Anti-Obesity Effect of Solanum nigrum L. Ethanol Extract (SNEE) on Adipogenesis and Lipogenesis in 3T3-L1 Cell

Da Hye Choi(최다혜),Jong Hui Kim(김종희),Hyun Ju Lee(이현주),Joon Hee Han(한준희),Min Hong(홍민),Hoang Viet Bach Khoa,Luong Van Dung,Tae Hyung Kwon(권태형),Yong-Jo Ahn(안용조) 한국약용작물학회 2022 한국약용작물학회 학술대회논문집 Vol.2022 No.1

영흥 풍력발전단지의 풍력발전량 예측을 위한 입력변수 선정 및 인공신경망과 1차원 합성곱 신경망 비교

박태희(Tae-Hui Park),장다슬(Da-Seul Jang),배경민(Gyeong-Min Bae),김경민(Kyung-Min Kim),안종화(Johng-Hwa Ahn) 대한환경공학회 2021 대한환경공학회지 Vol.43 No.4

목적 : 본 연구에선 비선형적 풍력발전량 예측 모델 개발을 목적으로 총 설치 용량 46 MW의 풍력발전단지가 설치된 영흥 풍력발전 단지의 자료를 이용하여 인공신경망(artificial neural network, ANN)과 1차원 합성곱신경망(1-dimension convolutional neural network, 1D-CNN)의 성능을 비교하고자 하였다. 방법 : 자료는 46 MW 발전능력을 가진 영흥 풍력발전단지의 2018년 1월부터 12월의 1시간 단위 풍력발전량 자료와 기상청에서 얻은 기상자료를 이용하였다. 최적 입력변수를 선정을 위하여 문헌연구를 바탕으로 시행착오를 거쳐 인자를 선정하였다. 전처리 과정을 거친 17,306개의 자료의 80%를 학습(training), 20%를 테스트(test)으로 사용하였으며, 학습 자료의 20%를 검증(validation)자료로 구성하였다. 모델 내 활성화 함수로는 rectified linear unit를 사용하였으며, 시행착오법을 통해 하이퍼파라미터(hyperparameter)의 최적값을 도출하였다. 모든 모델은 Python의 Keras 라이브러리를 이용하여 설계하였으며, 성능지표인 결정계수(coefficient of determination, R²), 평균제곱근오차(root mean square error, RMSE), 평균절대오차(mean absolute error, MAE) 등은 Scikit-learn 라이브러리에서 이용하였다. 결과 및 토의 : 최적 입력변수는 풍속, 풍향, 온도, 습도 등이었다. ANN의 최적점으로는 은닉층 8층, 은닉층별 노드수는 모두 100으로 나왔다. 최적 ANN 모델에서 성능지표는 R²=0.848, MAE=1.054, RMSE=1.616이었다. 1D-CNN 의 최적점으로는 합성곱층 4층, 층별 필터 수는 1층부터 64, 128, 64, 32개, 전결합층 1층에 노드 100개이다. 최적 1D-CNN 모델의 성능지표는 R²=0.875, MAE=0.982, RMSE=1.583였다. 1D-CNN이 ANN보다 R²는 높고, MAE와 RMSE는 낮았다. ANN, 1D-CNN의 결정계수가 모두 0.8 이상으로 예측 성능이 우수하나, 1D-CNN이 ANN보다 모든 성능지표에서 높았다. 결론 : 최적화된 모델의 성능지표 비교 결과 1D-CNN이 ANN보다 높은 성능을 보여 영흥 풍력 발전소 발전량 예측에 적합할 것으로 보인다. 최적 입력변수는 풍속, 풍향, 온도, 습도였다. Objectives : In this study, deep learning models of artificial neural network (ANN) and one-dimension convolutional neural networks (1D-CNN) were compared to predict nonlinear wind power generation at Yeongheung wind power plant. Methods : The study site was Yeongheung-do, which has a 46 MW wind power plant. Hourly wind power and meteorological data from January to December 2018 were collected. After pre-processing with standardscaler, the training data were 64%, the validation data were 16%, and the test data were 20%. The optimum input variables of the model were selected using literature, and trial and error method. Rectified linear unit was used as the activation function. Hyperparameters were adjusted by trial and error method to optimized models. To compare the optimized models, the coefficient of determination (R²), mean absolute error (MAE), and root mean square error (RMSE) were used as the performance efficiency. Both ANN, and 1D-CNN were imported from the Keras library, and all of the performance efficiency was imported from the Scikit-learn library. Results and Discussion : The optimized input variables in this study were wind speed, wind direction, temperature, and humidity. The optimized ANN performance was R²=0.848, MAE=1.054, and RMSE=1.616, and the hyperparameters were 8 hidden layers with 100 nodes in each layer. The optimized 1D-CNN (R²=0.875, MAE=0.982, and RMSE=1.583) had 4 convolutional layers and the number of filters were 64, 128, 64, and 32 in order from the first layer, and one hidden fully connected layer had 100 nodes. The 1D-CNN had higher R², and lower MAE and RMSE than the ANN. Therefore, the 1D-CNN was selected as the optimized model to predict wind generation of the Yeongheung wind power plant. Conclusions : The optimized 1D-CNN model in this study was more effective in predicting the Yeongheung wind power plant than the ANN. The optimal input variables were wind speed, wind direction, temperature, and humidity.

Distinct Bacterial and Fungal Communities Colonizing Waste Plastic Films Buried for More Than 20 Years in Four Landfill Sites in Korea

Chung Joon-hui,Yeon Jehyeong,Seong Hoon Je,An Si-Hyun,Kim Da-Yeon,Yoon Younggun,Weon Hang-Yeon,Kim Jeong Jun,Ahn Jae-Hyung 한국미생물·생명공학회 2022 Journal of microbiology and biotechnology Vol.32 No.12

Plastic pollution has been recognized as a serious environmental problem, and microbial degradation of plastics is a potential, environmentally friendly solution to this. Here, we analyzed and compared microbial communities on waste plastic films (WPFs) buried for long periods at four landfill sites with those in nearby soils to identify microbes with the potential to degrade plastics. Fourier-transform infrared spectroscopy spectra of these WPFs showed that most were polyethylene and had signs of oxidation, such as carbon-carbon double bonds, carbon-oxygen single bonds, or hydrogen-oxygen single bonds, but the presence of carbonyl groups was rare. The species richness and diversity of the bacterial and fungal communities on the films were generally lower than those in nearby soils. Principal coordinate analysis of the bacterial and fungal communities showed that their overall structures were determined by their geographical locations; however, the microbial communities on the films were generally different from those in the soils. For the pulled data from the four landfill sites, the relative abundances of Bradyrhizobiaceae, Pseudarthrobacter, Myxococcales, Sphingomonas, and Spartobacteria were higher on films than in soils at the bacterial genus level. At the species level, operational taxonomic units classified as Bradyrhizobiaceae and Pseudarthrobacter in bacteria and Mortierella in fungi were enriched on the films. PICRUSt analysis showed that the predicted functions related to amino acid and carbohydrate metabolism and xenobiotic degradation were more abundant on films than in soils. These results suggest that specific microbial groups were enriched on the WPFs and may be involved in plastic degradation.

건물형 지하구조물의 3차원 데이터 모델에 관한 연구

류지희(Ryu, Ji Hui),이지연(Lee, Ji Yeon),정다운(Jeong, Da Woon),안종욱(Ahn, Jong Wook) 대한공간정보학회 2022 대한공간정보학회지 Vol.30 No.1

본 연구는 지하 공간에서 발생하는 안전사고의 예방·대응을 위하여 『지하안전관리에 관한 특별법』에서 명시하는 지하구조물 중 지하주차장, 지하철 역사, 지하보도, 지하상가를 대상으로 건물형 데이터 모델을 개발하는 것을 목적으로 한다. 이를 위해 우선 3차원 공간정보 관련 국제 표준 데이터 모델 간의 비교·검토를 통해 국내 지하정보환경 및 특성에 적합한 참조 모델을 선정한다. 이후 건물형 지하구조물의 표준 구성 요소를 도출하고 요소 간의 확장 작업을 통해 국제 표준 데이터 모델에 앞서 도출한 표준 구성 요소를 적용하여 확장한다. 마지막으로 UML을 이용하여 표준화된 형태의 건물형 지하구조물의 3차원 데이터 모델에 관한 논리적 모델을 설계하고, 그 예를 시각화 구현한다. 본 연구 결과를 바탕으로 기존 지하공간통합지도에서 부족했던 건물의 실내 공간정보 영역까지 그 표현 범위를 확장했다는 것에 학술적 의의가 있을 것으로 사료된다. This study developed a building-type data model for the underground parking lot, subway station, underground passage, and underground shopping centre among underground structures which are specified in the special act on managing underground safety to prevent and deal with safety accidents. The reference model was selected based on the domestic underground environment and characteristics by comparing international standard data models of 3-Dimensional spatial information. This model extended with mapping process by applying extracted standard components of the building-type underground structure to the international standard data model. It developed a logical model about the 3D data model of standardized building type underground structure and visualized the examples by UML. It has academic significance as it overcomes the limitations of the current underground spatial integration map by extending the scope of expression to interior spatial information.

The Influence of O20 Service Usability on the Purchase Intention through Reliability Formation Process : Focusing on Smart Order of F&B industry

Hyung Jin Kim,Hui Ae Ahn,Da Hye Kim,Seong Soo Cha 한국유통과학회 2017 KODISA ICBE (International Conference on Business Vol.2017 No.-

With the popularity of smartphones, the limitations of media access tools have been removed, and marketing using location-based services has been activated due to digital technology development, attracting customers via O2O(online to offline) service, or online, and leading to offline marketing. O2O stands for Online to Offline, a new business model that connects and combines online and offline. It is expected that the O2O service will emerge as the most promising business in the IoT era, among which the Smart order, which is the leading business, will be the marketing service especially for the Korean food and restaurant industry. In this study, it is investigated how the accessibility, ease and innovation of smart orders affect usability, and then this affects reliability, and whether this formed reliability affects the intent to purchase. At this time, the TAM Theory was applied to predict the consumer’s intention to accept the technology based on its usefulness. As a result, accessibility, ease of use, innovation, and ease of smart order, among the three external variables applying the model of the structural equation, had the greatest impact on usability. Accordingly, the restaurant industry, especially franchise companies, should highlight the ease of smart orders and establish marketing strategies for the O2O service infrastructure.

섬유 배향 오차를 고려한 원추형 복합재 쉘의 이론적 설계 및 실험적 검증

황상균(Sang Kyun Hwang),권다솜(Da Som Kwon),안준혁(Jun Hyeuk Ahn),황희윤(Hui Yun Hwang) 대한기계학회 2016 대한기계학회 춘추학술대회 Vol.2016 No.4

지하공간통합지도의 3차원 터널 데이터 모델에 관한 연구

이지연(Lee, Ji Yeon),류지희(Ryu, Ji Hui),정다운(Jeong, Da Woon),안종욱(Ahn, Jong Wook) 한국측량학회 2021 한국측량학회지 Vol.39 No.6

P-10 : Role of Polypyrimide Tract-Binding Protein in HCV RNA Replication

( Hye Soo Son ),( Bo Kyoung Kim ),( Da Hui Ahn ),( Eun Ju Baek ),( Jeong Hoon Park ),( Kyung Soo Chang ) 대한임상병리사협회 2008 임상미생물검사학회 발표자료집 Vol.2008 No.-

Background : Translation initiation of the hepatitis C virus (HCV) is regulated by an internal ribosome entry site (IRES) which requires polypyrimidine tractbinding protein (PTB), which binds to the 5``-untranslated region (UTR) and the 3``-UTR and the end of the core coding region of HCV RNA, for its function. Aims of this Study are to determine the role of PTB in HCV replication. Methods : siRNA technology was used to specifically knockdown the PTB expression in the cell. We determined whether down-expression of PTB affects the EMCV IRES-mediated translation, and examined whether interferon (IFN) down-regulates PTB expression. Results : In this study, we discovered that the level of PTB expression was efficiently decreased by PTB-specific siRNA. PTB knockdown expression by siRNA significantly reduced the efficiency of cell colony formation induced by HCV RNA replication. PTB siRNA resulted in a significant reduction of PTB expression and therein HCV RNA replication in a subgenomic HCV replicon-bearing Huh7 cell line, suggesting that PTB is required for efficient HCV replication in vivo. Result: PTB siRNA does not significantly affect the efficiency of the EMCV IRES-mediated translation. IFN-α resulted in an inhibition of PTB expression, suggesting a potential mechanism by which IFN inhibits HCV replication. Discussion : PTB siRNA efficiently knockdowns the level of PTB expression and subsequently resulted in a significant reduction of HCV RNA replication, indicating that PTB is required for efficient HCV RNA replication in vivo. It appears that IFN-α inhibits PTB expression, suggesting that inhibition of HCV replication by IFN might be due to suppression of cellular proteins that are required for HCV RNA replication.

Anti-gout Effect of Asparpagus (Asparagus officinalis L.) Root Water Extract

Hyeon Ju Lee(이현주),Tae Hyung Kwon(권태형),Joon Hee Han(한준희),Da Hye Choi(최다혜),Min Hong(홍민),Jong Hui Kim(김종희),Jae Hee Lee(이재희),Hae Ju Kang(강해주),Yong Jo Ahn(안용조) 한국약용작물학회 2022 한국약용작물학회 학술대회논문집 Vol.2022 No.1

아스파라거스(Asparagus officinalis L.) 뿌리 추출물의 항염증 및 항통풍 효과

이현주(Hyeon Ju Lee),한준희(Joon-Hee Han),홍민(Min Hong),최다혜(Da-Hye Choi),김종희(Jong-Hui Kim),박가희(Ka-Hee Park),박연희(Yeon-Hee Park),이재희(Jae Hee Lee),강해주(Hae Ju Kang),권태형(Tae-Hyung Kwon),안용조(Yong Jo Ahn) 한국식품과학회 2022 한국식품과학회지 Vol.54 No.6

본 연구에서는 ARW의 항염증 및 항통풍 효능을 평가하였다. LPS가 처리된 RAW 264.7 대식 세포에서 독성을 보이지 않았으며, ARW는 NO 생성 비율을 250 μg/mL 농도에서 87.3±3.3%, 500 μg/mL 농도에서 73.5±4.7%으로 NO 생성을 억제하였다. 또한 LPS를 단독 처리한 군의 경우 iNOS, COX-2 mRNA 발현이 증가하였고 LPS 및 ARW 500 μg/mL 처리한 농도군에서 COX-2 및 iNOS의 mRNA와 단백질 발현 수준이 감소함을 확인할 수 있었다. MSU를 주입하여 통풍을 유도한 마우스 발 부종은 ARW를 섭취한 군과 비교하여 감소하였다. 통풍 유도 마우스의 혈중요산, creatinine 및 BUN의 농도를 측정한 결과 ARW 투여군에서 creatinine과 요산이 감소하였으며, 마우스 신장에서 URAT1과 GLUT9의 mRNA와 단백질 발현 분석 결과 또한 감소하였다. HLPC를 이용하여 ARW의 지표성분 분석 결과 caffeic acid 함량은 1.25 mg/g, 루틴 함량은 0.08 mg/g으로 측정되었다. 국내에서 아스파라거스는 순 부위만 식용으로 사용하고 뿌리 등은 식품 원료로 등록되지 않아 모두 폐기되고 있다. 따라서 본 연구를 통해 ARW의 기능성 소재로서의 개발 가능성을 확인하였고, 향후 독성 평가 및 원료의 특성 분석 등을 통하여 한시적식품원료 등록 및 기능성 소재로서의 개발에 도움이 될 것으로 사료된다. This study aimed to evaluate the anti-inflammatory and anti-gout effects of asparagus root water extract (ARW). ARW was not cytotoxic up to 500 μg/mL and effectively inhibited nitric oxide production in lipopolysaccharide-induced RAW 264.7 macrophages. It was confirmed that the mRNA and protein expression levels of COX-2 and iNOS decreased at an ARW concentration of 500 μg/mL. We also explored the anti-gout effects using a monosodium urate-induced mouse model. Decreased concentrations of uric acid, creatinine, and blood urea nitrogen were observed at an ARW concentration of 400 μg/mL. The mRNA and protein expression of URAT1 and GLUT9 in the mouse kidney decreased to the level of the positive control (allopurinol 50 μg/mL) at an ARW concentration of 400 μg/mL. We analyzed the caffeic acid and rutin contents in the ARW using HLPC; the results obtained were 1.25 and 0.08 mg/g, respectively. We suggest that ARW can be used as a functional materials agent, for its anti-inflammatory and anti-gout properties.