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Xiaoying Li

As seen in: Allergy - European Journal of Allergy and Clinical Immunology, Color Research & Application, Nature, Wiley Online Library, PLOS, ScienceDirect, BMJ Open, Frontiers, MDPI, Taylor & Francis Online and
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Articles

Stakeholder Conflicts in Low-Carbon Tourism: A Process-Oriented Framework

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By Panpan Sun, Xiaoying Li, Songshan Huang
| Taylor & Francis Online
ABSTRACT Low-carbon tourism initiatives frequently generate stakeholder conflicts, even when sustainability goals are widely shared. This study examines how such conflicts arise and propagate in heritage tourism, using Quanzhou Ancient City, China, as the focal case. Findings show that government officials, tourism operators, residents, and tourists hold divergent cognitive, emotional, and behavioural orientations toward low-carbon policies.
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Phage-mediated expansion of the virulence gene types and enhanced ecological integration of pathogens in wild mice from human-impacted environments

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By Huanhuan Lu, Jiaxuan Bian, Hui Wang, Huiqun Jia, Xiaoying Li, Mingjuan Yang, Hongbin Song, Weilong Tan, Ligui Wang, Chenqionglu Feng
| Nature Verified
Abstract Wild mice are crucial in the transmission of infectious diseases; however, quantitative indicators for evaluating risk of virulence factors transmission are still lacking. We combined metagenomics and network analysis to evaluate ecological connectivity and functional gene profiles of microbial communities in wild mice from human-impacted environments (HE) and woodland environments (WE). We found that the pathogen centrality was significantly higher in HE than in WE (p < 0.001).
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Intelligent fall risk prediction and real-time warning system for elderly care based on multimodal deep learning and wearable sensor fusion

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By Xiaoying Li, Zhen Liu, Yuzhou Wu, Huiyang Zhu, Liu Liu
| Nature Verified
Abstract Falls remain a leading cause of injury-related morbidity and mortality among adults aged 65 and older, and these human and economic costs keep rising as populations age worldwide. Most existing risk assessment tools rely on periodic clinical evaluations or single-sensor wearable devices, neither of which tracks the dynamic, multifactorial nature of fall risk throughout daily life.
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