This study examined impact of agricultural cooperative membership on technical efficiency, income, and costs of coffee farmers in Southern Shan State, Myanmar. Using stochastic frontier analysis (SFA) and propensity score matching (PSM) methods, this study estimated average treatment effect on the treated of agricultural cooperative participation. Results showed that technical efficiency, total income, and total variable costs were significantly higher for cooperative members than for comparable non-members. However, net income of members is not significantly different from that of comparable non-members.

Effective cooling strategies are critical for cultivating high-quality ornamental plants during the summer. The fan-and-pad cooling system reduces greenhouse temperatures by drawing air through wet pads, which humidify and cool the air, aided by fans on the opposite side. However, the paper-based pads (corrugated cellulose) used in this system have limited durability and degrade with prolonged use. Nanocomposite hydrogels, with their polymer-based structure, can absorb and retain moisture through swelling, presenting a promising alternative. This study examines the application of nanocomposite hydrogels, focusing on their hygroscopic properties and cooling efficiency under various temperatures and wind speeds. When treated with lithium chloride solutions at 25%, 50%, 75%, and 100% saturation, higher LiCl concentrations reduced weight but increased swelling capacity. Optimal cooling effects were achieved with wind speeds of 1.0 m/s at 25°C and 1.5 m/s at 35°C, with greater efficiency observed at lower wind speeds. These findings suggest that integrating nanocomposite hydrogels into cooling pads could enhance durability and reduce maintenance compared with conventional paper pads.

가위벌과에 속하는 Coelioxys의미기록 2종 Coelioxys conoidea Illiger, 1806 와 Coelioxys formosicola Strand, 1913을 한국에서 처음으로 보 고한다. 본 종의 기재, 분포정보, 그리고 삽화를 제공한다.

목적 : 근시 어린이를 대상으로 2년 동안 OK-렌즈 착용자의 근시 감소에 대한 효능을 평가하고자 하였다. 방법 : OK-렌즈 그룹은 OK 렌즈 착용 기준에 부합하는 30명의 대상자로 구성되었고, 단초점 안경을 착용한 대조군에는 31명이 포함되었다. 이 연구에 사용된 OK-렌즈는 CRT였고, 굴절이상 측정은 조절마비제 사용없이 자 동굴절검사기와 자각적 굴절검사를 통하여 이루어졌다. 결과 : 총 61명(OK-렌즈 그룹과 대조군은 각각 30명, 31명)의 대상자가 2년 동안의 검사를 완료했다. 연구 초 기의 OK-렌즈군과 대조군의 평균 연령±SD는 각각 10.13±1.81세와 10.32±1.73세였고, 등가구면굴절력은 OK-렌즈군에서 –2.53±0.96 D, 대조군에서 -2.56±1.10 D로 두 그룹 간 유의미한 차이는 없었다. 2년 동안 등 가구면굴절력의 증가는 OK-렌즈군과 대조군에서 각각 –0.70±0.56 D, -1.27±0.78 D였으며, 그 차이는 통계적 으로 유의한 차이가 있었다(p<0.001). 결론 : OK-렌즈 치료는 학령기 어린이의 근시 진행을 늦추는 데 도움이 될 수 있다.

As part of the 2024 research initiative, “Investigation and Discovery of Prokaryotes in Freshwater Systems,” samples were collected from diverse freshwater habitats, including both water and soil environments. Approximately 2,000 bacterial strains were isolated as single colonies and identified through 16S rRNA gene sequence analysis. Among these, 38 strains shared ≥98.7% 16S rRNA gene sequence similarities with those of known bacterial species not previously reported in Korea. These strains were thus categorized as newly recorded bacterial species in Korea. These 38 bacterial strains displayed significant phylogenetic diversities, spanning 2 phyla, 4 classes, 15 orders, 24 families, and 34 genera. These unrecorded species were classified into the following classes: Actinomycetia (with genera including Microcella, Conyzicola, Curtobacterium, Leucobacter, Microbacterium, Frigoribacterium, Lysinibacter, Streptomyces, Nonomuraea, Actinocorallia, Ruania, and Actinoplanes), Alphaproteobacteria (Paracoccus, Youngimonas, Loktanella, Corticibacterium, Neorhizobium, Onobrychidicola, Ferranicluibacter, Aureimonas, Asticcacaulis, and Novosphingobium), Betaproteobacteria (Rhodoferax, Rugamonas, and Cupriavidus), and Gammaproteobacteria (Rheinheimera, Shewanella, Kosakonia, Leclercia, Hafnia, Yersinia, Pseudomonas, Lysobacter, and Acinetobacter ). Further characterization included assessment of Gram reaction, colony and cell morphology, biochemical properties, and phylogenetic relationships. This report presents detailed phylogenetic and phenotypic characteristics of these bacterial species.

This study aims to improve the interpretability and transparency of forecasting results by applying an explainable AI technique to corporate default prediction models. In particular, the research addresses the challenges of data imbalance and the economic cost asymmetry of forecast errors. To tackle these issues, predictive performance was analyzed using the SMOTE-ENN imbalance sampling technique and a cost-sensitive learning approach. The main findings of the study are as follows. First, the four machine learning models used in this study (Logistic Regression, Random Forest, XGBoost, and CatBoost) produced significantly different evaluation results depending on the degree of asymmetry in forecast error costs between imbalance classes and the performance metrics applied. Second, XGBoost and CatBoost showed good predictive performance when considering variations in prediction cost asymmetry and diverse evaluation metrics. In particular, XGBoost showed the smallest gap between the actual default rate and the default judgment rate, highlighting its robustness in handling class imbalance and prediction cost asymmetry. Third, SHAP analysis revealed that total assets, net income to total assets, operating income to total assets, financial liability to total assets, and the retained earnings ratio were the most influential factors in predicting defaults. The significance of this study lies in its comprehensive evaluation of predictive performance of various ML models under class imbalance and cost asymmetry in forecast errors. Additionally, it demonstrates how explainable AI techniques can enhance the transparency and reliability of corporate default prediction models.

본 연구는 딥러닝 영상 재구성 기법을 적용한 8개의 뇌질환군의 감마나이프 수술 계획용 자기공명영상(magnetic resonance imaging, MRI)의 유용성을 알아보고자 하였다. 연구 방법은 전이성 뇌종양, 뇌동정맥 기형, 수막종, 뇌하수체선종, 삼차신경통, 청신경초종, 맥락얼기 유두종, 해면상 혈관종, 총 8개의 질병을 진단받은 사람들의 T2 강조 영상(T2 weighted imaging, T2WI), 조영증강 T1 강조영상(contrast enhancement T1 weighted imaging, CE-T1WI)의 방법으로 검사한 MRI 영상을 SwiftMR을 이용하여 딥러닝 영상 재구성 기법인 디노이징(denoising)과 초해상도(super resolution)가 적용된 영상을 획득하였다. 이에 대한 성능 평가는 최대 신호대잡음비(peak signal to noise ratio, PSNR), 구조적 유사도(structural similarity index measure, SSIM), 감마나이프 방사선수술(gamma knife radiosurgery, GKRS)의 좌표계로 평가하였다. 그 결과, 원본영상을 기반으로 영상 품질이 개선된 영상의 PSNR과 SSIM은 높은 수치를 나타냄으로써 MRI 영상의 재구성이 문제없이 이루어졌고, GKRS의 수술 좌표계 또한 변화를 보이지 않았다. 결론적으로 딥러닝 영상 재구성 기법은 영상 품질 향상과 영상 보존에서 뛰어난 성능을 보임과 동시에 좌표계도 변화를 보이지 않아서, 딥러닝 영상 재구성 기법은 감마나이프 수술 계획에 유용하게 사용할 수 있는 기법임을 확인하였다.

Periodontitis is a chronic inflammatory disease characterized by the progressive destruction of periodontal tissue and alveolar bone loss. To develop effective treatment strategies, a model that mimics this disease must be implemented. From this perspective, animal models can be used to investigate its mechanisms by reproducing disease progression and providing insights into host-microbe interactions, immune responses, and bone remodeling. In addition, periodontitis-associated bone loss fundamentally differs from systemic bone loss. Targeted treatments require distinguishing periodontitis-induced and systemic bone loss mechanisms. This review examines the rationale for using animal models in periodontal research and evaluates various experimental approaches, such as bacterial inoculation, ligature-induced periodontitis, and chemically induced inflammation. These models have advanced our understanding of periodontal disease but have limitations in replicating the chronic nature of periodontitis and human immune responses. However, current models cannot fully replicate chronic disease progression and human immune responses. Recent developments have focused on improving animal models to more accurately simulate disease progression and host responses, which has led to the elucidation of the immunomodulatory mechanisms of periodontitis and their relevance to the human dental environment. Moreover, new approaches, such as developing age-related periodontitis models and improving ligature techniques, could enhance experimental reproducibility and translational potential. Future studies are needed to reflect these improvements and enhance the clinical relevance of periodontitis models.

본 연구를 통해 미기록종 Homalotylus albifrons (Ishii, 1925) (벌목: 깡충좀벌과)를 한국에 최초로 보고한다. 이 종에 대한 진단과 사진과 한국 의 Homalotylus 속의 종 키를 수록한다.

This study explored how teachers could provide support to enhance students’ out-ofclass mobile-assisted language learning (MALL) engagement. We interviewed five Korean English teachers who used Class Card, a focal technology of this study, for their students’ self-directed vocabulary learning. Additionally, students of the interviewed teachers completed a survey on their perceptions of teacher support and MALL engagement. This study has three major findings. First, the teachers adopted either a proactive or a passive approach to promoting students’ out-of-class MALL engagement, which was influenced by their beliefs about whether teachers or students should be responsible for learning beyond the classroom. Second, all teachers provided orientation and behavioral support to enhance out-of-class MALL engagement, although the consistency and intensity in providing this support varied between proactive and passive teachers. Finally, students who perceived higher levels of teacher support reported greater out-of-class MALL engagement. We discuss the importance of classroom-based teacher support to enhance MALL engagement beyond the classroom as pedagogical implications.

본 연구에서 Acyrthosiphon (Acyrthosiphon) lactucae를 국내에서 처음으로 보고한다. 이 종의 무시성충에 대한 형태학적 정보, 분포지역, 기주 식물, 한국에 분포하는 Acyrthosiphon 속 종들의 분류키를 제공한다.

Hydrangea is widely grown as an ornamental plant with a high commercial value owing to its appealing features. Although many cultivars exist as genetic resources, they cannot be effectively used for breeding due to insufficient information regarding their genetic relationships and breeding compatibility. Intraspecific and intergeneric hybridizations within the family, Hydrangeaceae present opportunities to create cultivars with desirable traits, however, breeding efforts in Hydrangea through interspecific hybridization have achieved limited success. The low viability of interspecific hybrids may be attributed to cytogenetic incompatibility between the species. Therefore, a deeper cytogenetic understanding of this genus could enhance future breeding programs. This review focuses on the importance of cytogenetic data in the breeding of hydrangeas and the different cytogenetic techniques utilized in this genus. Future directions for cytogenetic research in Hydrangea are also discussed.

Production technology trials for PARC’s new fodder oat cultivar (PARC-Oat) were conducted at the National Agricultural Research Center (NARC) under rain-fed conditions in Islamabad from 2021 to 2023. The effects of different fertilizer doses, planting densities (seed rates), and inter-row spacing on green fodder yield were studied. The experiment comprised four fertilizer doses of nitrogen and phosphorus (N:P) (55:30, 65:40, 75:50, and 85:60 kg/ha), four seed rate densities (30 kg/ac, 35 kg/ac, 40 kg/ac, and 45 kg/ac), and four inter-row spacings (15 cm, 30 cm, 45 cm, and 60 cm). Results based o n k ey p arameters a ffecting t he y ield of PARC-O at—namely plant height (cm), leaf area (cm²), leaves per tiller, number of tillers per plant, and green fodder yield (t/ha)—indicated that the maximum yield of 72.74 t/ha was observed with the fertilizer dose of 75:50 kg/ha (N:P). Similarly, a seed rate of 40 kg/ha produced optimal planting densities, resulting in the highest green fodder yield of 72.85 t/ha, while an inter-row spacing of 30 cm yielded the maximum green fodder yield of 74.30 t/ha. These results suggest that to achieve maximum green fodder biomass of oats, best management practices should include the application of a fertilizer dose of 75:50 (N:P), a seed rate of 40 kg/ha, and an inter-row spacing of 30 cm.

Mauremys reevesii (Reeves’ turtle) is an endemic freshwater turtle species found throughout East Asia. Due to a rapid population decline, the International Union for Conservation of Nature (IUCN) and the Korean government have classified this species as Endangered (EN). The reported largest population size of M. reevesii in the Republic of Korea was previously estimated to be approximately 20-30 individuals. Our study assessed the population size and structure of M. reevesii at Geumho Reservoir, Republic of Korea, using a capture-recapture data. A total of 433 M. reevesii were incidentally captured during a 35-week trapping process conducted from March to October 2023. The sex ratio of the captured population exhibited a male bias of 1.3 : 1. Sexual size dimorphism was observed only in body weight. Individuals were recaptured up to 11 times during the study period, with males and females being recaptured at an average of 2.1±2.0 times and 1.5±0.9 times, respectively. The estimated population size of M. reevesii in Geumho Reservoir was approximately 891 turtles. The absence of notable sexual size dimorphism and significant sex ratio differences suggests that the population in this area may have been established relatively recently. Compared to previous records, the population in Geumho Reservoir represents the largest single population of M. reevesii, both within the Republic of Korea and globally.

This study presents a novel methodology for analyzing disease relationships from a network perspective using Large Language Model (LLM) embeddings. We constructed a disease network based on 4,489 diseases from the International Classification of Diseases (ICD-11) using OpenAI’s text-embedding-3-small model. Network analysis revealed that diseases exhibit small-world characteristics with a high clustering coefficient (0.435) and form 16 major communities. Notably, mental health-related diseases showed high centrality in the network, and a clear inverse relationship was observed between community size and internal density. The embedding-based relationship analysis revealed meaningful patterns of disease relationships, suggesting the potential of this methodology as a novel tool for studying disease associations. Results suggest that mental health conditions play a more central role in disease relationships than previously recognized, and disease communities show distinct organizational patterns. This approach shows promise as a valuable tool for exploring large-scale disease relationships and generating new research hypotheses.

Oral cancer has a high mortality rate, making early diagnosis crucial for effective treatment and prognosis. Unlike other cancers, oral cancer develops in the oral cavity, enabling direct contact between saliva and cancer cells. Therefore, saliva is a more useful diagnostic tool than serum or tissue. When DNA, RNA, or proteins produced by cancer cells enter the saliva, they can be easily detected as tumor markers. Therefore, salivary biomarkers can serve as a noninvasive alternative to serum- or tissue-based biomarkers. Early diagnosis is essential for increasing the treatment success rate, improving prognosis, and enhancing post-treatment recovery, ultimately improving the quality of life. Proteins are essential molecules involved in key processes, such as the development, growth, death, and metastasis of oral cancer. Recent advancements in molecular biology and salivary proteomics have enabled the detection and analysis of numerous proteins in saliva. Many of these protein molecules are currently the focus of extensive research. This article aims to review the potential of saliva as a diagnostic tool, techniques for detecting protein biomarkers, and salivary protein biomarkers for oral cancer diagnosis.

목적 : 본 연구에서는 회절격자가 광원의 깊이에 따라 회절영상을 주기적으로 생성하는 광학적 특성을 이용하여 중간 범위의 깊이를 측정할 수 있는 시스템을 연구하였다. 방법 : 첫 번째로 회절격자 영상시스템을 기하광학적으로 분석합니다. 두 번째로 회절격자의 주기적인 결상특성 을 파동광학적으로 분석하였다. 세 번째로 주기적인 함수사이의 콘볼루션 특성을 이용하여 깊이에 대응하는 공간주 기를 도출하였다. 네 번째로 1 m에서 4 m까지 1 m마다 타켓을 설치한후 회절격자, 카메라, 레이저로 구성된 회절 격자 영상시스템을 이용하여 회절영상을 획득하는 광학실험을 수행하였다. 다섯 번째로 첫 번째 과정에서 세 번째 과정까지 수행한 이론적 분석을 네 번째 과정에서 획득된 회절영상에 적용하여 깊이측정을 수행하였다. 마지막으로 결과 분석을 통해 시스템의 깊이해상도를 도출하였다. 결과 : 깊이 측정 실험을 수행하였고 제안된 방법의 타당성을 검증하였다. 회절영상배열의 공간주기는 타겟물체 와 회절격자사이의 거리가 멀어질수록 증가한다, 그러나 그 증가하는 비율은 물체거리에 반비례하였다. 결론 : 회절격자의 특성을 응용한 깊이 측정 시스템을 제안하였으며 이론분석과 광학실험을 통해 타당성을 검증 하였다.

에듀테크 시대에 접어들면서 디지털 기술을 활용한 학습 방식이 점점 확대되고 있으며, 특히 모바일 기반 애플리케이션 을 활용한 학습이 적극적으로 도입되고 있다. 이러한 학습 방식은 학습자의 참여도를 높이고, 흥미를 유발하며, 학습 효율성 향상에 긍정적인 영향을 미치고 것으로 보고되고 있다. 본 연구는 자기공명영상학 학습에서 모바일 기반 애플리 케이션 사용에 대한 학습자들의 인식, 학습 효과, 학습 만족도를 알아보고자 하였다. 대구시 소재 S 대학교 자기공명영 상학을 수강한 2, 3학년 학생 70명을 대상으로 2024년 11월 24일부터 29일까지 수업 후 모바일 애플리케이션을 활용한 퀴즈 활동을 시행하였다. 연구 결과, 애플리케이션 활용에 대한 학습자들의 인식 평균 점수는 4.58±0.66, 학습 효과는 4.61±0.62, 학습 만족도는 4.58±0.65로 나타났다. 또한, 애플리케이션 활용 전후 비교 분석에서 인식 (활용 전 3.62±0.97, 활용 후 4.58±0.66), 학습 효과(활용 전 3.60±0.92, 활용 후 4.61±0.62), 학습 만족도(활용 전 3.64±0.93, 활용 후 4.58±0.65) 모두 통계적으로 유의한 차이가 있었다(p<0.05). 이러한 결과는 자기공명영상학 교육에서 모바일 애플리케이션 기반 학습이 학습자의 참여도, 이해도, 만족도를 높이는 데 효과적임을 시사한다. 따라서 자기공명영상학뿐만 아니라 다양한 전공 분야에서도 애플리케이션 기반 학습이 유용한 교육 도구로 활용될 수 있으며, 향후 교육 및 임상 실습 현장에서 적용 가능한 기초자료로 활용될 수 있을 것 기대된다.

생성형 인공지능의 급속한 발전은 사회 전반에 광범위한 영향을 미치며, 일상생활을 포함한 다양한 분야 에 활용되고 있다. 본 연구에서는 인공지능 기술의 발전 동향을 대규모 언어모델(Large Language Models, LLM)을 중심으로 살펴보고 생성형 인공지능 기반 솔루션이 정치 및 공공 부문의 효율성과 서비스 최적화 에 기여하고 있음을 확인하였다. 본 연구는 미국, 싱가포르, 인도 등의 사례분석을 통해 인공지능 도구가 선거의 확장성과 시민과의 상호작용 개선에 역할 할 수 있다는 것을 주장한다. 동시에, 대규모 언어모델의 실사용 과정에서 제기되는 편향성, 허위정보 확산, 규제 공백 등의 쟁점들을 고찰할 필요가 있음을 지적한 다. 요컨대, 생성형 인공지능은 민주주의 발전과 공공서비스 증진에 대한 가능성을 제공하지만, 기술의 지속 가능하고 적실한 활용을 위해 투명성, 공정성과 책임성을 고려한 사용이 요구된다.

자발적 지역 검토(VLR)는 도시 차원에서 지속가능발전목표(SDGs) 이행 현황을 자발적으로 점검하는 보고서이자 SDGs의 현지화 과정이다. VLR을 통해 도시의 지속가능발전 리더십을 확인하고, 지방정부와 도시 구성원이 2030 의제 목표에 대한 진행 상황을 평가하고, 가속화 방안을 모색하는 데 유용한 도구가 된다. 또한, VLR은 SDGs 인식을 제고하고, 파트너십을 활성화하며 지역 차원의 행동을 촉진하여 도시가 사회・경제・환경 발전을 위한 일관된 미래 비전을 제시하도록 돕는다. 나아가 도시 민주주의 전략을 글로 벌 의제와 연결하는 중요한 역할을 한다. 본 연구는 대한민국에서 아직 널리 알려지지 않은 VLR의 성공적 정착과 확산을 목표로 한다. 이를 위해 VLR의 개념, 역사, 주요 논의, 효과 및 성공 요인을 분석하고, 도시 민주주의와 이를 위한 다단계 거버넌스 및 SDGs 확산의 관련성을 규명하고자 한다. 또한 도시 VLR 적용 과정에서 예상되는 과제를 제시하며, 한국적 VLR 운동에 대한 관심을 높이고 실질적 적용을 촉진하고자 한다.