http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
전세훈,김의성,전원진,홍수린,최인희,신치범,이종협 한국고분자학회 2009 Macromolecular Research Vol.17 No.3
Recently, the multi-screening of target materials has been made possible by the development of the surface plasmon resonance (SPR) imaging method. To adapt this method to biochemical analysis, the multi-patterning technology of protein microarrays is required. Among the different methods of fabricating protein microarrays, the microfluidic platform was selected due to its various advantages over other techniques. Microfluidic devices were designed and fabricated with polydimethylsiloxane (PDMS) by the replica molding method. These devices were designed to operate using only capillary force, without the need for additional flow control equipment. With these devices, multiple protein-patterned sensor surfaces were made, to support the two-dimensional detection of various protein-protein interactions with SPR. The fabrication technique of protein microarrays can be applied not only to SPR imaging, but also to other biochemical analyses.
Urea-Driven Conformational Changes in Surface-Bound Superoxide Dismutase
이종협,최인희,강태욱,홍수린,Jung-Joon Sung 대한화학회 2008 Bulletin of the Korean Chemical Society Vol.29 No.8
Both surface plasmon resonance (SPR) spectroscopy and atomic force microscopy (AFM) have been used to observe the change in Cu/Zn superoxide dismutase (SOD1) tethered to a Au film upon urea-induced denaturation. Exposure to a urea solution causes denaturation of SOD1, which shifts the minimum in the SPR curve to a larger angle without any change in reflectivity at the resonant angle (θSPR) for different urea concentrations. The differential reflectivity at θSPR (Δ(Rmin/Ro)) increases sigmoidally as a function of urea concentration becoming saturated at concentrations above 4 M. With the assumption of a two-state model for the denaturation of SOD1, the Gibbs free energy change for the denaturation of SOD1 on the Au surface is estimated to be ΔGo = 1.8 ± 0.7 kcal/mol, which is lower by approximately one order of magnitude than that of SOD1 in the bulk solution. The immobilized SOD1 on the Au surface can be reversibly denatured and renatured. Consistent with calculations based on Fresnel equations for a multilayer system, liquid-AFM images show that upon denaturation, the thickness of the tethered SOD1 increases by ca. 2.0 times. Thus, SOD1 on the Au film tries to stretch its polypeptide chain in the vertical direction on unfolding.
박천음(Cheoneum Park),이창기(Changki Lee),홍수린(Sulyn Hong),황이규(Yigyu Hwang),유태준(Taejoon Yoo),김현기(Hyunki Kim) 한국정보과학회 2018 정보과학회논문지 Vol.45 No.12
기계 독해는 주어진 문맥을 이해하고, 질문에 적합한 답을 문맥 내에서 찾는 문제이다. Simple Recurrent Unit (SRU)은 GRU 등과 같이 neural gate를 이용하여 RNN에서 발생하는 베니싱 그래디언트 문제를 해결하고, gate 입력에서 이전 hidden state를 제거하여 GRU보다 속도를 향상시킨 모델이며, Self-matching Network는 R-Net 모델에서 사용된 것으로, 자기 자신의 RNN sequence에 대하여 어텐션 가중치를 계산하여 비슷한 의미 문맥 정보를 볼 수 있기 때문에 상호참조해결과 유사한 효과를 볼 수 있다. 본 논문에서는 한국어 기계 독해 데이터 셋을 구축하고, 여러 층의 SRU를 이용한 Encoder에 Self-matching layer를 추가한 S2-Net 모델을 제안한다. 실험 결과, 본 논문에서 제안한 S²-Net 모델이 한국어 기계 독해 데이터 셋에서 EM 70.81%, F1 82.48%의 성능을 보였다. Machine reading comprehension is the task of understanding a given context and identifying the right answer in context. Simple recurrent unit (SRU) solves the vanishing gradient problem in recurrent neural network (RNN) by using neural gate such as gated recurrent unit (GRU), and removes previous hidden state from gate input to improve speed. Self-matching network is used in r-net, and this has a similar effect as coreference resolution can show similar semantic context information by calculating attention weight for its RNN sequence. In this paper, we propose a S²-Net model that add self-matching layer to an encoder using stacked SRUs and constructs a Korean machine reading comprehension dataset. Experimental results reveal the proposed S²-Net model has EM 70.81% and F1 82.48% performance in Korean machine reading comprehension.