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Health services in Iraq - A cross-sectional survey of adolescents in Basra

Al Saeedi et al. | Aug 12, 2022

Health services in Iraq - A cross-sectional survey of adolescents in Basra

This study is a cross-sectional survey of adolescents in Basra, Iraq, from November 2020 to March 2021 about types of adolescent problems, the individuals and institutions adolescents turn to, and the role of public health centers in dealing with their problems. The survey found that psychological problems represent the largest proportion of health problems, and most adolescents turn to their parents to discuss their problems. The work indicates that there is an urgent need to pay attention to public health centers and provide health and psychological support to adolescents.

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Attitudes towards mental health in Indians who practice yoga regularly and those who do not

Komar et al. | Jul 13, 2022

Attitudes towards mental health in Indians who practice yoga regularly and those who do not

Whether it is through implicit association or intentional practice, yoga has been known to help individuals maintain good mental health. However, many communities, such as South Asian communities, often project the stereotype that embodies neglecting topics such as mental health and considering them taboo. In this online survey-based study, the authors focused on examining whether yoga would alter individuals’ attitudes toward mental health. They hypothesized that 1) participants who regularly practiced yoga would be more familiar with the term mental health, 2) participants who practiced yoga would value their mental health more, and 3) participants who practiced yoga regularly would be more open about their mental health and be more likely to reach out for professional help if needed. They did not find a statistical significance for any of our hypotheses which suggests that yoga may not have an effect on perceptions of mental health in yoga-practicing Indian adults.

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A machine learning approach for abstraction and reasoning problems without large amounts of data

Isik et al. | Jun 25, 2022

A machine learning approach for abstraction and reasoning problems without large amounts of data

While remarkable in its ability to mirror human cognition, machine learning and its associated algorithms often require extensive data to prove effective in completing tasks. However, data is not always plentiful, with unpredictable events occurring throughout our daily lives that require flexibility by artificial intelligence utilized in technology such as personal assistants and self-driving vehicles. Driven by the need for AI to complete tasks without extensive training, the researchers in this article use fluid intelligence assessments to develop an algorithm capable of generalization and abstraction. By forgoing prioritization on skill-based training, this article demonstrates the potential of focusing on a more generalized cognitive ability for artificial intelligence, proving more flexible and thus human-like in solving unique tasks than skill-focused algorithms.

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Artificial Intelligence-Based Smart Solution to Reduce Respiratory Problems Caused by Air Pollution

Bhardwaj et al. | Dec 14, 2021

Artificial Intelligence-Based Smart Solution to Reduce Respiratory Problems Caused by Air Pollution

In this report, Bhardwaj and Sharma tested whether placing specific plants indoors can reduce levels of indoor air pollution that can lead to lung-related illnesses. Using machine learning, they show that plants improved overall indoor air quality and reduced levels of particulate matter. They suggest that plant-based interventions coupled with sensors may be a useful long-term solution to reducing and maintaining indoor air pollution.

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Can the Growth Mindset Encourage Girls to Pursue “Male” Careers?

Lateef et al. | Oct 03, 2021

Can the Growth Mindset Encourage Girls to Pursue “Male” Careers?

Despite major advances in gender equality, men still far outnumber women in science, technology, engineering and math (STEM) professions. The purpose of this project was to determine whether mindset could affect a student’s future career choices and whether this effect differed based on gender. When looking within the gender groups, 86% of females who had a growth mindset were likely to consider a “male” career, whereas only 16% of females with fixed mindset would likely to consider a “male” career. Especially for girls, cultivating a growth mindset may be a great strategy to address the problem of fewer girls picking STEM careers.

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