• Journal of Life Science
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• v.33 no.2
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• pp.138-148
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• 2023

This study compared and analyzed the antioxidant activities of various organic solvent fractions from the leaves and roots of Peucedanum insolens Kitagawa. For this study, the dried leaves and roots of P. insolens Kitagawa were first extracted using 70% ethanol. The extracts were sequentially sub-fractionated in the order of hexane, chloroform, ethyl acetate, n-butanol, and water. The results revealed that the distribution of total phenolic contents by organic solvent fractions showed the same pattern in both the leaves and roots, with the highest in the ethyl acetate fraction (101.1±1.0 mg vs 71.2±3.4 mg of GAE/mg), but the lowest content in the hexane fraction (9.5±0.2 mg vs 7.5±2.1 mg of GAE/mg). The distribution of total flavonoid content in the organic solvent fractions showed the same pattern as that of total phenolic content. The results of DPPH, ABTS, and FRAP assays showed that the leaf and root extracts exhibited free radical scavenging activity in the same pattern, particularly, the ethyl acetate fraction had the highest activity. These results indicate that not only the roots of P. insolens Kitagawa but also the leaves possess potential substances that exhibit strong antioxidant activity. Significant correlations (R=0.903, p<0.0001, DPPH radical; R=0.891, p<0.001, ABTS radical; R=0.745, p<0.05, FRAP radical) between total phenolics and radical scavenging activities, but also significant correlations (R=0.867, p<0.001, DPPH vs. ABTS radicals; R=0.882, p<0.0001, DPPH vs. FRAP radicals; R=0.973, p<0.0001, ABTS vs. FRAP radicals) between radical scavenging activities were found in the organic solvent fractions. Therefore, as in the roots of P. insolens Kitagawa, the leaves possess strong antioxidant capacity and can be used as the main antioxidant material.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.167-183
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• 2023

In the recent field of recommendation systems, various studies have been conducted to model sparse data effectively. Among these, GLocal-K(Global and Local Kernels for Recommender Systems) is a research endeavor combining global and local kernels to provide personalized recommendations by considering global data patterns and individual user characteristics. However, due to its utilization of kernel tricks, GLocal-K exhibits diminished performance on highly sparse data and struggles to offer recommendations for new users or items due to the absence of side information. In this paper, to address these limitations of GLocal-K, we propose the GEase-K (Global and EASE kernels for Recommender Systems) model, incorporating the EASE(Embarrassingly Shallow Autoencoders for Sparse Data) model and leveraging side information. Initially, we substitute EASE for the local kernel in GLocal-K to enhance recommendation performance on highly sparse data. EASE, functioning as a simple linear operational structure, is an autoencoder that performs highly on extremely sparse data through regularization and learning item similarity. Additionally, we utilize side information to alleviate the cold-start problem. We enhance the understanding of user-item similarities by employing a conditional autoencoder structure during the training process to incorporate side information. In conclusion, GEase-K demonstrates resilience in highly sparse data and cold-start situations by combining linear and nonlinear structures and utilizing side information. Experimental results show that GEase-K outperforms GLocal-K based on the RMSE and MAE metrics on the highly sparse GoodReads and ModCloth datasets. Furthermore, in cold-start experiments divided into four groups using the GoodReads and ModCloth datasets, GEase-K denotes superior performance compared to GLocal-K.

• Journal of the Korean Society of International Agriculture
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• v.31 no.4
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• pp.378-383
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• 2019

To determine whether FT-IR spectral analysis based on multivariate analysis for whole cell extracts can be used to discriminate papaya at metabolic level. FT-IR spectral data from leaves were analyzed by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700-1,500, 1,500-1,300 and 1,100-950 cm^-1, respectively. These spectral regions were reflecting the quantitative and qualitative variations of amide I, II from amino acids and proteins (1,700-1,500 cm^-1), phosphodiester groups from nucleic acid and phospholipid (1,500-1,300 cm^-1) and carbohydrate compounds (1,100-950 cm^-1). The result of PCA analysis showed that papaya leaves could be separated into clusters depending on different growth temperature. In this case, showed discrimination confirmed according to metabolite content of growth condition from papaya. And PLS-DA analysis also showed more clear discrimination pattern than PCA result. Furthermore, these metabolic discrimination systems could be applied for rapid selection and classification of useful papaya cultivars.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.267-275
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• 2023

This study predicted rice harvest date in South Korea using 11-year (2012-2022) hindcasts based on dynamically downscaled 2m air temperature at subseasonal (1-month lead) timescale. To obtain high (5 km) resolution meteorological information over South Korea, global prediction obtained from the NOAA Climate Forecast System (CFSv2) is dynamically downscaled using the Weather Research and Forecasting (WRF) double-nested modeling system. To estimate rice harvest date, the growing degree days (GDD) is used, which accumulated the daily temperature from the seeding date (1 Jan.) to the reference temperature (1400℃ + 55 days) for harvest. In terms of the maximum (minimum) temperatures, the hindcasts tends to have a cold bias of about 1. 2℃ (0. 1℃) for the rice growth period (May to October) compared to the observation. The harvest date derived from hindcasts (DOY 289) well simulates one from observation (DOY 280), despite a margin of 9 days. The study shows the possibility of obtaining the detailed predictive information for rice harvest date over South Korea based on the dynamical downscaling method.

• Korean Journal of Culture and Social Issue
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• v.16 no.3
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• pp.355-383
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• 2010

In this study, the effects of skill-utilization based underemployment on self-esteem and mental health were examined. Also the moderating effects of employment commitment and social support were verified. Data obtained by a longitudinally designed survey with the reemployed (N=153) after job loss were used. The skill-utilization based underemployment was measured in two ways. One is measured in the way that use objective data, the ratio of education - 'educational requirement for the current job' divided by 'individual educational attainment.' The other is measured in the way that use psychological and self-reported measure, two factors of overqualification - the absence of opportunity for growth (no-growth) and the occupational mismatch in educational attainment, skills and experiences (mismatch). The main effect revealed that the no-growth made self-esteem lower and mental health (GHQ-social maladjustment) worse. The significant interaction of the ratio of education and employment commitment indicates that the negative effects of underemployment measured by the ratio of education on mental health (GHQ-social maladjustment, GHQ-depression/anxiety) were greater for those perceiving low employment commitment than for those perceiving high employment commitment. The significant interaction of the ratio of education and social support indicates that the negative effects of underemployment measured by the ratio of education on mental health (GHQ-depression/anxiety) were greater for those perceiving low social support than for those perceiving high social support. The two moderators also interacted with the two factors of perceived overqualification. Employment commitment had significant interaction effects with the no-growth and the mismatch on self-esteem and mental health (GHQ-depression/anxiety), whereas social support had a significant interaction only with the no-growth on mental health (GHQ-depression/anxiety). The significant interactions show that employment commitment and social support function as buffers in reducing the negative effects of skill-utilization based underemployment on self-esteem and mental health.

• Korean Journal of Mineralogy and Petrology
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• v.36 no.4
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• pp.355-363
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• 2023

In this study, we explore the nature of clumped isotopes of H₂O molecule using quantum chemical calculations. Particularly, we estimated the relative clumping strength between diverse isotopologues, consisting of oxygen (¹⁶O, ¹⁷O, and ¹⁸O) and hydrogen (hydrogen, deuterium, and tritium) isotopes and quantify the effect of temperature on the extent of isotope clumping. The optimized equilibrium bond lengths and the bond angles of the molecules are 0.9631-0.9633 Å and 104.59-104.62°, respectively, and show a negligible variation among the isotopologues. The calculated frequencies of the modes of H₂O molecules decrease as isotope mass number increases, and show a more prominent change with varying hydrogen isotopes over those with oxygen isotopes. The equilibrium constants of isotope substitution reactions involving these isotopologues reveal a greater effect of hydrogen mass number than oxygen mass number. The calculated equilibrium constants of clumping reaction for four heavy isotopologues showed a strong correlation; particularly, the relative clumping strength of three isotopologues was 1.86 times (HT¹⁸O), 1.16 times (HT¹⁷O), and 0.703 times (HD¹⁷O) relative to HD¹⁸O, respectively. The relative clumping strength decreases with increasing temperature, and therefore, has potential for a novel paleo-temperature proxy. The current calculation results highlight the first theoretical study to establish the nature of clumped isotope fractions in H₂O including ¹⁷O and tritium. The current results help to account for diverse geochemical processes in earth's surface environments. Future efforts include the calculations of isotope fractionations among various phases of H₂O isotopologues with a full consideration of the effect of anharmonicity in molecular vibration.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.2
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• pp.89-102
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• 2024

Land Surface Phenology (LSP) plays a crucial role in understanding vegetation dynamics. The near-infrared reflectance of vegetation (NIRv) has been increasingly adopted in LSP studies, being recognized as a robust proxy for gross primary production (GPP). However, NIR v is sensitive to the terrain effects in mountainous areas due to artifacts in NIR reflectance cannot be canceled out. Because of this, estimating phenological metrics in mountainous regions have a substantial uncertainty, especially in the end of season (EOS). The topographically corrected NIRv (TCNIRv) employs the path length correction (PLC) method, which was deduced from the simplification of the radiative transfer equation, to alleviate limitations related to the terrain effects. TCNIRv has been demonstrated to estimate phenology metrics more accurately than NIRv, especially exhibiting improved estimation of EOS. As the topographic effect is significantly influenced by terrain properties such as slope and aspect, our study compared phenology metrics estimations between south-facing slopes (SFS) and north-facing slopes (NFS) using NIRv and TCNIRv in two distinct mountainous regions: Gwangneung Forest (GF) and Odaesan National Park (ONP), representing relatively flat and rugged areas, respectively. The results indicated that TCNIR v-derived EOS at NFS occurred later than that at SFS for both study sites (GF : DOY 266.8/268.3 at SFS/NFS; ONP : DOY 262.0/264.8 at SFS/NFS), in contrast to the results obtained with NIRv (GF : DOY 270.3/265.5 at SFS/NFS; ONP : DOY 265.0/261.8 at SFS/NFS). Additionally, the gap between SFS and NFS diminished after topographic correction (GF : DOY 270.3/265.5 at SFS/NFS; ONP : DOY 265.0/261.8 at SFS/NFS). We conclude that TCNIRv exhibits discrepancy with NIR v in EOS detection considering slope orientation. Our findings underscore the necessity of topographic correction in estimating photosynthetic phenology, considering slope orientation, especially in diverse terrain conditions.

• Journal of the Korean earth science society
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• v.45 no.3
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• pp.260-276
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• 2024

The purpose of this study is to explore whether pre-service teachers majoring in earth science improve their perception of computational thinking through STEAM classes focused on engineering-based wave power plants. The STEAM class involved designing the most efficient wave power plant model. The survey on computational thinking practices, developed from previous research, was administered to 15 Earth science pre-service teachers to gauge their understanding of computational thinking. Each group developed an efficient wave power plant model based on the scientific principal of turbine operation using waves. The activities included problem recognition (problem solving), coding (coding and programming), creating a wave power plant model using a 3D printer (design and create model), and evaluating the output to correct errors (debugging). The pre-service teachers showed a high level of recognition of computational thinking practices, particularly in "logical thinking," with the top five practices out of 14 averaging five points each. However, participants lacked a clear understanding of certain computational thinking practices such as abstraction, problem decomposition, and using bid data, with their comprehension of these decreasing after the STEAM lesson. Although there was a significant reduction in the misconception that computational thinking is "playing online games" (from 4.06 to 0.86), some participants still equated it with "thinking like a computer" and "using a computer to do calculations". The study found slight improvements in "problem solving" (3.73 to 4.33), "pattern recognition" (3.53 to 3.66), and "best tool selection" (4.26 to 4.66). To enhance computational thinking skills, a practice-oriented curriculum should be offered. Additional STEAM classes on diverse topics could lead to a significant improvement in computational thinking practices. Therefore, establishing an educational curriculum for multisituational learning is essential.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.12
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• pp.1856-1864
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• 2015

The purpose of this study was to investigate the nutrient intake status of university students in Chuncheon area (175 males and 131 females). This study was conducted by employing a self-administered questionnaire. Dietary assessment was measured by a 24-h recall method. The average height and weight of male students were $175.2{\pm}6.2cm$ and $68.2{\pm}9.9kg$, respectively. For female students, average values were $161.7{\pm}5.2cm$ and $55.1{\pm}6.5kg$, respectively. The mean BMIs for both male and female students were 22.2 and 21.1, respectively. In both male and female students, the rate of skipping breakfast was high. Daily averages for energy, carbohydrates, protein, and fat intakes in male students were significantly higher than those of female students (P<0.001). For male students, protein, vitamin B1, P, Fe, and Na were above recommended nutrient intake and adequate intake, whereas for female students, they were protein, vitamin A, P, and Na. For male students, nutrient intakes for Ca, vitamin $B_2$, vitamin C, and vitamin $B_6$ were below the estimated average requirement (EAR) by at least 50% or more, whereas for female students, they were vitamin C, Fe, vitamin $B_6$, vitamin $B_2$, niacin, folate, and Ca. Ca was alarmingly low, with more than 75% of both male and female students showing levels below the EAR. Therefore, it is important that nutritional education be facilitated for college students to take responsibility of their own health through learning about nutrient intake as well as developing positive eating habits.

• Journal of the Korean Society of Food Culture
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• v.32 no.5
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• pp.383-393
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• 2017

This study was conducted to analyze the dietary lifestyle of local Chinese consumers and to classify dietary characteristics according to their dietary lifestyle factors and dietary behaviors. This investigation was conducted for 1 month from 1 January 2017 targeting 300 adult males and females living in China using the online survey company surveymonkey. Four factors relating to dietary lifestyle were identified, gourmet factor, healthy factor, convenience factor and economic factor, and these were grouped into 4 clusters according to their dietary lifestyle factor scores. Group 1, the gourmet economy group, showed a high percentage of living alone and a high frequency of eating out, but a relatively low percentage of three regular meals per day. Their dietary lifestyle was sensitive to gourmet factors and economic factors, but less sensitive to health and convenience factors. Group 2, the wide interest group, contained a high percentage of individuals in their 30s, as well as more highly educated individuals and a higher income than other groups. Because their dietary lifestyle scores tended to be higher than those of other groups, they sought a variety of new foods and gourmet meals for enjoyment of dining and life, as well as well-being food materials and foods related to health. Group 3, the health economic group, constituted a family-type consumer group with lower income level than the other groups. Members of this group were seeking health food and natural food in their dietary lifestyle and tended to pursue a high economic profit ratio when purchasing food. Finally, group 4 showed a relatively higher percentage of women over 30 and individuals with a college level or higher education than the other groups. This group was more interested in health and taste than price and convenience, and showed the highest LOHAS orientation among middle aged Chinese women. Moreover, members of this group directly utilized their knowledge regarding nutrition in real life.