90 research outputs found
ํจ๋ฐฑ์ฐ ๋ถ๋น๋๋ฌด์ ์ง๋จ ๋ด ์ ์ ๋ณ์ด์ ์ข ์ ํน์ฑ
ํ์๋
ผ๋ฌธ(์์ฌ) -- ์์ธ๋ํ๊ต๋ํ์ : ๋์
์๋ช
๊ณผํ๋ํ ์ฐ๋ฆผ๊ณผํ๋ถ(์ฐ๋ฆผํ๊ฒฝํ์ ๊ณต), 2023. 2. ๊ฐ๊ท์.Abies nephrolepis (Trautv. ex Maxim.) Maxim. is a subalpine conifer species and its southernmost natural populations are distributed in South Korea. Conservation actions should be considered as population decline is expected due to climate change. For ex-situ conservation of A. nephrolepis, securing enough genetic diversity and quantity of seeds is important. There were several studies on the weak genetic variation among populations of A. nephrolepis in South Korea, but there were few studies on genetic variation within a population. This study aimed to provide a reference for ex-situ conservation of an A. nephrolepis population in South Korea. Genetic variations and seed characteristics were investigated in an A. nephrolepis population at Mt. Hambaeksan, Gangwon-do, South Korea. The population of A. nephorlepis in Mt. Hambaeksan had the observed heterozygosity of 0.809 and the expected heterozygosity of 0.820. Spatial autocorrelation analysis revealed that the individuals had a positive genetic relationship within a 30 m distance, which was interpreted as a minimal sampling distance. The bigger trees had a stronger spatial genetic structure than the smaller trees. The inferred number of clusters (K) within a population did not converge: STRUCTURE inferred K=1 while GENELAND inferred K=2, but principal coordinates analysis (PCoA) supported K=1. Sampling simulation found that at least 20 individuals need to be sampled to secure the genetic diversity in a population. The seeds of A. nephrolepis population in Mt. Hambaeksan had similar characteristics to other populations in South Korea, with a germination percentage of 32.2%. However, there was a lower purity, probably caused by the higher temperature and less precipitation in the sampling year. The correlation analysis showed that the seed weight could be the most effective indicator of seed quality. The mother trees that were genetically closer to overall individuals had poorer seed quality, but it was insignificant. This study provided some strategies that contribute to the ex-situ conservation of A. nephrolepis. Further studies on the mating system and gene dispersal are needed to improve the understanding of the genetic structure of an A. nephrolepis population.๋ถ๋น๋๋ฌด Abies nephrolepis (Trautv. ex Maxim.) Maxim.๋ ์๊ณ ์ฐ ์นจ์ฝ์์ข
์ ํ๋๋ก ๋จ๋ฐฉํ๊ณ ์ง๋จ์ด ๊ตญ๋ด์ ๋ถํฌํด ์๋ค. ํ์ฌ ๋ถ๋น๋๋ฌด๋ ๊ธฐํ๋ณํ ์ทจ์ฝ์ข
์ผ๋ก ์ ํด๊ฐ ์งํ๋๊ณ ์์ด ๋ณด์ ์ ์ค์์ฑ์ด ์ฆ๊ฐํ๊ณ ์์ผ๋ฉฐ, ํ์ง์ธ ๋ณด์ ์ ์ํด์๋ ์ ์ ๋ค์์ฑ๊ณผ ์ข
์์ ๋ํ ์ดํด๊ฐ ํ์์ ์ด๋ค. ๊ทธ ๋์ ๋ถ๋น๋๋ฌด ์ง๋จ์ ๋ํด์๋ ์ง๋จ ๊ฐ ๋ณ์ด๋ฅผ ํ์ธํ๋ ์ฐ๊ตฌ๊ฐ ์ฃผ๋ก ์งํ๋์ด ์์ผ๋ฉฐ, ์ง๋จ ๊ฐ ๋ถํ๊ฐ ์์์ ํ์ธํ์๋ค. ๊ทธ๋ฌ๋ ๋ถ๋น๋๋ฌด์ ์ง๋จ ๋ด ๋ณ์ด์ ๋ํ ์ฐ๊ตฌ๋ ๊ฑฐ์ ์งํ๋ ๋ฐ๊ฐ ์๋ค. ๋ณธ ์ฐ๊ตฌ๋ ๋ถ๋น๋๋ฌด์ ํ์ง์ธ ๋ณด์ ์ ๋ต ์๋ฆฝ์ ํ์ํ ์ ๋ณด๋ฅผ ์ ๊ณตํ๋ ๊ฒ์ ๋ชฉํ๋ก ํ์๋ค. ์ด๋ฅผ ์ํด ํจ๋ฐฑ์ฐ ๋ถ๋น๋๋ฌด์ ์ง๋จ ๋ด ์ ์ ๊ตฌ์กฐ์ ์ข
์ ํน์ฑ์ ํ์
ํ๊ณ ์ ํ์๋ค. ๊ฒฐ๊ณผ์ ์ผ๋ก ํจ๋ฐฑ์ฐ ๋ถ๋น๋๋ฌด์ ์ดํ์ ํฉ๋ ๊ด์ธก์น๋ 0.809, ์ดํ์ ํฉ๋ ๊ธฐ๋์น๋ 0.820๋ก ๋ํ๋ฌ๋ค. ๊ณต๊ฐ์ ์๊ธฐ์๊ด์ฑ ๋ถ์ ๊ฒฐ๊ณผ, ๋ถ๋น๋๋ฌด ๊ฐ์ฒด๋ 30 m ์ด๋ด์์ ์๋ก ์ ์ ์ ์ผ๋ก ์ฐ๊ด๋์ด ์์์ด ํ์ธ๋์๋ค. ์ด๋ ๊ณง ์ํ๋ง์ ์์ด ๊ฐ์ฒด ๊ฐ ๊ฑฐ๋ฆฌ๊ฐ 30 m ์ด์ ๊ฐ๊ฒฉ์ด ์ ์ง๋์ด์ผ ํจ์ ์๋ฏธํ๋ค. ์ง๊ฒฝ๊ธ ๊ฐ ๊ณต๊ฐ์ ์ ์ ๊ตฌ์กฐ์ ์ ๋๋ฅผ ๋น๊ตํ ๊ฒฐ๊ณผ, ์ง๊ฒฝ์ด ํฐ ๋๋ฌด๋ค์์ ์๋์ ์ผ๋ก ๊ฐํ ๊ตฌ์กฐ๋ฅผ ๊ฐ์ง๋ ๊ฒ์ผ๋ก ํ์ธ๋์๋ค. ์ง๋จ ๋ด ํ๋ถ ์ง๋จ์ ์(K)๋ฅผ ๊ณ์ฐํ ๊ฒฐ๊ณผ, STRUCTURE์ GENELAND๋ ๊ฐ๊ฐ K=1, K=2๋ก ์ฐจ์ด๋ฅผ ๋ณด์๋ค. ๊ทธ๋ฌ๋ ์ฃผ์ขํ ๋ถ์ ๊ฒฐ๊ณผ, ํน๋ณํ ํ๋ถ ๊ตฌ์กฐ๊ฐ ๋ฐ๊ฒฌ๋์ง ์์ K=1์ ๊ฒฐ๊ณผ๊ฐ ์ง์ง๋์๋ค. ์ํ๋ง ์๋ฎฌ๋ ์ด์
๊ฒฐ๊ณผ, ์ถฉ๋ถํ ์ ์ ๋ณ์ด๋ฅผ ํ๋ณดํ๊ธฐ ์ํด์๋ ์ ์ด๋ 20 ๊ฐ์ฒด ์ด์์ด ์ฑ์ง๋์ด์ผ ํ๋ ๊ฒ์ผ๋ก ๋ํ๋ฌ๋ค. ํจ๋ฐฑ์ฐ ๋ถ๋น๋๋ฌด์ ์ข
์๋ ๊ธฐ์กด ์ฐ๊ตฌ์ ๋ค๋ฅธ ์ง๋จ๊ณผ ์ ์ฌํ ํน์ฑ์ ๋ณด์์ผ๋ฉฐ, 32.2%์ ๋ฐ์์จ์ ๋ณด์๋ค. ํ์ง๋ง ์๋์จ์ ๊ฒฝ์ฐ ๋ถ๋น๋๋ฌด ์๋ชฉ์ข
์ํ์คํ์ง์ ๋นํด ๋ค์ ๋ฎ์ ์์น๋ฅผ ๋ณด์๋ค. ์ด๋ ์ฑ์ง ์ฐ๋๊ฐ ํ๋
์ ๋นํด ๊ธฐ์จ์ด ๋ ๋์๊ณ ๊ฐ์๋์ด ๋ ์ ์๋ ๊ฒ๊ณผ ๊ด๋ จ๋์์ ๊ฒ์ผ๋ก ์ถ์ ๋์๋ค. ์๊ด๋ถ์ ๊ฒฐ๊ณผ, ์ข
์ ๋ฌด๊ฒ๊ฐ ์ข
์ ํ์ง์ ๊ฐ์ฅ ํจ๊ณผ์ ์ธ ์งํ๋ก ์ฌ์ฉ๋ ์ ์์ ๊ฒ์ผ๋ก ๋ณด์๋ค. ๋ค๋ฅธ ๊ฐ์ฒด๋ค๊ณผ ์ ์ ์ ๊ฑฐ๋ฆฌ๊ฐ ๋น๊ต์ ๊ฐ๊น์ด ๋ชจ์์์ ์ข
์ ํ์ง์ด ๋จ์ด์ง๋ ๊ฒฝํฅ์ด ์กด์ฌํ์์ผ๋ ํต๊ณ์ ์ผ๋ก ์ ์ํ์ง๋ ์์๋ค. ๋ณธ ์ฐ๊ตฌ๋ ๋ถ๋น๋๋ฌด์ ๊ณต๊ฐ์ ์ ์ ๊ตฌ์กฐ์ ์ข
์์์ฐ์ ํจ๊ป ๊ณ ๋ คํจ์ผ๋ก์จ ํ์ง์ธ ๋ณด์ ์ ์ ์ฉ๊ฐ๋ฅํ ์ ๋ณด๋ฅผ ์ ๊ณตํ์๋ค. ์ถํ ์ ์ ์ ๋ถ์ฐ ๋ฐ ๊ต๋ฐฐ์์์ ๋ํ ์ฐ๊ตฌ๋ฅผ ํตํด ๋ถ๋น๋๋ฌด์ ์ ์ ๊ตฌ์กฐ์ ๋ํ ์ดํด๋ฅผ ๋์ผ ์ ์์ ๊ฒ์ผ๋ก ๊ธฐ๋๋๋ค.1. Introduction 1
1.1. Study background 1
1.2. Objectives of this research 3
2. Literature Review 4
2.1. Abies nephrolepis 4
2.2. Spatial genetic structure within population 7
2.3. Ex-situ conservation 10
3. Materials and Methods 13
3.1. Study site 13
3.2. Within-population genetic variation 15
3.2.1. Sampling 15
3.2.2. Genetic diversity 16
3.2.3. Spatial genetic structure 18
3.2.4. Sampling simulation study 22
3.3. Seed characteristics and germination 23
3.3.1. Cone sampling and analysis 23
3.3.2. Germination test 24
3.3.3. Statistical analysis 27
4. Results 29
4.1. Within-population genetic variation 29
4.1.1. Selection of microsatellite markers 29
4.1.2. Genetic diversity 30
4.1.3. Spatial genetic structure 30
4.1.4. Sampling simulation study 39
4.2. Seed characteristics and germination 41
4.2.1. Seed characteristics 41
4.2.2. Germination test 45
4.2.3. Statistical analysis 46
5. Discussions 52
5.1. Spatial genetic structure 52
5.2. Seed production 56
5.3. Strategy for ex-situ conservation 59
6. Conclusions 61
References 63
์ด ๋ก 75์
Healthcare spending and utilization of lung cancer patients using 2002-2012 health insurance claims data
Dept. of Public Health/๋ฐ์ฌBackground: Over the past decades, lung cancer has one of the highest fatality rates, and is the leading cause of cancer-related mortality and disease burden not only in South Korea but also worldwide. Studies focused on lung cancer are well documented, however, the factors that are associated with survival probability of lung cancer patients and their healthcare spending and utilization using long periods of large dataset is less researched in this country. The purpose of this study was to investigate how different individual and hospital factors are associated with total, inpatient, outpatient spending and utilizations measured by length of stays and outpatient days among nationwide dead or 5 years follow-up lung cancer patients using 2002-2012 health insurance claims data.Materials and Methods: We used nationwide lung cancer patientsโ health insurance claims during 2002-2012 which accounted for 1,417,380 (673,122 inpatients and 744,258 outpatients). We transposed the dataset into a retrospective cohort design study that the unit of analysis is information of each lung cancer patient. We included patients who newly diagnosed with lung cancer after 2005 and dead or follow-up of 60 months which eventually included patients diagnosed during 2005-2007. Furthermore, this study also excluded patients who had inpatient spending less than KRW 400,000 to minimize bias of real lung cancer patient selection. We then calculated various spending and utilization measures (total, inpatient, outpatient spending, length of stays and outpatient days). Survival time was also measure for each patient that the variable is measured by time from diagnosis to all-cause mortality or end of 60 months follow-up. Finally we obtained total population for analysis of 53,451 lung cancer patients and matched 916 hospitals. Hospital data included characteristics of the hospital, such as
hospital type, teaching status, number of beds, specialists, and nurses. Cox-proportional hazard model was performed to investigate survival probability of lung cancer patients by using individual factors. In order to investigate individual and hospital factors associated with healthcare spending and utilization of lung cancer patients, multi-level linear mixed models that avoid problems created by possible nesting of patient level observations within hospital clusters and overestimation of significance were performed.Results: Our retrospective cohort design study using nationwide claim data of past decade showed that increase in new lung cancer cases during year 2005 to 2007 (16,654 in 2005, 18,149 in 2006, 18,648 in 2007 which are similar to actual number of patients reported by national cancer center), increased spending and utilization (total spending of KRW 22,883,645 to KRW 27,462,222; inpatient LOS of 51.4 days to 58.8 days; outpatient utilization of 25.4 days to 26.1 days for patient diagnosed in 2005 and 2007 respectively), and higher proportion of spending and utilization during very first periods after diagnosis and last periods before death or follow-up ends of lung cancer patients (about 70% over total), no significant improvements of 5 years survival rates by year of diagnosis (20.4%, 19.7%, and 20.3% for diagnosed in 2005, 2006, and 2007 respectively, P=0.462) and higher spending and utilization trend among dead population (5-years survivors: total spending of KRW 24,486,381, inpatient LOS of 39.2 days, outpatient utilization of 40.9 days; Dead population: total spending of KRW 15,936,865~54,945,330, inpatient LOS of 44.4~107.8 days, Outpatient utilization of 9.0~66.0 days). Results of Cox-proportional hazard model showed that indifferent hazard ratio by insurance type (health insurance vs. medical aids, HR=0.99, P=0.489), however, hazard ratio was
increased for male (female HR=0.74, P<0.001), as older age of diagnosis after 40+ for lung cancer (HR range from 2.02 to 6.63, P<0.001). Using the multi-level linear mixed analysis models, we found evidences of differences in the use of healthcare resources among individual and hospital factors that individual with health insurance (2.9% higher in total spending, P<0.001; 23.8% higher in outpatient days, P<0.001), male (5.6% higher in total spending, P<0.001; 8.6% higher in outpatient days, P<0.001), 40-79 age group (28.0% to 61.0% higher in total spending, P<0.001; 24.8% to 34.0% in LOS, P<0.001; 38.9% to 65.8% higher in outpatient days, P<0.001) and hospital type with tertiary/large (27.6%, 12.7% higher in total spending), teaching (35.6% higher in total spending, P<0.001; 13.4% higher in LOS, P=0.001; 21.9% higher in outpatient days, P<0.001) had relatively higher spending and utilization among nationwide 5 year follow-up lung cancer patients. Some population groups showed that higher hazard ratios with higher healthcare spending and utilization.Discussion & Conclusion: This study might suggest that efficient manner of healthcare policy implementation for patientsโ spending and utilization in order to maintain financial viability of national health insurance program that the allocation of limited health-care resources demands an agreed rational allocation principle, and consequently priority setting is considerably importance. In addition, healthcare spending and utilization considered to be targeted to under-served population groups that will ensure efficient locus of healthcare service delivery by accounting for survival probability of different sub-population groups. Results of this study might be useful to health policy makers not only in South Korea but also international readers that need to develop a national cancer management strategy that reduce
differences in the use of healthcare resources and flexible healthcare benefits plan which might helpful to targeted sub population groups.ope
The changing Meaning of Gardens in Jane Austen's Sense and Sensibility(1811) and Mansfield Park(1814)
ํ์๋
ผ๋ฌธ (์์ฌ)-- ์์ธ๋ํ๊ต ํ๊ฒฝ๋ํ์ : ํ๊ฒฝ๋ํ์ ํ๊ฒฝ์กฐ๊ฒฝํ๊ณผ, 2016. 2. ์ฑ์ข
์.๋ณธ ์ฐ๊ตฌ๋ ์ ์์ ์๋ฏธ๋ฅผ 18, 19์ธ๊ธฐ ์๊ตญ์ ์ ์ ์์์ ๋ง๋ผํ ํ๊ฒฝ์ ์ ์์ ํตํ์ฌ ๊ณ ์ฐฐํด ๋ณด๊ณ ์ ํ์๋ค. ํ๊ฒฝ์ ์ ์์ ๋ํ ์ฃผ์ฒด ๊ด์ ์ ํด์์ ๋น๋ ์ ์๊ณผ ๊ฐ๊น์ด ๊ด๊ณ๋ฅผ ์ ์งํ๋ฉฐ ์งํ๋ ์ ์ธ ์ค์คํด์ ์ผ๋ จ์ ์์ค๋ค, ใ์ด์ฑ๊ณผ ๊ฐ์ฑใ, ใ๋งจ์คํ๋ ํํฌใ๋ฅผ ํตํด ๋น๊ตํด๋ณด๊ณ ์ ํ์๋ค. ๋ ์ํ์ ๊ฐ๊ฐ ๊ทธ๋
๊ฐ ์ถ๊ฐํ ์ํ๋ค ์ค ์ฒซ์งธ์ ํ๊ธฐ ์ธ ์ํ ๊ฐ์ด๋ฐ ์ฒซ ๋ฒ์งธ ์ํ์ผ๋ก, ๋ ์์ค์ด ์งํ๋ 18์ธ๊ธฐ ๋ง๊ณผ 19์ธ๊ธฐ ์ด์ ์ ์์ ๋ํ ์ธ์์ ๋ณํ๋ฅผ ๊ฐ๊ฐ ์๊ณต๊ฐ์ ์ผ๋ก ๋๋ณํ๋ค. ๋ณธ ์ฐ๊ตฌ์์๋ ํ์์ ํ๋ก์ ๊ตฌ์ถ๋ ํ๊ฒฝ์ ์ ์์ ํ ์๊ฐ์ ์ผ์์ ๊ธฐ๋ก์ ํตํ์ฌ ์ฌ-ํด์ฒดํจ์ผ๋ก์ ํ ์ฌํ์ ํํ ์์์ผ๋ก์, ์ ์์ด ์ง๋ ์ ์ฌ์ฑ์ ์ธก์ ํด๋ณด๊ณ ๋์๊ฐ ์ ์ ์ ์ฃผ์ฒด์์ ๋ฐ ์ด๋ฐ์ฌ๋ก๊ธฐ(ideology)์ ํฝํฝํ ๊ธด์ฅ๊ฐ์ด ์ ์์ ์์๋ค์ ํตํ์ฌ ๋ค์ํ๊ณ ๋ณตํฉ์ ์ผ๋ก ํํ๋ ์์์ ๋ถ์ํ๊ณ ์ ํ์๋ค.
์ค์คํด์ ์์ค ์ ์ ์์ ์ง, ๊ฐ์ธ-์ฌํ์ ๊ด๊ณ์ ์ฅ, ์์ฐํ ๋ฐ ์์(gazing)์ ์ฅ์๋ก์ ํนํ ์ํ์ ์์ฐ์ ๋ํ ์ญ๋์ ์์๋ฅผ ํตํ ์๋ก์ด ์์์ ๋ฐ๊ฒฌ ๋ฐ ๊ด๊ณ์ฑ์ ํ๋ณต์ ๋๋ชจํ๋ฉฐ, ๊ท๊ฒฐ๋๋ ์ถ์ ๊ณผ์ ์ ์ผ๋ถ์๋ค. ํ๊ฒฝ์์ด๋ผ๋ ์ ํ์ ์ธ ์์ ์๋ ๊ทธ๋
์ ์ฃผ์ธ๊ณต๋ค์ ๋ด๋ฉด์๋ ํจ์ฌ ๋ํ์ ์ด๊ณ ์ํธ ์ฐ๊ด๋ ๊ด๊ณ์ฑ์ด ์ ๋ฆฝ๋์๋ค. ๋ณธ ์ฐ๊ตฌ์ ๋ชฉ์ ์ ์ฌํ-๋ฌธํ์ ๋งฅ๋ฝ ์์์ ์์ด๋ดํฐํฐ(identity)์ ๊ฐ๋ฑ์ด ์ฌํ๋๊ฑฐ๋ ํด์๋๋ ๊ณผ์ ์ ํ๋กํ๊ณ ๋์คํธ(protagonist)์ ์ ์์ ํตํด์ ์ดํดํ๋ ๊ฒ์ด์๋ค. ์ค์คํด์ด ๊ฑฐ์ฃผํ๋ ์ค์ ์ ์๋ค์ด ์์ค ์์ ๋ฌ์ฌ๋ ์๋ฏธ๋ฅผ ์ ์ถํ๊ธฐ ์ํ์ฌ ์ฅ์(place), ํ๋(manner), ๊ฐ์ (emotion), ์ธ๋ฌผ(character), ์์(self)์ ์๋ฏธ์๋ค์ ๊ธฐ์ ๋ก ์ค์ ํ๊ณ ์์ค ์ ์ ์ ๊ณต๊ฐ์์ ์ถํํ ๋จ์ด ๋น๋ํ๊ฐ ์์ฑ๋์๋ค. ์ดํ, ์์ง๋ ์ดํ์ ์๊ด๊ด๊ณ๋ฅผ ๋ฐํ์ผ๋ก ์ด๋ถ๋ฒ์ ๊ตฌ๋๋ก ์๋ฏธ ๋จ์๋ฅผ ์์ฑํ์๋ค. ๋ถ์ ์ฃผ์ ๋ฅผ ์ค์ ํ์ฌ ๋ ํ
์คํธ๋ฅผ ๋น๊ต ๋ถ์ํจ์ผ๋ก์จ ์ ์์ ์๋ฏธ๋ฅผ ๋์ถํ์๋ค. ์ ์์ด ์กฐํ์ ๊ณผ์ ์ผ๋ก์์ ์ ์, ๋ด๋ฉด๊ณผ ํ๋ ๋๋ ์์๋ก์์ ํ๊ฒฝ, ๊ด์์ ํ์์ฃผ์, ์ฐฝ๋ฌธ ํตํ ์ด์ฐจ์ ์กฐ๋ง, ์์ ์์ง ๋ฑ์ผ๋ก ์ ์์ ์ธ์ํ ๋ฐ๋ฉด ํ์์์๋ ๊ถ์์ ๊ฒฐ๊ณผ๋ก์์ ์ ์, ์ ์ฒด์ ๊ทธ๋ฆผ์ผ๋ก์์ ํ๊ฒฝ, ํ๋์ ์ ์ฒด์ฃผ์, ์ง์ ์ ์์ฉ, ์์ ์์ฌ ๋ฑ์ ํตํ์ฌ ์ ์์ ๋ณด์๋ค. ๋์๊ฐ, ๋ ์์ค์์ ๋ณดํธ์ ์ธ ์ ์์ ์๋ฏธ๋ ํ์ ์ ์ ์, ๊ณต๊ฐ์ ์ ์, ์ ์ถฉ์ ์ ์, ์น์ ์ ์ ์, ๋น์ ์ ์ ์์ด์๋ค.
๋ญ๋ง์ฃผ์์ ๊ณ ์ ์ฃผ์ ์ฌ์ด์์ ์ ์ธ ์ค์คํด์ ์์ค ์ ์ ์๋ค์ ์์๋ค์ด ๋ ๊ฐ์ง ๋งฅ๋ฝ์ ๋ํ์ฌ ๋ถ๋ถ์ ์ผ๋ก ๋ณด์ถฉ๋๊ณ ๊ฒฐํ๋๋ ๊ธฐ์์ ์ฅ์, ํ๋, ๊ฐ์ , ์ธ๋ฌผ, ์์์ ์์์ ๋ณํ๋ฅผ ํตํ์ฌ ํ๊ธฐํ๋ค. ํ๊ฒฝ์ ์ ์์ ์์ ํ ์ ํ์ ์ด์ง๋, ํํ์ ์ด์ง๋ ์์ ๋จ์ง ๋งค๊ฐ์ ์ํฌ๋ฌผ๋ก ์ธ์ํ ๊ทธ๋
์๊ฒ ์์ด ์ ์์ ์๋ฏธ์ฑ์ ๋ค์ํ ์ธ๋ฌผ๋ค์ ์ฃผ์ฒด์ ์์์ด ์ ์์ ์ฌํ๋ฌธํ์ ๋งฅ๋ฝ ์์์ ์๊ฐ์ ์ผ๋ก ์ ๊ฐ๊ธฐ ๋ฐํ๋๋ ์๊ฐ๋ค์ด๋ค. ๊ทธ๋ฌํ ์๊ฐ๋ค์ด ๊ทธ๋
์ ์์ฌ ๋จ์๋ก ๊ตฌ์ฑ๋์ด ์ ์์์์ ๋ณด๋ค ์ฑ์๋ ์ผ๋ฐ์ ์ฌ๊ณ ๋ฐ ๋นํ ์์์ผ๋ก ์ง์ฒ๋๋ ๋ฐ๋ฌ ์์์ ๊ทธ๋
๊ฐ ๋น์ ํ๊ฒฝ์ ์ ์์์ ๋ก์ ์ธ์ํ ๊ฒฐ๊ณผ๋ฌผ๋ก ๋ณผ ์ ์๋ค. ๋ณธ ์ฐ๊ตฌ๋ ์ค์คํด์ด ์ค์ ๊ฑฐ์ฃผํ๋ ๋น์ ์ ์๋ค์ ๋ํ ๊ธฐ๋ก์ ๋ํ ์ธ๋ฐํ ์ฐ๊ตฌ๊ฐ ๋ถ์กฑํ๋ฉฐ, ํฅํ ์ด์ฉ์์ ์ ํธ๋ ๋ฐ ์ดํ์ ์์ง์ ๋ํ ์ฐ๊ตฌ๋ก ์ด์ด์ง ์ ์์ ๊ฒ์ผ๋ก ์ฌ๋ฃ๋๋ค.์ 1์ฅ ์๋ก 01
1์ . ์ฐ๊ตฌ์ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์ 01
1. ์ฐ๊ตฌ์ ๋ฐฐ๊ฒฝ 01
2. ์ฐ๊ตฌ์ ๋ชฉ์ 07
2์ . ์ ์ ๊ฐ๋
08
1. ๊ณต๊ฐ์ ํด์์ ๋ฒ์ 08
2. ๋ด์ฉ์ ํด์์ ๋ฒ์ 12
3์ . ์ฐ๊ตฌ์ ๋ฐฉ๋ฒ 14
1. ์๋ฏธ์ 15
2. ์๋ฏธ ๋จ์ 23
3. ๋ถ์์ ์ฃผ์ 29
์ 2์ฅ ์ ์ธ ์ค์คํด์ ์ ์ 42
1์ . ์ฝํฐ์ง (1775-1801, 1809-1817) 42
1. ์ ์์ ๋ฐฐ๊ฒฝ 42
2. ์์ค ์ ๊ตฌํ ๋ฐฉ์ 43
2์ . ๋์ ํ ์กฐ๊ฒฝ (1801-1806, 1806-1809) 49
1. ์ ์์ ๋ฐฐ๊ฒฝ 49
2. ์์ค ์ ๊ตฌํ ๋ฐฉ์ 50
3์ . ํํ ์ ์ (1806-1809) 52
1. ์ ์์ ๋ฐฐ๊ฒฝ 52
2. ์์ค ์ ๊ตฌํ ๋ฐฉ์ 53
4์ . ์ ์ธ ์ค์คํด์ ์์ค ์ ์ ์์ ์ฌ๊ตฌ์ฑ 55
์ 3์ฅ ๋ ์์ค ์ ์ ์์ ์ธ์ ๋น๊ต 58
1์ . ์ฅ์(place)์ ๋ํ ์ธ์๊ณผ ์๋ฏธ 58
1. ์ด์ฑ๊ณผ ๊ฐ์ฑ 58
2. ๋ฉ์คํ๋ ํํฌ 65
2์ . ํ๋(manner)์ ๋ํ ์ธ์๊ณผ ์๋ฏธ 71
1. ์ด์ฑ๊ณผ ๊ฐ์ฑ 71
2. ๋ฉ์คํ๋ ํํฌ 76
3์ . ๊ฐ์ (emotion)์ ๋ํ ์ธ์๊ณผ ์๋ฏธ 78
1. ์ด์ฑ๊ณผ ๊ฐ์ฑ 78
2. ๋ฉ์คํ๋ ํํฌ 80
4์ . ์ธ๋ฌผ(character)์ ๋ํ ์ธ์๊ณผ ์๋ฏธ 82
1. ์ด์ฑ๊ณผ ๊ฐ์ฑ 82
2. ๋ฉ์คํ๋ ํํฌ 84
5์ . ์์(self)์ ๋ํ ์ธ์๊ณผ ์๋ฏธ 84
1. ์ด์ฑ๊ณผ ๊ฐ์ฑ 84
2. ๋ฉ์คํ๋ ํํฌ 86
์ 4์ฅ ์ ์ธ ์ค์คํด ์์ค ์ ์ ์์ ์๋ฏธ ๋ณํ 88
1์ . ์ฅ์(place)์ ๋ํ ์๋ฏธ ๋ณํ 88
2์ . ํ๋(manner)์ ๋ํ ์๋ฏธ ๋ณํ 89
3์ . ๊ฐ์ (emotion)์ ๋ํ ์๋ฏธ ๋ณํ 90
4์ . ์ธ๋ฌผ(character)์ ๋ํ ์๋ฏธ ๋ณํ 91
5์ . ์์(self)์ ๋ํ ์๋ฏธ ๋ณํ 92
์ 5์ฅ ๊ฒฐ๋ก ๋ฐ ๊ณ ์ฐฐ 93
1์ . ์ ์ธ ์ค์คํด์ ๋ ์์ค ๊ฐ ์ ์ ์ธ์์ ๋ถํ 93
2์ . ์ ์ธ ์ค์คํด์ ์์ค ์ ์ ์์ ์๋ฏธ 95
1. ํ์ ์ ์ ์ 95
2. ๊ณต๊ฐ์ ์ ์ 95
3. ์ ์ถฉ์ ์ ์ 96
4. ์น์ ์ ์ ์ 96
5. ๋น์ ์ ์ ์ 97
3์ . ๊ฒฐ๋ก ๋ฐ ๊ณ ์ฐฐ 97
์ฐธ๊ณ ๋ฌธํ 99
๋ถ๋ก 103
Abstract 113Maste
์ผ๋ฐํ๋ 4์ฐจ์ ๋์ ํน์ง์ ์ด์ฉํ ์์ ๊ฐ์ ๋ฌด๊ดํ ํ๋ ์ธ์
ํ์๋
ผ๋ฌธ (๋ฐ์ฌ)-- ์์ธ๋ํ๊ต ๋ํ์ : ์ ๊ธฐยท์ปดํจํฐ๊ณตํ๋ถ, 2014. 8. ์ต์ง์.๋ณธ ๋
ผ๋ฌธ์ ์ผ๋ฐํ๋ 4์ฐจ์ [x,y,z,t] ๋์ ํน์ง์ ์ด์ฉํ์ฌ ์์ ๊ฐ์ ๋ฌด๊ดํ ํ๋ ๋ฐ ํ๋ ๋ฐฉํฅ ์ธ์ ๋ฌธ์ ๋ฅผ ํด๊ฒฐํ๋ ๊ฒ์ ๋ชฉ์ ์ผ๋ก ์ํ๋์๋ค. ๊ธฐ์กด์ ํ๋ ์ธ์ ์ฐ๊ตฌ๋ ์ฃผ๋ก ์นด๋ฉ๋ผ์ ์์น๋ ๊ณ ์ ๋์ด์๊ณ ์ฌ๋๋ค์ ์นด๋ฉ๋ผ๋ฅผ ๋ฐ๋ผ๋ณด๊ณ ์์๋ ์ํฉ์ ๊ฐ์ ํ์๋ค. ๊ทธ๋ฌ๋ ์ค์ ๋น๋์ค๋ ๊ฐ์์นด๋ฉ๋ผ์ ๋ฑ์ฅํ๋ ์ฌ๋๋ค์ ์นด๋ฉ๋ผ๋ฅผ ์์ํ์ง ์๊ณ ์์ฐ์ค๋ฝ๊ฒ ํ๋ํ๊ธฐ ๋๋ฌธ์ ์ ํ๋ ์กฐ๊ฑด, ํ๊ฒฝ์์ ํ๋์ ์ธ์ํ๋ ๊ฒ๊ณผ ๋ฌ๋ฆฌ, ์นด๋ฉ๋ผ์ ์์น์ ์ฌ๋์ ๋ฐฉํฅ์ ๋ฐ๋ผ์ ๋ค์ํ ์์ ๊ฐ์์ ์์์ด ์ดฌ์๋ ์ ์๋ค. ๋ฐ๋ผ์ ์ค์ ์ดํ๋ฆฌ์ผ์ด์
์ ์ ์ฉํ๊ธฐ ์ํด์๋ ๋ฌด์์์ ์์ ๊ฐ์์ ์์์ด ๋ค์ด์์ ๋ ํ๋ ์ธ์์ ํ๋ ๊ฒ์ด ํ์์ ์ด๋ฉฐ, ์ด๋ค ๋ฐฉํฅ์ผ๋ก ํ๋ํ๋ ์ง ์ ์ ์๋ค๋ฉด ๋๊ตฌ์ ์ํธ์์ฉ์ ํ๋ ์ง ์๋๋ฐ ๋์์ ์ค ์ ์๋ค.
๋ณธ ๋
ผ๋ฌธ์์๋ ๋ช ๊ฐ์ ๋ค๋ฅธ ์์ ๊ฐ์์ ์ฐํ ์์์ ์ด์ฉํ์ฌ 3์ฐจ์ [x,y,z] ์
์ฒด๋ฅผ ๋ณต์ํ๊ณ , ์ฐ์๋ 3์ฐจ์ ์
์ฒด์์ 4์ฐจ์ ์๊ณต๊ฐ ํน์ง์ ์ ๊ตฌํ๋ ๋ฐฉ๋ฒ์ ์ ์ํ์ฌ ์์ ๊ฐ์ ๋ฌด๊ดํ ํ๋ ๋ฐ ํ๋ ๋ฐฉํฅ ์ธ์์ ์ํํ์๋ค. 3์ฐจ์ ์
์ฒด ๋ฐ ์ฐ์๋ 3์ฐจ์ ์
์ฒด์์ ๊ตฌํ 4์ฐจ์ ์๊ณต๊ฐ ํน์ง์ ์ ๋ชจ๋ ์์ ๊ฐ์์์ ์ ๋ณด๋ฅผ ๊ฐ๊ณ ์์ผ๋ฏ๋ก, ์ํ๋ ์์ ๊ฐ์ผ๋ก ์ฌ์์ ํ์ฌ ๊ฐ ์์ ๊ฐ์์์ ํน์ง์ ์ป์ ์ ์๋ค. ์ฌ์๋ ์ค๋ฃจ์ฃ๊ณผ 4์ฐจ์ ์๊ณต๊ฐ ํน์ง์ ์ ์์น๋ฅผ ๋ฐํ์ผ๋ก ๊ฐ๊ฐ ์์ง์ด๋ ๋ถ๋ถ๊ณผ ์์ง์ด์ง ์๋ ๋ถ๋ถ์ ๋ํ ์ ๋ณด๋ฅผ ํฌํจํ๋ motion history images (MHIs)์ non motion history images (NMHIs) ๋ฅผ ๋ง๋ค์ด ํ๋ ์ธ์์ ์ํ ํน์ง์ผ๋ก ์ฌ์ฉ์ ํ์๋ค. MHIs๋ง์ผ๋ก๋ ํ๋ ์ ์์ง์ด๋ ๋ถ๋ถ์ด ๋น์ทํ ํจํด์ ๋ณด์ผ ๋ ์ข์ ์ฑ๋ฅ์ ๋ณด์ฅํ ์ ์๊ณ ๋ฐ๋ผ์ ํ๋ ์ ์์ง์ด์ง ์๋ ๋ถ๋ถ์ ๋ํ ์ ๋ณด๋ฅผ ์ค ์ ์๋ NMHIs๋ฅผ ์ ์ํ์๋ค. ํ๋ ์ธ์์ ์ํ ํ์ต ๋จ๊ณ์์ MHIs์ NMHIs๋ ํด๋์ค๋ฅผ ๊ณ ๋ คํ ์ฐจ์ ์ถ์ ์๊ณ ๋ฆฌ์ฆ์ธ class-augmented principal component analysis (CA-PCA)๋ฅผ ํตํด์ ์ฐจ์์ด ์ถ์๋๋ฉฐ, ์ด ๋ ํ๋ ๋ผ๋ฒจ์ ์ด์ฉํ์ฌ ์ฐจ์์ ์ถ์ํ๋ฏ๋ก ๊ฐ ํ๋์ด ์ ๋ถ๋ฆฌ๊ฐ ๋๋๋กํ๋ principal axis๋ฅผ ์ฐพ์ ์ ์๋ค. ์ฐจ์์ด ์ถ์๋ MHIs์ NMHIs๋ support vector data description (SVDD) ๋ฐฉ๋ฒ์ผ๋ก ํ์ต๋๊ณ , support vector domain density description (SVDDD)๋ฅผ ์ด์ฉํ์ฌ ์ธ์๋๋ค. ํ๋ ๋ฐฉํฅ์ ํ์ตํ ๋์๋ ๊ฐ ํ๋์ ๋ํด ๋ฐฉํฅ ๋ผ๋ฒจ์ ์ฌ์ฉํ์ฌ principal axis๋ฅผ ๊ตฌํ๋ฉฐ, ๋ง์ฐฌ๊ฐ์ง๋ก SVDD๋ก ํ์ต์ ํ๊ณ SVDDD๋ฅผ ์ด์ฉํ์ฌ ์ธ์๋๋ค.
์ ์๋ 4์ฐจ์ ์๊ณต๊ฐ ํน์ง์ ์ ์์ ๊ฐ์ ๋ฌด๊ดํ ํ๋ ๋ฐ ํ๋ ๋ฐฉํฅ ์ธ์์ ์ฌ์ฉ๋ ์ ์์ผ๋ฉฐ ์คํ์ ํตํด 4์ฐจ์ ์๊ณต๊ฐ ํน์ง์ ์ด ๊ฐ ํ๋์ ํน์ง์ ์์ถ์ ์ผ๋ก ์ ๋ณด์ฌ์ฃผ๊ณ ์์์ ๋ณด์๋ค. ๋ํ ์ค์ ์ดํ๋ฆฌ์ผ์ด์
์์์ฒ๋ผ ๋ฌด์์์ ์์ ๊ฐ์์ ์์์ด ๋ค์ด์์ ๊ฒฝ์ฐ๋ฅผ ๊ฐ์ ํ๊ธฐ ์ํ์ฌ ํ์ต ๋ฐ์ดํฐ์
๊ณผ ์ ํ ๋ค๋ฅธ ์๋ก์ด ์ธ์ ๋ฐ์ดํฐ์
์ ๊ตฌ์ถํ์๋ค. ๊ธฐ์กด์ ์ฌ๋ฌ ์์ ๊ฐ์์ ์ดฌ์ ๋ IXMAS ํ๋ ์ธ์ ๋ฐ์ดํฐ์
์ ์ด์ฉํ์ฌ ํ์ต์ ํ๊ณ , ํ์ต ๋ฐ์ดํฐ์
๊ณผ ๋ค๋ฅธ ์์ ๊ฐ์์ ์ดฌ์ํ SNU ๋ฐ์ดํฐ์
์์ ์ธ์ ์คํ์ ํ์ฌ ์ ์ํ ์๊ณ ๋ฆฌ์ฆ์ ๊ฒ์ฆํ์๋ค. ์คํ ๊ฒฐ๊ณผ ์ ์ํ ๋ฐฉ๋ฒ์ ํ์ต์ ์ํด ์ดฌ์ํ ์์์ ํฌํจ๋์ง ์๋ ์์ ๊ฐ์์ ํ
์คํธ ์์์ด ๋ค์ด์์ ๊ฒฝ์ฐ์๋ ์ข์ ์ฑ๋ฅ์ ๋ณด์ด๋ ๊ฒ์ ํ์ธํ์๋ค. ๋ํ 5๊ฐ์ ๋ฐฉํฅ์ผ๋ก ์ดฌ์๋ SNU ๋ฐ์ดํฐ์
์ ์ด์ฉํ์ฌ ํ๋ ๋ฐฉํฅ ์ธ์ ์คํ์ ํ์์ผ๋ฉฐ, ์ข์ ๋ฐฉํฅ ์ธ์๋ฅ ์ ๋ณด์ด๋ ๊ฒ์ ํ์ธํ์๋ค. ํ๋ ๋ฐฉํฅ ์ธ์์ ํตํด์ ์์ ๋ด์์ ์ฌ๋ฌ ์ฌ๋์ด ๋ฑ์ฅํ ๋ ๋ค๋ฅธ์ฌ๋๋ค๊ณผ ์ด๋ป๊ฒ ์ํธ ์์ฉ์ ํ๋์ง ์ ๋ณด๋ฅผ ์ ์ ์๊ณ , ์ด๋ ์์์ ํด์ํ๋๋ฐ ๋์์ ์ค ์ ์์ ๊ฒ์ผ๋ก ์๊ฐ๋๋ค.In this thesis, we propose a method to recognize human action and their orientation independently of viewpoints using generalized 4D [x,y,z,t] motion features. The conventional action recognition methods assume that the camera view is fixed and people are standing towards the cameras. However, in real life scenarios, the cameras are installed at various positions for their purposes and the orientation of people are chosen arbitrarily. Therefore, the images can be taken with various views according to the position of camera and the orientation of people. To recognize human action and their orientation under this difficult scenario, we focus on the view invariant action recognition method which can recognize the test videos from any arbitrary view.
For this purpose, we propose a method to recognize human action and their orientation independently of viewpoints by developing 4D space-time interest points (4D-STIPs, [x,y,z,t]) using 3D space (3D-S, [x,y,z]) volumes reconstructed from images of a finite number of different views. Since the 3D-S volumes and the 4D-STIPs are constructed using volumetric information, the features for arbitrary 2D space (2D-S, [x,y]) viewpoint can be generated by projecting the 3D-S volumes and 4D-STIPs on corresponding test image planes. With these projected features, we construct motion history images (MHIs) and non-motion history images (NMHIs) which encode the moving and non-moving parts of an action respectively. Since MHIs cannot guarantee a good performance when moving parts of an object show similar patterns, we propose NMHIs and combine it with MHIs to add the information from stationary parts of an object in the description of the particular action class. To reduce the dimension of MHIs and NMHIs, we apply class-augmented principal component analysis (CA-PCA) which uses class information for dimension reduction. Since we use the action label for reducing the dimension of features, we obtain the principal axis which can separate each action well. After reducing the feature dimension, the final features are trained by support vector data description method (SVDD) and tested by support vector domain density description (SVDDD). As for the recognition of action orientation, the features are reduced the dimension using orientation label. Similarly, the reduced features are trained by SVDD and tested by SVDDD.
The proposed 4D-STIPs can be applied to view invariant recognition of action and their orientation, and we verify that they represent the properties of each action compactly in experiments. To assume arbitrary test view as in real applications, we develop a new testing dataset which is totally different from the training dataset. We verify our algorithm by training action models using the multi-view IXMAS dataset and testing using SNU dataset. Experimental results show that the proposed method is more generalized and outperforms the state-of-the-art methods, especially when training the classifier with the information insufficient about the test views. As for the recognition of action orientation, we experiment with SNU dataset taken from 5 different orientations to verify recognition performance. The recognition of action orientation can be helpful in analyzing the video by providing the information about interactions of people.1 Introduction 1
1.1 Motivations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Contents of the research . . . . . . . . . . . . . . . . . . . . . . . . 7
1.2.1 Generalized 4D motion features . . . . . . . . . . . . . . . . 10
1.2.2 View invariant action recognition . . . . . . . . . . . . . . . 11
1.2.3 Recognition of action orientation . . . . . . . . . . . . . . . 12
2 Generalized 4D Motion Features 14
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.2 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.2.1 Harris corner detector . . . . . . . . . . . . . . . . . . . . . 18
2.2.2 3D space-time interest points . . . . . . . . . . . . . . . . . 21
2.2.3 3D reconstruction . . . . . . . . . . . . . . . . . . . . . . . 23
2.3 Proposed method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.3.1 Modified 3D space-time interest points . . . . . . . . . . . . 27
2.3.2 4D space-time interest points . . . . . . . . . . . . . . . . . 30
2.4 Experimental results . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.5 Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3 View Invariant Action Recognition 40
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.2 Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3.2.1 Motion history images . . . . . . . . . . . . . . . . . . . . . 45
3.2.2 Class-augmented principal component analysis . . . . . . . 47
3.2.3 Support vector data description . . . . . . . . . . . . . . . . 53
3.2.4 Support vector domain density description . . . . . . . . . . 56
3.3 Proposed method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
3.3.1 Silhouettes . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
3.3.2 Space-time interest points . . . . . . . . . . . . . . . . . . . 67
3.3.3 Motion history images and Non-motion history images . . . 69
3.3.4 Training and Testing . . . . . . . . . . . . . . . . . . . . . . 72
3.4 Experimental results . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.5 Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . 86
4 Recognition of Action Orientation 87
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
4.2 Proposed method . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
4.2.1 Training and Testing . . . . . . . . . . . . . . . . . . . . . . 93
4.3 Experimental results . . . . . . . . . . . . . . . . . . . . . . . . . . 95
4.4 Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . 99
5 Conclusions 100
Bibliography 103
Abstract in Korean 113Docto
Serum Calcitonin-Negative Medullary Thyroid Carcinoma: A Case Series of 19 Patients in a Single Center
Introduction: Medullary thyroid carcinoma (MTC) is a rare cancer that accounts for 5% of thyroid cancers. Serum calcitonin is a good biomarker for MTC, which is used for diagnosis, prognosis, and monitoring of recurrence. Calcitonin-negative MTC (CNMTC) is rare but confounds diagnostic and prognostic directions. This study introduces 19 cases of CNMTC in a single center.
Method: From 2002 March to 2020 July, more than 76,500 patients had undergone thyroid surgery due to thyroid cancer at the Severance Hospital, and a total of 320 patients were diagnosed with MTC (0.4%). Serum calcitonin levels were obtained from every patient who was suspected with MTC. These patients had undergone either bilateral total thyroidectomy or unilateral thyroidectomy with central compartment lymph node dissection, and additional modified radical lymph node dissection if lateral lymph node metastasis was positive. Postoperative monitoring and out-patient clinic follow-up were performed with obtaining the serum calcitonin levels.
Result: Nineteen patients tested negative for calcitonin preoperatively (6%). The mean preoperative calcitonin level was 5.1pg/mL if undetectable level is regarded as 0pg/mL. Only two patients were males, and the female bias was significant (p = 0.017). No one except two patients with modified radical neck dissection showed central compartment lymph node metastasis. Every patient's postoperative calcitonin level remained low. The median follow-up period was 71 months. There was no recurrence and only one fatality, and the overall survival rate was 95%.
Conclusion: Since incidence of CNMTC is not negligible, MTC should not be ruled out in the diagnostic phase even if serum calcitonin is negative in preoperative examination. We presented 19 cases of CNMTC whose prognosis in general were favorable. Markers of serum and immunohistochemical samples other than calcitonin should be actively examined.ope
Effect of Nutritional Intervention by the Nutrition Support Team on Postnatal Growth in Preterm Infants
"Purpose: Nutritional intervention by an interdisciplinary nutrition support team (NST) can potentially improve postnatal growth
outcomes in preterm infants. This study aimed to measure the growth impact of a nutritional intervention package performed
by an NST in a quality improvement effort in a neonatal intensive care unit (NICU).
Methods: Fifty-two infants born below 2,000 g and admitted to NICU participated in the Quality Improvement (QI) program
between March 2016 and February 2017. The nutritional intervention was applied according to newly established nutritional guidelines
on parenteral and enteral nutrition, and an NST performed a weekly nutritional assessment. The Z-scores of weight, height,
and head circumference were calculated according to the gestational age and sex. The clinical impact on postnatal growth was
compared between the QI and pre-QI groups. The pre-QI group included 69 infants admitted in the same NICU between 2014
and 2015.
Results: The time to the initiation of enteral nutrition decreased significantly (P๏ผ0.001). Changes in weight (P=0.027), head
circumference (P=0.003), Z-scores between birth, and 40 weeks postconceptional age (PCA) were significantly larger in the QI
than the pre-QI group. The percentage of infants weighing below the 10th percentile at one month after birth and at 40 weeks
PCA was higher in the pre-QI than the QI group.
Conclusion: The implementation of evidence-based best practices for preterm nutrition resulted in significant improvements in
the growth outcomes in preterm infants."22othe
Identification of a radiosensitivity signature using integrative metaanalysis of published microarray data for NCI-60 cancer cells.
BACKGROUND: In the postgenome era, a prediction of response to treatment could lead to better dose selection for patients in radiotherapy. To identify a radiosensitive gene signature and elucidate related signaling pathways, four different microarray experiments were reanalyzed before radiotherapy.
RESULTS: Radiosensitivity profiling data using clonogenic assay and gene expression profiling data from four published microarray platforms applied to NCI-60 cancer cell panel were used. The survival fraction at 2โGy (SF2, range from 0 to 1) was calculated as a measure of radiosensitivity and a linear regression model was applied to identify genes or a gene set with a correlation between expression and radiosensitivity (SF2). Radiosensitivity signature genes were identified using significant analysis of microarrays (SAM) and gene set analysis was performed using a global test using linear regression model. Using the radiation-related signaling pathway and identified genes, a genetic network was generated. According to SAM, 31 genes were identified as common to all the microarray platforms and therefore a common radiosensitivity signature. In gene set analysis, functions in the cell cycle, DNA replication, and cell junction, including adherence and gap junctions were related to radiosensitivity. The integrin, VEGF, MAPK, p53, JAK-STAT and Wnt signaling pathways were overrepresented in radiosensitivity. Significant genes including ACTN1, CCND1, HCLS1, ITGB5, PFN2, PTPRC, RAB13, and WAS, which are adhesion-related molecules that were identified by both SAM and gene set analysis, and showed interaction in the genetic network with the integrin signaling pathway.
CONCLUSIONS: Integration of four different microarray experiments and gene selection using gene set analysis discovered possible target genes and pathways relevant to radiosensitivity. Our results suggested that the identified genes are candidates for radiosensitivity biomarkers and that integrin signaling via adhesion molecules could be a target for radiosensitization.ope
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ํ์๋
ผ๋ฌธ(์์ฌ)--์์ธ๋ํ๊ต ๋ํ์ :์๋ช
๊ณผํ๋ถ,2004.Maste
Weavable asymmetric carbon nanotube yarn supercapacitor for electronic textiles
Asymmetric supercapacitors are receiving much research interests due to their wide operating potential window and high energy density. In this study, we report the fabrication of asymmetrically configured yarn based supercapacitor by using liquid-state biscrolling technology. High loading amounts of reduced graphene oxide anode guest (90.1 wt%) and MnO2 cathode guest (70 wt%) materials were successfully embedded into carbon nanotube yarn host electrodes. The resulting asymmetric yarn supercapacitor coated by gel based organic electrolyte (PVDF-HFP-TEABF(4)) exhibited wider potential window (up to 3.5 V) and resulting high energy density (43 W h cm(-2)). Moreover, the yarn electrodes were mechanically strong enough to be woven into commercial textiles. The textile supercapacitor exhibited stable electrochemical energy storage performances during dynamically applied deformations.This work was supported by the Creative Research Initiative Center for Self-powered Actuation in Korea, Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1A6A3A04004987), and DGIST R&amp;D Program of Ministry of Science, ICT and Future Planning of Korea (17-NT-02). Support at the University of Texas at Dallas was provided by Air Force Office of Scientific Research grants AOARD-FA2386-13-1-4119 and FA9550-15-1-0089 and Robert A. Welch Foundation grant AT-0029. Additional support was from the Australian Research Council (DP110101073)
Harvesting electrical energy from torsional thermal actuation driven by natural convection
The development of practical, cost-effective systems for the conversion of low-grade waste heat to electrical energy is an important area of renewable energy research. We here demonstrate a thermal energy harvester that is driven by the small temperature fluctuations provided by natural convection. This harvester uses coiled yarn artificial muscles, comprising well-aligned shape memory polyurethane (SMPU) microfibers, to convert thermal energy to torsional mechanical energy, which is then electromagnetically converted to electrical energy. Temperature fluctuations in a yarn muscle, having a maximum hot-to-cold temperature difference of about 13 degrees C, were used to spin a magnetic rotor to a peak torsional rotation speed of 3,000 rpm. The electromagnetic energy generator converted the torsional energy to electrical energy, thereby producing an oscillating output voltage of up to 0.81 V and peak power of 4 W/kg, based on SMPU mass.This work was supported by the Creative Research Initiative Center for Self-Powered Actuation of the National Research Foundation and the Ministry of Science, ICT &amp; Future Planning (MSIP) in Korea. Support in Australia was from Centre of Excellence funding from the Australian Research Council. Support in the USA was from Air Force Grant AOARD-FA2386-13-4119, Air Force Office of Scientific Research grant FA9550-15-1-0089, and Robert A. Welch Foundation grant AT-0029
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