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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>
LIDAR 데이터로부터 지표점 추출을 위한 피쳐 기반 방법
이임평 ( Im Pyeong Lee ) 大韓遠隔探査學會 2006 大韓遠隔探査學會誌 Vol.22 No.4
지표점의 추출은 DTM 생성을 위한 가장 중요한 과정이다. 기존의 지표점 추출 방법은 대부분 점기반방법으로 분류될 수 있다. 점기반방법은 모든 개별점(point)에 대하여 해당 점이 지표를 구성하는 점인지를 시험하는 방법이다. 이 때 시험의 회수는 점의 개수와 동일하기 때문에, 특히 점의 수가 많은 데이터를 처리할 경우 계산량이 심각하게 늘어나 시험에 보다 정교한 기준과 전략을 사용하는데 어려움이 있었다. 이로 인해 많은 연구에도 불구하고 아직 만족할만한 결과를 제공하는 방법이 개발되지 못하였다. 이에 본 연구는 시험하는 개체의 수를 줄이면서 보다 안정적인 결과를 얻을 수 있도록 점이 아닌 피쳐에 기반한 방법을 제안한다. 여기서, 피쳐란 점을 그룹화하여 얻을 수 있는 개체를 의미한다. 제안된 방법에서는 먼저 점들로부터 표면패치들을 생성하고, 이어서 표면패치들로부터 표면집단들을 구성한다. 구성된 표면집단들로부터 지표에 해당하는 표면집단을 식별한 후 식별된 표면집단에 포함된 모든 점들을 지표점으로 명시한다. 이 방법을 항공 LIDAR 실측데이터에 적용하여 제안된 방법의 뛰어난 성능을 실험적으로 증명하였다. Extracting ground points is the kernel of DTM generation being considered as one of the most popular LIDAR applications. The previous extraction approaches can be mostly characterized as a point based approach, which sequentially examines every individual point to determine whether it is measured from ground surfaces. The number of examinations to be performed is then equivalent to the number of points. Particularly in a large set, the heavy computational requirement associated with the examinations is obviously an obstacle to employing more sophisticated criteria for the examination. To reduce the number of entities to be examined and produce more robust results, we developed an approach based on features rather than points, where a feature indicates an entity constructed by grouping some points. In the proposed approach, we first generate a set of features by organizing points into surface patches and grouping the patches into surface clusters. Among these features, we then attempt to identify the ground features with the criteria based on the attributes of the features. The points grouped into these identified features are labeled ground points, being used for DTM generation afterward. The proposed approach was applied to many real airborne LIDAR data sets. The analysis on the results strongly supports the prominent performance of the proposed approach in terms of not only the computational requirement but also the quality of the DTM.
우리별 1호 지구 관측 영상의 방사학적 및 기하학적 보정
이임평 ( Im Pyeong Lee ),김태정 ( Tae Jung Kim ) 大韓遠隔探査學會 1996 大韓遠隔探査學會誌 Vol.12 No.1
CCD 지구 영상 실험 장치(CCD Earth Image Experiment, CEIE)는 우리별 1호의 주 탑재체중의 하나이다. 우리별 1호가 발사된 후에 CEIE는 이제까지 약 500여장의 세계 곳곳의 지표면 영상을 촬영하였다. 내재한 방사학적 (radiometric) 오차 및 기하학적 (geometric) 찌그러짐으로 인해, 관측된 영상은 지표면의 모습과 아주 다르다. 관측된 영상을 다양한 목적의 응용을 위해 처리하고 분석하기 전에 이러한 오차를 제거하기 위한 전처리 과정을 반드시 수행하여야 한다. 이 논문은 우리별 1호가 관측한 영상에 방사학적 및 기하학적 보정을 수행하는 전처리 과정을 설명한다. The CCD Earth Image Experiment(CEIE) is one of the main payload of the KITSAT-l. Since it was launched on Oct. 10, 1992, the CEIE has taken more than 500 images on the Earth surface world-wide so far. An image from the space is very different from a feature on the real Earth surface due to various radiometric and geometric distortions. Preprocessing to remove those distortions has to take place before the image data are processed and analyzed further for various applications. This paper describes the procedure to perform preprocessing including radiometric and geometric correction.
Pseudogulbenkiania gefcensis sp. nov., isolated from soil.
Lee, Dong-Geol,Im, Dong-Moon,Kang, HeeCheol,Yun, Pyeong,Park, Sun-Ki,Hyun, Seung-Su,Hwang, Dong-Youn Society for General Microbiology 2013 International journal of systematic and evolutiona Vol.63 No.1
<P>A novel strain, yH16, was isolated on nutrient agar from soil samples collected at KyungHee University, Suwon City, Republic of Korea. Cells of strain yH16(T) were short rods, Gram-negative-staining, motile and non-spore-forming, with a polar flagellum. Biochemical and molecular characterization revealed that this strain was most similar to Pseudogulbenkiania subflava BP-5(T). Further 16S rRNA gene sequencing studies revealed that the new strain clustered with Pseudogulbenkiania subflava BP-5(T) (95.9 % similarity), Paludibacterium yongneupense 5YN8-15(T) (95.2 % similarity), Gulbenkiania mobilis E4FC31-5(T) (94.6 % similarity) and Chromobacterium aquaticum CC-SE-YA-1(T) (93.9 % similarity). The isolate was able to grow at 25-40 C, 0.3-2 % NaCl and pH 5.5-7. The DNA G+C content was 65.9 1.0 mol%. The predominant fatty acids were summed feature 3 (C(16 : 1)ω7c and/or iso-C(15 : 0) 2-OH) and C(16:0). Ubiquinone 8 was the major respiratory quinone. It was evident from the data obtained that the strain should be classified as a novel species of the genus Pseudogulbenkiania. The name proposed for this taxon is Pseudogulbenkiania gefcensis sp. nov., and the type strain is yH16(T) (=KCCM 90100(T) = JCM 17850(T)).</P>
Lee, Jung Seok,Kim, Jaesung,Im, Se Pyeong,Kim, Si Won,Jung, Jae Wook,Lazarte, Jassy Mary S.,Lee, Jeong-Ho,Thompson, Kim D.,Jung, Tae Sung Elsevier 2018 Journal of immunological methods Vol.462 No.-
<P><B>Abstract</B></P> <P>Monomeric variable lymphocyte receptor B (VLRB) is one of the smallest binding scaffold (20–25 kDa) from jawless vertebrates, hagfish and lamprey. This relatively new class of binding scaffold has various advantages: i) it has a single peptide composition, amenable to molecular engineering for enhancing its stability and affinity; ii) it has a small size, contributing better tissue penetration and easier production using microorganism expression system. Monomeric arVLRB142, which can specifically bind to the glycoprotein of viral hemorrhagic septicemia virus (VHSV), was expressed in <I>Pichia pastoris</I>. High quantity recombinant monomeric arVLRB142 (rVLR142<SUP>mono</SUP>) was purified from 100 ml of culture with a resulting yield of 2.6 ±1.3 mg of target protein. Functional studies revealed that the purified rVLR142<SUP>mono</SUP> can specifically recognize low levels of the target antigen (recombinant glycoprotein) (i.e. as low as 0.1 nM), but also the native glycoprotein of VHSV. The expressed rVLR142<SUP>mono</SUP> exhibited high levels of stability and it retained it binding capacity over broad temperature (4 °C ~ 60 °C) and pH ranges (pH 1.5–12.5). We developed an effective expression system for mass production of monomeric VLRB based on <I>P. pastoris</I>. The recombinant protein that was obtained offers promising binding avidity and biophysical stability and its potential use in various biotechnological applications.</P>
Lee, Dong-Cheon,Seo, Su-Young,Lee, Im-Pyeong,Kwon, Jay-Hyoun,Tuell, Grady H. Korean Society of Surveying 2007 한국측량학회지 Vol.25 No.6
Extraction of the coastal boundary is important because the boundary serves as a reference in the demarcation of maritime zones such as territorial sea, contiguous zone, and exclusive economic zone. Accurate nautical charts also depend on well established, accurate, consistent, and current coastline delineation. However, to identify the precise location of the coastal boundary is a difficult task due to tidal and wave motions. This paper presents an efficient way to extract coastlines by applying digital image processing techniques to Synthetic Aperture Radar (SAR) imagery. Over the past few years, satellite-based SAR and high resolution airborne SAR images have become available, and SAR has been evaluated as a new mapping technology. Using remotely sensed data gives benefits in several aspects, especially SAR is largely unaffected by weather constraints, is operational at night time over a large area, and provides high contrast between water and land areas. Various image processing techniques including region growing, texture-based image segmentation, local entropy method, and refinement with image pyramid were implemented to extract the coastline in this study. Finally, the results were compared with existing coastline data derived from aerial photographs.