14 research outputs found

    ๊ฒฝ์˜์ž ์žฌ์ž„ ๊ธฐ๊ฐ„๊ณผ ํ˜„๊ธˆ ํ๋ฆ„ ์กฐ์ •

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ฒฝ์˜๋Œ€ํ•™ ๊ฒฝ์˜ํ•™๊ณผ, 2021.8. ๊น€ํ˜œ๋ฆฐ.์‹œ์žฅ์€ ์ƒˆ๋กœ์šด ๊ฒฝ์˜์ž์˜ ๋Šฅ๋ ฅ์— ๋Œ€ํ•ด ๋ถˆํ™•์‹ค์„ฑ์„ ๊ฐ€์ง„๋‹ค. ์ด๋Ÿฌํ•œ ๋ถˆํ™•์‹ค์„ฑ์„ ์ค„์ด๊ธฐ ์œ„ํ•ด ๊ฒฝ์˜์ž๋Š” ์žฌ์ž„ ๊ธฐ๊ฐ„ ์ดˆ๊ธฐ์— ์„ฑ๊ณผ๋ฅผ ์ƒํ–ฅ ์กฐ์ •ํ•œ๋‹ค. ์„ ํ–‰ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์— ๋”ฐ๋ฅด๋ฉด, ๊ฒฝ์˜์ž๋Š” ์žฌ์ž„ ๊ธฐ๊ฐ„ ๋ง๊ธฐ ๋ณด๋‹ค ์ดˆ๊ธฐ์— ์ด์ต์„ ์ƒํ–ฅ ์กฐ์ •ํ•  ์œ ์ธ์ด ๋” ํฌ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ–ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ํ˜„๊ธˆ ํ๋ฆ„ ์˜ˆ์ธก์— ๋Œ€ํ•œ ์ •๋ณด ์‚ฌ์šฉ์ž์˜ ์ˆ˜์š”๊ฐ€ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๊ธฐ ๋•Œ๋ฌธ์— ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์žฌ์ž„ ๊ธฐ๊ฐ„ ์ดˆ๊ธฐ์˜ ๊ฒฝ์˜์ž๊ฐ€ ํ˜„๊ธˆ ํ๋ฆ„์„ ์ƒํ–ฅ ์กฐ์ •ํ•  ์œ ์ธ์ด ์žˆ๋Š”์ง€์— ๋Œ€ํ•ด ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์ฒซ์งธ๋กœ, ์žฌ์ž„ ๊ธฐ๊ฐ„ ์ดˆ๊ธฐ์˜ ๊ฒฝ์˜์ž๊ฐ€ ์˜์—… ํ˜„๊ธˆ ํ๋ฆ„์„ ์ƒํ–ฅ ์กฐ์ •ํ•  ์œ ์ธ์ด ๋” ๋†’๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ–ˆ๋‹ค. ๋˜ํ•œ, CEO ์™€ CFO ๊ฐ„์˜ ์˜ํ–ฅ๋ ฅ์˜ ์ฐจ์ด๋Š” ์—†๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋‘˜์งธ๋กœ, ์žฌ์ž„ ๊ธฐ๊ฐ„ ์ดˆ๊ธฐ์˜ CEO ์— ์˜ํ•ด ์กฐ์ •๋œ ์˜์—… ํ˜„๊ธˆ ํ๋ฆ„์ด ๊ทธ๋ ‡์ง€ ์•Š์€ CEO ์— ์˜ํ•ด ์กฐ์ •๋œ ์˜์—… ํ˜„๊ธˆ ํ๋ฆ„๋ณด๋‹ค ์ง€์†์„ฑ์ด ๋‚ฎ์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋˜ํ•œ, ์žฌ์ž„ ๊ธฐ๊ฐ„ ์ดˆ๊ธฐ์˜ CFO ์— ์˜ํ•ด ์กฐ์ •๋œ ์˜์—… ํ˜„๊ธˆ ํ๋ฆ„์€ ๊ทธ๋ ‡์ง€ ์•Š์€ CFO ์— ์˜ํ•ด ์กฐ์ •๋œ ์˜์—… ํ˜„๊ธˆ ํ๋ฆ„๋ณด๋‹ค ์ง€์†์„ฑ์ด ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๊ทธ๋ฆฌ๊ณ , ์ง€์†์„ฑ์˜ ์ธก๋ฉด์—์„œ ์˜์—… ํ˜„๊ธˆ ํ๋ฆ„ ์กฐ์ •์—๋Š” CFO ๊ฐ€ CEO ๋ณด๋‹ค ๋” ํฐ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ, ํ˜„๊ธˆ ์ „ํ™˜ ์ฃผ๊ธฐ (cash conversion cycle)์„ ํ†ตํ•ด ํ˜„๊ธˆ ํ๋ฆ„์„ ์กฐ์ •ํ•œ๋‹ค๋Š” ๊ฒฐ๊ณผ๋Š” ์ œ์‹œํ•˜์ง€ ๋ชปํ–ˆ๋‹ค.The market is uncertain about the ability of executives in their early years of service. To favorably influence the markets perception of their ability, executives manage firm performance. Prior literature shows that CEOs have stronger incentives for earnings overstatement in their early years of service than in their final years of service. However, since there is an increased demand of the market for cash flow information, I examine whether executives have stronger incentives for cash flow management in their early years of service. I find that executives are more likely to manage cash flow in their early years of service due to career concerns, even after controlling for accruals. Also, I find that cash flow managed by CEOs (CFOs) in their early years of service is less (more) persistent than cash flow managed by CEOs (CFOs) who have been in office longer. I find that, in terms of cash flow persistence, CFOs in their early years of service are more influential on cash flow management than CEOs in their early years of service. Lastly, the mechanism through which executives manage cash flow is unknown in this paper.Chapter 1. Introduction 1 Chapter 2. Prior Literature and Hypothesis Development 3 Chapter 3. Sample Selection and Research Design 8 Chapter 4. Results 10 Chapter 5. Robustness Test and Additional Analysis 14 Chapter 6. Conclusion 17 References 19 Tables 22 Appendix 28 Abstract in Korean 31์„

    ๊ทธ๋ž˜ํ”„ ํ˜‘์—… ํ•„ํ„ฐ๋ง์„ ์œ„ํ•œ ๊ฐ•๋ ฅํ•œ ๋ถ€ํŠธ์ŠคํŠธ๋ž˜ํ•‘ ๊ธฐ๋ฐ˜ ์ž๊ธฐ ์ง€๋„ ํ•™์Šต

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€, 2023. 2. ๊ถŒํƒœ๊ฒฝ.๋Œ€์กฐ ํ•™์Šต ๊ธฐ๋ฐ˜ ๋ชจ๋ธ์€ ์›์‹œ ๋ฐ์ดํ„ฐ์—์„œ ์ž์ฒด ๊ฐ๋… ์‹ ํ˜ธ๋ฅผ ์ถ”์ถœํ•˜๋Š” ๊ธฐ๋Šฅ์ด ๋ฐ์ดํ„ฐ ํฌ์†Œ์„ฑ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ์ถ”์ฒœ ์‹œ์Šคํ…œ์˜ ์š”๊ตฌ ์‚ฌํ•ญ๊ณผ ์ผ์น˜ํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์ถ”์ฒœ ์—ฐ๊ตฌ์—์„œ ์ฃผ๋ชฉ์„ ๋ฐ›๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ํšจ์œจ์„ฑ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๋Œ€์กฐ ํ•™์Šต ๊ธฐ๋ฐ˜ ๋ชจ๋ธ์—๋Š” ์ค‘์š”ํ•œ ํ•œ๊ณ„์ ์ด ์žˆ๋‹ค. ๋ฐ”๋กœ ๋„ค๊ฑฐํ‹ฐ๋ธŒ ์ƒ˜ํ”Œ๋ง์ด๋‹ค. ๋„ค๊ฑฐํ‹ฐ๋ธŒ ์ƒ˜ํ”Œ๋ง ๋ฐฉ์‹์„ ์‚ฌ์šฉํ•˜๋ฉด ์‚ฌ์šฉ์ž์˜ ์ทจํ–ฅ์— ๋งž๋Š” ํ•ญ๋ชฉ์ด์ง€๋งŒ ์ƒํ˜ธ์ž‘์šฉ์ด ๊ด€์ฐฐ๋˜์ง€ ์•Š์€ ์‚ฌ์šฉ์ž-ํ•ญ๋ชฉ ์Œ์„ ๋„ค๊ฑฐํ‹ฐ๋ธŒ๋กœ ์„ ํƒํ•  ์ˆ˜ ์žˆ๋‹ค. ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๋„ค๊ฑฐํ‹ฐ๋ธŒ ์ƒ˜ํ”Œ๋ง์ด ํ•„์š”ํ•˜์ง€ ์•Š์€ ๋ถ€ํŠธ์ŠคํŠธ๋ž˜ํ•‘ ๊ธฐ๋ฐ˜์˜ ์ž๊ธฐ ์ง€๋„ ํ•™์Šต ๋ฐฉ๋ฒ•์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด ๋ฐฉ๋ฒ•์—๋„ ํ•œ๊ณ„์ ์ด ์žˆ๋‹ค. ๊ด€์ฐฐ๋œ ์ƒ˜ํ”Œ๋งŒ ์‚ฌ์šฉํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๋…ธ์ด์ฆˆ๊ฐ€ ์žˆ๋Š” ์ƒํ˜ธ ์ž‘์šฉ์— ์ทจ์•ฝํ•˜๋‹ค. ๋˜ํ•œ ์‹ค์ œ ๋ฐ์ดํ„ฐ ์…‹์—๋Š” ํฌ์†Œ์„ฑ ๋ฌธ์ œ๊ฐ€ ์žˆ๋‹ค. ์œ„์˜ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ๊ทธ๋ž˜ํ”„ ํ˜‘์—… ํ•„ํ„ฐ๋ง์„ ์œ„ํ•œ ๊ฐ•๋ ฅํ•œ ๋ถ€ํŠธ์ŠคํŠธ๋ž˜ํ•‘ ๊ธฐ๋ฐ˜ ์ž๊ธฐ ์ง€๋„ ํ•™์Šต ๋ชจ๋ธ, RBS๋ฅผ ์†Œ๊ฐœํ•œ๋‹ค. RBS๋Š” ๊ทธ๋ž˜ํ”„ ๋…ธ์ด์ฆˆ ์ œ๊ฑฐ ๋ชจ๋“ˆ๊ณผ ์ž๊ฐ€ ์ง€๋„ ํ•™์Šต ๋ชจ๋“ˆ์˜ ๋‘ ๊ฐ€์ง€ ๋ชจ๋“ˆ๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. ๊ทธ๋ž˜ํ”„ ๋…ธ์ด์ฆˆ ์ œ๊ฑฐ ๋ชจ๋“ˆ์€ ์žก์Œ์ด ์žˆ๋Š” ์ƒํ˜ธ ์ž‘์šฉ์˜ ์˜ํ–ฅ์„ ์ค„์ด๊ธฐ ์œ„ํ•ด ์„ค๊ณ„๋˜์—ˆ๋‹ค. ์ž๊ธฐ ์ง€๋„ ํ•™์Šต ๋ชจ๋“ˆ์€ ์˜จ๋ผ์ธ ์ธ์ฝ”๋”์™€ ํƒ€๊นƒ ์ธ์ฝ”๋”๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. RBS๋Š” ํƒ€๊นƒ ์ธ์ฝ”๋”์˜ ํ‘œํ˜„์„ ์˜ˆ์ธกํ•˜๋„๋ก ์˜จ๋ผ์ธ ์ธ์ฝ”๋”๋ฅผ ํ•™์Šตํ•˜๋Š” ๋ฐ˜๋ฉด, ํƒ€๊นƒ ์ธ์ฝ”๋”๋Š” ์˜จ๋ผ์ธ ์ธ์ฝ”๋”๋ฅผ ์ฒœ์ฒœํžˆ ๊ทผ์‚ฌํ•˜์—ฌ ์ผ๊ด€๋œ ํƒ€๊นƒ์„ ์ œ๊ณตํ•œ๋‹ค. ๋˜ํ•œ RBS๋Š” ์ธ์ฝ”๋” ์ž…๋ ฅ์— ๋…ธ์ด์ฆˆ๋ฅผ ์ถ”๊ฐ€ํ•˜์—ฌ ๋ฐ์ดํ„ฐ ํฌ์†Œ์„ฑ ๋ฌธ์ œ๋ฅผ ํšจ๊ณผ์ ์œผ๋กœ ์™„ํ™”ํ•œ๋‹ค. 3๊ฐ€์ง€ ๋ฒค์น˜๋งˆํฌ ๋ฐ์ดํ„ฐ ์…‹์— ๋Œ€ํ•œ ํฌ๊ด„์ ์ธ ๊ฒฝํ—˜์  ์—ฐ๊ตฌ๋Š” RBS๊ฐ€ ๋ชจ๋“  ๊ธฐ์ค€ ๋ชจ๋ธ์„ ์ผ๊ด€๋˜๊ณ  ํฌ๊ฒŒ ๋Šฅ๊ฐ€ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ค€๋‹ค.Contrastive learning (CL) based models are gaining traction in recommendation research, since their ability to extract self-supervised signals from raw data matches the requirements of recommender systems to solve the data sparsity issue. Despite their effectiveness, CL-based models have an important limitation: negative sampling. A negative sampling scheme allows positive but unobserved pairs to be selected as negative. To solve this problem, a bootstrapping-based self-supervised learning method that does not require negative sampling has been proposed. However, this method also has limitations. Because only positive samples are used, it is vulnerable to noisy interactions. Also, there is a sparsity issue in real-world data sets. To tackle the above issues, we introduce a Robust Bootstrapping-based Self-supervised learning model for graph collaborative filtering, named RBS. RBS consists of two modules: a graph denoising module and a self-supervised learning module. The graph denoising module is designed to reduce the influence of noisy interactions. The self-supervised learning module consists of an online encoder and a target encoder. RBS trains its online encoder to predict the target encoders representation, while the target encoder provides consistent targets by slowly approximating the online encoder. In addition, RBS effectively alleviates the data sparsity issue, by adding noises to encoder inputs. A comprehensive empirical study on three benchmark datasets demonstrates that RBS consistently and significantly outperforms all baseline methods.Chapter 1. Introduction 1 Chapter 2. Related Work 3 2.1. Graph Neural Networks 3 2.2. Graph Collaborative Filtering 3 2.3. Self-supervised Learning 4 Chapter 3. Methodology 6 3.1. Overview 6 3.2. Problem Definition 6 3.3. Graph Denoising Module 7 3.4. Self-supervised Learning Module 9 3.5. Prediction 11 Chapter 4. Experiments 12 4.1. Datasets 12 4.2. Baselines 13 4.3. Evaluation Metrics 13 4.4. Implementation Details 14 4.5. Overall Performance 14 4.6. Ablation Study 18 Chapter 5. Conclusion 21 Bibliography 22 ์ดˆ๋ก 27์„

    Association between real-world social relationship and neural responses to social exclusion in older adults

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‚ฌํšŒ๊ณผํ•™๋Œ€ํ•™ ์‹ฌ๋ฆฌํ•™๊ณผ, 2021. 2. ์ตœ์ง„์˜.๋…ธ๋…„๊ธฐ๋Š” ์ผ์ƒ์— ๊ฑธ์ณ ํ˜•์„ฑํ•œ ์‚ฌํšŒ๊ด€๊ณ„ ๋ฐ ์—ญํ• ์ด ์ ์ฐจ ์ถ•์†Œ๋˜์–ด ์‚ฌํšŒ์  ๊ณ ๋ฆฝ์— ์ทจ์•ฝํ•ด์ง€๊ธฐ ์‰ฌ์šด ์‹œ๊ธฐ์ด๋‹ค. ๋…ธ๋…„๊ธฐ ์‚ฌํšŒ์  ๊ณ ๋ฆฝ์€ ๋‹ค์–‘ํ•œ ์งˆํ™˜์˜ ๋ฐœ์ƒ ์œ„ํ—˜๊ณผ ์‚ฌ๋ง๋ฅ ์„ ๋†’์ด๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๊ฐ€์ƒ์˜ ๊ณต๋†€์ด ์‹คํ—˜(Cyberball paradigm)์€ ๊ณ ๋ฆฝ์— ๋Œ€ํ•œ ์ •์„œ ๋ฐ ์‹ ๊ฒฝํ•™์  ๋ฐ˜์‘์„ ์ธก์ •ํ•  ์ˆ˜ ์žˆ๋Š” ์‹คํ—˜ ํŒจ๋Ÿฌ๋‹ค์ž„์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ง€๊ธˆ๊นŒ์ง€ ๊ฐ€์ƒ์˜ ๊ณต๋†€์ด ์‹คํ—˜์€ ๋Œ€๋ถ€๋ถ„ ์ฒญ์†Œ๋…„ ๋ฐ ์ Š์€ ์„ฑ์ธ์„ ๋Œ€์ƒ์œผ๋กœ ์‹ค์‹œ๋˜์–ด ์™”๋‹ค. ๋˜ํ•œ ๊ฐ€์ƒ์˜ ๊ณต๋†€์ด ์‹คํ—˜์€ ๊ฐ€์ƒ์˜ ์ธ๋ฌผ๋กœ๋ถ€ํ„ฐ ๋ฐฐ์ œ๋‹นํ•˜๋Š” ํŒจ๋Ÿฌ๋‹ค์ž„์— ๊ธฐ๋ฐ˜ํ•˜๊ณ  ์žˆ์–ด, ์‹ค์ œ ์‚ฌํšŒ์—์„œ ๋‚˜ํƒ€๋‚˜๋Š” ์‚ฌ๋žŒ๋“ค ๊ฐ„์˜ ์ƒํ˜ธ์ž‘์šฉ์„ ์ถฉ๋ถ„ํžˆ ๋ฐ˜์˜ํ•˜์ง€ ๋ชปํ•˜๋Š” ํ•œ๊ณ„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” Korean Social Life, Health and Aging Project์— ์ฐธ๊ฐ€ํ•˜๋Š” 88๋ช…์˜ ๋…ธ์ธ(ํ‰๊ท ์—ฐ๋ น: 71.06์„ธ)์„ ๋Œ€์ƒ์œผ๋กœ ์ž๊ธฐ๊ณต๋ช…์˜์ƒ์žฅ์น˜ ์•ˆ์—์„œ ๊ฐ€์ƒ์˜ ๊ณต๋†€์ด ์‹คํ—˜์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ๊ฐ™์€ ๋งˆ์„์— ์‚ด๊ณ  ์žˆ๋Š” ์‚ฌ๋žŒ๋“ค๋กœ๋ถ€ํ„ฐ ๋ฐฐ์ œ๋‹นํ•˜๋„๋ก ์„ค๊ณ„๋œ ๊ฐ€์ƒ์˜ ๊ณต๋†€์ด ์‹คํ—˜์„ ํ™œ์šฉํ•˜์—ฌ, ์ฐธ๊ฐ€์ž๊ฐ€ ๋ฐฐ์ œ๋ฅผ ์ฃผ๋„ํ•˜๋Š” ์‚ฌ๋žŒ๊ณผ ๋งบ๊ณ ์žˆ๋Š” ๊ด€๊ณ„๊ฐ€ ๊ณ ๋ฆฝ์— ๋”ฐ๋ฅธ ๋ถ€์ •์  ์ •์„œ ๋ฐ ์‹ ๊ฒฝ๋ฐ˜์‘์„ฑ์— ์–ด๋–ค ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ์‚ดํŽด๋ณด์•˜๋‹ค. ์ด์— ๋”ํ•˜์—ฌ, ์™„์ „์‚ฌํšŒ์—ฐ๊ฒฐ๋ง ๋ถ„์„(global social network analysis)์„ ํ™œ์šฉํ•ด์„œ ๊ฐœ์ธ์ด ํ‰์†Œ์— ๋งˆ์„์—์„œ ๋งบ๊ณ  ์žˆ๋Š” ์‚ฌํšŒ๊ด€๊ณ„ ํŠน์„ฑ์ด ๋ฐฐ์ œ์— ๋”ฐ๋ฅธ ์‹ ๊ฒฝ๋ฐ˜์‘์„ฑ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ์‚ดํŽด๋ณด์•˜๋‹ค. ์‹ ๊ฒฝ๋ฐ˜์‘์„ฑ์€ ๊ฐ€์ƒ์˜ ๊ณต๋†€์ด๋ฅผ ํ•˜๋Š” ๋™์•ˆ ๋‚˜ํƒ€๋‚˜๋Š” ๊ด€์‹ฌ ๋‡Œ ์˜์—ญ์˜ ํ™œ์„ฑํ™” ์ˆ˜์ค€์œผ๋กœ ์ธก์ •์ด ๋˜์—ˆ์œผ๋ฉฐ, ๊ด€์‹ฌ์˜์—ญ์€ ์‚ฌํšŒ์  ๊ณ ํ†ต๊ณผ ๊ด€๋ จ๋œ ๋‡Œ ์˜์—ญ(์ „๋Œ€์ƒํ”ผ์งˆ, ์ „์ธก ์„ฌ์—ฝ)๊ณผ ์‚ฌํšŒ์  ์ •๋ณด ๋ฐ ๋‹ค๋ฅธ ์‚ฌ๋žŒ์˜ ์˜๋„๋ฅผ ์ถ”๋ก ํ•  ๋•Œ ๊ด€์—ฌํ•˜๋Š” ๋งˆ์Œ์ถ”๋ก  ์˜์—ญ(๋ฐฐ๋‚ด์ธก ์ „์ „๋‘ ํ”ผ์งˆ, ๋ณต๋‚ด์ธก ์ „์ „๋‘ ํ”ผ์งˆ, ์ธก๋‘์ •์—ฝ, ์๊ธฐ์•ž์†Œ์—ฝ)์œผ๋กœ ์„ค์ •ํ•˜์˜€๋‹ค. ์‚ฌํšŒ์—ฐ๊ฒฐ๋ง ๋ถ„์„์„ ํ†ตํ•ด ๊ฐœ์ธ์ด ์„œ๋กœ๋ฅผ ๋ชจ๋ฅด๋Š” ์‚ฌ๋žŒ๋“ค์„ ์—ฐ๊ฒฐ์‹œ์ผœ์ฃผ๋Š” ์‚ฌํšŒ์  ์œ„์น˜๋ฅผ ์ ํ•˜๊ณ  ์žˆ๋Š”์ง€(์ค‘๊ฐœ์ž ์—ญํ• ) ๊ทธ๋ฆฌ๊ณ  ์ค‘์š”ํ•œ ์ผ์„ ์ƒ์˜ํ•˜๋Š” ์‚ฌ๋žŒ์˜ ์ˆ˜๊ฐ€ ๋งŽ์€์ง€(์‚ฌํšŒ ์—ฐ๊ฒฐ๋ง ํฌ๊ธฐ)์— ๋Œ€ํ•œ ์ •๋ณด๋ฅผ ์–ป์—ˆ๋‹ค. ๊ฐ€์ƒ์˜ ๊ณต๋†€์ด์—์„œ ์•„๋Š” ์‚ฌ๋žŒ๋“ค๋กœ๋ถ€ํ„ฐ ๋ฐฐ์ œ๋ฅผ ๋‹นํ•˜๋Š” ๊ฒฝ์šฐ ๋ชจ๋ฅด๋Š” ์‚ฌ๋žŒ๋“ค๋กœ๋ถ€ํ„ฐ ๋ฐฐ์ œ๋ฅผ ๋‹นํ–ˆ์„ ๋•Œ๋ณด๋‹ค ์‚ฌํšŒ์  ๊ณ ํ†ต๊ณผ ๊ด€๋ จ๋œ ์˜์—ญ(t = -2.26, p = 0.03)๊ณผ ๋งˆ์Œ์ถ”๋ก ๊ณผ ๊ด€๋ จ๋œ ์˜์—ญ(t = -2.55, p = 0.01)์˜ ํ™œ์„ฑํ™” ์ˆ˜์ค€์ด ๋‚ฎ์•˜๋‹ค. ํ•ด๋‹น ํšจ๊ณผ๋Š” ํ•จ๊ป˜ ์ฐธ์—ฌํ•˜๋Š” ๋‚˜๋จธ์ง€ ๋‘ ์‚ฌ๋žŒ์˜ ๊ด€๊ณ„, ์ฐธ๊ฐ€์ž์˜ ๋ฐฐ์šฐ์ž ํฌํ•จ ์—ฌ๋ถ€, ๊ทธ๋ฆฌ๊ณ  ๊ฐœ์ธ์˜ ์„ฑ๊ฒฉ ํŠน์งˆ์„ ๊ณ ๋ คํ•œ ๊ฒฐ๊ณผ์ด๋‹ค. ๋ฐฐ์ œ๋ฅผ ์ฃผ๋„ํ•˜๋Š” ์‚ฌ๋žŒ๋“ค๊ณผ์˜ ๊ด€๊ณ„์— ๋”ฐ๋ผ ๋ถ€์ •์  ์ •์„œ๋ฐ˜์‘์˜ ์ฐจ์ด๋Š” ๊ด€์ฐฐ๋˜์ง€ ์•Š์•˜์ง€๋งŒ ์•„๋Š” ์‚ฌ๋žŒ๋“ค์—๊ฒŒ ๋ฐฐ์ œ๋‹นํ•  ๋•Œ ์‹ ๊ฒฝ๋ฐ˜์‘์„ฑ์ด ๋” ๋‚ฎ๊ฒŒ ๋‚˜ํƒ€๋‚œ ๊ฒƒ์€ ์•„๋Š” ์‚ฌ๋žŒ๋“ค ์‚ฌ์ด์—์„œ ๊ฒฝํ—˜ํ•˜๋Š” ์‚ฌํšŒ์  ๊ณ ๋ฆฝ์ด ๋œ ์œ„ํ˜‘์ ์ธ ์ƒํ™ฉ์œผ๋กœ ์ธ์‹๋˜์—ˆ์„ ๊ฐ€๋Šฅ์„ฑ์„ ์‹œ์‚ฌํ•œ๋‹ค. ๋˜ํ•œ, ๋งˆ์„ ๋‚ด์—์„œ ์‚ฌํšŒ์—ฐ๊ฒฐ๋ง ํฌ๊ธฐ๊ฐ€ ํฐ ์‚ฌ๋žŒ๋“ค๊ณผ (t = 2.28, p = 0.03), ์ค‘๊ฐœ์ž ์—ญํ• ์„ ๋งŽ์ด ํ•˜๋Š” ์‚ฌ๋žŒ๋“ค(t = 2.65, p = 0.01)์€ ์‚ฌํšŒ์  ๋ฐฐ์ œ์— ๋”ฐ๋ฅธ ์‚ฌํšŒ์  ๊ณ ํ†ต ์˜์—ญ์˜ ํ™œ์„ฑํ™” ์ •๋„๊ฐ€ ๋” ํฐ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ถ€์ •์  ์ •์„œ ๋ฐ ๋งˆ์Œ ์ถ”๋ก ๊ณผ ๊ด€๋ จ๋œ ๋‡Œ์˜์—ญ์—์„œ๋Š” ์ด์— ๋”ฐ๋ฅธ ์ฐจ์ด๊ฐ€ ๊ด€์ฐฐ๋˜์ง€ ์•Š์•˜๋‹ค. ์ด๋Ÿฌํ•œ ํšจ๊ณผ๋Š” ๊ฐ€์ƒ์˜ ๊ณต๋†€์ด ์ƒํ™ฉ์—์„œ ๊ด€์ฐฐ๋œ ์ƒํ™ฉ์  ์‚ฌํšŒ๊ด€๊ณ„์™€๋Š” ๋ณ„๊ฐœ๋กœ ๋‚˜ํƒ€๋‚ฌ๊ธฐ ๋•Œ๋ฌธ์—, ํ‰์†Œ์— ๋” ํ’๋ถ€ํ•œ ์‚ฌํšŒ์—ฐ๊ฒฐ๋ง ํŠน์„ฑ์„ ๊ฐ€์ง„ ์‚ฌ๋žŒ๋“ค์ด ์ˆœ๊ฐ„์ ์ธ ๊ณ ๋ฆฝ์„ ๊ฒฝํ—˜ํ–ˆ์„ ๋•Œ ์œ„ํ˜‘์„ ๋” ํฌ๊ฒŒ ์ง€๊ฐํ–ˆ์„ ๊ฐ€๋Šฅ์„ฑ์„ ์‹œ์‚ฌํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋Š” ์‚ฌํšŒ์  ๊ณ ๋ฆฝ๊ฒฝํ—˜์—์„œ ์‚ฌํšŒ์  ๊ด€๊ณ„๊ฐ€ ๋งค์šฐ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์•„๋Š” ์‚ฌ๋žŒ๋“ค๋กœ๋ถ€ํ„ฐ ์ผ์‹œ์  ๊ณ ๋ฆฝ์„ ๊ฒฝํ—˜ํ•˜๋Š” ๊ฒƒ์€ ๋ชจ๋ฅด๋Š” ์‚ฌ๋žŒ๋“ค๋กœ๋ถ€ํ„ฐ ๋ฐฐ์ œ ๋‹นํ•˜๋Š” ๊ฒƒ ๋ณด๋‹ค๋Š” ๊ฐ•๋„๊ฐ€ ๋‚ฎ์€ ์‚ฌํšŒ์  ์œ„ํ˜‘์œผ๋กœ ์—ฌ๊ฒจ์งˆ ๊ฐ€๋Šฅ์„ฑ์„ ์‹œ์‚ฌํ•˜์˜€๋‹ค. ๋™์‹œ์— ๋” ํ’๋ถ€ํ•œ ์‚ฌํšŒ์—ฐ๊ฒฐ๋ง ํŠน์„ฑ์„ ๊ฐ€์ง„ ์‚ฌ๋žŒ๋“ค์ด ์–ด๋–ค ์‚ฌ๋žŒ๋“ค๋กœ๋ถ€ํ„ฐ ๋ฐฐ์ œ๋‹นํ•˜๋Š”์ง€์™€ ๊ด€๊ณ„์—†์ด ์‚ฌํšŒ์  ๊ณ ํ†ต๊ณผ ๊ด€๋ จํ•œ ๋‡Œ ์˜์—ญ์—์„œ ๋” ํฐ ๋ฐ˜์‘์„ ๋‚˜ํƒ€๋‚ธ๋‹ค๋Š” ์ ์€ ์ด๋“ค์ด ํ‰์†Œ์— ๊ณ ๋ฆฝ์ƒํ™ฉ์—์„œ ๋‹ค๋ฅธ ์‚ฌ๋žŒ๋“ค ๋ณด๋‹ค ๋” ํฐ ์‚ฌํšŒ์  ์œ„ํ˜‘์˜ ์‹ ํ˜ธ๋ฅผ ์ง€๊ฐ ํ•  ๊ฐ€๋Šฅ์„ฑ์„ ์‹œ์‚ฌํ•˜์˜€๋‹ค.The experience of being socially excluded engenders painful feelings, which are coined as social pain. However, when an individual is being ostracized by others, such painful experiences may differ depending on a relationship with the excluders. In this study, we brought a real-world social relationship into a laboratory setting and conducted a social exclusion task in an fMRI scanner. Eighty-eight older adults (Mage = 71.06, SDage = 6.56) living in a rural village visited the research lab with the other two participants who have been living in the same village. Then, the three participants played a Cyberball game, a virtual ball-tossing game that induces rejection feelings by using an abrupt exclusion from the other players. We examined whether two characteristics of social relationship, including the social relationship with other players in Cyberball and individualsโ€™ social network characteristics in their village (social network size and brokerage), are associated with the neural response to the social exclusion in social pain and mentalizing area. The results indicate that the social rejection from known others mitigates neural response in social pain and mentalizing regions. In contrast, rejection from unknown others shows increased activation in social pain and mentalizing regions. In addition to this, the result demonstrated that individuals with large social network size and more opportunity for brokerage showed a sensitive neural response to the social exclusion compared to the others with a small social network size and less chance for brokerage. The individualsโ€™ social network effect was examined by accounting for the impact of contextual social relationships in the Cyberball triad. These findings extend our understanding of how social relationship with the excluder affects the response to social exclusion.์„œ ๋ก  6 1. ๊ฐ€์ƒ์˜ ๊ณต๋†€์ด ์‹คํ—˜์—ฐ๊ตฌ 8 2. ์‚ฌํšŒ์  ๊ณ ๋ฆฝ์— ๋Œ€ํ•œ ๋ฐ˜์‘ 11 3. ๊ณ ๋ฆฝ ์ƒํ™ฉ์—์„œ ์‚ฌํšŒ๊ด€๊ณ„์˜ ์—ญํ•  15 4. ์—ฐ๊ตฌ๋ชฉ์  21 ๋ฐฉ ๋ฒ• 24 1. ์—ฐ๊ตฌ ์ฐธ๊ฐ€์ž 24 2. ๊ฐ€์ƒ์˜ ๊ณต๋†€์ด ์‹คํ—˜ 26 3. ๋‡Œ ์˜์ƒ ํš๋“ ๋ฐ ์ „์ฒ˜๋ฆฌ 30 4. ์‚ฌํšŒ๊ด€๊ณ„ ์กฐ์‚ฌ 33 5. ์‹ฌ๋ฆฌ์„ค๋ฌธ 37 6. ์—ฐ๊ตฌ๋ฌธ์ œ๋ถ„์„ 38 ๊ฒฐ ๊ณผ 44 1. ๊ฐ€์ƒ์˜ ๊ณต๋†€์ด์—์„œ ๊ด€์ฐฐ๋œ ์‚ฌํšŒ์  ๊ด€๊ณ„ 44 2. ๋งˆ์„ ๋‚ด ์‚ฌํšŒ์  ๊ด€๊ณ„ 48 3. ๊ฐ€์ƒ์˜ ๊ณต๋†€์ด ์‹คํ—˜ ์ฒ˜์น˜ ํšจ๊ณผ ํ™•์ธ 49 4. ๋ฐฐ์ œ ๊ฒฝํ—˜์— ๋”ฐ๋ฅธ ์‹ ๊ฒฝ๋ฐ˜์‘์„ฑ 51 5. ์—ฐ๊ตฌ๋ฌธ์ œ ๋ถ„์„ ๊ฒฐ๊ณผ 56 ๋…ผ ์˜ 72 1. ๋ฐฐ์ œ๋ฅผ ์ฃผ๋„ํ•˜๋Š” ๋Œ€์ƒ๊ณผ์˜ ๊ด€๊ณ„์™€ ๋ฐฐ์ œ์— ๋”ฐ๋ฅธ ๋ฐ˜์‘์„ฑ 73 2. ๋งˆ์„ ๋‚ด ์‚ฌํšŒ๊ด€๊ณ„์™€ ๋ฐฐ์ œ์— ๋”ฐ๋ฅธ ๋ฐ˜์‘์„ฑ 76 3. ํ•œ๊ณ„ ๋ฐ ์ข…ํ•ฉ๋…ผ์˜ 78 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ 81Docto

    Cidofovir injection in canine glaucoma

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์ˆ˜์˜๊ณผ๋Œ€ํ•™ ์ˆ˜์˜ํ•™๊ณผ, 2023. 2. ์„œ๊ฐ•๋ฌธ.This study aimed to evaluate the long-term efficacy, prognostic factors, and complications of intravitreal cidofovir injection in dogs with end-stage glaucoma. Medical records of 130 dogs (153 eyes) that underwent intravitreal cidofovir injections between 2016 and 2021 were reviewed. A minimum follow-up period of 6 months was required as the inclusion criterion. Signalment, type of glaucoma, pre-injection intraocular pressure (IOP), types of applied glaucoma eye drops, pre-existing ocular diseases, outcomes, and complications were recorded. Success was defined as IOP of โ‰ค25 mmHg at the 2-week recheck that remained to the 6-month recheck. The overall success rate of intravitreal cidofovir injection was 91.5% (140/153). The success rate of a single injection was 69.3% (106/153). Forty-two eyes received a 2nd injection, and the success rate was 59.5% (25/42). Fourteen eyes received a 3rd injection, and the success rate was 42.9% (6/14). Six eyes received a 4th injection, and the success rate was 33.3% (2/6). Two eyes received a 5th injection, and the success rate was 50.0% (1/2). IOPs at 6 months post-injection were significantly higher when the injection was repeated, fewer glaucoma eye drops were applied prior to the injection, and cataract stages were advanced at the time of injection (p < 0.05). The most common complications were phthisis bulbi (42.5%), cataract progression (30.1%), and intraocular hemorrhage (16.3%). Six eyes were enucleated, and three were enucleated due to corneal perforation. Intravitreal cidofovir injection had a high long-term success rate in lowering IOP in dogs with end-stage glaucoma.๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฐœ์˜ ๋ง๊ธฐ ๋…น๋‚ด์žฅ์—์„œ ์œ ๋ฆฌ์ฒด ๋‚ด ์‹œ๋„ํฌ๋น„์–ด(cidofovir) ์ฃผ์‚ฌ์˜ ์žฅ๊ธฐ์ ์ธ ํšจ๊ณผ, ์˜ˆํ›„ ์ธ์ž, ๊ทธ๋ฆฌ๊ณ  ๋ณตํ•ฉ์ฆ์„ ํ‰๊ฐ€ํ•˜๊ธฐ ์œ„ํ•ด ์‹คํ–‰๋˜์—ˆ๋‹ค. 2016๋…„์—์„œ 2021๋…„ ์‚ฌ์ด ์œ ๋ฆฌ์ฒด ๋‚ด ์‹œ๋„ํฌ๋น„์–ด ์ฃผ์‚ฌ๋ฅผ ๋ฐ›์€ 130๋งˆ๋ฆฌ ๊ฐœ(153๊ฐœ ์•ˆ๊ตฌ)์˜ ์˜๋ฃŒ๊ธฐ๋ก์„ ๊ฒ€ํ† ํ•˜์˜€๋‹ค. ์‹œ์ˆ  ํ›„ ์žฌ์ง„ ๊ธฐ๊ฐ„์ด ์ตœ์†Œ 6๊ฐœ์›” ์ด์ƒ์ธ ํ™˜์ž๋“ค์„ ํฌํ•จํ•˜์˜€๋‹ค. ํ™˜์ž ์ •๋ณด, ๋…น๋‚ด์žฅ ์ข…๋ฅ˜, ์‹œ์ˆ  ์ „ ์•ˆ์••, ์ ์•ˆ๋œ ๋…น๋‚ด์žฅ ์•ˆ์•ฝ์˜ ๊ฐœ์ˆ˜, ๊ธฐ์ € ์•ˆ๊ณผ ์งˆํ™˜, ๊ฒฐ๊ณผ ๋ฐ ๋ณตํ•ฉ์ฆ์„ ๊ธฐ๋กํ•˜์˜€๋‹ค. ์‹œ์ˆ ์˜ ์„ฑ๊ณต์€ 2์ฃผ์ผ ํ›„ ์•ˆ์••์ด 25 mmHg ์ดํ•˜์ด๋ฉฐ, 6๊ฐœ์›”๋™์•ˆ ์ง€์†๋  ๊ฒฝ์šฐ๋กœ ์ •์˜ํ•˜์˜€๋‹ค. ์œ ๋ฆฌ์ฒด ๋‚ด ์‹œ๋„ํฌ๋น„์–ด ์ฃผ์‚ฌ์˜ ์ด ์„ฑ๊ณต๋ฅ ์€ 91.5% (140/153)๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. 1ํšŒ ์ฃผ์‚ฌ์˜ ์„ฑ๊ณต๋ฅ ์€ 69.3% (106/153)์˜€์œผ๋ฉฐ, 40๋งˆ๋ฆฌ์˜ ๊ฐœ์—์„œ 2ํšŒ ์‹œ์ˆ ์ด ๋ฐ˜๋ณต๋˜์—ˆ๊ณ , ์„ฑ๊ณต๋ฅ ์€ 59.5% (25/42)์˜€๋‹ค. ์‹œ์ˆ ์ด 3ํšŒ ๋ฐ˜๋ณต๋œ ์•ˆ๊ตฌ๋Š” 14๊ฐœ์˜€์œผ๋ฉฐ, ์„ฑ๊ณต๋ฅ ์€ 42.9% (6/14)์˜€๋‹ค. ์‹œ์ˆ ์ด 4ํšŒ ๋ฐ˜๋ณต๋œ ์•ˆ๊ตฌ๋Š” 6๊ฐœ์˜€์œผ๋ฉฐ, ์„ฑ๊ณต๋ฅ ์€ 33.3% (2/6)์˜€๋‹ค. ์‹œ์ˆ ์ด 5ํšŒ ๋ฐ˜๋ณต๋œ ์•ˆ๊ตฌ๋Š” 2๊ฐœ์˜€์œผ๋ฉฐ, ์„ฑ๊ณต๋ฅ ์€ 50.0% (1/2)์˜€๋‹ค. ์‹œ์ˆ ์ด ๋ฐ˜๋ณต๋œ ๊ฒฝ์šฐ, ์‹œ์ˆ  ์ „ ๋” ์ ์€ ์ˆ˜์˜ ๋…น๋‚ด์žฅ ์•ˆ์•ฝ์ด ์ ์•ˆ๋œ ๊ฒฝ์šฐ, ๊ทธ๋ฆฌ๊ณ  ์‹œ์ˆ  ๋‹น์‹œ ๋ฐฑ๋‚ด์žฅ ๋‹จ๊ณ„๊ฐ€ ๋” ๋†’์•˜์„ ๊ฒฝ์šฐ ์‹œ์ˆ  6๊ฐœ์›” ํ›„ ์•ˆ์••์ด ์œ ์˜์ ์œผ๋กœ ๋†’๊ฒŒ ํ™•์ธ๋˜์—ˆ๋‹ค(p<0.05). ๊ฐ€์žฅ ํ”ํ•œ ๋ณตํ•ฉ์ฆ์€ ์•ˆ๋กœ(42.5%), ๋ฐฑ๋‚ด์žฅ์˜ ์ง„ํ–‰(30.1%), ๊ทธ๋ฆฌ๊ณ  ์•ˆ๋‚ด ์ถœํ˜ˆ(16.3%)๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ์—ฌ์„ฏ ๊ฐœ์˜ ์•ˆ๊ตฌ์—์„œ ์•ˆ๊ตฌ ์ ์ถœ์ˆ ์„ ์ง„ํ–‰ํ•˜์˜€์œผ๋ฉฐ, ๊ทธ ์ค‘ ์„ธ ๊ฐœ์˜ ์•ˆ๊ตฌ๋Š” ๊ฐ๋ง‰ ์ฒœ๊ณต์ด ๋ฐœ์ƒํ•˜์—ฌ ์•ˆ๊ตฌ ์ ์ถœ์ˆ ์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์œ ๋ฆฌ์ฒด ๋‚ด ์‹œ๋„ํฌ๋น„์–ด ์ฃผ์‚ฌ๋Š” ๋ง๊ธฐ ๋…น๋‚ด์žฅ ๊ฐœ์—์„œ ์žฅ๊ธฐ์ ์œผ๋กœ ์•ˆ์••์„ ๋‚ฎ์ถ”๋Š”๋ฐ ํšจ๊ณผ์ ์ด์—ˆ๋‹ค.Introduction 1 Materials and Methods 3 1. Patients 3 2. Glaucoma eye drops 4 3. Intravitreal cidofovir injection 4 4. Clinical data 5 5. Statistics 6 Results 7 Discussion 20 Conclusions 26 References 27 Abstract in Korean 31์„

    A study of Manuel de Falla's Siete canciones populares Espaรฑolas and Aaron Coplands Old american songs โ…ก

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์Œ์•…๋Œ€ํ•™ ์Œ์•…๊ณผ, 2023. 2. ์„œํ˜œ์—ฐ.๋ณธ ๋…ผ๋ฌธ์€ ํ•„์ž์˜ ์„์‚ฌ๊ณผ์ • ์กธ์—…์—ฐ์ฃผํšŒ ํ”„๋กœ๊ทธ๋žจ ์ค‘, ๋งˆ๋ˆ„์—˜ ๋ฐ ํŒŒ์•ผ(Manuel de Falla, 1876-1946)์˜ ๊ฐ€๊ณก ๋ชจ์Œ์ง‘ ์™€ ์•„๋ก  ์ฝ”ํ”Œ๋žœ๋“œ(Aaron Copland, 1900-1990)์˜ ๊ฐ€๊ณก ๋ชจ์Œ์ง‘ ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ์ด๋‹ค. ๋งˆ๋ˆ„์—˜ ๋ฐ ํŒŒ์•ผ(Manuel de Falla, 1876-1946)๋Š” ์ŠคํŽ˜์ธ์˜ ๋ฏผ์กฑ์  ์š”์†Œ์™€ ์ธ์ƒ์ฃผ์˜ ์Œ์•…์„ ๊ฒฐํ•ฉํ•˜์—ฌ ์ŠคํŽ˜์ธ์˜ ๊ทผ๋Œ€ ์Œ์•…์„ ์ด๋ˆ ์ž‘๊ณก๊ฐ€์ด๋‹ค. ๋Š” 1914๋…„๋ถ€ํ„ฐ 1915๋…„์— ์ž‘๊ณก๋œ ๊ณก์œผ๋กœ, ๋ฏผ์† ์•…๊ธฐ์˜ ์ฃผ๋ฒ•์„ ํ˜•์ƒํ™”ํ•œ ๋ฐ˜์ฃผ๋ถ€์™€ ์ŠคํŽ˜์ธ์˜ ์ •์„œ๋ฅผ ํ‘œํ˜„ํ•˜๋Š” ํ’๋ถ€ํ•œ ํ™”์„ฑ๊ณผ ์„ ๋ฒ•, ๋‹ค์–‘ํ•œ ์ŠคํŽ˜์ธ ์ง€๋ฐฉ์˜ ๋ฏผ์† ์Œ์•… ๋ฆฌ๋“ฌ๊ณผ ์„ ์œจ์  ํŠน์ง•์„ ๋ฐ˜์˜ํ•˜์—ฌ ์ŠคํŽ˜์ธ์˜ ์ •์„œ๋ฅผ ์„ธ๋ จ๋˜๊ณ  ๊ฐ๊ฐ์ ์œผ๋กœ ํ‘œํ˜„ํ–ˆ๋‹ค. ์•„๋ก  ์ฝ”ํ”Œ๋žœ๋“œ(Aaron Copland, 1900-1990)๋Š” ๋‹ค์–‘ํ•œ ์–‘์‹์„ ๋…น์—ฌ๋‚ธ ๋›ฐ์–ด๋‚œ ์ž‘ํ’ˆ๋“ค์„ ์ž‘๊ณกํ•˜์—ฌ ๋ฏธ๊ตญ ํ˜„๋Œ€์Œ์•…์˜ ์•„๋ฒ„์ง€๋กœ ๋ถˆ๋ฆฐ๋‹ค. ๋Š” 1952๋…„์— ์ž‘๊ณก๋œ ๊ณก์œผ๋กœ, ๋ฏธ๊ตญ์˜ ์˜› ์Œ์•…๋“ค์„ ์ฑ„๋ณดํ•˜์—ฌ ํŽธ๊ณกํ•ด ์—ฎ์€ ๋ชจ์Œ์ง‘์ด๋‹ค. ๋Œ€์ค‘๋“ค์ด ์ดํ•ดํ•˜๊ธฐ ์‰ฌ์šด ๊ฐ„๋‹จํ•œ ํ…์Šค์ฒ˜๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์˜จ์Œ๊ณ„์  ์„ ์œจ๊ณผ ํ™”์„ฑ์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ฐ ์ž‘ํ’ˆ์˜ ์ž‘๊ณก๊ฐ€์ธ ํŒŒ์•ผ์™€ ์ฝ”ํ”Œ๋žœ๋“œ์˜ ์ƒ์• ์™€ ์Œ์•…์  ๋ฐฐ๊ฒฝ์— ๋Œ€ํ•ด ์‚ดํŽด๋ณธ ํ›„, ๊ณก์˜ ๊ตฌ์„ฑ๊ณผ ์ž‘๊ณก๊ธฐ๋ฒ•์„ ๋ฐ”ํƒ•์œผ๋กœ ์—ฐ์ฃผ์˜ ๋ฐฉํ–ฅ์„ฑ์„ ์ œ์‹œํ•œ๋‹ค. ๊ณก์„ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•œ ๋ฐฐ๊ฒฝ์ง€์‹์„ ์ œ๊ณตํ•จ์œผ๋กœ์จ ์—ฐ์ฃผ์— ์‹ค์งˆ์ ์ธ ๋„์›€์„ ์ฃผ๊ณ ์ž ํ•œ๋‹ค.This is a study of Manuel de Falla (1876-1946)'s song collection and Aaron Copland (1900-1990)'s song collection . Manuel de Falla(1876-1946) is a composer who led modern Spanish music by combining Spanish ethnic elements and impressionistic music. is a song written from 1914 to 1915. The accompaniment that embodies the method of playing folk instruments, the harmony and mode that express Spanish emotions, and the rhythm and melody of various local folk music were used to express Spanish emotions in a sophisticated and sensuous manner. Aaron Copland(1900-1990) is called as the father of contemporary American music for his outstanding compositions covering a wide range of styles. was composed in 1952. This is a collection of songs arranged by collecting old American music. Based on a simple elements that make the public easy to understand, the diatonic melody and harmony were used. In this thesis, after studying the life and musical background of composers Falla and Copland, I propose how to perform this songs according to the form and composition technique of the song. The purpose of this thesis is to provide background knowledge about the songs so that you can understand the song and play it academically.โ… . ์„œ ๋ก  1 โ…ก. ๋ณธ ๋ก  3 1. Manuel de Falla์˜ Siete canciones populares Espaรฑolas 3 1.1. Manuel de Falla์˜ ์ƒ์•  3 1.2. Manuel de Falla์˜ ์Œ์•…์  ํŠน์ง• 5 1.3. Siete canciones populares Espaรฑolas ๋ถ„์„ 6 (1) El paรฑo moruno(๋ฌด์–ด์ธ์˜ ์˜ท๊ฐ) 6 (2) Seguidilla murciana(๋ฌด์–ด์ธ์˜ ์„ธ๊ธฐ๋””์•ผ) 12 (3) Asturiana(์•„์Šค๋šœ๋ฆฌ์•„ ์—ฌ์ธ) 17 (4) Jota(ํ˜ธ๋”ฐ) 22 (5) Nana(๋‚˜๋‚˜) 28 (6) Canciรณn(๋…ธ๋ž˜) 31 (7) Polo(ํด๋กœ) 35 2. Aaron Copland์˜ Old american songs โ…ก 40 2.1. Aaron Copland์˜ ์ƒ์•  40 2.2. Aaron Copland์˜ ์Œ์•…์  ํŠน์ง• 42 2.3. Old american songs โ…ก ๋ถ„์„ 45 (1) The Little Horses(์ž‘์€ ๋ง๋“ค) 47 (2) Zions Walls(์‹œ์˜จ์˜ ์„ฑ๋ฒฝ) 54 (3) The Golden Willow Tree(ํ™ฉ๊ธˆ๋น› ๋ฒ„๋“œ๋‚˜๋ฌด) 60 (4) At the River(๊ฐ•๊ฐ€์—์„œ) 67 (5) Ching-a-Ring Chaw(์นญ์–ด๋ง ์ตธ) 73 โ…ข. ๊ฒฐ๋ก  82 ์ฐธ๊ณ ๋ฌธํ—Œ 84 Abstract 87์„

    Brain Correlates of Response-Time Variability in Cognitive Control Task among Older Adults

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ์‚ฌํšŒ๊ณผํ•™๋Œ€ํ•™ ์‹ฌ๋ฆฌํ•™๊ณผ, 2017. 8. ์ตœ์ง„์˜.๊ฐœ์ธ ๋‚ด ๋ฐ˜์‘์†๋„ ๋ณ€์‚ฐ์„ฑ์€ ๋…ธํ™”์— ๋”ฐ๋ผ ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ง„ ํ–‰๋™์ง€ํ‘œ๋กœ, ์ธ์ง€๊ณผ์ œ์—์„œ ๊ด€์ฐฐ๋œ ๊ฐœ์ธ์˜ ๋ฐ˜์‘ ์†๋„๊ฐ€ ์–ผ๋งˆ๋‚˜ ๋น„์ผ๊ด€์ ์ธ์ง€ ์ธก์ •ํ•˜๋Š” ์ง€ํ‘œ์ด๋‹ค. ๋ฐ˜์‘์†๋„ ๋ณ€์‚ฐ์„ฑ์˜ ์ฆ๊ฐ€๋Š” ๋…ธํ™”์— ๋”ฐ๋ฅธ ์ „๋‘์˜์—ญ์˜ ๊ตฌ์กฐ์  ๋ณ€ํ™”๋ฅผ ๋ฐ˜์˜ํ•˜๋ฉฐ, ์ธ์ง€๋…ธํ™”์˜ ์–‘์ƒ์„ ์˜ˆ์ธกํ•˜๋Š” ์ง€ํ‘œ๋กœ์„œ ์ฃผ๋ชฉ๋ฐ›๊ธฐ ์‹œ์ž‘ํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๊ฐœ์ธ ๋‚ด ๋ฐ˜์‘์†๋„ ๋ณ€์‚ฐ์„ฑ์˜ ์ฆ๊ฐ€๊ฐ€ ์–ด๋–ค ๋‡Œ ๊ธฐ๋Šฅ์  ํ™œ์„ฑํ™”์— ๊ธฐ๋ฐ˜ํ•˜๊ณ  ์žˆ๋Š”์ง€๋ฅผ ๋ฐํžŒ ์—ฐ๊ตฌ๋Š” ๋ถ€์กฑํ•˜๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ฑด๊ฐ•ํ•œ ๋…ธ์ธ 52๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ๋‹ค์ค‘๊ฐ„์„ญ๊ณผ์ œ(multi-source interference taskMSIT)๋ฅผ ์‹ค์‹œํ•จ๊ณผ ๋™์‹œ์— ์ž๊ธฐ๊ณต๋ช…์˜์ƒ์„ ํ†ตํ•ด ๋‡Œ ๊ธฐ๋Šฅ์  ํ™œ์„ฑํ™” ์–‘์ƒ์„ ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ๊ตฌ์ฒด์ ์œผ๋กœ MSIT์—์„œ ์–ป์€ ๊ฐœ์ธ ๋‚ด ๋ฐ˜์‘์†๋„ ๋ณ€์‚ฐ์„ฑ ์ง€ํ‘œ์™€ MSIT์˜ ์„ฑ๊ณต์  ์ˆ˜ํ–‰์—ฌ๋ถ€๋ฅผ ๋ฐ˜์˜ํ•˜๋Š” ๊ฐ„์„ญ ๋Œ€ ํ†ต์ œ ์กฐ๊ฑด ๊ฐ„ ๋ฐ˜์‘์†๋„ ์ฐจ์ด ์ง€ํ‘œ๊ฐ€ ๊ธฐ๋ฐ˜ํ•˜๊ณ  ์žˆ๋Š” ๋‡Œ ์˜์—ญ์„ ํƒ์ƒ‰ํ•˜์˜€๋‹ค. ๋”ํ•˜์—ฌ ๋‘ ๊ฐ€์ง€ ์ง€ํ‘œ์˜ ์‹ ๊ฒฝ์‹ฌ๋ฆฌ์  ํŠน์„ฑ์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ์ธ์ง€ํ†ต์ œ ๊ธฐ๋Šฅ์„ ์ธก์ •ํ•˜๋Š” ์‹ ๊ฒฝ์‹ฌ๋ฆฌ์ธก์ •์น˜๋“ค๊ณผ์˜ ์ƒ๊ด€ ๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. MSIT์˜ ํ–‰๋™์ˆ˜ํ–‰ ์ง€ํ‘œ์˜ ์‹ ๊ฒฝ๊ธฐ๋ฐ˜์„ ํƒ์ƒ‰ํ•˜๊ธฐ ์œ„ํ•œ ๋ถ„์„์˜ ๊ฒฐ๊ณผ๋Š” ๊ฐ ์ง€ํ‘œ๊ฐ€ ๋‹ค๋ฅธ ๋‡Œ ์˜์—ญ์˜ ๊ธฐ๋Šฅ์  ํ™œ์„ฑํ™”์— ๊ธฐ๋ฐ˜ํ•˜๊ณ  ์žˆ์Œ์„ ๋‚˜ํƒ€๋ƒˆ๋‹ค. ๊ฐœ์ธ ๋‚ด ๋ฐ˜์‘์†๋„ ๋ณ€์‚ฐ์„ฑ ์ง€ํ‘œ์˜ ๋ถ„์„ ๊ฒฐ๊ณผ, ์ขŒ์ธก ํ•˜์ „๋‘ํšŒ(inferior frontal gyrus) ์˜์—ญ์˜ ํ™œ์„ฑํ™” ์ˆ˜์ค€์ด ํด์ˆ˜๋ก ๋ฐ˜์‘์†๋„์˜ ๋ณ€์‚ฐ์„ฑ์ด ๋” ํฐ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ, ์กฐ๊ฑด ๊ฐ„ ๋ฐ˜์‘์†๋„ ์ฐจ์ด ์ง€ํ‘œ ๋ถ„์„์—์„œ๋Š” ์ธ์ง€ํ†ต์ œ ๊ธฐ๋Šฅ์— ๊ด€์—ฌํ•˜๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ง„ ๋‡Œ ์˜์—ญ๋“ค์˜ ํ™œ์„ฑํ™” ์ˆ˜์ค€์ด ๋” ํด์ˆ˜๋ก ์กฐ๊ฑด ๊ฐ„ ๋ฐ˜์‘์†๋„ ์ฐจ์ด ์ง€ํ‘œ๋กœ ์ธก์ •๋œ ํ–‰๋™์ˆ˜ํ–‰์€ ๋” ์„ฑ๊ณต์ ์ธ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์œ„์˜ ๋ถ„์„์—์„œ ํ™œ์„ฑํ™”๋œ ์˜์—ญ๋“ค์€ ์ค‘์ „๋‘ํšŒ(middle frontal gyrus), ํ•˜์ „๋‘ํšŒ(inferior frontal gyrus), ์„ฌ์—ฝ(insula lobe) ๋“ฑ์„ ํฌํ•จ ํ•˜์˜€๋‹ค. ๋‘ ์ง€ํ‘œ๋ฅผ ๋น„๊ตํ•˜๊ธฐ ์œ„ํ•ด ํƒ์ƒ‰์ ์œผ๋กœ ์‹ค์‹œํ•œ ๋‘ ์ง€ํ‘œ๊ฐ„์˜ ์ƒํ˜ธ์ž‘์šฉ์„ ํ™•์ธํ•˜๋Š” ๋ถ„์„ ๊ฒฐ๊ณผ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ๊ฐœ์ธ ๋‚ด ๋ฐ˜์‘์†๋„์˜ ๋ณ€์‚ฐ์„ฑ์ด ์ž‘์€ ๋…ธ์ธ์˜ ๊ฒฝ์šฐ ๋ฐฐ์ธก ์ „๋Œ€์ƒํšŒํ”ผ์งˆ(dorsal anterior cingulate cortex)์˜ ํ™œ์„ฑํ™” ์ˆ˜์ค€์ด ์ž‘์„์ˆ˜๋ก ์กฐ๊ฑด ๊ฐ„ ๋ฐ˜์‘์†๋„๋กœ ์ธก์ •ํ•œ ํ–‰๋™์ˆ˜ํ–‰์ด ๋” ์„ฑ๊ณต์ ์ธ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚œ ๋ฐ˜๋ฉด, ๊ฐœ์ธ ๋‚ด ๋ฐ˜์‘์†๋„์˜ ๋ณ€์‚ฐ์„ฑ์ด ํฐ ๋…ธ์ธ์˜ ๊ฒฝ์šฐ ๋ฐฐ์ธก์ „๋Œ€์ƒํ”ผ์งˆ์„ ๋” ๋งŽ์ด ํ™œ์„ฑํ™” ์‹œํ‚ค๋Š” ๊ฒƒ์ด ๋” ์„ฑ๊ณต์ ์ธ ์ธ์ง€ํ†ต์ œ ์ˆ˜ํ–‰์„ ์˜ˆ์ธกํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋‘ ์ง€ํ‘œ์˜ ์‹ ๊ฒฝ์‹ฌ๋ฆฌ์  ํŠน์„ฑ์„ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•ด ์‹ค์‹œํ•œ ํ–‰๋™์ˆ˜์ค€ ๋ถ„์„์˜ ๊ฒฐ๊ณผ, ๊ฐœ์ธ ๋‚ด ๋ฐ˜์‘์†๋„ ๋ณ€์‚ฐ์„ฑ์ด ํด์ˆ˜๋ก Stroop-์ƒ‰์ƒ ๋‹จ์–ด ๊ฒ€์‚ฌ์˜ ๊ฐ„์„ญ์ง€์ˆ˜๊ฐ€ ๋†’์•˜์œผ๋‚˜, ์กฐ๊ฑด ๊ฐ„ ๋ฐ˜์‘์†๋„ ์ฐจ์ด ์ง€ํ‘œ์™€ ์‹ ๊ฒฝ์‹ฌ๋ฆฌํ‰๊ฐ€ ๊ฒฐ๊ณผ์—์„œ๋Š” ์œ ์˜ํ•œ ์ƒ๊ด€์ด ๊ด€์ฐฐ๋˜์ง€ ์•Š์•˜๋‹ค. ์ด๋Ÿฌํ•œ ๋‡Œ ๋ฐ ํ–‰๋™ ๋ถ„์„์˜ ๊ฒฐ๊ณผ๋“ค์€ ์กฐ๊ฑด ๊ฐ„ ๋ฐ˜์‘์†๋„ ์ฐจ์ด ๋ฐ ๊ฐœ์ธ๋‚ด ๋ฐ˜์‘์†๋„ ๋ณ€์‚ฐ์„ฑ ์ง€ํ‘œ๊ฐ€ ์„œ๋กœ ๋‹ค๋ฅธ ๋‡Œ ๊ธฐ๋Šฅ์— ๊ธฐ๋ฐ˜ํ•˜๊ณ  ์žˆ์ง€๋งŒ, ์„œ๋กœ ๋ฐ€์ ‘ํ•˜๊ฒŒ ์ƒํ˜ธ์ž‘์šฉ ํ•œ๋‹ค๋Š” ๊ฒƒ์„ ์‹œ์‚ฌํ•œ๋‹ค. ๋‚˜์•„๊ฐ€ ๊ฐœ์ธ ๋‚ด ๋ฐ˜์‘์†๋„ ๋ณ€์‚ฐ์„ฑ ์ฐจ์ด์™€ ํ•จ๊ป˜ ๊ด€์ฐฐ๋œ ๋‡Œ๊ธฐ๋Šฅ ํ™œ์„ฑํ™”๊ฐ€ ๋ฐ˜์˜ํ•˜๋Š” ๋…ธํ™”์˜ ํŠน์„ฑ์— ๋Œ€ํ•œ ๋…ผ์˜์™€ ์ถ”ํ›„ ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ์ด ์ œ๊ธฐ๋˜์—ˆ๋‹ค.1. ์„œ๋ก  1 1.1 ์ธ์ง€ํ†ต์ œ ๊ธฐ๋Šฅ๊ณผ ๋…ธํ™” 1 1.2 ์ธ์ง€ํ†ต์ œ ๊ธฐ๋Šฅ์˜ ๋Œ€๋‡Œ ๊ธฐ์ „๊ณผ ๋…ธํ™” 3 1.3 ์ธ์ง€ํ†ต์ œ ๊ธฐ๋Šฅ์˜ ์ธก์ • 5 1.4 ๋ฌธ์ œ์ œ๊ธฐ ๋ฐ ์—ฐ๊ตฌ ๋ชฉ์  8 2. ๋ฐฉ๋ฒ• 10 2.1 ์ฐธ๊ฐ€์ž 10 2.2 ์ธก์ •๋„๊ตฌ 11 2.3 ์ ˆ์ฐจ 15 2.4 ๋ถ„์„ 16 3. ๊ฒฐ๊ณผ 20 3.1 ํ–‰๋™์ง€ํ‘œ ๋ถ„์„ 20 3.2 ๋‡Œ ๊ธฐ๋Šฅ ํ™œ์„ฑํ™” ๋ถ„์„ 25 4. ๋…ผ์˜ 33 4.1 ์ ˆ ๊ฒฐ๊ณผ์˜ ํ•ด์„ 34 4.2 ์—ฐ๊ตฌ์˜ ์˜์˜ ๋ฐ ํ•œ๊ณ„์  37 ์ฐธ๊ณ ๋ฌธํ—Œ 40 Abstract 47Maste

    An Analysis of Pre-service Science Teachersโ€™ NOS Lesson Planning and Demonstration: In the Context of โ€˜Science Inquiry Experimentโ€™ Developed Under the 2015 Revised National Curriculum

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    In this study, we investigated pre-service science teachers&apos; NOS-PCK by analyzing their NOS lesson planning and demonstration. Four pre-service science teachers participated in the study. They planned and demonstrated NOS lessons in the context of &apos;Science Inquiry Experiment&apos; developed under the 2015 Revised National Curriculum. Their lessons were observed. All of the teaching-learning materials were collected, and semi-structured interviews were also conducted. The analyses of the result revealed that pre-service teachers mainly referred to the curriculum and textbooks when selecting the NOS learning objectives. However, they felt difficulty because the curriculum and textbooks did not clearly present the NOS to be dealt. Although all of them took explicit approaches, there were not many open and divergent reflective approaches. In addition, they expected that high school students would consider scientific knowledge absolute and would have negative perceptions of NOS lessons. They rarely assessed students&apos; NOS learning, and were reluctant to assess. Finally, most of them had a negative perception that learning NOS is not necessary for all students. On the bases of the results, educational implications for improving the expertise of pre-service science teachers in NOS lessons were discussed.N

    ๋‹ค์ˆ˜์˜ ๋ชฉํ‘œ ์œ ์ „์ž๋ฅผ ๊ฒ€์ถœํ•  ์ˆ˜ ์žˆ๋Š” ํŠน์ด์„ฑ ์กฐ๊ฑด์„ ๋งŒ์กฑํ•˜๋Š” ์œ ํšจํ•œ primer ์„ธํŠธ์™€ probe ์„ธํŠธ๋ฅผ ํ•œ๊บผ๋ฒˆ์— ๋น ๋ฅด๊ฒŒ ์„ค๊ณ„ํ•  ์ˆ˜ ์žˆ๋Š” ์›น ๊ธฐ๋ฐ˜ ์‹œ์Šคํ…œ

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    <p id=1. A method of designing a valid primer pair satisfying a specificity condition, the method comprising: receiving a query language associated with a gene and primer-related filtering conditions;searching for an identifier of at least one base sequence from a provided genetic information index based on the query language;searching for at least one candidate primer from a provided candidate primer set index to satisfy the specificity condition based on the identifier of the at least one base sequence;filtering the at least one candidate primer based on the filtering conditions; andproviding information about a primer pair satisfying the query language and the filtering conditions based on a result of the filtering

    Method for rapid design of valid high-quality primers and probes for multiple target genes in qPCR experiments

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    ๋ณธ ๋ฐœ๋ช…์€ ์œ ์ „์ž์— ๊ด€ํ•œ ์งˆ์˜์–ด ๋ฐ ํ”„๋ผ์ด๋จธ์— ๊ด€ํ•œ ํ•„ํ„ฐ๋ง ์ œ์•ฝ์กฐ๊ฑด๋“ค์„ ์ˆ˜์‹ ํ•˜๊ณ , ์งˆ์˜์–ด์— ๊ธฐ์ดˆํ•˜์—ฌ, ๋ฏธ๋ฆฌ ๊ตฌ๋น„๋œ ์œ ์ „์ž ์ •๋ณด ์ƒ‰์ธ์œผ๋กœ๋ถ€ํ„ฐ ์ ์–ด๋„ ํ•˜๋‚˜์˜ ์—ผ๊ธฐ ์„œ์—ด์˜ ์‹๋ณ„์ž๋ฅผ ๊ฒ€์ƒ‰ํ•˜๊ณ , ์ ์–ด๋„ ํ•˜๋‚˜์˜ ์—ผ๊ธฐ ์„œ์—ด์˜ ์‹๋ณ„์ž์— ๊ธฐ์ดˆํ•˜์—ฌ, ํŠน์ด์„ฑ ์กฐ๊ฑด์„ ๋งŒ์กฑํ•˜๋„๋ก ๋ฏธ๋ฆฌ ๊ตฌ๋น„๋œ ํ›„๋ณด ํ”„๋ผ์ด๋จธ ์ง‘ํ•ฉ์˜ ์ƒ‰์ธ์œผ๋กœ๋ถ€ํ„ฐ ์ ์–ด๋„ ํ•˜๋‚˜์˜ ํ›„๋ณด ํ”„๋ผ์ด๋จธ๋ฅผ ๊ฒ€์ƒ‰ํ•˜๊ณ , ํ•„ํ„ฐ๋ง ์ œ์•ฝ์กฐ๊ฑด๋“ค์— ๊ธฐ์ดˆํ•˜์—ฌ, ์ ์–ด๋„ ํ•˜๋‚˜์˜ ํ›„๋ณด ํ”„๋ผ์ด๋จธ๋ฅผ ํ•„ํ„ฐ๋งํ•˜๊ณ , ํ•„ํ„ฐ๋ง ๊ฒฐ๊ณผ์— ๊ธฐ์ดˆํ•˜์—ฌ, ์งˆ์˜์–ด ๋ฐ ํ•„ํ„ฐ๋ง ์ œ์•ฝ์กฐ๊ฑด๋“ค์„ ๋งŒ์กฑํ•˜๋Š” ํ”„๋ผ์ด๋จธ ์Œ์— ๊ด€ํ•œ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ๋‹ค.์œ ์ „์ž์— ๊ด€ํ•œ ์งˆ์˜์–ด ๋ฐ ํ”„๋ผ์ด๋จธ์— ๊ด€ํ•œ ํ•„ํ„ฐ๋ง ์ œ์•ฝ์กฐ๊ฑด๋“ค์„ ์ˆ˜์‹ ํ•˜๋Š” ๋‹จ๊ณ„;์ƒ๊ธฐ ์งˆ์˜์–ด์— ๊ธฐ์ดˆํ•˜์—ฌ, ๋ฏธ๋ฆฌ ๊ตฌ๋น„๋œ ์œ ์ „์ž ์ •๋ณด ์ƒ‰์ธ์œผ๋กœ๋ถ€ํ„ฐ ์ ์–ด๋„ ํ•˜๋‚˜์˜ ์—ผ๊ธฐ ์„œ์—ด์˜ ์‹๋ณ„์ž๋ฅผ ๊ฒ€์ƒ‰ํ•˜๋Š” ๋‹จ๊ณ„;์ƒ๊ธฐ ์ ์–ด๋„ ํ•˜๋‚˜์˜ ์—ผ๊ธฐ ์„œ์—ด์˜ ์‹๋ณ„์ž์— ๊ธฐ์ดˆํ•˜์—ฌ, ํŠน์ด์„ฑ ์กฐ๊ฑด์„ ๋งŒ์กฑํ•˜๋„๋ก ๋ฏธ๋ฆฌ ๊ตฌ๋น„๋œ ํ›„๋ณด ํ”„๋ผ์ด๋จธ ์ง‘ํ•ฉ์˜ ์ƒ‰์ธ์œผ๋กœ๋ถ€ํ„ฐ ์ ์–ด๋„ ํ•˜๋‚˜์˜ ํ›„๋ณด ํ”„๋ผ์ด๋จธ๋ฅผ ๊ฒ€์ƒ‰ํ•˜๋Š” ๋‹จ๊ณ„;์ƒ๊ธฐ ํ•„ํ„ฐ๋ง ์ œ์•ฝ์กฐ๊ฑด๋“ค์— ๊ธฐ์ดˆํ•˜์—ฌ, ์ƒ๊ธฐ ์ ์–ด๋„ ํ•˜๋‚˜์˜ ํ›„๋ณด ํ”„๋ผ์ด๋จธ๋ฅผ ํ•„ํ„ฐ๋งํ•˜๋Š” ๋‹จ๊ณ„; ๋ฐ์ƒ๊ธฐ ํ•„ํ„ฐ๋ง ๊ฒฐ๊ณผ์— ๊ธฐ์ดˆํ•˜์—ฌ, ์ƒ๊ธฐ ์งˆ์˜์–ด ๋ฐ ์ƒ๊ธฐ ํ•„ํ„ฐ๋ง ์ œ์•ฝ์กฐ๊ฑด๋“ค์„ ๋งŒ์กฑํ•˜๋Š” ํ”„๋ผ์ด๋จธ ์Œ์— ๊ด€ํ•œ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•˜๋Š” ๋‹จ๊ณ„๋ฅผ ํฌํ•จํ•˜๋Š”, ํŠน์ด์„ฑ ์กฐ๊ฑด์„ ๋งŒ์กฑํ•˜๋Š” ์œ ํšจํ•œ ํ”„๋ผ์ด๋จธ ์Œ์„ ๋””์ž์ธํ•˜๋Š” ๋ฐฉ๋ฒ•

    Method for rapid design of valid high-quality primers and probes for multiple target genes in qPCR experiments

    No full text
    ๋ณธ ๋ฐœ๋ช…์€ ๋‹ค์ˆ˜์˜ ๋ชฉํ‘œ ์œ ์ „์ž๋ฅผ ๊ฒ€์ถœํ•  ์ˆ˜ ์žˆ๋Š” ํŠน์ด์„ฑ ์กฐ๊ฑด์„ ๋งŒ์กฑํ•˜๋Š” ์œ ํšจํ•œ ํ”„๋ผ์ด๋จธ ์„ธํŠธ์™€ ํ”„๋ฃจ๋ธŒ ์„ธํŠธ๋ฅผ ํ•œ๊บผ๋ฒˆ์— ๋น ๋ฅด๊ฒŒ ์„ค๊ณ„ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•œ ๋ฐฉ๋ฒ•์— ๊ด€ํ•œ ๊ฒƒ์œผ๋กœ์„œ, ์ƒ๊ธฐ ๋ฐฉ๋ฒ•์€, ๋Œ€๊ทœ๋ชจ DNA ์„œ์—ด ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค์— ๋Œ€ํ•œ ํ•˜๋‘ก ๊ธฐ๋ฐ˜์˜ ์˜คํ”„๋ผ์ธ ์—ฐ์‚ฐ์„ ํ†ตํ•ด ๊ฐ€๋Šฅํ•œ ๋ชจ๋“  ์œ ์ „์ž ์Œ์— ๋Œ€ํ•ด ํŠน์ด์„ฑ ์กฐ๊ฑด์„ ๋งŒ์กฑํ•˜๋Š” ํ›„๋ณด ํ”„๋ผ์ด๋จธ ์ง‘ํ•ฉ๊ณผ ํ”„๋ฃจ๋ธŒ ์ง‘ํ•ฉ์„ ์ถ”์ถœํ•˜๋Š” ์ œ 1 ๋‹จ๊ณ„; ์ƒ๊ธฐ ์ œ 1๋‹จ๊ณ„์—์„œ ์ถ”์ถœํ•œ ํ›„๋ณด ํ”„๋ผ์ด๋จธ ์ง‘ํ•ฉ๊ณผ ํ”„๋ฃจ๋ธŒ ์ง‘ํ•ฉ์„ ์ด์šฉํ•˜์—ฌ ํŠน์ด์„ฑ ๊ฒ€์‚ฌ๋ฅผ ํ•  ์ˆ˜ ์žˆ๋Š” ์ƒ‰์ธ ๊ตฌ์กฐ๋ฅผ ๋ฉ”์ธ ๋ฉ”๋ชจ๋ฆฌ ์ƒ์—์„œ ๊ตฌ์„ฑํ•˜๋Š” ์ œ 2 ๋‹จ๊ณ„; ์ƒ๊ธฐ ์ œ 2 ๋‹จ๊ณ„์—์„œ ๊ตฌ์„ฑ๋œ ์ƒ‰์ธ ๊ตฌ์กฐ๋ฅผ ์ด์šฉํ•˜์—ฌ ์‚ฌ์šฉ์ž์— ์˜ํ•ด ์ฃผ์–ด์ง„ ๋‹ค์ˆ˜์˜ ๋ชฉํ‘œ ์œ ์ „์ž๋“ค์˜ ๊ฐ๊ฐ์„ ๊ฒ€์ถœํ•  ์ˆ˜ ์žˆ๋Š” ์‹ฑ๊ธ€/ํŽ˜์–ด ํ•„ํ„ฐ๋ง ์ œ์•ฝ์กฐ๊ฑด๋“ค์„ ๋งŒ์กฑํ•˜๋Š” ์œ ํšจํ•œ ํ”„๋ผ์ด๋จธ ์ง‘ํ•ฉ๊ณผ ํ”„๋ฃจ๋ธŒ ์ง‘ํ•ฉ์„ ์˜จ๋ผ์ธ ์—ฐ์‚ฐ์„ ํ†ตํ•ด ๋น ๋ฅด๊ฒŒ ๊ฒ€์ƒ‰ํ•œ ํ›„, ๊ฐ ํ‘œ์  ์œ ์ „์ž๋ฅผ ์œ„ํ•œ ์ตœ์ ์˜ ํ”„๋ผ์ด๋จธ ์Œ๊ณผ ํ”„๋ฃจ๋ธŒ๋งŒ์„ ์„ ๋ณ„ํ•˜์—ฌ ์›น ํŽ˜์ด์ง€๋กœ ์ถœ๋ ฅํ•˜๋Š” ์ œ3 ๋‹จ๊ณ„๋ฅผ ํฌํ•จํ•œ๋‹ค.๋Œ€๊ทœ๋ชจ DNA ์„œ์—ด ๋ฐ์ดํ„ฐ๋ฒ ์ด์Šค์— ๋Œ€ํ•œ ํ•˜๋‘ก ๊ธฐ๋ฐ˜์˜ ์˜คํ”„๋ผ์ธ ์—ฐ์‚ฐ์„ ํ†ตํ•ด ๊ฐ€๋Šฅํ•œ ๋ชจ๋“  ์œ ์ „์ž ์Œ์— ๋Œ€ํ•ด ํŠน์ด์„ฑ ์กฐ๊ฑด์„ ๋งŒ์กฑํ•˜๋Š” ํ›„๋ณด ํ”„๋ผ์ด๋จธ ์ง‘ํ•ฉ๊ณผ ํ”„๋ฃจ๋ธŒ ์ง‘ํ•ฉ์„ ์ถ”์ถœํ•˜๋Š” ์ œ 1 ๋‹จ๊ณ„;์ƒ๊ธฐ ์ œ 1๋‹จ๊ณ„์—์„œ ์ถ”์ถœํ•œ ํ›„๋ณด ํ”„๋ผ์ด๋จธ ์ง‘ํ•ฉ๊ณผ ํ”„๋ฃจ๋ธŒ ์ง‘ํ•ฉ์„ ์ด์šฉํ•˜์—ฌ ํŠน์ด์„ฑ ๊ฒ€์‚ฌ๋ฅผ ํ•  ์ˆ˜ ์žˆ๋Š” ์ƒ‰์ธ ๊ตฌ์กฐ๋ฅผ ๋ฉ”์ธ ๋ฉ”๋ชจ๋ฆฌ ์ƒ์—์„œ ๊ตฌ์„ฑํ•˜๋Š” ์ œ 2 ๋‹จ๊ณ„; ์ƒ๊ธฐ ์ œ 2 ๋‹จ๊ณ„์—์„œ ๊ตฌ์„ฑ๋œ ์ƒ‰์ธ ๊ตฌ์กฐ๋ฅผ ์ด์šฉํ•˜์—ฌ ์‚ฌ์šฉ์ž์— ์˜ํ•ด ์ฃผ์–ด์ง„ ๋‹ค์ˆ˜์˜ ๋ชฉํ‘œ ์œ ์ „์ž๋“ค์˜ ๊ฐ๊ฐ์„ ๊ฒ€์ถœํ•  ์ˆ˜ ์žˆ๋Š” ์‹ฑ๊ธ€/ํŽ˜์–ด ํ•„ํ„ฐ๋ง ์ œ์•ฝ์กฐ๊ฑด๋“ค์„ ๋งŒ์กฑํ•˜๋Š” ์œ ํšจํ•œ ํ”„๋ผ์ด๋จธ ์ง‘ํ•ฉ๊ณผ ํ”„๋ฃจ๋ธŒ ์ง‘ํ•ฉ์„ ์˜จ๋ผ์ธ ์—ฐ์‚ฐ์„ ํ†ตํ•ด ๋น ๋ฅด๊ฒŒ ๊ฒ€์ƒ‰ํ•œ ํ›„, ๊ฐ ํ‘œ์  ์œ ์ „์ž๋ฅผ ์œ„ํ•œ ์ตœ์ ์˜ ํ”„๋ผ์ด๋จธ ์Œ๊ณผ ํ”„๋ฃจ๋ธŒ๋งŒ์„ ์„ ๋ณ„ํ•˜์—ฌ ์›น ํŽ˜์ด์ง€๋กœ ์ถœ๋ ฅํ•˜๋Š” ์ œ3 ๋‹จ๊ณ„๋ฅผ ํฌํ•จํ•˜๋Š” ๋‹ค์ˆ˜์˜ ๋ชฉํ‘œ ์œ ์ „์ž๋ฅผ ๊ฒ€์ถœํ•  ์ˆ˜ ์žˆ๋Š” ํŠน์ด์„ฑ ์กฐ๊ฑด์„ ๋งŒ์กฑํ•˜๋Š” ์œ ํšจํ•œ ํ”„๋ผ์ด๋จธ ์„ธํŠธ์™€ ํ”„๋ฃจ๋ธŒ ์„ธํŠธ๋ฅผ ๋™์‹œ์— ๋””์ž์ธํ•˜๋Š” ๋ฐฉ๋ฒ•
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