A 13-year-old female lion underwent a simple mastectomy for a rapidly growing abdominal mass, confirmed as mammary adenocarcinoma after histopathological examination. Mammary tumors are common in domestic cats but less frequently reported in African lions. This report presents the first documented case of mammary adenocarcinoma in an African lion in South Korea. The mass was successfully excised through stable anesthesia and surgery. This report adds to the limited literature on mammary tumors in large felids and discusses the need for tailored management strategies.

For risk assessment of spent nuclear fuel (SNF) transportation, it is necessary to calculate the damage ratio of SNF rods loaded in the cask. Due to the complexity in the geometry and material properties of SNF, it is impractical to analyze the detailed behavior of every fuel rod and assembly in a single cask model. This study presents a framework for performing cask-level analysis by sequentially simplifying the fuel rods and spent fuel assemblies for fuel damage ratio (FDR) calculation. Using the simplified fuel rod model developed in previous studies, we constructed a CE 16×16 fuel assembly model and presented a methodology to simplify the CE 16×16 assembly model into cuboids. Cask drop analyses were performed to validate the similarity of the detailed CE 16×16 model and the simplified model. Using the proposed simplified models, a procedure for quantifying the bending load and pinch load applied to the fuel rods during the drop impact is presented. The FDR can then be calculated by comparing the quantified loads with their respective failure criteria. Through a case study, the feasibility of the developed framework for systematic and accurate FDR calculation was effectively demonstrated.

The swelling capacity of bentonite buffers is vital in high-level radioactive waste (HLW) repositories, as it minimizes groundwater infiltration, prevents nuclides from reaching the biosphere, and stabilizes the HLW canisters. As swelling capacity is a function of temperature, understanding bentonite’s behavior at approximately 100°C (its presumed upper limit) is essential. However, research on this subject has been scarce. Hence, this study explored the effects of thermal treatment of Ca-bentonite at 105°C under injected water pressures. The results suggest a 19% reduction in “swell index” and a 35%–36% decrease in the total pressure in thermally treated bentonite. The heated samples demonstrated higher hydraulic conductivity than the non-heated ones, indicating potential performance deterioration in controlling the fluid movement. Furthermore, the injected water pressure (base pressure) was not fully transmitted to the sample owing to the difference between the base and back pressures, leading to variations in the total pressure despite maintaining a constant differential pressure. Thus, the results demonstrated a degradation in bentonite’s swelling capacity and its compromised role in safe HLW disposal, when subjected to treatment at 105°C. The insights from this research can assist in HLW repository design, while highlighting the need for further research into bentonite’s performance.

The recent release of contaminated water from the Fukushima Daiichi Nuclear Power Plant highlights the need for accurate tritium measurement, particularly near the minimum detectable activity (MDA) of 5 Bq·L−1 set by South Korea’s Nuclear Safety and Security Commission. This study aims to improve low-level tritium measurement accuracy by optimizing the region of interest (ROI) for quench curve determination. These adjustments are crucial for separating tritium signals from background noise. Quench standards were prepared and measured using a liquid scintillation counter (LSC). Three ROIs were analyzed to assess the impact of channel selection on measurement precision: A 20-148 channel range optimized via figure of merit (FOM) analysis, a 20-250 channel range covering tritium’s full beta spectrum, and a broad 1-1024 channel range. Quench curves were obtained by fitting the counting efficiency of each ROI to the quench standards. Tritium samples with six different activity levels were prepared, and their radioactivity was calculated using the quench curves. Selecting appropriate ROIs for quench curve determination is critical for measuring low-concentration tritium accurately. This approach reduces uncertainty and emphasizes reliable methods to improve the precision and consistency of tritium measurements.

육성한 화단국화 품종인 황색 국화(Chrysanthemum morifolium Ramat.)인 ‘한아름볼(Hanarum Ball)’은 충남농업기술원 화훼 연구소에서 모본 ‘Gigi Gold’와 부본 ‘Jinny Ball’을 이용하여 육성되었다. ‘한아름볼’ 품종은 2014년에 인공 교배를 통해 개 발되었으며, 2015년부터 2017년까지 품종 특성을 조사한 후 2017년에 최종 선발되었다. ‘한아름볼’의 초형은 반구형으로, 노랑색 꽃잎(Yellow 5B)을 가진 반겹꽃을 지니고 있으며, 개화 기는 9월 21일이다. 초장은 36.0cm로, 초폭은 66.0cm, 화폭 은 4.1cm, 본당 착화수는 1,147개, 꽃잎수는 81.0개이며, 엽색 은 녹색(Green 137B)이어서, 대조품종인 ‘금방울’과 유사한 형 태와 색을 가지고 있으나, 꽃크기와 착화수, 개화시기에서 차이 를 보였다. ‘한아름볼’은 도로변이나 화단 등 조경용으로 활용 가능하며, 화훼 농가에 새로운 소득원을 제공할 수 있는 품종으 로 기대된다.

Ectopic ureter refers to a congenital anomaly in which one or both ureters do not connect to the urinary bladder at the correct anatomical site. This case report discusses the case of a 6-year-old female mixed-breed dog diagnosed with chronic urinary incontinence, systemic hypertension, pancreatitis, and sepsis resulting from an ectopic ureter. Treatment involved an initial nephro-ureterectomy to address severe pyonephrosis, followed by ureteroneocystostomy for the remaining functional kidney. Post-surgical outcomes showed notable improvements in clinical symptoms, laboratory findings, and blood pressure. This report emphasizes the need for early diagnosis and appropriate surgical treatment in cases of ectopic ureter. Additionally, it aims to present the clinical symptoms and conditions resulting from prolonged disease progression, as well as the corresponding treatment methods and prognosis.

This study investigated the seasonal variations and environmental factors influencing soil respiration in Quercus mongolica forests at three distinct sites in South Korea: Mt. Jeombongsan, Mt. Namsan, and Mt. Jirisan. Monthly soil respiration rates were measured from 2009 to 2010 using a closed chamber method, alongside assessments of soil temperature, moisture, and organic matter. Results revealed significant seasonal and spatial variability, with the highest respiration rates recorded during summer months. Soil temperature was identified as the primary driver of respiration, showing strong positive correlations across all sites (R2=0.64 - 0.88). The temperature sensitivity (Q10) values ranged from 2.7 at Mt. Namsan to 5.7 at Mt. Jeombongsan, underscoring the heightened vulnerability of cooler, high-altitude forests to warming. Soil moisture had a dual role, promoting respiration at moderate levels but inhibiting it under saturated conditions, particularly at Mt. Jirisan. Soil organic matter content exhibited an inverse relationship with respiration rates, indicating that substrate quality, rather than quantity, predominantly governs microbial activity. Plant-soil interactions, including root respiration and litterfall decomposition, further modulated respiration patterns, with site-specific differences reflecting variations in vegetation density and ecosystem structure. These findings highlight the complexity of soil carbon dynamics in temperate forests and the critical influence of environmental factors and plant-soil processes. The study provides essential insights for improving carbon cycling models and informs climate-resilient forest management strategies. Future research should prioritize long-term monitoring and experimental manipulations to better predict soil respiration under changing climatic conditions.

This study aimed to investigate the metabolic and morphological responses of Italian ryegrass to waterlogging stress during its early growth stage. Waterlogging increased the number of adventitious roots and root porosity, indicating an enhanced oxygen transport mechanism. Phenolic compound levels were increased in both leaf and root tissues under waterlogging stress compared to the control, suggesting the development of a non-enzymatic antioxidant system. Waterlogging treatment also increased reactive oxygen species (ROS) levels only in roots. Total soluble carbohydrates and alcohol dehydrogenase (ADH) activity increased under waterlogging stress, suggesting an increased activity of carbohydrate breakdown and energy conversion mechanisms. This study suggests that Italian ryegrass exhibits significant metabolic and morphological adaptations to waterlogging stress during its early growth stage. These adaptations demonstrate that Italian ryegrass has developed tolerance mechanisms to cope with such stress.

The study explores the relationship among teacher identity, teacher transparency, teacher self-efficacy, and teachers’ adaptation to digital change. Eighty-four English teachers participated in the study. For comparison between English and other subject teachers, 38 survey results of different subject teachers were included in the analysis. The results showed that English teachers’ scores were lower across all the constructs in terms of both transparency and self-efficacy compared to the scores of teachers in other subjects. For further analysis, the Structural Equation Modeling was run, and the results revealed that teacher transparency influences teacher self-efficacy, facilitating digital adaptation. Instructional Transparency and Peer Transparency were significant predictors of selfefficacy, directly influencing digital adaptation. This result illustrates the dynamic interplay between evolving teacher identity and self-efficacy in relation to digital adaptation through the relationship between teacher transparency and teacher selfefficacy. The findings indicate the need for targeted programs to enhance English teachers’ transparency and self-efficacy as a pathway to their digital adaptation.

This study proposes a weight optimization technique based on Mixture Design of Experiments (MD) to overcome the limitations of traditional ensemble learning and achieve optimal predictive performance with minimal experimentation. Traditional ensemble learning combines the predictions of multiple base models through a meta-model to generate a final prediction but has limitations in systematically optimizing the combination of base model performances. In this research, MD is applied to efficiently adjust the weights of each base model, constructing an optimized ensemble model tailored to the characteristics of the data. An evaluation of this technique across various industrial datasets confirms that the optimized ensemble model proposed in this study achieves higher predictive performance than traditional models in terms of F1-Score and accuracy. This method provides a foundation for enhancing real-time analysis and prediction reliability in data-driven decision-making systems across diverse fields such as manufacturing, fraud detection, and medical diagnostics.

Defective product data is often very few because it is difficult to obtain defective product data while good product data is rich in manufacturing system. One of the frequently used methods to resolve the problems caused by data imbalance is data augmentation. Data augmentation is a method of increasing data from a minor class with a small number of data to be similar to the number of data from a major class with a large number of data. BAGAN-GP uses an autoencoder in the early stage of learning to infer the distribution of the major class and minor class and initialize the weights of the GAN. To resolve the weight clipping problem where the weights are concentrated on the boundary, the gradient penalty method is applied to appropriately distribute the weights within the range. Data augmentation techniques such as SMOTE, ADASYN, and Borderline-SMOTE are linearity-based techniques that connect observations with a line segment and generate data by selecting a random point on the line segment. On the other hand, BAGAN-GP does not exhibit linearity because it generates data based on the distribution of classes. Considering the generation of data with various characteristics and rare defective data, MO1 and MO2 techniques are proposed. The data is augmented with the proposed augmentation techniques, and the performance is compared with the cases augmented with existing techniques by classifying them with MLP, SVM, and random forest. The results of MO1 is good in most cases, which is believed to be because the data was augmented more diversely by using the existing oversampling technique based on linearity and the BAGAN-GP technique based on the distribution of class data, respectively.

3D printing using ceramic powder to produce precision ceramic parts has been studied with various additive manufacturing methods. This study analyzed problems occurring in alumina additive manufacturing that uses digital light processing (DLP) as well as methods to address such problems. For efficient analysis, we have classified alumina additive manufacturing into three types according to the driving method of the build platform - lifting type (LT), tilting type (TT) of the vat, and blade movement type (BT). LT had a problem with detachment and cracking of the alumina green body. However, this could be prevented by carefully controlling the cure depth of the suspension slurry and the bonding force between layers and improving the material used for coating the vat. TT, which resulted in non-uniform alumina additive manufacturing, could be improved by modifying the bidirectionality of the axis and the fluidity of the highly viscous alumina suspension slurry. BT resulted in detachment of the specimen as well as non-uniform results, but this could be avoided by shortening the shifting distance of the alumina suspension when it is introduced to the build platform, and enabling effective spreading.

In this study, we have determined mitochondrial genome of Matsucoccus thunbergianae isolated in Korea. The circular mitogenome of M. thunbergianae is 15,406 bp including 13 protein-coding genes, two ribosomal RNA genes, and 22 transfer RNAs. AT ratio is 78.2%. Maximum-likelihood and Bayesian inference phylogenetic trees show that M. thunbergianae is clustered with M. matsumurae, and family Margarodidae is clustered with family Pseudococcidae with enough supportive values.