This study proposes a weighted ensemble deep learning framework for accurately predicting the State of Health (SOH) of lithium-ion batteries. Three distinct model architectures—CNN-LSTM, Transformer-LSTM, and CEEMDAN-BiGRU—are combined using a normalized inverse RMSE-based weighting scheme to enhance predictive performance. Unlike conventional approaches using fixed hyperparameter settings, this study employs Bayesian Optimization via Optuna to automatically tune key hyperparameters such as time steps (range: 10-35) and hidden units (range: 32-128). To ensure robustness and reproducibility, ten independent runs were conducted with different random seeds. Experimental evaluations were performed using the NASA Ames B0047 cell discharge dataset. The ensemble model achieved an average RMSE of 0.01381 with a standard deviation of ±0.00190, outperforming the best single model (CEEMDAN-BiGRU, average RMSE: 0.01487) in both accuracy and stability. Additionally, the ensemble's average inference time of 3.83 seconds demonstrates its practical feasibility for real-time Battery Management System (BMS) integration. The proposed framework effectively leverages complementary model characteristics and automated optimization strategies to provide accurate and stable SOH predictions for lithium-ion batteries.

This research aimed to investigate heterogeneity regarding governance, agricultural productivity, and food security between developed and developing nations. Utilizing a three-stage least squares (3SLS) simultaneous equation model, this study found that governance could positively impact food security through capital accumulation and agricultural productivity in both developed and developing countries. However, the magnitude of these effects differed significantly between country groups, with developed countries showing stronger governance-food security linkages than developing countries. This study reaffirms the importance of governance while showcasing its potential to vary based on a country’s economic level. Additionally, it sheds comprehensive light on impacts of agricultural production and agricultural capital accumulation on food security.

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.

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.

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.

Korean English medium instruction (EMI) classes aim to foster active discussions and communicative interactions in English between instructors and students. However, many Korean students in these classes struggle due to their limited English proficiency. This paper examines the challenges faced by Korean EFL students in EMI environments, highlighting the necessity for support in both English and their native language to facilitate effective learning. It also identifies teaching strategies that have proven effective in helping these students navigate language barriers. The findings indicate that participants had difficulty developing their writing skills for assignments in EMI settings and encountered limited opportunities to communicate their understanding of course material with instructors. To address these challenges, it is important to assess students’ language skills and find a balance between Korean and English. Implementing flexible teaching methods can enhance the learning experience, making it more effective and supportive. By providing multiple approaches to learning, such as interactive activities or peer support, learning gaps can be bridged and overall educational outcomes enhanced.