59 research outputs found

    The approach of Healthcare Infrastructure Public-Private Partnership (PPP) in Developing Countries: for the equal good to Korea Interest Group and the Recipient Country

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    Over the past decade, Public-Private Partnerships (PPPs) have increasingly found their application in the sector of health infrastructure. The objective of this paper is to determine whether PPPs are a viable option for health infrastructure projects in developing countries. For this purpose, the author discusses and describes PPPs in general and specifies features of PPPs, which may be relevant for the healthcare sector and developing countries. In the next step, the author analyses PPP projects that are operating and projects that the author had involved and establishes key learnings from the undertaking. The combined evidence suggests that the PPP model for health infrastructure projects in developing countries can be highly risky for the countries, but also it possesses great insecurity for the participant entities. The author concludes PPP is not a better alternative to ODA in health infrastructure development in developing countries, but it should be an option. Also, the author suggests three conditions, those are prioritizing countries to build partnerships, secure evidence of partner countryโ€™s commitment, testify project design through multiple steps for both the public and the private to successfully use PPP for better health delivery.open์„

    Analysis of Random Telegraph Noise after Soft Breakdown in the Gate Induced Drain Leakage Current

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2013. 8. ์‹ ํ˜•์ฒ .A Random Telegraph Noise (RTN) in leakage current has been important for discovering the cause of Variable Retention Time (VRT) in Dynamic Random Access Memory (DRAM) cell transistor. Among the several leakage currents, random telegraph noise in Gate Induced Drain Leakage (GIDL) current of a Metal Oxide Semiconductor Field Effect Transistor (MOSFET) is believed as the dominant cause of the VRT. Furthermore, the Soft Breakdown (SBD) has long been one of the main issues of the reliability of MOS transistor when the gate oxide layer is thinner than 4-5 nm. After the SBD occurs, the leakage current suddenly jumps without obvious indication of steps as the stress continues. If the gate tunneling current gradually increases to a certain point, then it will become high enough to cease the circuit to function. There have been many analyses about RTN in gate current after SBD, whereas there is few about RTN in GIDL current. Therefore, there is a need to study RTN in GIDL current after SBD. In this paper, Intrinsic two-level RTN in Gate Induced Drain Leakage (GIDL) RTN in GIDL current after the Soft BreakDown (SBD) by Constant Voltage Stress (CVS) in the gate-drain overlapped region was measured. In order to conduct comparative analysis, we extracted fundamental parameters of the trap, including the time constant, the trap location (xT) and the energy level (ECox-ET), the capture cross section (ฯƒc) from the measured RTN. After the first SBD, as the stress is continually given, multi-level GIDL RTN was also observed. As a result, we could predict the gate oxide degradation due to the SBD by observing the GIDL RTN after SBD.Abstract i Contents iii 1. Introduction 1 2. Extraction of Location and Energy Level of Oxide Trap Generated after Soft Breakdown 4 2. 1 Introduction 4 2. 2 Experimetnal 6 2. 3 Model 7 2. 4 Result and Discussion 16 2. 5 Conclusion 28 3. New Equation of Capture Cross Section Involving Tunneling Analysis 30 3. 1 Introduction 30 3. 2 Model and Discussion 31 3. 3 Conclustion 36 4 Conclusion 37 References 39 Abstract in Korean 43Maste

    ๋ฌธํ™”์žฌ ๊ด€๋ฆฌ์— ๋Œ€ํ•œ ์ธ์ง€๋œ ์„ฑ๊ณผ์™€ ๋งŒ์กฑ๋„์— ๊ด€ํ•œ ์—ฐ๊ตฌ: ์„œ๋น„์Šค ๊ฐ€์น˜์ธ์‹์˜ ์กฐ์ ˆํšจ๊ณผ๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ํ–‰์ •๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ํ–‰์ •ํ•™๊ณผ ์ •์ฑ…ํ•™ ์ „๊ณต, 2016. 2. ๊ธˆํ˜„์„ญ.๋ณธ ์—ฐ๊ตฌ์˜ ๋ชฉ์ ์€ ๋ฌธํ™”์žฌ์— ๋Œ€ํ•œ ์„ฑ๊ณผ์ธ์‹๊ณผ ๋งŒ์กฑ๋„๊ฐ„์˜ ๊ด€๊ณ„๋ฅผ ์‹ค์ฆ์ ์œผ๋กœ ๋ถ„์„ํ•˜๋Š”๋ฐ ์žˆ๋‹ค. ํŠนํžˆ ์ด๋“ค ๊ด€๊ณ„๊ฐ€ ํ–ฅ์œ ์ž๋“ค์ด ์ธ์‹ํ•˜๋Š” ๋ฌธํ™”์žฌ์˜ ๊ฐ€์น˜, ์ฆ‰ ๋ฌธํ™”์žฌ ๊ด€๋ฆฌ๋ฅผ ํ†ตํ•ด ์ œ๊ณต๋˜๋Š” ์„œ๋น„์Šค์˜ ๊ฐ€์น˜๋ฅผ ๊ณ ๋ คํ–ˆ์„ ๋•Œ ์–ด๋–ป๊ฒŒ ๋‹ฌ๋ผ์ง€๋Š”์ง€ ์‚ดํŽด๋ณด๊ณ ์ž ํ•œ๋‹ค. ์ง€๊ธˆ๊นŒ์ง€ ๋ฌธํ™”์žฌ ์ •์ฑ…์€ ์›ํ˜•๋ณด์กด์— ์ง‘์ค‘ํ•˜๋ฉด์„œ ๋ฌธํ™”์žฌ ์ž์ฒด๋งŒ์„ ๊ด€๋ฆฌ ๋Œ€์ƒ์œผ๋กœ ์‚ผ์•„์™”์œผ๋‚˜, ์ตœ๊ทผ ๋“ค์–ด ๋ฌธํ™”์žฌ ํ–ฅ์œ  ํŠนํžˆ, ํ–ฅ์œ ์ž ์ž…์žฅ์—์„œ์˜ ๋ฌธํ™”์žฌ ๊ฐ€์น˜ ์ธก๋ฉด์ด ๋ถ€๊ฐ๋˜๋ฉด์„œ ๊ทธ๋“ค์˜ ๋งŒ์กฑ์ด ๋ฌธํ™”์žฌ ๊ด€๋ฆฌ์˜ ์ค‘์š”ํ•œ ๋Œ€์ƒ์ด ๋˜๊ณ  ์žˆ๋‹ค. ๋ฌธํ™”์žฌ ํ–ฅ์œ ์— ๋”ฐ๋ฅธ ๋งŒ์กฑ๋„๊ฐ€ ๋†’์„์ˆ˜๋ก ๋ฌธํ™”์žฌ ๋ณด์กด ๋ฐ ๊ฐœ๋ฐœ์— ๋Œ€ํ•œ ์• ์ฐฉ์ด ํ˜•์„ฑ๋˜๊ณ  ์ด๋ฅผ ํ†ตํ•ด ๋ฌธํ™”์žฌ ๊ด€๋ฆฌ ์ •์ฑ…์— ๋Œ€ํ•œ ์ˆ˜์šฉ์„ฑ ์ œ๊ณ  ๋ฐ ๋ฌธํ™”์žฌ ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•œ ์ž๋ฐœ์  ๋…ธ๋ ฅ์ด ์œ ๋„๋  ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ํ•˜์ง€๋งŒ ์ด๋Ÿฌํ•œ ์ธ์‹์˜ ์ „ํ™˜์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์‹ค์ œ ๋ฌธํ™”์žฌ ํ–ฅ์œ ์™€ ๊ด€๋ จํ•œ ํ•™์ˆ ์ ยท์ •์ฑ…์  ๋…ผ์˜๋Š” ํ–ฅ์œ ๊ธฐํšŒ์˜ ํ™•๋Œ€์™€ ๊ฐ™์€ ์–‘์ ์ธ ์ธก๋ฉด์— ๊ฒฝ์‚ฌ๋˜๋Š” ๊ฒฝํ–ฅ์ด ์ง™๋‹ค. ๋”์šฑ์ด ์„œ๋น„์Šค์— ๋Œ€ํ•œ ๋งŒ์กฑ ์—ฌ๋ถ€์™€ ๊ทธ ์ˆ˜์ค€์€ ์†Œ๋น„์ž๊ฐ€ ํ•ด๋‹น ์„œ๋น„์Šค์— ๋ถ€์—ฌํ•˜๋Š” ๊ฐ€์น˜์ธ์‹์— ๋”ฐ๋ผ ๋‹ฌ๋ผ์งˆ ์ˆ˜ ์žˆ์Œ์€ ๊ธฐ์กด ๊ฒฝ์˜ํ•™ ๋“ฑ ๋‹ค๋ฅธ ํ•™๋ฌธ๋ถ„์•ผ์—์„œ ์ผ๋ฐ˜์ ์ด๋ผ๋Š” ์ ์— ์ฐฉ์•ˆํ•ด ๋ณธ ์—ฐ๊ตฌ๋Š” ๋ฌธํ™”์žฌ ํ–ฅ์œ ์ž๋“ค์ด ์ธ์‹ํ•˜๋Š” ๋ฌธํ™”์žฌ์˜ ๊ฐ€์น˜๋ฅผ ๋ช…์‹œ์ ์œผ๋กœ ๊ณ ๋ คํ•จ์œผ๋กœ์จ ๋ฌธํ™”์žฌ ํ–ฅ์œ  ๋งŒ์กฑ์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ์ œ๊ณ ํ•˜๊ณ ์ž ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๋ฌธํ™”์žฌ์ฒญ์—์„œ ์‹ค์‹œํ•œ ใ€Œ2010 ๋ฌธํ™”์œ ์‚ฐ ํ–ฅ์œ ์‹คํƒœ ์กฐ์‚ฌใ€ ์ž๋ฃŒ๋ฅผ ๋ถ„์„ํ•˜์˜€์œผ๋ฉฐ, ๋ฌธํ™”์žฌ์— ๋Œ€ํ•ด ๊ฐœ์ธ์ด ๋ถ€์—ฌํ•˜๋Š” ๊ฐ€์น˜๋ฅผ ๋ฐฐ์›€์˜ ๊ณต๊ฐ„, ์ •์ฒด์„ฑ ํ™•์ธ ๊ณต๊ฐ„, ๊ทธ๋ฆฌ๊ณ  ๊ด€๊ด‘ ๋ฐ ํœด์‹๊ณต๊ฐ„์œผ๋กœ ๊ตฌ๋ถ„ํ•˜๊ณ  ์ด์— ๋”ฐ๋ผ ๋‹ค์–‘ํ•œ ์ฐจ์›์˜ ๋งŒ์กฑ๋„ ์ˆ˜์ค€์„ ๊ฒ€ํ† ํ•˜์˜€๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ ์„œ๋น„์Šค ์ „๋‹ฌ ์ฐจ์›์˜ ๋งŒ์กฑ ์ˆ˜์ค€์€ ๋ฌธํ™”์žฌ๋ฅผ ๋ฐฐ์›€์˜ ๊ณต๊ฐ„์œผ๋กœ ์ธ์‹ํ•˜๋Š” ์‚ฌ๋žŒ๋“ค๊ณผ ๊ตญ๊ฐ€ ์ •์ฒด์„ฑ ํ™•์ธ ๊ณต๊ฐ„์œผ๋กœ ์ธ์‹ํ•˜๋Š” ์‚ฌ๋žŒ๋“ค ์‚ฌ์ด์—์„œ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•œ ์ฐจ์ด๋ฅผ ๋ณด์ด๊ณ  ์žˆ์—ˆ๊ณ , ์šฉ์ด์„ฑ ์ฐจ์›์˜ ๋งŒ์กฑ ์ˆ˜์ค€์€ ๋ฐฐ์›€์˜ ๊ณต๊ฐ„์œผ๋กœ ์ธ์‹ํ•˜๋Š” ์‚ฌ๋žŒ๊ณผ ๊ด€๊ด‘ ๋ฐ ํœด์‹ ๊ณต๊ฐ„์œผ๋กœ ์ธ์‹ํ•˜๋Š” ์‚ฌ๋žŒ ์‚ฌ์ด์—์„œ ์œ ์˜๋ฏธํ•œ ์ฐจ์ด๊ฐ€ ๋ฐœ์ƒํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ฆ‰, ํ–ฅ์œ ์ž๋“ค์ด ๋ฌธํ™”์žฌ์— ๋Œ€ํ•ด ์–ด๋–ค ๊ฐ€์น˜๋ฅผ ๋ถ€์—ฌํ•˜๋Š”์ง€์— ๋”ฐ๋ผ ๋ฌธํ™”์žฌ ํ–ฅ์œ ์— ๋”ฐ๋ฅธ ๋งŒ์กฑ ์ˆ˜์ค€๊ณผ ์ฐจ์›์ด ๋‹ค๋ฅด๊ฒŒ ๋‚˜๊ณ  ์žˆ์Œ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค.์ œ 1 ์žฅ. ์„œ๋ก  1 ์ œ1์ ˆ ์—ฐ๊ตฌ ๋ชฉ์  ๋ฐ ํ•„์š”์„ฑ 1 ์ œ2์ ˆ ์—ฐ๊ตฌ ๋ฒ”์œ„์™€ ๋ฐฉ๋ฒ• 4 1. ์—ฐ๊ตฌ๋ฒ”์œ„ 4 2. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 5 ์ œ 2 ์žฅ. ์ด๋ก ์  ๋…ผ์˜์™€ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  6 ์ œ1์ ˆ ์ด๋ก ์  ๋…ผ์˜ 6 1. ์‹œ๋ฏผ๋งŒ์กฑ๋„ 6 1) ๊ฐœ๋… ๋ฐ ์˜์˜ 6 2) ์„ฑ๊ณผํ‰๊ฐ€ ์ˆ˜๋‹จ์œผ๋กœ์จ ๋งŒ์กฑ๋„ ์กฐ์‚ฌ์˜ ์œ ์šฉ์„ฑ 7 3) ์‹œ๋ฏผ๋งŒ์กฑ๋„ ์ธก์ • 9 2. ์ •๋ถ€์„ฑ๊ณผ 14 1) ๊ฐœ๋… 14 2) ์ •๋ถ€์„ฑ๊ณผ์— ๊ด€ํ•œ ๋…ผ์˜ 14 3) ์ •๋ถ€์„ฑ๊ณผ์˜ ์ธก์ • 17 ์ œ2์ ˆ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  18 1. ์ •๋ถ€์„ฑ๊ณผ์™€ ๋งŒ์กฑ๋„์˜ ๊ด€๊ณ„ 18 2. ์ •๋ถ€์„ฑ๊ณผ์™€ ๋งŒ์กฑ๋„ ๊ด€๊ณ„์— ์žˆ์–ด์„œ ์„œ๋น„์Šค ๊ฐ€์น˜์˜ ์—ญํ•  21 1) ๋งŒ์กฑ๋„ ์—ฐ๊ตฌ์—์„œ ๊ฐ€์น˜ ๋ณ€์ˆ˜์˜ ์—ญํ•  21 2) ๋ฌธํ™”์žฌ ๊ด€๋ฆฌ์— ์žˆ์–ด์„œ ๊ฐ€์น˜์— ๊ด€ํ•œ ๋…ผ์˜ 23 ์ œ3์ ˆ ์„ ํ–‰์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 27 ์ œ 3 ์žฅ. ์—ฐ๊ตฌ๋ฌธ์ œ์™€ ๊ฐ€์„ค 29 ์ œ1์ ˆ ์—ฐ๊ตฌ๋ฌธ์ œ 29 ์ œ2์ ˆ ์—ฐ๊ตฌ๊ฐ€์„ค 29 ์ œ 4 ์žฅ. ์—ฐ๊ตฌ์„ค๊ณ„ 32 ์ œ1์ ˆ ์—ฐ๊ตฌ์ž๋ฃŒ 32 1. ๋ถ„์„์ž๋ฃŒ : ๋ฌธํ™”์œ ์‚ฐ ํ–ฅ์œ ์‹คํƒœ์กฐ์‚ฌ 32 1) ์กฐ์‚ฌ ๊ฐœ์š” 32 2) ๋ฌธํ™”์œ ์‚ฐ ํ–ฅ์œ ์‹คํƒœ์กฐ์‚ฌ์˜ ๋‚ด์šฉ 33 2. ๋ถ„์„๋ฒ”์œ„ 33 ์ œ2์ ˆ ๋ณ€์ˆ˜์˜ ์กฐ์ž‘์  ์ •์˜ ๋ฐ ์ธก์ • 34 1. ์ข…์†๋ณ€์ˆ˜ 34 1) ์„œ๋น„์Šค ์ „๋‹ฌ 35 2) ์ •๋ณด 36 3) ์šฉ์ด์„ฑ 36 4) ์นœ์ ˆ์„ฑ 37 2. ๋…๋ฆฝ๋ณ€์ˆ˜ : ์ธ์ง€๋œ ์„ฑ๊ณผ 37 3. ์กฐ์ ˆ๋ณ€์ˆ˜ : ์„œ๋น„์Šค์— ๋Œ€ํ•œ ๊ฐ€์น˜์ธ์‹ 38 4. ํ†ต์ œ๋ณ€์ˆ˜ 38 1) ๊ฐœ์ธ์  ์š”์ธ 38 2) ์ง€์—ญ์  ์š”์ธ 39 ์ œ 5 ์žฅ. ์‹ค์ฆ๊ฒฐ๊ณผ ๋ถ„์„ 41 ์ œ1์ ˆ ์ž๋ฃŒ์˜ ๋ถ„์„๋ฐฉ๋ฒ• 41 ์ œ2์ ˆ ๊ฒฐ๊ณผ๋ถ„์„ 42 1. ๊ธฐ์ˆ ํ†ต๊ณ„๋Ÿ‰๊ณผ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ 42 1) ์ฃผ์š” ๋ณ€์ˆ˜๋“ค์˜ ๊ธฐ์ˆ ํ†ต๊ณ„ 42 2) ์„œ๋น„์Šค ๊ฐ€์น˜์ธ์‹ ๊ด€๋ จ ๊ธฐ์ˆ ํ†ต๊ณ„ 42 3) ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ 47 2. ์—ฐ๊ตฌ๊ฐ€์„ค ๊ฒ€์ฆ 48 1) ์ธ์ง€๋œ ์„ฑ๊ณผ์™€ ๋งŒ์กฑ๋„ ๊ด€๊ณ„์— ๋Œ€ํ•œ ๊ฒ€์ฆ 48 2) ์„œ๋น„์Šค ๊ฐ€์น˜์ธ์‹์˜ ์กฐ์ ˆํšจ๊ณผ์— ๋Œ€ํ•œ ๊ฒ€์ฆ 51 ์ œ 6 ์žฅ. ๊ฒฐ๋ก  60 ์ œ1์ ˆ ์—ฐ๊ตฌ๊ฒฐ๊ณผ ์š”์•ฝ 60 ์ œ2์ ˆ ์—ฐ๊ตฌ ์‹œ์‚ฌ์ ๊ณผ ํ•œ๊ณ„ 64 1. ์—ฐ๊ตฌ์˜ ์‹œ์‚ฌ์  64 2. ์—ฐ๊ตฌ์˜ ํ•œ๊ณ„ 65 ์ฐธ๊ณ ๋ฌธํ—Œ 67 ๋ถ€๋ก 78 [๋ถ€๋ก 1] ๊ฐ€์„ค 2-1 ๋ถ„์„ ๊ฒฐ๊ณผ : (์ข…์†๋ณ€์ˆ˜ : ์„œ๋น„์Šค ์ „๋‹ฌ ๋งŒ์กฑ๋„) 78 [๋ถ€๋ก 2] ๊ฐ€์„ค 2-2 ๋ถ„์„ ๊ฒฐ๊ณผ : (์ข…์†๋ณ€์ˆ˜ : ์ •๋ณด ๋งŒ์กฑ๋„) 81 [๋ถ€๋ก 3] ๊ฐ€์„ค 2-3 ๋ถ„์„ ๊ฒฐ๊ณผ : (์ข…์†๋ณ€์ˆ˜ : ์šฉ์ด์„ฑ ๋งŒ์กฑ๋„) 84 [๋ถ€๋ก 4] ๊ฐ€์„ค 2-4 ๋ถ„์„ ๊ฒฐ๊ณผ : (์ข…์†๋ณ€์ˆ˜ : ์นœ์ ˆ์„ฑ ๋งŒ์กฑ๋„) 87 Abstract 91Maste

    Corrosion Resistance of Surface and Cross Section of Al-Mg Films on Steel Sheet Prepared by PVD Method

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    Steel is one of widely used materials in various industries because of its excellent mechanical properties and low manufacturing costs. However it is highly susceptible to aggressive corrosion environments such as seawater, thus surface protection as coatings is necessary when using it properly. Aluminium coatings are used for the corrosion protection of ferrous metal for two main reasons. Firstly, aluminium, with its air-formed passive oxide film, forms an effective barrier layer against attacking materials. Secondly, if the underlying substrate is exposed at, for example, the base of pre-existing defects or corrosion pits, the aluminium coating will afford a degree of sacrificial protection to the substrate. A drawback of pure aluminium is, nevertheless, that since its corrosion potential is not far removed from that of many steels, it is unable to provide adequate levels of sacrificial protection, particularly under natural exposure conditions. If aluminium is alloyed with small amounts of active metals such as magnesium, its corrosion potential can be reduced, leading to a significant improvement in sacrificial properties. Therefore, Al-Mg alloy coating was studied and Al-Mg films using the physical vapor deposition(PVD) method that is drawing great attention as an alternative to the conventional coating process were also examined. In addition, cutting section is inevitable when using the surface-treated steel sheet, thus galvanic corrosion properties of Al-Mg films were also studied. In this experiment, Al-Mg films were deposited onto steel substrates using the eco-friendly PVD method under 10 ~ 31 wt.% Mg contents. The total thickness of every specimen was equal to 5ใŽ›. And then heat treatment was conducted at temperature of 400โ„ƒ for 10 minutes. The material properties of Al-Mg films were investigated by using SEM, GDS and XRD. The corrosion behaviour of the Al-Mg films determined using neutral salt fog test and electrochemical techniques. After the salt spray test, corrosion products were analyzed by SEM, EDS and XRD at the beginning, middle, and end of the test. Non heat treated Al-Mg specimens were analyzed after 48h, 96h, 168h, and heat treated Al-Mg specimens were analyzed after 72h, 168h, 240h. Based on the results of the immersion and salt spray tests, heat treated Al-Mg films obviously showed good corrosion resistance compared to non-heat treated Al-Mg films. In the salt spray test in a 5% NaCl environment, Al-Mg films containing 31 wt.% Mg had the most excellent corrosion resistance. In case of the immersion test in a 3% NaCl solution, Al-Mg films ranging from 18 to 22 wt.% Mg had the most excellent corrosion resistance. Also the mechanism of anti-corrosion can be obtained by the analysis of Al-Mg film's corrosion products at each stage. Consequently, the results of these experiments obtained were as follows-. The difference in corrosion properties between the salt spray test and immersion test is considered the density of corrosion products by the difference of oxygen concentration. Therefore, it is needed to apply the method of estimating the corrosion resistance considering the differences according to environmental conditions. -. It is thought therefore that the property of Al-Mg films can be improved by heat treatment and uniform distribution of intermetallic compounds.์ œ 1 ์žฅ ์„œ ๋ก  1.1 ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1.2 ์—ฐ๊ตฌ ์ง„ํ–‰ ๋‚ด์šฉ ์ œ 2 ์žฅ ์ด๋ก ์  ๋ฐฐ๊ฒฝ 2.1 ์ง„๊ณต ๋ฐ ํ”Œ๋ผ์ฆˆ๋งˆ๋ฅผ ์ด์šฉํ•œ ํ‘œ๋ฉด์ฒ˜๋ฆฌ 2.1.1 ํ”Œ๋ผ์ฆˆ๋งˆ์˜ ์ •์˜ ๋ฐ ์ด์šฉ 2.1.2 ํ”Œ๋ผ์ฆˆ๋งˆ๋ฅผ ์ด์šฉํ•œ ํ‘œ๋ฉด์ฒ˜๋ฆฌ 2.1.3 PVD๋ฒ• 2.2 ๋ฐ•๋ง‰์˜ ์ •์˜ ๋ฐ ํ˜•์„ฑ 2.2.1 ๋ฐ•๋ง‰์˜ ์ •์˜ ๋ฐ ํŠน์ง• 2.2.2 ๋ฐ•๋ง‰์˜ ํ˜•์„ฑ 2.3 ๋‚ด์‹์„ฑ ์ฝ”ํŒ…๋ง‰ 2.3.1 ๋ถ€์‹์˜ ์ „๊ธฐํ™”ํ•™์  ๋ฐ˜์‘ 2.3.2 ๋‚ด์‹์„ฑ์„ ์œ„ํ•œ ๊ธˆ์†ํ”ผ๋ณต์˜ ๋ถ„๋ฅ˜ ์ œ 3 ์žฅ ์‹คํ—˜ ๋ฐฉ๋ฒ• 3.1 ์‹คํ—˜ ์žฅ์น˜ ๋ฐ ๋ฐ•๋ง‰์˜ ์ œ์ž‘ ์กฐ๊ฑด 3.1.1 ์‹คํ—˜ ์žฅ์น˜ 3.1.2 ์‹œํ—˜ํŽธ์˜ ์ค€๋น„ 3.1.3 ๋ง‰์˜ ์ œ์ž‘ ๋ฐ ์—ด์ฒ˜๋ฆฌ 3.2 ์ œ์ž‘ ๋ง‰์˜ ๋ถ„์„ ๋ฐ ๋‚ด์‹์„ฑ ํ‰๊ฐ€ 3.2.1 ํ‘œ๋ฉด ๋ฐ ๋‹จ๋ฉด์˜ ๋ชฐํฌ๋กœ์ง€ ๋ถ„์„ 3.2.2 ์กฐ์„ฑ๋ถ„ํฌ ๋ถ„์„ 3.2.3 ์„ฑ๋ถ„ ์ƒ ๋ฐ ๊ฒฐ์ •๊ตฌ์กฐ ๋ถ„์„ 3.2.4 ์ „๊ธฐํ™”ํ•™์  ๋‚ด์‹์„ฑ ํ‰๊ฐ€ ์ œ 4 ์žฅ ์‹คํ—˜ ๊ฒฐ๊ณผ ๋ฐ ๊ณ ์ฐฐ 4.1 ํ”„๋กœ์„ธ์Šค ์กฐ๊ฑด์— ๋”ฐ๋ฅธ Al-Mg ๋ง‰์˜ ์žฌ๋ฃŒํŠน์„ฑ ๋ถ„์„ 4.1.1 ๋ง‰์˜ ๋ชฐํฌ๋กœ์ง€ ๋ฐ ์กฐ์„ฑ๋ถ„ํฌ ๋ถ„์„ 4.1.2 ์„ฑ๋ถ„ ์ƒ ๋ฐ ๊ฒฐ์ •๊ตฌ์กฐ ๋ถ„์„ 4.2 ํ”„๋กœ์„ธ์Šค ์กฐ๊ฑด์— ๋”ฐ๋ฅธ Al-Mg ๋ง‰์˜ ๋‚ด์‹์„ฑ ํ‰๊ฐ€ 4.2.1 Al-Mg ๋ง‰ ํ‘œ๋ฉด์˜ ์ „๊ธฐํ™”ํ•™์  ๋‚ด์‹์„ฑ ํ‰๊ฐ€ 4.2.2 Al-Mg ๋ง‰ ๋‹จ๋ฉด์˜ ์ „๊ธฐํ™”ํ•™์  ๋‚ด์‹์„ฑ ํ‰๊ฐ€ 4.3 Al-Mg ๋ง‰์˜ ๋ถ€์‹๋ฐฉ์‹ ํŠน์„ฑ ๊ด€๊ณ„ ๊ณ ์ฐฐ 4.3.1 Al-Mg ๋ง‰์˜ ์žฌ๋ฃŒํŠน์„ฑ๊ณผ ๋‚ด์‹์„ฑ ๊ด€๊ณ„ ๊ณ ์ฐฐ 4.3.2 ๋ฐฉ์‹์ „์œ„์—์„œ ์ฒ ์˜ ์ ๋…น๋ฐœ์ƒ ์›์ธ ๊ณ ์ฐฐ ์ œ 5 ์žฅ ๊ฒฐ

    ์‹œ์ƒํ•˜๋ถ€ ๋‡Œ์‹ค๊ณํ•ต ์„ธํฌ์˜ ์ „๊ธฐ์ƒ๋ฆฌํ•™์  ํ™œ์„ฑ์„ ์กฐ์ ˆํ•˜๋Š” ์ „์••์˜์กด์„ฑ K+ ํ†ต๋กœ์˜ ๋ถ„์ž์ƒ๋ฌผํ•™์  ํŠน์„ฑ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ˜‘๋™๊ณผ์ •๋‡Œ๊ณผํ•™์ „๊ณต, 2014. 8. ๋ฅ˜ํŒ๋™.์‹œ์ƒํ•˜๋ถ€์— ์กด์žฌํ•˜๋Š” ๋‡Œ์‹ค๊ณํ•ต(hypothalamic paraventricular nucleusPVN)์€ ๊ตฌ์กฐ์ ์œผ๋กœ ๋˜๋Š” ๊ธฐ๋Šฅ์ ์œผ๋กœ ๊ตฌ๋ณ„๋˜๋Š” ์ด์งˆ์ ์ธ ์„ธํฌ๋“ค๋กœ ์ด๋ฃจ์–ด์ ธ ์žˆ๋‹ค. ์ด๋“ค ์„ธํฌ๋“ค์˜ ์ „๊ธฐ์ƒ๋ฆฌํ•™์  ํŠน์„ฑ๊ณผ A-type K+ ์ „๋ฅ˜(IA)์˜ ๊ด€๋ จ์„ฑ์€ ์ž˜ ์•Œ๋ ค์ ธ ์žˆ์ง€๋งŒ, ๊ทธ ๋ถ„์ž์  ํŠน์„ฑ์— ๋Œ€ํ•ด์„œ๋Š” ๋ฐํ˜€์ง„ ๋ฐ”๊ฐ€ ์—†๋‹ค. ๋”ฐ๋ผ์„œ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” IA๋ฅผ ์ธ์ฝ”๋”ฉํ•˜๋Š” ์ „์••์˜์กด์„ฑ K+ ํ†ต๋กœ(voltage-gated K+ channelKv ํ†ต๋กœ)๊ฐ€ PVN์˜ ์ „๋ฆฌ์ƒ๋ฆฌํ•™์ ์ธ ํŠน์„ฑ์— ๊ด€์—ฌํ•  ๊ฒƒ์ด๋ผ๊ณ  ๊ฐ€์ •ํ•˜๊ณ , ์„ฑ๊ฒฉ์ด ๋‹ค๋ฅธ ์„ธํฌ ํ˜•ํƒœ(type I, type II)์—์„œ์˜ Kv ํ†ต๋กœ ๋ฐœํ˜„์ฐจ์ด์™€, ์‹ฌ๋ถ€์ „์ด๋‚˜ ์—์ŠคํŠธ๋กœ๊ฒ์— ์˜ํ•ด ๊ทธ ํ™œ์„ฑ์ด ๋ณ€ํ™”ํ•˜๋Š” ๊ต๊ฐ์‹ ๊ฒฝ์กฐ์ ˆ์„ธํฌ์—์„œ์˜ Kv ํ†ต๋กœ ๋ฐœํ˜„๋ณ€ํ™”๋ฅผ ์‚ดํŽด๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. PVN์—์„œ ํŠน์ • ์„ธํฌ์—์„œ์˜ ๋ถ„์ž์  ์ •๋ณด๋ฅผ ์–ป๊ธฐ ์œ„ํ•ด, ๋‹จ์ผ์„ธํฌ ์—ญ์ „์‚ฌ-์ค‘ํ•ฉํšจ์†Œ์—ฐ์‡„๋ฐ˜์‘๋ฒ•(single cell reverse transcription-polymerase chain reactionsingle cell RT-PCR) ๋˜๋Š” ๋‹จ์ผ์„ธํฌ ์‹ค์‹œ๊ฐ„ ์—ญ์ „์‚ฌ-์ค‘ํ•ฉํšจ์†Œ์—ฐ์‡„๋ฐ˜์‘๋ฒ• (single cell real-time RT-PCR)์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ, type I, type II ๋ชจ๋‘์—์„œ ๋‹ค์–‘ํ•œ Kv ์ฑ„๋„ subunit๋“ค์˜ ๋ฐœํ˜„์ด ๊ด€์ฐฐ๋˜์—ˆ๋Š”๋ฐ ๊ทธ ์ค‘, Kv4.2์™€ Kv4.3์€ ๊ทธ ๋ฐœํ˜„ ์ •๋„์— ์žˆ์–ด์„œ type II์—์„œ๋ณด๋‹ค type I์—์„œ ์œ ์˜์ ์œผ๋กœ ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ต๊ฐ์‹ ๊ฒฝ์กฐ์ ˆ์„ธํฌ์—์„œ๋„ Kv4.2์™€ Kv4.3์˜ ๋ฐœํ˜„์ด ๊ด€์ฐฐ๋˜์—ˆ๋Š”๋ฐ, ์‹ฌ๋ถ€์ „ ์œ ๋ฐœ์— ๋”ฐ๋ผ ๊ทธ ๋ฐœํ˜„์ด ๋‹ค๋ฅด๊ฒŒ ์กฐ์ ˆ๋˜์—ˆ๋‹ค. Kv4.2๋Š” ์ฆ๊ฐ€๋˜๊ณ  Kv4.3์€ ๊ฐ์†Œ๋˜์—ˆ๋‹ค. ๋ฐ˜๋ฉด ์—์ŠคํŠธ๋กœ๊ฒ์— ์˜ํ•ด์„œ๋Š” Kv4.2๋งŒ์ด ์„ ํƒ์ ์œผ๋กœ ๊ฐ์†Œ๋˜์—ˆ์œผ๋ฉฐ Kv4.3์€ ๋ณ€ํ™”๊ฐ€ ์—†์—ˆ๋‹ค. ๋˜ํ•œ IA ์˜ ๊ฐ์†Œ๋„ ํ•จ๊ป˜ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์—์ŠคํŠธ๋กœ๊ฒ์˜ ์˜ํ–ฅ์€ ๋ฐ”์†Œํ”„๋ ˆ์‹ ์ด ํŠน์ด์ ์œผ๋กœ ์ ๊ฒŒ ๋ถ„ํฌ๋˜์–ด ์žˆ๋Š” dorsal cap ์˜์—ญ์—์„œ๋งŒ ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ์œ„์˜ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋Š” Kv4.2์™€ Kv4.3์ด PVN์˜ type I, type II๋ฅผ ๊ตฌ๋ณ„ํ•˜๊ณ  ๊ต๊ฐ์‹ ๊ฒฝ์กฐ์ ˆ์„ธํฌ์˜ ์ „๊ธฐ์ƒ๋ฆฌํ•™์  ํ™œ์„ฑ์„ ์กฐ์ ˆํ•˜๋Š” ๋ฐ ์ฃผ์š”ํ•˜๊ฒŒ ์ž‘์šฉํ•˜๋ฉฐ, ์งˆ๋ณ‘์ด๋‚˜ ํ˜ธ๋ฅด๋ชฌ ๋ณ€ํ™”์— ์˜ํ•ด ์„œ๋กœ ๋…๋ฆฝ์ ์œผ๋กœ ์กฐ์ ˆ๋˜๊ณ  ์žˆ์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ๋”ฐ๋ผ์„œ, Kv ํ†ต๋กœ๋Š” ์ž์œจ์‹ ๊ฒฝ๊ณ„์™€ ๋‚ด๋ถ„๋น„๊ณ„์˜ ๊ธฐ๋Šฅ ์ด์ƒ์— ๋”ฐ๋ฅธ PVN์˜ ์‹ ๊ฒฝ์ „๋‹ฌ ๋ณ€ํ™”์— ์ฐธ์—ฌํ•˜๋Š” ํ•˜๋‚˜์˜ ๊ธฐ์ „์œผ๋กœ ์—ฌ๊ฒจ์ง„๋‹ค.The hypothalamic paraventricular nucleus (PVN) comprises anatomically and functionally distinct neuronal populations. The A-type K+ current (IA) is involved in their different electrophysiological properties, but the molecular identity responsible for these differences remains unknown. Accordingly, I hypothesized that voltage-gated K+ (Kv) channels encoding IA are molecular components underlying the determination of electrophysiological characteristics, and compared expressions of Kv channel subunits between distinct neuronal populations in the PVN, using single cell analysis (single cell reverse transcription-polymerase chain reaction [RT-PCR] or single cell real-time RT-PCR). Results revealed that several Kv channel subunits were expressed in type I and type II PVN neurons which are electrophysiologically distinct. However, the expression density of Kv4.2 and Kv4.3 was significantly higher in type I than in type II neurons. These two subunits were also expressed in the presympathetic neurons, which project to the rostral ventrolateral medulla (RVLMPVN-RVLM), but were differentially regulated during heart failure: Kv4.2 was up-regulated whereas Kv4.3 was down-regulated. In contrast, estrogen replacement into ovariectomized female rats down-regulated Kv4.2 mRNA levels, but did not affect Kv4.3 in the PVN-RVLM neurons. Estrogen also diminished IA density. These estrogenic effects occurred specifically in the dorsal cap parvocellular subdivision where vasopressin is remarkably sparse. Taken together, Kv4.2 and Kv4.3 are important molecular components underlying the determination of electrophysiological characteristics of different cell types and the modulation of neuronal properties of the presympathetic neurons. The finding of the differential and selective regulations of these two subunits under different pathophysiological conditions suggests that Kv4.2 and Kv4.3 play different roles independently of each other in the coordination of responses of the PVN to various types of stimuli.ABSTRACT CONTENTS LIST OF FIGURES LIST OF TABLES ABBREVIATIONS BACKGROUND CHAPTER I Single cell analysis of Kv channels that determine neuronal types of rat PVN neurons ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS CHAPTER II Differential regulation of Kv4 channel subunits in rat presympathetic PVN neurons after myocardial infarction ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS CHAPTER III Selective regulation of Kv channels in rat presympathetic PVN neurons by estrogen replacement ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS CHAPTER IV Differential distributions of neuropeptides in rat presympathetic PVN neurons ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS GENERAL CONCLUSIONS REFERENCES ABSTRACT IN KOREANDocto

    Molecular Testing in Diagnosis of Thyroid Cancer

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    With increasing prevalence of thyroid nodules, clinicians are increasingly impelled to identify the optimal predictor of thyroid cancer, with the goal of guiding management based on assessed risk. Fine-needle aspiration cytology is the gold standard diagnostic method for thyroid nodules. However, fine-needle aspiration cytology is not perfect and adjuncts which might complement its predictive value are being investigated from several innovative perspectives. For these vigorous efforts, remarkable advances have been achieved in understanding several major biologic areas of thyroid cancer, including the molecular alterations for loss of radioiodine avidity of thyroid cancer, the pathogenic role of the MAP kinase and PI3K/Akt pathways and their related genetic alterations in thyroid tumorigenesis and pathogenesis. These exciting advances provide unprecedented opportunities for development of molecular-based novel diagnostic and therapeutic strategies for thyroid cancer. The common somatic genetic changes in thyroid cancer of follicular cell origin (RET/PTC, NTRK, RAS, BRAF, PAX8-PPARฮณ) are generally mutually exclusive, with distinct genotypeโ€“histologic subtype associations of thyroid cancer. Mutation analysis in fine needle aspiration samples has been applied to improve the diagnostic accuracy. In studies regarding gene expression profiling, aberrant gene methylation and miRNA have shown significant progress toward identification of biomarkers that could improve the accuracy of fine needle aspiration cytology in the evaluation of patients with thyroid nodule and prediction of disease aggressiveness. Future clinical trials evaluating the accuracy and cost-effectiveness of applying these biomarkers in the management of thyroid neoplasm should be considered.ope

    Coupling of LETM1 up-regulation with oxidative phosphorylation and platelet-derived growth factor receptor signaling via YAP1 transactivation

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    Persistent cellular proliferation and metabolic reprogramming are essential processes in carcinogenesis. Here, we performed Gene Set Enrichment Analysis (GSEA) and found that that LETM1, a mitochondrial calcium transporter, is associated with cellular growth signals such as platelet-derived growth factor (PDGF) receptor signaling and insulin signaling pathways. These results were then verified by qRT-PCR and immnunoblotting. Mechanistically, up-regulation of LETM1 induced YAP1 nuclear accumulation, increasing the expression of PDGFB, PDGFRB and THBS4. Consistent with this, LETM1 silencing caused loss of YAP1 nuclear signal, decreasing the expression of PDGFB, PDGFRB and THBS4. Immunohistochemical staining consistently indicated a positive association between LETM1 up-regulation, YAP1 nuclear localization and high PDGFB expression. In clinical data analysis, LETM1 up-regulation in thyroid cancer was found to be related to aggressive tumor features such as lymphovascular invasion (LVI, P < 0.001) and lymph node metastasis (LNM, P = 0.011). Multivariate analysis demonstrated that LETM1 up-regulation increases the risk of LVI and LNM (OR = 3.455, 95% CI = 1.537-7.766 and OR = 3.043, 95% CI = 1.282-7.225, respectively). Collectively, these data suggest that up-regulation of LETM1 induces sustained activation of proliferative signaling pathways, such as PDGF signal pathway by AKT induced YAP1 transactivation, resulting in aggressive thyroid cancer phenotypes.ope

    Long-term oncologic outcomes of papillary thyroid mircrocarcinoma according to the presence of clinically apparent lymph node metastasi: a large retrospective analysis of 5,348 patients

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    Purpose: Active surveillance (AS) of low-risk papillary thyroid microcarcinoma (PTMC) may reduce the risk of overtreatment of clinically insignificant cancer. However, the absence of predictor for the progression of PTMC resulted in treatment delay and potentially compromising cure of aggressive disease. Therefore, to anticipate potential damage of delayed surgery, we investigated the oncologic outcomes of patients with low-risk PTMC initially eligible for AS except clinically apparent lymph node metastasis (LNM), imitating delayed surgery with neck dissection. Materials and methods: A total of 5,348 patients, enrolled between 1987 and 2016, with low-risk PTMC initially eligible for AS were included regardless of LNM. We classified our study patients into two groups: Group I, lobectomy with prophylactic central cervical node dissection; Group II, total thyroidectomy with modified radical neck dissection for LNM. In addition, we investigated the oncological outcomes of patients with second-wave surgery due to lateral lymph node recurrence (Group III, subgroup of Group I). Results: Group I showed more favorable clinicopathological characteristics compared with Group II. In Group I, only 29 (0.58%) of 4,927 patients underwent second-wave surgery with neck dissection for lateral lymph node recurrences, whereas in Group II, all 22 (5.23%) of 421 patients underwent second-wave selective node dissection because of nodal recurrence. Disease-free survival rates were significantly different between Groups I and II (P<0.05). Of note, the recurrence rate of Group II was still significantly higher than that of Group III (5.2% vs 0%, respectively; P=0.021). In addition, Kaplan-Mayer survival analysis indicated poor disease-free survival rates in Group II compared with Group III (P<0.05). Conclusion: The long-term treatment outcome of PTMC without LNM was favorable even if the recurrence occurs during follow-up period compared with that of PTMC with LNM. It should be noted that AS might be able to cause poor prognosis due to clinically apparent LNM.ope

    Dynamic risk stratification in medullary thyroid carcinoma: Single institution experiences

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    Recently, dynamic risk stratification has been found to be more valuable than static anatomic staging system in nonmedullary thyroid cancer and this strategy has also been accepted in medullary thyroid cancer (MTC). The present study was designed to compare the clinical usefulness of response to initial therapy stratification with a traditional anatomic staging system.From August 1982 to December 2012, a total of 144 MTC patients underwent thyroidectomy in Yonsei University Hospital. Among them, 117 (82.2%) patients with complete clinical data and sustained follow-up were enrolled in this study. Clinicopathological features and surgical outcomes were analyzed by retrospective medical chart review. Mean follow-up duration was 85.78โ€Šยฑโ€Š62.51 months.In this study, mean tumor size was 1.94โ€Šยฑโ€Š1.40โ€Šcm and 22 (18.9%) patients had hereditary MTC; 95 (81.1%) patients had sporadic MTC. Stage I patients had highest probability of excellent response to initial therapy (92.1%). Stage IV patients had highest probability of biochemical and structural incomplete response to initial therapy (57.5% and 30.3%) and lowest probability of excellent response to initial therapy (12.1%). Both response to initial therapy stratification and TNM staging system offered useful prognostic information in this study. The TNM staging system provided risk stratification pertaining to disease-free survival (DFS), disease-specific survival (DSS), and the probability of having no evidence of disease at final outcome, but did not provide risk stratification pertaining to the probability of having biochemical persistent/recurrence disease at final outcome. However, response to initial therapy stratification provided risk stratification pertaining to not only DFS, DSS, and the probability of having no evidence of disease at final outcome but also the probability of having biochemical persistent/recurrence disease at final outcome.In this study, we demonstrated that dynamic risk stratification with adjusted response to initial therapy system can offer more useful prognostic information than anatomic staging system in MTC.ope
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