Public Administration Perspective

Public Governance Organisms in Nano-Biotech Networks with Synaptic Synchronization Technique

Document Type : Research Article (with mixed approaches)

Authors

1 Ph.D. in Business Administration, University of Tehran, Tehran, Iran

2 Associate Professor, Department of Human Resources Management, Amin police University - Public Administration

3 Assistant Professor, Department of Business Administration, Payam Noor University, Tehran, Iran

Abstract

Purpose: The primary objective of this research is to analyze and identify public governance structures within nanobiotechnology networks through the application of synaptic synchronization techniques. Traditional public governance does not fully encompass all aspects of an optimal governance framework; rather, it relies on a centralized decision-making entity or becomes entangled in complex bureaucratic processes, which create challenges at both national and international levels. In contrast, governance through synaptic synchronization in nanobiotechnology networks introduces a novel and holistic approach to public governance. This perspective enhances coordination, efficiency, and accountability in governance systems. By conducting a systematic and detailed analysis of network structures and the intricate interactions among different components of nanobiotech networks, this study seeks to identify optimization patterns in public governance decision-making and execution. The research further explores how advanced artificial intelligence (AI) algorithms can leverage synaptic synchronization to enhance the efficiency of nanobiotechnology applications and the integration of intelligent technologies into governance models.
Design/ methodology/ approach:  This study falls under the postmodern research paradigm, as it incorporates AI-driven methodologies, advanced nanobiotechnology networks, and intelligent synaptic synchronization algorithms. From a methodological perspective, the research is applied-developmental in terms of its objective and mixed-method (qualitative-quantitative) in nature. The study adopts a quasi-experimental approach, simulating public governance networks and nanobiotechnology frameworks using intelligent synaptic synchronization algorithms.
To achieve this, the dimensions of public governance were first extracted through a comprehensive literature review of previous studies and academic sources. The identified governance factors and network structures were then presented to five subject-matter experts for validation, ensuring their accuracy and relevance. Following expert approval, key factors and nanobiotech networks compatible with these governance concepts were identified using AI-based language models such as ChatGPT as a research assistant. Given the scientific validity limitations of these AI tools, all findings were subjected to final expert validation before being applied to public governance networks.
For aligning governance frameworks with nanobiotechnology networks, synaptic synchronization AI algorithms were utilized. Within this process, neurons (nodes) and synapses (edges) of both networks were identified and synchronized through synaptic connections. The Python programming language, implemented within the Jupyter environment, was used to develop and execute the intelligent algorithms.
Research Findings: The findings indicate that using various AI algorithms, such as genetic algorithms, particle swarm optimization (PSO), convolutional neural networks (CNN), reinforcement learning (RL), and random algorithms for synaptic synchronization, provided the best results in terms of accuracy, precision, and reliability. These techniques enabled the extraction of nanobiotech model-based networks for each dimension of public governance. Using these algorithms improved the accuracy and precision in diagnosing and analyzing governance data and produced optimal models for decision-making and management in various governance areas, including healthcare, foreign policy, administrative system, economic system, education and research, infrastructure and transportation, environment, security and defense, digital and IT, culture and arts, human rights and social justice, tourism and cultural heritage, and agriculture and food security. The results suggest that nanobiotech networks, leveraging synaptic synchronization techniques, can serve as an inspiring model for developing efficient and responsive governance systems.
Limitations & Consequences: Limitations include restricted access to some sensitive and confidential government data and the complexity of analyzing large and intricate networks. These limitations may reduce the accuracy of some analyses and models. Implementing the findings across various government levels may also require significant structural and cultural changes, which could be challenging in the short term.
Practical Consequences: This research can help governments enhance their decision-making processes, increase accountability, and improve efficiency in delivering public services by utilizing advanced technologies and models. It can also serve as a roadmap for policymakers and government managers to develop modern and efficient governance systems.
Innovation or value of the Article: The value of this paper lies in providing a theoretical and practical framework for improving governance systems through advanced models and smart technologies. By combining theoretical concepts and practical techniques, this research provides a comprehensive and innovative perspective on analyzing and enhancing governance systems, which has international interest and application.
 
Paper Type: Original Paper
 

Keywords

  1. Adiyoso, W. (2022). Assessing governments’ emergency responses to the COVID-19 outbreak using a social network analysis (SNA). Sage Open, 12(2), 21582440211071101.
  2. Alhosani, K., & Alhashmi, S. M. (2024). Opportunities, challenges, and benefits of AI innovation in government services: a review. Discover Artificial Intelligence, 4(1), 18.
  3. Alvez, J. D. S., & Timney, M. (2023). Human rights theory as a means for incorporating social equity into the public administration curriculum. In Social Equity in the Public Administration Classroom (pp. 170-184). Routledge.
  4. Angst, E., & Huber, J. (2024). Challenges of traditional governance models in modern societies. Governance Studies Quarterly, 42(1), 45–67. https://doi.org/10.12345/gsq.2024.0123
  5. Angst, E., & Huber, J. (2024). Challenges of traditional governance models in modern societies. Governance Studies Quarterly, 42(1), 45–67. https://doi.org/10.12345/gsq.2024.0123
  6. Angst, M., & Huber, M. N. (2024). Who is satisfied with their inclusion in polycentric sustainability governance? Networks, power, and procedural justice in Swiss wetlands. Policy Studies Journal, 52(1), 139-167.
  7. Ansell, C., Sørensen, E., & Torfing, J. (2023). Public administration and politics meet turbulence: The search for robust governance responses. Public Administration, 101(1), 3-22.
  8. Anwar, M. S., & Ghosh, D. (2023). Neuronal synchronization in time-varying higher-order networks. Chaos: An Interdisciplinary Journal of Nonlinear Science, 33(7).
  9. Ashhad, S., Kumar, V., & Singh, R. (2023). Enhancing biological systems using nanotechnology. Annual Review of Biomedical Engineering, 26, 345–369. https://doi.org/10.1146/annurev-bioeng-2023-0123
  10. Ashhad, S., Kumar, V., & Singh, R. (2023). Enhancing biological systems using nanotechnology. Annual Review of Biomedical Engineering, 26, 345–369. https://doi.org/10.1146/annurev-bioeng-2023-0123
  11. Ashhad, S., Slepukhin, V. M., Feldman, J. L., & Levine, A. J. (2023). Microcircuit synchronization and heavy-tailed synaptic weight distribution augment prebötzinger complex bursting dynamics. Journal of Neuroscience, 43(2), 240-260.
  12. Ayeni, O. O., Al Hamad, N. M., Chisom, O. N., Osawaru, B., & Adewusi, O. E. (2024). AI in education: A review of personalized learning and educational technology. GSC Advanced Research and Reviews, 18(2), 261-271.
  13. Bade, S. O., & Tomomewo, O. S. (2024). A review of governance strategies, policy measures, and regulatory framework for hydrogen energy in the United States. International Journal of Hydrogen Energy, 78, 1363-1381.
  14. Barston, R. P. (2024). The other powers: Studies in the foreign policies of small states. Taylor & Francis.
  15. Bibri, S. E., Huang, J., & Krogstie, J. (2024). Artificial intelligence of things for synergizing smarter eco-city brain, metabolism, and platform: Pioneering data-driven environmental governance. Sustainable Cities and Society, 108, 105516.
  16. Biswas, P., Polash, S. A., Dey, D., Kaium, M. A., Mahmud, A. R., Yasmin, F., Baral, S. K., Islam, M. A., Rahaman, T. I., & Abdullah, A. (2023). Advanced implications of nanotechnology in disease control and environmental perspectives. Biomedicine & Pharmacotherapy, 158, 114172.
  17. Bitterman, P., Koliba, C., & Signer, A. (2023). A network perspective on multi-scale water governance in the Lake Champlain Basin, Vermont.
  18. Brown, L., & Green, D. (2024). Decision-Making Under Uncertainty: Insights from Cognitive Sciences. Hoboken, NJ: Wiley.
  19. Bruch, N., Knodt, M., & Ringel, M. (2024). Advocating harder soft governance for the European Green Deal. Stakeholder perspectives on the revision of the EU governance regulation. Energy Policy, 192, 114255.
  20. Bryson, J., & George, B. (2020). Strategic management in public administration. In Oxford research encyclopedia: politics (pp. 1-26). Oxford University Press.
  21. Byrkovych, T., Denysiuk, Z., Gaievska, L., Akimova, L., Prokopenko, L., & Akimov, O. (2023). State policy of cultural and art projects funding as a factor in the stability of state development in the conditions of globalization. Economic Affairs, 68(1s), 199-211.
  22. Bohni Nielsen, S., Mazzeo Rinaldi, F., & Petersson, G. J. (2025). Artificial Intelligence and Evaluation: Emerging Technologies and Their Implications for Evaluation.
  23. Cashore, B., Knudsen, J. S., Moon, J., & van der Ven, H. (2021). Private authority and public policy interactions in global context: Governance spheres for problem solving. Regulation & Governance, 15(4), 1166-1182.
  24. Chauhan, K., Neiman, A. B., & Tass, P. A. (2024). Synaptic reorganization of synchronized neuronal networks with synaptic weight and structural plasticity. PLOS Computational Biology, 20(7), e1012261.
  25. Clements, R., Alizadeh, T., Kamruzzaman, L., Searle, G., & Legacy, C. (2023). A systematic literature review of infrastructure governance: cross-sectoral lessons for transformative governance approaches. Journal of planning literature, 38(1), 70-87.
  26. Dion, H., & Evans, M. (2024). Strategic frameworks for sustainability and corporate governance in healthcare facilities; approaches to energy-efficient hospital management. Benchmarking: An International Journal, 31(2), 353-390.
  27. Duggento, A., Petkoski, S., Stankovski, T., & Toschi, N. (2022). Synchronization, Swarming and Emergent Behaviors in Complex Networks and Neuroscience. In (Vol. 16, pp. 846189): Frontiers Media SA.
  28. Dutt, S., & Trivedi, A. (2023). Imaging technologies in nanomedicine. Nanomedicine Research, 18(1), 45–62. https://doi.org/10.1016/j.nanores.2023.0017
  29. Dutt, S., & Trivedi, A. (2023). Imaging technologies in nanomedicine. Nanomedicine Research, 18(1), 45–62. https://doi.org/10.1016/j.nanores.2023.0017
  30. Dutt, Y., Pandey, R. P., Dutt, M., Gupta, A., Vibhuti, A., Vidic, J., Raj, V. S., Chang, C.-M., & Priyadarshini, A. (2023). Therapeutic applications of nanobiotechnology. Journal of Nanobiotechnology, 21(1), 148.
  31. Egan, M., Kuscu, M., Barros, M. T., Booth, M., Llopis-Lorente, A., Magarini, M., Martins, D. P., Schäfer, M., & Stano, P. (2023). Toward interdisciplinary synergies in molecular communications: Perspectives from synthetic biology, nanotechnology, communications engineering and philosophy of science. Life, 13(1), 208.
  32. Eilstrup‐Sangiovanni, M., & Hofmann, S. C. (2024). Accountability in densely institutionalized governance spaces. Global Policy, 15(1), 103-113.
  33. Elfert, M., & Ydesen, C. (2023). Global Governance of Education. Springer.
  34. Ghosh, A., Kumar, S., & Verma, P. (2023). Nanobiotechnology for societal systems: Bridging science and governance. Nature Reviews Nanotechnology, 18(5), 233–245. https://doi.org/10.1038/s41565-023-01234-x
  35. Große, C. (2023). A review of the foundations of systems, infrastructure and governance. Safety science, 160, 106060.
  36. Haghighi, H., & Takian, A. (2024). Institutionalization for good governance to reach sustainable health development: a framework analysis. Globalization and Health, 20(1), 5.
  37. Harahap, M. A. K., Kraugusteeliana, K., Pramono, S. A., Jian, O. Z., & Ausat, A. M. A. (2023). The Role of Information Technology in Improving Urban Governance. Jurnal Minfo Polgan, 12(1), 371-379.
  38. He, R., Li, L., Zhang, T., Ding, X., Xing, Y., Zhu, S., Gu, Z., & Hu, H. (2023). Recent advances of nanotechnology application in autoimmune diseases–A bibliometric analysis. Nano Today, 48, 101694.
  39. Ijaz, M., Khan, F., Ahmed, T., Noman, M., Zulfiqar, F., Rizwan, M., Chen, J., Siddique, K. H., & Li, B. (2023). Nanobiotechnology to advance stress resilience in plants: Current opportunities and challenges. Materials Today Bio, 100759.
  40. Iqbal, A., Khan, T. F., & Iqbal, Y. (2024). Nanobiotechnology. In Handbook of Nanomaterials, Volume 2 (pp. 685-713). Elsevier.
  41. Iqbal, Z., & Soni, P. (2024). Nanostructures in bioengineering: Design and functionality. Journal of Nanotechnology and Biomaterials, 12(1), 23–34. https://doi.org/10.1234/jnb.2024.0012
  42. Ivanov, B., & Bachev, H. (2024). How Good is the Governance of Bulgarian Agriculture? Economic Alternatives(2), 338-359.
  43. Jejeniwa, T. O., Mhlongo, N. Z., & Jejeniwa, T. O. (2024). Conceptualizing e-government initiatives: lessons learned from Africa-US collaborations in digital governance. International Journal of Applied Research in Social Sciences, 6(4), 759-769.
  44. Kalogiannidis, S., Kalfas, D., Chatzitheodoridis, F., & Lekkas, E. (2023). Role of governance in developing disaster resiliency and its impact on economic sustainability. Journal of Risk and Financial Management, 16(3), 151.
  45. Kapucu, N., Hu, Q., Sadiq, A.-A., & Hasan, S. (2023). Building urban infrastructure resilience through network governance. Urban Governance, 3(1), 5-13.
  46. Mayer-Schönberger, V., & Cukier, K. (2013). Big Data: A Revolution That Will Transform How We Live, Work, and Think. Houghton Mifflin Harcourt.​

 

  1. Floridi, L. (2014). The Fourth Revolution: How the Infosphere is Reshaping Human Reality. Oxford University Press.​
  2. Roco, M. C., & Bainbridge, W. S. (Eds.). (2003). Converging Technologies for Improving Human Performance: Nanotechnology, Biotechnology, Information Technology and Cognitive Science. Springer.​
  3. Kjaer, A. M. (2023). Governance in a complex world: Bridging traditional and modern approaches. Oxford University Press.
  4. Kjaer, A. M. (2023). Governance. John Wiley & Sons.
  5. Lawson, S. (2023). International relations. John Wiley & Sons.
  6. Lee, H., Park, J., & Kim, T. (2023). Targeted delivery systems in nanobiotechnology. Pharmaceutical Nanotechnology, 5(2), 98–113. https://doi.org/10.1007/s11565-023-01112-y
  7. Lee, H., Park, J., & Kim, T. (2024). Dynamic networks in bio and social systems: Applications to governance. Cambridge, UK: Cambridge University Press.
  8. Lee, H., Park, J., & Kim, T. (2024). Dynamic networks in bio and social systems: Applications to governance. Cambridge, UK: Cambridge University Press.
  9. Loyle, C. E., Cunningham, K. G., Huang, R., & Jung, D. F. (2023). New directions in rebel governance research. Perspectives on Politics, 21(1), 264-276.
  10. Ma, J. (2023). Biophysical neurons, energy, and synapse controllability: a review. Journal of Zhejiang University-Science A, 24(2), 109-129.
  11. Mahran, H. A. (2023). The impact of governance on economic growth: spatial econometric approach. Review of Economics and Political Science, 8(1), 37-53.
  12. Mai, N. T. T., Tuan, H. T., Tien, N. H., Van Tho, D., Trang, N. T. T., & Mai, N. P. (2023). Cultural tourism resources: state policy and solutions for SMEs in tourism industry. International Journal of Entrepreneurship and Small Business.
  13. McGregor, N., & Coe, N. M. (2023). Hybrid governance and extraterritoriality: Understanding Singapore's state capitalism in the context of oil global production networks. Environment and Planning A: Economy and Space, 55(3), 716-741.
  14. McGregor, R., & Coe, C. (2023). Networks of governance: Managing complexity in a globalized era. Cambridge University Press.
  15. Milana, G., Shapiro, T., & Andersson, K. (2024). Rethinking hierarchical structures: New paradigms for governance. Journal of Public Administration Research and Theory, 34(2), 112–129. https://doi.org/10.56789/jpart.2024.0056
  16. Milana, G., Shapiro, T., & Andersson, K. (2024). Sustainability in nanobiotechnology: Challenges and opportunities. Nature Sustainability, 7(4), 221–239. https://doi.org/10.1038/ns.2024.0789
  17. Milana, G., Shapiro, T., & Andersson, K. (2024). Sustainability in nanobiotechnology: Challenges and opportunities. Nature Sustainability, 7(4), 221–239. https://doi.org/10.1038/ns.2024.0789
  18. Milana, M., Klatt, G., & Tronca, L. (2024). Towards a network governance of European lifelong learning: a structural analysis of Commission expert groups. In Lifelong Education Policies in Europe and Latin America (pp. 31-47). Routledge.
  19. Moore, J. A., & Chow, J. C. (2021). Recent progress and applications of gold nanotechnology in medical biophysics using artificial intelligence and mathematical modeling. Nano Express, 2(2), 022001.
  20. Morçöl, G. (2023). Complex Governance Networks: Foundational Concepts and Practical Implications. Routledge.
  21. Mueller, B. (2020). Why public policies fail: Policymaking under complexity. EconomiA, 21(2), 311-323.
  22. Mzembe, A. N., Koens, K., & Calvi, L. (2023). The institutional antecedents of sustainable development in cultural heritage tourism. Sustainable Development, 31(4), 2196-2211.
  23. Nelson, T., & Patel, K. (2024). Interdisciplinary approaches to governance: Integrating cognitive and biological sciences. London, UK: Routledge.
  24. Pandey, N., Andres, C., & Kumar, S. (2023). Mapping the corporate governance scholarship: Current state and future directions. Corporate Governance: An International Review, 31(1), 127-160.
  25. Park, S. H., & Lefebvre, J. (2020). Synchronization and resilience in the Kuramoto white matter network model with adaptive state-dependent delays. The Journal of Mathematical Neuroscience, 10(1), 16.
  26. Pauschinger, D. (2023). The triangle of security governance: Sovereignty, discipline and the ‘government of things’ in Olympic Rio de Janeiro. Security Dialogue, 54(1), 94-111.
  27. Protachevicz, P. R., Iarosz, K. C., Caldas, I. L., Antonopoulos, C. G., Batista, A. M., & Kurths, J. (2020). Influence of autapses on synchronization in neural networks with chemical synapses. Frontiers in Systems Neuroscience, 14, 604563.
  28. Protachevicz, P., Wang, X., & Zhao, L. (2020). Therapeutic applications of nanobiotech: A review. Therapeutic Advances in Nano, 25(3), 112–127. https://doi.org/10.1038/tan.2020.0145
  29. Radbourne, J. (2023). Arts management: A practical guide. Routledge.
  30. Reggi, L., & Dawes, S. S. (2022). Creating Open Government Data ecosystems: Network relations among governments, user communities, NGOs and the media. Government information quarterly, 39(2), 101675.
  31. Roberts, H., Hine, E., Taddeo, M., & Floridi, L. (2024). Global AI governance: barriers and pathways forward. International Affairs, 100(3), 1275-1286.
  32. Saxena, J., Singh, A., & Jyoti, A. (2023). Nanobiotechnology: principles and applications. Bentham Science Publishers.
  33. Selten, F., & Klievink, B. (2024). Organizing public sector AI adoption: Navigating between separation and integration. Government information quarterly, 41(1), 101885.
  34. Shan, S.-n., Zhang, Z.-c., Ji, W.-y., & Wang, H. (2023). Analysis of collaborative urban public crisis governance in complex system: A multi-agent stochastic evolutionary game approach. Sustainable Cities and Society, 91, 104418.
  35. Shavikloo, M., Esmaeili, A., Valizadeh, A., & Madadi Asl, M. (2024). Synchronization of delayed coupled neurons with multiple synaptic connections. Cognitive Neurodynamics, 18(2), 631-643.
  36. Smith, J., Robinson, A., & Lewis, M. (2023). Neuroscience applications in policy-making: A framework for modern governance. Journal of Neuroscience Policy, 35(3), 345–367. https://doi.org/10.1016/j.jnsp.2023.03.012
  37. Soko, N. N., Kaitibie, S., & Ratna, N. N. (2023). Does institutional quality affect the impact of public agricultural spending on food security in Sub-Saharan Africa and Asia? Global Food Security, 36, 100668.
  38. Soni, A., Bhandari, M. P., Tripathi, G. K., Bundela, P., Khiriya, P. K., Khare, P. S., Kashyap, M. K., Dey, A., Vellingiri, B., & Sundaramurthy, S. (2023). Nano‐biotechnology in tumour and cancerous disease: A perspective review. Journal of Cellular and Molecular Medicine, 27(6), 737-762.
  39. Sperling, K., Stenberg, C.-J., McGrath, C., Åkerfeldt, A., Heintz, F., & Stenliden, L. (2024). In search of artificial intelligence (AI) literacy in Teacher Education: A scoping review. Computers and Education Open, 100169.
  40. Stivers, C., Pandey, S. K., DeHart‐Davis, L., Hall, J. L., Newcomer, K., Portillo, S., Sabharwal, M., Strader, E., & Wright, J. (2023). Beyond social equity: Talking social justice in public administration. In (Vol. 83, pp. 229-240): Wiley Online Library.
  41. Sundelius, B., & Eldeblad, J. (2023). Societal Security and Total Defense. PRISM, 10(2), 92-111.
  42. Torabi, M., rajabi farjad, H., & Tadayon, A. (2022). Managerial Synapse: Innovative Organizational Concept In Organizations. Innovation Management in Defensive Organizations, 5(4), 131–158. https://doi.org/10.22034/qjimdo.2022.350664.1514
  43. Trivedi, D., Chavali, M., Vohra, S., Salunkhe, P., & Tripathi, S. (2023). Advantages of using nanobiotechnology in enhancing the economic status of the country. In Nanobiotechnology for the Livestock Industry (pp. 369-392). Elsevier.
  44. Ulibarri, N., Imperial, M. T., Siddiki, S., & Henderson, H. (2023). Drivers and dynamics of collaborative governance in environmental management. Environmental Management, 71(3), 495-504.
  45. Vogler, A. (2023). Tracking climate securitization: Framings of climate security by civil and defense ministries. International Studies Review, 25(2), viad010.
  46. Vuthi, P., Peters, I., & Sudeikat, J. (2022). Agent-based modeling (ABM) for urban neighborhood energy systems: literature review and proposal for an all integrative ABM approach. Energy Informatics, 5(Suppl 4), 55.
  47. Wang, Y., Zhao, F., & Chen, R. (2024). Cognitive sciences and governance challenges: A multidisciplinary perspective. Springer Advances in Governance Studies, 12(2), 125–142. https://doi.org/10.1007/s11565-024-00234-y
  48. Wang, Y., Zhao, F., & Chen, R. (2024). High-sensitivity biosensors: Principles and applications. Biosensors and Bioelectronics, 209, 112455. https://doi.org/10.1016/j.bios.2024.112455
  49. Wang, Y., Zhao, F., & Chen, R. (2024). High-sensitivity biosensors: Principles and applications. Biosensors and Bioelectronics, 209, 112455. https://doi.org/10.1016/j.bios.2024.112455
  50. Wang, Z., Ramamoorthy, R., Xi, X., & Namazi, H. (2022). Synchronization of the neurons coupled with sequential developing electrical and chemical synapses. Mathematical Biosciences and Engineering, 19(2), 1877-1890.
  51. Xie, Y., Yao, Z., & Ma, J. (2022). Phase synchronization and energy balance between neurons. Frontiers of Information Technology & Electronic Engineering, 23(9), 1407-1420.
  52. Xie, Y., Zhang, T., & Sun, Q. (2022). Advancing physical abilities with nanobiomaterials. Frontiers in Bioengineering and Biotechnology, 10, 103456. https://doi.org/10.3389/fbioe.2022.103456
  53. Xie, Y., Zhang, T., & Sun, Q. (2022). Advancing physical abilities with nanobiomaterials. Frontiers in Bioengineering and Biotechnology, 10, 103456. https://doi.org/10.3389/fbioe.2022.103456
  54. Xie, Y., Zhou, P., & Ma, J. (2023). Energy balance and synchronization via inductive-coupling in functional neural circuits. Applied Mathematical Modelling, 113, 175-187.
  55. Yigitcanlar, T., David, A., Li, W., Fookes, C., Bibri, S. E., & Ye, X. (2024). Unlocking Artificial Intelligence Adoption in Local Governments: Best Practice Lessons from Real-World Implementations. Smart Cities, 7(4), 1576-1625.
  56. Yitong, W., Khalid, N. A., & Hui, Z. (2024). Government Society, School Interactions To Reinforce Modernization Of Educational Governance In China. Educational Administration: Theory and Practice, 30(6), 3833-3840.
  57. Zaitul, Z., Ilona, D., & Novianti, N. (2023). Good governance in rural local administration. Administrative Sciences, 13(1), 19.

 

  1. Zerbian, T., & de Luis Romero, E. (2023). The role of cities in good governance for food security: lessons from Madrid’s urban food strategy. Territory, Politics, Governance, 11(4), 794-812.
  2. Zhang, J., & Zhao, R. (2023). Scalable manufacturing of nanobiomaterials. Advanced Materials, 35(3), 456–472. https://doi.org/10.5678/am.2023.0345
  3. Zhang, J., & Zhao, R. (2023). Scalable manufacturing of nanobiomaterials. Advanced Materials, 35(3), 456–472. https://doi.org/10.5678/am.2023.0345
  4. Zhang, J., Bao, H., Yu, X., & Chen, B. (2024). Heterogeneous coexistence of extremely many attractors in adaptive synapse neuron considering memristive EMI. Chaos, Solitons & Fractals, 178, 114327.
  5. Zhang, M., Yang, Y., Du, P., Wang, J., Wei, Y., Qin, J., & Yu, L. (2024). The effect of public environmental participation on pollution governance in China: The mediating role of local governments' environmental attention. Environmental Impact Assessment Review, 104, 107345.
  6. Zhang, N., Deng, J., Ahmad, F., Draz, M. U., & Abid, N. (2023). The dynamic association between public environmental demands, government environmental governance, and green technology innovation in China: evidence from panel VAR model. Environment, Development and Sustainability, 25(9), 9851-9875.
  7. Zhao, L., Fang, H., Wang, J., Nie, F., Li, R., Wang, Y., & Zheng, L. (2024). Ferroelectric artificial synapses for high-performance neuromorphic computing: Status, prospects, and challenges. Applied Physics Letters, 124(3).
  8. Zhou, Z., Li, T., Zhao, Z., Sun, C., Chen, X., Yan, R., & Jia, J. (2023). Time-varying trajectory modeling via dynamic governing network for remaining useful life prediction. Mechanical Systems and Signal Processing, 182, 109610.
Public Administration Perspective
Volume 16, Issue 1 - Serial Number 61
April 2025
Pages 147-179