We investigated the epidemiological characteristics of the antimicrobial resistant Enterococcus isolates from the four major rivers of Korea in 2012. A total 316 surface water samples were collected from three distinct sites (nearby livestock farms, tributaries, and major rivers) at two different seasons (dry season: n = 76, wet season: n = 240). A total 654 bacterial cells were isolated from samples and their genus distribution were determined. We found that Gram-negative bacteria including various genera were prevalent (n = 522, 79.8%), and Enterococcus was the most common genus of Gram-positive bacteria (n = 119, 18.2%). The isolation rate of Gram-negative bacteria was higher in wet season, whereas that of Enterococcus isolates was higher in dry season. The prevalence of Enterococcus isolates was also higher nearby livestock farms than on tributaries and main rivers. Since Enterococcus isolate is a key indicator for animal fecal contamination, the following experiments focused on this microorganism. As compared to a previous report in 2006, the resistance rates in E. faecium to erythromycin (40.0% to 69.9%) and chloramphenicol (0% to 16.4%) were increased, whereas those to penicillin (56.0% to 4.1%) and teicoplanin (36.0% to 0%) were decreased. We also found that antimicrobial-resistant (AMR) E. faecium isolates from rivers and livestock samples shared similar pulsed-filed gel electrophoresis (PFGE) profiles, validating the transmission of AMR Enterococcus isolates from livestock to river. Taken together, this study provides us with detailed information about bacterial contamination status in four major rivers, and highlights the changes in AMR pattern of Enterococcus isolates, which are expected to have originated from livestock.

Research and interest in sustainable printing are increasing in the packaging printing industry. Currently, predicting the amount of ink required for each work is based on the experience and intuition of field workers. Suppose the amount of ink produced is more than necessary. In this case, the rest of the ink cannot be reused and is discarded, adversely affecting the company's productivity and environment. Nowadays, machine learning models can be used to figure out this problem. This study compares the ink usage prediction machine learning models. A simple linear regression model, Multiple Regression Analysis, cannot reflect the nonlinear relationship between the variables required for packaging printing, so there is a limit to accurately predicting the amount of ink needed. This study has established various prediction models which are based on CART (Classification and Regression Tree), such as Decision Tree, Random Forest, Gradient Boosting Machine, and XGBoost. The accuracy of the models is determined by the K-fold cross-validation. Error metrics such as root mean squared error, mean absolute error, and R-squared are employed to evaluate estimation models' correctness. Among these models, XGBoost model has the highest prediction accuracy and can reduce 2134 (g) of wasted ink for each work. Thus, this study motivates machine learning's potential to help advance productivity and protect the environment.

Intermuscular fat is essential for enhancing the flavor and texture of cultured meat. Mesenchymal stem cells derived from intermuscular adipose tissues are a source of intermuscular fat. Therefore, as a step towards developing a platform to derive intermuscular fat from mesenchymal stem cells (MSCs) for insertion between myofibrils in cultured beef, an advanced protocol of intermuscular adipose tissue dissociation effective to the isolation of MSCs from intermuscular adipose tissues was developed in cattle. To accomplish this, physical steps were added to the enzymatic dissociation of intermuscular adipose tissues, and the MSCs were established from primary cells dissociated with physical step-free and step-added enzymatic dissociation protocols. The application of a physical step (intensive shaking up) at 5 minutes intervals during enzymatic dissociation resulted in the greatest number of primary cells derived from intermuscular adipose tissues, showed effective formation of colony forming units-fibroblasts (CFU-Fs) from the retrieved primary cells, and generated MSCs with no increase in doubling time. Thus, this protocol will contribute to the stable supply of good quality adipose-derived mesenchymal stem cells (ADMSCs) as a fat source for the production of marbled cultured beef.

With the aging of nuclear power plants (NPPs) in 37 countries around the world, 207 out of 437 NPPs have been permanently shutdown as of August 2022 according to the IAEA. In Korea, the decommissioning of NPPs is emerging as a challenge due to the permanent shutdown of Kori Unit 1 and Wolsong Unit 1. However, there are no cases of decommissioning activities for Heavy Water Reactor (HWR) such as Wolsong Unit 1 although most of the decommissioning technologies for Light Water Reactor (LWR) such as Kori Unit 1 have been developed and there are cases of overseas decommissioning activities. This study shows the development of a decommissioning waste amount/cost/process linkage program for decommissioning Pressurized Heavy Water Reactor (PHWR), i.e. CANDU NPPs. The proposed program is an integrated management program that can derive optimal processes from an economic and safety perspective when decommissioning PHWR based on 3D modeling of the structures and digital mock-up system that links the characteristic data of PHWR, equipment and construction methods. This program can be used to simulate the nuclear decommissioning activities in a virtual space in three dimensions, and to evaluate the decommissioning operation characteristics, waste amount, cost, and exposure dose to worker. In order to verify the results, our methods for calculating optimal decommissioning quantity, which are closely related to radiological impact on workers and cost reduction during decommissioning, were compared with the methods of the foreign specialized institution (NAGRA). The optimal decommissioning quantity can be calculated by classifying the radioactivity level through MCNP modeling of waste, investigating domestic disposal containers, and selecting cutting sizes, so that costs can be reduced according to the final disposal waste reduction. As the target waste to be decommissioning for comparative study with NAGRA, the calandria in PHWR was modeled using MCNP. For packaging waste container, NAGRA selected three (P2A, P3, MOSAIK), and we selected two (P2A, P3) and compared them. It is intended to develop an integrated management program to derive the optimal process for decommissioning PHWR by linking the optimal decommissioning quantity calculation methodology with the detailed studies on exposure dose to worker, decommissioning order, difficulty of work, and cost evaluation. As a result, it is considered that it can be used not only for PHWR but also for other types of NPPs decommissioning in the future to derive optimal results such as worker safety and cost reduction.

최근 AI 기술은 하루가 다르게 빠르게 발전하고 있고, AI기술은 각 분야에서 다양하게 사용되어지고 있다. 본 논문은 예술분야에서 AI기술의 활용으로 COVID-19 상황에서 인간관계, 개인적인 이유로 지친 마음을 위 로해주는 힐링 게임을 제작하였다. 제작한 힐링게임에서는 주로 Self-help-therapy의 효과를 얻을 수 있어, 치 료자의 도움없이 이용자가 힐링게임을 통하여 일상적 이용과정에서 치유적 효과를 얻을 수 있는 것을 기대 하고 있다. 게임 리뷰 데이터를 통계 분석하여 힐링게임으로 대중들이 요구하는 부분을 수용하여 힐링게임 이 제작되었으며, 사용자는 게임 시작 전 간단한 스토리라인과 AI와 상호작용할 수 있는 간단한 대화를 통 화여 Self-help-therapy 효과를 얻을 수 있었다.

The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In ‘offset printing’ mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called ‘spot color’ ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through ‘Delta E’ provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.

연구는 참외 재배 지에서 흰가루병, 담배가루이 및 두점박이응애가 동시에 발생하였을 때 45, 40, 35°C (대조구)의 온도에서 측창으로 환기 처리 시, 온실 내 온 ․ 습도의 변화, 병충해 발생과 잎말림, 그리고 개화조절에 미 치는 효과를 검토하였다. 3월 3일 ‘히든파워’ 대목에 접붙여진 ‘알찬꿀’ 참외를 40cm 간격으로 격리상에 심었고, 위 에 언급한 병해충이 모든 처리구에서 발생한 6월 18일부터 7월 13일까지 처리하였다. 온실의 온도는 맑은 날에는 설정 온도 지점까지 증가되었고, 45°C 환기 처리에서 고온 고습이 약 9시간 동안 유지되었다. 주간 최고 기온과 최 저 상대습도 차이는 45°C 환기 처리에서 가장 높았다. 환기 처리 11일 후에는 흰가루병과 두점박이응애 피해가 45°C 환기 처리에서 거의 회복되었지만 40°C와 35°C에서는 그렇지 않았다. 처리 14일 후, 담배가루이와 두점박이 응애 밀도는 45°C에서 유의하게 감소하였으나 흰가루병 증상은 유의하게 감소하지는 않았다. 잎말림은 고온에서 유발되었으나 45°C에서도 심하지 않았다. 처리 26일 후, 새로 나온 줄기의 15 마디의 개화수를 조사한 결과, 45°C에 서 암꽃이 전혀 나오지 않았고 수꽃은 1.2개로 나타났다. 이상의 결과는, 고온기에 45°C의 고온에서 2－3주간 환기 처리는 온실 내부의 고온 고습을 유도하여 흰가루병, 담배가루이, 두점박이응애를 통제하고, 개화를 억제하여 참외 의 영양 생장을 회복할 수 있는 방법으로 사료되었다.

The printing process can have to print various colors with a limited capacity of printing facility such as ink containers that are needed cleaning to change color. In each container, cleaning time exists to assign corresponding inks, and it is considered as the setup cost required to reduce the increasing productivity. The existing manual method, which is based on the worker’s experience or intuition, is difficult to respond to the diversification of color requirements, mathematical modeling and algorithms are suggested for efficient scheduling. In this study, we propose a new type of scheduling problem for the printing process. First, we suggest a mathematical model that optimizes the color assignment and scheduling. Although the suggested model guarantees global optimality, it needs a lot of computational time to solve. Thus, we decompose the original problem into sequencing orders and allocating ink problems. An approximate function is used to compute the job scheduling, and local search heuristic based on 2-opt algorithm is suggested for reducing computational time. In order to verify the effectiveness of our method, we compared the algorithms' performance. The results show that the suggested decomposition structure can find acceptable solutions within a reasonable time. Also, we present schematized results for field application.