• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1009-1029
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• 2023

Urban trees play a vital role in urban ecosystems,significantly reducing impervious surfaces and impacting carbon cycling within the city. Although previous research has demonstrated the efficacy of employing artificial intelligence in conjunction with airborne light detection and ranging (LiDAR) data to generate urban tree information, the availability and cost constraints associated with LiDAR data pose limitations. Consequently, this study employed freely accessible, high-resolution multispectral satellite imagery (i.e., Sentinel-2 data) to estimate fractional tree canopy cover (FTC) within the urban confines of Suwon, South Korea, employing machine learning techniques. This study leveraged a median composite image derived from a time series of Sentinel-2 images. In order to account for the diverse land cover found in urban areas, the model incorporated three types of input variables: average (mean) and standard deviation (std) values within a 30-meter grid from 10 m resolution of optical indices from Sentinel-2, and fractional coverage for distinct land cover classes within 30 m grids from the existing level 3 land cover map. Four schemes with different combinations of input variables were compared. Notably, when all three factors (i.e., mean, std, and fractional cover) were used to consider the variation of landcover in urban areas(Scheme 4, S4), the machine learning model exhibited improved performance compared to using only the mean of optical indices (Scheme 1). Of the various models proposed, the random forest (RF) model with S4 demonstrated the most remarkable performance, achieving R² of 0.8196, and mean absolute error (MAE) of 0.0749, and a root mean squared error (RMSE) of 0.1022. The std variable exhibited the highest impact on model outputs within the heterogeneous land covers based on the variable importance analysis. This trained RF model with S4 was then applied to the entire Suwon region, consistently delivering robust results with an R² of 0.8702, MAE of 0.0873, and RMSE of 0.1335. The FTC estimation method developed in this study is expected to offer advantages for application in various regions, providing fundamental data for a better understanding of carbon dynamics in urban ecosystems in the future.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.68 no.3
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• pp.121-133
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• 2023

The purpose of this study was to improve weed management systems under varying carbon dioxide concentrations and temperatures by evaluating the growth of Acalypha australis and observing the efficacy of four foliar and four soil herbicides, as well as measuring phytotoxicity in soybean crops treated with these herbicides. In both growth chamber and greenhouse conditions, plant height and shoot fresh weight of Acalypha australis increased as temperature increased. The variable to maximum fluorescence ratio (Fv/Fm), relative electron transport rate (ETR), plant height, leaf area, and shoot fresh weight of Acalypha australis were higher at carbon dioxide concentrations of 800 ppm than at 400 ppm. The efficacy of a foliar herbicide, glufosinate, on Acalypha australis was lower at 30℃ than at 20℃ and 25℃ in the growth chamber condition and was also lower at 29℃ than at 21℃ and 25℃ in greenhouse conditions. In contrast, mecoprop efficacy on Acalypha australis was lower at 20℃ and 25℃ than at 30℃ in growth chamber conditions and lower at 21℃ and 25℃ than at 29℃ in greenhouse conditions. Glyphosate efficacy was lower at 21℃ than at 25℃ and 29℃ under greenhouse conditions. With soil herbicides, metolachlor and ethalfluraline, efficacies were higher at relatively high temperatures under both growth chamber and greenhouse conditions. However, in the case of linuron, the difference in efficacy was not observed under varying temperatures in both growth chamber and greenhouse conditions. When ¼ of the recommended glyphosate rates were applied to Acalypha australis, efficacy was lower under 800 ppm carbon dioxide concentrations than under 400 ppm. In contrast, when ¼ of the recommended rate of bentazone was applied to Acalypha australis, efficacy was higher under 800 ppm carbon dioxide concentrations than under 400 ppm. Despite application rates, glufosinate efficacy differed insignificantly under different carbon dioxide concentrations. When applied at ¼ of the recommended rate, the efficacy of ethalfuralin was higher under 800 ppm carbon dioxide concentrations than under 400 ppm. However, efficacies of other herbicides were not different despite varying carbon dioxide concentrations. Soybean phytotoxicity in crops treated with the recommended rate and twice the recommended rate of soil herbicides was not significantly different regardless of temperature and carbon dioxide concentrations. Overall, weed efficacy of some herbicides decreased in response to different temperatures and carbon dioxide concentrations. Therefore, new weed management methods are required to ensure high rates of weed control in conditions affected by climate change.

• Journal of Nutrition and Health
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• v.56 no.5
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• pp.483-495
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• 2023

Purpose: The purpose of this study was to determine whether the dietary quality of food consumed by the elderly is influenced by the consumption of healthy functional foods using Nutrition Quotients for the Elderly (NQ-E). Methods: The study subjects were 250 adults aged ≥ 65 living in Seoul or Gyeonggi-do. Those who had consumed healthy functional food for more than 2 weeks within the previous year were classified as healthy functional food consumers, and the quality of their meals was evaluated using the NQ-E. Statistical analysis was performed using SAS 9.4, and sex and age-associated differences were adjusted before comparing differences based on healthy functional food intake. Results: The average age of the study subjects was 70.8. The scores for each area and the Nutrition Quotient (NQ) score were as follows: balance 43.3 points, moderation 56.7 points, practice 65.7 points, and NQ 52.5 points. When comparing differences according to healthy functional food intake status, healthy functional food consumers had significantly higher balance and NQ scores than non-consumers. When considering each NQ item score, healthy functional food consumers had significantly higher scores than non-consumers for fruit, fish and seafood, eggs, nuts, and whole grain rice, and a higher score for effort to maintain a healthy diet. Conclusion: Dietary quality as assessed by Nutrition Quotients for the Elderly was better for healthy functional food consumers than non-consumers.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.523-541
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• 2023

As accessibility to 3D printers increases, there is a growing frequency of exposure to chemicals associated with 3D printing. However, research on the toxicity and harmfulness of chemicals generated by 3D printing is insufficient, and the performance of toxicity prediction using in silico techniques is limited due to missing molecular structure data. In this study, quantitative structure-activity relationship (QSAR) model based on data-centric AI approach was developed to predict the toxicity of new 3D printing materials by imputing missing values in molecular descriptors. First, MissForest algorithm was utilized to impute missing values in molecular descriptors of hazardous 3D printing materials. Then, based on four different machine learning models (decision tree, random forest, XGBoost, SVM), a machine learning (ML)-based QSAR model was developed to predict the bioconcentration factor (Log BCF), octanol-air partition coefficient (Log Koa), and partition coefficient (Log P). Furthermore, the reliability of the data-centric QSAR model was validated through the Tree-SHAP (SHapley Additive exPlanations) method, which is one of explainable artificial intelligence (XAI) techniques. The proposed imputation method based on the MissForest enlarged approximately 2.5 times more molecular structure data compared to the existing data. Based on the imputed dataset of molecular descriptor, the developed data-centric QSAR model achieved approximately 73%, 76% and 92% of prediction performance for Log BCF, Log Koa, and Log P, respectively. Lastly, Tree-SHAP analysis demonstrated that the data-centric-based QSAR model achieved high prediction performance for toxicity information by identifying key molecular descriptors highly correlated with toxicity indices. Therefore, the proposed QSAR model based on the data-centric XAI approach can be extended to predict the toxicity of potential pollutants in emerging printing chemicals, chemical process, semiconductor or display process.

• Clean Technology
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• v.29 no.4
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• pp.255-261
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• 2023

Power semiconductors are semiconductors used for power conversion, transformation, distribution, and control. Recently, the global demand for high-voltage power semiconductors is increasing across various industrial fields, and optimization research on high-voltage IGBT components is urgently needed in these industries. For high-voltage IGBT development, setting the resistance value of the wafer and optimizing key unit processes are major variables in the electrical characteristics of the finished chip. Furthermore, the securing process and optimization of the technology to support high breakdown voltage is also important. Etching is a process of transferring the pattern of the mask circuit in the photolithography process to the wafer and removing unnecessary parts at the bottom of the photoresist film. Ion implantation is a process of injecting impurities along with thermal diffusion technology into the wafer substrate during the semiconductor manufacturing process. This process helps achieve a certain conductivity. In this study, dry etching and wet etching were controlled during field ring etching, which is an important process for forming a ring structure that supports the 3.3 kV breakdown voltage of IGBT, in order to analyze four conditions and form a stable body junction depth to secure the breakdown voltage. The field ring ion implantation process was optimized based on the TEG design by dividing it into four conditions. The wet etching 1-step method was advantageous in terms of process and work efficiency, and the ring pattern ion implantation conditions showed a doping concentration of 9.0E13 and an energy of 120 keV. The p-ion implantation conditions were optimized at a doping concentration of 6.5E13 and an energy of 80 keV, and the p+ ion implantation conditions were optimized at a doping concentration of 3.0E15 and an energy of 160 keV.

• Clean Technology
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• v.29 no.4
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• pp.288-296
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• 2023

Coal is abundantly available compared to other energy sources and is used as a versatile energy resource worldwide. To address the environmental issues stemming from conventional coal utilization, efforts are underway to develop clean coal utilization technologies, with IGCC technology being a notable example. In IGCC plants, coal is subjected to a CMD process where both drying and pulverization are achieved by supplying hot air. However, if the temperature of the supplied hot air is excessively high, it can lead to devolatilization and spontaneous combustion, thereby compromising the stable operation of the CMD process. This study aimed to measure the devolatilization and spontaneous combustion temperatures of different types of bituminous coal, and to explore their correlations with the characteristics of the coals. Six coal types exhibited devolatilization between 350 and 400 ℃, while three coal types showed devolatilization at temperatures exceeding 400 ℃. Spontaneous combustion ℃curred in one coal type below 100 ℃, six coal types between 100 and 150 ℃, and two coal types above 150 ℃. The measured initiation temperatures were compared with the coal characteristics including the oxygen, moisture, Fe₂O₃, and CaO content, the H/C ratio, and the O/C ratio to establish correlations. Regression analysis was used to calculate the regression coefficients and determination coefficients for each ignition temperature. It was found that 52.44% of the FC/VM data significantly influenced the volatile matter ignition temperature, and 59.10% of the Fe₂O₃ data significantly affected the spontaneous combustionignition temperature.

• Journal of Life Science
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• v.33 no.12
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• pp.1002-1014
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• 2023

The root of Cirsium japonicum var. maackii (Maxim.) has long been used in traditional medicine to prevent the onset and progression of various diseases and has been reported to exert a wide range of physiological effects, including antioxidant activity. However, research on its effects on hepatocytes remains scarce. This study used the human hepatocellular carcinoma HepG2 cell line to investigate the antioxidant activity of ethanol extract of C. japonicum root (EECJ) on hepatocytes. Hydrogen peroxide (H₂O₂) was used to mimic oxidative stress. The results showed that EECJ significantly reverted the decrease in cell viability and suppressed the release of lactate dehydrogenase in HepG2 cells treated with H₂O₂. Moreover, an analysis of changes in cell morphology, flow cytometry, and microtubule-associated protein light chain 3 (LC3) expression showed that EECJ significantly inhibited HepG2 cell autophagy induced by H₂O₂. Furthermore, it attenuated H₂O₂-induced apoptosis and cell cycle disruption by blocking intracellular reactive oxygen species and mitochondrial superoxide production, indicating strong antioxidant activity. EECJ also restored the decreased levels of intracellular glutathione (GSH) and enhanced the expression and activity of superoxide dismutase and GSH peroxidase in H₂O₂-treated HepG2 cells. Although an analysis of the components contained in EECJ and in vivo validation using animal models are needed, these findings indicate that EECJ is a promising candidate for the prevention and treatment of oxidative stress-induced liver cell damage.

• Journal of Life Science
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• v.33 no.12
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• pp.1036-1045
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• 2023

Sarcopenia, a condition characterized by the insidious loss of skeletal muscle mass and strength, represents a significant and growing healthcare challenge, impacting the mobility and quality of life of aging populations worldwide. This study investigated the therapeutic potential of soybean leaf extract (SL) for dexamethasone (Dexa)-induced muscle atrophy in vitro and in an in vivo model. In vitro experiments showed that SL significantly alleviated Dexa-induced atrophy in C2C12 myotube cells, as evidenced by preserved myotube morphology, density, and size. Moreover, SL treatment significantly reduced the mRNA and protein levels of muscle RING-finger protein-1 (MuRF1) and muscle atrophy F-box (MAFbx), key factors regulating muscle atrophy. In a Dexa-induced atrophy mouse model, SL administration significantly inhibited Dexa-induced weight loss and muscle wasting, preserving the mass of the gastrocnemius and tibialis anterior muscles. Furthermore, mice treated with SL exhibited significant improvements in muscle function compared to their counterparts suffering from Dexa-induced muscle atrophy, as evidenced by a notable increase in grip strength and extended endurance on treadmill tests. Moreover, SL suppressed the expression of muscle atrophy-related proteins in skeletal muscle, highlighting its protective role against Dexa-induced muscle atrophy. These results suggest that SL has potential as a natural treatment for muscle-wasting conditions, such as sarcopenia.

• Journal of Life Science
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• v.33 no.12
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• pp.1015-1024
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• 2023

Antibiotics have greatly contributed to the treatment and prevention of bacterial diseases in humans, animals, and fish. However, antibiotic misuse has led to the emergence and spread of multidrug-resistant bacteria. In addition to antibiotic discovery research, efforts are being made to combat such multidrug-resistant bacteria using antimicrobial agents, antioxidants, host immune enhancement, probiotics, and bacteriophages, as well as various symptomatic therapies. To discover novel bioactive compounds, it is crucial to adopt approaches that incorporate fresh ideas, new targets, innovative techniques, and untapped resources. Halophytes are plants that grow in high-salt soils and are known to adapt to salt-induced stress through unique metabolic processes that produce secondary metabolites. This study aimed to investigate the effects of extracts of halophytes native to Korea on oxidative stress and to determine whether they exert inhibitory activity against biofilms, which are major pathogenic factors of infectious bacteria. The Acinetobacter baumannii strain ATCC 17978, a representative drug-resistant bacterium, was used to measure anti-biofilm activity. The results showed that Aster spathulifolius, Carex kobomugi, Rosa rugosa, and Asparagus cochinchiensis exerted strong antioxidant and anti-biofilm effects without affecting bacterial growth itself. The halophytes used in this study are promising candidates for the development of pharmaceutical agents with antioxidant and antimicrobial properties.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.