A5101912684- Anaerobic Digestion and Biogas Production
- Algal biology and biofuel production
- Microbial Metabolic Engineering and Bioproduction
- Microbial Fuel Cells and Bioremediation
- Biofuel production and bioconversion
- Biodiesel Production and Applications
- Wastewater Treatment and Nitrogen Removal
- Topic Modeling
- Electrochemical sensors and biosensors
- Advanced Photocatalysis Techniques
- Advanced oxidation water treatment
- Environmental remediation with nanomaterials
- Hybrid Renewable Energy Systems
- Microplastics and Plastic Pollution
- biodegradable polymer synthesis and properties
- Advanced Graph Neural Networks
- Pharmaceutical and Antibiotic Environmental Impacts
- Natural Language Processing Techniques
- Viral Infections and Vectors
- Adsorption and biosorption for pollutant removal
- Magnetic Field Sensors Techniques
- Wave and Wind Energy Systems
- X-ray Diffraction in Crystallography
- Crystallization and Solubility Studies
- Photosynthetic Processes and Mechanisms
Harbin Institute of Technology
2015-2025
Ministry of Agriculture and Rural Affairs
2023-2025
Northeast Agricultural University
2009-2025
Shanghai Ocean University
2019-2025
National Institute for Communicable Disease Control and Prevention
2020-2025
Guangzhou University
2025
Hefei Normal University
2024
Guangxi Veterinary Research Institute
2022-2024
Sichuan Academy of Forestry
2023-2024
Sichuan Agricultural University
2023-2024
Chlorinated organic pollutants constitute a significant category of persistent due to their widespread presence in the environment, which is primarily attributed expansion agricultural and industrial activities. These are characterized by persistence, potent toxicity, capability for long-range dispersion, emphasizing importance eradication mitigate environmental pollution. While conventional methods removing chlorinated encompass advanced oxidation, catalytic bioremediation, utilization...
Light-activated UL 3 generates active species (h + ) to attack DCF in a water environment, realizing efficient clean purification.
Population growth and industrialization have led to a rapid increase in the consumption of fossil fuels resources [...]
Pretraining a language model (LM) on text has been shown to help various downstream NLP tasks. Recent works show that knowledge graph (KG) can complement data, offering structured background provides useful scaffold for reasoning. However, these are not pretrained learn deep fusion of the two modalities at scale, limiting potential acquire fully joint representations and KG. Here we propose DRAGON (Deep Bidirectional Language-Knowledge Graph Pretraining), self-supervised approach pretraining...