• Title/Summary/Keyword: Yi Soyeon

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Is Yi Soyeon an astronaut or a space tourist? : The First Korean Astronaut Debate on the view of ANT (이소연은 우주인인가 관광객인가? : ANT의 관점으로 본 한국최초우주인 논쟁)

  • An, Hyoung-Joon
    • Journal of Science and Technology Studies
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    • v.9 no.1
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    • pp.89-127
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    • 2009
  • The Korean Astronaut Project(KAP) aims to make the first Korean astronaut fly and take part in space activities in the International Space Station(ISS) in April 2008. KAP was on the purpose of studying the requirement to master manned space technologies as part of the long-term basic plan for national space development. However, people criticized that Ms. Yi was a 'space tourist' not an 'astronaut' because KAP was a program for pride, prestige in 21c's new space race, not specifically science and technology. The government emphasized that Yi carried out her 15 experiments in ISS very competently. In contrast people devaluated Yi's space experiments as below the level, though some of them are enough meaningful to be published on SCI journals. Why did the government fail to make people take Ms. Yi as an astronaut? I answer to this question using the notion of "Network Analysis" based on Actor-Network Theory(ANT).

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Micro Cell Counter Using a Fixed Control Volume Between Double Electrical Sensing Zones (다수의 계수구역간의 검사체적을 이용한 소형 세포농도센서)

  • Lee Dong Woo;Yi Soyeon;Cho Young-Ho
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.12 s.243
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    • pp.1615-1620
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    • 2005
  • We present a novel flow-rate independent cell counter using a fixed control volume between double electrical sensing zones. The previous device based on the single electrical cell sensing in a given flow-rate requires an accurate fluid volume measurement or precision flow rate control. The present cell counter, however, offers the flow-rate independent method for the cell concentration measurement with counting cells in a fixed control volume of $22.9{\pm}0.98{\mu}{\ell}$. In the experimental study, using the RBC (Red Blood Cell), we have compared the measured RBC concentrations from the fabricated devices with those from Hemacytometer. The previous and present devices show the maximum errors of $20.3\%\;and\;16.1\%$, which are in the measurement error range of Hemacytometer (about $20\%$). The present device also shows the flow-rate independent performance at the constant flow-rates ($5{\mu}{\ell}/min$ and $10{\mu}{\ell}/min$) and the varying flow-rate (4, 2, and $4{\mu}{\ell}/min$). Therefore, we demonstrate that the present cell counter is a simple and automated method for the cell concentration measurement without requiring an accurate fluid measurement and precision flow-rate control.

A DNA Microextractor Using Crossed Field Electrophoresis (교차 전기영동법을 이용한 극소형 DNA 추출기)

  • Yi Soyeon;Seo Kyoung-Sun;Cho Young-Ho
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.8 s.227
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    • pp.1135-1139
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    • 2004
  • This paper presents a microextractor for the separation of DNA molecules by their sizes. The DNA microextractor immobilizes the DNA molecules of specific size in the micropillar array by adjusting the period of the crossed electric field, thus providing a starting-point independent target DNA extraction method without separation process monitoring. The DNA microextractor has been fabricated by a three-mask micromachining process. The velocity of three different DNA molecules has been measured at the electric field of E=5V/0.8cm in the fabricated DNA microextractor, resulting in the reorientation times of $4.80{\pm}0.44sec,\;7.12{\pm}0.75sec$, and $9.88{\pm}0.30sec$ for ${\lambda}$ DNA, micrococcus DNA, and T4 DNA, respectively. T4 DNA is trapped in the micropillar array when the crossed electric field of 5V/0.8cm is applied alternately at a 10 second time interval. The present DNA microextractor filters the DNA in a specific size range by adjusting the magnitude and/or the period of the crossed electric field applied in the micropillar array.

Glucose-dependent insulinotropic polypeptide (GIP) alleviates ferroptosis in aging-induced brain damage through the Epac/Rap1 signaling pathway

  • Jiwon Ko;Soyoung Jang;Soyeon Jang;Song Park;Junkoo Yi;Dong Kyu Choi;Seonggon Kim;Myoung Ok Kim;Su-Geun Lim;Zae Young Ryoo
    • BMB Reports
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    • v.57 no.9
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    • pp.417-423
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    • 2024
  • Glucose-dependent insulinotropic polypeptide (GIP), a 42-amino-acid hormone, exerts multifaceted effects in physiology, most notably in metabolism, obesity, and inflammation. Its significance extends to neuroprotection, promoting neuronal proliferation, maintaining physiological homeostasis, and inhibiting cell death, all of which play a crucial role in the context of neurodegenerative diseases. Through intricate signaling pathways involving its cognate receptor (GIPR), a member of the G protein-coupled receptors, GIP maintains cellular homeostasis and regulates a defense system against ferroptosis, an essential process in aging. Our study, utilizing GIP-overexpressing mice and in vitro cell model, elucidates the pivotal role of GIP in preserving neuronal integrity and combating age-related damage, primarily through the Epac/Rap1 pathway. These findings shed light on the potential of GIP as a therapeutic target for the pathogenesis of ferroptosis in neurodegenerative diseases and aging.

Detection of Marine Oil Spills from PlanetScope Images Using DeepLabV3+ Model (DeepLabV3+ 모델을 이용한 PlanetScope 영상의 해상 유출유 탐지)

  • Kang, Jonggu;Youn, Youjeong;Kim, Geunah;Park, Ganghyun;Choi, Soyeon;Yang, Chan-Su;Yi, Jonghyuk;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.38 no.6_2
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    • pp.1623-1631
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    • 2022
  • Since oil spills can be a significant threat to the marine ecosystem, it is necessary to obtain information on the current contamination status quickly to minimize the damage. Satellite-based detection of marine oil spills has the advantage of spatiotemporal coverage because it can monitor a wide area compared to aircraft. Due to the recent development of computer vision and deep learning, marine oil spill detection can also be facilitated by deep learning. Unlike the existing studies based on Synthetic Aperture Radar (SAR) images, we conducted a deep learning modeling using PlanetScope optical satellite images. The blind test of the DeepLabV3+ model for oil spill detection showed the performance statistics with an accuracy of 0.885, a precision of 0.888, a recall of 0.886, an F1-score of 0.883, and a Mean Intersection over Union (mIOU) of 0.793.