The acoustic emission (AE) is proposed as a feasible method for the real-time monitoring of the structural damage evolution in concrete materials that are typically used in the storage of nuclear wastes. However, the characteristics of AE signals emitted from concrete structures subjected to various environmental conditions are poorly identified. Therefore, this study examines the AE characteristics of the concrete structures during uniaxial compression, where the storage temperature and immersion conditions of the concrete specimens varied from 15℃ to 75℃ and from completely dry to water-immersion, respectively. Compared with the dry specimens, the water-immersed specimens exhibited significantly reduced uniaxial compressive strengths by approximately 26%, total AE energy by approximately 90%, and max RA value by approximately 70%. As the treatment temperature increased, the strength and AE parameters, such as AE count, AE energy, and RA value, of the dry specimens increased; however, the temperature effect was only minimal for the immersed specimens. This study suggests that the AE technique can capture the mechanical damage evolution of concrete materials, but their AE characteristics can vary with respect to the storage conditions.

Fescues, which are widely cultivated as grasses and forages around the world, are often naturally infected with the endophyte, Epichloë. This fungus, transmitted through seeds, imparts resistance to drying and herbivorous insects in its host without causing any external damage, thereby contributing to the adaptation of the host to the environment and maintaining a symbiosis. However, some endophytes, such as E. coenophialum synthesize ergovaline or lolitrem B, which accumulate in the plant and impart anti-mammalian properties. For example, when livestock consume excessive amounts of grass containing toxic endophytes, problems associated with neuromuscular abnormalities, such as convulsions, paralysis, high fever, decreased milk production, reproductive disorders, and even death, can occur. Therefore, pre-inoculation with non-toxic endogenous fungi or management with endophyte-free grass is important in preventing damage to livestock and producing high-quality forage. To date, the diagnosis of endophytes has been mainly performed by observation under a microscope following staining, or by performing an immune blot assay using a monoclonal antibody. Recently, the polymerase chain reaction (PCR)-based molecular diagnostic method is gaining importance in the fields of agriculture, livestock, and healthcare given the method’s advantages. These include faster results, with greater accuracy and sensitivity than those obtained using conventional diagnostic methods. For the diagnosis of endophytes, the nested PCR method is the only available option developed; however, it is limited by the fact that the level of toxic alkaloid synthesis cannot be estimated. Therefore, in this study, we aimed to develop a triplex real-time PCR diagnostic method that can determine the presence or absence of endophyte infection using DNA extracted from seeds within 1 h, while simultaneously detecting easD and LtmC genes, which are related to toxic alkaloid synthesis. This new method was then also applied to real field samples.

This study aimed to investigate whether bacterial ghosts (BGs), empty cell envelopes of a gram-negative bacterium, delivering envelope protein domain III (EDIII) of dengue virus (DENV) serotype 2 could induce protective immune responses against dengue infection. In this study, we constructed Salmonella Typhimurium BGs expressing and delivering EDIII (BG-EDIII) and evaluated these ghosts for their immunogenicity studies in C57BL/6 mice. Our results demonstrated that the mice vaccinated once orally with BG-EDIII followed by an intramuscular boosting with a recombinant EDIII protein elicited significantly higher humoral and cell-mediated immune responses compared to the BGs alone vaccinated group (p<0.001). Upon challenge with DENV2, significantly lower viral load and liver damage was observed in BG-EDIII vaccinated group than BGs alone control group (p<0.05). The outcomes of this study revealed the ability of BG- EDIII to stimulate immune response with no observable damage to the vital organs.

털부처꽃(Lythrum salicaria L.)은 전국에 분포하는 다년생 초본식물로 척박하고 습한 지역을 포함한 다양한 환경에서 잘 자라는 것으로 알려져 있다. 따라서 하천변, 척박지에서 정원 용, 화훼용 및 관상용 식물로 이용이 가능하다. 본 연구는 털 부처꽃의 적정 육묘 조건(토양종류, 플러그 트레이 셀 크기,파종립수, 액비농도 및 차광)을 조사하였다. 대조구(원예상토) 에서 재배된 유묘의 생육이 가장 우수하였다. 반면 피트모스 와 펄라이트의 혼합용토는 육묘기간이 지속되면서 생육수치 가 감소하는 경향을 나타냈다. 셀 크기는 용적이 가장 큰 162 셀에서 재배된 유묘의 생육이 우수하였으나, 200셀과 288셀에 서 자란 묘도 건강했다. 한편 유묘의 결주발생을 고려하면 셀 당 2립을 파종하는 것이 적합하였다. 액비 처리는 유묘의 생 육을 촉진하였다. 특히 Hyponex 1000배는 초장, 줄기직경, 엽수, 마디수, 근장, 지상부 생체중 및 지하부 생체중을 증가 시켰다. 또한 유묘의 생육은 55% 차광 하에서 우수하였다. 따 라서 털부처꽃의 가장 효과적인 생육조건은 원예상토가 충진 된 288셀 플러그 트레이에 셀 당 2립을 파종하고 Hyponex 1000배를 시비하면서 55% 차광 하에서 재배하는 것이었다.

DEA(data envelopment analysis) is a technique for evaluation of relative efficiency of decision making units (DMUs) that have multiple input and output. A DEA model measures the efficiency of a DMU by the relative position of the DMU’s input and output in the production possibility set defined by the input and output of the DMUs being compared. In this paper, we proposed several DEA models measuring the multi-period efficiency of a DMU. First, we defined the input and output data that make a production possibility set as the spanning set. We proposed several spanning sets containing input and output of entire periods for measuring the multi-period efficiency of a DMU. We defined the production possibility sets with the proposed spanning sets and gave DEA models under the production possibility sets. Some models measure the efficiency score of each period of a DMU and others measure the integrated efficiency score of the DMU over the entire period. For the test, we applied the models to the sample data set from a long term university student training project. The results show that the suggested models may have the better discrimination power than CCR based results while the ranking of DMUs is not different.

Busulfan is the most commonly used drug for preconditioning during the transplantation of hematopoietic stem cells and male germ cells. Here, we describe side effects of high doses of busulfan in male mongrel dogs. Busulfan was intravenously administered to three groups of dogs at doses of 10, 15, and 17.5 mg/kg body weight. The total white blood cell, neutrophil, eosinophil, lymphocyte, monocyte, and platelet counts steadily reduced in a dose-dependent manner following busulfan treatment. The white blood cell, neutrophil, and monocyte counts recovered after 6 weeks of busulfan treatment, however, the eosinophil, lymphocyte, and platelet counts remained unaltered. Additionally, there was one fatality in the each of the groups that were administered 15 and 17.5 mg/kg busulfan. The gross lesions included severe hemorrhage in the stomach, intestinal tracts, mesentery and urinary bladder. Microscopic investigation revealed severe pulmonary edema and hemorrhage in the lungs, and severe multifocal to coalescing transmural hemorrhage in the intestines and urinary bladder. These results indicated that treatment with busulfan at doses higher than 15 mg/kg initiates severe bleeding in the internal organs and can have fatal results.

The purpose of this study was to examine the extent to which influencing factors impact the transference willingness of farmers. The research method is based on the survey data on transference willingness, and the binary logistic model was used to analyze the influencing factors. The results show that the educational level, annual household income, farm labor, and farmers' understanding of land transfer policy notably influence land transfer. Based on the results, suggestions include improving farmers' social security system, improving a sound market for rural land transfer, and deepening the promotion and explanation of land-related policies.

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.

Natural environmental resources are considered a prospective source of microorganisms capable of producing biocatalysts with great potential in industrial areas. Arable soil fertilized with peat moss is a habitat for various microorganisms. The present research focused on the isolation and identification of hydrolase-producing bacteria that thrive at a broad temperature range. In this study, a total of 33 strains were isolated from arable soil fertilized with peat moss (Silla Garden in Busan, South Korea). The isolated bacteria were mesophiles and thermophiles with a wide temperature range. Taxonomic identification showed that the isolated strains belonged to 2 phyla, 5 families, 10 genera, and 24 species. Subsequently, the isolated strains were screened for hydrolase (amylase, lipase, and protease) activity. All isolates possessed activity of at least one enzyme and six bacterial isolates produced combined extracellular enzymes. Diversity of soil bacteria species in the present study suggest the potential of soil bacteria in the various industrial applications.

Gamma-ray spectroscopy, which is an appropriate method to identify and quantify radionuclides, is widely utilized in radiological leakage monitoring of nuclear facilities, assay of radioactive wastes, and decontamination evaluation of post-processing such as decommissioning and remediation. For example, in the post-processing, it is conducted to verify the radioactivity level of the site before and after the work and decide to recycle or dispose the generated waste. For an accurate evaluation of gamma-ray emitting radionuclides, the measurement should be carried out near the region of interest on site, or a sample analysis should be performed in the laboratory. However, the region is inaccessible due to the safety-critical nature of nuclear facilities, and excessive radiation exposure to workers could be caused. In addition, in the case of subjects that may be contaminated inside such as pipe structures generated during decommissioning, surveying is usually done over the outside of them only, so the effectiveness of the result is limited. Thus, there is a need to develop a radiation measurement system that can be available in narrow space and can sense remotely with excellent performance. A liquid light guide (LLG), unlike typical optical fiber, is a light guide which has a liquid core. It has superior light transmissivity than any optical fiber and can be manufactured with a larger diameter. Additionally, it can deliver light with much greater intensity with very low attenuation along the length because there is no packing fraction and it has very high radiation resistant characteristics. Especially, thanks to the good transmissivity in UV-VIS wavelength, the LLG can well transmit the scintillation light signals from scintillators that have relatively short emission wavelengths, such as LaBr3:Ce and CeBr3. In this study, we developed a radiation sensor system based on a LLG for remote gamma-ray spectroscopy. We fabricated a radiation sensor with LaBr3:Ce scintillator and LLG, and acquired energy spectra of Cs-137 and Co-60 remotely. Furthermore, the results of gamma-ray spectroscopy using different lengths of LLG were compared with those obtained without LLG. Energy resolutions were estimated as 7.67%, 4.90%, and 4.81% at 662, 1,173, and 1,332 keV, respectively for 1 m long LLG, which shows similar values of a general NaI(Tl) scintillator. With 3 m long LLG, the energy resolutions were 7.92%, 5.48%, and 5.07% for 662, 1,173, and 1,332 keV gamma-rays, respectively.

In this study, the positions of Cs-137 gamma ray source are estimated from the plastic scintillating fiber bundle sensor with length of 5 m, using machine learning data analysis. Seven strands of plastic scintillating fibers are bundled by black shrink tube and two photomultiplier tubes are used as a gamma ray sensing and light measuring devices, respectively. The dose rate of Cs-137 used in this study is 6 μSv·h−1. For the machine learning modeling, Keras framework in a Python environment is used. The algorithm chosen to construct machine learning model is regression with 15,000 number of nodes in each hidden layer. The pulse-shaped signals measured by photomultiplier tubes are saved as discrete digits and each pulse data consists of 1,024 number of them. Measurements are conducted separately to create machine learning data used in training and test processes. Measurement times were different for obtaining training and test data which were 1 minute and 5 seconds, respectively. It is because sufficient number of data are needed in case of training data, while the measurement time of test data implies the actual measuring time. The machine learning model is designated to estimate the source positions using the information about time difference of the pulses which are created simultaneously by the interaction of gamma ray and plastic scintillating fiber sensor. To evaluate whether the double-trained machine learning model shows enhancement in accuracy of source position estimation, the reference model is constructed using training data with one-time learning process. The double-trained machine learning model is designed to construct first model and create a second training data using the training error and predetermined coefficient. The second training data are used to construct a final model. Both reference model and double-trained models constructed with different coefficients are evaluated with test data. The evaluation result shows that the average values calculated for all measured position in each model are different from 7.21 to 1.44 cm. As a result, by constructing the double-trained machine learning model, the final accuracy shows 80% of improvement ratio. Further study will be conducted to evaluate whether the double-trained machine learning model is applicable to other data obtained from measurement of gamma ray sources with different energy and set a methodology to find optimal coefficient.

Concrete is one of the largest wastes, by volume, generated during the decommissioning of nuclear facilities, which significantly influences the projected costs for the disposal of decommissioning wastes. Concrete consists of aggregates and a cement binder. In radioactive concrete, the radioisotopes are mainly associated with the cement component. If the radioactive isotope can be separated from the concrete to below the clearance criteria, the volume of radioactive concrete waste could be reduced effectively. We were studied to separate the radioactive materials from the concrete by using the thermomechanical and chemical treatment processes, sequentially. From the study, separated aggregate could be treated to achieve the clearance level. However, these processes generate a large volume of secondary acidic radioactive wastewater, which might be a critical problem to reduce the volume of radioactive concrete waste. In this research, separating the 137Cs and 90Sr from dissolved concrete wastewater to below the discharge criteria by precipitation method, it would be released to the environment under industrial waste guidelines. The experiments were conducted to using a simulated radioactive wastewater, formed by the dissolution of concrete within HCl, which was spiking the 137Cs and 90Sr, respectively. In addition, we applied the chemical precipitation methods with wastewater, using ferrocyanide for 137Cs and BaSO4 coprecipitation for 90Sr. As a result, targeted radionuclides could be removed to the discharge level (137Cs: 0.05 Bq·ml−1, 90Sr: 0.02 Bq·ml−1) by precipitation method. Therefore, it could reduce the secondary wastewater effectively by precipitation method and enhance the additional volume reduction for radioactive concrete waste.

The bacterial soft-rot disease is one of the most critical diseases in vegetables such as Chinese cabbage. The researchers isolated two bacteria (Pseudomonas kribbensis and Pantoea vagans) from diseased tissue samples of Chinese cabbages and confirmed them as being the strains that cause soft-rot disease. Lactic-acid bacteria (LAB), were screened and used to control soft-rot disease bacteria. The researchers tested the treatments with hypochlorous acid water (HAW) and LAB supernatant to control soft-rot disease bacteria. The tests confirmed that treatments with the HAW (over 120 ppm) or LAB (Lactobacillus plantarum PL203) culture supernatants (0.5 mL) completely controlled both P. kribbensis and P. vagans.