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Chung, Jae-Uk,Kim, Su Yeon,Lim, Ju-Ok,Choi, Hyun-Kyung,Kang, Sang-Uk,Yoon, Hae-Seok,Ryu, HyungChul,Kang, Dong Wook,Lee, Jeewoo,Kang, Bomi,Choi, Sun,Toth, Attila,Pearce, Larry V.,Pavlyukovets, Vladimir 이화여자대학교 약학연구소 2008 藥學硏究論文集 Vol.- No.18
A series of α-substituted N-(4-tert-butylbenzyl)-N-[4-(methylsulfonylamino)benzyl]thiourea analogues have been investigated as TRPVl receptor antagonists. α-Methyl substituted analogues showed potent and stereospecific antagonism to the action of capsaicin on rat TRPVl heterologously expressed in Chinese hamster ovary cells, In particular, compounds 14 and 18, which possess the R-configuration, exhibited excellent potencies (respectively, K_(i) = 41 and 39.2 nM and K_(i(ant)) = 4.5 and 37 nM).
김현철(Hyungchul Kim),강우(Woo Kang),나병철(Byungchul Na),정재우(Jaewoo Chung),김명환(Myunghwan Kim) 한국자동차공학회 2005 한국자동차공학회 춘 추계 학술대회 논문집 Vol.2005 No.11_1
In order to confront the increasing air pollution and the tightening emission restrictions, the interest on DME has been dramatically increased resulting researches on DME in many nations. In this research, to study the spray, combustion, and emission characteristics of the DME engine, 3D CAD file was constructed using a 3D measurement machine. Using the obtained geometry, fine moving meshes are generated, and three dimensional non-steady turbulence flow field and combustion phenomenon including spray were numerically analyzed for exhaust gas prediction of the engine using DME, the advanced smoke-free alternative fuel. Therefore it was found that the advanced combustion modeling of DME engine and fuel amount need to be properly adjusted through matching the characteristics of DME fuel and combustion for further improvement.
Liu Yiping,Chen Tiantian,Chung Hyungchul,Jang Kitae 대한교통학회 2024 대한교통학회 학술대회지 Vol.90 No.-
Urban traffic accidents are closely related to street characteristics, and investigating this relationship is crucial for enhancing traffic safety. Street-level features primarily include the built environment elements that makes up the streets, such as greenery, sky, and other elements. As users of urban street spaces, travelers perception indicators of various streets also include subjective perspectives describing the differential characteristics among urban streets. Therefore, this study focuses on exploring the impact of the street built-environment and travelers perception indicators on the crash frequencies. The modeling process considers severity levels related to traffic crashes and then extends analysis to geospatial dimension to account for the spatial heterogeneity and correlation of coefficients. The study uses 587 road segments in the central area of Daejeon in Korea, with traffic crash data from the full year of 2019. All crashes are classified into killed/severe injury (KSI) and slight injury. Street built-environment elements are extracted from the street view images of the studied road sections using semantic segmentation technology, while street perception indicators are scored using deep learning methods based on the street view images, outputting results in six perceptual dimensions to create related variables. In addition, the impact of traffic variables such as AADT and road geometry (number of lanes, speed limits, etc.) is considered. The results suggest significant correlations among street built-environment, travelers perception indicators and the frequency of traffic crashes, with different trends of impact for various crash classification. The estimation results of coefficients also show variations in the spatial influence of different feature, which could help traffic authorities identify high-risk areas and understand contributing factors, thereby taking precaution actions.