The discussion concerning the modifications of Moreland test construction is also presented.Various forms of tobacco smoking and nicotine vaping tools are available on the market. This study quantified the prevalence of and identified factors associated with patterns of smoking and nicotine vaping among university students in the United Arab Emirates (UAE). A cross-sectional sample of students enrolled in three public universities was surveyed. Self-reported current smoking and nicotine vaping were recorded. Of 1123 students, 81.7% completed the online survey (mean age, 20.7 ± 3.4 (SD) years; 70.7% females). The prevalence of current smoking was 15.1% while the prevalence of current nicotine vaping was nearly 4.0%. Among current smokers, 54.7% reported conventional smoking only, 15.1% reported nicotine vaping only, and 28.8% were poly-users. Conventional midwakh (47.5%), followed by conventional shisha/waterpipe (36.7%), conventional cigarettes (36.7%), electronic shisha/waterpipe (25.2%), and electronic cigarettes (24.5%), were most commonly reported by students. Students aged 20-25 years (adjusted odds ratios (aOR) 2.08, 95% confidence interval (CI) 1.18-3.67) or >25 years (aOR 4.24, 95% CI 1.41-12.80) had higher odds of being current smokers compared to those aged 17-19 years. The male gender was also independently associated with higher odds of being a current smoker (aOR 5.45, 95% CI 3.31-8.97) as well as higher odds of smoking cigarettes, shisha, and midwakh, or nicotine vaping compared to being female.  https://www.selleckchem.com/products/jw74.html  Of nicotine vaping users, 36.1% reported using nicotine vaping because they enjoyed the flavor and vaporizing experience and 34.4% used it to help them to quit smoking. A relatively high prevalence of self-reported smoking was reported among university students in the UAE. The findings also suggest that nicotine vaping use is relatively widespread, but still less common than traditional smoking. Vigilant and tailored university-based smoking control and preventive measures are warranted.There is a large body of evidence that exposure to simulated natural scenes has positive effects on emotions and reduces stress. Some studies have used self-reported assessments, and others have used physiological measures or combined self-reports with physiological measures; however, analysis of facial emotional expression has rarely been assessed. In the present study, participant facial expressions were analyzed while viewing forest trees with foliage, forest trees without foliage, and urban images by iMotions' AFFDEX software designed for the recognition of facial emotions. It was assumed that natural images would evoke a higher magnitude of positive emotions in facial expressions and a lower magnitude of negative emotions than urban images. However, the results showed only very low magnitudes of facial emotional responses, and differences between natural and urban images were not significant. While the stimuli used in the present study represented an ordinary deciduous forest and urban streets, differences between the effects of mundane and attractive natural scenes and urban images are discussed. It is suggested that more attractive images could result in more pronounced emotional facial expressions. The findings of the present study have methodological relevance for future research. Moreover, not all urban dwellers have the possibility to spend time in nature; therefore, knowing more about the effects of some forms of simulated natural scenes surrogate nature also has some practical relevance.Background Currently, sedentariness is assessed over a short period of time, thus it is difficult to study its cognitive implications. To investigate the cognitive consequences of a sedentary lifestyle, the past level (i.e., the sedentary time accumulated over the years) and current level of sedentariness should be considered. This pilot study aimed to investigate the negative association between a sedentary lifestyle and cognition by considering both the current and past sedentariness. It was expected that the physical activity level moderates the potential negative association between sedentariness and cognition. Methods 52 college students (Mage = 20.19, SDage = 2; 36 women) participated in the study. Current sedentariness (ratio of sedentary time in the last year), past sedentariness (ratio of sedentary time accumulated in previous years), and physical activity (ratio of time spent in physical activity in years) were assessed using a questionnaire. Cognitive inhibition, cognitive flexibility, and working memory updating were measured through three specific tests. Results Past sedentariness significantly explained the inhibition performance when controlled for physical activity, whereas current sedentariness did not. More precisely, past sedentariness only negatively predicted cognitive inhibition when the physical activity level was low (β = -3.15, z(48) = -2.62, p = 0.01). Conclusions The impact of sedentariness on cognitive functioning might only be revealed when past sedentariness and physical activity are controlled.Harmful algal bloom (HAB) events have alarmed authorities of human health that have caused severe illness and fatalities, death of marine organisms, and massive fish killings. This work aimed to perform the long short-term memory (LSTM) method and convolution neural network (CNN) method to predict the HAB events in the West Coast of Sabah. The results showed that this method could be used to predict satellite time series data in which previous studies only used vector data. This paper also could identify and predict whether there is HAB occurrence in the region. A chlorophyll a concentration (Chl-a; mg/L) variable was used as an HAB indicator, where the data were obtained from MODIS and GEBCO bathymetry. The eight-day dataset interval was from January 2003 to December 2018. The results obtained showed that the LSTM model outperformed the CNN model in terms of accuracy using RMSE and the correlation coefficient r as the statistical criteria.The COVID-19 pandemic has worked as a catalyst, pushing governments, private companies, and healthcare facilities to design, develop, and adopt innovative solutions to control it, as is often the case when people are driven by necessity. After 18 months since the first case, it is time to think about the pros and cons of such technologies, including artificial intelligence-which is probably the most complex and misunderstood by non-specialists-in order to get the most out of them, and to suggest future improvements and proper adoption. The aim of this narrative review was to select the relevant papers that directly address the adoption of artificial intelligence and new technologies in the management of pandemics and communicable diseases such as SARS-CoV-2 environmental measures; acquisition and sharing of knowledge in the general population and among clinicians; development and management of drugs and vaccines; remote psychological support of patients; remote monitoring, diagnosis, and follow-up; and maximization and rationalization of human and material resources in the hospital environment.