A survey of plant-parasitic nematodes (PPNs) was carried out in medicinal crop cultivated fields from July to August in 2023. Three-leaf ladybell, Adenophora triphylla var. japonica is a highly valued medicinal plant that is used to treat or prevent bronchitis, cough, cancer, and obesity in Korea. A. triphylla plants with small root-galls were observed in a field of Yeongju Agricultural Technology Center, which were identified as a root-knot nematode. Additional morphological and molecular analyses studies were performed and identified as Meloidogyne hapla, Northern root-knot nematode. Population densities of M. hapla ranged from 20~30 nematodes per 100 cm3 of soil. M. hapla was detected at lower densities in soil compared to other infected host crops, but there are concerns about damage to M. hapla since A. triphylla is cultivated for more than two years once planted. Our results indicate that A. triphylla roots damage by M. hapla were identifed, it is necessary to prepare control methods such as registration of applicable nematicides and crop rotation.

As the importance of online virtual spaces increases due to COVID-19, interest in online virtual spaces using 4th industrial technology is increasing. Accordingly, the metaverse that combines virtual and real is becoming an issue. In the fashion industry, marketing using online is gradually increasing, and various attempts are being made by converging with the metaverse to provide new and enjoyable experiences to customers. This study looked at the impact of customer experience of a luxury fashion brand pop-up store on customer satisfaction, affective commitment and brand loyalty in a metaverse environment where utilization is increasing due to COVID-19 and technological development. For the analysis data of this study, a survey was conducted on the users who experienced the metaverse platform Zepeto's ' BVLGARI World'. As a result of examining the effect of the customer experience of a luxury fashion brand pop-up store on customer satisfaction, affective commitment, and brand loyalty in a metaverse environment, some of the customer experiences affect customer satisfaction, and the proposed hypothesis was partially accepted. In addition, it was confirmed that customer satisfaction affects affective commitment and brand loyalty, and affective commitment affects brand loyalty. In this study, we examine the impact of the customer experience of a luxury fashion brand pop-up store on customer satisfaction, affective commitment, and brand loyalty in the metaverse environment, and identify what is needed for more active convergence and activation of the metaverse and fashion brands. Also, we provide practical implications to people who involved in the metaverse and the fashion industry.

In the event of a radioactive release, it is essential to quickly detect and locate the source of the release, as well as track the movement of the plume to assess the potential impact on public health and safety. Fixed monitoring posts are limited in their ability to provide a complete picture of the radiation distribution, and the information they provide may not be available in real-time. This is why other types of monitoring systems, such as mobile monitoring, aerial monitoring, and personal dosimeters, are also used in emergency situations to complement the information provided by fixed monitoring posts. Also, the monitoring system can be improved by using the Kriging technique, which is one of the interpolation methods, to predict the radiation dose in the relevant districts. This can be achieved by utilizing both the GPS information and the radiation dose measured at a particular point. The Kriging method involves estimating the value between different measurement points by considering the distance between them. The model used GPS and radiation data that were measured around the Hanbit NPP. The data were collected using a radiation measuring detector on a bus that traveled around the NPP area at 2-second intervals for one day. From the collected data, 200 data points were randomly selected for analysis, excluding the data measured at the bus garage out of a total of 16,550 data points. The average dose of the daily measurement data was 117.94 nSv/h, and the average dose of the 200 randomly extracted data was 119.17 nSv/h. The GPS and radiation dose data were utilized to predict the radiation dose around the Yeonggwang area where the Hanbit NPP is located. In the event of an abnormal release of radioactive material, it can be difficult to accurately determine the dose unless a monitoring measurement point is present. This can delay the rapid evacuation of residents during an emergency situation. By utilizing the Kriging model to make predictions, it is anticipated that more accurate dose predictions can be generated, particularly during accident scenarios. This can aid in the development of appropriate resident protection measures.

The objective of this experiment was to investigate the effect of drip irrigation volume on tomatoes (Solanum lycopersicum L.) grown in a greenhouse using perlite medium. Plants were treated by three different irrigation treatment I0, I25, and I50 (where irrigation volume of I25 and I50 was 25% and 50% higher than I0, having limited or no leaching). Growth characteristics of plants, yield and water use efficiency were measured. The result showed that plant height, leaf length and leaf width were lowest in the I0 treated plants. However, these parameters were not statistically significant differences between the plants that were grown in the I25 and I50 treatment. Soluble solids content, acidity and dry matter of 111th, 132nd, and 143rd days harvested tomato were higher in the plants irrigated with lowest volume (I0) than the higher volume (I25 or I50). In addition, water content was lower in the 111th and 132nd days of harvested tomatoes from the I0 treatment. The number of big-size tomatoes (>180 g) was significantly higher in the I25 irrigated plants. There was no significant difference in the total number of harvested fruits among the treatments. The average fruit weight and total yield of harvested tomatoes were lowest in the I0 treated plants. The water consumption of tomato was not significantly different amongst the treatments but water use efficiency was lowest in the I0 treatment. Principal component analysis revealed that total soluble solid and acidity of tomato showed a positive correlation between each other. These results suggest that I25 was the optimum irrigation treatment for tomato based on its measured growth characteristics, yield and water use efficiency.

Since radon was detected in mattresses of famous bed furniture brands in 2018, the nuclear safety and security commission (NSSC) announced the radiation safety management act in April 2021 to protect the public health and environment. This act stipulates the safety management of radiation that can be encountered in the natural environment such as the notification of radioactivity concentration of source materials, process by-products, the installation and operation of radioactive monitors. In this study, a model was established to predict radioactive exposure dose from radioactive materials such as radon and uranium detected in consumer products such as bed mattresses, pillows, shower, bracelets and masks in order to identify major radioactive substances that largely affect the exposure dose. A period of seven years from 2014 to 2020 was investigated for the source materials and exposure doses of consumer products containing naturally occurring radioactive materials (NORMs). We analyzed these using machine learning models such as classification and regression tree (CART), Random Forest and TreeNet. Index development and verification were performed to evaluate the predictive performance of the models. Overall, predictive performance was highest when Random Forest or TreeNet was used for each consumer product. Thoron had a great influence on the internal exposure dose of bedding, clothing and mats. Uranium had a great influence on the internal exposure dose of other consumer products except whetstones. When the number of data is very small or the missing value rate is high, it is difficult to expect accurate predictive performance even with machine learning techniques. If we significantly reduce the missing value rate of data or use the limit of detection value instead of missing values, we can build a model with more accurate predictive performance.

The poor durability issue of polymer electrolyte membrane fuel cells is a major concern in terms of their commercialization. To understand the degradation mechanism of the catalysts, an accelerated durability test (ADT) was conducted according to the protocol established by internationally accredited organizations. However, reversible and irreversible factors contributing to the loss of activity have not yet been practically segregated because of the limitations of a batch-type three-electrode system, leading to the misunderstanding of the deactivation mechanism. In this study, we investigated the effect of a fresh electrolyte on the ADT and recovery process. When the fresh electrolyte was used at every range of the cycle, the chances of incorrect detection of dissolved CO and Pt ions in the electrolyte were very low. When the same electrolyte was used throughout the test, the accumulated Pt ions were deposited on the surface of the Pt nanoparticles or carbon support, affording an increased electrochemical surface area (ECSA) of Pt. Therefore, we believe that periodic replacement by a fresh electrolyte or a continuous-flow electrolyte is essential for the precise determination of the structural and electrochemical changes in Pt/C catalysts.

본 논문에서는 고리 1호기 해체 비용 추정을 위해 외국 원자력발전소 해체 비용 데이터를 현가화한 후 원자력발전소 해체 비용 추정 회귀 분석모델을 개발하였다. 이 모델 개발에 사용된 데이터는 해체 또는 진행 중인 BWR 13기, PWR 16기의 해체 비용 데이터이다. 회귀 분석모델 도출을 위해, 해체 비용을 종속변수로 정하고, 해체 원전의 운전 특성을 반영할 수 있게 고 안된 Contamination factor와 해체 기간을 독립변수로 선정하였다. 빅데이터 분석 도구인 R language의 통계패키지를 이용 하여 회귀 분석모델을 도출하였다. 이 회귀 분석 모델을 적용하여 고리 1호기 해체 비용을 예측한 결과, 미화 663.40~928.32 백만 달러, 한화 약 7,828.12억~1조 954.18억 원이 소요될 것으로 예측되었다.

This study analyzed what premium features significantly affect customer satisfaction and their recommendation, and what factors significantly affect product attributes. In the process, first, the loyalty program and the customer compensation program were studied to determine the impact of the customer satisfaction and recommendation. The study analyzed that quality and design of product properties had significant effects on all factors, but the brand was not significantly affected. Second, while superiority, differentiation and scarcity of luxury items are significant to customer satisfaction but superiority is only significant in relation to recommendation intention. Third, the preceding study shows that the customer compensation program has a significant impact on sales growth, but the study found that it was not for imported luxury car customers. Fourth, if the royalties program is low in awareness, it has been analyzed that the scarcity and customer satisfaction relationships among luxury goods have been adjusted. On the contrary, if there is a high level of awareness, it is analyzed that there is a control effect customer satisfaction and differentiation among luxury brands. In the conclusion, in order to satisfy customers at the import luxury car market, the differentiation of luxury goods by standard index must be strengthened and the brand must be strengthened among the attributes of the product. In addition, by raising awareness of the royalties program, the relationship between differentiation and customer satisfaction can be enhanced.