Dynamic responses of nuclear power plant structure subjected to earthquake loads should be carefully investigated for safety. Because nuclear power plant structure are usually constructed by material of reinforced concrete, the aging deterioration of R.C. have no small effect on structural behavior of nuclear power plant structure. Therefore, aging deterioration of R.C. nuclear power plant structure should be considered for exact prediction of seismic responses of the structure. In this study, a machine learning model for seismic response prediction of nuclear power plant structure was developed by considering aging deterioration. The OPR-1000 was selected as an example structure for numerical simulation. The OPR-1000 was originally designated as the Korean Standard Nuclear Power Plant (KSNP), and was re-designated as the OPR-1000 in 2005 for foreign sales. 500 artificial ground motions were generated based on site characteristics of Korea. Elastic modulus, damping ratio, poisson’s ratio and density were selected to consider material property variation due to aging deterioration. Six machine learning algorithms such as, Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), eXtreme Gradient Boosting (XGBoost), were used t o construct seispic response prediction model. 13 intensity measures and 4 material properties were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks present good prediction performance considering aging deterioration.

Machine learning is widely applied to various engineering fields. In structural engineering area, machine learning is generally used to predict structural responses of building structures. The aging deterioration of reinforced concrete structure affects its structural behavior. Therefore, the aging deterioration of R.C. structure should be consider to exactly predict seismic responses of the structure. In this study, the machine learning based seismic response prediction model was developed. To this end, four machine learning algorithms were employed and prediction performance of each algorithm was compared. A 3-story coupled shear wall structure was selected as an example structure for numerical simulation. Artificial ground motions were generated based on domestic site characteristics. Elastic modulus, damping ratio and density were changed to considering concrete degradation due to chloride penetration and carbonation, etc. Various intensity measures were used input parameters of the training database. Performance evaluation was performed using metrics like root mean square error, mean square error, mean absolute error, and coefficient of determination. The optimization of hyperparameters was achieved through k-fold cross-validation and grid search techniques. The analysis results show that neural networks and extreme gradient boosting algorithms present good prediction performance.

PURPOSES : In this study, the alkali aggregate reactivity and expansion characteristics of mortar mixed with waste glass (a recycled aggregate) were confirmed to verify the alkali-silica reaction (ASR) stability and review the appropriateness of the alkali aggregate reactivity test method following the replacement of recycled aggregate. METHODS : The alkali-aggregate reactivity of waste glass aggregates was measured using the chemical and physical methods described in KS F 2545 and ASTM C 1260, respectively. The reactivity was classified by comparing the results. Cement with a high-alkali content was used to simulate an environment that can induce ASR. Non-reactive fine aggregates, waste glass fine aggregates, reactive general aggregates, and Ferronickel slag aggregates were used as control groups. RESULTS : Waste glass fine aggregates were classified as reactive when applying the chemical method. In the physical method, they were classified as reactive at 100% and latent reactive at 1%, based on the mixing ratio. Additionally, we discovered that the reliability of the chemical method was low since the ASR of the aggregates was classified differently based on the evaluation method, while the results of the chemical and physical test methods were inconsistent. CONCLUSIONS : To determine the alkali reactivity of recycled aggregates, the complex use of chemical and physical methods and analysis based on the mixing ratio of the reactive aggregates are required. Small amounts of waste glass aggregate replacements affected the ASR. Because ASR reaction products can affect the long-term thermal expansion of the structure, further research is needed to use ASR aggregates in structures.

PURPOSES : The purpose of this study is to confirm the thermal expansion characteristics of concrete mixed with 1% waste glass fine aggregates, which is the amount stipulated for recycled aggregates in the current quality standard. METHODS : The coefficient of thermal expansion was measured by applying AASHTOT 336-10 using a LVDT. The results measured were used as physical properties in a finite element analysis to confirm the change in tensile stress and the displacement of the right angle section of the upper slab of a concrete pavement due to admixture substitution. RESULTS : The thermal expansion coefficients of concrete based on the replacement rate of the admixture when the waste glass fine aggregates are replaced are within the range of the thermal expansion coefficients of concrete specified in the Federal Highway Administration report. As the replacement rate of the admixture increases, the thermal expansion coefficient of concrete decreases. As the thermal expansion coefficient decreases, the slab pavement curling displacement and the tensile stress of the center of the upper slab of concrete decrease. CONCLUSIONS : In the short term, the presence or absence of waste glass fine aggregates does not significantly affect the thermal expansion coefficient of concrete. However, in the long term, waste glass fine aggregates are reactive aggregates that causes ASR, which creates an expandable gel around the aggregates and results in concrete expansion. Therefore, the relationship between ASR and the thermal expansion coefficient must be analyzed in future studies.

This study investigates the relationship between vitamin C intake and obesity prevalence among Korean adults. Based on data of the Korean National Health and Nutrition Examination Survey (2016-2017), a total of 1,356 participants were included in this analysis. Increasing the dietary vitamin C intake resulted in a significantly decreased occurrence of BMI obesity prevalence (p for trend=0.0194) and WC obesity prevalence (p for trend=0.0452). Moreover, increasing the dietary vitamin C intake of Korean adults having a high frequency of eating breakfast resulted in significantly decreased BMI obesity prevalence (p for trend=0.0406) and WC obesity prevalence (p for trend=0.0432). Among the Korean adults who ate out frequently, decreased BMI obesity prevalence was determined with increased intakes of dietary vitamin C (p for trend=0.0193) and total vitamin C (food and dietary supplements) (p for trend=0.0429), whereas significant decrease in WC obesity prevalence was observed with increased dietary vitamin C intake (p for trend=0.0484). Our results provide conclusive evidence that consumption of dietary vitamin C is associated with obesity prevalence in Korean adults, according to their habits of eating breakfast and frequency of eating out.

2020년 중국의 COVID-19 폐쇄는 한국의 풍상측에 위치한 중국의 대기오염 배출량을 감소시켰다. 몽골 북부로 부터 중국 동부를 거쳐 한반도에 이르는 지역에서는 2020년 1~2월에 기온 아노말리가 양(+)으로 온난하였고, 2020년 1월에는 동서류 아노말리가 음(−)으로 정체적인 특징을 보였다. 2019년 12월~2020년 3월에 한국 중부 서쪽의 석모리와 파도리에서 중국 배출량 감소의 영향에 따라 PM10, NO2, O3 농도 변동이 나타났다. 파도리에서 PM10, O3 월평균 농도와 최근 4년의 월평균 농도의 비는 2019년 12월과 비교하여 중국의 COVID-19 폐쇄 이후인 2020년 1~3월에 각각 0.7~4.7%, 9.2~22.8%로 감소하였다. 2020년 1월 중국의 춘절 기간에는 석모리와 파도리에서 PM10, NO2, O3 농도가 최근 4년의 춘절 기간과 마찬가지로 감소하였다. 그러나 2020년 1월 평균 농도가 최근 4년 1월과 비교하여 감소한 것은 중국 춘절 전후의 기간에도 배출량이 감소하였던 것과 관련 있다. 2020년 1~3월 석모리의 PM10, NO2, O3 농도의 비 ( /M)는 각각 70.8~89.7%, 70.5~87.1%, 72.5~97.1%이었고, 파도리에서도 각각 79.6~93.5%, 67.7~84.9%, 83.7~94.6% 로 추정 월평균(M)보다 월평균(Os)이 감소하였다. 2020년 1월에 몽골 북부로부터 중국 동부와 한반도에 이르는 지역의 온난화로 인한 광화학 반응으로 최근 4년과 비교하여 AOD가 높게 나타났으나 2020년 3월에는 풍상측인 중국에서 2차 에어로졸을 생성하는 전구물질 배출 감소로 최근 4년과 비교하여 낮은 AOD 분포를 보였던 것으로 분석되었다.

This systematic review and meta-analysis aimed to determine whether food intake is effective in preventing diseases related to cognitive impairment. We searched English databases namely MEDLINE, PubMed and ScienceDirect from 2000 to May 2020, and Korean databases namely RISS, KISS, and DBPIA from 1990 to May 2020. We divided the data into 15 groups using the food group classification of the Korean Nutrition Society (KNS). The effect size (Cohen’s d) was estimated using a random-effect model, and a 95% confidence interval was calculated for each study. We included 17 cross-sectional studies and 7 cohort studies which involved 45,115 participants. As a result of analyzing the subgroups in the Asian population of both sexes, it was observed that grain intake has a protective effect against cognitive impairment. For females, pulses and fish also have a protective role against cognitive impairment. In the case of seaweed, a negative relationship was found with a moderate protective effect against cognitive impairment (Cohen’s d:-0.533, 95% CI: -0.939, -0.126; p=0.010) in Korean studies. Dairy products are associated with an increased risk of cognitive impairment in the American and European population but drinking alcohol is associated with a lower impairment risk. These results provide a basis for formulating the dietary guidelines for preventing dementia for each country.

There is only limited evidence for the association between fruit and vegetable consumption and mental health in Korea. This study examined the relationship between fruit and vegetable consumption and mental health according to physical activity among Korean adult women. Based on data of the Korean National Health and Nutrition Examination Survey (2014-2016), a total of 5,332 participants were included in this analysis. With increasing fruits and vegetables consumption, the prevalence of depressive mood was significantly decreased (p for trend=0.0248). The prevalence of stress perception (p for trend=0.0422) and the prevalence of depressive mood (p for trend=0.0300) were decreased with increasing fruit consumption. The prevalence of depressive mood was significantly decreased when fruit and vegetable consumption (p for trend=0.0370) and fruit consumption (p for trend=0.0356) were increased for those Korean women with low intensity of physical activity. For the obesity group (Body mass index 25 kg/m2), the prevalence of depressive mood was decreased with increasing fruit and vegetable consumption (p for trend=0.0111) and increasing fruit consumption (p for trend=0.0165). In conclusion, fruit and vegetable consumption were associated with mental health according to physical activity among Korean adult women. Further prospective studies are warranted to explore the association between fruit and vegetable consumption and mental health among Korean adult women.

큰열매모자반은 제주도 연안 생태계에서 수관층을 형성하는 중요한 다년생 갈조류이다. 이 연구는 2018년 5월부터 2019년 6월까지 제주연안에서 큰열매모자반 개체군의 생장 및 생식패턴을 밝히기 위하여 수행되었다. 큰열매 모자반 개체군의 정량조사를 통해 월별 형질분석, 밀도 및 현존량 분석을 실시하였다. 또한 큰열매모자반의 생식자원 배분 특성을 조사하기 위하여 전체 엽체길이 및 엽중량에 대한 생식엽길이와 중량비율을 측정하였다. 조사지역에서 큰열매모자반의 최대 엽장은 6월에 135.3±20.0 cm, 최대 엽중량은 5월에 평균 3.6±2.1 kg·wet-wt., 평균밀도는 4.5 individuals·m-2 및 평균현존량은 4.6 kg·wet-wt.·m-2였다. 생식기탁의 형성은 4~8월 (수온 16.1~25.0°C)까지 관찰되었으며, 난방출 시기는 6~7월 (수온 19.3~22.9°C)이 었다. 엽체의 발달은 수온 14.1°C 이상의 조건에서 이루어졌으며, 성숙에 요구되는 유효 적산온도는 726.3 degreedays였다. 큰열매모자반의 생식배분은 6월에 최대 69.3% 로 나타났다. 큰열매모자반의 생장과 성숙패턴은 생장기 (10~1월), 생식시작기 (2~4월), 성숙기 (5~6월), 난 방출기 (6~7월) 및 휴지기 (8~9월)로 구분되었다.

The objective of this study was to investigate the effect of dietary education on undergraduate student’s health, environment, and consideration. A total of 54 participants were recruited from an undergraduate student in Seoul. We conductive quantitative analysis of a structured questionnaire and qualitative analysis of interviews recorded by photovoice. There are significant differences among knowledge, dietary attitude, and food behavior in the field of health (p<0.001). In the field of health, photovoice data were categorized as ‘health care practice’, ‘Korean dietary lifestyles’, or ‘awareness of importance of health’ (p<0.001). In the field of environment, photovoice data were categorized as ‘environment-friendly dietary lifestyle’ and ‘environmental contamination minimization’(p<0.001). In the field of consideration, photovoice data were categorized as ‘gratitude for others’, ‘joy of cooking’or ‘eating meals together’(p<0.01). In conclusion, we found that dietary education about health, environment, and consideration may affect healthy dietary lifestyle among undergraduate students. Our findings may warrant further studies to develop significantly effective dietary education for undergraduate students.