{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:36:10Z","timestamp":1760060170218,"version":"build-2065373602"},"reference-count":71,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T00:00:00Z","timestamp":1754179200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Machines"],"abstract":"<jats:p>This editorial introduces a Special Issue of Machines entitled \u201cRecent Developments in Machine Design, Automation and Robotics\u201d [...]<\/jats:p>","DOI":"10.3390\/machines13080683","type":"journal-article","created":{"date-parts":[[2025,8,5]],"date-time":"2025-08-05T10:50:21Z","timestamp":1754391021000},"page":"683","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Recent Developments in Machine Design, Automation and Robotics"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4167-4434","authenticated-orcid":false,"given":"Raul D. S. G.","family":"Campilho","sequence":"first","affiliation":[{"name":"CIDEM, ISEP\u2014School of Engineering, Polytechnic of Porto, 431, 4200-072 Porto, Portugal"},{"name":"INEGI\u2014Institute of Science and Innovation in Mechanical and Industrial Engineering, P\u00f3lo FEUP, 400, 4200-465 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.indmarman.2022.04.007","article-title":"Digital transformation and sustainable performance: The moderating role of market turbulence","volume":"104","author":"Li","year":"2022","journal-title":"Ind. Mark. Manag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"120271","DOI":"10.1016\/j.jenvman.2024.120271","article-title":"Unraveling the impact of digital transformation on green innovation through microdata and machine learning","volume":"354","author":"Han","year":"2024","journal-title":"J. Environ. Manag."},{"key":"ref_3","first-page":"100655","article-title":"Digital twin modelling for optimizing the material consumption: A case study on sustainability improvement of thermoforming process","volume":"35","author":"Turan","year":"2022","journal-title":"Sustain. Comput. Inform. Syst."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"101895","DOI":"10.1016\/j.rcim.2019.101895","article-title":"Digital twin-driven rapid reconfiguration of the automated manufacturing system via an open architecture model","volume":"63","author":"Leng","year":"2020","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Duro, R., and Kondratenko, Y. (2022). Advances in Intelligent Robotics and Collaborative Automation, CRC Press.","DOI":"10.1201\/9781003337119"},{"key":"ref_6","first-page":"338","article-title":"Enabling robotic adaptive behaviour capabilities for new industry 4.0 automated quality inspection paradigms","volume":"62","author":"Mineo","year":"2020","journal-title":"Insight Non Destr. Test. Cond. Monit."},{"key":"ref_7","first-page":"1525.68128","article-title":"Industrial revolution 5.0: The transformation of the modern manufacturing process to enable man and machine to work hand in hand","volume":"1533","author":"George","year":"2020","journal-title":"J. Seybold Rep. ISSN NO"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Ren, L., Dong, J., Liu, S., Zhang, L., and Wang, L. (2024). Embodied intelligence toward future smart manufacturing in the era of AI foundation model. IEEE\/ASME Trans. Mechatron., 1\u201311. early access.","DOI":"10.1109\/TMECH.2024.3456250"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1691","DOI":"10.1109\/TASE.2021.3122820","article-title":"An autonomous robotic platform for manipulation and inspection of metallic surfaces in industry 4.0","volume":"19","author":"Czimmermann","year":"2021","journal-title":"IEEE Trans. Autom. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"7092","DOI":"10.1109\/TSMC.2024.3446671","article-title":"Deep reinforcement learning of graph convolutional neural network for resilient production control of mass individualized prototyping toward industry 5.0","volume":"54","author":"Leng","year":"2024","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"119389","DOI":"10.1016\/j.applthermaleng.2022.119389","article-title":"Economically and thermodynamically efficient pressure-swing distillation with heat integration and heat pump techniques","volume":"218","author":"Zhai","year":"2023","journal-title":"Appl. Therm. Eng."},{"key":"ref_12","first-page":"43","article-title":"Manufacturing evolution: The intelligent automation revolution","volume":"64","author":"Lazarenko","year":"2025","journal-title":"Quality"},{"key":"ref_13","first-page":"107","article-title":"Robotic process automation with ML and artificial intelligence: Revolutionizing business processes","volume":"4","author":"Ghulaxe","year":"2024","journal-title":"Int. J. Eng. Technol. Manag. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Li, L., Liu, J., Wei, S., Chen, G., Blasch, E., and Pham, K. (2021, January 12\u201316). Smart robot-enabled remaining useful life prediction and maintenance optimization for complex structures using artificial intelligence and machine learning. Proceedings of the Sensors and Systems for Space Applications XIV, Online.","DOI":"10.1117\/12.2589045"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"127034","DOI":"10.1016\/j.eswa.2025.127034","article-title":"A system-centred predictive maintenance re-optimization method based on multi-agent deep reinforcement learning","volume":"274","author":"Zhang","year":"2025","journal-title":"Expert Syst. Appl."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Tsochev, G., and Sharabov, M. (2021). Artificial intelligence methods used in industry 4.0 in particular industrial control systems. AIP Conf. Proc., 2333.","DOI":"10.1063\/5.0041610"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1224","DOI":"10.1016\/j.eng.2021.04.023","article-title":"Intelligent manufacturing for the process industry driven by industrial artificial intelligence","volume":"7","author":"Yang","year":"2021","journal-title":"Engineering"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Fabiocchi, D., Giulietti, N., Carnevale, M., and Giberti, H. (2024). AI-driven virtual sensors for real-time dynamic analysis of mechanisms: A feasibility study. Machines, 12.","DOI":"10.3390\/machines12040257"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Haque, M.E., Zabin, M., and Uddin, J. (2025). EnsembleXAI-Motor: A lightweight framework for fault classification in electric vehicle drive motors using feature selection, ensemble learning, and explainable AI. Machines, 13.","DOI":"10.3390\/machines13040314"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Al-refai, G., Karasneh, D., Elmoaqet, H., Ryalat, M., and Almtireen, N. (2025). Surface classification from robot internal measurement unit time-series data using cascaded and parallel deep learning fusion models. Machines, 13.","DOI":"10.3390\/machines13030251"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Bougoffa, M., Benmoussa, S., Djeziri, M., and Palais, O. (2025). Hybrid deep learning for fault diagnosis in photovoltaic systems. Machines, 13.","DOI":"10.3390\/machines13050378"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Silaa, M.Y., Barambones, O., Bencherif, A., and Rougab, I. (2025). An adaptive control strategy with switching gain and forgetting factor for a robotic arm manipulator. Machines, 13.","DOI":"10.3390\/machines13050424"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Lisauskas, B., and Maskeliunas, R. (2025). Efficient transformer-based road scene segmentation approach with attention-guided decoding for memory-constrained systems. Machines, 13.","DOI":"10.3390\/machines13060466"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Osan, A.R., and Dren\u0163a, R.F. (2025). Application of artificial neural networks in predicting surface quality and machining time. Machines, 13.","DOI":"10.3390\/machines13070561"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ochoa, P., Peraza, C., Melin, P., Castillo, O., and Geem, Z.W. (2025). Type-3 fuzzy dynamic adaptation of the crossover parameter in differential evolution for the optimal design of type-3 fuzzy controllers for the inverted pendulum. Machines, 13.","DOI":"10.3390\/machines13060450"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"5","DOI":"10.14313\/PAR_235\/5","article-title":"Modern industrial robotics","volume":"24","author":"Olszewski","year":"2020","journal-title":"Pomiary Autom. Robot."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1109\/LRA.2022.3226366","article-title":"Human-multirobot collaborative mobile manipulation: The omnid mocobots","volume":"8","author":"Elwin","year":"2022","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Liang, H., Zheng, H., and Lu, Y. (September, January 28). Context-aware cognitive assistive assembly system based on online human action recognition. Proceedings of the 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE), Bari, Italy.","DOI":"10.1109\/CASE59546.2024.10711415"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3575","DOI":"10.1109\/TASE.2021.3126385","article-title":"Distributed competition of multi-robot coordination under variable and switching topologies","volume":"19","author":"Jin","year":"2021","journal-title":"IEEE Trans. Autom. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1109\/MNET.2024.3483829","article-title":"Wireless multi-robot collaboration: Communications, perception, control and planning","volume":"39","author":"Hu","year":"2024","journal-title":"IEEE Netw."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1007\/s41693-020-00035-8","article-title":"Augmented bricklaying: Human\u2013machine interaction for in situ assembly of complex brickwork using object-aware augmented reality","volume":"4","author":"Mitterberger","year":"2020","journal-title":"Constr. Robot."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Jokinen, K., Homma, K., Matsumoto, Y., and Fukuda, K. (2021, January 8\u201311). Integration and interaction of trustworthy ai in a virtual coach\u2013an overview of EU-Japan collaboration on eldercare. Proceedings of the Annual Conference of the Japanese Society for Artificial Intelligence, Online.","DOI":"10.1007\/978-3-030-96451-1_17"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Subramanian, K., Thomas, L., Sahin, M., and Sahin, F. (2024). Supporting human\u2013robot interaction in manufacturing with augmented reality and effective human\u2013computer interaction: A review and framework. Machines, 12.","DOI":"10.3390\/machines12100706"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Pham, H.V., Do, H.Q., Nguyen Quang, M., Asadi, F., and Moore, P. (2024). Proposed multi-ST model for collaborating multiple robots in dynamic environments. Machines, 12.","DOI":"10.3390\/machines12110797"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Voutsakelis, G., Dimkaros, I., Tzimos, N., Kokkonis, G., and Kontogiannis, S. (2025). Development and evaluation of a tool for blind users utilizing AI object detection and haptic feedback. Machines, 13.","DOI":"10.3390\/machines13050398"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Pan, J., Cheng, Y., Hu, C., Jiang, M., Ma, Y., Meng, F., and Shi, Q. (2025). The innovative design and performance testing of a mobile robot for the automated installation of spacers on six-split transmission lines. Machines, 13.","DOI":"10.3390\/machines13050432"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Florescu, A. (2024). Digital twin for flexible manufacturing systems and optimization through simulation: A case study. Machines, 12.","DOI":"10.3390\/machines12110785"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Tissot-Daguette, L., Vallat, C., Nijenhuis, M., Cosandier, F., and Henein, S. (2025). Near-zero parasitic shift rectilinear flexure stages based on coupled n-RRR planar parallel mechanisms. Machines, 13.","DOI":"10.3390\/machines13060530"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Foiani, F., Morettini, G., Palmieri, M., Carletta, S., Cianetti, F., and Dionigi, M. (2025). Multibody simulation of 1U CubeSat passive attitude stabilisation using a robotic arm. Machines, 13.","DOI":"10.3390\/machines13060509"},{"key":"ref_40","first-page":"10","article-title":"Design of robust manufacturing systems: A systemic approach","volume":"6","author":"Simmons","year":"2025","journal-title":"Am. J. Ind. Prod. Eng."},{"key":"ref_41","first-page":"100577","article-title":"Developing cyber-physical system and digital twin for smart manufacturing: Methodology and case study of continuous clarification","volume":"38","author":"Banerjee","year":"2024","journal-title":"J. Ind. Inf. Integr."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.jmapro.2025.04.006","article-title":"Autonomous learning of digital twins for intelligent extrusion optimisation in MEX","volume":"143","author":"Rossi","year":"2025","journal-title":"J. Manuf. Process."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1016\/j.jmsy.2020.05.001","article-title":"Semantic communications between distributed cyber-physical systems towards collaborative automation for smart manufacturing","volume":"55","author":"Lu","year":"2020","journal-title":"J. Manuf. Syst."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Musaeva, K., Vyachina, I., and Aliyeva, M. (2024, January 21\u201322). Smart factories and their impact on modern manufacturing enterprises: Prospects and challenges in the era of the digital economy. Proceedings of the E3S Web of Conferences, Les Mureaux, France.","DOI":"10.1051\/e3sconf\/202453707010"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Jia, L., and Pei, Y. (2025). Recent advances in multi-agent reinforcement learning for intelligent automation and control of water environment systems. Machines, 13.","DOI":"10.3390\/machines13060503"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Tzimas, E., Papazetis, G., Benardos, P., and Vosniakos, G.-C. (2024). Design and development of a flexible manufacturing cell controller using an open-source communication protocol for interoperability. Machines, 12.","DOI":"10.3390\/machines12080519"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Curralo, P.M.P., Campilho, R.D.S.G., Pereira, J.A.P., and Silva, F.J.G. (2024). Design of connector assembly equipment for the automotive industry. Machines, 12.","DOI":"10.3390\/machines12100731"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Rashed, A., Abdulazeem, Y., Farrag, T.A., Bamaqa, A., Almaliki, M., Badawy, M., and Elhosseini, M.A. (2025). Toward inclusive smart cities: Sound-based vehicle diagnostics, emergency signal recognition, and beyond. Machines, 13.","DOI":"10.3390\/machines13040258"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Paduraru, C., Cernat, M., and Staicu, A.-N. (2025). A unified framework for automated testing of robotic process automation workflows using symbolic and concolic analysis. Machines, 13.","DOI":"10.3390\/machines13060504"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Puri, D., Vita, L., Gattamelata, D., and Tulliani, V. (2025). Roll\/tip-over risk analysis of agricultural self-propelled machines using airborne LiDAR data: GIS-based approach. Machines, 13.","DOI":"10.3390\/machines13050377"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Klein Fiorentin, F., Dantas, R., Wolfs Gil, J., Piga Carboni, A., Fiorentin, T.A., and de Jesus, A.M.P. (2025). On the specimen design, physical properties and geometry effect on heat generation and thermal gradient in ultrasonic fatigue. Machines, 13.","DOI":"10.3390\/machines13050380"},{"key":"ref_52","unstructured":"Berezin, L., Oliinyk, O., and Rubanka, M. (2021). Innovative trends in industrial machinery engineering and education. Actual Probl. Mod. Sci."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Luo, Y., Wu, K., Spielberg, A., Foshey, M., Rus, D., Palacios, T., and Matusik, W. (May, January 30). Digital fabrication of pneumatic actuators with integrated sensing by machine knitting. Proceedings of the Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, New Orleans, LA, USA.","DOI":"10.1145\/3491102.3517577"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"182","DOI":"10.26855\/ea.2022.12.007","article-title":"Application of intelligent control in mechatronics system","volume":"3","author":"Chen","year":"2023","journal-title":"Eng. Adv."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Oomen, T., and Steinbuch, M. (2020). Model-based control for high-tech mechatronic systems. Proceedings of the Mechatronics and Robotics, CRC Press.","DOI":"10.1201\/9780429347474-4"},{"key":"ref_56","first-page":"219","article-title":"Towards condition monitoring: Fabrication and finite element analysis of a helical gear transmission rig for fault simulation","volume":"18","author":"Hammood","year":"2024","journal-title":"Jordan J. Mech. Ind. Eng."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Zhang, M., Zhang, Z., Xiong, J., and Chen, X. (2024). Accuracy analysis of complex transmission system with distributed tooth profile errors. Machines, 12.","DOI":"10.3390\/machines12070459"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Yang, B., Duan, M., Gu, R., Liang, S., and Chen, Y. (2024). Design and experimental research of a non-destructive detection device for high-precision cylindrical roller dynamic unbalance. Machines, 12.","DOI":"10.3390\/machines12100684"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Ahmed, S., Ali, Q., Sirewal, G.J., Kumar, K., and Choi, G. (2025). Hybrid brushless wound-rotor synchronous machine with dual-mode operation for washing machine applications. Machines, 13.","DOI":"10.3390\/machines13050342"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Vlachou, V.I., and Karakatsanis, T.S. (2025). Development of a fault-tolerant permanent magnet synchronous motor using a machine-learning algorithm for a predictive maintenance elevator. Machines, 13.","DOI":"10.3390\/machines13050427"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Kim, T.-S., Yang, J.-W., Shin, K.-H., Jang, G.-H., Han, C., and Choi, J.-Y. (2025). Analysis of electromagnetic characteristics of outer rotor type BLDC motor based on analytical method and optimal design using NSGA-II. Machines, 13.","DOI":"10.3390\/machines13060440"},{"key":"ref_62","first-page":"145","article-title":"Prospects for the development of process equipment in aggregate-modular design for sustainable mechanical engineering","volume":"13","author":"Yakovenko","year":"2023","journal-title":"Int. J. Mechatron. Appl. Mech."},{"key":"ref_63","unstructured":"Goodfellow, H.D., and Wang, Y. (2021). Industrial Ventilation Design Guidebook: Volume 2: Engineering Design and Applications, Academic press."},{"key":"ref_64","first-page":"e00416","article-title":"Energy consumption and ecological analysis of sustainable and conventional cutting fluid strategies in machining 15\u20135 PHSS","volume":"32","author":"Khanna","year":"2022","journal-title":"Sustain. Mater. Technol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1016\/j.jmapro.2021.02.011","article-title":"Performance of ionic liquid as a lubricant in turning inconel 825 via minimum quantity lubrication method","volume":"64","author":"Babu","year":"2021","journal-title":"J. Manuf. Process."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"134439","DOI":"10.1016\/j.jclepro.2022.134439","article-title":"More than recycling\u2013The potential of the circular economy shown by a case study of the metal working industry","volume":"377","author":"Hagedorn","year":"2022","journal-title":"J. Clean. Prod."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Kokkinis, A., Frantzis, T., Skordis, K., Nikolakopoulos, G., and Koustoumpardis, P. (2024). Review of automated operations in drilling and mining. Machines, 12.","DOI":"10.3390\/machines12120845"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Buldum, B.B., Leksycki, K., and Cagan, S.C. (2025). Comparative analysis of dry, minimum quantity lubrication, and nano-reinforced minimum quantity lubrication environments on the machining performance of AZ91D magnesium alloy. Machines, 13.","DOI":"10.3390\/machines13050430"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Maurya, S.K., Campatelli, G., Veracini, M., Arcioni, M., and Clori, D. (2025). Balancing productivity and sustainability in EDM: A comprehensive analysis of energy consumption and electrode degradation. Machines, 13.","DOI":"10.20944\/preprints202505.0231.v1"},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Ram\u00edrez-Jim\u00e9nez, D.F., and Torres Valencia, C.A. (2025). Experimental design and simulation of a fly-cutting plant for academic environment practices. Machines, 13.","DOI":"10.3390\/machines13010015"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Raman, V.V., Badarinath, R., and Prabhu, V.V. (2025). TOPSIS-based methodology for selecting fused filament fabrication machines. Machines, 13.","DOI":"10.3390\/machines13070574"}],"container-title":["Machines"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-1702\/13\/8\/683\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:22:09Z","timestamp":1760034129000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-1702\/13\/8\/683"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,3]]},"references-count":71,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2025,8]]}},"alternative-id":["machines13080683"],"URL":"https:\/\/doi.org\/10.3390\/machines13080683","relation":{},"ISSN":["2075-1702"],"issn-type":[{"type":"electronic","value":"2075-1702"}],"subject":[],"published":{"date-parts":[[2025,8,3]]}}}