A5101812804- Groundwater and Isotope Geochemistry
- Groundwater flow and contamination studies
- Seismic Imaging and Inversion Techniques
- Neural Networks Stability and Synchronization
- Hydrocarbon exploration and reservoir analysis
- Hydraulic Fracturing and Reservoir Analysis
- Geophysical Methods and Applications
- stochastic dynamics and bifurcation
- Drilling and Well Engineering
- Groundwater and Watershed Analysis
- Rock Mechanics and Modeling
- Hydrology and Watershed Management Studies
- Geochemistry and Geologic Mapping
- Nonlinear Dynamics and Pattern Formation
- Karst Systems and Hydrogeology
- Atmospheric and Environmental Gas Dynamics
- Climate variability and models
- Nuclear and radioactivity studies
- Noise Effects and Management
- Seismic Waves and Analysis
- Chaos control and synchronization
- Acoustic Wave Phenomena Research
- Remote Sensing and Land Use
- Geophysical and Geoelectrical Methods
- Neural Networks and Applications
Wuhan Institute of Technology
2016-2024
University of Chinese Academy of Sciences
2019-2024
Institute of Geology and Geophysics
2016-2024
Chinese Academy of Sciences
2014-2024
Shandong Center for Disease Control and Prevention
2024
Yangtze Optical Electronic (China)
2024
University of Minnesota
2020-2022
China Aerospace Science and Technology Corporation
2019-2022
Hefei Institutes of Physical Science
2022
Institute of Plasma Physics
2022
Abstract Hydraulic tomography (HT) has emerged as a potentially viable method for mapping fractures in geologic media demonstrated by recent studies. However, most of the studies adopted equivalent porous (EPM) models to generate and invert hydraulic interference test data HT. While these assign significant different properties matrix, they may not fully capture discrete nature rocks. As result, HT performance have been overrated. To explore this issue, study employed fracture network (DFN)...
Abstract. A comprehensive understanding of groundwater-surface water interaction patterns is crucial, particularly in arid regions Central Asia, where typical river-groundwater systems are prevalent. In this study, 31 river and groundwater samples were collected from the Shule River Basin (SRB) Northwest China analyzed for hydrochemical stable isotopic characteristics to elucidate spatial variations interactions. notable finding significant negative correlation between δ18O elevation, with a...
The finite-time Mittag–Leffler synchronization is investigated for fractional-order delayed memristive neural networks (FDMNN) with parameters uncertainty and discontinuous activation functions. relevant results are obtained under the framework of Filippov such systems. Firstly, novel feedback controller, which includes functions time delays, proposed to investigate Secondly, conditions on FDMNN established according properties calculus inequality analysis technique. At same time, upper...
<abstract abstract-type="Summary"> <sec> <b>What is already known about this topic?</b> Studies have extensively documented the separate and independent effects of extreme temperature ozone on morbidity mortality associated with respiratory circulatory diseases. </sec><sec> added by report?</b> The study revealed a significant association between elevated temperature, pollution, combined effect high pollution an increased risk all-cause medical emergency calls (MECs) MECs specifically...
Floodplain wetlands are of great importance in the entire river and floodplain ecosystems. Understanding hydrological processes is fundamental to study changes caused by climate change human activities. In this study, along middle reach Yellow River were selected as a area. The interactions between underlying aquifer investigated combining remote sensing, hydraulic monitoring, numerical modeling. Wetland areas from 2014 2019 extracted Landsat 8 sensing images, their correlation with runoff...
Light detection and ranging (LiDAR) is an essential sensor for three dimensional (3D) object via generating 3D point cloud of the surroundings, it has been widely used in various visual applications, especially autonomous driving. However, limited numbers labeled LiDAR datasets brutally restrain development detector, this situation breeds urgent demand on data augmentation field. By far, most traditional methods reuse samples, while those unlabeled are hastily untaken. Motivated by this, we...