Comparing perceived distributional equity in state-dominated and co-managed protected areas - Ying Lou; Yuqi Zhang; Yin Zhang; Yongbing Zhang; Zichen Fang; Jiale Tang; Xiaoqi Fan; Shakura N. Bashir (Land Use Policy, 2026)

Efficient degradation of chlorobenzene in a non-thermal plasma-liquid system enabled by Fe3O4@C catalysts - Caihong Qin; Xiaoge Zhang; Xuan Qu; Zichen Xue; Qiaoqiao Jiao; Xueyang Fan; Junji Lu (Journal of Environmental Chemical Engineering, 2026)

The interdecadal Pacific oscillation drives an extratropical tripole pattern in northern hemisphere summer rainfall anomalies - Zichen Tang; Song Yang; Noel Keenlyside; Lingling Suo; Hanjie Fan; Qingquan Li; Guillaume Gastineau; Tian Tian (Atmospheric Research, 2026)

Low-dose fluoride and lead co-exposure alters bone mineral density in youth: A nationally representative cross-sectional study - Chunxiang Li; Zeyuan Niu; Yuhui Du; Lihong Yang; Fan Wu; Xinxin Hu; Xiaohang Meng; Zichen Feng; Shu Niu; Qing Sun; Yan Wang; Xiaoli Fu; et al. (Journal of Trace Elements in Medicine and Biology, 2026)

Managing street-tree health under rapid urbanization: Relative roles of street context and root-zone conditions in a subtropical city - Wenting Wang; Min Wu; Hai Yan; Ying Chen; Zichen Zhao; Lin Zhu; Jiangnan Shi; Renwu Wu; Fan Yang; Zhiyi Bao (Journal of Environmental Management, 2026)

Advances and Perspectives in Atmospheric Environment Modeling in China - Zifa Wang; Xinwei Li; Meng Gao; Baozhu Ge; Xiao Tang; Xueshun Chen; Qizhong Wu; Lin Wu; Zhe Wang; Ting Yang; Xiaole Pan; Huansheng Chen; et al. (Advances in Atmospheric Sciences, 2026)

Notch1-dependent hippocampal apoptosis is associated with monocrotaline-induced anxiety-like behavior - Lai Baochang; Li Fan; Wang Fei; Yan Xianchun; Wang Zichen; Han Mengzhuan; Zhang Yiman; Kang Mengyang; Liu Bing; Wang Ying; Ma Qiang; Jia Pu; et al. (Toxicology, 2026)

Air temperature differences and view factor influences between sidewalks and roadways in urban streets: A case study in Hangzhou, China - Zichen Zhao; Hai Yan; Huaizhen Zhu; Xinge Nan; Renwu Wu; Wenting Wang; Wei Yang; Lin Zhu; Jiangnan Shi; Fan Yang; Zhiyi Bao (Building and Environment, 2026)

Systems metabolic engineering and process optimization for efficient l-tyrosine production from high-purity glucose syrup in Escherichia coli - Zhichao Chen; Ling Ma; Weiwei Liu; Changgeng Li; Meng Yuan; Zichen Yu; Lanxiao Li; Xiaoguang Fan; Qingyang Xu (Bioresource Technology, 2025)

The mechanism of pore pressure and adsorption swelling effect on permeability during geological storage of carbon dioxide in coal seams - Zhenbao Li; Zichen Fan; Hu Wang; Shaorui Wang; Chao Li (Fuel, 2025)

Nitrogen deposition enhances accumulation of microbial and plant-derived carbon in forest soils: a global meta-analysis - Chenying Wang; Xiaoyan Li; Meng Zhang; Zichen Han; Yun Xia; Pingping Lian; Liuming Yang; Kai Yue; Yuexin Fan (Plant and Soil, 2024)

Nanofiber aerogel with layered array with structure coupled photothermal/magnetothermal effect for continuous seawater desalination - Zichen Yu; Tingting Fan; Yang Liu; Bowen Yang; Luyao Wang; Fang Yin; Yuan Gao; Yun-Ze Long (Chemical Engineering Journal, 2024)

High-level and -yield orotic acid production in Escherichia coli through systematic modular engineering and “Chaos to Order Cycles” fermentation - Changgeng Li; Tangen Shi; Wenjing Fan; Meng Yuan; Lanxiao Li; Zichen Yu; Zhichao Chen; Qingyang Xu (Bioresource Technology, 2024)

Simulating liquefaction-induced resuspension flux in a sediment transport model - Zichen Zhu; Xing Du; Bingchen Liang; Linfeng Wang; Yupeng Song; Ping Li; Yaoshen Fan; Shuhua Bian; Yongzhi Wang; Yongqiang Zhang; Bing Li (Water Research, 2024)

Injectable photocrosslinkable acellular cartilage matrix hydrogel loaded with exosomes for promoting growth plate injury repair - Xinxin Si; Quan Zhang; Bo Ning; Lei Qiang; Qiang Li; Yihao Liu; Minjie Fan; Jing Shan; Guanlu Shen; Zichen Lin; Pengfei Zheng (Chemical Engineering Journal, 2024)

Migration mechanisms of 90Sr and 137Cs on terraces - Yongjing Guan; Zichen Guo; Wu Chen; Kaidi Fan; Hua He; Liangjia Cui; Chunping Huang; Xianwen He; Zeyue Xu; Jiajia Zhang; Ye He; Huijuan Wang (Journal of Environmental Radioactivity, 2024)

Assessment of the depositional characteristics of the Yellow River estuary from 1960s by 239+240Pu and 137Cs - Yongjing Guan; Kaidi Fan; Shenzhen Wang; Liangjia Cui; Huijuan Wang; Zichen Guo; Wu Chen; Hua He; Zhiyong Liu (Science of The Total Environment, 2024)

Heart valve-inspired self-lubricating anticoagulant surfaces - Yang Cheng; Zhiwei Yang; Xiaodan Gou; Qing Yang; Zichen Zhang; Shiyu Cui; Yuhua Ren; Lihong Fan; Haifeng Zhang; Zheng Fang; Yu Lu; Lin Kai; et al. (Chemical Engineering Journal, 2023)

Electromagnetic radiation prediction of damage characteristics of water-bearing sandstone under cyclic loading and unloading - Rongxi Shen; Hailiang Chen; Enlai Zhao; Taixun Li; Weijun Fan; Zichen Yuan (Bulletin of Engineering Geology and the Environment, 2022)

Risk factors for recurrent positive results of the nucleic acid amplification test for COVID-19 patients: a retrospective study - Wanwan Yi; Xuan Long; Jin Liu; LiShuai Shi; Zichen Chen; Jing Yang; Ziyu Yang; Zhongwei Lv; Hengwei Fan (Human Cell, 2021)
Positive retests of COVID-19 represent a public health concern because of the increased risk of transmission. This study explored whether factors other than the nucleic acid amplification test (NAAT) contribute to positive retest results. Patients with COVID-19 admitted to the Guanggu district of the Hubei Maternal and Child Health Hospital between February 17 and March 28, 2020, were retrospectively included. The patients were grouped into the negative ( n = 133) and positive ( n = 51) retest groups. The results showed that the proportion of patients presenting with cough was higher ( P < 0.001) and the proportion of patients with dyspnea was lower ( P = 0.018) in the positive than in the negative retest group. The positive retest group showed shorter durations between symptom onset and hospitalization ( P < 0.001) and symptom onset and the first positive NAAT ( P = 0.033). The positive retest group had higher basophil counts ( P = 0.023) and direct bilirubin ( P = 0.032) and chlorine concentrations ( P = 0.023) but lower potassium concentrations ( P = 0.001) than the negative retest group. Multivariable regression analysis showed that coughing (OR = 7.59, 95% CI 2.28–25.32, P = 0.001) and serum chloride concentrations (OR = 1.38, 95% CI 1.08–1.77, P = 0.010) were independently associated with a positive retest result. Coughing and serum chloride concentrations were independent risk factors for positive NAAT retest results. Patients with a hospital stay of < 2 weeks or a short incubation period should stay in isolation and be monitored to reduce transmission. These results could help identify patients who require closer surveillance.

Deep Learning Convolutional Neural Network Applying for the Arctic Acoustic Tomography Current Inversion Accuracy Improvement - Kangkang Jin; Jian Xu; Zichen Wang; Can Lu; Long Fan; Zhongzheng Li; Jiaxin Zhou (Journal of Marine Science and Engineering, 2021)
Warm current has a strong impact on the melting of sea ice, so clarifying the current features plays a very important role in the Arctic sea ice coverage forecasting study field. Currently, Arctic acoustic tomography is the only feasible method for the large-range current measurement under the Arctic sea ice. Furthermore, affected by the high latitudes Coriolis force, small-scale variability greatly affects the accuracy of Arctic acoustic tomography. However, small-scale variability could not be measured by empirical parameters and resolved by Regularized Least Squares (RLS) in the inverse problem of Arctic acoustic tomography. In this paper, the convolutional neural network (CNN) is proposed to enhance the prediction accuracy in the Arctic, and especially, Gaussian noise is added to reflect the disturbance of the Arctic environment. First, we use the finite element method to build the background ocean model. Then, the deep learning CNN method constructs the non-linear mapping relationship between the acoustic data and the corresponding flow velocity. Finally, the simulation result shows that the deep learning convolutional neural network method being applied to Arctic acoustic tomography could achieve 45.87% accurate improvement than the common RLS method in the current inversion.

The complete genome sequence of Escherichia phage SRT7, a novel T7-like phage - Kaili Zhao; Shukai Song; Zhipeng Zhao; Zichen Liu; Yan Ji; Pengfei Gu; Xiangyu Fan; Qiang Li (Archives of Virology, 2019)