Hui Gu

Dr. Hui Gu


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 December 2024 in Remote Sensing
Verified
Journal Article
Open access
PDF file
CLChenqin Lian
Chenqin Lian
ZFZhiming Feng
Zhiming Feng
HGHui Gu
Hui Gu
BGBeilei Gao
Beilei Gao
In the context of global warming, climate strongly affects forest fires. With long-term and strict fire prevention policies, China has become a unique test arena for comprehending the role of climatic variables in affecting forest fires. Here, using GIS spatial analysis, Pearson correlation, and geographical detector, the climate drivers of forest fires in China are revealed using the 2003–2022 active fire data from the MODIS C6 and climate products from CHELSA (Climatologies at high resolution for the Earth’s land surface areas). The main conclusions are as follows: (1) In total, 82% of forest fires were prevalent in the southern and southwestern forest regions (SR and SWR) in China, especially in winter and spring. (2) Forest fires were mainly distributed in areas with a mean annual temperature and annual precipitation of 14~22 °C (subtropical) and 800~2000 mm (humid zone), respectively. (3) Incidences of forest fires were positively correlated with temperature, potential evapotranspiration, surface downwelling shortwave flux, and near-surface wind speed but negatively correlated with precipitation and near-surface relative humidity. (4) Temperature and potential evapotranspiration dominated the roles in determining spatial variations of China’s forest fires, while the combination of climate variables complicated the spatial variation. This paper not only provides new insights on the impact of climate drives on forest fires, but also offers helpful guidance for fire management, prevention, and forecasting.

9 June 2025 in Healthcare
Verified
Journal Article
Open access
PDF file
YHYifan Hao
Yifan Hao
HZHu ZHAO
Hu ZHAO
RBRuhai Bai
Ruhai Bai
XZXu Zhixian
Xu Zhixian
FYFeng Yu
Feng Yu
HGHui Gu
Hui Gu
Background: East Asia accounts for the highest number of anxiety disorders cases globally, with China, Japan, and Republic of Korea representing 17.5% of global incidence according to GBD 2021. These nations offer a unique context for examining how different modernization paths impact anxiety disorders patterns. This study examined anxiety disorders incidence trends across these countries from 1992 to 2021 to compare disease burdens and inform public health strategies. Methods: Using GBD 2021 data, we employed age–period–cohort analysis to evaluate factors affecting anxiety disorders incidence, examining age-specific rates, period effects, and birth cohort influences. Results: All three countries experienced sharp increases in anxiety disorders following COVID-19. Age-standardized incidence rates decreased by 4.89% in China and 10.52% in Japan from 1992 to 2019, while remaining stable in Republic of Korea. Net drift was −0.40% for China, −0.50% for Japan, and approximately 0 for Republic of Korea. Local drifts were positive among older adults in China and Japan, and middle-aged adults in Republic of Korea. Longitudinal age curves showed inverted V-shaped patterns, peaking in the 10–14 age group across all three countries. China and Republic of Korea exhibit a second peak during middle age, while Japan shows continuous decline after the 10–14 age group. Period and cohort effects indicating overall decreases in China and Japan, with minimal changes in Republic of Korea. Conclusions: Different modernization trajectories have produced distinct anxiety disorders patterns across these East Asian nations. The elevated risk among adolescents across all countries warrants targeted interventions, while high risks among middle-aged adults in China and Republic of Korea requires age-specific approaches. Countries should utilize their healthcare systems’ strengths to create targeted strategies for reducing anxiety disorders while addressing pandemic-related mental health impacts.

2 December 2025 in Frontiers in Psychiatry
Verified
Journal Article
Open access
PDF file
YHYifan Hao
Yifan Hao
HZHu Zhao
Hu Zhao
ZXZhixian Xu
Zhixian Xu
YFYu Feng
Yu Feng
RBRuhai Bai
Ruhai Bai
HGHui Gu
Hui Gu
Background: Schizophrenia represents the psychiatric disorder with the highest per capita social cost globally, with East Asia bearing a disproportionate burden of schizophrenia episodes and associated disability-adjusted life years. This study aimed to comprehensively evaluate the long-term trends in schizophrenia incidence in China and Japan from 1990 to 2021. Methods: Data were extracted from the Global Burden of Disease 2021 study and systematically analyzed using age-period-cohort modeling approaches to disentangle temporal trends. Results: The overall drift values for schizophrenia incidence were -0.25% (95% CI: -0.28% to 0.23%) in China and 0.30% (95% CI: 0.20% to 0.41%) in Japan. In China, local drift values were positive only in the 10–25 age group and negative across all other age groups. For Japanese males, local drift values were negative except in the 15–25 age group. The longitudinal age curves for schizophrenia in the both countries demonstrated a characteristic inverted “V” shape, with peak incidence occurring in the 20–24 age group. Regarding period effects, China showed an overall decreasing trend that reversed toward unfavorable outcomes after 2014, while Japan also exhibited a decreasing trend recently, albeit with greater fluctuations. The cohort effect in China displayed a U-shaped pattern, whereas Japan showed an overall upward trend with a slight midpoint decrease, in the middle, followed by a sharp rise in risk for cohorts born after 2000. Conclusion: Despite established mental health initiatives in both China and Japan, schizophrenia risk is increasing among youth cohorts in both countries. This finding underscores the urgent need for both nations to develop more effective, demographically targeted approached to improve mental health outcomes across different population segments.