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Hippo/YAP signaling is implicated in tumorigenesis and progression of various cancers. By inhibiting a plethora signaling cascades, resveratrol has strong anti-tumorigenic and anti-metastatic activity. In the present study, we demonstrate that resveratrol decreases the expression of YAP target genes. In addition, our data showed that resveratrol attenuates breast cancer cell invasion through the activation of Lats1 and consequent inactivation of YAP. Strikingly, we also demonstrate that resveratrol inactivates RhoA, leading to the activation of Lats1 and induction of YAP phosphorylation. Further, resveratrol in combination with other agents that inactivate RhoA or YAP showed more marked suppression of breast cancer cell invasion compared with single treatment. Collectively, these findings indicate the beneficial effects of resveratrol on breast cancer patients by suppressing the RhoA/Lats1/YAP signaling axis and subsequently inhibiting breast cancer cell invasion.
Background: While smoking prevalence in Korean men has been decreasing, it is increasing in Korean women. Little is known about women's smoking inequalities in Korea. This study was conducted to investigate the association of socioeconomic indicators with the initiation and cessation of smoking among Korean women. Methods: This was a cross-sectional study on 9,089 women aged 25-64 years from the 2008 Seoul Community Health Survey. The data on smoking and socioeconomic status were obtained through face-to-face interviews. Smoking initiation rate was defined as the proportion of the individuals who had started smoking at least one cigarette among all subjects. Smoking cessation rate was calculated by dividing the number of individuals who had quit smoking by the number of ever smokers. Education level, total family income and occupation were investigated as socioeconomic indicators. Results: Education level was significantly associated with both initiation and cessation of smoking. Lower educated women had a higher likelihood of smoking initiation (odds ratio [OR], 1.72; 95% confidence interval [CI], 1.17 to 2.51) but lower likelihood of smoking cessation (OR, 0.38; 95% CI, 0.22 to 0.66) than higher educated women. Smoking initiation rate was higher in manual workers (OR, 1.65; 95% CI, 1.20 to 2.27) than in non-manual workers. However, there were no significant differences of both initiation and cessation of smoking according to total household income. Conclusion: This study shows that there are smoking inequalities among Korean women. It is thought that education level and occupation are important determinants of women's smoking status.
본 작품은 꽃을 주제로 한 직물 디자인이다. 본 작품에서도 모티브가 된 꽃은 우리 주위 어디에서나 쉽게 접할 수 있고 평범하면서도 무난한 소재인 동시에 소비자의 기호를 가장 크게 만족시켜주므로, 섬유디자인에서는 약 70%라는 비중을 꽃패턴이 차지한다. 섬유디자인에서 꽃패턴은 사실적인 문양, 로코로, 아르누보, 아르데코등의 전통적인 주조에서부터 오늘날에는 기하, 추상패턴등과 중복된 복합조의 패턴이 그 주류를 이루고 있으며 꽃의 여러 가지 표현방법과 꽃의 크기, 배열종류의 혼합에 따라서 다양한 느낌의 디자인을 구성할 수가 있다. 본 작품 또한 ‘속삭임’이라는 제목의 꽃을 주제로 한 것으로, 약화시킨 나비를 첨가하여 따뜻하고 정다운 느낌이 나도록 디자인하였으며 직물로서 여성스러움과 고급스러움에 중점을 둔 여성복지 용도로 제작하였다.
The purpose of this study is to provide the basic data for related policies by analyzing the relationship between the non-payment, optional treatment, hospitalization decision, and the payment of medical expenses. A total of 7,317 inpatients were selected as the final subjects using the 2011-2015 data of the Korea Medical Panel. It was analyzed using the chi-square test and the generalized estimating equation (GEE), and the demographic variables affecting payment of medical expenses and use of medical treatment variables were included as the correction variables. As a result of the analysis performed, compared to the inpatients with non-payment expenditures less than 250,000 won, 250,000 won to 500,000 won (OR: 1.19 95% CI: 1.01-1.39, P-value: 0.0319), 500,000 won to less than 1 million won (OR: 1.75 95% CI: 1.46-2.09, P-value: <.0001), over 1 million won (OR: 1.58 95% CI: 1.27-1.96, P-value: <.0001), there was a burden on the expenditure of medical expenses. Furthermore, while there was no recommendation for optional treatment, the inpatients who received optional treatment had a higher payment of medical expenses compared to the inpatients who did not (OR: 1.20 95% CI: 1.00-1.45, P-value: 0.0490). The patients who decided to be hospitalized had a higher payment of medical expenses than those who decided to be hospitalized by themselves (OR: 1.14 95% CI: 1.03-1.27, P-value: 0.0149). As a result of this study, the non-payment, optional treatment, and the hospitalization decision had an effect on the payment of medical expenses. Optional treatment was closed after 2018, but the payment of medical expenses due to the non-payment and the hospitalization decisions still exists, and hence, there is a need for the policy improvement to reduce them.
Thirteen compounds were isolated from n-hexane layer of the extracts of feces of Trogopterus xanthipes. Their chemical structures were elucidated as lupeol (1), lupenone (2), simiarenol (3), epitaraxerol (4), taraxerone (5), fatty acid esters of 11-oxo-b-amyrin (6), 12-oleane-3,11-dione (7), 5b-stigmastan-3a-ol (8), 5b-stigmastan-3b-ol (9), 5a-stigmastan-3-one (10), 5b-stigmastan-3-one (11), 5b-cholestan-3a-ol (12), and 2-methoxyphenanthrene (13) on the basis of spectroscopic data. Even though all the isolated compounds are known, to the best of our knowledge, all the compounds (1-13) are reported from this species for the first time.
The purpose of this study is to find out whether image similarity between celebrities and brands on social network service be a determinant to predict advertising effectiveness. To this end, an advertising effect prediction model for celebrity endorsed advertising was created and its validity was verified through a machine learning method which is a big data analysis technique. Firstly, the celebrity-brand image similarity, which was used as an independent variable, was quantified by the association network theory with social big data, and secondly a multiple regression model which used data representing advertising effects as a dependent variable was repeatedly conducted to generate an advertising effect prediction model. The accuracy of the prediction model was decided by comparing the prediction results with the survey outcomes. As for a result, it was proved that the validity of the predictive modeling of advertising effects was secured since the classification accuracy of 75%, which is a criterion for judging validity, was shown. This study suggested a new methodological alternative and direction for big data-based modeling research through celebrity-brand image similarity structure based on social network theory, and effect prediction modeling by machine learning. 본 연구는 소셜 빅데이터에 기반을 둔 유명인과 브랜드의 이미지 유사도가 광고효과를 예측할 수 있는 결정변수가 될 수 있는지를 파악하기 위해, 광고효과 예측모형을 생성하고 빅데이터 분석기법인 기계학습 방법을 통해 그 타당도를 검증하는 것을 목적으로 하였다. 이를 위해 SNS상의 키워드 네트워크 구조에 기반하여 유명인-브랜드 이미지 유사도를 정량화하고, 학습 데이터를 통해 이미지 유사도를 독립변수로, 광고효과 데이터를 종속변수로 하는 다중회귀모형을 반복 실시하여 광고효과 예측모형을 생성하였다. 이렇게 생성된 예측모형의 정확도를 판단하기 위해 예측 데이터에서 얻은 광고효과 예측값과 비교 기준으로서의 서베이값을 비교한 결과, 타당도를 판단하는 기준치인 75%의 분류 정확도를 보였으므로 본 광고효과 예측 모델링의 타당성은 확보된 것으로 입증되었다. 본 연구는 유명인-브랜드 이미지 유사성 구조를 소셜 네트워크 구조로 설명하고 그 효과를 기계학습을 통한 예측 모델링으로 검증하여 빅데이터 기반 모델링 연구에 새로운 방법론적 대안과 방향을 제시하였다.