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Your search keyword '"Zhang, Jiantao"' showing total 27 results
Start Over Author "Zhang, Jiantao" Publisher mdpi ag
27 results on '"Zhang, Jiantao"'

10. Derived Profiles of CCN and INP Number Concentrations in the Taklimakan Desert via Combined Polarization Lidar, Sun-Photometer, and Radiosonde Observations

Author

Zhang, Shuang, primary, Huang, Zhongwei, additional, Alam, Khan, additional, Li, Meishi, additional, Dong, Qingqing, additional, Wang, Yongkai, additional, Shen, Xingtai, additional, Bi, Jianrong, additional, Zhang, Jiantao, additional, Li, Wuren, additional, Li, Ze, additional, Wang, Wenbiao, additional, Cui, Zhengnan, additional, and Song, Xiaodong, additional

Published
2023
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22. Design of Plant Protection UAV Variable Spray System Based on Neural Networks

Author

Yubin Lan, Xuanchun Yin, Zhang Jiantao, Yufeng Ge, Sheng Wen, and Quanyong Zhang

Subjects
Imagination, UAV, Propeller (aeronautics), media_common.quotation_subject, Nozzle, variable spray, 02 engineering and technology, BP neural network, lcsh:Chemical technology, Biochemistry, Article, Wind speed, Automotive engineering, Analytical Chemistry, 0202 electrical engineering, electronic engineering, information engineering, Deposition (phase transition), lcsh:TP1-1185, Electrical and Electronic Engineering, Instrumentation, media_common, Artificial neural network, 04 agricultural and veterinary sciences, Atomic and Molecular Physics, and Optics, Backpropagation, Volumetric flow rate, droplet deposition, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, 020201 artificial intelligence & image processing
Abstract

Recently, unmanned aerial vehicles (UAVs) have rapidly emerged as a new technology in the fields of plant protection and pest control in China. Based on existing variable spray research, a plant protection UAV variable spray system integrating neural network based decision making is designed. Using the existing data on plant protection UAV operations, combined with artificial neural network (ANN) technology, an error back propagation (BP) neural network model between the factors affecting droplet deposition is trained. The factors affecting droplet deposition include ambient temperature, ambient humidity, wind speed, flight speed, flight altitude, propeller pitch, nozzles pitch and prescription value. Subsequently, the BP neural network model is combined with variable rate spray control for plant protection UAVs, and real-time information is collected by multi-sensor. The deposition rate is determined by the neural network model, and the flow rate of the spray system is regulated according to the predicted deposition amount. The amount of droplet deposition can meet the prescription requirement. The results show that the training variance of the ANN is 0.003, and thus, the model is stable and reliable. The outdoor tests show that the error between the predicted droplet deposition and actual droplet deposition is less than 20%. The ratio of droplet deposition to prescription value in each unit is approximately equal, and a variable spray operation under different conditions is realized.

Published
2019

26. Advanced Protocol for Molecular Characterization of Viral Genome in Fission Yeast ( Schizosaccharomyces pombe ).

Author

Zhang J, Benko Z, Zhang C, and Zhao RY

Abstract

Fission yeast, a single-cell eukaryotic organism, shares many fundamental cellular processes with higher eukaryotes, including gene transcription and regulation, cell cycle regulation, vesicular transport and membrane trafficking, and cell death resulting from the cellular stress response. As a result, fission yeast has proven to be a versatile model organism for studying human physiology and diseases such as cell cycle dysregulation and cancer, as well as autophagy and neurodegenerative diseases like Alzheimer's, Parkinson's, and Huntington's diseases. Given that viruses are obligate intracellular parasites that rely on host cellular machinery to replicate and produce, fission yeast could serve as a surrogate to identify viral proteins that affect host cellular processes. This approach could facilitate the study of virus-host interactions and help identify potential viral targets for antiviral therapy. Using fission yeast for functional characterization of viral genomes offers several advantages, including a well-characterized and haploid genome, robustness, cost-effectiveness, ease of maintenance, and rapid doubling time. Therefore, fission yeast emerges as a valuable surrogate system for rapid and comprehensive functional characterization of viral proteins, aiding in the identification of therapeutic antiviral targets or viral proteins that impact highly conserved host cellular functions with significant virologic implications. Importantly, this approach has a proven track record of success in studying various human and plant viruses. In this protocol, we present a streamlined and scalable molecular cloning strategy tailored for genome-wide and comprehensive functional characterization of viral proteins in fission yeast.

Published
2024
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27. SARS-CoV-2 ORF3a Protein as a Therapeutic Target against COVID-19 and Long-Term Post-Infection Effects.

Author

Zhang J, Hom K, Zhang C, Nasr M, Gerzanich V, Zhang Y, Tang Q, Xue F, Simard JM, and Zhao RY

Abstract

The COVID-19 pandemic caused by SARS-CoV-2 has posed unparalleled challenges due to its rapid transmission, ability to mutate, high mortality and morbidity, and enduring health complications. Vaccines have exhibited effectiveness, but their efficacy diminishes over time while new variants continue to emerge. Antiviral medications offer a viable alternative, but their success has been inconsistent. Therefore, there remains an ongoing need to identify innovative antiviral drugs for treating COVID-19 and its post-infection complications. The ORF3a (open reading frame 3a) protein found in SARS-CoV-2, represents a promising target for antiviral treatment due to its multifaceted role in viral pathogenesis, cytokine storms, disease severity, and mortality. ORF3a contributes significantly to viral pathogenesis by facilitating viral assembly and release, essential processes in the viral life cycle, while also suppressing the body's antiviral responses, thus aiding viral replication. ORF3a also has been implicated in triggering excessive inflammation, characterized by NF-κB-mediated cytokine production, ultimately leading to apoptotic cell death and tissue damage in the lungs, kidneys, and the central nervous system. Additionally, ORF3a triggers the activation of the NLRP3 inflammasome, inciting a cytokine storm, which is a major contributor to the severity of the disease and subsequent mortality. As with the spike protein, ORF3a also undergoes mutations, and certain mutant variants correlate with heightened disease severity in COVID-19. These mutations may influence viral replication and host cellular inflammatory responses. While establishing a direct link between ORF3a and mortality is difficult, its involvement in promoting inflammation and exacerbating disease severity likely contributes to higher mortality rates in severe COVID-19 cases. This review offers a comprehensive and detailed exploration of ORF3a's potential as an innovative antiviral drug target. Additionally, we outline potential strategies for discovering and developing ORF3a inhibitor drugs to counteract its harmful effects, alleviate tissue damage, and reduce the severity of COVID-19 and its lingering complications.

Published
2024
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