A typical trade-off relationship exists between strength and elongation in face-centered cubic metals. Studies have recently been conducted to enhance strength without ductility reduction through surface-treatment-based ultrasonic nanocrystalline surface modification (UNSM), which creates a gradient microstructure in which grains become smaller from the inside to the surface. The transformation-induced plasticity effect in Fe-Mn alloys results in excellent strength and ductility due to their high work-hardening rate. This rate is achieved through strain-induced martensitic transformation when an alloy is plastically deformed. In this study, Fe-6%Mn powders with different sizes were prepared by high-energy ball milling and sintered through spark plasma sintering to produce Fe-6%Mn samples. A gradient microstructure was obtained by stacking the different-sized powders to achieve similar effects as those derived from UNSM. A compressive test was performed to investigate the mechanical properties, including the yielding behavior. The deformed microstructure was observed through electron backscatter diffraction to determine the effects of gradient plastic deformation.

In this study, we collect water control valves that have had accidents due to existing cracks, etc. are collected, and propose investigation items for strengthening the valve structural safety evaluation through a series of analyzes from valve specifications to physicochemical properties are proposed. The results of this study are as follows. First, there was a large variation in the thickness of the body or flange of the valves to be investigated, which is considered to be very important factor, because it may affect the safety of the valve body against internal pressure and the flange connected with the bolt nut. Second, 60% of the valves under investigation had many voids in the valve body and flange, etc. and the decrease in thickness due to corrosion was relatively large on the inner surface in contact with water rather than the outer surface. It is judged that the investigation of depth included voids is very important factor. Third, all valves to be investigated are made of gray cast iron foam, and therefore it is judged that there is no major problem in chemical composition. It is judged that the chemical composition should be investigated. Fourth, as a physical investigation item, the analysis of metal morphology structure seems to be a very important factor for nodular cast iron from rather than a gray cast iron foam water valve with a flake structure. As it was found to be 46.7~68.8% of the standard recommended by KS, it could have a direct effect on damage such as cracks, and therefore it is judged that the evaluation of tensile strength is very important in evaluating the safety of the valve.

리튬-이온 전지 기술의 발전과 함께 다량의 리튬 사용에 따라 리튬-이온 전지에 대한 수요와 공급의 균형이 무너지고 있으며, 따라서 리튬을 대체할 수 있는 차세대 이차 전지의 개발이 필요해지고 있다. 최근 친환경적이며, 값싸며 안전 하고, 다가의 전자를 활용할 수 있는 아연 이온을 활용하는 수계 아연-이온 전지가 주목받고 있다. 그럼에도 불구하 고 아연-이온 전지에 사용될 수 있는 전류 집전체에 대한 개발 연구는 거의 없으며, 특히 현재 사용되고 있는 금속 기반의 전류 집전체는 그 무게가 무거워 실용적으로 사용되기 힘들다. 본 연구에서는 접착 특성이 매우 우수한 키틴 바인더를 사용하여 집전체 없이 지탱이 가능한 전극을 개발하였으며 아연-이온 전지에서의 그 특성을 평가하였다. 전 극 제조는 전통적인 코팅법과 스핀 코팅법을 사용하여 비교하였으며, 스핀 코팅이 더 균일한 전극 형성과 함께 더 우 수한 배터리 성능을 나타냄을 확인하였다.

In this study, the cooling performance change according to the arrangement of the fin-tube heat exchanger using a single tube and the cooling performance change according to the air flow rate were studied. The arrangement of basic heat exchanger was set to 4 columns and 4 rows, and the performance change was studied while changing the columns and rows. In addition, the performance change was investigated by changing the air flow rate of the basic heat exchanger.

The prediction of algal bloom is an important field of study in algal bloom management, and chlorophyll-a concentration(Chl-a) is commonly used to represent the status of algal bloom. In, recent years advanced machine learning algorithms are increasingly used for the prediction of algal bloom. In this study, XGBoost(XGB), an ensemble machine learning algorithm, was used to develop a model to predict Chl-a in a reservoir. The daily observation of water quality data and climate data was used for the training and testing of the model. In the first step of the study, the input variables were clustered into two groups(low and high value groups) based on the observed value of water temperature(TEMP), total organic carbon concentration(TOC), total nitrogen concentration(TN) and total phosphorus concentration(TP). For each of the four water quality items, two XGB models were developed using only the data in each clustered group(Model 1). The results were compared to the prediction of an XGB model developed by using the entire data before clustering(Model 2). The model performance was evaluated using three indices including root mean squared error-observation standard deviation ratio(RSR). The model performance was improved using Model 1 for TEMP, TN, TP as the RSR of each model was 0.503, 0.477 and 0.493, respectively, while the RSR of Model 2 was 0.521. On the other hand, Model 2 shows better performance than Model 1 for TOC, where the RSR was 0.532. Explainable artificial intelligence(XAI) is an ongoing field of research in machine learning study. Shapley value analysis, a novel XAI algorithm, was also used for the quantitative interpretation of the XGB model performance developed in this study.

Among migratory insect pests, Mythimna seperata and Cnaphalocrocis medinalis are invasive pests introduced into South Korea through westerlies from southern China. M. seperata and C. medinalis are insect pests that use rice as a host. They injure rice leaves and inhibit rice growth. To understand the distribution of M. seperata and C. medinalis, it is important to understand environmental factors such as temperature and humidity of their habitat. This study predicted current and future habitat suitability models for understanding the distribution of M. seperata and C. medinalis. Occurrence data, SSPs (Shared Socio-economic Pathways) scenario, and RCP (Representative Concentration Pathway) were applied to MaxEnt (Maximum Entropy), a machine learning model among SDM (Species Distribution Model). As a result, M. seperata and C. medinalis are aggregated on the west and south coasts where they have a host after migration from China. As a result of MaxEnt analysis, the contribution was high in the order of Land-cover data and DEM (Digital Elevation Model). In bioclimatic variables, BIO_4 (Temperature seasonality) was high in M. seperata and BIO_2 (Mean Diurnal Range) was found in C. medinalis. The habitat suitability model predicted that M. seperata and C. medinalis could inhabit most rice paddies.

Frankliniella occidentalis is an invasive pest insect, which affects over 500 different species of host plants and transmits viruses (tomato spotted wilt virus; TSWV). Despite their efficiency in controling insect pests, pesticides are limited by residence, cost and environmental burden. Therefore, a fixed-precision level sampling plan was developed. The sampling method for F. occidentalis adults in pepper greenhouses consists of spatial distribution analysis, sampling stop line, and control decision making. For sampling, the plant was divided into the upper part (180 cm above ground), middle part (120-160 cm above ground), and lower part (70-110 cm above ground). Through ANCOVA, the P values of intercept and slope were estimated to be 0.94 and 0.87, respectively, which meant there were no significant differences between values of all the levels of the pepper plant. In spatial distribution analysis, the coefficients were derived from Taylor’s power law (TPL) at pooling data of each level in the plant, based on the 3-flowers sampling unit. F. occidentalis adults showed aggregated distribution in greenhouse peppers. TPL coefficients were used to develop a fixed-precision sampling stop line. For control decision making, the pre-referred action thresholds were set at 3 and 18. With two action thresholds, Nmax values were calculated at 97 and 1149, respectively. Using the Resampling Validation for Sampling Program (RVSP) and the results gained from the greenhouses, the simulated validation of our sampling method showed a reasonable level of precision.

This study aimed to examine the major domestic and foreign regulations related to the production of organic products. The production and consumption of organic products have been expanding due to the increase in consumer demand for safe food, as well as improved certification procedures and industry trends. In case of organic mushrooms, there were 405 certified farms nationwide in 2021, with a cultivation area of 3,886,628 m2 and a planned production of 6,011 tons. Jeollanamdo has 221 farms, a cultivation area of 2,923,402 m2, and a certification plan for 2,132 tons. Shiitake mushrooms are ranked first with 369 farms, a cultivation area of 3,805,636 m2, and a certification plan for 3,576 tons, representing 91% of the farms, 98% of the cultivation area, and 60% of the certification planning.

본 연구에서는, 5가지 식물의 메탄올 추출물을 이용하여 모기기피 효과 실험을 진행하고 누드 쥐를 모델로 하여 흰줄숲모기에 대한 모기기 피제의 유효용량 및 유효시간을 평가하였다. 그리고 식물의 휘발성분을 GC-MS로 분석하였다. 유효용량은 개박하가 10, 50, 100, 200 μg/mL 에서 72.9, 83.7, 86.4, 97.3%의 효율로 가장 높았다. 누드 쥐를 대상으로 한 유효시간 연구에서는 5가지 식물의 메탄올 추출물 중 개박하, 개다 래 및 개똥쑥이 90.5%로, 30분까지만 지속하였다. 각 식물의 휘발성분을 분석한 결과, 애플민트 28개 성분, 개다래 19개 성분, 개똥쑥 27개 성분, 개박하 26개 성분, 민들레 19개 성분이 확인 되었다. 특히 모기기피제의 유효 성분으로 알려진 네페탈락톤(nepetalactone)이 개박하의 휘발성분 중 한 성분으로 확인 되었다(27.95 mg/Kg). 본 연구결과는 다양한 휘발성분을 함유한 식물을 이용한 모기기피제 재료로서 가능성을 제시한다.

전국 최대 규모의 고추(Capsicum annuum L.) 재배지는 안동이다. 이 지역을 중심으로 본 연구는 시설재배지 고추를 가해하는 총채벌레의 연중(2021년 3월 31일~10월25일) 발생을 보고한다. 황색트랩을 이용하여 포획한 총채벌레를 유관으로 동정한 결과 꽃노랑총채벌레(Frankliniella occidentalis)와 대만총채벌레(F. intonsa)가 우점종으로 나타났다. 전체 포획충은 107,873마리였으며 이 가운데 꽃노랑총채벌레가 약 82%, 대만총채벌레가 약 17% 그리고 기타 총채벌레가 약 0.3% 를 차지하였다. 연중 전체적으로 2회 총채벌레 발생 피크를 보였다. 첫 번째 발생피크는 5-6월에 나타났고, 두 번째 발생 피크는 9월 이후에 일어났다. 발생규모는 첫 번째보다는 두 번째 발생 피크에서 높았으며 대부분은 꽃노랑총채벌레가 차지하였다. 흥미롭게 7-8월에 이들 총채벌레의 발생이 매우 낮았는데 이들 주요 총채벌레 가 고온에 대한 높은 감수성으로 기인되었다. 실내 고온 노출실험은 총채벌레들이 35°C 이상에서 고온 감수성을 보여 45°C에서는 1시간 노출을 견디지 못하였다. 실 제로 안동지역 7-8월 시설재배지는 최고온도가 45°C 이상을 기록하였다. 이 가운데 꽃노랑총채벌레가 대만총채벌레에 비해 낮은 고온 감수성을 보였다. 반면에 안동 에 비해 기온이 낮은 강원지역의 시설 고추 재배지에서는 7-8월에 오히려 최대 총채벌레 발생피크를 나타냈으며, 이 시기 최고온도는 45°C 이하를 기록하였다. 조사 한 안동지역 고추에서는 TSWV (tomato spotted wilt virus)에 의해 발병되는 바이러스병이 발생하였다. 다중 PCR 검정법으로 이 바이러스 보독 유무 및 대상 총 채벌레를 동시에 분석하였다. 이 결과 바이러스 보독충 비율은 최대 30%를 기록하며 연중 지속적으로 검출되었는데 이들 모두는 대만총채벌레로 판명되었다. 이상 의 결과는 시설 고추재배지에서 꽃노랑총채벌레는 고추 수확기에 최성기를 이루며 고추에 직접피해를 줄 가능성이 높으며, 대만총채벌레는 높은 바이러스 보독율로 고추의 간접피해를 유발할 위험성이 있다는 것을 각각 제시하고 있다.

Fashion companies and brands’ marketing activities focus on resolving environmental problems; however, these companies’ efforts, there are some examples of so-called “greenwashing”. This paper aims to analyze different perceptions of brand authenticity, green marketing, and purchase intention toward the brand before and after exposure to case information about greenwashing. A total of 211 data were gathered and analyzed using SPSS 25.0. Respondents were asked to respond to same questionnaires related to green marketing and the brand authenticity before and after their exposure to greenwashing information. The study participants’ perceptions of green marketing from the brand were statistically significantly negatively changed after exposure compared to before exposure. Similar patterns in results were found in the context of consumers’ perception of brand authenticity (genuineness, originality, and consistency), and purchase intention. The originality of this study is in evaluating consumers’ perception of greenwashing focused on brand authenticity. The findings of the study suggest that if a fashion brand’s green marketing activity is perceived as greenwashing by consumers, the perceptions of green marketing, brand authenticity, and purchase intention can all decline. It is suggested that fashion brands need to develop a sincere and truthful green marketing campaigns to keep and enhance their brand authenticity.

The CoCrFeMnNi high-entropy alloy (HEA), which is the most widely known HEA with a single facecentered cubic structure, has attracted significant academic attention over the past decade owing to its outstanding multifunctional performance. Recent studies have suggested that CoCrFeMnNi-type HEAs exhibit excellent printability for selective laser melting (SLM) under a wide range of process conditions. Moreover, it has been suggested that SLM can not only provide great topological freedom of design but also exhibit excellent mechanical properties by overcoming the strength–ductility trade-off via producing a hierarchical heterogeneous microstructure. In this regard, the SLM-processed CoCrFeMnNi HEA has been extensively studied to comprehensively understand the mechanisms of microstructural evolution and resulting changes in mechanical properties. In this review, recent studies on CoCrFeMnNi-type HEAs produced using SLM are discussed with respect to process-induced microstructural evolution and the relationship between hierarchical heterogeneous microstructure and mechanical properties.

본 실험에서는 α-Al2O3 세라믹 중공사를 지지체로 사용하였고, 무전해 도금을 통해 Pd 및 Pd-Ag가 도금된 수소 분리막을 제조하였다. Pd-Ag 분리막은 Pd와 Ag 합금 형태로 만들기 위하여 500°C, 10 h 동안의 annealing 과정을 거쳤으며, EDS (Energy Dispersive X-ray Spectroscopy) 분석을 통해 Pd-Ag 합금이 되었다는 것을 확인하였다. 또한, SEM (Scanning Electron Microscope) 분석을 통해 제조된 Pd 및 Pd-Ag 도금층의 두께는 약 8.98, 9.29 μm으로 측정되었다. 제조된 수소 분 리막은 350~450°C, 1-4 bar의 범위에서 수소 단일 가스, 혼합가스(H2, N2)를 이용하여 수소 투과 실험을 진행하였다. 수소 단 일 가스에서 Pd와 Pd-Ag 분리막은 최대 각각 21.85, 13.76 mL/cm2⋅min의 flux를 가지며, 혼합가스에서는 450°C, 4 bar의 조건일 때, 1216, 361의 separation factor가 각각 나오는 것을 확인하였다.