• Clinical and Experimental Reproductive Medicine
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• v.48 no.2
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• pp.111-123
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• 2021

Objective: Using domestic cats as a biomedical research model for fertility preservation, the present study aimed to characterize the influences of ovarian tissue encapsulation in biodegradable hydrogel matrix (fibrinogen/thrombin) on resilience to cryopreservation, and static versus non-static culture systems following ovarian tissue encapsulation and cryopreservation on follicle quality. Methods: In experiment I, ovarian tissues (n=21 animals; 567 ovarian fragments) were assigned to controls or hydrogel encapsulation with 5 or 10 mg/mL fibrinogen (5 or 10 FG). Following cryopreservation (slow freezing or vitrification), follicle viability, morphology, density, and key protein phosphorylation were assessed. In experiment II (based on the findings from experiment I), ovarian tissues (n=10 animals; 270 ovarian fragments) were encapsulated with 10 FG, cryopreserved, and in vitro cultured under static or non-static systems for 7 days followed by similar follicle quality assessments. Results: In experiment I, the combination of 10 FG encapsulation/slow freezing led to greater post-thawed follicle quality than in the control group, as shown by follicle viability (66.9%±2.2% vs. 61.5%±3.1%), normal follicle morphology (62.2% ±2.1% vs. 55.2%±3.5%), and the relative band intensity of vascular endothelial growth factor protein phosphorylation (0.58±0.06 vs. 0.42±0.09). Experiment II demonstrated that hydrogel encapsulation promoted follicle survival and maintenance of follicle development regardless of the culture system when compared to fresh controls. Conclusion: These results provide a better understanding of the role of hydrogel encapsulation and culture systems in ovarian tissue cryopreservation and follicle quality outcomes using an animal model, paving the way for optimized approaches to human fertility preservation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.454-460
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• 2021

This study focused on the sex culture and the sexual rights of women, examining the gender-role stereotype that is related to the protection of the sexual rights of female college students and identifying the influence of self- esteem. The research was conducted on gender-role stereotypes, sexual assertiveness, and self-esteem among female university students attending four-year universities in Seoul and Gyeonggi. Four hundred eighty-two copies were used for analysis. The Pearson's correlation coefficient was used to identify the correlation between the variables. Multiple regression analysis was conducted to identify the mediated effects of self-esteem in the effects of gender-role stereotypes on sexual assertiveness. The Sobel test was conducted to confirm that the effects were statistically significant. The results of this study were as follows. First, the gender-role stereotype had negative correlations with self-esteem and sexual assertiveness. Self-esteem had positive correlations with sexual assertiveness. Second, self-esteem was found to be a partial mediating factor when the gender-role stereotype had a statistically significant effect on sexual assertiveness. Therefore, a coping strategy under the influence of the gender-role stereotype is necessary for improving the sexual assertiveness skill of female students. This study also suggests the need for sex role-related education programs or counseling on self-esteem.

• Journal of Korea Water Resources Association
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• v.54 no.2
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• pp.121-133
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• 2021

Suspended Solids (SS) generated in rivers are mainly introduced from non-point pollutants or appear naturally in the water body, and are an important water quality factor that may cause long-term water pollution by being deposited. However, the conventional method of measuring the concentration of suspended solids is labor-intensive, and it is difficult to obtain a vast amount of data via point measurement. Therefore, in this study, a model for measuring the concentration of suspended solids based on remote sensing in the Nakdong River was developed using Sentinel-2 data that provides high-resolution multi-spectral satellite images. The proposed model considers the spectral bands and band ratios of various wavelength bands using a machine learning model, Support Vector Regression (SVR), to overcome the limitation of the existing remote sensing-based regression equations. The optimal combination of variables was derived using the Recursive Feature Elimination (RFE) and weight coefficients for each variable of SVR. The results show that the 705nm band belonging to the red-edge wavelength band was estimated as the most important spectral band, and the proposed SVR model produced the most accurate measurement compared with the previous regression equations. By using the RFE, the SVR model developed in this study reduces the variable dependence compared to the existing regression equations based on the single spectral band or band ratio and provides more accurate prediction of spatial distribution of suspended solids concentration.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.845-856
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• 2020

This study proposes a bridge evaluation system for indivisible permit vehicles such as hydraulic cranes. The permit loads for the bridge evaluation are divided into three categories: routine permit loads, special permit 1 loads, and special permit 2 loads. Routine permit and special permit 1 vehicles are allowed to cross a bridge with normal traffic. For these two permits, the standard lane model in the Korean Highway Bridge Design Code was adopted to consider normal traffic in the same lane. Special permit 2 vehicles are assumed to cross a bridge without other traffic. Structural analyses of two prestressed-beam bridges and two steel box girder bridges were conducted for the proposed permit loads. The rating factors of the four bridges for all permit loads were calculated as sufficiently large values for the moment and shear force so that crossing the bridges can be permitted. A reliability assessment of the bridges was performed to identify the reliability levels for the permit vehicles. It was confirmed that the reliability level of the minimum required strength obtained by the load-resistance factors yields the target reliability index of the design code for the permit vehicles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.169-180
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• 2021

This study was undertaken to determine the degree of quality of life, and factors influencing osteoarthritis in hypertensive elderly 65 years or older patients, using data from the 7th National Health and Nutrition Survey 2018. Totally, 843 subjects were included from a national sample. The SPSS WIN 26.0 program was used to analyze complex samples by applying the Rao-Scott chi-square test, t-test, and multiple regression analysis. Results indicate that quality of life of the hypertensive group with osteoarthritis is significantly lower than the group with only hypertension (t=5.07, p<0.001). Factors affecting the decrease in quality of life of the hypertensive group were age, subjective health status, and activity restrictions, and the explanatory power was 46.1% (F=12.33, p<0.001). In the hypertensive group with osteoarthritis, the effective factors included gender, cohabitation status, economic activity, subjective health status, activity restriction, body mass index, sleep time, stress perception, and depression, and the explanatory power was 44.6% (F=99.82, p<0.001). Subsequent studies showed that in order to improve the quality of life of hypertensive seniors, intervention programs are required to actively accommodate health conditions and minimize activity restrictions. In addition, for the elderly with osteoarthritis and hypertension, it is necessary to include exercise and nutrition education for body mass index management, and the development and intervention of multidisciplinary participation programs to strengthen mental health.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.671-678
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• 2021

In a previous study, technology protection levels were set on a qualitative basis. That study lacked quantitative standards, so here, we conduct a study to complement the previous study and to present an objective standard. This paper provides a method of setting a technical protection level that applies statistical analysis. To set the technology protection level, statistical analysis of six technical survey items is performed first. Second, the technical survey items are analyzed by AHP to quantify the opinions of experts in order to derive weights for each technical survey item. Finally, by using the normal distribution scatter map and median calculation method, the technology protection level is selected in three stages using the final detailed factor technology score reflecting the weight. The technology protection level methodology developed through this study is the first methodology with objectivity that can evaluate defense technology by level. If this methodology is applied in practice, it is believed that it will provide a scientific and quantitative technology value judgment criterion when setting the technology protection level in the future.

• Journal of Korean Society of Forest Science
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• v.110 no.1
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• pp.64-71
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• 2021

Recently, climate change has gradually accelerated the occurrence of landslides. Among the various effects caused by landslides,debris flow is recognized as particularly threatening because of its high speed and propagating distance. In this study, the impacts of various factors were analyzed using quantification theory(I) for the prediction of debris flow hazard soil volume in Seoraksan National Park, Korea. According to the range using the stepwise regression analysis, the order of impact factors was as follows: vertical slope (0.9676), cross slope (0.6876), altitude (0.2356), slope gradient (0.1590), and aspect (0.1364). The extent of the normalized score using the five-factor categories was 0 to 2.1864, with the median score being 1.0932. The prediction criteria for debris flow occurrence based on the normalized score were divided into four grades: class I, >1.6399; class II, 1.0932-1.6398; class III, 0.5466-1.0931; and class IV, <0.5465. Predictions of debris flow occurrence appeared to be relatively accurate (86.3%) for classes I and II. Therefore, the prediction criteria for debris flow will be useful for judging the dangerousness of slopes.

• Journal of The Korean Society of Grassland and Forage Science
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• v.40 no.4
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• pp.216-220
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• 2020

This field evaluated the effect of different yields on the drying rate of Italian ryegrass ("Kowinearly", Lolium multiflorum Lam.) hay during the spring season. The experiment was performed at Hwaseong, 2015. The different yields of the plot were selected by growth and development check. Three treatments were 35 t/ha(Y1), 45 t/ha(Y2), and 60 t/ha(Y3). After harvest with conditioner, it was conducted tedding 1/day. It was investigated patterns for changes in moisture content. The changes in moisture content were respectively Y1 from 78.9% to 14.4%, Y2 from 79.1% to 18.3%, and Y3 from 77.9% to 25.5% for 5days. It was no different significantly for changes in moisture content by yields from 1st day ~ 2nd day, But It was different significantly from 3rd day to 5th day. the content of neural detergent fiber(NDF) and acid detergent fiber(ADF) were respectively about 34%, 59%, regardless of yields (P>0.05). Crude protein of Yields Y1, Y2, and Y3 were respectively 6.9%, 8.7%, and 9.4% (P<0.05). The result of this study that the higher yields, the slower it dried. The Quantity is a factor to effect on drying rate.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.81-94
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• 2020

Based on innovative technologies and new start-up ideas, startups have been actively researched on the entrepreneurship needed to strengthen the organization's capabilities and generate results in the start-up process. This study studied the entrepreneurial orientation on the performance of startups in the Philippines and the financial and non-financial performance of enterprises. This study carried out not only the entrepreneurial orientation to the performance of Filipino startups but also the role of social capital as parameters in the performance of enterprises. The empirical research was completed for 93 Philippine startups and the suitability of the research model was evaluated with a PLS-based structural equation model. The results of the study first confirmed that the enterprise orientation of Philippine startups has a positive impact on both financial and non-financial performance of the enterprises. Second, the entrepreneurial orientation of Philippine startups has been shown to have a positive effect on both the structural, cognitive and relational dimensions of social capital. Third, it was found that the relevant dimensions of social capital mediated both the corporate orientation and the relationship between the financial and non-financial performance of the entity. Entrepreneurial orientation has been confirmed to be directly or indirectly affecting the performance of startups through social capital. These findings reaffirmed that entrepreneurial orientation is still a valid important factor in developing countries as well as in countries such as Korea and the United States. Based on this study, we have identified the need for research from a more integrated perspective, such as the concept of strategic orientation. Finally, practical implications were presented to reflect the findings analyzed.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1193-1201
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• 2020

This study aims to develop a regression model that estimates a low-flow index that can be applied to ungauged basins. A total of 30 midsized basins in South Korea use long-term runoff data provided by the National Integrated Water Management System (NIWMS) to calculate average low-flow, average minimum streamflow, and low-flow index duration and frequency. This information is used in the correlation analysis with 18 basin factors and 3 climate change factors to identify the basin area, average basin altitude, average basin slope, water system density, runoff curve number, annual evapotranspiration, and annual precipitation in the low-flow index regression model. This study evaluates the model's accuracy by using the root-mean-square error (RMSE) and the mean absolute error (MAE) for 10 ungauged, verified basins and compares them with the previous model's low-flow calculations to determine the effectiveness of the newly developed model. Comparative analysis indicates that the new regression model produces average low-flow, attributed to the consideration of varied basin and hydrologic factors during the new model's development.