From early facies-controlled karstification to hydrothermal alteration: Multistage diagenesis and reservoir evolution of the Ediacaran Qigebrak Formation, Tarim Basin, NW China - Xiangyong Li; Dongfang Zhao; Anping Hu; Shaorui Li; Zhanfeng Qiao; Lingzhi Du; Chonghao Sun; Yan Yi; Xiucheng Tan (Sedimentary Geology, 2026)

Exposure to 4-hydroxy-4′-isopropoxydiphenylsulfone causes retinal structural damage and visual impairment in zebrafish - Kaini Hu; Congshu Wang; Chengzhi Ying; Jiatong Shen; Tingting Wu; Zhendong Sun; Teng Zhang; Siying Hu; Kexin Xu; Jiajun Lu; Anping Zhang; Shengnan Zhang; et al. (Journal of Environmental Sciences, 2026)

Types, genesis, and distribution of deep to ultra-deep carbonate reservoirs: insights from China - Anjiang Shen; Anping Hu; Tianjie Jin; Xi Li; Junmao Duan; Zhanfeng Qiao; Jianfeng Zheng (Earth-Science Reviews, 2026)

Optimizing economy-energy-environment (3Es) policy mixes for decarbonization: Synergies, trade-offs, and regional implementation in China - Anping Ye; Yu-Jie Hu; Bao-Jun Tang; Ting Wang; Yao Tao (Energy Policy, 2026)

Genomic insights into stepwise selection reshaping fruit traits and male-biased selection driving hermaphroditism in papayas - Changmian Ji; Ruizong Jia; Yuliang Zhang; Xiaoxi Du; Xueying Huang; Huiliang Li; He Dai; Yu Wang; Qian Jiang; Zhengnan Xie; Shanshan Huo; Yang Cao; et al. (Molecular Plant, 2026)

Microglial Necroptosis Mediated by RIPK3 Leads to Retinal Ganglion Cell Apoptosis Through the Release of FGF2 After Ischemia/Reperfusion - Jian Liu; Anping Ma; Guangyi Huang; Wen Hu; Xin Xu; Rong Huang; Yaguang Hu; Qiaochu Cheng; Yanlin Feng; Dan Ye; Fan Xu; Aimin Sang (Journal of Molecular Neuroscience, 2025)

Digital economy-driven decarbonization pathways: An integrated input-output and scenario analysis for China's 3060 dual-carbon targets - Yu-Jie Hu; Anping Ye; Bao-Jun Tang (Journal of Cleaner Production, 2025)

Novel HF pre-enrichment approach for high-precision molybdenum isotope analysis in low-Mo carbonates by MC-ICP-MS - Yan Han; Lian Zhou; Anping Hu; Lanping Feng; Anjiang Shen; Zhaochu Hu (Analytica Chimica Acta, 2025)

Key geochemical processes in typical magmatic hydrothermal systems explaining REE patterns in the neutral boiling springs - Xiaobo Zhang; Qinghai Guo; Xin Li; Anping Luo; Feng Hu; Mengzhao Zhang; Weihao Sun (Journal of Hydrology, 2025)

The Regulation Mechanism of MYC on MeJA-Induced Flavonoids Synthesis in Dendrobium officinale - Yue Jia; Wenna Meng; Guihong Chen; Xiangqian Fan; Yu Zhang; Anping Ding; Mengyao Xu; Gang Hu; Mingpu Tan; Zengxu Xiang (Journal of Plant Growth Regulation, 2025)

Characterization and fine mapping of a white stripe leaf mutant in rice - Binhua Hu; Zhiyuan He; Xiaoli Xiang; Hui Li; Anping Du; Mingxia Wang; Yulu Bai; Lanying Wang; Cong Zhang; Ping Wang; Zhigang Pu (Genetic Resources and Crop Evolution, 2024)

Development and preservation mechanism of deep and ultra-deep carbonate reservoirs - Anjiang Shen; Anping Hu; Zhanfeng Qiao; Jianfeng Zheng; Min She; Liyin Pan (Science China Earth Sciences, 2024)

Vessel Trajectory Prediction Based on Automatic Identification System Data: Multi-Gated Attention Encoder Decoder Network - Fan Yang; Chunlin He; Yi Liu; Anping Zeng; Longhe Hu (Journal of Marine Science and Engineering, 2024)
Utilizing time-series data from ship trajectories to forecast their subsequent movement is crucial for enhancing the safety within maritime traffic environments. The application of deep learning techniques, leveraging Automatic Identification System (AIS) data, has emerged as a pivotal area in maritime traffic studies. Within this domain, the precise forecasting of ship trajectories stands as a central challenge. In this study, we propose the multi-gated attention encoder decoder (MGAED) network, a model based on an encoder–decoder structure specialized for predicting ship trajectories in canals. The model employs a long short-term memory network (LSTM) as an encoder, combined with multiple Gated Recurrent Units (GRUs) and an attention mechanism for the decoder. Long-term dependencies in time-series data are captured through GRUs, while the attention mechanism is used to strengthen the model’s ability to capture key information, and a soft threshold residual structure is introduced to handle sparse features, thus enhancing the model’s generalization ability and robustness. The efficacy of our model is substantiated by an extensive evaluation against current deep learning benchmarks. Through comprehensive comparison experiments with existing deep learning methods, our model shows significant improvements in prediction accuracy, with an at least 9.63% reduction in the mean error (MAE) and an at least 20.0% reduction in the mean square error (MSE), providing a new solution to improve the accuracy and efficiency of ship trajectory prediction.

Seismic stability of expansive soil slopes reinforced by anchor cables using a modified horizontal slice method - Long Wang; Guoxing Chen; Wei Hu; Enquan Zhou; Jianxue Feng; Anping Huang (Earthquake Engineering and Engineering Vibration, 2024)

Cenozoic tectonic transition within the western segment of the Longmenshan fault, southeast margin of the Tibetan Plateau: Insights from geological and geophysical data - Jian Yang; Qiao Wang; Shibin Xia; Guozhong Liao; Chuanlong Mou; Hu Wang; Anping Xiang; Hua Li; Wei Zhang; Xuben Wang (Tectonophysics, 2024)

Dolomite dissolution and porosity enhancement simulation with acetic acid: Insights into the influence of temperature and ionic effects - Min She; Jintong Liang; Yuzhen Lv; Anping Hu; Zhanfeng Qiao (Applied Geochemistry, 2024)

Influence of organic cosolvents on hexabromobenzene degradation in solution by montmorillonite-templated subnanoscale zero-valent iron - Anping Peng; Hu Gao; Huimin Wang; Yi Wang; Zeyou Chen (Environmental Research, 2023)

δ26Mg-δ13C-δ18O systems as geochemical tracers for dolomite recrystallization: A case study of lower Ordovician dolomite from Tarim Basin - Hairuo Qing; Zhanfeng Qiao; Siyang Zhang; Jason Cosford; Anping Hu; Feng Liang; Yongsheng Wang; Jianfeng Zheng (Chemical Geology, 2023)

The global decline in the sensitivity of vegetation productivity to precipitation from 2001 to 2018 - Xiang Zeng; Zhongmin Hu; Anping Chen; Wenping Yuan; Guolong Hou; Daorui Han; Minqi Liang; Kai Di; Ruochen Cao; Dengnan Luo (Global Change Biology, 2022)
The sensitivity of vegetation productivity to precipitation ( S ppt ) is a key metric for understanding the variations in vegetation productivity under changing precipitation and predicting future changes in ecosystem functions. However, a comprehensive assessment of S ppt over all the global land is lacking. Here, we investigated spatial patterns and temporal changes of S ppt across the global land from 2001 to 2018 with multiple streams of satellite observations. We found consistent spatial patterns of S ppt with different satellite products: S ppt was highest in dry regions while low in humid regions. Grassland and shrubland showed the highest S ppt , and evergreen needle‐leaf forest and wetland showed the lowest. Temporally, S ppt showed a generally declining trend over the past two decades ( p S ppt was especially noticeable in North America and Europe, likely due to the increase in precipitation. In central Russia and Australia, however, S ppt showed an increasing trend. Biome‐wise, most ecosystem types exhibited significant decrease in S ppt , while grassland, evergreen broadleaf forest, and mixed forest showed slight increases or non‐significant changes in S ppt . Our finding of the overall decline in S ppt implies a potential stabilization mechanism for ecosystem productivity under climate change. However, the revealed S ppt increase for some regions and ecosystem types, in particular global grasslands, suggests that grasslands might be increasingly vulnerable to climatic variability with continuing global climate change.

Identification and Expression Analyses of the Special 14–3-3 Gene Family in Papaya and its Involvement in Fruit Development, Ripening, and Abiotic Stress Responses - Meiying Li; Licheng Ren; Zhi Zou; Wei Hu; Susheng Xiao; Xiaoliang Yang; Zehong Ding; Yan Yan; Weiwei Tie; Jinghao Yang; Anping Guo (Biochemical Genetics, 2021)

Identification, Expression, and Interaction Network Analyses of the CDPK Gene Family Reveal Their Involvement in the Development, Ripening, and Abiotic Stress Response in Banana - Meiying Li; Wei Hu; Licheng Ren; Caihong Jia; Juhua Liu; Hongxia Miao; Anping Guo; Biyu Xu; Zhiqiang Jin (Biochemical Genetics, 2020)

Towards elucidation of the toxic mechanism of copper on the model green alga Chlamydomonas reinhardtii - Yongguang Jiang; Yanli Zhu; Zhangli Hu; Anping Lei; Jiangxin Wang (Ecotoxicology, 2016)

Stereoselective toxicity of malathion and its metabolites, malaoxon and isomalathion - Anping Zhang; Xuemei Xie; Jing Ye; Chunmian Lin; Xiaoyan Hu (Environmental Chemistry Letters, 2011)

Changes in topsoil carbon stock in the Tibetan grasslands between the 1980s and 2004 - YUANHE YANG; JINGYUN FANG; PETE SMITH; YANHONG TANG; ANPING CHEN; CHENGJUN JI; HUIFENG HU; SHENG RAO; KUN TAN; JIN‐SHENG HE (Global Change Biology, 2009)
Climate warming is likely inducing carbon loss from soils of northern ecosystems, but little evidence comes from large‐scale observations. Here we used data from a repeated soil survey and remote sensing vegetation index to explore changes in soil organic carbon (SOC) stock on the Tibetan Plateau during the past two decades. Our results showed that SOC stock in the top 30 cm depth in alpine grasslands on the plateau amounted to 4.4 Pg C (1 Pg=10 15 g), with an overall average of 3.9 kg C m −2 . SOC changes during 1980s–2004 were estimated at −0.6 g C m −2 yr −1 , ranging from −36.5 to 35.8 g C m −2 yr −1 at 95% confidence, indicating that SOC stock in the Tibetan alpine grasslands remained relatively stable over the sampling periods. Our findings are nonconsistent with previous reports of loss of soil C in grassland ecosystems due to the accelerated decomposition with warming. In the case of the alpine grasslands on the Tibetan Plateau studied here, we speculate that increased rates of decomposition as soils warmed during the last two decades may have been compensated by increased soil C inputs due to increased grass productivity. These results suggest that soil C stock in terrestrial ecosystems may respond differently to climate change depending on ecosystem type, regional climate pattern, and intensity of human disturbance.

Antioxidant responses of microalgal species to pyrene - Anping Lei; Zhangli Hu; Yukshan Wong; Nora Fungyee Tam (Journal of Applied Phycology, 2006)