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With the convergence and innovation of emerging information technologies, Digital Twin (DT) technology has become a key enabler for digital transformation and the evolution of intelligent systems. It has been widely applied and received significant attention in fields such as industrial manufacturing, smart cities, and intelligent transportation. However, existing research on traditional DT technologies has predominantly focused on the modeling and analysis of physical entities ("objects"), with limited systematic integration of "human" and "environmental" factors. The lack of exploration into human−environment interactions makes it difficult for current digital twin frameworks to meet the advanced demands of complex intelligent systems for multi−level, comprehensive interaction capabilities. In view of this, this paper innovatively introduces the "object−human−environment" interactive vision and comprehensively and systematically analyzes the research frontiers and progress of digital twin technology from the three core dimensions of intelligent physical entity (object), intelligent individual (human), and virtual−real fusion environment (environment). Firstly, the paper analyzes the traditional digital twin technology system with "object" as the core and focuses on its theoretical origin, framework, and application. Secondly, it discusses the definition, development context, national policies, and core technologies of digital people driven by AI. Finally, expand the vision to the dimension of "environment" and explore the application practice of "environment" in multiple scenes of the meta−universe, deeply discuss the deep integration and interaction mechanism of the three elements of "object", "human" and "environment", reveal how the three interact and promote each other, and provide support for the construction of the meta−universe. Furthermore, this study discusses the current research challenges and future development trends of digital twin technology from the perspective of "Object−Human−Environment" interaction and proposes three key research directions: (1) developing an intelligent, multi−layered data fusion framework; (2) exploring AIGC−enabled intelligent virtual−real mapping and native virtual evolution; and (3) constructing novel virtual economy architectures and intelligent governance systems. The research outcomes provide both theoretical foundations and practical insights for building next−generation digital twin systems characterized by multi−agent collaborative perception, multimodal intelligent interaction, and closed−loop integration of virtual and real environments.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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