No abstract

No abstract

This study investigated sex differences in homonegativity and their correlates among 197 Vietnamese college students (males = 49, females = 148, M = 20.9 years, SD = 2.9) in Ho Chi Minh City. The survey included Vietnamese-language versions of four scales measuring attitudes toward homosexuality (ATHS), traditional masculinity ideology, knowledge of homosexuality, and contact experiences with homosexuals. An exploratory factor analysis indicated a 3-factor structure for the ATHS: Homonegativity, Tolerance, and Positive Images. Male respondents reported significantly higher scores on homonegativity. Traditional masculinity ideology was positively related to females' homonegativity, but negatively correlated with tolerant attitudes of both males and females. Knowledge about homosexuality was negatively correlated with homonegativity. Media contact with homosexuals was negatively correlated with males' homonegativity, but positively correlated with both females and males' tolerant attitudes. Results suggest that future research develop a new scale to measure Vietnamese's homonegativity and that media contact as well as ample and accurate knowledge about homosexuality can alter homonegativity.

No abstract

Changes in surface water might result in natural disasters such as floods, water shortages, landslides, waterborne diseases, which lead to loss of lives. Timely extracting for surface water and predicting its movement is essential for planning activities and decision-making processes. Most existing works on extracting water surface using satellite images focus on static spectral images and ignore the temporal evolution of data in streams, leading to less accuracy and lack of prediction power. Although some works realize that modeling temporal information of satellite signals could boost the forecasting capability on environmental changes, most of them only focus on prediction tasks independently and separately from the extraction task. In this paper, we propose a unified framework for water extraction and change prediction (WECP) built on top of imagery data streams, which are free to access from orbiting satellites, to locate water surface and predict its changes over time. Our framework is evaluated on Landsat 8 data due to its high spatial resolution. Empirical evaluations on real imagery datasets of different landscapes reveal that our framework is robust in extracting and capturing spatio-temporal changes in the water surface.