A survey was used with 293 male and female college students to examine problem gambling and binge drinking. The results indicate that males are more likely to engage in gambling activities, experience more consequences from gambling, and meet the criteria for problem gambling compared with females. The results further indicate that white male athletes are more likely to engage in binge drinking compared with their female counterparts. We detected both similarities and differences in correlates for gambling and drinking and found a consistent theme of gender differences for alcohol consumption, binge drinking, and gambling behavior. Implications for gender-specific prevention are discussed.

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Smart city is an aspiration of the various stakeholders of the city. We strongly believe that social media can be one of the real-time data sources, which help stakeholder to realize this dream. In this paper, we have analyzed the real-time data provided by Twitter in order to empower citizens by keeping them updated about what is happening around the city. We have implemented various clustering algorithms like k-means, Hierarchical agglomerative, LDA topic modeling on Twitter stream and reported results with purity 0.476, normal mutual information (NMI) 0.3835, and F-measure 0.54. We conclude that HA-ward outperforms Kmeans and LDA substantially. We also conclude that results are not impressive and need to design separate feature based clustering algorithm. We have identified various tasks to mine microblog in the ambit of smart city such as event detection, geo-tagging, city clustering based upon the user activity on ground.

There have been numerous epidemiological studies and intervention studies that support direct relationships between nutrition, susceptibility to stress, mental health, and cognitive function across the lifespan, suggesting a strong correlation between a healthy diet and mental well‐being (Adan et al., 2019, p. 1322–1323).