Biomechanical insights from molecular to systemic levels in comparison and transformation paths of urban renewal governance modes under the “new normal” via data mining technique
In the urban development “new normal” of China, urban renewal governance transformation resembles the complex orchestration within cellular molecular biomechanics. Just as cells and molecules interact in a hierarchical and coordinated manner, diverse stakeholders and policies in urban renewal must align. The current urban and rural planning has underplayed the essential governance models. Here, data mining is the microscope to dissect urban renewal, similar to how biologists study molecular biomechanics. Examining cases like Shenzhen’s, Guangzhou’s “three old” renovations, and Beijing’s “key villages” renovations is like observing different cellular responses. Each stakeholder and policy factor in urban renewal can be seen as molecular elements. Their interactions, like molecular forces, determine the system’s behavior. By integrating new institutionalism theory, we map a transformation path, much as understanding molecular pathways guides biological system changes. Our data mining model, like a biomechanical analysis tool, shows strong capabilities. It can handle and describe the multimodal information of urban renewal. The significant performance improvement over the baseline model parallels the enhanced understanding gained from advanced biomechanical studies. This approach offers a new perspective, using the principles of cellular molecular biomechanics to optimize urban renewal governance and drive sustainable urban development.
Authors
- Jintao Liu (ORCID: https://orcid.org/0000-0002-6710-2605)
- Xiaoqing Zhang (ORCID: https://orcid.org/0000-0002-7405-1893)
- Yeting Chen (ORCID: https://orcid.org/0000-0001-6329-6994)
- Siyuan He (ORCID: https://orcid.org/0000-0003-3308-4143)
- Lanxin Peng
Institutions
- Yunnan Normal University (CN)
Publication Details
- Journal
- Molecular & cellular biomechanics
- Published
- 2025-01-10
- DOI
- https://doi.org/10.62617/mcb511
- Primary Topic
- Genetics, Bioinformatics, and Biomedical Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00