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TiO2-MMT를 이용한 디젤오염 철도토양의 개선방안에 관한 연구
양영민(Youngmin Yang),허현수(Hyun Sue Huh),이재영(Jae-Young Lee),이철규(Cheul-Kyu Lee),전유미(Yumi Jeon) 한국철도학회 2011 한국철도학회 학술발표대회논문집 Vol.2011 No.10
Soil pollution around railroad has been occurred mainly by diesel and lubricant oil which is difficult to treat due to high carbon number. In this study we investigated the feasibility of inorganic-inorganic nanohybrid photo-catalyst for the remediation of diesel-contaminated railroad soil. Generally the TiO2 nanoparticle easily removes organic pollutants due to photo and natural clay of layer structure. Also montmorillonite (MMT) have an excellent absorption property with organic component. So we prepared TiO2 pillared MMT nanohybrid photo-catalyst as a chemical oxidant through the integration of theses advantage. As a result the removal efficiency of diesel was more than 45% at a laboratory-scale test with diesel concentration and the amount of TiO2-MMT. In future we will improve the removal efficiency of diesel to optimize experimental parameters and apply the field soil The remediation method using photo-catalyst can be used to clean up the railroad soil polluted with high concentration instead of common methods such as soil washing bioremediation etc..
Alterations in Social Brain Network Topology at Rest in Children With Autism Spectrum Disorder
Narae Yoon,Youngmin Huh,Hyekyoung Lee,Johanna Inhyang Kim,Jung Lee,Chan-Mo Yang,Soomin Jang,Yebin D. Ahn,Mee Rim Oh,Dong Soo Lee,Hyejin Kang,Bung-Nyun Kim 대한신경정신의학회 2022 PSYCHIATRY INVESTIGATION Vol.19 No.12
Objective Underconnectivity in the resting brain is not consistent in autism spectrum disorder (ASD). However, it is known that the functional connectivity of the default mode network is mainly decreased in childhood ASD. This study investigated the brain network topology as the changes in the connection strength and network efficiency in childhood ASD, including the early developmental stages. Methods In this study, 31 ASD children aged 2–11 years were compared with 31 age and sex-matched children showing typical development. We explored the functional connectivity based on graph filtration by assessing the single linkage distance and global and nodal efficiencies using resting-state functional magnetic resonance imaging. The relationship between functional connectivity and clinical scores was also analyzed. Results Underconnectivities within the posterior default mode network subregions and between the inferior parietal lobule and inferior frontal/superior temporal regions were observed in the ASD group. These areas significantly correlated with the clinical phenotypes. The global, local, and nodal network efficiencies were lower in children with ASD than in those with typical development. In the preschool-age children (2–6 years) with ASD, the anterior-posterior connectivity of the default mode network and cerebellar connectivity were reduced. Conclusion The observed topological reorganization, underconnectivity, and disrupted efficiency in the default mode network subregions and social function-related regions could be significant biomarkers of childhood ASD.
Jang, Yujin,Huh, Jinbum,Lee, Namhun,Lee, Seungsoo,Park, Youngmin The Korean Society for Aeronautical Space Sciences 2018 International Journal of Aeronautical and Space Sc Vol.19 No.1
The RANS equations are widely used to analyze complex flows over aircraft. The equations require a turbulence model for turbulent flow analyses. A suitable turbulence must be selected for accurate predictions of aircraft aerodynamic characteristics. In this study, numerical analyses of three-dimensional aircraft are performed to compare the results of various turbulence models for the prediction of aircraft aerodynamic characteristics. A 3-D RANS solver, MSAPv, is used for the aerodynamic analysis. The four turbulence models compared are the Sparlart-Allmaras (SA) model, Coakley's $q-{\omega}$ model, Huang and Coakley's $k-{\varepsilon}$ model, and Menter's $k-{\omega}$ SST model. Four aircrafts are considered: an ARA-M100, DLR-F6 wing-body, DLR-F6 wing-body-nacelle-pylon from the second drag prediction workshop, and a high wing aircraft with nacelles. The CFD results are compared with experimental data and other published computational results. The details of separation patterns, shock positions, and $C_p$ distributions are discussed to find the characteristics of the turbulence models.