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    ๋ชฝ๊ณจ ๋ถ๋ถ€์— ์œ„์น˜ํ•œ ์—๋ฅด๋ฐ๋„ท ์˜ค๋ณด ๋ฐ˜์•” ๋™-๋ชฐ๋ฆฌ๋ธŒ๋ด ๊ด‘์ƒ๊ณผ ์ค€๋ชจ๋“œ ์ง€์—ญ ์กฐ์‚ฐํ˜• ๊ธˆ ๊ด‘์ƒ์˜ ์ง€์งˆํ•™, ๊ด‘๋ฌผํ•™ ๋ฐ ์•ˆ์ •๋™์œ„์›์†Œ ์ง€๊ตฌํ™”ํ•™ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์ž์—ฐ๊ณผํ•™๋Œ€ํ•™ ์ง€๊ตฌํ™˜๊ฒฝ๊ณผํ•™๋ถ€, 2019. 2. ์ด์ธ์„ฑ.This study reports geological, mineralogical and stable isotope geochemical results of porphyry Cu-Mo deposit and orogenic gold deposit in northern Mongolia. The former is the Erdenetiin Ovoo deposit located in Orkhon province and the latter is the Dzuunmod gold area deposit in Selenge province. Both deposits have large tonnage of Cu, Mo and Au, and been mined for a long time. Compared to many geological studies about petrographic and mineralogical characteristic of both deposits, few researches have been conducted for ore genesis and material sources. Based on geological, mineralogical and stable isotope geochemical measurements, therefore, this study focuses on the ore genesis and sources of metal and sulfur, implying for deposit origin and mineral exploration. The copper (ฮด65Cu) and sulfur (ฮด34S) isotope compositions of ore minerals from the Erdenetiin Ovoo porphyry Cu-Mo deposit in northern Mongolia were measured. The ฮด65Cu values of Cu (I) sulfide minerals ranged from 0.14 โ€ฐ to 2.69 โ€ฐ, suggesting that Cu predominantly originated from magmatic sources, whereas Cu (II) minerals such as chrysocolla, malachite and azurite presented much larger variations of ฮด65Cu values from -1.01 โ€ฐ to 10.0 โ€ฐ. The small difference between the primary and secondary Cu sulfide minerals indicates an insignificant influence of Cu isotope fractionation processes during their formation, which may be explained by large mass transport and/or the involvement of biogenic activities. The ฮด65Cu values of primary chalcopyrite suggest source heterogeneity and/or the occurrence of isotope fractionation under a high-temperature environment. The positive ฮ”Cu (II) mineral โ€“ Cu (I) mineral values imply little transport of Cu in the deposit, with a rough mass balance and fast redox reaction. The ฮด34S values of the primary sulfide minerals (pyrite, molybdenite and chalcopyrite) clustered near 0 โ€ฐ, indicating that the sulfur is mainly derived from a homogeneous magmatic source. By contrast, the ฮด34S values of secondary Cu sulfide minerals ranged from -3.2 โ€ฐ to -0.3 โ€ฐ, with an average of -1.6 โ€ฐ. The lower ฮด34S values are likely influenced by either S isotope fractionation processes or input of sulfur with different S isotope compositions during their formation. The measured ฮด65Cu and ฮด34S values of these ore minerals suggest a large mass transportation of Cu to an adjacent location, indicating little possibility of a hidden Cu occurrence in the Erdenetiin Ovoo deposit area. The Dzuunmod gold area located in the North Khentii Gold belt (NKGB) of Central Northern Mongolia includes lode gold deposits such as Gatsuurt, Boroo, Sujigtei, Ereen and Ulaanbulag with several gold occurrences. These show similar alteration types and ore mineral assemblages, where sericite, siliceous and potassic alteration assemblages are major hydrothermal alteration types. Pyrite and arsenopyrite are main sulfide minerals with minor amount of galena, sphalerite and chalcopyrite. Gold occurs as native form and invisible gold in pyrite and arsenopyrite. The major sulfide minerals are separated into earlier non-auriferous stage and later auriferous grains containing invisible gold. Native gold postdates the major sulfide mineralization. Gold and arsenic content of pyrite grains indicates that gold exists mainly as solid solution form (Au+1) in the Gatsuurt and Boroo deposit whereas gold nanoparticle (Au0) is present in the Sujigtei deposit. High Co/Ni and Mo/Ni ratios of pyrite grain suggest a post-sedimentary or hydrothermal origin and the ore-forming fluid was significantly affected by fluid-rock interaction during mineralization processes. Large variation of ฮด34S values of pyrite and arsenopyrite from -2.6 โ€ฐ to 17.2 โ€ฐ indicates that sulfur seems to be mainly derived from a source with heterogeneous sulfur isotope composition, which is the pyrite-bearing sediment mainly produced by the reduction of seawater sulfate. Consistent with geological evidence, relatively positive ฮด34S values suggest that sulfidation plays an important role for gold and sulfide precipitation. The calculated ฮด18O values of hydrothermal fluid from the measured ฮด18O values of quartz samples (from 14.7 โ€ฐ to 17.7 โ€ฐ) indicate that a metamorphic derivation of ore-forming fluid. Based on the observation and analytical results in this study, gold mineralization processes seem to occur several times by multiple input of hydrothermal fluid, fluid-rock interactions and mixing of ore-forming fluids. Therefore, the gold deposits in the Dzuunmod area is considered to be orogenic gold type influenced by fluid-rock interactions in the deposit area.์ด ๋…ผ๋ฌธ์€ ๋ชฝ๊ณจ ๋ถ๋ถ€์— ์œ„์น˜ํ•œ ์—๋ฅด๋ฐ๋„ทํ‹ด ์˜ค๋ณด ๋ฐ˜์•” ๋™-๋ชฐ๋ฆฌ๋ธŒ๋ด ๊ด‘์ƒ๊ณผ ์ค€ ๋ชจ๋“œ ์ง€์—ญ ์กฐ์‚ฐํ˜• ๊ธˆ ๊ด‘์ƒ์˜ ์ง€์งˆํ•™, ๊ด‘๋ฌผํ•™ ๋ฐ ์•ˆ์ •๋™์œ„์›์†Œ ์ง€๊ตฌํ™”ํ•™ ์—ฐ๊ตฌ์ด๋‹ค. ๋‘ ๊ด‘์ƒ ๋ชจ๋‘ ๋งŽ์€ ๊ตฌ๋ฆฌ, ๋ชฐ๋ฆฌ๋ธŒ๋ด ๋ฐ ๊ธˆ ๋งค์žฅ๋Ÿ‰์„ ๊ฐ–๊ณ  ์žˆ์œผ๋ฉฐ, ์˜ค๋žœ ๊ธฐ๊ฐ„ ๋™์•ˆ ๊ฐœ๋ฐœ๋˜์–ด ์™”๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์•”์„ํ•™ ๋ฐ ๊ด‘๋ฌผํ•™์  ํŠน์ง•์„ ํŒŒ์•…ํ•˜๊ธฐ ์œ„ํ•œ ์—ฐ๊ตฌ์— ๋น„ํ•ด ๊ด‘์ƒ์˜ ์„ฑ์ธ๊ณผ ๋ฌผ์งˆ๋“ค์˜ ๊ธฐ์›์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ๊ฑฐ์˜ ์ˆ˜ํ–‰๋˜์ง€ ๋ชปํ•˜์˜€๋‹ค. ๋”ฐ๋ผ์„œ ์ด๋ฒˆ ์—ฐ๊ตฌ์—์„œ๋Š” ์ง€์งˆํ•™, ๊ด‘๋ฌผํ•™ ๋ฐ ์•ˆ์ •๋™์œ„์›์†Œ ์ง€๊ตฌํ™”ํ•™ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ๊ด‘์ƒ์˜ ์„ฑ์ธ๊ณผ ๊ธˆ์† ๋ฐ ํ™ฉ์˜ ๊ธฐ์› ์ถ”์ ์„ ํ†ตํ•ด ๊ด‘์ƒ์˜ ๊ธฐ์›๊ณผ ๊ด‘๋ฌผ ํƒ์‚ฌ์— ๋Œ€ํ•ด ์ดˆ์ ์„ ๋งž์ถ”๊ณ ์ž ํ•œ๋‹ค. ๋ชฝ๊ณจ ๋ถ๋ถ€์˜ ์—๋ฅด๋ฐ๋„ทํ‹ด ์˜ค๋ณด ๋ฐ˜์•” ๋™-๋ชฐ๋ฆฌ๋ธŒ๋ด ๊ด‘์ƒ์—์„œ ์‚ฐ์ถœ๋˜๋Š” ๊ด‘์„ ๊ด‘๋ฌผ์˜ ๊ตฌ๋ฆฌ(ฮด65Cu) ๋ฐ ํ™ฉ(ฮด34S) ๋™์œ„์›์†Œ ์กฐ์„ฑ์„ ์ธก์ •ํ•˜์˜€๋‹ค. 1๊ฐ€ ๊ตฌ๋ฆฌ(Cu (I))๋ฅผ ํ•จ์œ ํ•œ ๊ตฌ๋ฆฌ ํ™ฉํ™”๋ฌผ์˜ ฮด65Cu ๊ฐ’์€ 0.14 ~ 2.69โ€ฐ์˜ ๋ฒ”์œ„๋ฅผ ๋ณด์ด๋ฉฐ, ์ด๋Š” ๊ตฌ๋ฆฌ๊ฐ€ ๋งˆ๊ทธ๋งˆ์—์„œ ๊ธฐ์›ํ•˜์˜€์Œ์„ ์ง€์‹œํ•œ๋‹ค. ๋ฐ˜๋ฉด์— 2๊ฐ€ ๊ตฌ๋ฆฌ(Cu (II))๋ฅผ ํ•จ์œ ํ•œ ํฌ๋ฆฌ์†Œ์ฝœ๋ผ, ๊ณต์ž‘์„ ๋ฐ ๋‚จ๋™์„๊ณผ ๊ฐ™์€ ๊ตฌ๋ฆฌ ๊ด‘๋ฌผ๋“ค์˜ ฮด65Cu ๊ฐ’์€ -1.01 ~ 10.0โ€ฐ์˜ ๋” ํฐ ๋ฒ”์œ„๋ฅผ ๋ณด์ธ๋‹ค. 1์ฐจ ๋ฐ 2์ฐจ ๊ตฌ๋ฆฌ ํ™ฉํ™”๋ฌผ ๊ฐ„์˜ ์ž‘์€ ๊ตฌ๋ฆฌ ๋™์œ„์›์†Œ ๊ฐ’์˜ ์ฐจ์ด๋Š” 2์ฐจ ๊ตฌ๋ฆฌ ํ™ฉํ™”๋ฌผ์ด ์ƒ์„ฑ๋˜๋Š” ๋™์•ˆ ๊ตฌ๋ฆฌ ๋™์œ„์›์†Œ ๋ถ„๋ณ„ ์ž‘์šฉ์ด ํฌ์ง€ ์•Š์•˜์Œ์„ ์ง€์‹œํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ž‘์€ ๋ถ„๋ณ„ ์ž‘์šฉ์€ ๋Œ€๊ทœ๋ชจ์˜ ๊ตฌ๋ฆฌ ์ด๋™์ด ์ผ์–ด๋‚ฌ๊ฑฐ๋‚˜ ์ƒ๋ฌผํ•™์  ํ™œ๋™์— ์˜ํ•œ ๊ฒƒ์œผ๋กœ ์ƒ๊ฐ๋œ๋‹ค. ํ™ฉ๋™์„์˜ ฮด65Cu ๊ฐ’์€ ๊ธฐ์› ๋ฌผ์งˆ์˜ ๋น„๊ท ์งˆํ•œ ๊ตฌ๋ฆฌ ๋™์œ„์›์†Œ ์กฐ์„ฑ ๋˜๋Š” ๊ณ ์˜จ์—์„œ ์ผ์–ด๋‚œ ๊ตฌ๋ฆฌ ๋™์œ„์›์†Œ ๋ถ„๋ณ„ ์ž‘์šฉ์— ์˜ํ•œ ๊ฒƒ์œผ๋กœ ์—ฌ๊ฒจ์ง„๋‹ค. ๋˜ํ•œ ์–‘์˜ ฮ”Cu (II) mineral โ€“ Cu (I) mineral ๊ฐ’์€ ๊ด‘์ƒ์—์„œ ๊ตฌ๋ฆฌ์˜ ์ด๋™์ด ๋จผ ๊ณณ๊นŒ์ง€ ์ด๋ค„์ง€์ง€ ์•Š์•„ ๋Œ€๋žต์ ์ธ ๋ฌผ์งˆ ์ˆ˜์ง€์™€ ๋น ๋ฅธ ์‚ฐํ™”ํ™˜์› ๋ฐ˜์‘์ด ์ผ์–ด๋‚ฌ์Œ์„ ์ง€์‹œํ•œ๋‹ค. 1์ฐจ ํ™ฉํ™”๋ฌผ(ํ™ฉ์ฒ ์„, ํ™ฉ๋™์„ ๋ฐ ํœ˜์ˆ˜์—ฐ์„)์˜ ฮด34S ๊ฐ’์€ 0โ€ฐ ๊ทผ์ฒ˜์— ๋ชจ์—ฌ ์žˆ์œผ๋ฉฐ, ์ด๋Š” ํ™ฉ์ด ๊ท ์งˆํ•œ ๋งˆ๊ทธ๋งˆ์—์„œ ๊ธฐ์›ํ•˜์˜€์Œ์„ ์ง€์‹œํ•œ๋‹ค. ๋ฐ˜๋ฉด์— 2์ฐจ ํ™ฉํ™”๋ฌผ๋“ค์˜ ฮด34S ๊ฐ’์€ -3.2 ~ -0.3โ€ฐ์˜ ๋ฒ”์œ„๋ฅผ ๊ฐ–์œผ๋ฉฐ, -1.6โ€ฐ์˜ ํ‰๊ท ๊ฐ’์„ ๊ฐ–๋Š”๋‹ค. ์ด๋Ÿฌํ•œ ๋” ๋‚ฎ์€ ํ™ฉ ๋™์œ„์›์†Œ ์กฐ์„ฑ์€ ํ™ฉ ๋™์œ„์›์†Œ ๋ถ„๋ณ„ ์ž‘์šฉ ๋˜๋Š” ๋‹ค๋ฅธ ํ™ฉ ๋™์œ„์›์†Œ ์กฐ์„ฑ์„ ๊ฐ–๋Š” ํ™ฉ์˜ ์œ ์ž…์— ์˜ํ•œ ๊ฒƒ์œผ๋กœ ์—ฌ๊ฒจ์ง„๋‹ค. ๊ด‘์„ ๊ด‘๋ฌผ์˜ ์ด๋Ÿฌํ•œ ๊ตฌ๋ฆฌ ๋ฐ ํ™ฉ ๋™์œ„์›์†Œ ๊ฐ’์€ ๊ทผ์ฒ˜ ์ง€์—ญ์œผ๋กœ ๋Œ€๊ทœ๋ชจ์˜ ๊ตฌ๋ฆฌ ๋ฌผ์งˆ์ด ์ด๋™ํ•˜์—ฌ, ์—ฐ๊ตฌ ์ง€์—ญ์—์„œ ๋‹ค๋ฅธ ์ˆจ๊ฒจ์ง„ ๊ด‘์ฒด๊ฐ€ ๋ฐœ๊ฒฌ๋  ๊ฐ€๋Šฅ์„ฑ์€ ๋งค์šฐ ์ž‘์Œ์„ ์ง€์‹œํ•œ๋‹ค. ๋ชฝ๊ณจ ์ค‘๋ถ๋ถ€์˜ ๊ฒํ‹ฐ ๊ธˆ ๊ด‘ํ™”๋Œ€์— ์œ„์น˜ํ•œ ์ค€๋ชจ๋“œ ์ง€์—ญ์—๋Š” ๊ฐ“์ญˆ๋ฅดํŠธ(Gatsuurt), ๋ณด๋ฃจ(Boroo), ์ˆ˜์ง€ํ…Œ์ด(Sujigtei), ์—๋ฆฐ(Ereen) ๋ฐ ์šธ๋ž€๋ถˆ๋ผ๊ทธ(Ulaanbulag)์™€ ๊ฐ™์€ ๊ธˆ ๊ด‘์ƒ๋“ค์ด ๋‚˜ํƒ€๋‚œ๋‹ค. ์ด๋“ค์€ ๋น„์Šทํ•œ ๋ณ€์งˆ ๋ฐ ๊ด‘์„ ๊ด‘๋ฌผ ์กฐํ•ฉ์„ ๋ณด์—ฌ์ฃผ๋ฉฐ, ์ฃผ๋กœ ๊ฒฌ์šด๋ชจ์งˆ, ๊ทœ์‚ฐ์งˆ ๋ฐ K-์žฅ์„์งˆ์˜ ๋ณ€์งˆ ๊ด‘๋ฌผ ์กฐํ•ฉ์ด ๊ธˆ ๊ด‘ํ™”์ž‘์šฉ๊ณผ ์—ฐ๊ด€๋˜์–ด ๋‚˜ํƒ€๋‚œ๋‹ค. ํ™ฉ์ฒ ์„๊ณผ ํ™ฉ๋น„์ฒ ์„์ด ์ฃผ์š” ๊ด‘์„ ๊ด‘๋ฌผ์ด๋ฉฐ, ์ ์€ ์–‘์˜ ๋ฐฉ์—ฐ์„, ์„ฌ์•„์—ฐ์„ ๋ฐ ํ™ฉ๋™์„์ด ํ•จ๊ป˜ ์‚ฐ์ถœ๋œ๋‹ค. ๊ธˆ์€ ์ž์—ฐ๊ธˆ๊ณผ ํ™ฉํ™”๋ฌผ ๋‚ด์— ํฌํ•จ๋œ ์œก์•ˆ์œผ๋กœ ๊ด€์ฐฐ๋˜์ง€ ์•Š์€ ๊ธˆ์˜ ํ˜•ํƒœ๋กœ ๋ชจ๋‘ ๋‚˜ํƒ€๋‚œ๋‹ค. ์ฃผ์š” ํ™ฉํ™”๋ฌผ๋“ค์€ ์ดˆ๊ธฐ์˜ ๊ธˆ์„ ํ•จ์œ ํ•˜์ง€ ์•Š์€ ๊ด‘ํ™” ๋‹จ๊ณ„์™€ ํ›„๊ธฐ์˜ ๊ธˆ์„ ํ•จ์œ ํ•œ ๊ด‘ํ™” ๋‹จ๊ณ„๋กœ ๋‚˜๋‰˜๋ฉฐ, ์ž์—ฐ๊ธˆ์€ ์ดํ›„์— ํ˜•์„ฑ๋œ ๊ฒƒ์œผ๋กœ ์—ฌ๊ฒจ์ง„๋‹ค. ํ™ฉ๋น„์ฒ ์„ ๋‚ด์˜ ๊ธˆ๊ณผ ๋น„์†Œ ํ•จ๋Ÿ‰์€ ๊ธˆ์ด ๊ฐ“์ญˆ๋ฅดํŠธ์™€ ๋ณด๋ฃจ ๊ด‘์ƒ์—์„œ๋Š” ๊ณ ์šฉ์ฒด ํ˜•ํƒœ์˜ 1๊ฐ€ ๊ธˆ์œผ๋กœ ์กด์žฌํ•˜๋Š”๋ฐ ๋ฐ˜ํ•ด, ์ˆ˜์ง€ํ…Œ์ด ๊ด‘์ƒ์—์„œ๋Š” ๋‚˜๋…ธ ์ž…์ž ํ˜•ํƒœ๋กœ ์กด์žฌํ•จ์„ ๋ณด์—ฌ์ค€๋‹ค. ํ™ฉ์ฒ ์„ ๋‚ด์˜ ๋†’์€ Co/Ni๊ณผ Mo/Ni ๋น„๋Š” ์ด๋“ค์ด ํ‡ด์ ์ž‘์šฉ ์ดํ›„์— ์ƒ์„ฑ๋˜์—ˆ์œผ๋ฉฐ, ๊ด‘ํ™” ์œ ์ฒด๊ฐ€ ๊ด‘ํ™” ์ž‘์šฉ ๋™์•ˆ์— ์œ ์ฒด-์•”์„ ์ž‘์šฉ์— ๋งŽ์€ ์˜ํ–ฅ์„ ๋ฐ›์•˜์Œ์„ ์ง€์‹œํ•œ๋‹ค. ํ™ฉ์ฒ ์„๊ณผ ํ™ฉ๋น„์ฒ ์„์˜ ฮด34S ๊ฐ’์€ -2.6 ~ 17.2โ€ฐ์˜ ๋„“์€ ๋ฒ”์œ„๋ฅผ ๊ฐ–์œผ๋ฉฐ, ์ด๋Š” ํ™ฉ์ด ๋น„๊ท ์งˆํ•œ ํ™ฉ ๋™์œ„์›์†Œ ์กฐ์„ฑ์„ ๊ฐ–๋Š” ๋ฌผ์งˆ์—์„œ ๊ธฐ์›ํ•˜์˜€์Œ์„ ์ง€์‹œํ•œ๋‹ค. ์ฃผ๋กœ ํ•ด์ˆ˜ ๋‚ด ํ™ฉ์‚ฐ์—ผ์˜ ํ™˜์›์— ์˜ํ•ด ์ƒ์„ฑ๋œ ํ™ฉ์ฒ ์„์ด ํฌํ•จ๋œ ํ‡ด์ ๋ฌผ์ด ๊ฐ€์žฅ ์ฃผ์š”ํ•œ ํ™ฉ์˜ ๊ธฐ์› ๋ฌผ์งˆ์ด๋ผ ์—ฌ๊ฒจ์ง„๋‹ค. ์ง€์งˆํ•™์  ์ฆ๊ฑฐ๋“ค๊ณผ ์ผ์น˜ํ•˜์—ฌ ์ƒ๋Œ€์ ์œผ๋กœ ์–‘์˜ ๊ฐ’์„ ๋ณด์ด๋Š” ฮด34S ๊ฐ’์€ ํ™ฉํ™”์ž‘์šฉ์ด ๊ธˆ๊ณผ ํ™ฉํ™”๋ฌผ์˜ ์นจ์ „์— ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•˜์˜€์Œ์„ ์ง€์‹œํ•œ๋‹ค. ์„์˜ ๋งฅ ์‹œ๋ฃŒ๋“ค์˜ ฮด18O ๊ฐ’(14.7 ~ 17.7โ€ฐ)์„ ํ†ตํ•ด ๊ณ„์‚ฐ๋œ ์—ด์ˆ˜์˜ ฮด18O ๊ฐ’์€ ๊ด‘ํ™” ์œ ์ฒด๊ฐ€ ๋ณ€์„ฑ ๊ธฐ์›์„ ๊ฐ–์Œ์„ ๋ณด์—ฌ์ค€๋‹ค. ์ด๋ฒˆ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ์–ป์–ด์ง„ ๊ด€์ฐฐ ๋ฐ ์ธก์ • ๊ฒฐ๊ณผ๋“ค์€ ๊ธˆ ๊ด‘ํ™”์ž‘์šฉ์ด ์—ฌ๋Ÿฌ ์ฐจ๋ก€์˜ ์—ด์ˆ˜ ์œ ์ž…, ์œ ์ฒด-์•”์„ ๋ฐ˜์‘๊ณผ ๊ด‘ํ™” ์œ ์ฒด ๊ฐ„์˜ ํ˜ผํ•ฉ์— ์˜ํ•ด ์ผ์–ด๋‚ฌ์Œ์„ ๊ฐ€๋ฆฌํ‚จ๋‹ค. ๋”ฐ๋ผ์„œ ์—ฐ๊ตฌ ์ง€์—ญ์˜ ๊ธˆ ๊ด‘์ƒ์€ ์œ ์ฒด-์•”์„ ์ƒํ˜ธ ์ž‘์šฉ์— ์˜ํ–ฅ์„ ๋ฐ›์€ ์กฐ์‚ฐํ˜• ๊ธˆ ๊ด‘์ƒ ์œ ํ˜•์œผ๋กœ ์—ฌ๊ฒจ์ง„๋‹ค.Contents Abstract ------------------------------------------------------------------------------- i ์ดˆ๋ก ---------------------------------------------------------------------------------- iv Preface -------------------------------------------------------------------------------- vii Contents ------------------------------------------------------------------------------ xii List of Figure ------------------------------------------------------------------------ xiv List of Table ------------------------------------------------------------------------ xviii Chapter 1. Cu and S isotopic signatures of the Erdenetiin Ovoo porphyry Cu-Mo deposit, northern Mongolia: Implications for their origin and mineral exploration ----------------------------------------------------------------- 1 Abstract ---------------------------------------------------------------------------- 2 1. Introduction--------------------------------------------------------------------- 3 2. Geological setting ------------------------------------------------------------- 6 2.1. Regional Geology --------------------------------------------------------- 6 2.2. Deposit Geology ----------------------------------------------------------- 7 2.3. Age of the Deposit --------------------------------------------------------- 9 3. Sample description ------------------------------------------------------------ 10 4. Analytical method ------------------------------------------------------------- 12 4.1. Cu isotope analysis -------------------------------------------------------- 12 4.1.1. Pretreatment processes for Cu isotopes ----------------------------- 12 4.1.2. Ion exchange chromatography for separation of Cu -------------- 13 4.1.3. Cu isotope analysis ---------------------------------------------------- 13 4.2. S isotope analysis ---------------------------------------------------------- 14 5. Results -------------------------------------------------------------------------- 15 6. Discussion ---------------------------------------------------------------------- 16 6.1. The ฮด65Cu values of ore deposits and igneous rocks ------------------ 16 6.2. Cu isotope data ------------------------------------------------------------ 20 6.2.1. The ฮด65Cu values of Cu sulfide minerals -------------------------- 20 6.2.2. The ฮด65Cu values of Cu (II) minerals ------------------------------- 24 6.3. S isotope data -------------------------------------------------------------- 27 6.4. Implications for mineral exploration and deposit environment ----- 30 7. Conclusions -------------------------------------------------------------------- 31 References ------------------------------------------------------------------------ 32 Chapter 2. Geological, trace elemental and stable isotopic characteristics of the Dzuunmod gold area in northern Mongolia: Constraints for formation of deposit and sources of sulfur and fluid ---------------------------------------- 60 Abstract ---------------------------------------------------------------------------- 51 1. Introduction -------------------------------------------------------------------- 63 2. Geological setting ------------------------------------------------------------- 66 2.1. Regional geological setting ---------------------------------------------- 66 2.2. Deposit geological setting ------------------------------------------------ 67 2.3. Ages of the deposits ------------------------------------------------------- 69 3. Samples and analytical methods -------------------------------------------- 70 4. Characteristics of the Dzuunmod gold area ------------------------------- 72 4.1. Gatsuurt deposit ----------------------------------------------------------- 73 4.2. Sujigtei deposit ------------------------------------------------------------ 74 4.3. Ereen deposit --------------------------------------------------------------- 75 4.4. Boroo deposit -------------------------------------------------------------- 75 4.5. Ulaanbulag deposit -------------------------------------------------------- 76 4.6. Khargana deposit ---------------------------------------------------------- 76 4.7. Balj occurrence ------------------------------------------------------------ 77 4.8. Biluut occurrence ---------------------------------------------------------- 77 4.9. Paragenetic sequences ---------------------------------------------------- 78 5. Trace element geochemistry ------------------------------------------------- 79 6. Stable isotope systematics --------------------------------------------------- 82 6.1. Sulfur isotope data -------------------------------------------------------- 82 6.2. Oxygen isotope data ------------------------------------------------------ 87 7. Implications for ore genesis and sources and Conclusions -------------- 89 References ------------------------------------------------------------------------ 92 Concluding Remarks ---------------------------------------------------------------- 125 ๊ฐ์‚ฌ์˜ ๊ธ€ -------------------------------------------------------------------------- 127Docto

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ํ–‰์ •ํ•™๊ณผ, 2021. 2. ์—„์„์ง„.๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ƒˆ๋กœ์šด ์ง€๋Šฅ์ •๋ณด๊ธฐ์ˆ ์ด ๋“ฑ์žฅํ•˜๋Š” ์ƒํ™ฉ์—์„œ ๊ณต๊ณต ์•ฑ์˜ ๋ฐœ์ „์ˆ˜์ค€ ๋ชจํ˜•์„ ์ƒˆ๋กญ๊ฒŒ ๊ตฌ์„ฑํ•˜๊ณ , ์ด์— ๊ทผ๊ฑฐํ•˜์—ฌ ์ค‘์•™ํ–‰์ •๊ธฐ๊ด€์ด ์ œ๊ณตํ•˜๋Š” ๊ณต๊ณต ์•ฑ์˜ ๋ฐœ์ „์ˆ˜์ค€์„ ์ธก์ •ํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๊ณต๊ณต ์•ฑ์˜ ๋ฐœ์ „์ˆ˜์ค€์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ์„ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด ์ˆœ์„œ ํ”„๋กœ๋น— ํšŒ๊ท€๋ถ„์„์„ ์‹ค์‹œ ํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ ์ฒซ์งธ, ๊ณต๊ณต ์•ฑ์˜ ๋ฐœ์ „์ˆ˜์ค€ ๋ชจํ˜•์€ ๊ธฐ์กด Eom & Kim(2014)์˜ 6๋‹จ๊ณ„ ๋ชจํ˜•์—์„œ ์ธ๊ณต์ง€๋Šฅ๊ณผ ๋น…๋ฐ์ดํ„ฐ ๋ถ„์„๊ณผ ๊ฐ™์€ ์ƒˆ๋กœ์šด ์ง€๋Šฅ์ •๋ณด๊ธฐ์ˆ ์ด ๋ฐ˜์˜๋œ โ€˜๊ฐ•ํ™”์ œ์‹œโ€™, โ€˜์ž๋™์ƒํ˜ธ์ž‘์šฉโ€™, โ€˜์ž๋™์—…๋ฌด์ฒ˜๋ฆฌโ€™, โ€˜์˜ˆ์ธกโ€™์ด๋ผ๋Š” 4๊ฐœ์˜ ๋‹จ๊ณ„๊ฐ€ ์ถ”๊ฐ€๋œ 10๋‹จ๊ณ„ ๋ชจํ˜•์œผ๋กœ ์ƒˆ๋กญ๊ฒŒ ๊ตฌ์„ฑ๋˜์—ˆ๋‹ค. ๋‘˜์งธ, ์ƒˆ๋กญ๊ฒŒ ๊ตฌ์„ฑ๋œ ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€ ๋ชจํ˜•์„ ๋ฐ”ํƒ•์œผ๋กœ ์ค‘์•™ํ–‰์ •๊ธฐ๊ด€์ด ์ œ๊ณตํ•˜๋Š” 175๊ฐœ ๊ณต๊ณต ์•ฑ์˜ ๋ฐœ์ „์ˆ˜์ค€์„ ์ธก์ •ํ•œ ๊ฒฐ๊ณผ, ๋Œ€๋ถ€๋ถ„์˜ ๊ณต๊ณต ์•ฑ์ด 2๋‹จ๊ณ„์—์„œ 5๋‹จ๊ณ„ ์‚ฌ์ด์˜ ๋ฐœ์ „์ˆ˜์ค€์„ ๋ณด์ด๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ์…‹์งธ, ๊ณต๊ณต ์•ฑ์˜ ๋ฐœ์ „์ˆ˜์ค€์„ ๊ฒฐ์ •ํ•˜๋Š” ์š”์ธ์„ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ, ์ •๋ณด ์šฉ๋Ÿ‰์ด ํฐ ๊ณต๊ณต ์•ฑ, ๋ฏผ์›๋งŒ์กฑ๋„๊ฐ€ ๋†’์€(๊ฐ€, ๋‚˜ ๋“ฑ๊ธ‰) ๊ธฐ๊ด€์—์„œ ์ œ๊ณตํ•˜๋Š” ๊ณต๊ณต ์•ฑ, ์œ„๊ณ„๊ฐ€ ๋†’์€(๋ถ€ ๋‹จ์œ„) ๊ธฐ๊ด€์—์„œ ์ œ๊ณตํ•˜๋Š” ๊ณต๊ณต ์•ฑ์ด ๋†’์€ ๋ฐœ์ „์ˆ˜์ค€์— ์†ํ•  ํ™•๋ฅ ์ด ํฐ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๊ณ , ์ •๋ณดํ™” ์—ญ๋Ÿ‰์ด ๋†’์€ ๊ธฐ๊ด€์—์„œ ์ œ๊ณตํ•˜๋Š” ๊ณต๊ณต ์•ฑ, ๊ทœ๋ชจ(์„ธ์ถœ์˜ˆ์‚ฐ)๊ฐ€ ํฐ ๊ธฐ๊ด€์—์„œ ์ œ๊ณตํ•˜๋Š” ๊ณต๊ณต ์•ฑ์˜ ๊ฒฝ์šฐ ๋†’์€ ๋ฐœ์ „์ˆ˜์ค€์— ์†ํ•  ํ™•๋ฅ ์ด ์ž‘์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ด๋ก ์  ์ฐจ์›์—์„œ ์ง€๋Šฅ์ •๋ณด๊ธฐ์ˆ ์„ ์ ์šฉํ•œ ๊ณต๊ณต ์•ฑ์˜ ์ƒˆ๋กœ์šด ๊ฐ€๋Šฅ์„ฑ์„ ๋ถ„์„ํ•˜๊ณ  ์ด๋ฅผ ๊ณ ๋ คํ•œ ๋ฐœ์ „์ˆ˜์ค€ ๋ชจํ˜•์„ ๊ตฌ์„ฑํ•จ์œผ๋กœ์จ ๋ชจ๋ฐ”์ผ ์ •๋ถ€ ์ดํ›„์˜ ์ƒˆ๋กœ์šด ํŒจ๋Ÿฌ๋‹ค์ž„์ธ ์ง€๋Šฅํ˜• ์ •๋ถ€์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ์ฆ์ง„์‹œ์ผฐ๋‹ค๋Š” ์ ์—์„œ ์˜์˜๊ฐ€ ์žˆ๋‹ค. ๋˜ํ•œ, ์‹ค์šฉ์  ์ฐจ์›์—์„œ ๊ณต๊ณต ์•ฑ์˜ ๋ฐœ์ „์ˆ˜์ค€์— ์˜ํ–ฅ์„ ๋ฏธ์น  ์ˆ˜ ์žˆ๋Š” ๊ฒฐ์ •์š”์ธ์„ ๋ถ„์„ํ•จ์œผ๋กœ์จ ํ–ฅํ›„ ๊ณต๊ณต ์•ฑ์„ ์ œ์ž‘ํ•˜๋Š” ๊ธฐ๊ด€์—๊ฒŒ ๋‹ค์–‘ํ•œ ์ •์ฑ…์  ์‹œ์‚ฌ์ ์„ ์ œ๊ณตํ•œ๋‹ค๋Š” ์ ์—์„œ๋„ ์˜๋ฏธ๊ฐ€ ์žˆ๋‹ค.In this study, a new public application maturity model was formed in the face of the emergence of new intelligent information technology, and based on this, the level of development of public apps provided by central government agencies was measured. In addition, the ordered probit regression analysis was conducted to analyze the determinants affection the maturity level of public apps. According to to the analysis, the maturity model of public apps was newly constructed from the six-stage model of Eom & Kim (2014), with four stages of โ€˜augmented presentationโ€™, โ€˜automatic interactionโ€™, โ€˜automatic task processingโ€™ and โ€˜predictionโ€™, which reflect new intelligence technologies such as artificial intelligence and big data analysis. Second, based on the newly constructed maturity model, 175 public apps provided by central government agencies showed that most public apps showed maturity levels between 2nd and 5th stages. Finally, the analysis of factors that determine the level of maturity of public apps showed that public apps with high information capacity, public apps with high civil service satisfaction and public apps with high hierarchies were more likely to have high levels of development. The analysis of determinants, however, showed that public apps provided by institutions with high information capabilities and public apps provided by large institutions are less likely to have high levels of development. On a theoretical level, this study is meaningful in that it has improved understanding of the new paradigm of intelligent government after mobile government by analyzing the new possibilities of public apps applying intelligent information technology and forming a new maturity model. It is also meaningful in that it provides various policy implications to institutions that produce public apps in the future by analyzing determinants that can affect the level of maturity of public apps on a practical level.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ๋ฐฐ๊ฒฝ๊ณผ ๋ชฉ์  1 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ๊ณผ ๋ฐฉ๋ฒ• 3 ์ œ 2 ์žฅ ์ด๋ก ์  ๋ฐฐ๊ฒฝ ๋ฐ ์„ ํ–‰์—ฐ๊ตฌ์˜ ๊ฒ€ํ†  4 ์ œ 1 ์ ˆ ์ง€๋Šฅ์ •๋ณด์‹œ๋Œ€์˜ ์ƒˆ๋กœ์šด ์ •๋ณด๊ธฐ์ˆ ๊ณผ ๊ณต๊ณต ์•ฑ 4 1. ์ƒˆ๋กœ์šด ์ง€๋Šฅ์ •๋ณด๊ธฐ์ˆ ์˜ ๋“ฑ์žฅ 4 2. ์ง€๋Šฅ์ •๋ณด๊ธฐ์ˆ  ๊ธฐ๋ฐ˜์˜ ์ƒˆ๋กœ์šด ํ–‰์ •ํ˜์‹  8 3. ๋ชจ๋ฐ”์ผ์˜ ๋ฏธ๋ž˜์™€ ๊ณต๊ณต ์•ฑ 9 ์ œ 2 ์ ˆ ์ •๋ถ€์˜ ๊ณต๊ณต ์•ฑ ๋„์ž…๊ณผ ํ™œ์šฉ 11 1. ๋ชจ๋ฐ”์ผ ์•ฑ์˜ ๊ฐœ๋… ๋ฐ ์œ ํ˜• 11 2. ๊ณต๊ณต ์•ฑ๊ณผ ๋ชจ๋ฐ”์ผ ์ •๋ถ€์˜ ๋“ฑ์žฅ 13 ์ œ 3 ์ ˆ ์ •๋ณด์‹œ์Šคํ…œ์˜ ๋ฐœ์ „์ˆ˜์ค€๊ณผ ๊ฒฐ์ •์š”์ธ 16 1. ์ •๋ณด์‹œ์Šคํ…œ ์ˆ˜์ค€์˜ ์ธก์ •์— ๊ด€ํ•œ ๋…ผ์˜ 16 2. ์ •๋ณด์‹œ์Šคํ…œ ๋ฐœ์ „์ˆ˜์ค€์˜ ๊ฒฐ์ •์š”์ธ 19 ์ œ 4 ์ ˆ ์„ ํ–‰์—ฐ๊ตฌ์˜ ๊ฒ€ํ†  22 1. ์ผ๋ฐ˜์ ์ธ ๋ชจ๋ฐ”์ผ ์•ฑ์— ๊ด€ํ•œ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  22 2. ๊ณต๊ณต ์•ฑ์— ๊ด€ํ•œ ์ผ๋ฐ˜์ ์ธ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  23 3. ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€์˜ ์ธก์ • ๋ฐ ๊ฒฐ์ •์š”์ธ์— ๊ด€ํ•œ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  25 4. ์„ ํ–‰์—ฐ๊ตฌ์— ๋Œ€ํ•œ ๋น„ํŒ์  ๊ฒ€ํ†  30 ์ œ 3 ์žฅ ์—ฐ๊ตฌ ์„ค๊ณ„ 33 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ์˜ ์ ˆ์ฐจ ๋ฐ ๊ณ„ํš 33 1. 1๋‹จ๊ณ„: ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€ ๋ชจํ˜•์˜ ๊ตฌ์„ฑ 33 2. 2๋‹จ๊ณ„: ๊ณต๊ณต ๋ชจ๋ฐ”์ผ ์•ฑ ์ „์ˆ˜์กฐ์‚ฌ 33 3. 3๋‹จ๊ณ„: ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€ ๊ฒฐ์ •์š”์ธ ๋ถ„์„ 34 ์ œ 2 ์ ˆ ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€ ์ธก์ • ๋ฐ ๊ฒฐ์ •์š”์ธ ๋ถ„์„ 35 1. ์—ฐ๊ตฌ์˜ ๋ถ„์„ํ‹€ ๋ฐ ๊ฐ€์„ค ์„ค์ • 35 2. ๋ณ€์ˆ˜์˜ ์กฐ์ž‘์  ์ •์˜ 41 ์ œ 3 ์ ˆ ์ž๋ฃŒ ์ˆ˜์ง‘ ๋ฐ ๋ถ„์„ ๋ฐฉ๋ฒ• 46 1. ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€ ๋ชจํ˜• ๊ตฌ์„ฑ ๋ฐ ์ˆ˜์ค€ ์ธก์ • 46 2. ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€์˜ ๊ฒฐ์ •์š”์ธ ๋ถ„์„ 46 ์ œ 4 ์žฅ ๋ถ„์„๊ฒฐ๊ณผ 49 ์ œ 1 ์ ˆ ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€ ๋ชจํ˜•์˜ ๊ตฌ์„ฑ 49 1. ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€ ๋ชจํ˜• ๊ตฌ์„ฑ์˜ ์›๋ฆฌ 49 2. ์ƒˆ๋กœ์šด ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€ 51 3. ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€ ๋ชจํ˜• 57 ์ œ 2 ์ ˆ ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€ ์ธก์ • ๊ฒฐ๊ณผ 61 1. ์ค‘์•™ํ–‰์ •๊ธฐ๊ด€์˜ ๊ณต๊ณต ์•ฑ ์ œ๊ณต ํ˜„ํ™ฉ 61 2. ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€ ๋ถ„์„ 65 ์ œ 3 ์ ˆ ๊ณต๊ณต ์•ฑ ๋ฐœ์ „์ˆ˜์ค€ ๊ฒฐ์ •์š”์ธ ๋ถ„์„ 70 1. ๊ธฐ์ดˆํ†ต๊ณ„๋ถ„์„ 70 2. ์ˆœ์„œ ํ”„๋กœ๋น— ํšŒ๊ท€๋ถ„์„ 74 ์ œ 5 ์žฅ ๊ฒฐ๋ก  82 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์˜ ์š”์•ฝ ๋ฐ ํ•ด์„ 82 ์ œ 2 ์ ˆ ์—ฐ๊ตฌ์˜ ์˜์˜ ๋ฐ ํ•œ๊ณ„ 83 ์ฐธ๊ณ ๋ฌธํ—Œ 85 ๋ถ€๋ก: ์ค‘์•™ํ–‰์ •๊ธฐ๊ด€ ์ œ๊ณต ๊ณต๊ณต ์•ฑ ๋ชฉ๋ก 95Maste

    Association between skeletal muscle attenuation and gastroesophageal reflux disease: A health check-up cohort study

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    Sarcopenia is defined as skeletal muscle attenuation and has an association with metabolic syndrome. Metabolic syndrome, which includes obesity, is one of known predictive factors for gastroesophageal reflux disease (GERD). This study aimed to elucidate the association between sarcopenia and GERD. We retrospectively reviewed electronic medical records of 8,218 patients who were performed an upper gastrointestinal endoscopy at check-up center of the Gangnam Severance Hospital. GERD was diagnosed by endoscopic findings. Erosive reflux disease (ERD) included Barrett's esophagus and reflux esophagitis, with the exception of minimal change esophagitis. Sarcopenia was defined by appendicular skeletal muscle (skeletal muscle in the upper and lower limbs). Sarcopenic obesity was defined as the presence of both sarcopenia and obesity. Associations between sarcopenia and GERD, as well as between sarcopenic obesity and ERD, were analyzed. A total of 3,414 patients were diagnosed with GERD, and 574 (16.8%) had sarcopenia. Sarcopenia was independent predictive factor for GERD (odds ratio [OR]โ€‰=โ€‰1.170, 95% confidence interval [CI]: 1.016-1.346, Pโ€‰=โ€‰0.029). In addition, male sex, smoking, alcohol, and diet, including sweets and fatty food, had a significant association with GERD. A total of 1,423 (17.3%) of 8,218 patients were diagnosed with ERD, and 302 (21.2%) had sarcopenia. Male sex, smoking, and fatty food consumption had a significant association with ERD. Moreover, sarcopenia (ORโ€‰=โ€‰1.215, 95% CI: 1.019-1.449, Pโ€‰=โ€‰0.030), obesity (ORโ€‰=โ€‰1.343, 95% CI: 1.163-1.552, Pโ€‰<โ€‰0.001), and sarcopenic obesity (ORโ€‰=โ€‰1.406, 95% CI: 1.195-1.654, Pโ€‰<โ€‰0.001) were independent predictive factors for ERD. Sarcopenia is associated with GERD, and sarcopenic obesity may be predictive factor for ERD.ope

    Relationships between production management indices and production factors of the shipyard production system

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์กฐ์„ ํ•ด์–‘๊ณตํ•™๊ณผ, 2018. 2. ์‹ ์ข…๊ณ„.์กฐ์„  ์‚ฐ์—…์€ ์ƒ์‚ฐ์„ ์œ„ํ•œ ์š”์†Œ๋“ค์ด ๋ณต์žกํ•˜๊ณ  ๋‹ค์–‘ํ•˜๋‹ค. ๊ธด ์ƒ์‚ฐ ๊ธฐ๊ฐ„๋™์•ˆ ๊ณ ๋„์˜ ์ƒ์‚ฐ ๊ด€๋ฆฌ๋ฅผ ์œ ์ง€ํ•˜๊ธฐ ์œ„ํ•œ ์ƒ์‚ฐ๊ด€๋ฆฌ์ง€ํ‘œ ๋˜ํ•œ ๋ณต์žกํ•˜๊ณ  ๋‹ค์–‘ํ•˜๋ฉฐ ์ •๋Ÿ‰ํ™”ํ•˜๊ธฐ ์–ด๋ ต๋‹ค๋Š” ํŠน์ง•์ด ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ, ์กฐ์„ ์†Œ์˜ ์ƒ์‚ฐ์„ฑ ํ–ฅ์ƒ์„ ์œ„ํ•ด์„œ๋Š” ์ฒด๊ณ„์ ์ด๊ณ  ๊ณผํ•™์ ์ธ ์ ‘๊ทผ์ด ํ•„์š”ํ•˜๋‹ค. ์ƒ์‚ฐ์— ๊ธฐ์—ฌํ•˜๋Š” ์š”์†Œ๋“ค์ด ๋ฌด์—‡์ธ์ง€ ํŒŒ์•…ํ•˜๊ณ  ์ƒ์‚ฐ์„ฑ์„ ๋‚˜ํƒ€๋‚ผ ์ •๋Ÿ‰ํ™”๋œ ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ๋“ค์ด ํ•„์š”ํ•˜๋ฉฐ ์ด๋ฅผ ํ†ตํ•ด ์ƒ์‚ฐ์„ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋Š” ์ƒ์‚ฐ ์š”์†Œ์™€ ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ ์‚ฌ์ด์˜ ๊ด€๊ณ„๊ฐ€ ์ •๋ฆฝ๋˜์–ด์•ผ ํ•œ๋‹ค. ํ•™๋ฌธ์  ์—ฐ๊ตฌ์˜ ์—ญ์‚ฌ๊ฐ€ ๋‹ค๋ฅธ ๋ถ„์•ผ์— ๋น„ํ•ด ์งง์€ ํŽธ์ธ ์กฐ์„  ์ƒ์‚ฐ ๋ถ„์•ผ๋Š” ๋‹ค๋ฅธ ์ œ์กฐ์—… ๋ถ„์•ผ๋ฅผ ๋ฒค์น˜๋งˆํ‚นํ•˜๊ณ  ์ ์šฉํ•˜๋ ค๋Š” ๋…ธ๋ ฅ์„ ํ•ด ์™”๋Š”๋ฐ, ๋ฌผ๋ก  ๋‹ค๋ฅธ ๋ถ„์•ผ์˜ ์„ฑ๊ณต์ ์ธ ๋ฐฉ๋ฒ•์„ ์—ฐ๊ตฌํ•˜๊ณ  ์šฐ๋ฆฌ์—๊ฒŒ ๋งž๊ฒŒ ์ ์šฉํ•˜๋ ค๋Š” ๋…ธ๋ ฅ์€ ๋งค์šฐ ์ค‘์š”ํ•œ ์ผ์ด์ง€๋งŒ, ์กฐ์„  ์‚ฐ์—…๋งŒ์˜ ํŠน์„ฑ ๋•Œ๋ฌธ์— ์ž˜ ๋งž์ง€ ์•Š๋Š” ๋ถ€๋ถ„๋„ ์žˆ์–ด ๊ทธ ์ ์šฉ์ด ์ œํ•œ์ ์ธ ๊ฒฝ์šฐ๊ฐ€ ๋งŽ์•˜๋‹ค ์ด๋Ÿฌํ•œ ๊ด€์ ์—์„œ ์š”๊ตฌ๋˜๋Š” ์กฐ์„ ์†Œ์˜ ์ƒ์‚ฐ์— ๊ด€ํ•œ ๋ฒ•์น™์˜ ํŠน์„ฑ์„ ์ •๋ฆฌํ•ด ๋ณด๋ฉด ๋‹ค์Œ๊ณผ ๊ฐ™๋‹ค. ์šฐ์„ , ๊ฐ๊ด€์ ์ด๋ฉฐ ์ •๋Ÿ‰์ ์œผ๋กœ ์ธก์ • ๊ฐ€๋Šฅํ•œ ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ๊ฐ€ ์ •์˜๋˜์–ด์•ผ ํ•œ๋‹ค. ๋‹ค์Œ์œผ๋กœ, ๋ชจ๋“  ์ƒ์‚ฐ ์š”์†Œ๋ฅผ ๊ณ ๋ คํ•˜์—ฌ์•ผ ํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ , ์ƒ์‚ฐ ์š”์†Œ์™€ ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ์˜ ๊ด€๊ณ„๊ฐ€ ์ •์˜๋˜์–ด ์ง€ํ‘œ์˜ ํ–ฅ์ƒ์„ ์œ„ํ•ด (ํ˜น์€ ๋ชฉํ‘œ ์ง€ํ‘œ ๋‹ฌ์„ฑ์„ ์œ„ํ•ด) ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ์–ด์•ผ ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ง€๊ธˆ๊นŒ์ง€ ์—ฐ๊ตฌ๋œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์— ๊ด€ํ•œ ์—ฐ๊ตฌ๋‚ด์šฉ์„ ์ •๋ฆฌํ•˜์—ฌ ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์กฐ์„ ์‚ฐ์—…์— ์ ํ•ฉํ•œ ํ•ฉ๋ฆฌ์ ์ด๊ณ  ์ฒด๊ณ„์ ์ธ ์ ‘๊ทผ๋ฐฉ๋ฒ•๋ก ์„ ์ œ์‹œํ•˜๊ณ ์ž ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•˜์—ฌ ๋จผ์ € ์ •๋Ÿ‰์œผ๋กœ ์ธก์ •๊ฐ€๋Šฅํ•œ ์ƒ์‚ฐ ๋ชฉํ‘œ๋กœ์„œ์˜ ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ๋ฅผ ์ •์˜ํ•œ๋‹ค. ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ๋Š” ์กฐ์„ ์†Œ ํ˜„์žฅ์—์„œ๋„ ์“ฐ์ด๋ฉฐ ์ „์‚ฌ์ ์ธ ๋ชฉํ‘œ ์„ค์ •์ด ๊ฐ€๋Šฅํ•œ key performance indicator (KPI)๋ฅผ ์„ค์ •ํ•œ๋‹ค. ๋‹ค์Œ์œผ๋กœ ๋ชจ๋“  ์ƒ์‚ฐ ์š”์†Œ๋ฅผ ํฌํ•จํ•˜๋Š” ์ž…๋ ฅ ์ •๋ณด ์ฒด๊ณ„๋กœ์„œ The 6-factor model์„ ์ •์˜ํ•œ๋‹ค. ์ด๋Š” ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ดˆ ๋ก ii ๋ชจ๋“  ์ž…๋ ฅ ๋ณ€์ˆ˜๋“ค์„ ์™„์ „ํ•˜๊ณ  ๋น ์ง์—†์ด ๊ด€๋ฆฌํ•  ์ˆ˜ ์žˆ๋Š” ์ฒด๊ณ„์ด๋‹ค. ์—ฌ๊ธฐ์—๋Š” ์ œํ’ˆ, ๊ณต์ •, ์„ค๋น„, ์‚ฌ๋žŒ, ๊ณต๊ฐ„, ์Šค์ผ€์ค„(์ƒ์‚ฐ๊ณ„ํš)์˜ ์—ฌ์„ฏ ๊ฐ€์ง€ ์š”์†Œ๊ฐ€ ํฌํ•จ๋œ๋‹ค. ๊ทธ๋ฆฌ๊ณ , ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ์™€ ์ƒ์‚ฐ ์š”์†Œ ์‚ฌ์ด์˜ ๊ด€๊ณ„๋ฅผ ๊ตฌ์ถ•ํ•˜์—ฌ ์กฐ์„ ์†Œ ์ƒ์‚ฐ์„ ์ง€๋ฐฐํ•˜๋Š” ์กฐ์„ ์†Œ์˜ ์ƒ์‚ฐ์— ๊ด€ํ•œ ๋ฒ•์น™์„ ์—ฐ๊ตฌํ•œ๋‹ค. ์ผ๋ จ์˜ ๊ณผ์ •์„ ํ†ตํ•˜์—ฌ ์ผ๋ฐ˜ ์ œ์กฐ์—…๊ณผ๋Š” ๋‹ค๋ฅธ ์กฐ์„ ์‚ฐ์—…์˜ ํŠน์„ฑ์„ ๊ณ ๋ คํ•˜๊ณ  ์กฐ์„ ์‚ฐ์—…์— ์žˆ์–ด์„œ ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ์™€ ์ƒ์‚ฐ ์š”์†Œ์‚ฌ์ด์˜ ๊ด€๊ณ„๊ฐ€ ๋ฒ”ํ•จ์ˆ˜์ ์ธ ํŠน์„ฑ์œผ๋กœ ๋‚˜ํƒ€๋‚จ์„ ํŒŒ์•…ํ•˜์—ฌ ์กฐ์„ ์†Œ ์ƒ์‚ฐ์‹œ์Šคํ…œ์˜ ๊ฑฐ๋™์„ ์ดํ•ดํ•˜๋Š” ์กฐ์„ ์†Œ ์ƒ์‚ฐ ์˜ˆ์ธก ๋ชจ๋ธ์„ ์ œ์•ˆํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ์ œ์•ˆ๋œ ์กฐ์„ ์†Œ ์ƒ์‚ฐ ์˜ˆ์ธก ๋ชจ๋ธ์„ ์ ์šฉํ•œ ์˜ˆ์ œ๋“ค์„ ์ œ์‹œํ•˜๊ณ  ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ์™€ ์ƒ์‚ฐ ์š”์†Œ๋“ค ์‚ฌ์ด์˜ ๋ฒ”ํ•จ์ˆ˜์ ์ธ ํŠน์„ฑ์„ ๋ฐ˜์˜ํ•œ ํšจ๊ณผ๋ฅผ ์ž˜ ์ดํ•ดํ•  ์ˆ˜ ์žˆ๋„๋ก ๋‹ค์–‘ํ•œ ๊ด€์ ์—์„œ ๋ชจ๋ธ์˜ ์ดํ•ด๋ฅผ ๋•๋Š”๋‹ค. ์ด๋ฅผ ์œ„ํ•˜์—ฌ ์กฐ์„ ์†Œ์˜ ๊ฐ€๊ณต๊ณต์žฅ์—์„œ ์ ˆ๋‹จ๋ถ€ํ„ฐ ์‹œ์ž‘ํ•˜์—ฌ ๊ณกํŒ์„ ๋งŒ๋“œ๋Š” ํ”„๋กœ์„ธ์Šค์™€ ์กฐ๋ฆฝ๊ณต์žฅ์—์„œ panel line์˜ ์˜ˆ์ œ๋ฅผ ์ œ์‹œํ•œ๋‹ค.1. ์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ 2 1.1.1 ์กฐ์„  ์‚ฐ์—…์˜ ์ƒ์‚ฐ ํŠน์„ฑ 2 1.1.2 ์กฐ์„ ์†Œ ์ƒ์‚ฐ์‹œ์Šคํ…œ์˜ ํ•™๋ฌธ์  ์—ฐ๊ตฌ 4 1.2 ๊ด€๋ จ์—ฐ๊ตฌ๋™ํ–ฅ 7 1.2.1 ๊ณต์žฅ์˜ ๋ฒ•์น™์— ๊ด€ํ•œ ์—ฐ๊ตฌ 7 1.2.2 ์กฐ์„ ์†Œ ์ƒ์‚ฐ์„ฑ ๋ฐ ์ƒ์‚ฐ๊ด€๋ฆฌ์— ๊ด€ํ•œ ์—ฐ๊ตฌ 8 1.2.3 ๊ด€๋ จ ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์˜ ํ•œ๊ณ„์  11 1.3 ์—ฐ๊ตฌ ๋ชฉ์  ๋ฐ ๊ตฌ์„ฑ 13 2. ์กฐ์„ ์†Œ ์ƒ์‚ฐ์‹œ์Šคํ…œ์˜ ๋ฒ”ํ•จ์ˆ˜์  ํŠน์„ฑ 15 2.1 ์กฐ์„ ์†Œ ์ƒ์‚ฐ์‹œ์Šคํ…œ์˜ dynamics 16 2.1.1 ์ผ๋ฐ˜ ์ œ์กฐ์—…๊ณผ ๋‹ค๋ฅธ ์กฐ์„ ์†Œ ์ƒ์‚ฐ์‹œ์Šคํ…œ์˜ ํŠน์ง• 16 2.1.2 ์กฐ์„ ์†Œ์˜ ์ƒ์‚ฐ์‹œ์Šคํ…œ์—์„œ ๊ณ ๋ คํ•ด์•ผ ํ•  ์‚ฌํ•ญ 18 2.2 ๋ฒ”ํ•จ์ˆ˜(functional)์™€ ๋ณ€๋ถ„๋ฒ• 21 2.3 ์กฐ์„ ๊ณตํ•™ ๋ฐ ์‚ฐ์—…์—์„œ ์“ฐ์ด๋Š” ๋ฒ”ํ•จ์ˆ˜ 25 2.3.1 Principle of minimum total potential energy 25 2.3.2 ์ƒ์‚ฐ๋Ÿ‰ ๊ฒฐ์ •๋ฌธ์ œ 30 2.4 ์กฐ์„ ์†Œ ์ƒ์‚ฐ ์˜ˆ์ธก ๋ชจ๋ธ ๊ตฌํ˜„์„ ์œ„ํ•œ ํŠน์„ฑ 34 3. ์กฐ์„ ์†Œ ์ƒ์‚ฐ ์˜ˆ์ธก ๋ชจ๋ธ 37 3.1 ์กฐ์„ ์†Œ์˜ ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ 38 3.1.1 ์ฒด๊ณ„์ ์ธ ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ์˜ ์„ค์ • 38 3.1.2 Key Performance Indicator์˜ ๋„์ถœ๊ณผ์ • 41 3.2 ์กฐ์„ ์†Œ์˜ ์ƒ์‚ฐ ์š”์†Œ 43 3.2.1 ์กฐ์„ ์†Œ ์ƒ์‚ฐ ๊ด€๋ฆฌ ์ง€ํ‘œ์— ์˜ํ–ฅ์„ ์ฃผ๋Š” ์ƒ์‚ฐ ์š”์†Œ 43 3.2.2 ์ •๋ณด ๋ชจ๋ธ์— ๊ด€ํ•œ ์—ฐ๊ตฌ 44 3.2.3 The 6-factor model 47 3.3 ์กฐ์„ ์†Œ ์ƒ์‚ฐ ์˜ˆ์ธก ๋ชจ๋ธ 49 3.4 ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๋ชจ๋ธ์˜ ๊ตฌ์„ฑ 55 3.5 ๋ณธ ์—ฐ๊ตฌ์—์„œ ์‚ฌ์šฉํ•˜๋Š” ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ธฐ๋ฒ• 57 3.5.1 ์‹œ๋ฎฌ๋ ˆ์ด์…˜์˜ ์ข…๋ฅ˜ 57 3.5.2 Process-centric simulation modeling๊ณผ Dynamic resolution 63 3.6 ์กฐ์„ ์†Œ ์ƒ์‚ฐ์‹œ์Šคํ…œ ์‹œ๋ฎฌ๋ ˆ์ด์…˜์˜ ์ ˆ์ฐจ 66 4. ์ ์šฉ ์˜ˆ์ œ 69 4.1 ์กฐ์„ ์†Œ ๊ฐ€๊ณต ๊ณต์žฅ 70 4.1.1 Model 1 72 4.1.2 Model 2 77 4.1.3 Model 3 78 4.2 ๊ฐ€๊ณต ๊ณต์žฅ์˜ ๋ฒ”ํ•จ์ˆ˜์  ํŠน์„ฑ์˜ ์˜ํ–ฅ 81 4.2.1 ์ œํ’ˆ์— ๋”ฐ๋ฅธ ๊ฐ€๊ณต ์‹œ๊ฐ„์˜ ์ฐจ์ด 82 4.2.2 ์„ค๋น„ ์„ฑ๋Šฅ ๊ฐœ์„ ์˜ ํšจ๊ณผ 84 4.2.3 ์—ด๊ฐ„ ๊ฐ€๊ณต ์ž‘์—…์ž์˜ ๊ธฐ๋Ÿ‰ ์ฐจ์ด 85 4.2.4 ์˜ˆ์ œ ๊ฒฐ๊ณผ Summary 87 4.3 ๊ฐ€๊ณต ๊ณต์žฅ์˜ ์ ˆ๋‹จ ๊ณต์ • 88 4.4 ์กฐ๋ฆฝ๊ณต์žฅ์˜ Panel line ๊ณต์ • 92 5. ๊ฒฐ ๋ก  96 5.1 ๊ฒฐ๋ก  97 5.2 ๊ธฐ๋Œ€ํšจ๊ณผ 99 ์ฐธ๊ณ ๋ฌธํ—Œ 100 ๋ถ€๋ก I ๋ฒ”ํ•จ์ˆ˜(functionals)์™€ ๋ณ€๋ถ„๋ฒ•(calculus of variations) 106Docto

    Female Wage Inequality and the Minimum Wage

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    ๋ณธ ์—ฐ๊ตฌ๋Š” ํ†ต๊ณ„์ฒญ์˜ ๊ฒฝ์ œํ™œ๋™์ธ๊ตฌ 8์›” ๋ถ€๊ฐ€์กฐ์‚ฌ(2004, 2010)๋ฅผ ์ด์šฉํ•˜์—ฌ ์ตœ์ €์ž„๊ธˆ๋ณ€ํ™”๊ฐ€ ์—ฌ์„ฑ ์ž„๊ธˆ๊ทผ๋กœ์ž์˜ ์ž„๊ธˆ๋ถˆํ‰๋“ฑ์— ๋ฏธ์น˜๋Š” ํšจ๊ณผ๋ฅผ ๋ฐ˜์‚ฌ์‹ค์ (counterfactual) ์ž„๊ธˆ๋ถ„ํฌ ๋ชจํ˜•์„ ์ด์šฉํ•˜์—ฌ ๋ถ„์„ํ•œ๋‹ค. ๋ฏผ๊ฐ๋„ ๋ถ„์„ ๊ฒฐ๊ณผ ์ตœ์ €์ž„๊ธˆ์˜ ์ƒ์Šน์ด ์ƒ๋Œ€์ ์œผ๋กœ ๋‚ฎ์€ ์ž„๊ธˆ์„ ๋ฐ›๋Š” ๊ทผ๋กœ์ž์˜ ์ž„๊ธˆ์ƒ์Šน์„ ํ†ตํ•ด ๊ฐ€์ง€๋Š” ์ž„๊ธˆ๋ถˆํ‰๋“ฑ ์™„ํ™”ํšจ๊ณผ๊ฐ€ ๊ด€์ฐฐ๋˜์ง€ ์•Š์•˜๋‹ค. ์ด๋Š” ์ตœ์ €์ž„๊ธˆ ์ดํ•˜๋ฅผ ๋ฐ›๋Š” ๊ทผ๋กœ์ž ์ค‘์—์„œ ๋น„๊ณต์‹๋ถ€๋ฌธ(informal sector)์— ์ข…์‚ฌํ•˜๋Š” ๊ทผ๋กœ์ž์˜ ๋น„์ค‘์ด ๋†’๊ธฐ ๋•Œ๋ฌธ์ธ ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค.To evaluate the marginal effects of the minimum wage and other labor market conditions on female wage inequality, we estimate counterfactual wage distribution using the Economically Active Population Surveys of 2004 and 2010. We find that the rising minimum wage has an ambiguous effect on female wage inequality. We suspect that the significant share of female workers in the informal sector weakens the effect of minimum wages on female wage inequality, which calls for further studies

    Altered Intestinal Permeability and Drug Repositioning in a Post-operative Ileus Guinea Pig Model

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    Background/aims: The aim of this study is to identify the alteration in intestinal permeability with regard to the development of post-operative ileus (POI). Moreover, we investigated drug repositioning in the treatment of POI. Methods: An experimental POI model was developed using guinea pigs. To measure intestinal permeability, harvested intestinal membranes of the ileum and proximal colon was used in an Ussing chamber. To identify the mechanisms associated with altered permeability, we measured leukocyte count and expression of calprotectin, claudin-1, claudin-2, and mast cell tryptase. We compared control, POI, and drug groups (mosapride [0.3 mg/kg and 1 mg/kg, orally], glutamine [500 mg/kg, orally], or ketotifen [1 mg/kg, orally] with regard to these parameters. Results: Increased permeability after surgery significantly decreased after administration of mosapride, glutamine, or ketotifen. Leukocyte counts increased in the POI group and decreased significantly after administration of mosapride (0.3 mg/kg) in the ileum, and mosapride (0.3 mg/kg and 1 mg/kg), glutamine, or ketotifen in the proximal colon. Increased expression of calprotectin after surgery decreased after administration of mosapride (0.3 mg/kg), glutamine, or ketotifen in the ileum and proximal colon, and mosapride (1 mg/kg) in the ileum. The expression of claudin-1 decreased significantly and that of claudin-2 increased after operation. After administration of glutamine, the expression of both proteins was restored. Finally, mast cell tryptase levels increased in the POI group and decreased significantly after administration of ketotifen. Conclusions: The alteration in intestinal permeability is one of the factors involved in the pathogenesis of POI. We repositioned 3 drugs (mosapride, glutamine, and ketotifen) as novel therapeutic agents for POI.ope

    Sarcopenia and Sarcopenic Obesity as Novel Risk Factors for Gastric Carcinogenesis: A Health Checkup Cohort Study

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    Background: Insulin resistance, the primary mechanism of metabolic syndrome, promotes gastric carcinogenesis. Metabolic syndrome is associated with sarcopenia. We aimed to investigate the association between sarcopenia and gastric carcinogenesis, including precancerous conditions such as atrophic gastritis (AG), intestinal metaplasia (IM), and dysplasia. Methods: The study included adult patients who underwent gastroduodenoscopy at a checkup center. AG and IM were evaluated using endoscopy. Based on muscle mass, sarcopenia was de๏ฌned as a skeletal muscle index <1 standard deviation below the sex-speci๏ฌc mean for healthy adults aged 20โ€“39 years (cutoff point: 29.3% for males and 26.7% for females). Obesity was de๏ฌned as a body mass index (BMI) โ‰ฅ25 kg/m2 accordingtotheAsia-Paci๏ฌccriteria.Sarcopenicobesitywasde๏ฌnedasacombinationof sarcopenia and obesity. The association between gastric carcinogenesis and sarcopenia was evaluated. Results: Among 8,356 enrolled participants, 0.14 and 42.5% were diagnosed with gastric cancer and precancerous conditions, respectively. Approximately 41.7% of gastric cancer patients and 16.9% of patients with precancerous conditions were diagnosed with sarcopenia. Both sarcopenic obesity (odds ratio [OR] = 4.139, P = 0.016) and diabetes mellitus (DM) (OR = 5.152, P = 0.005) were signi๏ฌcantly associated with gastric cancer. Sarcopenia, DM, hypertension, dyslipidemia, Helicobacter pylori infection, smoking, and alcohol consumption were signi๏ฌcantly associated with precancerous conditions. Conclusions: Sarcopenia and sarcopenic obesity were associated with gastric carcinogenesis and may be novel risk factors for gastric carcinogenesis.ope

    Design and Development of Scenario-Based Simulation System to Improve Shipbuilding Execution Scheduling Assessment - A Case Study on Panel Line -

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    Todays ever-increasingly competitive shipbuilding market makes it essential for a shipbuilding company to have more efficient production processes and higher productivity as well as better design ability to obtain its competitiveness. A well-established production execution schedule plays an indispensable role to achieve this goal. Most shipbuilding companies carry out an evaluation on their mid-term plan once it is established. However, no evaluation activity exists for a production execution schedule, because practically all the companies depend on the field workers for the production execution scheduling. In this study, a prototype of a ship production execution schedule evaluation system is developed based on the component based design (CBD) methodology. This system enables one to make a production execution schedule that reflects upto-date shipyard situation and to validate whether the schedule is feasible or not by running a production simulation according to the schedule. Users can also make use of the system as a decision supporting tool that compares several different execution schedules and evaluates which one is the best execution schedule.๋ณธ ์—ฐ๊ตฌ๋Š” ์ง€์‹๊ฒฝ์ œ๋ถ€ ๊ธ€๋กœ๋ฒŒ์ „๋ฌธ๊ธฐ์ˆ ๊ฐœ๋ฐœ์‚ฌ์—… Smart Work ๊ธฐ๋ฐ˜ ์กฐ์„ ์ƒ์‚ฐ์‹คํ–‰์‹œ์Šคํ…œ ๊ฐœ๋ฐœ๊ณผ์ œ (10039739), ์‚ฐ์—…์›์ฒœ๊ธฐ์ˆ ๊ฐœ๋ฐœ์‚ฌ์—… ์‹œ๋ฎฌ๋ ˆ์ด์…˜ ๊ธฐ ๋ฐ˜์˜ ์„ ๋ฐ• ๋ฐ ํ•ด์–‘ํ”Œ๋žœํŠธ ์ƒ์‚ฐ๊ธฐ์ˆ  ๊ฐœ๋ฐœ๊ณผ์ œ (10035331)์˜ ์ง€์›์„ ๋ฐ›์•„ ์ˆ˜ํ–‰ํ•˜์˜€์Œ.OAIID:oai:osos.snu.ac.kr:snu2013-01/102/0000001908/4SEQ:4PERF_CD:SNU2013-01EVAL_ITEM_CD:102USER_ID:0000001908ADJUST_YN:YEMP_ID:A002495DEPT_CD:414CITE_RATE:0FILENAME:์ฒจ๋ถ€๋œ ๋‚ด์—ญ์ด ์—†์Šต๋‹ˆ๋‹ค.DEPT_NM:์กฐ์„ ํ•ด์–‘๊ณตํ•™๊ณผEMAIL:[email protected]_YN:NCONFIRM:

    Peri-operative Inflammatory Marker as a Predictive Factor for Prolonged Post-operative Ileus After Gastrectomy for Gastric Cancer

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    Background/aims: Although prolonged post-operative ileus (PPOI) is an important factor for the prolonged length of post-operative hospital stay, there is still a lack of effective predictive and therapeutic methods for PPOI. Previous studies reported that increased inflammatory markers, such as C-reactive protein (CRP) level and neutrophil to lymphocyte ratio (NLR), are associated with malignancies. The aim of our study is to elucidate the association between peri-operative inflammatory markers and PPOI after gastrectomy for gastric cancer. Methods: We enrolled patients who received gastrectomy for gastric cancer from June 2013 to January 2016 at a single tertiary referral center in Seoul, Korea. We evaluated peri-operative inflammatory markers, including CRP level, NLR, and platelet to lymphocyte ratio (PLR) of enrolled patients. We compared these data between control group and PPOI group. Results: A total of 390 subjects were enrolled in this study, and 132 patients (33.8%) showed PPOI. In univariate analysis, preoperative CRP level and NLR, post-operative day (POD) 1 CRP level, NLR, and PLR, and POD3 CRP level, NLR, and PLR were significantly associated with PPOI. In multivariate analysis, preoperative NLR (P = 0.014), POD1 NLR (P = 0.019), POD3 CRP (P = 0.004), and POD3 NLR (P = 0.008) were independent risk factors for PPOI. Conclusions: Peri-operative inflammatory markers, such as CRP level and NLR, are useful predictive factors for PPOI who received gastrectomy for gastric cancer. Moreover, prophylactic antibiotics and anti-inflammatory drugs can be preventive and therapeutic agents for PPOI.ope

    Triglyceride-glucose index is associated with gastroesophageal reflux disease and erosive reflux disease: a health checkup cohort study

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    The triglyceride-glucose (TyG) index was proposed as a useful marker of metabolic syndrome. Insulin resistance, the main mechanism underlying metabolic syndrome, is related to gastroesophageal reflux disease (GERD). This study aimed to elucidate the association between the TyG index and GERD/erosive reflux disease (ERD). We retrospectively reviewed the electronic medical records of patients who underwent gastroduodenoscopy at a checkup center. The calculation of TyG index used following formula: ln (fasting triglycerides [mg/dL] ร— fasting glucose [mg/dL]/2). We divided the patients into four groups according to the TyG index quartile (Q). We evaluated the relationship between the alteration of the TyG index and GERD in patients who received health checkups two times. Among the 52,605 enrolled patients, 3073 (5.8%) and 434 (0.8%) were diagnosed with GERD and ERD, respectively. The odds ratios (ORs) for GERD in the TyG index progressively increased across quartiles (P < 0.001): Q2 (OR = 2.477), Q3 (OR = 3.013), and Q4 (OR = 4.027) compared with Q1, which was used as a reference, respectively. Those for ERD also progressively increased across quartiles (P < 0.001): Q2 (OR = 4.264), Q3 (OR = 4.841), and Q4 (OR = 7.390) compared with Q1, respectively. Moreover, the degree of TyG index increase during the first and second tests in the GERD group was more prominent than in the control group (P = 0.001). In conclusion, the higher TyG index was significantly associated with GERD. The TyG index may be a novel predictive biomarker of GERD and ERD.ope
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