• KOREAN JOURNAL OF CROP SCIENCE
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• v.63 no.3
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• pp.175-185
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• 2018

The aim of this study was to evaluate the variation of growth and quality characteristics in colored rice from 178 accessions and to develop useful, basic rice breeding data by classifying these germplasm characteristics via principal component (PC) analysis. The coefficient of variation of the 178colored rice accessions were the highest for panicle length (PL) and protein contents, followed by length-width ratio (LWR), 1000-grain weight (TGW), culm length (CL), and amylose contents, whereas the lowest was for the number of panicles per hill (NP), which is a yield component. The results from the PC analysis exhibited eigenvalues and contributions respective to each PC as follows: PC1, 2.06 and 29.49%; PC2, 1.31 and 18.75%; PC3, 1.21 and 17.36%; PC4, 1.01 and 14.38%. The eigenvalues of four PCs were over 1.0, and their cumulative contributions were 79.98%, which completes the necessary condition for evaluation of the 178 colored rice accessions. Cluster analysis showed cluster I as the largest, which included 79 accessions, while clusters II, III, IV, V, VI, and VII comprised 46, 19, 13, 4, 8, and 9 accessions, respectively. Moreover, dark brown accessions were dispersed in clusters I and II, and many resources of purple seed coat color were found in clusters V, VI, and VII. Particularly, cluster V had resources of only black and purple seed coat colors. Resources of cluster VII were found to have a relatively small average CL, PL, and LWR; notably, cluster V had the smallest average TGW, and cluster IV the lowest NP but the highest TGW. Finally, considering the yield potential, growth characteristics, heading stage, and color during breeding of colored rice, we obtained the following conclusions: cluster VII is suitable for breeding of colored rice; cross breeding among clusters I, II, and VII has a high yield potential; and it is possible to produce a superior color by cross breeding plants from cluster V and VI.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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• pp.945-950
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• 2014

Purpose: To explore the value of systemic inflammatory markers as independent prognostic factors and the extent these markers improve prognostic classification for patients with inoperable advanced or metastatic gastric cancer (GC) receiving palliative chemotherapy. Methods: We studied the prognostic value of systemic inflammatory factors such as circulating white blood cell count and its components as well as that combined to form inflammation-based prognostic scores (Glasgow Prognostic Score (GPS), Neutrophil-Lymphocyte Ratio (NLR), Platelet Lymphocyte Ratio (PLR), Prognostic Index (PI) and Prognostic Nutritional Index (PNI)) in 384 patients with inoperable advanced or metastatic gastric cancer (GC) receiving first-line chemotherapy. Univariate and multivariate analyses were performed to examine the impact of inflammatory markers on overall survival (OS). Results: Univariate analysis revealed that an elevated white blood cell, neutrophil and/or platelet count, a decreased lymphocyte count, a low serum albumin concentration, and high CRP concentration, as well as elevated NLR/PLR, GPS, PI, PNI were significant predictors of shorter OS. Multivariate analysis demonstrated that only elevated neutrophil count (HR 3.696, p=0.003) and higher GPS (HR 1.621, p=0.01) were independent predictors of poor OS. Conclusion: This study demonstrated elevated pretreatment neutrophil count and high GPS to be independent predictors of shorter OS in inoperable advanced or metastatic GC patients treated with first-line chemotherapy. Upon validation of these data in independent studies, stratification of patients using these markers in future clinical trials is recommended.

• Journal of Food Hygiene and Safety
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• v.35 no.5
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• pp.430-437
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• 2020

This is an approach study on the sensory properties (taste and odor) of 15 types of Korean conventional soups and stews using electronic nose and tongue. The relative sensor intensity for the taste components of the samples using electronic tongue was demonstrated. By SRS (sourness) sensor, sogogi-baechuguk (beef and cabbage soup) had the highest rate of 9.0. The STS (saltiness) sensor showed the highest score of 8.2 for ojingeoguk (squid soup). For the UMS (umami) sensor, which identifies savoriness, the sogogi-baechuguk was the highest at 10.1. The SWS (sweetness) sensors showed relatively little difference, with sigeumchi-doenjangguk (spinach and bean paste soup) at the highest of 7.3. According to the BRS sensor, which tests for bitterness, the siraegi-doenjangguk (dried radish green and bean paste soup) was the highest at 7.8. By principal component analysis (PCA), we observed variances of 56.21% in principal component 1 (PC1) and 25.23% in PC2. For each flavor component, we observed -0.95 and -0.20 for factor loading of PC1 and PC2 for SRS sensors, 0.96 and 0.14 for STS sensors, and -0.94 and 0.22 for PC1 and PC2 for UMS sensors, and PC1 and 0.22 for PC1 and PC2 loading for SWS sensors. The similarity between the samples identified by clustering analysis was largely identified by 4 clusters. A total of 25 kinds of volatile compounds in 15 samples were identified, and the ones showing the highest relative content in all samples were identified as ethanol and 2-methylthiophhene. The main ingredient analysis confirmed variances of 28.54% in PC1 and 20.80% in PC2 as a result of the pattern for volatile compounds in 15 samples. In the cluster analysis, it was found to be largely classified into 3 clusters. The data in this study can be used for a sensory property database of conventional Korean soups and stews using electronic sensors.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.6
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• pp.2979-2982
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• 2016

Background: High dose ionizing radiation can induce ovarian cancer, but the effect of low dose radiation on the development of ovarian cancer has not been extensively studied. We evaluated the effect of low dose radiation and total background radiation, and the radiation delivered to the ovaries during the treatment of rectosigmoid cancer and breast cancer on ovarian cancer incidence. Materials and Methods: Background radiation measurements are from Assessment of Variations in Radiation Exposure in the United States, 2011. Ovarian cancer incidence data are from the Centers for Disease Control and Prevention. Standardized incidence ratios (SIR) of ovarian cancer following breast cancer and rectosigmoid cancer are from Surveillance, Epidemiology, and End Results (SEER) data. Obesity data by US state are from the Centers for Disease Control and Prevention. Mean ages of US state populations are from the United States Census Bureau. Results: We calculated standardized incidence ratios (SIR) from Surveillance, Epidemiology, and End Results (SEER) data, which reveal that in 194,042 cases of breast cancer treated with beam radiation, there were 796 cases of ovarian cancer by 120+ months of treatment (0.41%); in 283, 875 cases of breast cancer not treated with radiation, there were 1,531 cases of ovarian cancer by 120+ months (0.54%). The difference in ovarian cancer incidence in the two groups was significant (p < 0.001, two tailed Fisher exact test). The small dose of scattered ovarian radiation (about 3.09 cGy) from beam radiation to the breast appears to have reduced the risk of ovarian cancer by 24%. In 13,099 cases of rectal or rectosigmoid junction cancer treated with beam radiation in the SEER data, there were 20 cases of ovarian cancer by 120+ months of treatment (0.15%). In 33,305 cases of rectal or rectosigmoid junction cancer not treated with radiation, there were 91 cases of ovarian cancer by 120+ months (0.27%). The difference in ovarian cancer incidence in the two groups was significant (p = 0.017, two tailed Fisher exact test). In other words, the beam radiation to rectum and rectosigmoid that also reached the ovaries reduced the risk of ovarian cancer by 44%. In addition, there was a significant inverse relationship between ovarian cancer in white women and radon background radiation (r = - 0.465. p = 0.002) and total background radiation (r = -0.456, p = 0.002). Because increasing age and obesity are risk factors for ovarian cancer, multivariate linear regression was performed. The inverse relationship between ovarian cancer incidence and radon background was significant (${\beta}=-0.463$, p = 0.002) but unrelated to age (${\beta}=-0.080$, p = 0.570) or obesity (${\beta}=-0.180$, p = 0.208). Conclusions: The reduction of ovarian cancer risk following low dose radiation may be the result of radiation hormesis. Hormesis is a favorable biological response to low toxin exposure. A pollutant or toxin demonstrating hormesis has the opposite effect in small doses as in large doses. In the case of radiation, large doses are carcinogenic. However, lower overall cancer rates are found in U.S. states with high impact radiation. Moreover, there is reduced lung cancer incidence in high radiation background US states where nuclear weapons testing was done. Women at increased risk of ovarian cancer have two choices. They may be closely followed (surveillance) or undergo immediate prophylactic bilateral salpingo-oophorectomy. However, the efficacy of surveillance is questionable. Bilateral salpingo-oophorectomy is considered preferable, although it carries the risk of surgical complications. The data analysis above suggests that low-dose pelvic irradiation might be a good third choice to reduce ovarian cancer risk. Further studies would be worthwhile to establish the lowest optimum radiation dose.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.3
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• pp.1-15
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• 2016

This study has analyzed predication capabilities leveraging multi-variate model, logistic regression model, and artificial neural network model based on financial information of medium-small sized companies list in KOSDAQ. 83 delisted companies from 2009 to 2012 and 83 normal companies, i.e. 166 firms in total were sampled for the analysis. Modelling with training data was mobilized for 100 companies inlcuding 50 delisted ones and 50 normal ones at random out of the 166 companies. The rest of samples, 66 companies, were used to verify accuracies of the models. Each model was designed by carrying out T-test with 79 financial ratios for the last 5 years and identifying 9 significant variables. T-test has shown that financial profitability variables were major variables to predict a financial risk at an early stage, and financial stability variables and financial cashflow variables were identified as additional significant variables at a later stage of insolvency. When predication capabilities of the models were compared, for training data, a logistic regression model exhibited the highest accuracy while for test data, the artificial neural networks model provided the most accurate results. There are differences between the previous researches and this study as follows. Firstly, this study considered a time-series aspect in light of the fact that failure proceeds gradually. Secondly, while previous studies constructed a multivariate discriminant model ignoring normality, this study has reviewed the regularity of the independent variables, and performed comparisons with the other models. Policy implications of this study is that the reliability for the disclosure documents is important because the simptoms of firm's fail woule be shown on financial statements according to this paper. Therefore institutional arragements for restraing moral laxity from accounting firms or its workers should be strengthened.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1031-1031
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• 2001

The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.

• The Journal of Korean Academic Society of Nursing Education
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• v.3
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• pp.78-98
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• 1997

Health education, as the most fundamental concept for national health promotion, alms for developing the self-care ability of the general public. High school days are regarded as the period when most important physical, mental and social developments occur, and most health-related behaviors are formed. School health education is one of the major learning resources influencing health potential in the home and community as well as for the individual student. High school health education in Korea has a fundamental systemic flaw in that health-related subjects are divided and taught under various subjects areas at school. In order to achieve the goal of school health education, it is essential to make a systematic assessment of the learner's concerns connected with his health and life, and the factors affecting them. So far, most of the research projects that had been carried out for improving high school health education were limited in their concerns to a particular aspect of health. Even though some had been done in view of comprehensive school health education, they failed to Include a health assessment of the learner. Therefore, in this study the high school students' concerns related to health and life were investigated in the first place on the basis of the PRECEDE model, developed by Green and others for the purpose of a comprehensive diagnostic research on high school health education. This study was done in two steps : one was the basic study for developing research instrument and the other was the main one. The former was conducted at five high schools in Seoul and Cheongju for 2 months-beginning in March, 1996. The students were asked to respond to questions related to their health and lives in unstructured open-ended question forms. On the basis of analysis of the basic study, the diagnostic instruments for the quality of life, health problems, health behavior and educational factors were constructed to be used for the collection of data for main study. An expert panel and the pilot study were used to improve content validity and reliability of the instruments. The reliability of the instruments was measured at between .7697 and .9611 by the Cronbach $\alpha$. The data for this study were collected from the sample consisted of the junior and senior classes of twenty general and vocational high schools in Seoul and Cheongju for two months period beginning in July, 1996. In analyzing the data, both t-test and $X^2$-test were done by using SAS-$PC^+$ Program to compare data between the sexes of the high school students and the types of high school. A canonical correlation analysis was carried out to determine the relationships among the diagnostic variables, and a multivariate multiple regression analysis was conducted by using LISREL 8.03 to ascertain the influences of variables on the high school students' health and quality of life. The results were as follows : 1) The findings of the hypothesis tests (1) The canonical correlation between the educational diagnosis variables and behavioral, epidemiological, social diagnosis variables was .7221, which was significant at the level of p<.001. (2) The canonical correlation between the educational diagnosis variables and the behavior variables was .6851, which also was significant (p<.001). (3) The canonical correlation between the behavioral diagnosis variables and the epidemiological variables was 4295, which was significant (p<.001). (4) The canonical correlation between the epidemiological diagnosis variables and the social variables was .6005, which was also significant (p<.001). Therefore, the relationship between each diagnosis variable suggested by the PRECEDE model had been experimentally proven to be valid, supporting the conceptual framework of the study as appropriate for assessing the multi-dimensional factors affecting high school students' health and quality of life. Health behavior self-efficacy, the level of parents' interest and knowledge of health, and the level of the perception of school health education, all of which are the educational diagnostic variables, are the most influential variables in students' health and quality of life. In particular, health behavior self-efficacy, a causative factor, was one of the main influential variables in their health and quality of life. Other diagnostic variables suggested in the steps of the PRECEDE model were found to have reciprocal relations rather than a unidirectional causative relationship. The significance of this research is that it has diagnosed the needs of high school health education by the learner-centered assessment of variety of factors related to the health and the life of the students. This research findings suggest an integrated system of school health education to be contrived to enhance the effectiveness of the education by strengthening the influential factors such as self-efficacy to improve the health and quality of the lives of high school students.

• KDI Journal of Economic Policy
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• v.30 no.2
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• pp.99-128
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• 2008

Nearly all Koreans are insured through National Health Insurance(NHI). While NHI coverage is nearly universal, it is not complete. Coverage is largely limited to minimal level of hospital and physician expenses, and copayments are required in each case. As a result, Korea's public insurance system covers roughly 50% of overall individual health expenditures, and the remaining 50% consists of copayments for basic services, spending on services that are either not covered or poorly covered by the public system. In response to these gaps in the public system, 64% of the Korean population has supplemental private health insurance. Expansion of private health insurance raises negative externality issue. Like public financing schemes in other countries, the Korean system imposes cost-sharing on patients as a strategy for controlling utilization. Because most insurance policies reimburse patients for their out-of-pocket payments, supplemental insurance is likely to negate the impact of the policy, raising both total and public sector health spending. So far, most empirical analysis of supplemental health insurance to date has focused on the US Medigap programme. It is found that those with supplements apparently consume more health care. Two reasons for higher health care consumption by those with supplements suggest themselves. One is the moral hazard effect: by eliminating copayments and deductibles, supplements reduce the marginal price of care and induce additional consumption. The other explanation is that supplements are purchased by those who anticipate high health expenditures - adverse effect. The main issue addressed has been the separation of the moral hazard effect from the adverse selection one. The general conclusion is that the evidence on adverse selection based on observable variables is mixed. This article investigates the extent to which private supplementary insurance affect use of health care services by public health insurance enrollees, using Korean administrative data and private supplements related data collected through all relevant private insurance companies. I applied a multivariate two-part model to analyze the effects of various types of supplements on the likelihood and level of public health insurance spending and estimated marginal effects of supplements. Separate models were estimated for inpatients and outpatients in public insurance spending. The first part of the model estimated the likelihood of positive spending using probit regression, and the second part estimated the log of spending for those with positive spending. Use of a detailed information of individuals' public health insurance from administration data and of private insurance status from insurance companies made it possible to control for health status, the types of supplemental insurance owned by theses individuals, and other factors that explain spending variations across supplemental insurance categories in isolating the effects of supplemental insurance. Data from 2004 to 2006 were used, and this study found that private insurance increased the probability of a physician visit by less than 1 percent and a hospital admission by about 1 percent. However, supplemental insurance was not found to be associated with a bigger health care service utilization. Two-part models of health care utilization and expenditures showed that those without supplemental insurance had higher inpatient and outpatient expenditures than those with supplements, even after controlling for observable differences.

• Economic and Environmental Geology
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• v.55 no.6
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• pp.737-760
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• 2022

For the geological disposal of high-level radioactive wastes (HLW), an understanding of deep subsurface environment is essential through geological, hydrogeological, geochemical, and geotechnical investigations. Although South Korea plans the geological disposal of HLW, only a few studies have been conducted for characterizing the geochemistry of deep subsurface environment. To guide the hydrogeochemical research for selecting suitable repository sites, this study overviewed the status and trends in hydrogeochemical characterization of deep groundwater for the deep geological disposal of HLW in developed countries. As a result of examining the selection process of geological disposal sites in 8 countries including USA, Canada, Finland, Sweden, France, Japan, Germany, and Switzerland, the following geochemical parameters were needed for the geochemical characterization of deep subsurface environment: major and minor elements and isotopes (e.g., ³⁴S and ¹⁸O of SO₄^2-, ¹³C and ¹⁴C of DIC, ²H and ¹⁸O of water) of both groundwater and pore water (in aquitard), fracture-filling minerals, organic materials, colloids, and oxidation-reduction indicators (e.g., Eh, Fe²⁺/Fe³⁺, H₂S/SO₄^2-, NH₄⁺/NO₃^-). A suitable repository was selected based on the integrated interpretation of these geochemical data from deep subsurface. In South Korea, hydrochemical types and evolutionary patterns of deep groundwater were identified using artificial neural networks (e.g., Self-Organizing Map), and the impact of shallow groundwater mixing was evaluated based on multivariate statistics (e.g., M3 modeling). The relationship between fracture-filling minerals and groundwater chemistry also has been investigated through a reaction-path modeling. However, these previous studies in South Korea had been conducted without some important geochemical data including isotopes, oxidationreduction indicators and DOC, mainly due to the lack of available data. Therefore, a detailed geochemical investigation is required over the country to collect these hydrochemical data to select a geological disposal site based on scientific evidence.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4D
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• pp.313-322
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• 2012

This study analyzes taxi driver's risk-taking propensity with respect to risk-taking behaviour and traffic locus of control. In order to explore the traffic risk-taking, we present a predictive model by structural analysis of driver's risk-taking propensity. By applying this model to survey data from taxi drivers, we can observe that driver's risk-taking propensity has a significant impact on the traffic violation intention, and the higher perception of law and the lower lack of law-abiding drivers have, the more they tend to violate. Second, we test using multivariate analysis if the level of risk-taking propensity differs by the locus of control( external or internal). Drivers of external control shows higher risk-taking level compared to those of internal control so that the risk-taking propensity shows difference according to the locus of control for the responsibility of traffic accidents. The structural equation model of our study yielded ${\chi}^2$ = 279.7, ${\chi}^2$/df = 1.55, RMSEA = 0.44, GFI = 0.911, TLI = 0.916, CFI = 0.929.