• Journal of the Korean Society of Food Culture
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• v.23 no.2
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• pp.222-227
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• 2008

This study examined the chemical composition of lotus root and functionally evaluated a fermented lotus root drink. Electron-donating ability using DPPH along with nitrite-scavenging ability were used to compare the antioxidative activities of unfermented and fermented lotus root drinks. The electron-donating abilities of the unfermented lotus root drink (1%) and fermented lotusroot drink (1%) were 22.55% and 23.88%, respectively. At pH 6.0, the nitrite-scavenging abilities of the unfermented lotus root drink and the fermented lotus root drink (100%) were 27.64% and 40.3%, respectively, and their scavenging ability increased in a dose-dependent manner at all pH values. In order to study the anti-obesity effects of the two drinks, male Sprague-Dawley rats were divided into four groups (A: basal diet, B: high fat diet, C: high fat diet+unfermented lotus root drink, D: high fat diet+fermented lotus root drink). Net weight gains were not significantly different among the four groups. Plasma total cholesterol concentrations significantly decreased in the groups receiving the unfermented and fermented lotus root drinks. Also, plasma total lipid and triglyceride contents were lower in the groups receiving the unfermented and fermented lotus root drinks as compared to the high fat diet group; however, the differences among the three groups were not significant.

• Korean Journal of Culture and Social Issue
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• v.23 no.2
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• pp.131-157
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• 2017

Loving-kindness & compassion meditation (LCM) is one of the popular intervention on clinical setting to cultivate loving-kindness & compassion for self and other. Shame is known for unconscious and implicit emotion including negative self-concept. Some researchers suggest that people with high shame have difficulty in cultivating loving-kindness & compassion toward oneself because of shame including the negative self-critic. In this research, it is explored the influence of shame for the object of LCM. There are 2 experiments to find out the answer to this question. In experiment 1, participants (N = 108) are randomly assigned to two conditions. The one condition is loving-kindness meditation for self, and the other is loving-kindness meditation for positive others. Dislike and engagement from participants about loving-kindness meditation instruction are measured after meditation for 8 minutes. From the experiment 2, loving-kindness meditation is replaced with compassion meditation from the design of experiment 1. This experiment is conducted because of psychological differences between loving-kindness and compassion. Participants (N = 116) are randomly assigned to two conditions, compassion meditation for self and positive others, respectively. The results of experiment 1 show that dislike of loving-kindness meditation for self seems to high when people have high shame, but shame does not have an influence on engagement. For loving-kindness meditation for positive others, shame seems to not affect on dislike and engagement about loving-kindness meditation instruction. The results of experiment 2 show that dislike is higher for self than for positive others about compassion meditation for people with high shame, but shame does not affect on engagement. For discussion, it is suggested that shame has special features of emotion. For the future, we discuss the therapeutic strategy for people with negative self-concept.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.49 no.4
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• pp.313-321
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• 2023

Platycodon grandiflorus (P. grandiflorus) flower is a perennial plant belonging to the family Campanulaceae and has many excellent pharmacological effects, so it has been used as a medicinal ingredient since ancient times. In addition, anthocyanin is a purple or blue natural pigment contained in plant flowers and fruits, and is known as a powerful antioxidant. The purpose of this study was to confirm the dermatological functionality of P. grandiflorus flower extract and the value of the bluish anthocyanin contained in flowers as a cosmetic material as a natural pigment. Firstly, 50% ethanol and 80% ethanol were added to the P. grandiflorus flower and extracted under reflux for 4 h at 25, 60, and 80 ℃, and the pH of each treatment group was similar. Based on the anthocyanin content and chromaticity (E^*ab), 50% ethanol 60 ℃ extraction conditions showing the color development most similar to the natural color of the P. grandifloras flower were selected, and a sample was prepared by concentrating and lyophilizing. The analysis results showed that the total phenol, total flavonoid, and total anthocyanin contents were in the ranges of 23 ㎍/mL, 16 ㎍/mL, and 0.17 ㎍/mL, respectively. The P. grandiflorus flower extract suppressed the production of nitric oxide (NO) and interleukin-6 (IL-6) in lipopolysaccharide (LPS) induced RAW264.7 cells. Furthermore, the P. grandiflorus flower extract showed wound healing effects through the promotion of skin cell migration in TNF-α stimulated human keratinocytes. The stability of anthocyanin and extract color was studied during a storage period of 50 days at various temperatures (4 ℃, 25 ℃, and 45 ℃). Color values (L, a, and b) of the P. grandiflorus flower extract changed over 50 days, whereas the bluish-purple color of the extract was stabilized using 5% maltodextrin. These results suggest that P. grandiflorus flower extract may be useful as a natural cosmetic pigment.

• Journal of Korea Port Economic Association
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• v.39 no.2
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• pp.15-23
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• 2023

In a situation where the necessity and importance of ESG management is increasing recently, it is judged that selecting important ESG-related variables for container terminals, which are the bases of export and import logistics, among various variables of ESG evaluation agencies will help to establish ESG management strategies for container terminals which led us to proceed with this study. The results of word network analysis are summarized as follows. The weighed degree, that is, the AWD of Environmental management(E) variables, is obtained in the order of Environmental Protection Investment(54), Environmental Awareness Education(45), Work Team Structure(31), Environmental certification(32). Page Ranks, the order of centrality and connectivity index is Environmental Awareness Education(0.0765), Employee Engagement(0.0765), Environmental Protection Investment(0.0761), Work Team Composition(0.0761), and Environmental certification(0.0761). The AWD(Average Weighed Degree) of the Social Responsibility Management(S) variables, followed by Protecting workers' human rights and contributing to local communities(68), Safety Education(63), Safety certification(59), and Responding to infectious diseases(40). Orders by Page Ranks, centrality and connectivity Index, are Protecting workers' human rights and contributing to local communities(0.165), Safety Education(0.153), Safety Certification(0.144) and Responding to infectious diseases(0.102). The AWD of Governance and Ethical management(G) variables, followed by Anti-corruption(27), Transparent management(24), Mutual cooperation between stakeholders(19), and Sustainability reporting(9). Page Ranks, the order of centrality and connectivity index is the Anti Corruption(0.241), Transparent management(0.216), Mutual cooperation between stakeholders(0.174), Directors' roles and responsibilities(0.105), Shareholder protection(0.097) and Sustainability Report(0.096).

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.695-713
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• 2023

In coastal waters, phytoplankton,suspended particulate matter, and dissolved organic matter intricately and nonlinearly alter the reflectivity of seawater. Neural network technology, which has been rapidly advancing recently, offers the advantage of effectively representing complex nonlinear relationships. In previous studies, a three-stage neural network was constructed to extract the inherent optical properties of each component. However, this study proposes an algorithm that directly employs a deep neural network. The dataset used in this study consists of synthetic data provided by the International Ocean Color Coordination Group, with the input data comprising above-surface remote-sensing reflectance at nine different wavelengths. We derived inherent optical properties using this dataset based on a deep neural network. To evaluate performance, we compared it with a quasi-analytical algorithm and analyzed the impact of log transformation on the performance of the deep neural network algorithm in relation to data distribution. As a result, we found that the deep neural network algorithm accurately estimated the inherent optical properties except for the absorption coefficient of suspended particulate matter (R² greater than or equal to 0.9) and successfully separated the sum of the absorption coefficient of suspended particulate matter and dissolved organic matter into the absorption coefficient of suspended particulate matter and dissolved organic matter, respectively. We also observed that the algorithm, when directly applied without log transformation of the data, showed little difference in performance. To effectively apply the findings of this study to ocean color data processing, further research is needed to perform learning using field data and additional datasets from various marine regions, compare and analyze empirical and semi-analytical methods, and appropriately assess the strengths and weaknesses of each algorithm.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.949-965
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• 2023

In this study, we propose a method to monitor the surface area of agricultural reservoirs in South Korea using Sentinel-1 synthetic aperture radar images and the deep learning model, Swin Transformer. Utilizing the Google Earth Engine platform, datasets from 2017 to 2021 were constructed for seven agricultural reservoirs, categorized into 700 K-ton, 900 K-ton, and 1.5 M-ton capacities. For four of the reservoirs, a total of 1,283 images were used for model training through shuffling and 5-fold cross-validation techniques. Upon evaluation, the Swin Transformer Large model, configured with a window size of 12, demonstrated superior semantic segmentation performance, showing an average accuracy of 99.54% and a mean intersection over union (mIoU) of 95.15% for all folds. When the best-performing model was applied to the datasets of the remaining three reservoirsfor validation, it achieved an accuracy of over 99% and mIoU of over 94% for all reservoirs. These results indicate that the Swin Transformer model can effectively monitor the surface area of agricultural reservoirs in South Korea.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.3
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• pp.134-146
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• 2023

Phytophthora root rot (PRR) is a major soybean disease caused by an oomycete, Phytophthora sojae. PRR can be severe in poorly drained fields or wet soils. The disease management primarily relies on resistance genes called Rps (resistance to P. sojae). This study aimed to identify resistance loci associated with resistance to P. sojae isolate 40468 in Daepung × CheonAl recombinant inbred line (RIL) population. CheonAl is resistant to the isolate, while Daepung is generally susceptible. We genotyped the parents and RIL population via high-throughput single nucleotide polymorphism genotyping and constructed a set of genetic maps. The presence or absence of resistance to P. sojae was evaluated via hypocotyl inoculation technique, and phenotypic distribution fit to a ratio of 1:1 (R:S) (χ² = 0.57, p = 0.75), indicating single gene mediated inheritance. Single-marker association and the linkage analysis identified a highly significant genomic region of 55.9~56.4 megabase pairs on chromosome 18 that explained ~98% of phenotypic variance. Many previous studies have reported several Rps genes in this region, and also it contains nine genes that are annotated to code leucine-rich repeat or serine/threonine kinase within the approximate 500 kilobase pairs interval based on the reference genome database. CheonAl is the first domestic soybean genotype characterized for resistance against P. sojae isolate 40468. Therefore, CheonAl could be a valuable genetic source for breeding resistance to P. sojae.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.1
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• pp.42-55
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• 2008

To evaluate the accuracy of currents measured by HF radar in the coastal sea off Keum River estuary, we compared the facing radial vectors of two HF radars, and HF radar-derived currents with in-situ measurement currents. Principal component analysis was used to extract regression line and RMS deviation in the comparison. When two facing radar's radial vectors at the mid-point of baseline are compared, RMS deviation is 4.4 cm/s in winter and 5.4 cm/s in summer. When GDOP(Geometric Dilution of Precision) effect is corrected from the RMS deviations that is analyzed from the comparison between HF radar-derived and current-metermeasured currents, the error of velocity combined by HF radar-derived current is less than 5.1 cm/s in the stations having moderate GDOP values. These two results obtained from different method suggest that the lower limit of HF radar-derived current's accuracy is 5.4 cm/s in our study area. As mentioned in previous researches, RMS deviations become large in the stations located near the islands and increase as a function of mean distance from the radar site due to decrease of signal-to-noise level and the intersect angle of radial vectors. We found that an uncertain error bound of HF radar-derived current can be produced from the separation process of RMS deviations using GDOP value if GDOP value for each component is very close and RMS deviations obtained from current component comparison are also close. When the current measured in the stations having moderate GDOP values is separated into tidal and subtidal current, characteristics of tidal current ellipses analyzed from HF radar-derived current show a good agreement with those from current-meter-measured current, and time variation of subtidal current showed a response reflecting physical process driven by wind and density field.

• Journal of Life Science
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• v.34 no.7
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• pp.500-508
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• 2024

Recently, there has been increasing interest in enhancing the indoor air quality, particularly in response to the growing utilization of public facilities. The focus of this study was on assessing the efficacy and safety of an air sterilizer equipped with electrolytic salt catalysts. To that end, we evaluated the antimicrobial activity of the vapor spraying from the air sterilizer and its cytotoxicity in condensed form on human cell lines (HaCaT, BEAS-2B, and THP-1). Against the test organisms, which comprised five bacterial strains (Staphylococcus aureus, Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa, Salmonella typhimurium) and one fungal strain (Candida albicans), the air sterilizer exhibited relatively high antimicrobial activities ranging from 10.89 to 73.98% following 1 and 3 hr of vapor spraying, which were notably time-dependent. Importantly, cytotoxicity assessments on human cells indicated no significant harmful effect even at a 1.0% concentration. Comprehensive safety evaluations included morphological observations, gene expression (Bcl-2, Bax) tests, and FACS analysis of intracellular ROS levels. Consistent with previous cytotoxicity findings, these estimates demonstrated no significant changes, highlighting the air sterilizer's safety and antimicrobial activities. In a simulated 20-hr operation within an indoor environment, the air sterilizer not only showed an 89.4% removal of total bacteria but also a 100.0% removal of Escherichia sp. and fungi. This research outlines the potential of the developed electrolytic salt catalyst air sterilizer to effectively remove indoor microbial pollutants without compromising human safety, underscoring the solution that it offers for improving indoor air quality.