In this study, we analyzed the structural and mechanical properties of aluminum foams fabricated using aluminum powders of varying sizes and mixtures. The effects of sintering and pore structure at each size on the integrity and mechanical properties of the foams were investigated. Structural characteristics were examined using scanning electron microscopy and micro–computed tomography, while mechanical properties were evaluated through compression testing. The experimental results demonstrated that smaller powder sizes improved foam integrity, reduced porosity and pore size, and resulted in thinner cell walls. In combination, these effects increased compressive strength as the powder size decreased. The findings of this study contribute to the understanding and improvement of the mechanical properties of aluminum foams and highlight their potential for use in a wide range of applications.

Italian ryegrass (Lolium multiflorum Lam., IRG) is a widely cultivated winter forage crop known for its high yield and nutritional value. This study evaluated the processing characteristics and feeding performance of IRG-based pellets in Hanwoo cattle (Bos taurus coreanae) and Korean native black goats (Capra hircus). IRG was harvested at the optimal growth stage and processed into two pellet formulations: IRG ≥80% (with up to 20% soybean meal) and 100% IRG. Feeding trials were conducted under ad libitum feeding conditions. Hanwoo cattle showed higher intake of 100% IRG pellets (7.9 kg/day/head) than IRG ≥80% pellets (7.5 kg/day/head, p<0.05), with similar average daily gain (0.9 ± 0.4 kg/day/head). Conversely, black goats exhibited significantly lower intake of IRG ≥80% pellets (54.6 g/day/head) compared to 100% IRG pellets (266 g/day/head), likely due to reduced palatability associated with soybean meal inclusion. These findings suggest that IRG pellets are suitable for Hanwoo cattle, while further optimization of pellet size and formulation is required to improve acceptance in goats. Future studies should assess long-term impacts on digestion, rumen fermentation, and metabolic responses.

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.

본 연구는 절화 장미‘All For Love’에 대해 과산화초산 (peracetic acid, PAA)의 보존용액 적용 가능성과 적정 처리 농도를 구명하고자 수행되었다. 보존용액 처리는 Distilled water(DW), PAA 50, 100, 200μL·L-1, FloraLife 1%로 하였 다. 절화수명은 대조구 DW(5.27일)에 비해 PAA(5.87~6.20 일)와 FloraLife(5.87일) 처리구에서 절화수명 연장효과가 있었 다. 모든 처리구에서 80% 이상 꽃목 굽음(Bent neck)과 20% 이상 꽃잎 청변화(Blueing) 현상이 나타났다. 화색 변화율과 잎의 엽록소 함량은 처리간 차이가 없었다. 화폭변화율의 경 우, DW(135%)보다 PAA 50μL·L-1(155%), 100μL·L-1(154%), 200μL·L-1(161%) 처리구에서 높은 개화율을 보였다. 상대생체 중은 DW와 FloraLife 처리구에서는 2일, PAA 처리구에서는 3일까지 증가 후 감소하였다. 수분균형은 DW에서 가장 빠르게 (-)의 값을 나타냈고, PAA 50μL·L-1 처리구에서 가장 길게 수분 균형이 유지되었다. PAA와 FloraLife 처리구에서 보존용액과 줄기 절단면 모두 세균이 검출되지 않았다. 결론적으로 PAA 50μL·L-1 처리는 DW에 비해 장미의 절화수명 연장 및 품질 유지에 효과적이었다.

Limited fashion products serve as a strategy for demonstrating the brand’s vitality and presence by satisfying the emotional needs of consumers seeking to escape from the boredom of similar products. The MZ generation values unique experiences and desires to purchase rare and unique products. Accordingly, the fashion industry prioritizes launching limited fashion products that emphasize artistry and can convey different values compared to existing products. The open-run phenomenon, characterized by people waiting in line before the store opens and then running to the store to purchase these limited products as soon as the store opens, is rapidly emerging as a consumer trend in our society. This study explored the impact of fashion consumers’ psychological factors-that is, FOMO, brand attachment, and need for uniqueness-on their open-run intention for limited fashion products. An online survey was administered to test the research hypotheses on Korean consumers, and 300 responses were statistically analyzed using the SPSS 28.0 program. The results revealed that FOMO, brand attachment, and the need for uniqueness significantly increased open-run intention for limited fashion products. Furthermore, consumers’ fashion involvement appeared to have a significant positive moderating effect on FOMO, brand attachment, and open-run intention. However, it did not substantially impact the effect of the need for uniqueness on open-run intention.

This study explores how to integrate the generative artificial intelligence (AI) tool Midjourney into the fashion design process, emphasizing the visualization of sporty fashion concepts. The research applied Midjourney at every stage of the fashion design process: mood board, fashion sketch, flat drawing, production package, fashion show presentation, and store display and sales. Specifically, sporty fashion was selected as the theme, and customized prompts were developed from prior research and design principles to generate visual outputs for each stage. Furthermore, three apparel design experts evaluated the AI-generated images to assess Midjourney’s practical applicability and effectiveness in each phase of the fashion design workflow. Expert evaluations revealed that Midjourney was particularly effective in the early stages, offering diverse and visually engaging imagery that supported creative ideation and mood expression. The tool allowed quick exploration of different silhouettes during the sketching stage but was imprecise in detailed forms and proportions. Limitations became more evident in the flat drawing and work instruction stages, where outputs failed to accurately reflect material textures and technical construction. Prompt refinements and referencebased prompts were tested but often resulted in inconsistent or stylized outputs. Additionally, continuity between stages was missing. Midjourney shows potential as a creative tool, but experts highlight its limitations for practical industry application. Further research is needed to improve prompt optimization and training data for enhanced accuracy and usability in AI-assisted fashion design workflows.

본 논문은 라이소자임이 칸디다 알비칸스에 항균효능이 있음을 발견하였고 라이소자임의 분해 절편도 또한 항균효능이 있는지 단백질 분해 효소인 트립신을 처리하여 확인해 보았다. 130개의 아미노산 으로 구성된 14 kDa 단백질인 라이소자임을 약 24 kDa의 분자량을 가지는 단백질 분해 효소인 트립신으 로 분해 하였다. 분해된 생성물은 고성능 액체 크로마토그래피인 분석용 및 제조용 HPLC를 사용하여 분 석 및 분리하였다. 이를 통해 효율적인 라이소자임 소화를 위한 최적 조건을 확인하고, 분해된 펩타이드 절 편들을 분리하였다. 효능평가 결과, 일부 펩타이드 절편들이 칸디다 알비칸스에 강한 항균 활성을 보임을 확인하였으며 몇몇은 활성이 줄어드는 결과를 보였다.