• BMB Reports
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• v.55 no.6
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• pp.275-280
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• 2022

The treatment of atopic dermatitis (AD) is challenging due to its complex etiology. From epidermal disruption to chronic inflammation, various cells and inflammatory pathways contribute to the progression of AD. As with immunosuppressants, general inhibition of inflammatory pathways can be effective, but this approach is not suitable for long-term treatment due to its side effects. This study aimed to identify a plant extract (PE) with anti-inflammatory effects on multiple cell types involved in AD development and provide relevant mechanistic evidence. Degranulation was measured in RBL-2H3 cells to screen 30 PEs native to South Korea. To investigate the anti-inflammatory effects of Parasenecio auriculatus var. matsumurana Nakai extract (PAE) in AD, production of cytokines and nitric oxide, activation status of FcεRI and TLR4 signaling, cell-cell junction, and cell viability were evaluated using qRT-PCR, western blotting, confocal microscopy, Griess system, and an MTT assay in RBL-2H3, HEK293, RAW264.7, and HaCaT cells. For in vivo experiments, a DNCBinduced AD mouse model was constructed, and hematoxylin and eosin, periodic acid-Schiff, toluidine blue, and F4/80-staining were performed. The chemical constituents of PAE were analyzed by HPLC-MS. By measuring the anti-degranulation effects of 30 PEs in RBL-2H3 cells, we found that Paeonia lactiflora Pall., PA, and Rehmannia glutinosa (Gaertn.) Libosch. ex Steud. show an inhibitory activity of more than 50%. Of these, PAE most dramatically and consistently suppressed cytokine expression, including IL-4, IL-9, IL-13, and TNF-α. PAE potently inhibited FcεRI signaling, which mechanistically supports its basophil-stabilizing effects, and PAE downregulated cytokines and NO production in macrophages via perturbation of toll-like receptor signaling. Moreover, PAE suppressed cytokine production in keratinocytes and upregulated the expression of tight junction molecules ZO-1 and occludin. In a DNCB-induced AD mouse model, the topical application of PAE significantly improved atopic index scores, immune cell infiltration, cytokine expression, abnormal activation of signaling molecules in FcεRI and TLR signaling, and damaged skin structure compared with dexamethasone. The anti-inflammatory effect of PAE was mainly due to integerrimine. Our findings suggest that PAE could potently inhibit multi-inflammatory cells involved in AD development, synergistically block the propagation of inflammatory responses, and thus alleviate AD symptoms.

• Journal of the Korean GEO-environmental Society
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• v.23 no.3
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• pp.23-29
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• 2022

In this study, we investigated the ozone nanobubble process in which nanobubble and ultrasonic cavitation were applied simultaneously to improve the dissolution and self-decomposition of ozone. To confirm the organic decomposition efficiency of the process, a 200 mm × 200 mm × 300 mm scale reactor was designed and phenol decomposition experiments were conducted. The use of nanobubble was 2.07 times higher than the conventional ozone aeration in the 60 minutes reaction and effectively improved the dissolution efficiency of ozone. Ultrasonic irradiation increased phenol degradation by 36% with nanobubbles, and dissolved ozone concentration was lowered due to the promotion of ozone self-decomposition. The higher the ultrasonic power was, the higher the phenol degradation efficiency. The decomposition efficiency of phenol was the highest at 132 kHz. The ozone nanobubble process showed better decomposition efficiency at high pH like conventional ozone processes but achieved 100% decomposition of phenol after 60 minutes reaction even at neutral conditions. The effect by pH was less than that of the conventional ozone process because of self-decomposition promotion. To confirm the change in bubble properties by ultrasonic irradiation, a Zetasizer was used to measure the bubbles' size and zeta potential analysis. Ultrasonic irradiation reduced the average size of the bubbles by 11% and strengthened the negative charge of the bubble surface, positively affecting the gas transfer of the ozone nanobubble and the efficiency of the radical production.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.2
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• pp.285-298
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• 2022

This study is to investigate the effects and characteristics of science and engineering integrated lessons on elementary students' creative engineering problem solving propensity (CEPSP). The science and engineering integrated lessons used in this study was a 10 lesson-hours STEM program, co-developed by University of Minnesota and Purdue University. The program was implemented in the 6th grade science class of H Elementary School located in P Metropolitan city. The main data of this study are the pre-post CEPSP result and interview with 5 students collected before and after the research. The CEPSP result was analyzed by a paired-sample t-test and hierarchical cluster analysis. As a result of the t-test, it was found that overall, the program has a positive effect on the students' CEPSP score. As a result of cluster analysis, it was confirmed that studnets' CEPSP could be classified into two groups (lower and higher score cluster). Five students whose, CEPSP score has significantly improved after the lessons were interviewed to find out what the characteristics of the program that contribute the significant change are. As a result of conducting centroid analysis of the interview transcription and the hybrid analysis method, it was found that the meaningful experiences that the five students commonly shared were 'problem solving through collaboration' and 'through repeated experiments (redesign)', problem solving' and 'utilization of scientific knowledge'. As minor reactions, 'choice of the best experimental method' and 'difference between science and engineering' appeared.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1201-1208
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• 2022

In general, to maximize the supply and efficiency of floating offshore wind power generation energy, the motion caused by wave attenuation of the substructure must be reduced. According to previous studies, the motion response was reduced due to the vortex viscosity generated by the damping plate installed in the lower structure among the waves. In this study, a 5 MW semi-submersible OC5 platform and two platforms with attenuation plates were designed, and free decay experiments and numerical calculations were performed to confirm the effect of reducing motion due to vortex viscosity. As a result of the model test, when the heave free decay tests were conducted at drop heights of 30 mm, 40 mm, and 50 mm, compared with the OC5 platform, the platform with two types of damping plates attached had relatively improved motion damping performance. In the model test and numerical calculation results, the damping plate models, KSNU Plate 1 and KSNU Plate 2, were 1.1 times and 1.3 times lower than OC5, respectively, and the KSNU Plate 2 platform showed about two times better damping performance than OC5. This study shows that the area of the damping plate and the vortex viscosity are closely related to the damping rate of the heave motion.

• Journal of IKEEE
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• v.27 no.3
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• pp.345-349
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• 2023

In this paper, we propose a study on the development of deep learning structure for defective pixel detection of next-generation smart LED display board using imaging device. In this research, a technique utilizing imaging devices and deep learning is introduced to automatically detect defects in outdoor LED billboards. Through this approach, the effective management of LED billboards and the resolution of various errors and issues are aimed. The research process consists of three stages. Firstly, the planarized image data of the billboard is processed through calibration to completely remove the background and undergo necessary preprocessing to generate a training dataset. Secondly, the generated dataset is employed to train an object recognition network. This network is composed of a Backbone and a Head. The Backbone employs CSP-Darknet to extract feature maps, while the Head utilizes extracted feature maps as the basis for object detection. Throughout this process, the network is adjusted to align the Confidence score and Intersection over Union (IoU) error, sustaining continuous learning. In the third stage, the created model is employed to automatically detect defective pixels on actual outdoor LED billboards. The proposed method, applied in this paper, yielded results from accredited measurement experiments that achieved 100% detection of defective pixels on real LED billboards. This confirms the improved efficiency in managing and maintaining LED billboards. Such research findings are anticipated to bring about a revolutionary advancement in the management of LED billboards.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.5
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• pp.357-371
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• 2023

In cable tunnel construction using TBM, the vertical shaft is an essential structure for entrance and exit of TBM equipment and power lines. Since a shaft penetrates the ground vertically, it often encounters rock mass. Blasting or rock splitting methods, which are mainly used to the rock excavation, cause public complaints due to the noise, vibration and road occupation. Therefore, mechanical excavation using vertical shaft excavation machine are considered as an alternative to the conventional methods. However, at the current level of technology, the vertical excavation machine has limitation in its performance when applied for high strength rock with a compressive strength of more than 120 MPa. In this study, the potential utilization of waterjet technology as an excavation assistance method was investigated to improve mechanical excavation performance in the hard rock formations. Rock cutting experiments were conducted to verify the cutting performance of the abrasive waterjet. Based on the experimental result, it was found that ensuring excavation performance with respect to changing in ground conditions can be achieved by adjusting waterjet parameters such as standoff distance, traverse speed and water pressure. In addition, based on the relationship between excavation performance, uniaxial compressive strength and RQD, it was suggested that excavation performance could be improved by artificially creating joints using the abrasive waterjet. It is expected that these research results can be utilized as fundamental data for the introduction of vertical shaft excavation machines in the future.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.8 no.2
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• pp.53-61
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• 2022

This study aimed to increase the targeting ability against PSMA in cell therapy using metabolic glycoengineering and biorthogonal chemistry and to visualize cell trafficking using PET imaging. Cellular membranes of THP-1 cells were decorated with azide(-N₃) using Ac₄ManNAz by metabolic glycoengineering. Engineered THP-1 cells were conjugated with DBCO-bearing fluorophore (ADIBO-Cy5.5) for 1 h at different concentrations and analyzed by confocal fluorescence microscopy and flow cytometry. For PSAM ligand conjugation to THP-1 cells, Ac₄ManNAz treated THP-1 cells were incubated with DBCO-PSMA ligand (ADIBO-GUL) at a final concentration with 100 µM for 1 h. To evaluate the effect on cell recognition, PSMA ligand conjugated THP-1 cells(as effectors) were co-cultured with PSMA positive 22RV1 (as target cells) at 3 : 1 a effector-to-target cell (E/T) ratio. The interaction between THP-1 and 22RV1 was monitored by confocal fluorescence microscopy. For preparing the radiolabeled THP-1, the cells were treated at the activity of ~ 740 kBq of [⁸⁹Zr]Zr(oxinate)₄/5 × 10⁶ cells. Radiolabeled cells were analyzed for determination of cell-associated radioactivity by gamma counting and viability using MTS assay. In the cytotoxicity assay, THP-1 cells did not have any cytotoxicity even when the Ac₄ManNAz concentration was 100 µM. In confocal microscopy and flow cytometry, THP-1 cells were efficiently labeled ADIBO-Cy5.5 in a dose-dependent manner, and the dose of 100 µM was the optimal concentration for the following experiments. The clusters of PSMA ligand-conjugated THP-1 cells and 22RV1 cells were identified, indicating cell-cell recognition over the cell surface between two types of cells. Cell radiolabeling efficiency was 54.5 ± 17.8%. THP-1 labeled with 0.09 ± 0.03 Bq/cell showed no significant cytotoxicity compared to unlabeled THP-1 up to 7 days. We successfully demonstrated that Ac₄ManNAz treated cells were efficiently conjugated with ADIBO-GUL for preparing the PSMA-targeting cells, and [⁸⁹Zr]Zr(oxinate)₄ could be used to label cells without toxicity. It suggested that PSMA-ligand conjugated cell therapy could be improved cell targeting and be monitored by PET imaging.

• The Mathematical Education
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• v.62 no.3
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• pp.363-380
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• 2023

This study analyzed the difficulties and mathematical modeling knowledge improvement that an elementary school teacher experienced in modifying a mathematics textbook task to a mathematical modeling task. To this end, an elementary school teacher with 10 years of experience participated in teacher-researcher community's repeated discussions and modified the average task in the data and pattern domain of the 5th grade. The results are as followings. First, in the process of task modification, the teacher had difficulties in reflecting reality, setting the appropriate cognitive level of mathematical modeling tasks, and presenting detailed tasks according to the mathematical modeling process. Second, through repeated task modifications, the teacher was able to develop realistic tasks considering the mathematical content knowledge and students' cognitive level, set the cognitive level of the task by adjusting the complexity and openness of the task, and present detailed tasks through thought experiments on students' task-solving process, which shows that teachers' mathematical modeling knowledge, including the concept of mathematical modeling and the characteristics of the mathematical modeling task, has improved. The findings of this study suggest that, in terms of the mathematical modeling teacher education, it is necessary to provide teachers with opportunities to improve their mathematical modeling task development competency through textbook task modification rather than direct provision of mathematical modeling tasks, experience mathematical modeling theory and practice together, and participate in teacher-researcher communities.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.1
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• pp.71-78
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• 2023

The possibility of improving plating thickness distribution was investigated through quantitative consideration of bipolar electrodes without external power applied. By having the cathode tilted with respect to the anode, the potential distribution in the electrolyte solution adjacent to the cathode is different due to the difference in iR drop due to the path difference to the anode in each region of the cathode. The purpose of this study is to observe the bipolar characteristics in the case of an auxiliary anode for the non-uniform potential distribution of such a Hull cell. In particular, in order to evaluate the possibility of improving the non-uniform thickness distribution of the cathode by utilizing these bipolar characteristics, it was verified through experiments and simulations, and the electric potential and current density distribution around the bipolar electrode were analyzed. The electroplating in a Hull cell was performed for 75 min at a current density of 10 mA/cm², and the average thickness is about 16 ㎛. The standard deviation of the thickness was 10 ㎛ in the normal Hull cell without using the auxiliary anode, whereas it was 3.5 ㎛ in the case of using the auxiliary cathode. Simulation calculations also showed 8.9 ㎛ and 3.3 ㎛ for each condition, and it was found that the consistency between the experimental and simulation results was relatively high, and the thickness distribution could be improved through using the auxiliary anode by the bipolar phenomenon.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.159-172
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• 2023

In general, social problem-solving research aims to create important social value by offering meaningful answers to various social pending issues using scientific technologies. Not surprisingly, however, although numerous and extensive research attempts have been made to alleviate the social problems and issues in nation-wide, we still have many important social challenges and works to be done. In order to facilitate the entire process of the social problem-solving research and maximize its efficacy, it is vital to clearly identify and grasp the important and pressing problems to be focused upon. It is understandable for the problem discovery step to be drastically improved if current social issues can be automatically identified from existing R&D resources such as technical reports and articles. This paper introduces a comprehensive dataset which is essential to build a machine learning model for automatically detecting the social problems and solutions in various national research reports. Initially, we collected a total of 700 research reports regarding social problems and issues. Through intensive annotation process, we built totally 24,022 sentences each of which possesses its own category or label closely related to social problem-solving such as problems, purposes, solutions, effects and so on. Furthermore, we implemented four sentence classification models based on various neural language models and conducted a series of performance experiments using our dataset. As a result of the experiment, the model fine-tuned to the KLUE-BERT pre-trained language model showed the best performance with an accuracy of 75.853% and an F1 score of 63.503%.