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Abstract Background The Arab Teens Lifestyle (ATLS) questionnaire was an initiative to assess the lifestyle habits influencing obesity rates in the Middle East and North Africa (MENA) region, including physical activity (PA) patterns, sedentary and eating behaviours. Since its implementation, the ATLS questionnaire has been used in several studies among different age groups and populations. This instrument has not previously been administered among the university students of the Eastern Province of Saudi Arabia, where the obesity rates are the highest in the country. This research was the first that aimed to identify lifestyle habits influencing the rates of obesity among 18-25-year-old university students in the Eastern Province of the Kingdom of Saudi Arabia (KSA) using the ATLS questionnaire. Methods Quantitative cross-sectional research among n = 426 students of the Eastern Province of Saudi Arabia using the ATLS questionnaire. Results Out of n = 426 participants, n = 200 (47%) were categorised (using body mass index) as normal weight; n = 113 (26.5%) were overweight, and n = 73 (17.1%) were obese. The findings showed that most of the nutritional, PA, and sedentary behavioural factors (e.g., screen time) in the questionnaire were not associated with obesity status amongst the participants. In the obese group, more of the males that consumed fruits, French fries, cakes, sweets and doughnuts more than three times per week were likely to be obese, which was not the case for females. Conclusion The reported lifestyles of the students could potentially lead to long-term negative health effects, which is of concern given the rising rates of overweight, obesity, and obesity-related non-communicable diseases (NCDs) among the Kingdom’s adult and ageing population. Further studies are recommended to explore the knowledge, attitudes, and perceptions of Saudi students in the Eastern Province in relation to PA, sedentary behaviours, and dietary habits, along with their views on how these can be improved.

Epidemiologic research on zoonotic tuberculosis historically used Mycobacterium bovis as a surrogate measure; however, increased reports of human tuberculosis caused by other animal-associated Mycobacterium tuberculosis complex members like Mycobacterium orygis necessitates their inclusion. We performed a retrospective cohort study including persons infected with any animal-lineage M tuberculosis complex species in Alberta, Canada, from January 1995 to July 2021, identifying 42 patients (20  M bovis , 21  M orygis , 1 M caprae). Demographic, epidemiologic, and clinical characteristics were compared against persons with culture-confirmed M tuberculosis infection. The proportion of culture-positive infections caused by M orygis increased continuously from 2016 to 2020. Significantly more females at a higher median age were impacted by M orygis , with all patients originating from South Asia. Mycobacterium bovis caused significantly more extrapulmonary disease and disproportionately impacted young females, particularly those pregnant or postpartum. All infections were acquired abroad. These findings can aid in developing targeted public health interventions. [ABSTRACT FROM AUTHOR]

Background: The Arab Teens Lifestyle (ATLS) questionnaire was an initiative to assess the lifestyle habits influencing obesity rates in the Middle East and North Africa (MENA) region, including physical activity (PA) patterns, sedentary and eating behaviours. Since its implementation, the ATLS questionnaire has been used in several studies among different age groups and populations. This instrument has not previously been administered among the university students of the Eastern Province of Saudi Arabia, where the obesity rates are the highest in the country. This research was the first that aimed to identify lifestyle habits influencing the rates of obesity among 18-25-year-old university students in the Eastern Province of the Kingdom of Saudi Arabia (KSA) using the ATLS questionnaire. Methods: Quantitative cross-sectional research among n = 426 students of the Eastern Province of Saudi Arabia using the ATLS questionnaire. Results: Out of n = 426 participants, n = 200 (47%) were categorised (using body mass index) as normal weight; n = 113 (26.5%) were overweight, and n = 73 (17.1%) were obese. The findings showed that most of the nutritional, PA, and sedentary behavioural factors (e.g., screen time) in the questionnaire were not associated with obesity status amongst the participants. In the obese group, more of the males that consumed fruits, French fries, cakes, sweets and doughnuts more than three times per week were likely to be obese, which was not the case for females. Conclusion: The reported lifestyles of the students could potentially lead to long-term negative health effects, which is of concern given the rising rates of overweight, obesity, and obesity-related non-communicable diseases (NCDs) among the Kingdom's adult and ageing population. Further studies are recommended to explore the knowledge, attitudes, and perceptions of Saudi students in the Eastern Province in relation to PA, sedentary behaviours, and dietary habits, along with their views on how these can be improved. [ABSTRACT FROM AUTHOR]

This article focuses on training work carried out in artificial intelligence (AI) at the National Center for Supercomputing Applications at the University of Illinois Urbana-Champaign via a research experience for undergraduates program named FoDOMMaT. It also describes why we are interested in AI, and concludes by discussing what we've learned from running this program and its predecessor over six years. [ABSTRACT FROM AUTHOR]

This article demonstrates how scientists and engineers can use modern artificial intelligence (AI) tools such as ChatGPT and GitHub Copilot to learn computer programming skills that are relevant to their jobs. It begins by summarizing common ways that AI tools can already help people learn programming in general and then presents six new opportunities catered to the needs of scientists and engineers: 1) create customized programming tutorials for one's own domain of work, 2) learn complex data visualization libraries, 3) learn to refactor exploratory code into more maintainable software, 4) learn about inherited legacy code, 5) learn new programming languages on demand within the context of one's workflow, and 6) question the assumptions that one's scientific code is making. Taken together, these opportunities point toward a future where AI can help scientists and engineers learn programming on demand within the context of their existing real-world workflows. [ABSTRACT FROM AUTHOR]

Our biology affects how we interact with the world, including how we learn new knowledge and respond to challenges. This article explores the impact of neurochemicals in our brain on learning and explains how to leverage our biology to improve education and problem solving, focusing on computing education. Within this context, the article particularly examines the role of failure while learning. Learning, especially in technical fields, includes making errors on the path to success. Although these errors trigger the necessary neurochemical conditions for rapid learning, these failures can also be demotivating. To gain the benefits of failure while mitigating its negative consequences, this article recommends evidence-based behavioral strategies for making the best out of failing while learning and designing for failure in learning environments. [ABSTRACT FROM AUTHOR]