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Im, Se Pyeong,Kim, Jaesung,Lee, Jung Seok,Kim, Si Won,Jung, Jae Wook,Lazarte, Jassy Mary S.,Kim, Jong Yong,Kim, Young Rim,Lee, Jeong Ho,Chong, Roger S. M.,Jung, Tae Sung American Association of Immunologists 2018 Journal of Immunology Vol. No.
<P>The variable lymphocyte receptor (VLR) B of jawless vertebrates functions as a secreted Ab of jawed vertebrates and has emerged as an alternative Ab with a single polypeptide chain. After observing an upregulated VLRB response in hagfish immunized with avian influenza virus (AIV) subtype H9N2, we screened AIV H9N2–specific VLRB using a mammalian expression system. To improve the binding avidity of the Ag-specific VLRB to the Ag, we enabled multimerization of the VLRB by conjugating it with C-terminal domain of human C4b-binding protein. To dramatically enhance the expression and secretion of the Ag-specific VLRB, we introduced a glycine–serine linker and the murine Ig κ leader sequence. The practical use of the Ag-specific VLRB was also demonstrated through various immunoassays, detected by anti-VLRB Ab (11G5). Finally, we found that the Ag-specific VLRB decreased the infectivity of AIV H9N2. Together, our findings suggest that the generated Ag-specific VLRB could be used for various immunoapplications.</P>
Review : Current Status of Tree Height Estimation from Airborne LiDAR Data
Se Ran Hwang,Im Pyeong Lee 大韓遠隔探査學會 2011 大韓遠隔探査學會誌 Vol.27 No.3
Most nations around the world have expressed significant concern in the climate change due to a rapid increase in green-house gases and thus reach an international agreement to control total amount of these gases for the mitigation of global warming. As the most important absorber of carbon dioxide, one of major green-house gases, forest resources should be more tightly managed with a means to measure their total amount, forest biomass, efficiently and accurately. Forest biomass has close relations with forest areas and tree height. Airborne LiDAR data helps extract biophysical properties on forest resources such as tree height more efficiently by providing detailed spatial information about the wide-range ground surface. Many researchers have thus developed various methods to estimate tree height using LiDAR data, which retain different performance and characteristics depending on forest environment and data characteristics. In this study, we attempted to investigate such various techniques to estimate tree height, elaborate their advantages and limitations, and suggest future research directions. We first examined the characteristics of LiDAR data applied to forest studies and then analyzed methods on filtering, a precedent procedure for tree height estimation. Regarding the methods for tree height estimation, we classified them into two categories: individual tree-based and regression-based method and described the representative methods under each category with a summary of their analysis results. Finally, we reviewed techniques regarding data fusion between LiDAR and other remote sensing data for future work.
Current Status of Tree Height Estimation from Airborne LiDAR Data
Hwang, Se-Ran,Lee, Im-Pyeong The Korean Society of Remote Sensing 2011 大韓遠隔探査學會誌 Vol.27 No.3
Most nations around the world have expressed significant concern in the climate change due to a rapid increase in green-house gases and thus reach an international agreement to control total amount of these gases for the mitigation of global warming. As the most important absorber of carbon dioxide, one of major green-house gases, forest resources should be more tightly managed with a means to measure their total amount, forest biomass, efficiently and accurately. Forest biomass has close relations with forest areas and tree height. Airborne LiDAR data helps extract biophysical properties on forest resources such as tree height more efficiently by providing detailed spatial information about the wide-range ground surface. Many researchers have thus developed various methods to estimate tree height using LiDAR data, which retain different performance and characteristics depending on forest environment and data characteristics. In this study, we attempted to investigate such various techniques to estimate tree height, elaborate their advantages and limitations, and suggest future research directions. We first examined the characteristics of LiDAR data applied to forest studies and then analyzed methods on filtering, a precedent procedure for tree height estimation. Regarding the methods for tree height estimation, we classified them into two categories: individual tree-based and regression-based method and described the representative methods under each category with a summary of their analysis results. Finally, we reviewed techniques regarding data fusion between LiDAR and other remote sensing data for future work.