Ahn, Hee Ju;Kang, Kyung Soo;Song, Yun Ha;Lee, Da Hae;Kim, Mun Ho;Lee, Jae Kyoung;Woo, Hee Chul
Clean Technology
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v.28
no.1
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pp.24-31
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2022
Petroleum-based plastics are used for various purposes and pose a significant threat to the earth's environment and ecosystem. Many efforts have been taken globally in different areas to find alternatives. As part of these efforts, this study manufactured alginate-based polyvinyl alcohol (PVA) blended films by casting from an aqueous solution prepared by mixing 10 wt% petroleum-based PVA with biodegradable, marine biomass-derived alginate. Glutaraldehyde was used as a cross-linking agent, and cardanol, an alkyl phenol-based bio-oil extracted from cashew nut shell, was added in the range of 0.1 to 2.0 wt% to grant antibacterial activity to the films. FTIR and TGA were performed to characterize the manufactured blended films, and the tensile strength, degree of swelling, and antibacterial activity were measured. Results obtained from the FTIR, TGA, and tensile strength test showed that alginate, the main component, was well distributed in the PVA by forming a matrix phase. The brittleness of alginate, a known weakness as a single component, and the low thermal durability of PVA were improved by cross-linking and hydrogen bonding of the functional groups between alginate and PVA. Addition of cardanol to the alginate-based PVA blend significantly improved the antibacterial activity against S. aureus and E. coli. The antibacterial performance was excellent with a death rate of 98% or higher for S. aureus and about 70% for E. coli at a contact time of 60 minutes. The optimal antibacterial activity of the alginate-PVA blended films was found with a cardanol content range between 0.1 to 0.5 wt%. These results show that cardanol-containing alginate-PVA blended films are suitable for use as various antibacterial materials, including as food packaging.
The purpose of this study was to confirm the dissolution of arsenic from the stabilized soil around abandoned coal mines by cultivation activities. Experimental soils were collected from the agricultural field around Okdong and Buguk coal mines, and the concentration of arsenic in the soil and the geochemical mobility were confirmed. The average arsenic concentration was 20 mg/kg. The soil with relatively high geochemical mobility of arsenic in the soil was used in the batch and column experiment. The limestone was mixed with soil for soil stabilization, and the mixing ratio was 3% of limestone, based on the soil weight. The phosphoric acid fertilizer (NH4H2PO4) was added to the soil to simulate a cultivation condition according to the Rural Development Administration's rules. Comparative soil without mixing limestone was prepared and used as a control group. The arsenic extraction from soil was increased following the fertilizer mixing amount and it shows a positive relationship. The concentration of phosphate in the supernatant was relatively low under the condition of mixing limestone, which is determined to be result of binding precipitation of phosphate ions and calcium ions dissolved in limestone. Columns were set to mix phosphoric acid fertilizers and limestone corresponding to cultivation and stabilization conditions, and then the column test was conducted. The variations of arsenic extraction from the soil indicated that the stabilization was effectible until 10 P.V.; however, the stabilization effect of limestone decreased with time. Moreover, the geochemical mobility of arsenic has transformed by increasing the mobile fractions in soil compared to initial soil. Therefore, based on the arsenic extraction results, the cultivation activities using phosphoric fertilizer could induce a decrease in the stabilization effect.
Lee, So Min;Jung, So Young;Brito, Sofia;Heo, Hyojin;Cha, Byungsun;Lei, Lei;Lee, Sang Hun;Lee, Mi-Gi;Bin, Bum-Ho;Kwak, Byeong-Mun
Journal of the Society of Cosmetic Scientists of Korea
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v.48
no.3
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pp.189-196
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2022
Plasma refers to an ionized gas that is often referred to as "the fourth phase of matter", following solid, liquid, and gas. Plasma has traditionally been utilized for industrial applications such as welding and neon signs, but its promise in biomedical fields such as cancer treatment and dermatology has lately been recognized. Indeed, due to its beneficial effects in promoting collagen production, improving skin tone, and eliminating harmful bacteria in the skin, plasma treatment constitutes an important target for dermatological research. In this study, a plasma device for cosmetic manufacturing based on nitrogen, the main component of the atmosphere, was designed and assembled. Moreover, nitric oxide (NO) was selected since is easier to follow and evaluate than other nitrogen plasma active species, and its contents were measured to perform a quantitative and qualitative evaluation of plasma. First, an injection method, using different proximities labeled "sinking" and "non sinking" treatments, was performed to test the most efficient plasma treatment method. As a result, it was observed that the formulation obtained by a non sinking treatment was more effective. Furthermore, toner and ampoule were selected as cosmetics formulations, and the characteristics of the formulation and changes in the injected plasma state were observed. In both formulations, the successful injection of NO plasma was 2 times higher in toner formulation than ampoule formulation, and it gradually decreased with time, having dissipated after a week. It was confirmed that the nitrogen plasma used did not affect the stability of the toner and ampoule formulations at low temperature (4 ℃), room temperature (25 ℃), and high temperature (37 ℃ and 50 ℃) conditions. The results of this study demonstrate the potential of plasma cosmetics and highlight the importance of securing the stability of the injected plasma.
Lee, Jun Oh;Lee, Geun Dong;Kim, Hyeong Ryul;Kim, Dong Kwan;Park, Seung-Il;Cho, Jong Ho;Kim, Hong Kwan;Choi, Yong Soo;Kim, Jhingook;Shim, Young Mog;Park, Samina;Park, In Kyu;Kang, Chang Hyun;Kim, Young Tae;Park, Seong Yong;Lee, Chang Young;Lee, Jin Gu;Kim, Dae Joon;Paik, Hyo Chae;the Korean Association for Research on the Thymus,
Journal of Chest Surgery
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v.55
no.2
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pp.126-142
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2022
Background: Thymic epithelial tumors (TETs) are rare, and information regarding their surgical outcomes and prognostic factors has rapidly changed in the past few decades. We analyzed surgical treatment practices for TETs and outcomes in terms of overall survival (OS) and freedom from recurrence (FFR) during a 13-year period in Korea. Methods: In total, 1,298 patients with surgically resected TETs between 2000 and 2013 were enrolled retrospectively. OS and FFR were calculated using the Kaplan-Meier method and evaluated with the log-rank test. Prognostic factors for OS and FFR were analyzed with multivariable Cox regression. Results: A total of 1,098 patients were diagnosed with thymoma, and 200 patients were diagnosed with thymic carcinoma. Over the study period, the total number of patients with surgically treated TETs and the proportion of patients who underwent minimally invasive thymic surgery (MITS) increased annually. The 5-year and 10-year survival rates of surgically treated TETs were 91.0% and 82.1%, respectively. The 5-year and 10-year recurrence rates were 86.3% and 80.0%, respectively. The outcomes of surgically treated TETs improved over time. Multivariable Cox hazards analysis for OS, age, tumor size, and Masaoka-Koga stage were independent predictors of prognosis. The World Health Organization classification and tumor-node-metastasis (TNM) staging were also related to the prognosis of TETs. Conclusion: Surgical treatment of TETs achieved a good prognosis with a recent increase in MITS. The M-K stage was the most important prognostic factor for OS and FFR. The new TNM stage could also be an effective predictor of the outcomes of TETs.
Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.
According to media reports, the carcasses of euthanized abandoned dogs were processed at high temperature and pressure to make powder, and then used as feed materials (meat and bone meal), raising the possibility of residuals in the feed of the anesthetic ketamine and dexmedetomidine used for euthanasia. Therefore, a simultaneous analysis method using QuEChERS combined with high-performance liquid chromatography coupled with electrospray ionization tandem mass spectrometry was developed for rapid residue analysis. The method developed in this study exhibited linearity of 0.999 and higher. Selectivity was evaluated by analyzing blank and spiked samples at the limit of quantification. The MRM chromatograms of blank samples were compared with those of spiked samples with the analyte, and there were no interferences at the respective retention times of ketamine and dexmedetomidine. The detection and quantitation limits of the instrument were 0.6 ㎍/L and 2 ㎍/L, respectively. The limit of quantitation for the method was 10 ㎍/kg. The results of the recovery test on meat and bone meal, meat meal, and pet food showed ketamine in the range of 80.48-98.63 % with less than 5.00 % RSD, and dexmedetomidine in the range of 72.75-93.00 % with less than 4.83 % RSD. As a result of collecting and analyzing six feeds, such as meat and bone meal, prepared at the time the raw material was distributed, 10.8 ㎍/kg of ketamine was detected in one sample of meat and bone meal, while dexmedetomidine was found to have a concentration below the limit of quantitation. It was confirmed that the detected sample was distributed before the safety issue was known, and thereafter, all the meat and bone meal made with the carcasses of euthanized abandoned dogs was recalled and completely discarded. To ensure the safety of the meat and bone meal, 32 samples of the meat and bone meal as well as compound feed were collected, and additional residue investigations were conducted for ketamine and dexmedetomidine. As a result of the analysis, no component was detected. However, through this investigation, it was confirmed that some animal drugs, such as anesthetics, can remain without decomposition even at high temperature and pressure; therefore, there is a need for further investigation of other potentially hazardous substances not controlled in the feed.
Journal of the Society of Cosmetic Scientists of Korea
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v.48
no.4
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pp.365-372
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2022
Cellobiose is a dissacharide constituted by two glucose units joined by a β-('1,4') glycosidic bond that is produced by the decomposition of cellulose. This product exists naturally in plants and has been utilized in different industries as a food sweetener, and as a cosmetic and pharmaceutical material. In this study, the potential of cellobiose as a whitening cosmetic product was evaluated by analyzing autophagy induction and the inhibition of melanin production. A cytotoxicity test conducted in the human melanin-producing cell line MNT-1 with increasing concentrations of cellobiose revealed that this compound did not cause cytotoxicity at 20 mg/mL or less. Based on this, autophagy was firstly evaluated by immunostaining with the autophagy marker microtubule-associated protein 1 light chain 3 (LC3) after treatment with 20 mg/mL of cellobiose. The subsequent confocal microscopy analysis revealed an increase in LC3 puncta, indicating induction of autophagy. In addition, autophagy was further confirmed by western blot analysis, which demonstrated that cellobiose converted LC3-I to LC3- ∏ in a concentration- and time-dependent manners. An analysis of melanin contents after cellobiose treatment at a concentration of 20 mg/mL during 7 days revealed that melanin production was reduced by more than 50%. Additionally, the expression levels of melanogenesis-related proteins TYR and TYRP1 were markedly decreased after cellobiose treatment. Based on these studies, a cosmetic cream formulation containing cellobiose was prepared and the change in formulation was tested for 4 weeks, and it was confirmed that the appearance changed to liquid form at high temperature, but the pH did not change. In conclusion, the present research demonstrated that cellobiose activates autophagy and inhibits melanin production, and showed the potential of this product as a material for whitening cosmetics.
Due to river maintenance projects such as the creation of hydrophilic areas around rivers and the Four Rivers Project, the flow characteristics of rivers are continuously changing, and the risk of water quality accidents due to the inflow of various pollutants is increasing. In the event of a water quality accident, it is necessary to minimize the effect on the downstream side by predicting the concentration and arrival time of pollutants in consideration of the flow characteristics of the river. In order to track the behavior of these pollutants, it is necessary to calculate the diffusion coefficient and dispersion coefficient for each section of the river. Among them, the dispersion coefficient is used to analyze the diffusion range of soluble pollutants. Existing experimental research cases for tracking the behavior of pollutants require a lot of manpower and cost, and it is difficult to obtain spatially high-resolution data due to limited equipment operation. Recently, research on tracking contaminants using RGB drones has been conducted, but RGB images also have a limitation in that spectral information is limitedly collected. In this study, to supplement the limitations of existing studies, a hyperspectral sensor was mounted on a remote sensing platform using a drone to collect temporally and spatially higher-resolution data than conventional contact measurement. Using the collected spatio-temporal hyperspectral images, the tracer concentration was calculated and the transverse dispersion coefficient was derived. It is expected that by overcoming the limitations of the drone platform through future research and upgrading the dispersion coefficient calculation technology, it will be possible to detect various pollutants leaking into the water system, and to detect changes in various water quality items and river factors.
Purpose: This study aims is to provide a total care solution preventing disaster based on Big Data and AI technology and to service safety considered by individual situations and various risk characteristics. The purpose is to suggest a method that customized comprehensive index services to prevent and respond to safety accidents for calculating the living safety index that quantitatively represent individual safety levels in relation to daily life safety. Method: In this study, we use method of mixing AHP(Analysis Hierarchy Process) and Likert Scale that extracted from consensus formation model of the expert group. We organize evaluation items that can evaluate life safety prevention services into risk indicators, vulnerability indicators, and prevention indicators. And We made up AHP hierarchical structure according to the AHP decision methodology and proposed a method to calculate relative weights between evaluation criteria through pairwise comparison of each level item. In addition, in consideration of the expansion of life safety prevention services in the future, the Likert scale is used instead of the AHP pair comparison and the weights between individual services are calculated. Result: We obtain result that is weights for life safety prevention services and reflected them in the individual risk index calculated through the artificial intelligence prediction model of life safety prevention services, so the comprehensive index was calculated. Conclusion: In order to apply the implemented model, a test environment consisting of a life safety prevention service app and platform was built, and the efficacy of the function was evaluated based on the user scenario. Through this, the life safety index presented in this study was confirmed to support the golden time for diagnosis, response and prevention of safety risks by comprehensively indication the user's current safety level.
The current performance evaluation of slope anchors qualitatively determines the physical bonding between the anchor head and ground as well as cracks or breakage of the anchor head. However, such performance evaluation does not measure these primary factors quantitatively. Therefore, the time-dependent management of the anchors is almost impossible. This study is an evaluation of the 3D numerical model by SfM which combines UAS images with terrestrial LiDAR to collect numerical data on the damage factors. It also utilizes the data for the quantitative maintenance of the anchor system once it is installed on slopes. The UAS 3D model, which often shows relatively low precision in the z-coordinate for vertical objects such as slopes, is combined with terrestrial LiDAR scan data to improve the accuracy of the z-coordinate measurement. After validating the system, a field test is conducted with ten anchors installed on a slope with arbitrarily damaged heads. The damages (such as cracks, breakages, and rotational displacements) are detected and numerically evaluated through the orthogonal projection of the measurement system. The results show that the introduced system at the resolution of 8K can detect cracks less than 0.3 mm in any aperture with an error range of 0.05 mm. Also, the system can successfully detect the volume of the damaged part, showing that the maximum damage area of the anchor head was within 3% of the original design guideline. Originally, the ground adhesion to the anchor head, where the z-coordinate is highly relevant, was almost impossible to measure with the UAS 3D numerical model alone because of its blind spots. However, by applying the combined system, elevation differences between the anchor bottom and the irregular ground surface was identified so that the average value at 20 various locations was calculated for the ground adhesion. Additionally, rotation angle and displacement of the anchor head less than 1" were detected. From the observations, the validity of the 3D numerical model can obtain quantitative data on anchor damage. Such data collection can potentially create a database that could be used as a fundamental resource for quantitative anchor damage evaluation in the future.
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