The Yeongsan River is a prominent inland waterway, alongside the Han River, Nakdong River, and Geum River in South Korea. Numerous bacterial strains were isolated from the Yeongsan River basin for a comprehensive investigation into indigenous prokaryotic species conducted between 2020 and 2023. These bacterial strains were identified using 16S rRNA gene sequencing, wherein 45 bacterial strains shared >98.7% sequence similarities with bacterial species not recorded in Korea thus far. Therefore, this study aimed to catalogue aforementioned unrecorded species and characterize them contingent upon their Gram nature, colony and cell morphologies, biochemical properties, and phylogenetic positions. These bacterial species were determined to be phylogenetically diverse. They were categorized into nine classes, 18 orders, and 25 families. These previously unrecorded species were classified into the following genera and classes: Chitinophaga (class Chitinophagia); Flavobacterium (class Flavobacteriia); Rhodopseudomonas, Gemmobacter, Paracoccus, Azospirillum, Sphingomonas, Novosphingobium, Sphingorhabdus, and Erythrobacter (class Alphaproteobacteria); Bordetella, Pararobbsia, Polynucleobacter, Rhodoferax, Aquabacterium, Malikia, Comamonas, Ideonella, Paucibacter, Undibacterium, Cupriavidus, and Thauera (class Betaproteobacteria); Pectobacterium, Arenimonas, Lysobacter, and Luteimonas (class Gammaproteobacteria); Luteolibacter (class Verrucomicrobiia); Mycolicibacterium, Angustibacter, Ornithinibacter, Janibacter, Schumannella, Aurantimicrobium, Luedemannella, Nocardioides, and Propionicimonas (class Actinomycetes); Geothrix (class Holophagae); and Lactococcus (class Bacilli).

국립원예특작과학원에서는 밝은 화색과 안정적인 화형의 생 육이 우수한 빨간색 스탠다드 장미 품종을 육성하기 위해 진한 적색 스탠다드 장미 품종 ‘엔드리스러브(Endless Love)’를 모 본으로, 꽃잎수가 많고 안정적으로 가시가 적은 밝은 노란색 ‘페니레인(Penny Lane)’ 품종을 부본으로 인공교배하였다. 37 개의 교배실생을 양성해 1, 2, 3차에 걸친 특성검정 및 현장실증 을 통해 꽃이 크고 화형이 안정적이며, 재배안정성 및 생산성, 절화특성이 우수한 ‘원교 D1-390’을 최종 선발하였다. 2023년 ‘루비레드(Ruby Red)’로 명명하여 국립종자원에 품종보호출원·등록되었다. ‘루비레드’ 품종은 밝은 적색(R53C)을 가졌으 며, 꽃잎수가 32.8매, 화폭과 화고는 각각 10.9, 5.9cm로 대조 품종보다 크다. 절화장은 평균 71.7cm, 절화수명은 약 16.7일, 수량은 연간 168대/m2로 대조품종인 ‘레드스퀘어(Red Square)’ 대비 절화장이 길고 절화수명도 2배 이상 길며, 수확량도 1.4배 우수하다. 2023년 국내 육성 장미 품종 서울식물원 관람객 대상 공동평가회에서 스탠다드 장미 중 우수한 평가를 받았으며, 현 장 실증 결과 농가별로 균일하고 우수한 수량과 절화품질을 보 였다. 절화용 장미 ‘루비레드’ 품종은 밝은 적색과 우수한 화형 을 가지는 품종으로 해외 대체 품종으로 국내에서 많이 재배될 것으로 기대된다.

We aimed to evaluate the effectiveness of ensemble optimal interpolation (EnOI) in improving the analysis of significant wave height (SWH) within wave models using satellite-derived SWH data. Satellite observations revealed higher SWH in mid-latitude regions (30o to 60o in both hemispheres) due to stronger winds, whereas equatorial and coastal areas exhibited lower wave heights, attributed to calmer winds and land interactions. Root mean square error (RMSE) analysis of the control experiment without data assimilation revealed significant discrepancies in high-latitude areas, underscoring the need for enhanced analysis techniques. Data assimilation experiments demonstrated substantial RMSE reductions, particularly in high-latitude regions, underscoring the effectiveness of the technique in enhancing the quality of analysis fields. Sensitivity experiments with varying ensemble sizes showed modest global improvements in analysis fields with larger ensembles. Sensitivity experiments based on different decorrelation length scales demonstrated significant RMSE improvements at larger scales, particularly in the Southern Ocean and Northwest Pacific. However, some areas exhibited slight RMSE increases, suggesting the need for region-specific tuning of assimilation parameters. Reducing the observation error covariance improved analysis quality in certain regions, including the equator, but generally degraded it in others. Rescaling background error covariance (BEC) resulted in overall improvements in analysis fields, though sensitivity to regional variability persisted. These findings underscore the importance of data assimilation, parameter tuning, and BEC rescaling in enhancing the quality and reliability of wave analysis fields, emphasizing the necessity of region-specific adjustments to optimize assimilation performance. These insights are valuable for understanding ocean dynamics, improving navigation, and supporting coastal management practices.

Carbon fusion is important to understand the late stages in the evolution of a massive star. Astronomically interesting energy ranges for the 12C+12C reactions have been, however, poorly constrained by experiments. Theoretical studies on stellar evolution have relied on reaction rates that are extrapolated from those measured in higher energies. In this work, we update the carbon fusion reaction rates by fitting the astrophysical S-factor data obtained from direct measurements based on the Fowler, Caughlan, & Zimmerman (1975) formula. We examine the evolution of a 20M⊙ star with the updated 12C+12C reaction rates performing simulations with the MESA (Modules for Experiments for Stellar Astrophysics) code. Between 0.5 and 1 GK, the updated reaction rates are 0.35 to 0.5 times less than the rates suggested by Caughlan & Fowler (1988). The updated rates result in the increase of core temperature by about 7% and of the neutrino cooling by about a factor of three. Moreover, the carbon-burning lifetime is reduced by a factor of 2.7. The updated carbon fusion reaction rates lead to some changes in the details of the stellar evolution model, their impact seems relatively minor compared to other uncertain physical factors like convection, overshooting, rotation, and mass-loss history. The astrophysical S-factor measurements in lower energies have large errors below the Coulomb barrier. More precise measurements in lower energies for the carbon burning would be useful to improve our study and to understand the evolution of a massive star.