
Xuewen Liu
Articles
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Dec 21, 2024 |
nature.com | Chenchen Wang |Yaobin Liu |Xuewen Liu |Haibo Xia
In the context of the global move into the digital economy (DEC) era and the accelerated development of the green industry, constructing a unified large market provides a powerful accelerating effect for the green transformation and upgrading of the manufacturing industry (GTUM) empowered by DEC. This study employs panel data combining China’s provincial level with the level of manufacturing subsectors from 2011 to 2020. It examines the impact of DEC and the construction of a unified large market on GTUM and its action mechanism at the theoretical and empirical levels by combining the traditional econometric models with geographic information systems, machine learning models, and other advanced technologies. Results indicate that DEC significantly enhances GTUM. Relative to the efficiency aspects of GTUM, the impact of DEC is more pronounced on energy consumption and environmental protection. Mechanism tests reveal that DEC primarily facilitates GTUM by reducing market segmentation effects, stimulating market potential effects, and matching market supply and demand effects. Heterogeneity analysis finds that in regions with higher levels of trade openness, technological innovation, and public environmental awareness, DEC more effectively promotes GTUM. Analyzing the temporal dynamics of this influence, the impact of DEC on GTUM aligns with Metcalfe’s Law, which posits a non-linear characteristic. Furthermore, the construction of a unified large market amplifies the effect of DEC empowering GTUM. This study offers a novel pathway for China to fully leverage DEC and the advantages of an ultra-large market to enhance the level of GTUM. It also provides valuable insights for the green development of industries globally.
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Sep 12, 2024 |
mdpi.com | Ping Yao |Xuewen Liu
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Oct 10, 2023 |
mdpi.com | Yuanlong Li |Shang Gao |Xuewen Liu |Peiliang Zuo
3.1. Selection of Supplementary Inspection Points We have noticed that the density of patrol points can greatly affect the quality of drone inspections on highways, as (1) the highway management department does not recommend drones to fly directly over highways, but rather over both sides of the road to prevent drones from falling to the ground and posing risks to the operation of highways; (2) if the drone’s patrol points are too sparse, the drone’s straight-line flight between points will...
Deep-Reinforcement-Learning-Based Wireless IoT Device Identification Using Channel State Information
Jul 12, 2023 |
mdpi.com | Yuanlong Li |Yiyang Wang |Xuewen Liu |Peiliang Zuo
Abstract:Internet of Things (IoT) technology has permeated into all aspects of today’s society and is playing an increasingly important role. Identity authentication is crucial for IoT devices to access the network, because the open wireless transmission environment of the IoT may suffer from various forms of network attacks. The asymmetry in the comprehensive capabilities of gateways and terminals in the IoT poses significant challenges to reliability and security.
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Jun 9, 2023 |
link.aps.org | Yu Xin Liu |Xuewen Liu |Bin Zhu
Abstract The early kinetic decoupling (eKD) effect is an inevitable ingredient in calculating the relic density of dark matter (DM) for various well-motivated scenarios. It appears naturally in forbidden dark matter annihilation, the main focus of this work, which contains fermionic DM and a light singlet scalar that connects the DM and standard model (SM) leptons.
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