient-free method for distributed multi-agent optimization via push-sum algorithms. Internat. J. Robust Nonlinear Control 25(10), 1569\u20131580 (2015)","journal-title":"Internat. J. Robust Nonlinear Control"},{"issue":"6","key":"1506_CR47","doi-asserted-by":"publisher","first-page":"5095","DOI":"10.1109\/TIE.2016.2617832","volume":"64","author":"T Yang","year":"2017","unstructured":"Yang, T., et al.: A Distributed Algorithm for Economic Dispatch Over Time-Varying Directed Networks With Delays. IEEE Transactions on Industrial Electronics 64(6), 5095\u20135106 (2017)","journal-title":"IEEE Transactions on Industrial Electronics"},{"issue":"1","key":"1506_CR48","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1109\/TAC.2020.2981035","volume":"66","author":"MS Assran","year":"2021","unstructured":"Assran, M.S., Rabbat, M.G.: Asynchronous Gradient Push. IEEE Transactions on Automatic Control 66(1), 168\u2013183 (2021)","journal-title":"IEEE Transactions on Automatic Control"},{"key":"1506_CR49","doi-asserted-by":"crossref","unstructured":"Yu, W., Liu, H., Zheng, W., Zhu, Y.: Distributed discrete-time convex optimization with nonidentical local constraints over time-varying unbalanced directed graphs. Automatica J. IFAC 134 (2021)","DOI":"10.1016\/j.automatica.2021.109899"}],"container-title":["Journal of Global Optimization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10898-025-01506-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10898-025-01506-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10898-025-01506-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T06:49:27Z","timestamp":1751611767000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10898-025-01506-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,22]]},"references-count":49,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,7]]}},"alternative-id":["1506"],"URL":"https:\/\/doi.org\/10.1007\/s10898-025-01506-4","relation":{},"ISSN":["0925-5001","1573-2916"],"issn-type":[{"value":"0925-5001","type":"print"},{"value":"1573-2916","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,22]]},"assertion":[{"value":"31 August 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 May 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 May 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}