Kori Unit 1, the first commercial nuclear power plant (NPP) in Korea, was permanently shut down in 2017 and was scheduled for decommissioning. Various programs must be planned early in the decommissioning process to safely decommission NPPs. Radiological characterization is a key program in decommissioning and should be a high priority. Radiological characterization involves determining the decommissioning technology to be applied to a nuclear facility by identifying the radiation sources and radioactive contaminants present within the facility and assessing the extent and nature of the radioactive contaminants to be removed from the facility. This study introduces the regulatory requirements, procedures, and implementation methods for radiological characterization and proposes a methodology to link the results of radiological characterizations for each stage. To link radiological characteristics, this study proposes to conduct radiological characterization in the decommissioning phase to verify the results of radiological characterization in the transitional phase of decommissioning NPPs. This enables significantly reducing the scope and content of radiological characterization that must be performed in the decommissioning phase and maintaining the connection with the previous phase.

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).

본 연구를 통해 미기록종 Acronicta gigasa (큰뿔무늬저녁나방, 신칭)를 한국에 최초로 보고한다. 이 종에 대한 진단과 분류학적 기재문을 작성 하였고, 성충과 생식기 도해사진을 함께 제공하였다.

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.

Because plastics are cheap and light, their use is indispensable in our daily lives. However, the extensive use of plastics causes the disposal issue. Among various disposal processes, plastic recycling is of great attention because of minimizing waste and harmful byproducts. Herein, we recycle the most popular thermoplastic materials, high-density and low-density polyethylene, producing the anode materials for the Li-ion batteries. The electrochemical properties of the as-recycled soft carbon are investigated to study the energy storage capability as the anode of Li-ion batteries. Our work demonstrates the soft carbon recycled from plastic wastes is a promising anode material.

High-entropy alloys (HEAs) have been reported to have better properties than conventional materials; however, they are more expensive due to the high cost of their main components. Therefore, research is needed to reduce manufacturing costs. In this study, CoCrFeMnNi HEAs were prepared using metal injection molding (MIM), which is a powder metallurgy process that involves less material waste than machining process. Although the MIM-processed samples were in the face-centered cubic (FCC) phase, porosity remained after sintering at 1200°C, 1250°C, and 1275°C. In this study, the hot isostatic pressing (HIP) process, which considers both temperature (1150°C) and pressure (150 MPa), was adopted to improve the quality of the MIM samples. Although the hardness of the HIP-treated samples decreased slightly and the Mn composition was significantly reduced, the process effectively eliminated many pores that remained after the 1275°C MIM process. The HIP process can improve the quality of the alloy.

The development of thermoelectric (TE) materials to replace Bi2Te3 alloys is emerging as a hot issue with the potential for wider practical applications. In particular, layered Zintl-phase materials, which can appropriately control carrier and phonon transport behaviors, are being considered as promising candidates. However, limited data have been reported on the thermoelectric properties of metal-Sb materials that can be transformed into layered materials through the insertion of cations. In this study, we synthesized FeSb and MnSb, which are used as base materials for advanced thermoelectric materials. They were confirmed as single-phase materials by analyzing X-ray diffraction patterns. Based on electrical conductivity, the Seebeck coefficient, and thermal conductivity of both materials characterized as a function of temperature, the zT values of MnSb and FeSb were calculated to be 0.00119 and 0.00026, respectively. These properties provide a fundamental data for developing layered Zintl-phase materials with alkali/alkaline earth metal insertions.

The pet industry, especially pet food, is experiencing rapid growth. This growth is accompanied by increasing concerns about pets' gut health, as an imbalanced microbiota can lead to various diseases. This study analyzes global patent trends in microbiome-based technologies for treating pet digestive issues using the WIPS database across major markets. Of 1,194 patents identified, 394 key references were examined, highlighting the increasing number of probiotic and microbiome-related patents since 2016. China dominates this sector, followed by Korea, Japan, and the United States. The findings provide a foundation for advancing microbiome-driven solutions for pet digestive ailments.

목적 : 광학 시뮬레이션 프로그램을 통해 Gullstrand 모형안을 입체적으로 설계하여, 정시와 굴절이상을 구현하 였다. 이를 이용하여 망막 상의 해상도 변화를 확인하고 정량적인 분석법을 제시하고자 하였다. 방법 : 3D 광학 시뮬레이션 프로그램인 Ansys SPEOS Ver. 2012(ANSYS Inc., USA)를 이용하여 모형안을 설계하였으며, 각막 전면 곡률반지름을 변화시켜 근시 및 원시의 굴절이상을 구현하였다. 각막 전면에서 우측 24.00, 24.38 및 25.00 mm 떨어진 위치에 탐지기를 설치하여 위치에 따른 상의 변화를 분석하였다. 굴절이상의 정도와 검출기 위치에 따른 상의 겉보기 해상도, 세기 분포, 가시성, 선명도를 확인하였으며 도출하였으며, 최종적 으로 정량적 해상도를 계산하였다. 결과 : 망막 상의 겉보기 해상도는 근시는 망막 앞에, 그리고 원시는 망막 뒤에 결상된 상에서 가장 우수한 결과 를 보였다. 세기 분포는 24.76 mm에서 +1.00과 +2.00 D가 모두 유사하게 높은 것으로 나타나 겉보기 해상도와 일부 차이를 보였다. 가시성은 24.00 mm에서 –2.00과 –1.00 D, 24.38 mm에서 –1.00과 +0.00 D, 24.76 mm에 서 +1.00과 +2.00 D가 높게 측정되었다. 선명도는 24.00 mm에서 –2.00 D, 24.38 mm에서는 -1.00 D, 그리고 24.76 mm에서는 +1.00 D에서 가장 높게 측정되었다. 이로써 가시성과 선명도 값은 위치와 굴절이상도에 따른 서로 다른 결과로 분석되었다. 정량적인 해상도는 24.00 mm에서 –2.00 D, 24.38 mm에서 –1.00과 +0.00 D, 24.76 mm에서 +1.00 D가 가장 우수하게 분석되었으며, 겉보기 해상도와 잘 일치하는 것이 확인되었다. 결론 : 본 연구에서 제안된 망막 상의 정량적 해상도 분석 결과를 통해 상대적으로 비교가 까다로운 망막 상에 대하여 정량적으로 명확한 분석이 가능할 것으로 판단된다.

Nursing research in veterinary hospitals is critical to the work of veterinary nursing and is necessary for continued advancements that promote optimal nursing care. Since the work of veterinary nursing involves animals with whom communication is difficult, the level of work performance can vary greatly depending on the experience, knowledge, and abilities of each animal nurse. In addition, veterinary nursing might establish a successful work environment through collaboration with veterinarians, and smooth work cooperation and communication among hospital members are direct factors in improving the work performance of animal hospitals. Because the work of nursing shows significant differences in performance depending on the individual, much research is being conducted to develop tools to measure work performance in the veterinary nursing field of medical assistants. In the present study, we attempted to develop a work performance measurement tool that is useful and suitable for veterinary nursing using the Delphi method. As a result of this study, an 18-item questionnaire was developed to measure the work performance of veterinary nursing, and these evaluation items were found to have excellent suitability in terms of content and construct validity. The evaluation scale of work performance of animal nurses developed through this study is believed to be useful in evaluating work performance in terms of work performance ability, attitude, and work performance relationship. Additionally, it is considered that the results of this study can be actively used to understand and develop the work relationships of veterinary nursing.

This study was conducted to collect the patents of microbiome-based treatment technology for pets. An electronic search for microbiome or probiotics in brain nervous system disease was studied using the WINTELIPS database. Patent Cooperation Treaty of Korea, Japan, the EU, the US, and China that were registered by October 31, 2022 were selected in this study. A total of 206 patents were included for final analysis. Since 2016, patent activity has shown an explosive increase in recent years. China is the leading market in this technology field, and Korea has the second-highest market share. To provide the groundwork for the next research and development, we examined the industrial trend of microbiome for brain nervous system diseases in this study using an analysis of patents that have been applied for and registered up to this point. Looking at the overall patent trends by year in the technology field related to treating of brain and nervous system diseases using the microbiome, there was a tendency to repeat increasing and decreasing trends. However, considering 2021 and 2022, which have undisclosed sections, it can be seen that patent activity has tended to increase explosively in recent years, starting in 2016. If related studies use the patent analysis data constructed in this way strategically, it is expected that it will lead to patent registration and the development of new products, ultimately contributing to the revitalization of the companion animal industry.

This study introduces a novel approach for identifying potential failure risks in missile manufacturing by leveraging Quality Inspection Management (QIM) data to address the challenges presented by a dataset comprising 666 variables and data imbalances. The utilization of the SMOTE for data augmentation and Lasso Regression for dimensionality reduction, followed by the application of a Random Forest model, results in a 99.40% accuracy rate in classifying missiles with a high likelihood of failure. Such measures enable the preemptive identification of missiles at a heightened risk of failure, thereby mitigating the risk of field failures and enhancing missile life. The integration of Lasso Regression and Random Forest is employed to pinpoint critical variables and test items that significantly impact failure, with a particular emphasis on variables related to performance and connection resistance. Moreover, the research highlights the potential for broadening the scope of data-driven decision-making within quality control systems, including the refinement of maintenance strategies and the adjustment of control limits for essential test items.