• Korean Journal of Mineralogy and Petrology
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• v.37 no.1
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• pp.1-11
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• 2024

World stone production in 2021 stood at 162.5 million tons, up by 7.5 million tons, or 4.8 percent, compared to the previous year when the production came in at 155 million tons. Six top countries with the most of stone production were China, India, Turkey, Brazil, Iran and Italy and these six countries accounted for 72.8 percent of total production in the world. Stone exports stood at $21.68 billion in 2021, up by $2.3 billion from the previous year. Exports of raw materials and processed stones stood at 54.4 million tons, up by 2.98 million tons from the previous year. In terms of aggregate exports, exports of natural stones increased by $2.3 billion to $21.7 billion while exports of artificial stones rose $2.6 billion to $13.6 billion in 2021 compared to the previous year. The average price of stone (Code: 68.02) was up by $65.2 per ton to $794.82. The price of board, processed stone, an ingredient for building materials, increased by $3.52 per square meter to $42.96 per square meter. Recycling was always the problem as the volume of the total quarry was 333.5 million tons, of which only 28.8 percent were finished products and the remaining 71.2 percent were waste generated from stone extraction and processing. Korea's stone exports stood at $1.97 million in 2021, down 38.3 percent on year, while imports were up 8.6 percent to $758.9 million. Stone exports are expected to grow to 66.1 million tons in 2025, while usage is expected to reach 108.92 million tons, or 2 billion square meters.

• Journal of Life Science
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• v.34 no.4
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• pp.245-253
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• 2024

We investigated to analyze total flavonoid content and fatty acid composition of Stachys sieboldii Miq root. In order to determine antioxidant and anti-inflammatory effects of fractions from S. sieboldii Miq. root, we conducted 1.1-Diphenyl-2-picryhydrazyl (DPPH) and 2,2'-Azino-bis (3-ethylbenothiazoline-6-sulfonic acid) diammonium salt radical cation (ABTS) assays for antioxidant and measured nitric oxide (NO) production induced by lipopolysaccharide (LPS) in RAW 264.7 cells. In addition, we examined an inhibitory effect of fractions from S. sieboldii Miq. root on smad signaling induced by transforming growth factor (TGF) β. Among the fractions, n-butanol (n-BuOH) fraction showed the highest flavonoid content (16.67 mg/g), followed by n-Hexane, water and 85% aqueous methanol (85% aq. MeOH) fractions. The fatty acid composition of S. sieboldii Miq. root was in the following order : n-6 fatty acids (54.3%) > n-3 fatty acids (21.2%) > saturated fatty acids (19.7%) > n-9 fatty acids (3.6%). As a result of the antioxidant efficacy, the DPPH and ABTS assays showed that n-BuOH fraction had higher scavenging activity compared to other fractions. Inhibitory effect on NO production showed that all fractions decreased LPS-induced NO production, indicating an anti-inflammatory activity of S. sieboldii Miq. root. 85% aq. MeOH and water fractions showed a higher efficacy in inhibiting transforming growth factor (TGF) β induced smad signaling. From the results, it suggests that food processing products using S. sieboldii Miq. root will be developed as a functional food for promoting health.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.87-104
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• 2023

Recently, concerns are growing over small and medium-sized companies holding out on debt as domestic loan interest rates have risen sharply due to the prolonged impact of COVID-19 and soaring raw material prices. In addition, loans from small and medium-sized enterprises, which are difficult in the business environment, are increasingly being rejected due to high loan interest rates and excessive submission documents and financial statements-oriented screening of loans by the financial sector. Therefore, since it is necessary to discuss ways to promote financing and investment by SMEs, this study intends to suggest ways to promote investment through the use of SMEs' ESG systems. The purpose of this study is to suggest that the use of ESG evaluation indicators used as non-financial indicators helps predict the corporate value of SMEs and the importance of SMEs actively participating in ESG information disclosure. This study suggests the necessity of introducing and practicing ESG by SMEs where financing is important, and aims to analyze as an empirical result that the use of non-financial indicators helps predict corporate value. As a result of the study, the ESG performance and corporate value of SMEs showed a positive (+) relationship. It can be seen that both the grades and corporate value of SMEs by ESG sector have a positive (+) influence relationship. The total ESG rating was confirmed to have a positive effect on corporate value, and it was confirmed that SMEs with higher ESG environment, social, and governance ratings were evaluated higher. According to the research results, it is suggested that SMEs also need to use ESG evaluation indicators, and in order to promote the growth of SMEs, it is suggested that research on ways to re-examine the corporate value of SMEs is necessary. Therefore, this study suggests that the use of ESG should be actively recommended and implemented as a way to establish a management strategy for SMEs, and that efforts to disclose ESG information can soon help SMEs solve information asymmetry. In addition, SMEs want to understand the investment mechanism that the introduction and practice of ESG can lead to the improvement of the value of SMEs and suggest the necessity of SME-type ESG policies in the future.

• Journal of Practical Agriculture & Fisheries Research
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• v.25 no.4
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• pp.24-38
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• 2024

Five species of plants (Pimpinella brachycarpa (Kom.) Nakai, Hylotelephium erythrostictum (Miq.) H. Ohba, Magnolia sieboldii K. Koch, Sanguisorba hakusanensis Makino, Agastache rugosa (Fisch. & Mey.) Kuntze) native to the clean area of Mt. Jiri were selected. The collection period was from May to September 2021, and the five species plants were collected in their native habitats with flowers in full bloom. The collected plants were extracted with 70% EtOH and 17 kinds of polyphenol components were analyzed. Next, flowers, leaves and roots were separated from plants, extracted with 70% EtOH for each part and experiments were conducted on DPPH, ABTS, total polyphenols, and total flavonoids. The results are as follows. 1. There were a total of 13 polyphenol components contained in the 5 species of plants native to Mt. Jiri. Among them, the total content of the most detected substance was Sanguisorba hakusanensis Makino, which was 126.2 ppm, and the main substance was ellagic acid (=ELA), which was 122.4 ppm. 2. As a result of examining the DPPH radical scavenging activity, the flowers, stems, and roots of Sanguisorba hakusanensis Makino showed the best scavenging activity, while the flower extracts of other plants showed good scavenging activity. 3. The highest ABTS radical scavenging activity was Sanguisorba hakusanensis Makino flower extract at 13.5 ㎍/㎖, followed by roots at 16.8 ㎍/㎖ and leaves at 22.6 ㎍/㎖;. Although such a large ABTS radical scavenging activity could not be confirmed in other plants, the flower extract was overall better than the leaf and root extracts of other parts. 4. The highest total polyphenol content was found in the leaves of Magnolia sieboldii K. Koch, at 161.4mg GAE/g, followed by the highest content in the roots of Magnolia sieboldii K. Koch and the roots of Agastache rugosa (Fisch. & Mey.) Kuntze, at 130.0mg GAE/g. Also, the lowest was found to be Sanguisorba hakusanensis Makino. 5. The total flavonoid content was 186.2mg CAE/g in the roots of Agastache rugosa (Fisch. & Mey.) Kuntze, 166.9mg CAE/g in the flowers, and the lowest was 116.1mg CAE/g in the leaves. As shown in the results above, Sanguisorba hakusanensis Makino has excellent antioxidant efficacy and has a high polyphenol content, so it is expected to be fully utilized in the cosmetics industry in the future.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.27 no.4
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• pp.403-414
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• 2023

Backgrounds/Aims: Pancreatoduodenectomy (PD) is recommended in fit patients with a carcinoma (PDAC) of the pancreatic head, and a delayed resection may affect survival. This study aimed to correlate the time from staging to PD with long-term survival, and study the impact of preoperative investigations (if any) on the timing of surgery. Methods: Data were extracted from the Recurrence After Whipple's (RAW) study, a multicentre retrospective study of PD outcomes. Only PDAC patients who underwent an upfront resection were included. Patients who received neoadjuvant chemo-/radiotherapy were excluded. Group A (PD within 28 days of most recent preoperative computed tomography [CT]) was compared to group B (> 28 days). Results: A total of 595 patents were included. Compared to group A (median CT-PD time: 12.5 days, interquartile range: 6-21), group B (49 days, 39-64.5) had similar one-year survival (73% vs. 75%, p = 0.6), five-year survival (23% vs. 21%, p = 0.6) and median time-to-death (17 vs. 18 months, p = 0.8). Staging laparoscopy (43 vs. 29.5 days, p = 0.009) and preoperative biliary stenting (39 vs. 20 days, p < 0.001) were associated with a delay to PD, but magnetic resonance imaging (32 vs. 32 days, p = 0.5), positron emission tomography (40 vs. 31 days, p > 0.99) and endoscopic ultrasonography (28 vs. 32 days, p > 0.99) were not. Conclusions: Although a treatment delay may give rise to patient anxiety, our findings would suggest this does not correlate with worse survival. A delay may be necessary to obtain further information and minimize the number of PD patients diagnosed with early disease recurrence.

• Clean Technology
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• v.30 no.1
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• pp.47-54
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• 2024

Jatropha oil extracted from the seeds of Nepalese Jatropha curcas, a non-edible crop, was used as a raw material and converted to biodiesel through a two-step process consisting of an esterification reaction and a transesterification reaction. Amberlyst-15 catalyst was applied to the esterification reaction between the free fatty acids contained in the Jatropha oil and methanol. The acid value of the Jatropha oil could be lowered from 11.0 to 0.26 mgKOH/g through esterification. Biodiesel was synthesized through a transesterification reaction between Jatropha oil with an acid value of 0.26 mgKOH/g and methanol over NaOH/γ-Al₂O₃ catalysts. As the loading amount of NaOH increased from 3 to 25 wt%, the specific surface area decreased from 129 to 28 m²/g and the pore volume decreased from 0.249 to 0.129 cm³/g. The amount and intensity of base sites over the NaOH/γ-Al₂O₃ catalysts increased simultaneously with the NaOH loading amount. It was confirmed that the optimal NaOH loading amount for the NaOH/γ-Al₂O₃ catalyst was 12 wt%. The optimal temperature for the transesterification reaction of Jatropha oil using the NaOH/γ-Al₂O₃ catalyst was selected to be 65 ℃. In the transesterification reaction of Jatropha oil using the NaOH/γ-Al₂O₃ catalyst, the reaction rate was affected by external diffusion limitation when the stirring speed was below 150 RPM, however the external diffusion limitation was negligible at higher stirring speeds.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.151-164
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• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.

• The Journal of Korean Society for School & Community Health Education
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• v.25 no.2
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• pp.45-57
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• 2024

Objectives: The purpose of this study is to determine the impact of artificial menopause on the diagnosis of thyroid cancer, breast cancer, and cervical cancer, and to provide basic data for cancer prevention and early diagnosis in women. Methods: Analysis was conducted using raw data from the 2011-2020 National Health and Nutrition Examination Survey. Among the 79,262 people surveyed in the 2011-2020 National Health and Nutrition Examination Survey, 10,207 people were selected as the final research subjects, excluding men, those under 18 years old, those over 80 years old, those who did not participate in the health survey, those with missing data, and those who were not in menopause. Among them, 248 people were diagnosed with thyroid cancer (2.7%), 225 people were diagnosed with breast cancer (2.5%), and 143 people were diagnosed with cervical cancer (21.5%). Results: First, there appeared to be differences between the thyroid cancer diagnosed group and the non-diagnosed group depending on educational level, childbirth experience, and menopause type. Second, there appeared to be differences between the breast cancer diagnosis group and the non-diagnosis group depending on educational level, menopause age, pregnancy experience, childbirth experience, subjective health status, and menopause type. Third, there appeared to be differences between the cervical cancer diagnosis group and the non-diagnosis group depending on menopause age, subjective health status, and menopause type. Fourth, compared to natural menopause, in the case of artificial menopause, the diagnosis probability of women increased by 2.010 times for thyroid cancer, 3.872 times for breast cancer, and 14.902 times for cervical cancer. Conclusion: For thyroid cancer, breast cancer, and cervical cancer, the probability of cancer diagnosis increases in the case of artificial menopause compared to natural menopause, so it is considered important to avoid experiencing artificial menopause to prevent cancer.

• Journal of Korea Water Resources Association
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• v.57 no.7
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• pp.437-449
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• 2024

Rainfall-runoff prediction studies using deep learning while considering catchment attributes have been gaining attention. In this study, we selected two models: the Transformer model, which is suitable for large-scale data training through the self-attention mechanism, and the LSTM-based multi-state-vector sequence-to-sequence (LSTM-MSV-S2S) model with an encoder-decoder structure. These models were constructed to incorporate catchment attributes and predict the inflow of 10 multi-purpose dam watersheds in South Korea. The experimental design consisted of three training methods: Single-basin Training (ST), Pretraining (PT), and Pretraining-Finetuning (PT-FT). The input data for the models included 10 selected watershed attributes along with meteorological data. The inflow prediction performance was compared based on the training methods. The results showed that the Transformer model outperformed the LSTM-MSV-S2S model when using the PT and PT-FT methods, with the PT-FT method yielding the highest performance. The LSTM-MSV-S2S model showed better performance than the Transformer when using the ST method; however, it showed lower performance when using the PT and PT-FT methods. Additionally, the embedding layer activation vectors and raw catchment attributes were used to cluster watersheds and analyze whether the models learned the similarities between them. The Transformer model demonstrated improved performance among watersheds with similar activation vectors, proving that utilizing information from other pre-trained watersheds enhances the prediction performance. This study compared the suitable models and training methods for each multi-purpose dam and highlighted the necessity of constructing deep learning models using PT and PT-FT methods for domestic watersheds. Furthermore, the results confirmed that the Transformer model outperforms the LSTM-MSV-S2S model when applying PT and PT-FT methods.

• Korean Journal of Food Science and Technology
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• v.48 no.2
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• pp.133-141
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• 2016

The physicochemical properties, antioxidant capacities, and sensory optimization of taro (Colocasia esculenta) under different aging conditions were investigated to develop black taro. Black taro was processed in three steps (steaming: $95{\pm}3^{\circ}C$ for 1 h; aging: 85, 90, $95^{\circ}C$ for 20, 40, and 60 h; drying: $60^{\circ}C$ for 24 h) and ground into a powder for all experiments. Black taro showed an increased crude fiber content and browning index compared to raw taro. Calcium oxalate contents, reducing sugar contents, moisture contents, and lightness values were decreased during the processing of taro. Improvements in total polyphenol content and antioxidant activity (DPPH, ABTS, FRAP) were observed in the black taro samples aged at higher temperature. Response surface methodology was used for sensory optimization, and the optimum aging conditions with the highest acceptance values were found to be $88.73^{\circ}C$ for 39.50 h for taste, and $88.82^{\circ}C$ for 42.60 h for overall acceptance.