15 research outputs found

    Experimental Study on the Motion of Floating Structure for Design of Wave Energy Generation Systems

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    In this paper, a measurement technique which can measure simultaneously the motions of a free-floating structure and the flows around it is introduced. To investigate the flow field and the motion of the floater, we constructed a measurement system with which analysis on the results of the interactions between fluid flows and structures motions was carried out. The measurement system consists of four cameras, a laser, and a host computer. The laser was used to illuminate the tracer particles. The particles' images were used to reconstruct the 3D measurement volume. The study focuses on the influences of the fluid viscosity onto the motion of the floating structure. A cylindrical structure (d=30mm, L=100mm) was put over the water surface. The motions of the floating structure was produced by the wave generated in the water channel. The floating structure is made of acrylic and the waves were generated by a DC servo motor which was installed at the top of the channel. 4 wave conditions were generated by the motor rotation speed with 40rpm, 46rpm, 53rpm and 59rpm. The wave height and frequency were measured by a ultrasound-based level sensor(UltraLab ULS 20130). After confirming the wave generated with the motor speed 40rpm to be optimal to the actual sea condition, the floating model was installed in the water channel. Simultaneous measurement was performed for the structure's motion and the flow motion around it. For the measurement of the structure's motions, โ€˜Bidirectional Motion Tracking Algorithmโ€™ was adopted as target tracking method. On the other hand, For the measurement of the flow motion, tomographic flow visualization technique in which MART algorithm was used. The structure's motions and the flow motions were quantitatively measured by the constructed measurement system, and the their feasibility for the study of viscosity effects of the waves was confirmed.์ œ1์žฅ ์„œ ๋ก  1 1.1 ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ ๋ฐ ๋ฐฐ๊ฒฝ 1 1.2 ์—ฐ๊ตฌ์˜ ๋ชฉ์  2 1.3 ํŒŒ๋ ฅ๋ฐœ์ „์‹œ์Šคํ…œ์˜ ๊ฐœ์š” 3 1.4 ํŒŒ๋ ฅ๋ฐœ์ „์‹œ์Šคํ…œ์˜ ๋ถ„๋ฅ˜ 6 ์ œ2์žฅ ํŒŒ๋ž‘์— ๋”ฐ๋ฅธ ๋ถ€์œ ์ฒด ์šด๋™ ์ธก์ • ํ•ด์„ 14 2.1 ์‹คํ—˜์žฅ์น˜ ๋ฐ ๋ฐฉ๋ฒ• 14 2.2 ํŒŒ ๋ฐœ์ƒ ์‹คํ—˜ ๋ฐ ๊ฒฐ๊ณผ 29 2.3 ๋ถ€์œ ์ฒด ์šด๋™ ์ธก์ • ์›๋ฆฌ ๋ฐ ์ธก์ • ๊ฒฐ๊ณผ 34 2.4 ๋ถ€์œ ์ฒด ์ฃผ์œ„ ์œ ๋™์žฅ ์ธก์ • ์›๋ฆฌ ๋ฐ ์ธก์ • ๊ฒฐ๊ณผ 47 ์ œ3์žฅ ๊ฒฐ๋ก  77 ์ฐธ๊ณ ๋ฌธํ—Œ 7

    ํ†ต์‹ ์šฉ ์†Œํ”„ํŠธ์›จ์–ด์˜ ์‚ฌ์šฉ์ž ์ธํ„ฐํŽ˜์ด์Šค ๋””์ž์ธ์— ๊ด€ํ•œ ์—ฐ๊ตฌ : GUI๋ฅผ ์ค‘์‹ฌ์œผ๋กœ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์‚ฐ์—…๋””์ž์ธ๊ณผ ์‹œ๊ฐ๋””์ž์ธ์ „๊ณต,1995.Maste

    Incidence and risk of osteoporotic refractures in cancer survivors compared to controls - a nationwide claims study in Korea

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๋ณด๊ฑด๋Œ€ํ•™์› ๋ณด๊ฑดํ•™๊ณผ(๋ณด๊ฑดํ•™์ „๊ณต), 2020. 8. ์„ฑ์ฃผํ—Œ.Background: Osteoporosis is the most common bone disorder and especially occurred on hip and vertebrae and frequently worsened to osteoporotic fracture. Osteoporotic fracture causes high mortality by disabling the physical activities. Incidence of cancer is a substantial risk factor on osteoporotic fracture and especially breast and prostate cancer contribute to incidence of refractures. Furthermore, relative risk of mortality of refracture patient is 1.4 to fracture patients who had no relapse. Recently, Fracture Liaison Service (FLS) and high adherence rate of Bisphosphonate have reduced refracture rate on cancer patients. Although there are prior studies researching the association of refracture and cancer diagnosis, few studies with larger subjects and long-term time series study observed the refracture rate on cancer patients. The study purpose is to comprehend the overall incidence rate and survival rate of osteoporotic fracture and relapse on cancer patients and primary risk factors of osteoporotic fracture following the appropriate policy making which includes persistent monitoring on high-risk group. Methods: Using patients tailored claim data of National Health Insurance Services (NHIS) from 2006 to 2018, osteoporotic fracture patients who have history of breast or prostate cancer was set to exposure group and no history of cancer as controls to make the retrospective nested cohort study. To ascertain the fracture code as osteoporotic fracture, patients older than 50 years old were only included and subjects who had history of osteoporotic fracture in 2006 were excluded in the analysis. Hip, vertebra, radius and humerus fractures were defined by main or sub disorder with ICD-10 codes and operational codes. Refracture was defined as secondary fracture more or equal than 180 days after primary fracture index date. 1:1 Propensity score matching with age, sex, level of insurance payment, residence, Charlsons comorbidity index excluding breast and prostate cancer were conducted. Baseline demographic characteristics of exposure and control group will be analyzed by Pearsons chi-square test to categorical variable and student t-test to continuous variable. Primary endpoint is the incidence rate of osteoporotic refracture. Secondary endpoint will be two types of cancer and cumulative incidence ratio of osteoporotic fractures in each fracture type and total fracture Survival rate will be calculated by cox-proportional hazards model with covariates including age, sex, location, CCI score. Results: 1,179,400 patients were diagnosed as having primary osteoporotic fracture and 23,202 patients are cancer patients comorbid with osteoporotic fracture. Compared to both control group before and after propensity score matching, patients with cancer history were statistically lower survival rate. Odds ratio of refracture comorbid with cancer was higher in overall fractures while stratification of OR showed that cancer comorbidity had lower odds ratio than patients who had no cancer history. Vertebral fractures cumulative refracture rate was the highest in each group and refracture of radius, hip, humerus followed in sequence. Except for hip fracture, there is statistically different in trend of refracture incidence and older age was the most powerful covariate of mortality (HR = 1.941, CI = 1.892, 1.991) Conclusion: Cancer patients have higher incidence and mortality of most types of osteoporotic refracture than patients who have no history on cancer except for vertebral cancer. Longitudinal follow-up cares and adding medication and chemotherapy records are required to monitor cancer patients to prevent relapse of fracture.์—ฐ๊ตฌ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์ : ๊ณจ๋‹ค๊ณต์ฆ์€ ๊ฐ€์žฅ ํ”ํ•œ ๊ณจ์งˆํ™˜ ์ค‘ ํ•˜๋‚˜๋กœ ๊ณ ๊ด€์ ˆ ๋ฐ ์ฒ™์ถ”์—์„œ ๊ฐ€์žฅ ๋งŽ์ด ๋ฐœ์ƒํ•˜๋ฉฐ, ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ๋กœ ์ž์ฃผ ์•…ํ™”๋œ๋‹ค. ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ์€ ์‹ ์ฒด ๊ฑฐ๋™์„ ์–ด๋ ต๊ฒŒ ํ•˜์—ฌ ์š•์ฐฝ, ์š”๋กœ๊ฐ์—ผ ๋“ฑ ๋‚ด๊ณผ์  ํ•ฉ๋ณ‘์ฆ ๋ฐ ์‚ฌ๋ง๋ฅ ์„ ๋†’์ด๋ฉฐ ์•”์˜ ๋ฐœ์ƒ๋„ ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ ๋ฐœ์ƒ์˜ ์œ ์˜ํ•œ ์š”์ธ์ด ๋œ๋‹ค. ๊ฑฐ์˜ ๋ชจ๋“  ์ข…๋ฅ˜์˜ ์•”์€ ํ•ญ์•”์š”๋ฒ• ๋ฐ ๋ฉด์—ญ ๋ฐ˜์‘ ๋“ฑ์œผ๋กœ ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ์„ ์œ ๋ฐœ์‹œํ‚ค๋Š” ์œ„ํ—˜์š”์ธ์ด ๋˜๋ฉฐ, ์ƒ๋Œ€์ ์œผ๋กœ ์•”์˜ ๋ณ‘๋ ฅ์ด ์—†๋Š” ์‚ฌ๋žŒ๋“ค๋ณด๋‹ค ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ์„ ํ˜ธ๋ฐœ์‹œํ‚ฌ ์ˆ˜ ์žˆ๋‹ค. ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ์€ ์žฌ๊ณจ์ ˆ์˜ ์˜ˆ๋ฐฉ์ด ์ค‘์š”ํ•œ๋ฐ, ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ์ด ํ•œ ๋ฒˆ๋งŒ ์ผ์–ด๋‚œ ํ™˜์ž์— ๋น„ํ•˜์—ฌ ์žฌ๊ณจ์ ˆ์ด ๋ฐœ์ƒํ•œ ํ™˜์ž๋Š” ์‚ฌ๋ง์˜ ์ƒ๋Œ€ ์œ„ํ—˜๋„๊ฐ€ 1.4๋ฐฐ ๋†’์•„์ง€๋Š” ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๊ณจ์ ˆ ์˜ˆ๋ฐฉ ํ”„๋กœ๊ทธ๋žจ ๋ฐ ๋†’์€ ๋ณต์•ฝ ์ˆœ์‘๋„๊ฐ€ ์•” ํ™˜์ž์˜ ๊ณจ์ ˆ ์˜ˆ๋ฐฉ์— ๋„์›€์ด ๋œ๋‹ค๊ณ  ์™ธ๊ตญ์—์„œ ์—ฐ๊ตฌ๋œ ๋ฐ”๊ฐ€ ์žˆ์œผ๋‚˜ ์•” ํ™˜์ž ๋ฐ ๊ณจ์ ˆ ํ™˜์ž์˜ ์žฌ๊ณจ์ ˆ ๋ฐœ์ƒ์— ๋Œ€ํ•˜์—ฌ ๋น„๊ต์  ๋Œ€๊ทœ๋ชจ์˜ ์—ฐ๊ตฌ๋‚˜ ์žฅ๊ธฐ ์ถ”์  ๊ด€์ฐฐ ์—ฐ๊ตฌ๋Š” ๋ถ€์กฑํ•œ ์‹ค์ •์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•˜์—ฌ ์ „์ฒด์ ์ธ ์ฃผ์š” ์•” ํ™˜์ž์—์„œ์˜ ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ ๋ฐ ์žฌ๊ณจ์ ˆ์˜ ๋ฐœ์ƒ์œจ์„ ํŒŒ์•…ํ•˜๊ณ  ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ ๋ฐœ์ƒ์˜ ์œ„ํ—˜ ์š”์ธ์„ ๋ถ„์„ํ•˜์—ฌ ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ์˜ ๊ณ ์œ„๊ตฐ์„ ํŒŒ์•…ํ•˜๊ณ , ๊ณจ์ ˆ ์˜ˆ๋ฐฉ์„ ์ ๊ทน์ ์œผ๋กœ ๋„์ž…ํ•  ํ•„์š”์„ฑ์„ ๊ฒ€ํ† ํ•˜๊ณ ์ž ํ•œ๋‹ค. ์—ฐ๊ตฌ๋ฐฉ๋ฒ•: ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฑด๊ฐ•๋ณดํ—˜๊ณต๋‹จ์˜ ๋งž์ถคํ˜• ์ฒญ๊ตฌ์ž๋ฃŒ๋ฅผ ์‹ ์ฒญํ•˜์—ฌ 2006๋…„๋ถ€ํ„ฐ 2018๋…„ ์•ˆ์— ์œ ๋ฐฉ์•” ๋ฐ ์ „๋ฆฝ์„ ์•”, ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ธฐ๋ก์ด ์žˆ๋Š” ํ™˜์ž๊ตฐ์„ ์ถ”์ถœํ•˜์˜€๋‹ค. ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ์˜ ๋ณ‘๋ ฅ์ด ์žˆ๋Š” ํ™˜์ž ์ค‘ ๊ณจ์ ˆ๋ณด๋‹ค ๋จผ์ € ์œ ๋ฐฉ์•”, ์ „๋ฆฝ์„ ์•” ๋ณ‘๋ ฅ์ด ์žˆ๋Š” ๊ฒฝ์šฐ๋ฅผ ๋…ธ์ถœ๊ตฐ์œผ๋กœ ์„ค์ •ํ•˜์˜€๊ณ , ์•” ๋ณ‘๋ ฅ์ด ์—†๋Š” ๊ณจ์ ˆ ํ™˜์ž๋ฅผ ๋Œ€์กฐ๊ตฐ์œผ๋กœ ์„ค์ •ํ•˜์˜€๋‹ค. ๊ณจ์ ˆ์˜ ์ง„๋‹จ ์ฝ”๋“œ๋ฅผ ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ๋กœ ์„ค์ •ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ 50์„ธ ์ด์ƒ์˜ ํ™˜์ž๋งŒ ์—ฐ๊ตฌ์— ํฌํ•จํ•˜์˜€๊ณ  2006๋…„์— ๊ณจ์ ˆ ๊ด€๋ จ ๊ธฐ๋ก์ด ์žˆ๋Š” ํ™˜์ž๋Š” ์—ฐ๊ตฌ ๋Œ€์ƒ์—์„œ ์žฌ์™ธํ•˜์˜€๋‹ค. ๊ณจ์ ˆ์˜ ๋ฒ”์œ„๋Š” ๊ณ ๊ด€์ ˆ, ์ฒ™์ถ”, ์›์œ„์š”๊ณจ ๋ฐ ๊ทผ์œ„์ƒ์™„๊ณจ์ด๋ฉฐ ์žฌ๊ณจ์ ˆ์˜ ์ •์˜๋Š” ์ฒซ ๋ฒˆ์งธ ๊ณจ์ ˆ์ด ์ผ์–ด๋‚œ ์ดํ›„ ์ตœ์†Œ 180์ผ ์ดํ›„๋กœ ์„ค์ •ํ•˜์˜€์œผ๋ฉฐ, ์ฒ™์ถ” ๊ณจ์ ˆ์„ ์ œ์™ธํ•œ ๋‚˜๋จธ์ง€ ๊ณจ์ ˆ์€ ์ฒซ ๋ฒˆ์งธ ์žฌ๊ณจ์ ˆ๋งŒ ์žฌ๊ณจ์ ˆ๋กœ ์ธ์ •ํ•˜์˜€๋‹ค. 1:1 ์„ฑํ–ฅ ์ ์ˆ˜ ๋งค์นญ์„ ํ†ตํ•˜์—ฌ ์—ฐ๋ น, ์„ฑ๋ณ„, ๋ณดํ—˜์ง€๋ถˆ ๋“ฑ๊ธ‰, ๊ฑฐ์ฃผ์ง€์—ญ, ๋…ธ์ถœ์— ํ•ด๋‹นํ•˜๋Š” ์•”์„ ์ œ์™ธํ•œ ์ฐฐ์Šจ๋™๋ฐ˜์งˆํ™˜์ง€์ˆ˜๋ฅผ ๊ณต๋ณ€๋Ÿ‰์œผ๋กœ ์„ค์ •ํ•˜์˜€๋‹ค. ์ผ์ฐจ ํ‰๊ฐ€ ๋ณ€์ˆ˜๋Š” ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ์žฌ๊ณจ์ ˆ์˜ ๊ตฐ๋ณ„ ๋ฐœ์ƒ๋ฅ ์ด๋ฉฐ ์ธตํ™” ์ฝ•์Šค ๋น„๋ก€์œ„ํ—˜๋ชจํ˜•์„ ์ด์šฉํ•˜์—ฌ ์ƒ์กด์œจ์„ ์ด์ฐจ ํ‰๊ฐ€ ๋ณ€์ˆ˜๋กœ ์„ค์ •ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ: 1,179,400 ๋ช…์˜ ํ™˜์ž๋“ค์ด ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ์˜ ๋ณ‘๋ ฅ์ด ์žˆ๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๊ณ  23,202๋ช…์˜ ์ „๋ฆฝ์„  ๋ฐ ์œ ๋ฐฉ์•” ํ™˜์ž๋“ค์ด ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ์„ ๊ฒฝํ—˜ํ•˜์˜€๋‹ค. ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ๊ณผ ์žฌ๊ณจ์ ˆ์€ ์—ฐ๋„๋ณ„๋กœ ๋‹จ์กฐ์ฆ๊ฐ€ํ•˜์˜€์œผ๋ฉฐ, ์•” ํ™˜์ž์™€ ์•”์˜ ๋ณ‘๋ ฅ์ด ์—†๋Š” ํ™˜์ž ๋ชจ๋‘ ์ฒ™์ถ” ๊ณจ์ ˆ์˜ ๋ฐœ์ƒ๋ฅ ์ด ๊ฐ€์žฅ ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๊ณ , 80์„ธ์—์„œ 89์„ธ์˜ ๋ฐœ์ƒ๋ฅ ์ด ๊ฐ€์žฅ ๋†’์•˜์œผ๋ฉฐ, ์›์œ„์š”๊ณจ ๊ณจ์ ˆ์˜ ๊ฒฝ์šฐ๋Š” 60 โ€“ 69์„ธ์˜ ๋ฐœ์ƒ๋ฅ ์ด ๋ชจ๋“  ์—ฐ๋„์—์„œ ๊ฐ€์žฅ ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์„ฑํ–ฅ์ ์ˆ˜ ๋งค์นญ ์ „ํ›„๋กœ ๋น„๊ตํ•˜์˜€์„ ๋•Œ์— ์ฒ™์ถ” ๊ณจ์ ˆ์˜ ๊ฒฝ์šฐ๋งŒ ์ œ์™ธํ•˜๊ณ  ๋ชจ๋“  ๊ณจ์ ˆ์—์„œ ์•”์˜ ๋ณ‘๋ ฅ์ด ์žˆ๋Š” ๊ณจ์ ˆ ํ™˜์ž๋“ค์˜ ์ƒ์กด์œจ์ด ๋” ๋‚ฎ์•˜์œผ๋ฉฐ, ์ „์ฒด์ ์ธ ์•” ํ™˜์ž์˜ ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ์žฌ๊ณจ์ ˆ์˜ ์Šน์‚ฐ๋น„๋Š” ์•”์ด ์—†๋Š” ํ™˜์ž๋“ค๋ณด๋‹ค ๋” ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ์ง€๋งŒ ๊ณจ์ ˆ ์ข…๋ฅ˜๋ณ„๋กœ ์ธตํ™”ํ•˜์˜€์„ ๋•Œ ๊ทผ์œ„์ƒ์™„๊ณจ์˜ ๊ฒฝ์šฐ๋Š” ์˜ค์ฆˆ๋น„ ์ฐจ์ด๊ฐ€ ์œ ์˜ํ•˜์ง€ ์•Š์•˜๊ณ  ๊ณ ๊ด€์ ˆ, ์ฒ™์ถ”, ์›์œ„์š”๊ณจ์˜ ๊ฒฝ์šฐ๋Š” ์Šน์‚ฐ๋น„๊ฐ€ ์•”์ด ์žˆ๋Š” ๊ฒฝ์šฐ์— ๋” ๋‚ฎ์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ ๊ณจ์ ˆ๋ณ„ ์‚ฌ๋ง๋ฅ ์€ ๊ณ ๊ด€์ ˆ์ด ๊ฐ€์žฅ ๋†’์•˜๊ณ  ์ฒ™์ถ” ๊ณจ์ ˆ, ๊ทผ์œ„ ์ƒ์™„๊ณจ, ์›์œ„ ์š”๊ณจ ์ˆœ์ด์—ˆ๋‹ค. ๊ฑฐ์ฃผ ์ง€์—ญ์„ ์ œ์™ธํ•˜๊ณ  ์‚ฌ๋ง ์œ„ํ—˜๋น„์— ๋†’์€ ์—ฐ๋ น, ๋‚จ์„ฑ, ๋‚ฎ์€ ๋ณดํ—˜ ์ง€๋ถˆ ๋“ฑ๊ธ‰ ๋ฐ ๋†’์€ CCI score๊ฐ€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์ณค์œผ๋ฉฐ, ๋†’์€ ์—ฐ๋ น์˜ ๊ธฐ์—ฌ ์œ„ํ—˜๋„๊ฐ€ ๊ฐ€์žฅ ๋†’์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค (HR = 1.941, CI = 1.892, 1.991). ๊ฒฐ๋ก : ์•” ํ™˜์ž๋“ค์€ ์•” ๋ณ‘๋ ฅ์ด ์—†๋Š” ํ™˜์ž๋“ค๋ณด๋‹ค ๋†’์€ ์žฌ๊ณจ์ ˆ์˜ ๋ฐœ์ƒ๊ณผ ์ „์ฒด์ ์œผ๋กœ ๋‚ฎ์€ ์ƒ์กด์œจ์„ ๋ณด์˜€์œผ๋‚˜ ๊ณจ์ ˆ๋ณ„๋กœ ์ธตํ™”ํ•˜์˜€์„ ๋•Œ ์Šน์‚ฐ๋น„๋Š” ์•”์˜ ๋ณ‘๋ ฅ์ด ์—†๋Š” ๊ณจ์ ˆ ์ข…๋ฅ˜๋ณ„ ํ™˜์ž๋“ค๋ณด๋‹ค ์ผ๋ถ€ ๋‚ฎ์€ ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์•” ํ™˜์ž์—๊ฒŒ ์‚ฌ์šฉ๋œ ํ™”ํ•™ ์š”๋ฒ•์˜ ์ข…๋ฅ˜ ๋ฐ ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ๊ณจ์ ˆ ํŠน์ด์  ์•ฝ๋ฌผ ์†Œ์ง€์œจ์— ๋”ฐ๋ฅธ ์ถ”๊ฐ€์ ์ธ ์ข…๋‹จ ์—ฐ๊ตฌ๊ฐ€ ์•”์˜ ๋ณ‘๋ ฅ๊ณผ ๊ณจ๋‹ค๊ณต์ฆ์„ฑ ์žฌ๊ณจ์ ˆ ๋ฐœ์ƒ์˜ ์ธ๊ณผ์„ฑ ๋ถ„์„์„ ์œ„ํ•˜์—ฌ ํ•„์š”ํ•  ๊ฒƒ์œผ๋กœ ์ƒ๊ฐ๋œ๋‹ค.Chapter 1. Introduction 1 Chapter 2. Methods 6 2.1 Study data and participants 6 2.2 Inclusion and exclusion criteria 6 2.3 Study variables 7 2.4 Statistical analysis 8 Chapter 3. Results 10 Chapter 4. Discussion 26 4.1 Discussion 26 4.2 Conclusion 28 References 29 Appendix 33 Abstract (Korean) 38Maste

    Authentic leadership of nursing managers, Psychological safety in work teams and Intention to medication error reporting of nurses

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    ํˆฌ์•ฝ์˜ค๋ฅ˜๋ณด๊ณ ๋Š” ํˆฌ์•ฝ์˜ค๋ฅ˜๋ฅผ ๊ฐ์†Œ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ๊ฐœ์„  ํ™œ๋™ ์ค‘ ํ•˜๋‚˜๋กœ ํˆฌ์•ฝ์˜ค๋ฅ˜๋ณด๊ณ ์œจ์„ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋Š” ํˆฌ์•ฝ์˜ค๋ฅ˜ ๋ณด๊ณ ์˜๋„๋ฅผ ํ–ฅ์ƒ์‹œํ‚ค๋Š” ๊ฒƒ์€ ํ™˜์ž์•ˆ์ „์‚ฌ๊ณ ๋ฅผ ์˜ˆ๋ฐฉํ•˜๊ณ  ์žฌ๋ฐœ์„ ๋ฐฉ์ง€ํ•˜๊ธฐ ์œ„ํ•œ ๋ฐฉ์•ˆ ์ค‘ ํ•˜๋‚˜์ด๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ฐ„ํ˜ธ์‚ฌ๊ฐ€ ์ธ์‹ํ•˜๋Š” ๊ฐ„ํ˜ธ๊ด€๋ฆฌ์ž์˜ ์ง„์„ฑ๋ฆฌ๋”์‹ญ, ํŒ€ ๋‚ด ์‹ฌ๋ฆฌ์  ์•ˆ์ „๊ฐ๊ณผ ํˆฌ์•ฝ์˜ค๋ฅ˜ ๋ณด๊ณ ์˜๋„์™€์˜ ๊ด€๊ณ„๋ฅผ ํŒŒ์•…ํ•˜๊ธฐ ์œ„ํ•œ ์„œ์ˆ ์  ์กฐ์‚ฌ์—ฐ๊ตฌ๋ฅผ ์‹œํ–‰ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ๊ฐ„ํ˜ธ์‚ฌ 167๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ๊ตฌ์กฐํ™”๋œ ์„ค๋ฌธ์ง€๋ฅผ ์ด์šฉํ•˜์—ฌ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€์œผ๋ฉฐ, ์ž๋ฃŒ ๋ถ„์„์€ SPSS statistics 26.0๊ณผ SPSS Process macro ver 3.4.1 ํ”„๋กœ๊ทธ๋žจ์„ ์ด์šฉํ•˜์—ฌ ๋นˆ๋„๋ถ„์„, ๊ธฐ์ˆ ํ†ต๊ณ„, independent t-test, ANOVA, Pearsonโ€™s correlation coefficient, ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„, ๋ถ€ํŠธ์ŠคํŠธ๋žฉ์„ ์ด์šฉํ•œ Process macro model 4๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ ์ง„์„ฑ๋ฆฌ๋”์‹ญ 3.41ยฑ.56์ , ์‹ฌ๋ฆฌ์  ์•ˆ์ „๊ฐ 3.50ยฑ.52์ , ํˆฌ์•ฝ์˜ค๋ฅ˜ ๋ณด๊ณ ์˜๋„ 71.06ยฑ19.13์ ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๊ณ , ํˆฌ์•ฝ์˜ค๋ฅ˜ ๋ณด๊ณ ์˜๋„์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ์œผ๋กœ๋Š” 3ํšŒ ์ด์ƒ์˜ ํˆฌ์•ฝ์˜ค๋ฅ˜ ๊ด€๋ จ ๊ต์œก์ฐธ์—ฌ(ฮฒ=.28, p=.003), ํŒ€ ๋‚ด ์‹ฌ๋ฆฌ์  ์•ˆ์ „๊ฐ(ฮฒ=.21, p=.004), ํˆฌ์•ฝ ๊ทผ์ ‘์˜ค๋ฅ˜๊ฒฝํ—˜(ฮฒ=-.17, p=.041)์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ง„์„ฑ๋ฆฌ๋”์‹ญ์ด ํˆฌ์•ฝ์˜ค๋ฅ˜ ๋ณด๊ณ ์˜๋„์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์—์„œ ์‹ฌ๋ฆฌ์  ์•ˆ์ „๊ฐ์„ ํ†ตํ•œ ๊ฐ„์ ‘ํšจ๊ณผ๊ฐ€ ๊ฒ€์ฆ๋˜์–ด(ฮฒ=.2042, CI=.0025~.4892) ๊ฐ„ํ˜ธ๊ด€๋ฆฌ์ž์˜ ์ง„์„ฑ๋ฆฌ๋”์‹ญ๊ณผ ๊ฐ„ํ˜ธ์‚ฌ์˜ ํˆฌ์•ฝ์˜ค๋ฅ˜ ๋ณด๊ณ ์˜๋„ ์‚ฌ์ด์—์„œ ํŒ€ ๋‚ด ์‹ฌ๋ฆฌ์  ์•ˆ์ „๊ฐ์€ ๋งค๊ฐœ ์—ญํ• ์„ ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๊ฒ€์ฆ๋˜์—ˆ๋‹ค. ์ด์ƒ์˜ ์—ฐ๊ตฌ๊ฒฐ๊ณผ๋ฅผ ์ข…ํ•ฉํ•˜๋ฉด, ํˆฌ์•ฝ์˜ค๋ฅ˜ ๋ณด๊ณ ์˜๋„๋ฅผ ๋†’์ด๊ธฐ ์œ„ํ•ด์„œ๋Š” ํˆฌ์•ฝ์˜ค๋ฅ˜์— ๊ด€ํ•œ ์ •์˜, ์‚ฌ๋ก€, ํˆฌ์•ฝ์˜ค๋ฅ˜๋ณด๊ณ  ์ฒด๊ณ„, ์˜ค๋ฅ˜ ๋ณด๊ณ ์˜ ์ค‘์š”์„ฑ์ด ํฌํ•จ๋œ ์ฒด๊ณ„์ ์ด๊ณ  ๋ฐ˜๋ณต์ ์ธ ํˆฌ์•ฝ์˜ค๋ฅ˜ ๊ด€๋ จ ๊ต์œก ํ”„๋กœ๊ทธ๋žจ์„ ๊ตฌ์ถ•ํ•˜๋Š” ๊ฒƒ์ด ํ•„์š”ํ•˜๊ณ , ํˆฌ์•ฝ์˜ค๋ฅ˜๋ณด๊ณ ๋กœ ๊ฒช์€ ๊ฐ„ํ˜ธ์‚ฌ์˜ ๋ถ€์ •์ ์ธ ๊ฒฝํ—˜์„ ๊ทน๋ณตํ•˜๊ณ , ์‹ฌ๋ฆฌ์  ์•ˆ์ „๊ฐ์„ ์ฆ์ง„์‹œํ‚ค๊ธฐ ์œ„ํ•œ ์กฐ์ง์  ์ ‘๊ทผ ์ „๋žต๊ณผ ๊ฐ„ํ˜ธ๊ด€๋ฆฌ์ž์˜ ์ง„์„ฑ๋ฆฌ๋”์‹ญ ๊ฐœ๋ฐœ์„ ์œ„ํ•œ ๋…ธ๋ ฅ์ด ํ•„์š”ํ•˜๋‹ค. The medication error report is one of the improvement activities to reduce medication error, and improving the intention of reporting medication error that can predict medication error rate is one of the measures to prevent patient safety accidents. Thus, in this study, a descriptive investigation study was conducted to identify the relationship between the authentic leadership of the nurse's perceived nursing manager, the psychological safety in work team, and the intent to report the medication error. This study was conducted on 167 nurses using structured questionnaires. The collected data were analyzed by the SPSS WIN 26.0 and SPSSใ€€process macro ver 3.4.1 software program and descriptive statistics, such as independent t-test, ANOVA, Pearson/s correlation coedfficient, multiple linear regressionanlysis, Scheff test, and mediation analysis. Mediation alalysis was conducted using SPSS macro process model 4 to examine mediationi effect of psychological safety in work team on the relationship between authentic leadership of nursing managers and intention to medication error reporting of nurses. The study found that authentic leadership was 3.41ยฑ.56 points, psychological safety was 3.50ยฑ.52 points, and intention to medication error reporting was 71.06ยฑ19.13 points, and factors affecting the intention to medication error reporting of nurses were participation in education related to medication error (ฮฒ =.28, p=.003), psychological safety in work team( =.21, p=.ฮฒ 004), experience of near miss related medication error(ฮฒ=-.17 and p=.041). The specific indirect effect through psychological safety in work team was ฮฒ=.2042(CI=.0025-4892). Between the authentic leadership of nursing manager and the intention of the nurse to report an error in medication, psychological safety in the team has been verified to play a mediating role. These results showed that it is necessary to establish a systematic and repetitive medication error-related education program that includes the definition of medication error, cases, medication error reporting system, and the importance of error reporting, and to overcome the negative experiences of nurses who have experienced medication error reporting, and to make efforts to develop authentic leadership of nursing managers and to enhance psychological safety in work team.open์„

    Impact of Patent Invalidity on the Appraisal of Proper Compensation for the Employeeโ€™s Invention

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    Inhibitory effects of Artemisia asiatica on osteoclast formation induced by periodontopathogens

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    Bone resorption surrounding tooth root causes tooth loss in periodontitis patients. Osteoclast has bone resorption activity. Effects of Artemisia asiatica on bone resorption induced by periodontopathogens, Porphyromonas gingivalis and Treponema denticola, were examined using co-culture systems of mouse osteoblasts and bone marrow cells. Addition of A. asiatica ethanol extract to bacterial sonicate abolished bacteria-induced osteoclastogenesis. To determine inhibitory mechanism of A. asiatica against osteoclastogenesis, effects of A. asiatica on expressions of osteoclastogenesis-inducing factors such as receptor activator of NF-ฮบB ligand (RANKL), prostaglandin E2 (PGE2), interleukin (IL)-1, and tumor necrosis factor (TNF)-ฮฑ, in osteoblasts were examined. A. asiatica suppressed expressions of RANKL, PGE2, IL-1ฮฒ, and TNF-ฮฑ increased by each bacterial sonicate. These results suggest inhibitory action of A. asiatica against osteoclastogenesis is associated with downregulations of RANKL, PGE2, IL-1ฮฒ, and TNF-ฮฑ expressions.restrictio

    Prostaglandin E2 Is a Main Mediator in Receptor Activator of Nuclear Factor-ฮบB Ligand-Dependent Osteoclastogenesis Induced by Porphyromonas gingivalis, Treponema denticola, and Treponema socranskii

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    BACKGROUND: Periodontitis is an inflammatory disease that often leads to destruction of alveolar bone; a number of bacteria in subgingival plaque are associated with bone destruction in periodontitis. To understand the mechanism of how periodontopathogens induce osteoclastogenesis, we determined which mediators are involved in the osteoclastogenesis. METHODS: We investigated effects of sonicates from three periodontopathic bacteria, Porphyromonas gingivalis, Treponema denticola, and Treponema socranskii, on osteoclast formation in a co-culture system of mouse calvaria-derived osteoblasts and bone marrow cells. The osteoclast formation was determined by tartrate resistant acid phosphatase (TRAP) staining. The expression of the receptor activator of nuclear factor-kappa B ligand (RANKL), prostaglandin E(2) (PGE(2)) and osteoprotegerin (OPG) in mouse calvaria-derived osteoblasts was determined by immunoassay. RESULTS: Each bacterial sonicate induced the osteoclast formation in the co-culture system. These bacterial sonicates increased the expression of RANKL and PGE(2), and decreased the expression of OPG in osteoblasts. The addition of OPG, an inhibitor of RANKL, in the co-culture completely suppressed the osteoclastogenesis that was stimulated by each bacterial sonicate. Indomethacin, which is an inhibitor of PGE(2) synthesis, reduced more than 88% of the osteoclast formation induced by each bacterial sonicate. Indomethacin inhibited more than 80% of RANKL expression in osteoblasts induced by T. denticola and T. socranskii, and 59% by P. gingivalis. Indomethacin completely recovered the depression of OPG expression in osteoblasts by T. denticola and T. socranskii to the level of the untreated osteoblasts. Indomethacin recovered the reduction of OPG expression by P. gingivalis to 67%. CONCLUSION: These findings suggest that the osteoclastogenesis by P. gingivalis, T. denticola, and T. socranskii is mediated by a RANKL-dependent pathway and that PGE(2) is a main factor in the pathway by the enhancing of RANKL expression and the depression of osteoprotegerin, a RANKL inhibitor.restrictio

    Effect of Treponema lecithinolyticum lipopolysaccharide on matrix metalloproteinase-9 expression

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    Bone resorption involves sequential stages of osteoclast precursor migration and differen-tiation of osteoclast precursors into multinucleated osteoclasts. Stromal cell derived factor (SDF)-1 is a chemotactic factor for osteoclast precursor migration. Matrix metalloproteinase (MMP)-9 is involved in migration of osteoclast precursors and activation of interleukin(IL)-1beta. Alveolar bone destruction is a characteristic feature of periodontal disease. Treponema lecithinolyticum is a oral spirochete isolated from the periodontal lesions. The effect of lipopolysaccharide(LPS) from T. lecithinolyticum on expression of SDF-1 and MMP-9 was examined in cocultures of bone marrow cells and osteblasts derived from mouse calvariae. T. lecithinolyticum LPS increased expression of MMP-9 in the coculture. Polymyxin B, an inhibitor of LPS, abolished the increase of MMP-9 mRNA expression by LPS. LPS did not increase the expression of SDF-1, IL-1beta and tumor necrosis factor(TNF)-alpha mRNA in cocultures. Prostaglandin E2(PGE2) up-regulated the expression of MMP-9 and NS398, an inhibitor of PGE2 synthesis, down-regulated the induction of MMP-9 expression by T. lecithinolyticm LPS. These results suggest that T. lecithinolytium LPS increases MMP-9 expression in bone cells via PGE2 and that the induction of MMP-9 expression by T. lecithinolyticum LPS is involved in alveolar bone destruction of periodontitis patients by the increase of osteoclast precursor migration and the activation of bone resorption-inducing cytokine.ope
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