With the increasing demand for flexible electronic devices, smaller and lighter flexible supercapacitors have gained significant research attention. Among the various materials, self-supporting reduced graphene oxide (rGO) paper has emerged as one of the most promising electrode materials for supercapacitors due to its low cost, high chemical/thermal stability, and excellent electrical conductivity. Nevertheless, a major drawback of rGO paper is the limited ion diffusion between stacked rGO layers, hindering the effective formation of electrochemical double-layer at the electrode/electrolyte interface. In this study, we prepared the rGO paper derived from ball-milled followed-by water oxidation process for reducing the sheet size. The smaller-sized rGO sheets facilitated ion transport between graphene layers, promoting efficient electric double-layer formation. Moreover, the increased presence of edge planes in ball-milled rGO sheets achieved high capacitance, further enhancing the performance of rGO as an electrode material. Notably, the 2-BMOX rGO paper obtained from ball-milling and wet-oxidized graphite exhibited a capacitance of 117.9 F/g in cyclic voltammetry (CV) and 128.6 F/g in galvanostatic charge–discharge (GCD) tests, approximately twice that of conventional rGO. Additionally, the capacitance retained 91% of its initial performance after 2,000 cycles, indicating excellent cycling stability.

한국 분포가 확인되지 않았던 니토베은주둥이벌 Ectemnius nitobei (Matsumura, 1912)을 경기도 포천시 광릉숲에서 처음으로 확인하였다. 국립수목원 내 휴게광장의 가래나무과(Juglandaceae) 목재 벤치 구멍에서 암컷의 둥지 짓기 행동을 관찰하였으며, 유충의 먹이로 사용하기 위해 나방류 성충을 운반하는 행동을 확인하였다. 본 연구에서는 니토베은주둥이벌 암컷의 전신 사진, 주요 형태학적 진단 형질, 그리고 DNA 바코드 (COI) 서열을 함께 제시하여 향후 국내 분류학적 및 생태학적 연구의 기초 자료로 제공하고자 한다.

This study presents the results of a comprehensive investigation of the macrofungal diversity in South Korea conducted between 2022 and 2025. Our approach has integrated detailed morphological observations with molecular analyses of large subunit (LSU) sequences. In the present study, we have identified four species, Retiboletus fuscus, R. sinensis, R. sinogriseus, and R. zhangfeii —that were previously unrecorded in South Korea. These findings significantly enhance the current understanding of fungal biodiversity within this region and also provide essential foundational data for advancing local and international mycological research.

This study was conducted to provide comprehensive information on the current status, constraints, and policy responses regarding rice cultivation in Uzbekistan for researchers and policymakers engaged in rice production in Central Asia. Despite annual fluctuations, Uzbekistan’s rice cultivation area has consistently exceeded 100,000 hectares each year. The yield per unit area improved by 19.2%, increasing from 4.21 t/ha in 2021 to 5.02 t/ha in 2024. In terms of cultivation methods, the proportion of doub le c ropping rose f rom 50.7% t o 71.6%, a lthough productivity remained h igher in s ingle cropping (5.35 t/ha) compared to double cropping (4.88 t/ha). Rice demonstrated an economic advantage of 2-5 times per hectare compared to major crops such as wheat, corn, and cotton. However, domestic production growth has not kept pace with rising consumption demands, leading to a sharp increase in imports, from 9,000 tons in 2019 to 108,800 tons in 2023. The structure of rice imports is shifting from a heavy reliance on Kazakhstan (90%) toward diversification, including partnerships with Pakistan, Thailand, and other countries. Major constraints to rice production in Uzbekistan include an arid climate, chronic irrigation water shortages, and soil salinization, which affects 50-70% of irrigated farmland. In response, the government established a comprehensive development strategy through Cabinet Resolution No. 986 in 2019 and is currently promoting economies of scale by establishing 42 clusters across 8 provinces (covering 41,440 hectares, or 29.7% of the total area). To address water scarcity, laser land leveling technology has been implemented on over 700,000 hectares as of 2024, aimed at reducing irrigation water usage and increasing yields, with plans to further expand water-saving cultivation technologies. In terms of international cooperation, the KOPIA project is enhancing quality seed production and distribution, as well as establishing machine transplanting cultivation technology. Partnerships with IRRI and participation in the Council for Partnership on Rice Research in Asia (CORRA) are strengthening the development of climate- adaptive varieties and international networks. Overall, Uzbekistan’s rice industry has the strategic potential to contribute significantly to food security, rural economic development, and regional trade activation through systematic policy implementation and enhanced international cooperation.

This study explores the transformative impact of artificial intelligence (AI) on the structure of the music industry and the evolving patterns of digital music consumption. The research aims to investigate how AI-driven music platforms foster new forms of user engagement, leading to a paradigm shift from passive listening to active participation and co-creation. Traditionally, digital music consumption has centered on streaming and algorithmic recommendations. However, with the advent of AI technologies, users are increasingly engaging in personalized experiences, interactive creation, and collaborative musical expression. Drawing upon theoretical frameworks of digital consumption and user engagement, this study reviews the evolution of music consumption behaviors and examines key AI music platforms such as Spotify’s AI DJ, Boomy, and Mubert. Through case analysis, the research identifies how personalized recommendations, generative AI music composition, and interactive interfaces enhance user motivation, emotional involvement, and behavioral participation. The findings reveal that AI music platforms not only provide tailored listening experiences but also empower users to take part in music creation, transforming their role from passive consumers to active co-creators. This shift signifies a broader transformation in the digital music ecosystem, where consumption becomes a participatory and expressive act. Ultimately, the study highlights how the integration of AI and user engagement is redefining the meaning of music consumption, generating new cultural and economic value within platform-based ecosystems. The results provide theoretical and practical implications for future music industry strategies and platform business models.

This study explores the expressive characteristics of new media fashion collections, which have emerged through the convergence of fashion and digital technologies. As new media develops with the integration of old media, fashion collections are increasingly functioning as media tools to convey identity, narrative, and artistic intent beyond aesthetic presentation. Through a literature review and case analysis of collections from 2000 S/S to 2025 S/S, this study defines the term ‘new media fashion collection’ and investigates its communicative functions. The findings reveal that such collections embody the significance of the expansion of space-time, evolution of expression methods, and decentralization of experience, while diversifying meanings and modes of expression based on new media attributes such as extensibility, integrativeness, and interactivity. More specifically, their expressive characteristics can be understood through four characteristics: the direct representation through borrowing, the diversity of message expression, the immersion through unreality, and the narrative construction via editing. Collectively, these characteristics demonstrate how new media fashion collections emphasize themes by using digital technology to borrow or transform old media content. Digital technologies allow fashion collections to unfold across limitless space-time dimensions, positioning them as versatile communication media and enhancing expressive possibilities. These approaches reflect how fashion collections in the digital era integrate technological elements to enrich communication and viewer engagement. This research contributes to the positioning of fashion collections as a form of media and offers a framework for analyzing their evolving expressions. Further, it highlights the need for continued interdisciplinary research bridging fashion, technology, and media theory.

본 연구는 환경 요인을 바탕으로 절화용 국화 생장 예측을 위한 최적의 모델을 개발하는 것을 목표로 하였다. 이를 위해 13개의 모델(Linear Regression, Lasso Regression, Ridge Regression, ElasticNet Regression, K-Nearest Neighbors (KNN), Support Vector Regression (SVR), Neural Network, Decision Tree, Random Forest, XGBoost, AdaBoost, CatBoost, Stacking)의 성능을 R2, MAE, RMSE를 평가 지표 로 비교하였다. 단일 모델 중에서는 Decision Tree가 가장 우수한 성능을 보였으며, R2값은 0.90에서 0.91 사이였다. 앙 상블 모델 중에서는 CatBoost가 가장 높은 성능을 보였으며 (R2=0.90~0.92) Random Forest와 XGBoost 또한 유사한 성 능을 보였다. 전체적으로 트리 기반 앙상블 모델이 국화 생장 예측에 적합한 모델로 나타났다.

Virtual Reality Head Mounted Display (VR HMD)-based flight simulators have recently emerged as promising tools for enhancing pilot training effectiveness. This study aims to establish a set of evaluation criteria for the development of VR HMD-based flight simulators and to determine their relative importance and priority using the Analytic Hierarchy Process (AHP). Through an extensive review of the literature, a hierarchical evaluation model was constructed, consisting of three primary criteria and ten sub-criteria. A structured questionnaire was administered to experienced pilots, and the collected data were analyzed using the AHP methodology to assess the relative weights of each criterion. The analysis revealed that the fidelity of system performance is the most influential factor in evaluating VR HMD-based flight simulators. These findings present a structured evaluation framework and offer practical insights for guiding the strategic development and optimization of VR HMD-based flight training systems.