Pengxiang Hong

ORCID: 0009-0009-4114-4637
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About
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Research Areas
  • Insect symbiosis and bacterial influences
  • Spectroscopy and Chemometric Analyses
  • Plant Virus Research Studies
  • Model Reduction and Neural Networks
  • Smart Agriculture and AI
  • Plant and Fungal Interactions Research
  • Insect-Plant Interactions and Control
  • Seismic Imaging and Inversion Techniques
  • Entomopathogenic Microorganisms in Pest Control
  • Fire Detection and Safety Systems
  • Dam Engineering and Safety
  • Plant-Microbe Interactions and Immunity

Fujian Agriculture and Forestry University
2020-2024

Southern University of Science and Technology
2023

Tetranychus urticae is a highly polyphagous and global pest. Spider mites primarily feed on the underside of leaves, resulting in decreased photosynthesis, nutritional loss, development chlorotic patches. We investigated life tables two-spotted spider mite T. fungal endophyte Beauveria bassiana colonized untreated plants common Phaseolus vulgaris L., bean plant. Based age-stage, two-sex table theory, data were evaluated. The raised had protonymphs, deutonymphs, total pre-adult stage...

10.3390/insects15010073 article EN cc-by Insects 2024-01-21

p2 of rice stripe virus may translocate from the nucleus to cytoplasm and recruit nucleolar functions promote systemic movement. Cajal bodies (CBs) are nuclear components associated with nucleolus, which play a major role in plant infection. Coilin, marker protein CBs, is essential for CB formation function. Coilin contains three domains, N‐terminal, center, C‐terminal fragments. Using yeast two‐hybrid, colocalization, bimolecular fluorescence complementation (BiFC) approaches, we show that...

10.1155/2020/5182164 article EN cc-by BioMed Research International 2020-01-01

Introduction Biot's consolidation model in poroelasticity describes the interaction between fluid and deformable porous structure. Based on fixed-stress splitting iterative method proposed by Mikelic et al. (Computat Geosci, 2013), we present a network approach to solve using physics-informed neural networks (PINNs). Methods Two independent small are used displacement pressure variables separately. Accordingly, separate loss functions proposed, fixed stress algorithm is couple these...

10.3389/fams.2023.1206500 article EN cc-by Frontiers in Applied Mathematics and Statistics 2023-08-03
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