This study was conducted to determine the appropriate seeding dates by verifying the difference in winter survival and productivity of alfalfa according to fall sowing dates in the central area of South Korea. The experiment was conducted for 2 years (2020 and 2021) at the field in the Department of Animal Resources Development, NIAS located in Cheonan. Sowing dates started from September 18 to November 8 with 10 days of intervals during 2020 and 2021; SO1 (September 18), SO2 (September 28), SO3 (October 8), SO4 (October 18), SO5 (October 28), and SO6 (November 8). After sowing, the winter survival rate was measured in the spring of the following year, and the dry matter yield was measured by harvesting at 10% flowering and harvesting five times a year. SO6 failed to winter survival, and SO5 also had a lower winter survival rate than SO1~4 (p<0.05). The average annual dry matter yield of alfalfa linearly decreased with delaying sowing dates (p<0.05). The feed value did not differ in the same year by delaying the sowing date in the same year. These results suggest that sowing date should be started before October 18 to increase winter survival and productivity of alfalfa in the central area of South Korea.

This qualitative case study explores multilingual learners’ linguistic practices and how they are interrelated with their identities in the context of a Korean alternative school. The learners are two Chosunjok, and one North Korean refugee child. The data were derived from the learners’ digital storytelling videos, semi-structured interviews, stimulated-recall interviews, and observation field notes. The data were thematically analyzed and organized using Rose’s (2007) sites of visual meaning-making structure. The findings revealed that the learners had different amounts of access to information regarding second language learning, and that they depended on the resources available within the communities they belonged to. Moreover, the participants’ levels of investment in language learning were constructed around their communities and identities. Their attitudes in language learning were also interrelated with the broader English language ideologies in South Korea. By sharing the stories of three multilingual learners, the study provides pedagogical implications on the influence of resources on multilingual learners’ language learning. We emphasize the importance of providing a space for multilingual learners to critically reflect on current and future resources, utilize their full communicative repertoire, and identify ways to increase their affordances of learning.

The purpose of this study was to investigate preservice teachers’ understanding of democratic citizenship. This study utilized the democratic citizenship frame to assess 17 participants’ comprehension of this concept. The researcher designed a method course where participants in groups analyzed science activities to identify democratic citizenship components. Through the analysis of two science activities—one on energy and the other on climate change—and the development of science panels addressing various global issues, preservice teachers' understanding of democratic citizenship was enhanced. Preservice teachers showed a good understanding of critical thinking, communication and collaboration, and STS (science, technology, and society); and the most enhanced understanding of empathy, which was the least perceived in pre-survey, component of democratic citizenship. The democratic citizenship frame proved to be a valuable tool for teaching and learning this topic, particularly when applied to socioscientific issues in the classroom. More research-based revisions of the science curriculum are necessary, and more systematic practices with reflections are essential in teacher education.

Civil defense originally refers to the protection of civilians in the events of war-related disasters. Today, it encompasses a wide range of protection, rescue, and recovery activities not only aimed at minimizing the damage caused by war but also addressing natural and man-made disasters such as wildfires, typhoons, and floods. Civil defense uniforms are worn by volunteers who participate in civil defense training organized by practitioners, government officials, and military personnel. Therefore, more than 3,350,000 persons (+6.5 % of the Korean population) likely should wear civil defense uniforms. As such, the functionalities of civil defense uniforms need to be reexamined and improved in response to the wider and newer responsibilities of the civil defense system to protect the civil defense personnel from potential hazards and to help better serve the Korean citizens. The essential functions of civil defense uniforms were proposed by analyzing various civil defense activities. Per the level and type of safety hazards, the design and materials for civil defense uniforms should ideally differ, similar to civil defense uniforms in other countries. We surveyed the current Korean civil defense uniforms’ design, material compositions and important functionalities such as water repellency, water pressure resistance, and flame resistance. Compared to common functional workwear, we suggest room for improvement in the functional properties of civil defense uniforms. This research paves a new road for the functional design of civil defense uniforms to address a wider range of hazards, potentially leading to rational guidelines for protective workwear and government uniform development.

A typical consumer is exposed to more than 5,000 advertisements per day (Story 2015) by exposure to around 500 advertising messages before ending breakfast (Marshall, 2015), and it is impossible for consumers to remember most of the advertisement images and messages. Thus, one consistent yet not thoroughly investigated question for advertisers is how advertisers draw consumers' attention by differentiating their brand from competitors' brands. One suggestion from academia is making more "creative" advertising (Dahlén et al., 2008; Lehnert et al., 2014; Rosengren et al., 2013; Smith et al., 2008). However, it is still questionable the exact meaning of "advertising creativity," and the effects of creative advertising on consumer evaluation have not been fully investigated the effects of creativity in advertising evaluation by considering various boundary conditions. The objective of this research is to redefine advertising creativity, to understand how advertising creativity shapes consumers' evaluation, and how these effects are moderated by the different types of boundary conditions, such as industry category, by analyzing more than 100,000 advertising images and copies using a cutting-edge transfer learning technique. The results of the transfer learning algorithm indicate that both cognitive dimensions (e.g., novelty of image) and affective dimensions (e.g., awe and coolness) simultaneously affect the consumers' perception of the advertising creativity, and the current algorithm enables to detect of creative advertising image with 92% accuracy rate.

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.

In this article, we address this shortcoming by exploring the concept of AI-based sustainable service—an offering that embeds artificial intelligence in ways that meet the needs of current consumers by contributing to socio-economic equalities and conserving the natural environment.

Social media have emerged as one of the most important tools for firms to engage customers (e.g., Chandrasekaran et al., 2022; Cheng & Edwards, 2015; Lee et al., 2018; Wedel & Kannan, 2016). Within the tourism industry, scholars have investigated the role of social media communication in various contexts, such as online travel information search (Xiang & Gretzel, 2010), sharing travel experiences (So et al., 2018; Wang et al., 2022) and establishing positive customer relationships (Jamshidi et al., 2021). Insights into which social media content makes for generating positive engagement are, however, still largely based on marketers’ intuitions or focusing on message factors of social media posts such as message appeals (e.g., Wang & Lehto, 2020). It also often neglects the importance of the visual component of social media posts, and only a few research have investigated the effects of the image in social media on the travel industry (e.g., Fusté-Forné, 2022). The objective of this research is, therefore, to understand how textual features and image features generate user engagement in social media utilizing cutting-edge transfer learning techniques and to propose how these features should be customized to maximize user engagement for online travel shopping companies. We collect and analyze more than 10,000 Instagram posts from three online travel shopping companies, including Expedia, Priceline, and Kayak. The results from transfer learning algorithms utilizing 24 features, such as the number of people in the image, emotions expressed in the people in the image, hue, and RGB value, successfully predict the level of engagement measured by the number of likes and comments.

From the past to the present, we are living in an age of social comparison. Above all, upward social comparison to those who are superior in terms of their social and economic status makes individuals feel psychologically deficient and threatened. As a result, individuals oftentimes exhibit compensatory consumption to relieve their unfulfilled desires such as stress, disappointment, and self-esteem deficiency by purchasing high-end products or brands (Mandel, Petrova, & Cialdini, 2006; Pettit & Sivanathan, 2011).

For the commercialization of hydrogen energy, a technology enabling safe storage and the transport of large amounts of hydrogen is needed. Porous materials are attracting attention as hydrogen storage material; however, their gravimetric hydrogen storage capacity (GHSC) at room temperature (RT) is insufficient for actual use. In an effort to overcome this limitation, we present a N-doped microporous carbon that contains large proportion of micropores with diameters below 1 nm and small amounts of N elements imparted by the nitrogen plasma treatment. The N-doped microporous carbon exhibits the highest total GHSC (1.59 wt%) at RT, and we compare the hydrogen storage capacities of our sample with those of metal alloys, showing their advantages and disadvantages as hydrogen storage materials.

While metadiscourse use has been well-attended in second language (L2) writing research, relatively less effort has been made in documenting changing patterns of metadiscourse use among L2 writers. The present study addressed this gap by probing a diachronic change of interactive metadiscourse in research articles published in English Teaching across a span of 40 years. Using the corpus of 931 articles written by Korean L2 writers, we examined whether, and to what extent, interactive metadiscourse use in academic writing had changed over time. Our findings revealed an overall increase in the frequency of interactive resources mainly driven by a significant increase of evidentials. The observed pattern of change in interactives suggests that academic discourse within the applied linguistics community in Korea is becoming more persuasive and reader-oriented over time, consistent with Hyland and Jiang (2018) who reported a dramatic rise in interactive metadiscourse in the global discourse community of applied linguistics.

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.

The Animal and Plant Quarantine Agency conducts a targeted sampling plan and analysis for veterinary drugs within the country every year. Target compounds included tetrachlorvinphos as an organophosphate, diminazene as an anti-infective medication, ketoprofen as a nonsteroidal anti-inflammatory drug, triclabendazole and clorsulon as flukicides in 2022. These compounds were not included in National Residues Program (NRP), despite their high sales ranking. A total of 94 bovine muscle samples and 20 equine muscle samples were collected from various locations across the country. The analysis of target compounds in muscle was performed using LC-MS/MS coupled with Food code 8.3.1 revised in 2022. A 2 g sample of muscle tissue was extracted using a water: acetonitrile (1:4, v/v) solution, then cleaned up with C18 and hexane saturated with acetonitrile. Compounds were separated with C18 column and mobile phases consisted of 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B). All analytes exhibited good linearity with correlation coefficients (R2) higher than 0.992. The limit of quantification (LOQ) of these compounds ranged from 0.21 to 2.79 μg/kg except for diminazene (3.85~6.86 μg/kg). The average recoveries of these analytes were 89.45~129.13% in muscle at spiked level of 10 or 20 μg/kg. Relative standard deviations (%) (intra-day and inter-day) were lower than 20% for all target compounds, except for diminazene and triclabendazole, whose intra-day RSD % was slightly higher than 20% in equine muscle. Testing confirmed that all 94 bovine and 20 equine muscle samples from 9 provinces were free from residues of veterinary drugs. Monitoring of compounds not included in the NRP should continue to ensure consumer health and food safety.

Babesiosis is a tick-borne disease caused by intraerythrocytic protozoa. Despite the increasing acknowledgement that babesiosis represents a threat to animal and human health, to date there have been few studies focusing on the disease in the Republic of Korea (ROK). In the present study, we report a Babesia capreoli infection in an Ixodes nipponensis tick obtained from a Korean water deer (Hydropotes inermis argyropus). The tick was identified with polymerase chain reaction analysis as I. nipponensis (Japanese hard tick). A phylogenetic analysis based on the 18S rRNA gene sequences revealed that the isolate found in I. nipponensis belonged to the B. capreoli lineage and was distinct from the Asian, European, and North American lineages of Babesia divergens. Although our isolate belonged to the B. capreoli lineage it did not form a cluster with others isolates in the same lineage; this may be due to differences in the tick species that transmit B. capreoli or in the host species. We were unable to identify the reservoir host for our case of B. capreoli transmission, though regional ticks may be the primary vector. This study confirms the presence of B. capreoli in the ROK, and its presence suggests that further study is warranted to determine its prevalence and pathogenicity in wild and domesticated animals.

Macrophages secrete various cytokines and inflammatory mediators, resulting in playing critical roles in inflammation and immunity. In this study, we investigated anti-inflammatory and immune enhancing properties of PB203, which is a water-soluble extract powder from the fruit of Actinidia polygama, in macrophages. A. polygama is a medicinal plant traditionally known to treat abdominal pain, stroke and rheumatoid arthritis. However, the molecular mechanism for the immune modulation of PB203 is still unclear. Therefore, we assessed the effects of PB203 on the lipopolysaccharide (LPS)-induced inflammation and immune activation, and elucidated its action mechanism in mouse macrophage, RAW264.7 cells. PB203 significantly suppressed not only the levels of nitric oxide (NO), prostaglandin E2, tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β), but also the mRNA expression of inducible NO synthase, cyclooxygenase-2, TNF-α and IL-1β in LPS-stimulated RAW264.7 cells. We also found that these anti-inflammatory activities of PB203 were mediated through the inhibition of toll-like receptor 4 and nuclear factor kappa B (NF-κB) induced by LPS. On the other hand, in normal macrophages, PB203 dose-dependently elevated the gene expression of immunomodulators including granulocyte-macrophage colony-stimulating factor, granulocyte colony-stimulating factor, monocyte chemoattractant protein-1 and TNF-α in a statistically significant manner. The expression of IL-10, IL-1β, IL-6, and interferon-γ were also remarkably upregulated by the treatment of 500 μg/mL PB203. In addition, PB203-mediated production of NO and TNF-α was attenuated by NF-κB inhibition in RAW264.7 cells. Interestingly, PB203 promoted the production of nuclear factor erythroid-2-related factor 2, resulting in the increased level of heme oxygenase-1, which is a representative antioxidant enzyme, in both LPS-stimulated and normal RAW264.7 cells. Taken all together, these results suggest that PB203 may have great potential as the candidate of anti-inflammatory agent for improving inflammatory diseases or immune enhancing agent for preventing infectious diseases. Keywords: Actinidia polygama extract (PB203); macrophages; immunomodulator; nuclear factor kappa B (NF-κB); heme oxygenase-1 (HO-1)

본 연구는 간 담도기 이미지에서 CAIPIRINHA, 압축 센싱(CS), 딥러닝(DL) 기법을 비교하여 주관적 영상의 질과 국소병변 을 평가하였다. 후향적 연구로 간 담도기 이미지를(획득 시간, CAIPIRINHA 16초, DL 11초, CS 15초; 절편두께, 3mm, 3mm, 1.5mm) 포함한 가도세틱산 조영증강 자기공명영상을 시행한 51명의 환자에서 3개의 이미지와 국소 간 병변은 주관적 이미지 질 평가를 분석하였다. 간 가장자리 선명도는 CAIPIRINHA(3.9±0.8), DL(4.5±0.6), CS(4.5±0.8), 호흡에 의한 운동 허상은 CAIPIRINHA(4.3±0.9), DL(4.7±0.6), CS(4.5±0.8)를 보였다. 21명 환자의 48개 병변에서, 가장자리 선예 도는 CAIPIRINHA(4.3±0.7), DL(4.5±0.6), CS(4.6±0.5), 선명도는 CAIPIRINHA(4.4±0.7), DL(4.7±0.5), CS (4.7±0.5)을 보였다. DL은 검사 시간을 줄이면서 CAIPIRINHA와 비슷한 질을 보이고 호흡 허상을 줄일 수 있다. CS는 얇은 절편 영상의 획득이 가능하여 비슷한 영상의 질을 보여 선택적으로 유용하게 사용할 수 있다.

한자는 특유의 고유성을 지닌 문자언어의 또 다른 형식이며, 인류 문명사의 중 요한 자산 중 하나이다. 그럼에도 표음문자 중심의 시각에서는 한자가 전근대적인 문자 로 폄훼되는 경우들이 많았다. 본서는 바로 이러한 인식의 전환의 필요성과 함께, 한자가 가진 형체-의미 간 통합성에 따른 문화적 보고로서의 가치와 의의를 인식해야 함을 강조 하고 있다. 저자는 이와 같은 주장을 뒷받침하기 위해 다양한 한자들의 형체와 의미를 분 석하였고, 이 형체-의미 간의 연관성을 입증하기 위해 방대한 문자·문헌·문화 자료들을 활용하였다. 저자는 또한 한자의 고유성과 가치에 대한 인식이 동양의 가치와 위상을 바 로잡을 수 있는 첫걸음이며, 또한 이러한 인식의 확장은 인류 문명사를 통합적 관점에서 바라볼 수 있는 중요한 계기를 마련할 수 있음을 역설하고 있다.