Periodontal disease has been implicated in the progression of various systemic diseases, including chronic kidney disease (CKD). Recent evidence suggests that infection of Porphyromonas gingivalis , a major periodontal pathogen, may also contribute to vascular calcification in patients with CKD. In the present study, antibody array analysis of serum samples from CKD mice administered with oral P. gingivalis revealed significant alterations in protein expression profiles, with notable interleukin-7 (IL-7) upregulation. We demonstrated that P. gingivalis infection enhances the inorganic phosphate-induced calcification of vascular smooth muscle cells (VSMCs), a pathological process that is characteristically accelerated in CKD. Notably, IL-7 expression was significantly upregulated in the P. gingivalis -stimulated calcification of VSMCs. Moreover, IL-7 knockdown in VSMCs markedly attenuated the P. gingivalis -stimulated calcification of VSMCs and suppressed the expression of osteogenic markers, including alkaline phosphatase and Runt-related transcription factor 2. These findings suggest that IL-7 plays a crucial role in P. gingivalis -stimulated vascular calcification, potentially providing new therapeutic targets for preventing vascular calcification in CKD patients with periodontal infection.

The oral microbiome plays a vital role in maintaining oral and overall health and affects immune responses, digestion, and pathogen suppression. While most studies focus on age groups prone to specific conditions, such as dental caries in children or periodontal disease in older adults, limited data exist on preschool-aged children and young adults. This study investigates the composition and diversity of the oral microbiome between these age groups for enhanced understanding of a healthy oral microbiome. Microbial samples from the supragingival regions of 41 children and 31 young adults in Korea were analyzed using 16S rRNA gene sequencing. Alpha and beta diversity were assessed, and linear discriminant analysis effect size (LEfSe) identified taxa with significant differences in abundance between the groups. No significant differences in alpha diversity were observed between children and young adults however, beta diversity analysis revealed notably compositional differences. At the phylum level, Firmicutes were more abundant in children, whereas Actinobacteria were more prevalent in young adults. Genera such as Veillonella and Lautropia were more abundant among children, whereas Haemophilus and Rothia were more common among young adults. LEfSe analysis identified Veillonella rogosae and Lautropia mirabilis as more abundant in children, whereas Haemophilus parainfluenzae and Rothia dentocariosa were more prevalent in young adults. The observed differences suggest that children’s microbiomes are associated with biofilm development, while young adults’ microbiomes involve biofilm maturation and immune modulation. These findings highlight the age-related shift in oral microbiome composition, emphasizing the importance of monitoring these changes to support long-term oral health.

Endoplasmic reticulum (ER) stress, caused by the accumulation of misfolded or unfolded proteins, activates the unfolded protein response to maintain cellular homeostasis and is implicated in bacterial infections. This study investigated ER stress activation in THP-1-derived macrophages infected with oral bacteria Porphyromonas gingivalis , Prevotella intermedia , Aggregatibacter actinomycetemcomitans , and Streptococcus oralis at an multiplicity of infection of 50 for 4 hours. mRNA and protein expressions related to ER stress were analyzed by real-time polymerase chain reaction and Western blot, while pro-inflammatory cytokines were measured using enzymelinked immunosorbent assay. P. gingivalis induced the highest mRNA expression of XBP1 and PERK, whereas A. actinomycetemcomitans showed elevated GRP78, ATF6, IRE1α, ATF4, and CHOP. P. intermedia strongly expressed PERK, while S. oralis showed higher GRP78, PERK, ATF4, and CHOP expression. Protein analysis revealed S. oralis had the highest phosphorylation levels of eIF2α and IRE1α, while CHOP was most highly expressed in P. intermedia . Pro-inflammatory cytokine expression showed P. intermedia and P. gingivalis elicited the most TNF-α, while P. gingivalis induced the highest IL-1β levels. These findings suggest oral bacteria induce varying levels of ER stress, influencing the progression of oral infectious diseases. Targeting ER stress could offer therapeutic potential for managing inflammatory conditions like periodontitis.

Micro display technology has become a key element of digital innovation, gaining attention with immersive technologies like AR/VR, and advancing in fields such as education, military, and healthcare. This study aims to analyze micro display technology trends, which are increasingly important across industries, and to provide insights that help companies develop strategies for related technologies. Using the patent database, BERTopic, a recent topic modeling technique, was applied to identify key themes in micro display technology development. Time-series analysis was also conducted to examine changes in research trends over time. These findings are expected to guide companies and research institutions in setting future technology development directions and strategies.

In 2024, the South Korean government’s research and development budget cuts sparked significant concerns in the scientific community, prompting increased interest in international research funding opportunities. In this regard, South Korea’s upcoming participation as an Associated Country in the European Union’s (EU’s) Horizon Europe offers a timely opportunity. Horizon Europe is the EU’s flagship research and innovation program, running from 2021 to 2027 with a budget of €95.5 billion. It is structured on three key pillars: 1) excellent science; 2) global challenges and European industrial competitiveness; and 3) innovative Europe. South Korea’s direct benefits will focus on Pillar II, which emphasizes global challenges across six clusters, including health, climate, and digital innovation. It should be noted that participation in the program mandates international collaborations, typically involving consortia with diverse expertise. Meanwhile, the National Contact Points network has been expanded to support Korean researchers, offering the necessary resources to facilitate engagement with EU counterparts. By leveraging these opportunities, South Korean researchers aim to collaboratively address global challenges, thus enhancing the nation’s scientific standing.

This study reviewed Chinese primary school writing curriculum from 1902 to 2022 to reflect on its strengths and weaknesses. The review came to the following conclusions: 1) The teaching of writing should be done independently from general Chinese language education; 2) Teaching objectives should not be limited to skills training but should also include emotional literacy; 3) Teaching methods should be connected to the mental and physical developmental stage of students; 4) The teaching process should not be random, but should be standardized, and; 5) Evaluation of teaching should be measured on an objective and detailed evaluation scale.

This study analyzes the impact of ESG (Environmental, Social, and Governance) activities on Corporate Financial Performance(CFP) using machine learning techniques. To address the linear limitations of traditional multiple regression analysis, the study employs AutoML (Automated Machine Learning) to capture the nonlinear relationships between ESG activities and CFP. The dataset consists of 635 companies listed on KOSPI and KOSDAQ from 2013 to 2021, with Tobin's Q used as the dependent variable representing CFP. The results show that machine learning models outperformed traditional regression models in predicting firm value. In particular, the Extreme Gradient Boosting (XGBoost) model exhibited the best predictive performance. Among ESG activities, the Social (S) indicator had a positive effect on CFP, suggesting that corporate social responsibility enhances corporate reputation and trust, leading to long-term positive outcomes. In contrast, the Environmental (E) and Governance (G) indicators had negative effects in the short term, likely due to factors such as the initial costs associated with environmental investments or governance improvements. Using the SHAP (Shapley Additive exPlanations) technique to evaluate the importance of each variable, it was found that Return on Assets (ROA), firm size (SIZE), and foreign ownership (FOR) were key factors influencing CFP. ROA and foreign ownership had positive effects on firm value, while major shareholder ownership (MASR) showed a negative impact. This study differentiates itself from previous research by analyzing the nonlinear effects of ESG activities on CFP and presents a more accurate and interpretable prediction model by incorporating machine learning and XAI (Explainable AI) techniques.

이 연구의 목적은 척추 자기공명영상 검사 시 기존의 포화 펄스와 함께 호흡 유도하(respiratory triggering, RTr) 기법을 적용하는 것이 영상화질 개선에 있어 효과적인지를 평가해 보기 위함이다. 이에 본 연구는 2024년 2월부터 2024년 10월까지 척추 MRI 검사를 받은 환자를 대상으로 분석하였다. 사용된 장비는 GE 사의 3.0T SIGNA Premier을 사용하였고, 축상 T2강조영상에서 동일한 부위를 RTr 기법을 적용하지 않은 영상과 RTr 기법을 적용한 영상 두 개를 획득해 평가하였다. 정성평가는 2명의 평가자의 평가점수를 Wilcoxon test로 비교하였다. 정성평가 결과, 경추와 요추에서는 RTr 기법 적용 시 영상화질 개선에 있어서 유의미한 차이를 보이지는 않았지만 흉추에서는 RTr 기법 적용 시 영상화질 개선에 있어서 유의미한 차이를 보였다. 결론적으로 경추와 요추보다는 포화펄스 사용에 있어 제한이 있고 호흡에 영향을 많이 받는 흉추 MRI 검사 시 RTr 기법을 적용하는 것이 더 효과적이다. 다만 RTr 기법 적용 시 검사 시간이 늘어나는 단점이 있어서 환자의 상태에 맞춰 검사하는 것이 요구되는 바이다.

This study investigated a learning environment that can enhance memory using LED lighting. Thus, it employed experimental verification to evaluate the effect of LED lighting's illuminance and correlated color temperature on long-term memory. The lighting environment was created under six conditions: two illuminance levels of 400 lx and 1,000 lx, and three correlated color temperatures of 3,000 K, 5,000 K, and 7,000 K. The participants of this study consisted of 30 cognitively healthy adults, with an average age of 21.7 years (SD = 1.73). The learning (memory) task used meaningless letters of only seven consonants, and the word fragment completion task measured memory retention after 20 minutes. The results of the study revealed that a relatively dim light of 400 lx, 5,000 K condition yielded the best long-term memory (Mean = 37.67, SD = 14.55), while the 1,000 lx, 5,000 K condition elicited the worst long-term memory (Mean = 25.67, SD = 12.78).

On the wooden slabs unearthed from the tomb of Guojianao (formerly, Guo) in the period of Sun Wu of the Three Kingdoms, there is a sentence with the words “針囊一枚, 白糸一 , 青糸一”. Past scholars interpreted the three characters “ ” ,“ ” and “ ” as the word “縱 (zong)” , which means “silk thread”, and “ ” ,“ ” as the word “㢧 (卷, juan, volume)”, which is a measure word. This study verifies that the word “ ” is “ ”, and “ ”, “ ” are “ ”, which are all variants of the word “線 (xian, line)”. This was achieved by changing the phonetic note. The measure word “ ”, “ ” used for weighing silk thread should be a variant form of the word “斤 (jin)”, which is similar to the writing of “ (jin)” or “ (jin)” in the Pan’s clothing list of the Eastern Jin Dynasty.

이 연구는 인공지능(AI)이 문화콘텐츠와 미디어 산업에 미치는 영향을 다각적으로 분석하고, AI의 창의 적 생산, 미디어 소비 변화, 윤리적·사회적 쟁점에 대해 논의하였다. 그리고 AI가 콘텐츠 제작에서 창의성과 효율성을 높이며, 창작자와의 협력을 통해 새로운 형태의 콘텐츠 창출을 가능하게 한다는 점을 확인하였다. 또한 AI 기반 추천 시스템을 통해 개인화된 미디어 소비 경험이 제공됨으로써 사용자 만족도와 소비 지속 성이 강화된다는 사실을 밝혔다. 그러나 AI 도입은 저작권 문제, 알고리즘 편향성, 문화적 다양성 보존, 사회적 고용 변화 등 다양한 윤리적·사회적 과제도 야기하고 있다. 이를 해결하기 위해 법적, 기술적, 정책 적 접근이 필요하며, AI의 투명성과 공정성을 확보하는 것이 필수적임을 강조하였다. AI와 인간이 협력하 여 공정하고 신뢰할 수 있는 콘텐츠 제작을 지향할 때, AI는 문화콘텐츠와 미디어 산업의 발전에 이바지할 수 있을 것이다. 본 연구는 AI와 문화산업의 융합을 둘러싼 다양한 이슈를 종합적으로 검토함으로써 향후 지속 가능한 발전을 위한 방향성을 제시하고자 한다.

본 연구는 K-공간 기반 노이즈 제거 딥러닝(DL)을 이용한 확산강조영상(DWI)의 유용성을 평가하고자 하였다. 연구 를 위해 간세포암으로 확진된 환자 30명을 대상으로 DL 기법 적용 전후의 DWI에 각각 확산경사자계(b-value) 50 과 800을 적용하여 영상화하였다. 획득한 영상에서 간세포암 조직과 정상 간 조직에 관심 영역을 설정하여 b50, b800에서의 신호대잡음비(SNR)와 대조대잡음비(CNR)를 측정하였고 두 명의 관찰자가 각 영상에서 간세포암 조직 을 측정하여 겉보기확산계수(ADC) 값을 계산하였다. 모든 측정값의 평가는 T-검정(T-test)을 사용하여 상관관계 를 평가하였으며 급내상관계수(ICC)를 이용하여 두 관찰자 간 ADC 측정값의 일치도와 신뢰도를 평가하였다. 연구 결과, DL 적용 후 영상에서 SNR과 CNR이 모두 높아졌으며 통계적으로 유의한 것으로(p<0.05) 나타났다. 또한, 간세포암의 ADC 값은 통계적으로 유의하지 않은 것으로(p<0.05) 나타났지만 두 관찰자 간 ADC 측정값의 일치에 대한 신뢰도는 상관계수가 0.75 이상으로 우수하였고, 간세포암의 고유한 성질로 인해 ADC 값의 변화가 적은 점을 고려한다면 충분히 유의한 결과라고 볼 수 있다. 결론적으로 DL DWI은 영상 획득 시간을 단축하면서도 기존 DWI 보다 질적으로 더 나은 영상을 획득했다. 향후 다양한 MRI 검사에 DL이 적용된다면 더욱 유용하게 사용될 것으로 사료 된다.

As the Fourth Industrial Revolution advances, smart factories have become a new manufacturing paradigm, integrating technologies such as Information and Communication Technology (ICT), the Internet of Things (IoT), Artificial Intelligence (AI), and big data analytics to overcome traditional manufacturing limitations and enhance global competitiveness. This study offers a comprehensive approach by evaluating both technological and economic performance of smart factory Research and Development (R&D) projects, addressing gaps in previous studies that focused narrowly on either aspect. The research combines Latent Dirichlet Allocation (LDA) topic modeling and Data Envelopment Analysis (DEA) to quantitatively compare the efficiency of various topics. This integrated approach not only identifies key research themes but also evaluates how effectively resources are utilized within each theme, supporting strategic decision-making for optimal resource allocation. Additionally, non-parametric statistical tests are applied to detect performance differences between topics, providing insights into areas of comparative advantage. Unlike traditional DEA methods, which face limitations in generalizing results, this study offers a more nuanced analysis by benchmarking efficiency across thematic areas. The findings highlight the superior performance of projects incorporating AI, IoT, and big data, as well as those led by the Ministry of Trade, Industry, and Energy (MOTIE) and small and medium-sized enterprises (SMEs). The regional analysis reveals significant contributions from non-metropolitan areas, emphasizing the need for balanced development. This research provides policymakers and industry leaders with strategic insights, guiding the efficient allocation of R&D resources and fostering the development of smart factories aligned with global trends and national goals.

This study examines the beliefs and practices regarding performance assessment among Korean English teachers in secondary schools. A survey was conducted with 109 teachers using a 52-item online questionnaire to investigate the extent to which teachers’ beliefs align with their instructional practices and to categorize them based on these criteria. Although teachers acknowledge the pedagogical advantages of performance assessment, a significant gap exists between their beliefs and actual implementation, primarily due to the considerable time required for its execution. Teachers with longer tenure and higher qualifications demonstrated a more positive and effective application of performance assessment. The findings highlight the necessity for targeted professional development to enhance teachers’ use of performance assessment strategies, especially for those who are skeptical about their effectiveness. Such initiatives are essential for bridging the gap between beliefs and practices, fostering an environment that promotes the effective use of performance assessment, and ultimately improving teaching quality and student learning outcomes in Korean English education.

본 연구는 간 자기공명영상 검사 시 프리모비스트(Gd-EOB-DTPA) 조영제를 사용한 동적 동맥기(dynamic arterial phase)에서 호흡기 운동인공물을 최소화하기 위한 최적의 방법을 연구하였다. 연구는 총 세 집단으로 나누 어 진행되었으며, 첫 번째 집단은 별도의 사전 교육(pre-scan preparation, PSPP) 없이 촬영한 집단, 두 번째 집단은 사전 교육만 시행하고 촬영한 집단, 세 번째 집단은 사전 교육과 검사 중 숨 참기 보조 신호(breath-holding assistance signal, BHAS)를 제공한 집단으로 구성되었다. 각 집단의 촬영 결과를 비교한 결과, 사전 교육과 검사 시 숨 참기 보조 신호를 함께 시행한 집단에서 동적 동맥기 영상의 호흡기 운동인공물이 가장 적었으며, 영상의 품질 도 더 높게 평가되었다. 이러한 결과는 간 MRI 촬영의 동적 동맥 단계 검사에서 사전 교육과 검사 중 숨 참기 보조 신호가 결합한 접근법이 환자의 숨 참기 협조를 강화하여 영상 품질을 개선하고, 정확한 진단에 기여할 수 있음을 시사한다.

The green supply chain has become a central concern for global businesses, particularly in maritime industries, where sustainable development is pursued as both an economic growth strategy and a means of environmental preservation. This study seeks to identify the key challenges to implementing green supply chain in Vietnam. The Analytical Hierarchy Process (AHP) is employed to assess the significance of various factors, while Fuzzy Structural Modeling (FSM) is used to explore their interrelationships. Five major factors - economic, technological, organizational, governmental, and social - are identified as critical to the implementation of green supply chain. The study highlights that the organizational factor is the most crucial, with customer pressure, particularly regarding environmental standards from export countries, being the most influential sub-factor. The findings provide important insights for developing government policies, offering support to businesses, and guiding investment decisions in green supply chain.

With the increasing integration of generative Artificial Intelligence (AI) in education, there is a growing demand for accessible AI-powered platforms for teachers and students. This study examines the efficacy of an online question-making platform using GPT-3.5 generated content to develop Korean students’ question-asking skills in English. Employing a mixed-methods approach, we assessed the platform’s impact on students’ question making abilities and its feasibility in classroom settings. Participants included thirty students from a 4th grade elementary school English classroom in Korea and seven elementary school teachers. Quantitative data were collected through pre- and post-tests measuring students’ question-making skills, while qualitative insights were gathered from semi-structured teacher interviews. Results indicated that the application was able to significantly improve students’ question-making abilities. Thematic analysis of interviews indicated positive perceptions of the platform’s usability and p otential f or l anguage learning. Findings m ay contribute to the growing body of research on using artificial intelligence in L2 education and offer practical insights for educators seeking to leverage advance language models in their instructions.

This study investigated the morphological characteristics and regional variations of leaves, flowers, and seeds of Quercus myrsinifolia Blume to understand its ecological adaptation and the effects of environmental factors. Samples were collected from Jinju, Hapcheon, and Sancheong, and nine leaf traits, six flower traits, and five seed traits were analyzed. Significant regional variations were observed, with Hapcheon exhibiting the largest leaf and flower sizes, while Sancheong showed the largest and heaviest seeds. Jinju recorded the smallest values for most traits. Principal Component Analysis (PCA) revealed distinct regional groupings, with Hapcheon displaying intermediate traits, Sancheong larger traits, and Jinju smaller traits. Correlation analysis identified strong positive relationships between leaf length and width, seed length and weight, and the number of staminate flowers and catkin width, highlighting key indicators for growth. Climate factors such as temperature and precipitation significantly influenced morphological traits, with higher temperatures negatively affecting leaf and seed sizes, while precipitation showed a weak positive correlation with seed weight. Among soil factors, pH and magnesium content were closely related to morphological traits. pH exhibited a negative correlation with leaf length and petiole length, while magnesium showed a positive correlation with seed weight and leaf width. These findings underscore the significant role of environmental factors in morphological variation and provide valuable insights for developing regionally adaptive breeding strategies. These findings provide foundational data for developing region-specific breeding strategies and cultivars for Q. myrsinifolia, contributing to ecological management and climate change adaptation strategies.

In the integrated ancient East Asian sphere, literature is an explicit expression of unity. However, due to differences in perspectives, there are huge contrasts and disharmony in contemporary East Asia surrounding historical issues. Using artificial intelligence, specifically the retrieval-enhanced generative model, to build an intelligent research platform for Yanxinglu, and completing research auxiliary work that includes named entity recognition, relationship extraction, and knowledge graph construction, the study of East Asian history can be enhanced. This paper focuses on the construction of the LLM-RAG model and rules in the construction of the Yanxinglu knowledge base, and discusses the time process and precautions for the refined processing of the Yanxinglu text data.

이 논문은 W. B. 예이츠의 유산과 멜리스 베스리의 소설 􋺷흩어진 사랑􋺸에 서 나타나는 뼈의 상징적 공명을 탐구한다. 소설에서 예이츠의 유령은 그의 삶, 예술, 그 리고 자신의 유해라는 수수께끼 같은 운명을 되새기며 지속적인 주제들을 반추한다. 뼈의 모티프는 사랑, 죽음, 그리고 기억의 교차점을 포괄하는 서사적이고 은유적인 축으로 기능한다. 이러한 관점에서 이 논문은 베스리가 예이츠의 미완의 열정, 특히 모드 곤에 대한 사랑을 어떻게 재구성하며 그의 정체성의 더 넓은 문화적, 역사적 차원을 어떻게 탐구하는지를 살펴본다. 예이츠의 유해 발굴과 재매장에 얽힌 논란은 예술적 불멸성과 신체의 덧없음 사이의 긴장을 심화시키며, 이는 아일랜드의 복잡하고 종종 단절된 역사 적 서사를 반영한다. 예이츠를 현대 문학적 맥락에 배치함으로써 베스리는 그의 비전을 확장하면서도 변모시키며, 사랑, 상실, 유산에 대한 예이츠의 사색을 현대적 맥락에 녹여 낸다. 이 논문은 베스리의 소설이 뼈를 기억의 매개체로 부각시키며 예이츠의 시적 상상 력과 그녀 자신의 재해석 사이의 다리를 놓는다고 주장한다. 궁극적으로, 이 연구는 예 이츠와 베스리가 공유하는 죽음, 역사, 그리고 예술과 감정의 초월적 힘에 대한 탐구가 여전히 중요한 의미를 가진다는 점을 강조한다. 􋺷흩어진 사랑􋺸 은 예이츠의 사랑의 유산 을 재구성하며, 그 자체로 그 유산의 본질적 일부가 된다.