This study investigated the impact of various soil environmental factors on the growth and yield of Actinidia arguta (A. arguta) in Suwon, South Korea. By employing Pearson correlation analysis, we explored the relationships between soil properties such as pH, electrical conductivity (EC), organic matter content, available phosphorus, available silicon, soil moisture, and soil temperature with A. arguta growth and yield. The results revealed that soil temperature and EC had the strongest positive correlations with A. arguta growth, while organic matter content exhibited a strong negative correlation with fruit yield. The high levels of available phosphorus emerged as a potential adverse factor affecting yield. These findings suggest that managing soil temperature, EC, and phosphorus levels is crucial for optimizing A. arguta productivity. Future research should focus on fine-tuning phosphorus levels and further investigating the interactions between soil factors to enhance A. arguta yield and sustainability.

Effective mixing of different-sized aggregates in mobile asphalt plant dryers is crucial for ensuring high-quality, consistent asphalt production. This study explores the application of spatial analysis techniques, particularly the Discrete Element Method (DEM), to understand and optimize the mixing process of aggregates in drum dryers. The research emphasizes the importance of proper mixing to achieve uniform moisture removal and heating across various aggregate sizes. Larger aggregates heat more slowly, while finer particles risk overheating or being carried away by air currents, necessitating careful management of the mixing process. Using LIGGGHTS, an open-source simulation framework, we conducted DEM simulations to analyze the spatial distribution and behavior of aggregates within a 3D model of a drum dryer. The study considered multiple factors affecting mixing efficiency, including drum inclination, rotational speed, and aggregate feeding frequency. Results indicate that the rotational speed of the drum dryer has the most significant impact on mixing effectiveness. The DEM simulations provided valuable insights into particle movement, heat transfer, and potential segregation issues within the dryer. Further investigations into additional factors that may influence aggregate mixing in drum dryers is recommended, paving the way for improved efficiency and quality in asphalt manufacturing.

Electric-propulsion systems for ships, also known as electric propulsion devices, represent the current direction of development for maritime power. Issues concerning the environment and fuel economy have compelled the maritime transport sector to seek solutions that reduce emissions and improve fuel efficiency. In this process, power electronics technology plays a significant role in the propulsion systems of ships. Selecting an efficient battery system is of great importance for enhancing the cruising range of yachts and minimizing environmental impact. The battery model is crucial for revealing the working principles of batteries, and it is extremely critical for the application and development of battery technology. The Battery Management System (BMS) serves a crucial regulatory function, optimizing both the safety and performance of battery cells. Central to its operation is the precise estimation of the battery's State of Charge (SOC), a process dependent on an exacting battery model. This system not only enhances longevity and reliability but also ensures that energy storage solutions meet high standards of efficacy. This study focused on testing the impedance characteristics of lithium-sulfur batteries (LSB) at various SOC points and establishing first- and second-order RC equivalent circuit models. The model parameters were identified through experimental data. Subsequently, a simulation platform was constructed using MATLAB/Simulink to simulate the behavior of LSB under a constant current discharge condition. The simulation results showed that the second-order RC model had significantly lower errors than the first-order model, demonstrating higher accuracy. These achievements can provide technical support for the research of energy storage systems in the green aviation and maritime industries.

태풍 매미 통과 시에 부산연안에서 폭풍해일고를 해석하기 위한 수치실험을 수행하였다. 태풍 매미는 2003년 9월 12일 21:00에 중심기압 950hPa로 우리나라 남해안에 상륙하였으며, 지난 수십년 간에 걸쳐 최악의 해안재해로 기록되었다. 태풍 매미 통과시 부산항, 여 수항, 통영항, 마산항, 제주항 및 서귀포항에서 관측된 폭풍해일고와 계산된 해일고의 시계열을 비교하였으며, 계산결과와 관측결과는 잘 일치하였다. 태풍해일고는 마산항에서 약 230 cm로 가장 크게 나타났으며, 여수항과 통영항에서는 약 200 cm, 부산항에서는 약 75 cm로 나 타났다. 폭풍해일 수치실험결과, 부산 동부 연안에서 해일고는 52∼55 cm 범위이고, 외해로 갈수록 해일고는 감소하였다. 따라서 반폐쇄된 만에서는 해일고의 상승으로 인한 연안 침수범람 피해가 크게 발생할 것으로 사료되며, 본 수치실험결과는 태풍으로 인한 연안재해 저감 을 위한 중요한 자료로 사용될 수 있다.

Nowadays, artificial intelligence model approaches such as machine and deep learning have been widely used to predict variations of water quality in various freshwater bodies. In particular, many researchers have tried to predict the occurrence of cyanobacterial blooms in inland water, which pose a threat to human health and aquatic ecosystems. Therefore, the objective of this study were to: 1) review studies on the application of machine learning models for predicting the occurrence of cyanobacterial blooms and its metabolites and 2) prospect for future study on the prediction of cyanobacteria by machine learning models including deep learning. In this study, a systematic literature search and review were conducted using SCOPUS, which is Elsevier’s abstract and citation database. The key results showed that deep learning models were usually used to predict cyanobacterial cells, while machine learning models focused on predicting cyanobacterial metabolites such as concentrations of microcystin, geosmin, and 2-methylisoborneol (2-MIB) in reservoirs. There was a distinct difference in the use of input variables to predict cyanobacterial cells and metabolites. The application of deep learning models through the construction of big data may be encouraged to build accurate models to predict cyanobacterial metabolites.

The Bayesian algorithm model is a model algorithm that calculates probabilities based on input data and is mainly used for complex disasters, water quality management, the ecological structure between living things or living-non-living factors. In this study, we analyzed the main factors affected Korean Estuary Trophic Diatom Index (KETDI) change based on the Bayesian network analysis using the diatom community and physicochemical factors in the domestic estuarine aquatic ecosystem. For Bayesian analysis, estuarine diatom habitat data and estuarine aquatic diatom health (2008~2019) data were used. Data were classified into habitat, physical, chemical, and biological factors. Each data was input to the Bayesian network model (GeNIE model) and performed estuary aquatic network analysis along with the nationwide and each coast. From 2008 to 2019, a total of 625 taxa of diatoms were identified, consisting of 2 orders, 5 suborders, 18 families, 141 genera, 595 species, 29 varieties, and 1 species. Nitzschia inconspicua had the highest cumulative cell density, followed by Nitzschia palea, Pseudostaurosira elliptica and Achnanthidium minutissimum. As a result of analyzing the ecological network of diatom health assessment in the estuary ecosystem using the Bayesian network model, the biological factor was the most sensitive factor influencing the health assessment score was. In contrast, the habitat and physicochemical factors had relatively low sensitivity. The most sensitive taxa of diatoms to the assessment of estuarine aquatic health were Nitzschia inconspicua, N. fonticola, Achnanthes convergens, and Pseudostaurosira elliptica. In addition, the ratio of industrial area and cattle shed near the habitat was sensitively linked to the health assessment. The major taxa sensitive to diatom health evaluation differed according to coast. Bayesian network analysis was useful to identify major variables including diatom taxa affecting aquatic health even in complex ecological structures such as estuary ecosystems. In addition, it is possible to identify the restoration target accurately when restoring the consequently damaged estuary aquatic ecosystem.

본 연구는 시설토경에 적합한 간단관개의 1회 관개량, 관개주기 및 최대 관개횟수를 구명하기 위해 토양 수직단면 상에서의 수분이동을 모델링하였다. 간단관개는 특정양의 물을 관개할 때, 소량의 물을 일정한 시간 간격으로 여러 번 나누어 급수하여 토양표면의 용수 손실을 줄이고, 근권부까지 수분이 원활히 침투되도록 하기 위한 관개 방법이다. 토양 내부의 수분이동 특성은 관개방법, 토성 등에 따라 다양하게 변화한다. 반면, 현장에서 간단관개는 토마토 시설토경 재배의 경우 40분 간격으로 1회 4분간 최대 4회 관개, 사과의 경우 110분 간격으로 1회 5분간 최대 3∼5회 등 경험에 따라 관개하고 있다. 본 연구에서는 국내의 대표적인 밭토성인 사질양토, 양토, 양질사토에 대해 10, 20, 40분 간격으로 관개깊이 5㎜의 용수를 1.0, 1.7, 2.5, 5.0㎜씩 각 1∼5회로 나누어 관개하는 조건을 모의하였다. 모의할 토층단면은 폭 10㎝, 깊이 30㎝로 설정하고, 모의 프로그램은 Hydrus- 2D를 이용하였다. 기존 관련 연구의 실측 자료를 이용해 모델을 보정하고, 토층단면에 걸쳐 시간 경과에 따른 토양 내 수분 변화를 2차원 토양수분 패턴도로 작성하였다. 간단관개 방법에 따라 토양표면 및 근권부 토층에서의 수분 변화를 분석한 결과 모든 조건에서 연속관개 보다는 간단관개가 근권부의 수분전달에 유리하고, 양토, 사질양토, 양질사토의 순으로 관개용수의 침투가 원활한 것으로 파악되었다. 1회 관개량 1.7㎜ 이상, 간단시간 40분 이상인 경우에 토양표면에서의 수분 침투가 원활해지는 것으로 나타났으며, 근권부의 토양수분 전달에 가장 유리한 것은 1회 관개량 1.7㎜, 3회 간단관개하는 경우로 분석되었다. 토성에 따른 토양수분이동의 특성 차이는 크지 않은 것으로 나타났다. 본 연구 결과 시설토경 관개에서 토양표면에서의 용수손실을 감소시키면서, 근권부 수분공급에 적합한 간단관개법을 구명할 수 있었으며, 이를 향후 자동관개 제어 시스템에 적용한다면 용수손실을 최소화하면서 토양수분을 작물생육에 최적의 상태로 제어할 수 있을 것으로 사료된다.

This study aimed to explore research trends of nursing ethics in Korea applying text network analysis and topic modelling. 306 articles published in KCI journals from 1998 to 2021 were identified and 516 author-provided keywords were collected. A co-occurrence matrix with 123 keywords, which appeared at least in two articles, were developed based on the Jaccard coefficient. Degree centrality and betweenness centrality were calculated and LDA topic modelling were performed using NetMiner software. The largest number of the articles (70, 23%) were published in Korean Journal of Medical Ethics. The most critical core-keywords, defined as the top 30 keywords in degree centrality and betweenness centrality, were ‘nursing students’ and ‘moral sensitivity’. The other core-keywords included ‘attitude,’ ‘awareness,’ ‘professionalism,’ ‘knowledge,’ and ‘critical thinking.’ related to ethical competence, ‘death,’ ‘hospice,’ ‘euthanasia,’ and ‘research ethics’ related to bioethical issues, and ‘job satisfaction,’ ‘burn out,’ ‘stress,’ ‘organizational culture,’ ‘ethical leadership,’ and ‘ethical climate’ related to organization and leadership. Five topics were identified and named as a) bioethics education for nursing students, b) knowledge and attitudes for bioethical issues, c) awareness and values of bioethics, d) ethical conflicts of RNs, and e) nursing ethics education. This study found that bioethics was the main topics in Korean nursing ethics research and suggested nursing research should focus on ethical issues RNs frequently experience in patient care. Also, research gaps were inferred in multiple topics including nurse-to-nurse relationships, theoretical perspectives of virtue ethics and care ethics, or witnessing healthcare professionals’ unethical behavior.