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  1. 301

    Impact of Climate Change on Hydrologic Extremes in the Upper Basin of the Yellow River Basin of China by Jun Wang, Zhongmin Liang, Dong Wang, Tian Liu, Jing Yang

    Published 2016-01-01
    “…On this basis, quantitative estimation of the impact of climate change on long duration flood volume extremes was conducted. …”
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  2. 302

    Analysis of Climate and Land Use Changes Impacts on Land Degradation in the North China Plain by Zhihui Li, Xiangzheng Deng, Fang Yin, Cuiyuan Yang

    Published 2015-01-01
    “…Land degradation is a complex process which involves both the natural ecosystem and the socioeconomic system, among which climate and land use changes are the two predominant driving factors. To comprehensively and quantitatively analyze the land degradation process, this paper employed the Normalized Difference Vegetation Index (NDVI) as a proxy to assess land degradation and further applied the binary panel logit regression model to analyze the impacts of the driving factors on land degradation in the North China Plain. …”
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    The impact of chronic disease diagnoses on smoking behavior change and maintenance: Evidence from China by Xinxin Chi, Xihua Liu, Cong Li, Wen Jiao

    Published 2024-01-01
    “…CS-DID was run using the study sample from the 2011 to 2018 waves of the China Health and Retirement Longitudinal Study, comparing results with traditional two-way fixed effects and event-study models. …”
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    Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in China by Xuepeng Zhang, Taixia Wu, Qiqi Du, Ninglei Ouyang, Wei Nie, Yang Liu, Peng Gou, Guangchao Li

    Published 2025-01-01
    “…The study found that: (1) From 1995 to 2020, EH in the Loess Plateau increased from 0.42 to 0.58, and the forms of spatial clustering changed. Moreover, there are significant differences in the speed and patterns of EH improvement in different regions, especially after 2010. (2) The importance of precipitation (PRE), SED, ERP, and temperature (TEM) is 33 %, 26 %, 24 %, and 17 %, respectively. …”
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  7. 307

    Nonlinearity and Fractal Properties of Climate Change during the Past 500 Years in Northwestern China by Shiquan Wan, Qunqun Liu, Jianxin Zou, Wenping He

    Published 2016-01-01
    “…By using detrended fluctuation analysis (DFA), the present paper analyzed the nonlinearity and fractal properties of tree-ring records from two types of trees in northwestern China, and then we disclosed climate change characteristics during the past 500 years in this area. …”
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  8. 308

    Responses of Streamflow to Climate Change and Human Activities in a River Basin, Northeast China by Hanwen Zhang, Wei Xu, Xintong Xu, Baohong Lu

    Published 2017-01-01
    “…In this paper, the long-term trend of precipitation and streamflow in Yi River Basin, from 1964 to 2010, was investigated via Mann-Kendall test. The change point occurred in the year 1965 dividing the long-term series into two periods. …”
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  9. 309

    Vegetation Activity Trend and Its Relationship with Climate Change in the Three Gorges Area, China by Guifeng Han, Yongchuan Yang, Shuiyu Yan

    Published 2013-01-01
    “…Therefore, temperature and precipitation are not major influences on vegetation activity change. Instead, increasing vegetation cover benefits from a number of environment protection policies and management, and ecological construction is a major factor resulting in the upward trend. …”
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    Changes in Air Quality during the COVID-19 Lockdown in Singapore and Associations with Human Mobility Trends by Jiayu Li, Federico Tartarini

    Published 2024-12-01
    “…The concentrations of the following pollutants PM10, PM2.5, NO2, CO, and SO2 decreased by 23, 29, 54, 6, and 52%, respectively, whilst that of O3 increased by 18%. …”
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    Statistical analysis of stress–strength in a newly inverted Chen model from adaptive progressive type-Ⅱ censoring and modelling on light-emitting diodes and pump motors by Refah Alotaibi, Mazen Nassar, Zareen A. Khan, Ahmed Elshahhat

    Published 2024-12-01
    “…By analyzing the failure times of organic white light-emitting diodes and pump motors, we focus on the inferences of the stress–strength index $ \mathfrak{R} = P(Y < X) $, where: (1) the strength $ (X) $ and stress $ (Y) $ are independent random variables following inverted Chen distributions, and (2) the data are acquired using the adaptive progressive type- censoring plan. …”
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