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Template-assisted Morphological Evolution of Cu2S and Cu2MoS4 from Octahedral Cu2O Crystals
장민경,조영식,박가람,오인환,허영덕 대한화학회 2018 Bulletin of the Korean Chemical Society Vol.39 No.11
Various morphologies of Cu2S and Cu2MoS4 were synthesized from an octahedral Cu2O template in the presence of various concentrations of sodium molybdate and thioacetamide by carrying out solvothermal reactions in an ethylene glycol solvent. The morphology varied from hollow octahedral Cu2S structures, through small pieces of P-Cu2MoS4, and finally to thin square-like plates of I-Cu2MoS4, depending on the concentrations of sodium molybdate and thioacetamide. The XRD data indicated that the Cu2MoS4 structural phases changed from P2m to I2m the concentrations of sodium molybdate and thioacetamide increased.
갈파래(Ulva lactuca) 추출분획의 암 세포주에 대한 세포독성 및 면역활성 효과
장민경,김남영,이동근,이재화,하종명,하배진,김미향,배송자,장정수,이상현,Jang, Min-Kyung,Kim, Nam-Young,Lee, Dong-Geun,Lee, Jae-Hwa,Ha, Jong-Myung,Ha, Bae-Jin,Kim, Mi-Hyang,Bae, Song-Ja,Jang, Jeong-Su,Lee, Sang-Hyeon 한국생명과학회 2006 생명과학회지 Vol.16 No.7
본 연구는 갈파래(Ulva lactuca) 추출분획의 암세포주에 대한 세포독성 및 면역활성 효과를 조사하였다. 갈파래의 에탄올 추출물로부터 분획물의 제조는 hexane, ethyl ether, methanol, butanol, $H_2O$의 용매를 이용하여 행하였다. 인간 백혈암세포주(U937), 생쥐 신경아종세포주(NB41A3), 인체간암세포주(HepG2),큰지 신경교세포주(C6) 등에 대한 갈파래 분획물의 세포독성을 측정하였다. 갈파래의 Ethyl ether 층은 4종류의 세포 모두에서 가장 높은 세포독성을 나타냈다. 또한 수층 역시 비교적 높은 세포독성을 나타냈다. 4종류의 세포 모두에서 농도의존적 경향을 나타냈다. 갈파래 분획물의 큰쥐 대식세포주(RAW 264.7)에 대한 면역활성 효과도 조사하였다. 갈파래 추출물의 5가지 분획물 모두에서 농도의존적으로 NO 생산을 활성화시켰다. 이러한 결과들로 잔파래가 항암 덴 면역활성을 나타내는 천연 소재개발에 있어 유용한 후보가 될 수 있을 것으로 사료된다. Extracted fractions of the green seaweed Ulva lactuca were studied to verify the cytotoxicity and immunostimulating activity. The fractions from the ethanol extract of U. lactuca were prepared by the systematic extraction procedure with solvents such as hexane, ethyl ether, methanol, butanol and $H_2O$. The cytotoxic effects of U. lactuca fractions against human leukemia cell line U937, mouse neuroblastoma cell line (NB41A3), human hepatoma cell line (HepG2) and rat glioma cell line (C6) were investigated. Ethyl ether fraction showed the highest cytotoxicity against all four cell lines tested. In addition, $H_2O$ fraction also showed relatively high cytotoxicity. Dose dependent patterns were observed on all four cell lines. The immune-stimulating effects of U. lactuca fractions on rat macrophage cell line (RAW 264.7) were also investigated. All five fractions of U. lactuca extract stimulated NO production with concentration dependant manner. These results suggest that U. lactuca may be a useful candidate for a natural cancer preventing and immune-stimulating agents.
GD-MS 분석 장비를 활용한 극미량 무기물 질량 분석을 위한 표준RSF 구축 및 응용
장민경,양재열,이종현,윤재식 한국분석과학회 2018 분석과학 Vol.31 No.6
The present study analyzed standard samples of three types of aluminum matrix certified reference materials (CRM) using GD-MS. Calibration curves were constructed for 13 elements (Mg, Si, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ga, Sn, and Pb), with the slope representing the relative sensitivity factor (RSF). The x- and y-axes of the calibration curve represented ion beam ratio (IBR) and the authenticated value of the standard sample, respectively. In order to evaluate precision and linearity of the calibration curve, RSD and the coefficient of determination were calculated. Curve RSD for every element reflected high precision (within 10 %). For most elements, the coefficient of determination was ≥ 0.99, indicating excellent linearity. However, vanadium, nickel, and gallium curves exhibited relatively low linearity (0.90~0.95), likely due to their narrow concentration ranges. Standard RSF was calculated using the slope of the curve generated for three types of CRM. Despite vanadium, nickel, and gallium exhibiting low coefficients of determination, their standard RSF resembled that of the three types of CRM. Therefore, the RSF method may be used for element quantitation. Standard iron matrix samples were analyzed to verify the applicability of the aluminum matrix standard RSF, as well as to calculate the RSD-estimated error of the measured value relative to the actual standard value. Six elements (Al, Si, V, Cr, Mn, and Ni) exhibited an RSD of approximately 30 %, while the RSD of Cu was 77 %. In general, Cu isotopes are subject to interference: 63Cu to 54Fe2+-36Ar and 65Cu to 56Fe-Al3+ interference. Thus, the influence of these impurities may have contributed to the high RSD value observed for Cu. To reliably identify copper, the resolution should be set at ≥8000. However, high resolutions are inappropriate for analyzing trace elements, as it lowers ion permeability. In conclusion, quantitation of even relatively low amounts of six elements (Al, Si, V, Cr, Mn, and Ni) is possible using this method.
Pre-service Teachers' Education Needs for AI-Based Education Competency
장민경,이현우 한국교육공학회 2023 Educational Technology International Vol.24 No.2
This study aims to analyze the perceptions and educational needs of pre-service teachers for the use of Artificial Intelligence (AI) in education. To this end, we collected survey data from 25 undergraduate students who were enrolled in a teacher education college in Seoul. The purpose of the survey was to measure the importance and current performance for instructional AI use based on the technological, pedagogical, and content knowledge (TPACK) framework, and to explore the priority of educational needs using Borich's needs analysis and the Locus for Focus model. The results of the study confirmed that Ethics and TPK competencies are prioritized. Additionally, the results indicated a high demand for practical knowledge that can be implemented in the practice of education. Based on the results, it is necessary to develop a teacher education program that focuses on ethical aspects and teaching strategy competencies in AI-based education.
이동로봇의 안전한 엘리베이터 탑승을 위한 RGB-D 센서 기반의 엘리베이터 인식 및 위치추정
장민경,조현준,송재복 한국로봇학회 2020 로봇학회 논문지 Vol.15 No.1
Multi-floor navigation of a mobile robot requires a technology that allows the robot to safely get on and off the elevator. Therefore, in this study, we propose a method of recognizing the elevator from the current position of the robot and estimating the location of the elevator locally so that the robot can safely get on the elevator regardless of the accumulated position error during autonomous navigation. The proposed method uses a deep learning-based image classifier to identify the elevator from the image information obtained from the RGB-D sensor and extract the boundary points between the elevator and the surrounding wall from the point cloud. This enables the robot to estimate the reliable position in real time and boarding direction for general elevators. Various experiments exhibit the effectiveness and accuracy of the proposed method.