This study examined how learners’ use of ChatGPT (GPT-4) during a revision task was associated with changes in second language (L2) writing performance and explored its relationship with learners’ level of language analytic ability (LAA), as well as their perceptions of the revision process. Twenty-six Korean university students completed IELTS Academic Writing Task 2 essays before and after a ChatGPT-supported revision activity. Writing performance was evaluated in terms of task response, coherence and cohesion, lexical resource, and grammatical range and accuracy. LAA was measured using an artificial-language rule-induction test, and learner perceptions were collected through surveys and interviews. Results showed gains across all assessed dimensions following the revision activity. Correlational analyses indicated that LAA was associated with improvements in grammatical accuracy and task response, but not with lexical resource. Learners generally perceived ChatGPT as helpful for identifying issues and supporting revision, while also noting the cognitive effort required to engage with its feedback. These findings suggest that ChatGPT can function as a useful tool for supporting L2 writing revision; however, the extent to which learners benefit from such support may depend, in part, on their language analytic ability.

본 연구는 경상북도 안동시와 영양군의 고추 주산지를 대상으로 고추 품종의 생육 특성과 수량을 조사하고 SIMPLE 작물모델의 예측 성능을 평가하기 위해 수행되었다. 시험에는 기존 품종 2개와 신육성 품종 5개를 포함한 총 7개 품종이 사용되었으며, 육종가가 제공한 성능 자료를 바탕으로 적응형(adaptive)과 회복형(resilience) 그룹 으로 분류하였다. 2019년부터 2023년까지의 기온 자료를 분석한 결과 두 지역 간 기후 차이는 미미하였으며, 두 지 점 모두 작기 종료 시점에 약 1,800°C·day의 GDD가 누적되었다. 적응형 품종은 밀집형 수관 구조와 더 많은 영양 생장 바이오매스를 나타낸 반면, 회복형 품종은 개방형 수관 구조와 신장된 절간을 보였다. 생식효율의 지역적 차 이가 뚜렷하여, 안동에서는 두 그룹의 최종 수량이 유사하였으나 영양에서는 적응형 품종의 수량이 유의하게 높았 다. SIMPLE 모델은 잎 노화 및 성숙과실로의 동화산물 재분배에 따른 작기 후반부 바이오매스 감소를 반영하기 위 해 1차 감쇠항(first-order decay term)을 도입하여 수정되었다. 캘리브레이션 결과 두 지역에서 서로 다른 매개변수 세트가 도출되었으며, 안동은 빠른 초기 생장, 높은 광이용효율, 낮은 내고온성을, 영양은 점진적 생장, 높은 내고온 성, 높은 수확지수를 특징으로 하였다. 모델 성능은 지점-품종 조합에 따라 상당한 변이를 보였으며, 이는 예측 정확 도가 품종 특성과 미환경 조건 간 상호작용에 의해 결정됨을 시사하였다. 한국의 다양한 고추 생산환경에서 모델의 강건성과 전이성을 향상시키기 위해서는 지역 특이적 캘리브레이션과 기계론적으로 개선된 노화 모듈이 필수적이 며, 다년차·다지점 검증과 불확실성 분석이 향후 우선 과제로 제시된다.

Constructing high-density single-walled carbon nanotubes (SWCNTs) network assemblies is essential for improving their electrical conductivity. However, controlling the nanoporosity, including specific surface area (SSA) and pore structure, is critical for maintaining reversible capacity in CNT-based energy storage systems. In this study, we investigated a solution-based strategy using acid and surfactant treatments to enhance the electrical conductivity of SWCNT networks while minimizing changes in nanoporosity. HNO3/H2SO4 acid treatment and sodium dodecyl benzene sulfonate (SDBS)- assisted dispersion were applied to form uniform, densely packed SWCNT assemblies. Acid treatment increased the SSA from 246 to 732 m2 g⁻1 and the micropore volume from 0.06 to 0.28 mL g⁻1. In contrast, SDBS treatment moderately increased the SSA (246 to 350 m2·g⁻1) with minor changes in meso/microporosity and preserved the overall pore structure well. In addition the electrical conductivity increased by a factor of 3.5 after acid treatment and by a factor of 6 after SDBS treatment, reaching 1.39 × 105 and 2.36 × 105 S m⁻1, respectively. These results demonstrate that SDBS treatment, via surfactant-driven reassembly, offers a simple, scalable, and structure-preserving strategy to tailor nanoporosity and enhance the performance of SWCNT-based electrochemical devices.

장미 ‘Sahara’는 국립원예특작과학원에서 2022년에 육성한 분홍톤 아이보리 스프레이 장미 품종으로 2013년 빨간색 스프레 이 품종 ‘Fangfare’에 아이보리색 스프레이 품종 ‘Vivien’을 부본으로 인공 교배 하였다. 총 73개의 교배 실생을 얻었으며 2015년부터 1, 2, 3차 특성검정을 통해,화색과 화형이 안정적이 며 생산성 및 절화 특성이 우수한 ‘원교 D1-360’을 최종 선발하 여 2022년 ‘Sahara’로 명명하고 국립종자원에 품종보호 출원· 등록하였다(등록번호 제9771호). 장미 ‘Sahara’ 품종은 분홍톤 크림색(155D)의 꽃잎수는 71.5매인 겹꽃으로 화폭과 화고는 각각 4.9, 3.1cm이며 소화수가 7.4개/줄기인 스프레이 장미이 다. 장미 ‘Sahara’ 품종의 절화장은 평균 73.8cm로 대조 품종 ‘Pink shin’56.9cm 대비 길며, 절화 수명은 약 17.8일로 ‘Pink shin’ 15.6일 보다 2일 정도 길다. ‘Sahara’는 절화 생산량은 연간 168본/m2로 ‘Pink Shine’ 140본 대비 생산량이 많다. 전자코를 이용한 PCA분석결과 주성분1과 2는 각각 99.3%와 0.6%로 전체 변이량의 99.9%를 반영하고 있다. Rader plot 분석결과 P10/2,P40/1 및 T30/1 센서 반응이 높았으며 총 6개 센서에서 모두 ‘Sahara’는 대조품종 ‘Pink Shine’에 비해 반응이 낮았다. 절화용 스프레이 장미 ‘Sahara’ 품종은 파스텔톤 의 중형 소화로, 균일한 절화 품질 및 우수한 수량으로 재배농가 의 선호도가 높아 국내에서 많이 재배될 것으로 기대된다.

Background: Hallux valgus (HV) is a common forefoot deformity that can lead to pain, altered gait, and musculoskeletal dysfunctions. Accurate severity assessment is essential for clinical decision-making, yet radiographic methods, though accurate—are costly and less accessible. Objects: This study aimed to develop and clinically validate an end-to-end artificial intelligence (AI)-based mobile application for HV severity classification from smartphone-captured dorsal foot photographs. Methods: The study comprised two phases. In Phase 1 (App & Model Development), we developed a mobile application integrating foot Red-Green-Blue (RGB) image capture, HV severity classification, and immediate reporting. Paired (weight-bearing anteroposterior foot) radiographs and smartphone dorsal foot photographs were collected from 180 adults with HV. Radiographic HV angle and intermetatarsal angle were measured to categorize severity (mild, moderate, severe) as ground truth. A MobileNetV2 convolutional neural network (CNN) was trained on dorsal foot images to predict severity. In Phase 2 (External Validation & Usability Assessment), 30 independent participants underwent both radiographic and app-based severity assessments. Diagnostic times were recorded for both assessments. Participants then completed a 10-item Likert-scale usability questionnaire, with internal consistency assessed using Cronbach’s α. Results: The CNN successfully classified HV severity based on radiographic ground truth and showed consistent performance on an external dataset. App-based assessment was on average approximately 12 minutes faster than radiographic evaluation (p < 0.001). Usability evaluation indicated positive user experience (overall mean = 3.84/5, Cronbach’s α = 0.706). Conclusion: This study presents fully operational mobile AI application that enables rapid, accurate, and user-friendly classification of HV severity directly from smartphone photographs. By combining machine learning with an accessible mobile platform, it can support point-ofcare screening, patient self-monitoring, and community-based care where radiographic evaluation is impractical.

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.

Pine wilt disease (PWD), caused by the pine wood nematode (Bursaphelenchus xylophilus), is a major threat to Pinus thunbergii forests in South Korea. Although climatic conditions are known to affect the spread of PWD, the specific influences of temperature and geography on nematode density and tree mortality remain unclear. This study assessed monthly PWN density and black pine mortality across three regions—two coastal (Geoje and Sacheon) and one inland (Jinju)—from 2021 to 2023. Nematode density and tree mortality consistently peaked in autumn across all regions. A strong positive correlation was observed between nematode density and tree mortality (r = 0.7468, p < 0.01), while temperature showed no significant correlation with either variable. These results indicate that PWD severity is more closely tied to nematode activity than to temperature alone, and that regional and seasonal variability must be considered in disease assessment. The findings highlight the need for region-specific monitoring and management strategies that prioritize high-risk periods, particularly autumn, when nematode activity and disease expression are most pronounced. This research provides essential data to support adaptive PWD control programs under changing climatic conditions.