기존에는 생산되는 키틴과 키토산의 대부분이 게, 새우등 갑각류 껍질에서 유래하였다. 하지만 어업에 의존하 는 기존 갑각류 비해 친환경적이며 품질 유지에 이점을 가지는 곤충으로부터 유래한 키틴이 최근 주목 받기 시작 하며 연구가 활발해지고 있다. 이에 키토산이 남조류의 응집을 통해 녹조 제거 효과를 가지며 기존에 녹조를 억제하기 위해 널리 사용되던 살조제들이 독성을 띠어 환경에 악영향을 미치는 문제를 해결할 수 있다는 연구를 참고하여 매미 탈피각으로부터 추출한 키토산을 녹조 방제에 활용해 보고자 하였다. 매미 탈피각으로부터 키토 산을 추출하고 대표적인 녹조 원인종인 Microcystis aeruginosa 배양 후 추출한 키토산을 처리하여 녹조의 응집 효과를 관찰하였다. 본 연구에서 새로운 키토산 추출 원으로서 매미 탈피각의 가능성을 제시하였으며 이를 녹조 방제에 활용함으로써 버려지는 자원인 매미 탈피각의 활용 방안을 제시하였다.

Background: The grading of Hanwoo (Korean native cattle) is based on four economic traits, and efforts have been continuously made to improve the genetic traits associated with these traits. There is a technology to predict the expected grade based on the 4 economic genetic SNP characteristics of Korean cattle calves using single nucleotide polymorphism (SNP) technology. Selection of highly proliferative, self-renewing, and differentiating satellite cells from cattle is a key technology in the cultured meat industry. Methods: We selected the Hanwoo with high and low-scored of genomic estimated breeding value (GEBV) by using the Hanwoo 50K SNP bead chip. We then isolated the bovine satellite cells from the chuck mass. We then conducted comparative analyses of cell proliferation, immunocytochemistry, qRT-PCR at short- and long-term culture. We also analyzed the differentiation capability at short term culture. Results: Our result showed that the proliferation was significantly high at High scored GEBV (Hs-GEBV) compared to Low scored GEBV (Ls-GEBV) at short- and long-term culture. The expression levels of Pax3 were significantly higher in Hs-GEBV bovine satellite cells at long-term culture. However, there were no significant differences in the expression levels of Pax7 between Hs- and Ls-GEBV bovine satellite cells at short- and long- term culture. The expression levels of MyoG and MyHC were significantly high at Ls-GEBV bovine satellite cells. Conclusions: Our results indicated that selection of bovine satellite cells by Hanwoo 50K SNP bead chip could be effective selection methods for massive producing of satellite cells.

This study was aimed to isolate bacterial inoculants producing chitinase and evaluate their application effects on corn silage. Four corn silages were collected from four beef cattle farms to serve as the sources of bacterial inoculants. All isolates were tested against Fusarium graminearum head blight fungus MHGNU F132 to confirm their antifungal effects. The enzyme activities (carboxylesterase and chitinase) were also measured to isolate the bacterial inoculant. Based on the activities of anti-head blight fungus, carboxylesterase, and chitinase, L. buchneri L11-1 and L. paracasei L9-3 were subjected to silage production. Corn forage (cv. Gwangpyeongok) was ensiled into a 10 L mini silo (5 kg) in quadruplication for 90 days. A 2 × 2 factorial design consists of F. graminearum contamination at 1.0104 cfu/g (UCT (no contamination) vs. CT (contamination)) and inoculant application at 2.1 × 105 cfu/g (CON (no inoculant) vs. INO (inoculant)) used in this study. After 90 days of ensiling, the contents of CP, NDF, and ADF increased (p<0.05) by F. graminearum contamination, while IVDMD, acetate, and aerobic stability decreased (p<0.05). Meanwhile, aerobic stability decreased (p<0.05) by inoculant application. There were interaction effects (p<0.05) on IVNDFD, NH3-N, LAB, and yeast, which were highest in UCT-INO, UCT-CON, CT-INO, and CT-CON & INO, respectively. In conclusion, this study found that mold contamination could negatively impact silage quality, but isolated inoculants had limited effects on IVNDFD and yeast.

This research examines the impact of visualizing virtual luxury products in the metaverse on consumers' perceptions of luxury products in the real world. We explore the metaverse as a marketing platform and investigate the relationship between the quality of visualization of virtual luxury products and consumers’ evaluations of real luxury products. The study hypothesizes that poor visualization quality of virtual luxury products will decrease the evaluation of authentic luxury goods, and this effect will be mediated by decreased perceived authenticity. Additionally, we predict that the negative effect will be mitigated by high-quality visualization.

Blockchain is an immutable ledger that records transactions and tracks assets using a common communication protocol. It stores a copy of the blockchain and implements a consensus function to verify transactions. Blockchain is applied to industries beyond finance, such as retail, to maintain security and transparency. Consumers with knowledge of blockchain technology are likely to be affected when evaluating products with blockchain embedded, impacting their product evaluation. The study investigates the impact of blockchain technology on consumers' product evaluation and how knowledge of blockchain and product quality moderate its effects.

We enjoy various forms of leisure every day. Human play culture continues to change according to the development of technology and social environment. In line with the changing society, humans experience socialization, and the market continues to change in response to human new ways of life.

This study investigates social media posts on Twitter concerning cryptocurrency marketing. We applied unsupervised Latent Dirichlet Allocation (LDA) topic modeling and sentiment analysis techniques to 98,716 tweets to examine the Twitter content for subjects and sentiments related to cryptocurrency. We discovered that tweets about cryptocurrency fell into four categories, with “cryptocurrency trading,” “NFT airdrop,” “cryptocurrency affiliate program,” and “Dogecoin on social media” being the most popular. Most of the topics had positive sentiments. Theoretical and practical implications for developing cryptocurrency marketing communication strategies are discussed.

APro, developed in KAERI for the process-based total system performance assessment (TSPA) of deep geological disposal systems, performs finite element method (FEM)-based multiphysics analysis. In the FEM-based analysis, the mesh element quality influences the numerical solution accuracy, memory requirement, and computation time. Therefore, an appropriate mesh structure should be constructed before the mesh stability analysis to achieve an accurate and efficient process-based TSPA. A generic reference case of DECOVALEX-2023 Task F, which has been proposed for simulating stationary groundwater flow and time-dependent conservative transport of two tracers, was used in this study for mesh stability analysis. The relative differences in tracer concentration varying mesh structures were determined by comparing with the results for the finest mesh structure. For calculation efficiency, the memory requirements and computation time were compared. Based on the mesh stability analysis, an approach based on adaptive mesh refinement was developed to resolve the error in the early stage of the simulation time-period. It was observed that the relative difference in the tracer concentration significantly decreased with high calculation efficiency.

Expanding exports of small and medium-sized companies is crucial for the continuous growth of the Korean economy. Therefore, the government operates various support systems to enhance the export capabilities of these companies. This study aims to analyze the impact of the Korean government's flagship export support system, known as the export initiation support system, on the performance of participating domestic companies. A fixed effect model using panel data was applied to examine the characteristics of 11,099 companies that participated in the export initiation support system from 2016 to 2019. The analysis revealed that the number of exporting countries, employees, and previous export volume had a significant impact on the export amount of participating companies. However, contrary to expectations, the number of overseas marketing participation and the GCL (global competence level) test did not show a significant impact. This study is significant as it provides implications for the development of support projects tailored to the specific needs of small and medium-sized companies, with the goal of improving the export support system.

This research proposes a novel approach to tackle the challenge of categorizing unstructured customer complaints in the automotive industry. The goal is to identify potential vehicle defects based on the findings of our algorithm, which can assist automakers in mitigating significant losses and reputational damage caused by mass claims. To achieve this goal, our model uses the Word2Vec method to analyze large volumes of unstructured customer complaint data from the National Highway Traffic Safety Administration (NHTSA). By developing a score dictionary for eight pre-selected criteria, our algorithm can efficiently categorize complaints and detect potential vehicle defects. By calculating the score of each complaint, our algorithm can identify patterns and correlations that can indicate potential defects in the vehicle. One of the key benefits of this approach is its ability to handle a large volume of unstructured data, which can be challenging for traditional methods. By using machine learning techniques, we can extract meaningful insights from customer complaints, which can help automakers prioritize and address potential defects before they become widespread issues. In conclusion, this research provides a promising approach to categorize unstructured customer complaints in the automotive industry and identify potential vehicle defects. By leveraging the power of machine learning, we can help automakers improve the quality of their products and enhance customer satisfaction. Further studies can build upon this approach to explore other potential applications and expand its scope to other industries.

본 연구는 좌우뇌의 활용 성향에 따라 다중지능이 어떻게 나타나는지, 모바일 웹사이트의 색채, 형태, 운동, 깊이 등의 지각 요소에 대한 반응의 차이가 어떻게 나타나는지 알아보고자 한다. 본 연구에 필요한 뇌 성향에 대한 데이터를 위하여 참여자를 모집하여 뇌 선호도 검사를 실시하였고, 이들의 다중지능을 확인하였다. 이들 을 뇌 성향별로 구분하고, 모바일 웹사이트의 지각 요소에 대해 선호도 조사를 하였고, 집단 간의 차이가 유 의미한지 확인하였다.

To improve the quality of jujube (Zizyphus jujuba Miller var. hoonensis), which is a fruit of health functional, the effect of polyphenol preparation treatment on the fruit characteristics of two cultivars (cv. Bokjo and cv. Sangwang) of jujube was investigated. There was no difference in the height and breast diameter of jujubes tested between the polyphenol treatments and non treatment. Jujube trees treated with polyphenol preparation produced significantly more fruit than untreated in both cultivars. In cvultivar of Bokjo, the polyphenol preparation treatment increased the fruit's fresh weight and dry weight more than two times, respectively, compared to the untreated treatment. Polyphenol preparation tr eatments also changed the leaf characteristics of jujube trees. In the polyphenol-treated trees, leaf thickness tended to be thickest at the top and thinnest at the bottom. Polyphenol preparation treated jujube trees showed no difference in chlorophyll content. Moisture content was slightly higher in the untreatment than in the treatments. Visually, the polyphenol preparation treatment had a dark green color. Jujubes treated with polyphenol preparations showed differences in polyphenol content in fruits. The polyphenol content in both peel and flesh of the treatments were much higher than that of the untreatment. Reducing sugar was contained more in the peel than in the flesh and was higher in the untreatment than in the polyphenol preparation treatments. Treatment with polyphenol preparation showed differences in fruit appearance. As described above, it was found that the treatment of polyphenol preparation changed the leaves, fruit shapes and components of jujube trees. In particular, jujubes treated with polyphenol preparations are expected to contribute significantly to eco-friendly and highly functional jujube cultivation, as they appear to produce many fruits and increase the content of polyphenols and sugars.