Detecting fake news and disinformation using artificial intelligence and machine learning to avoid supply chain disruptions.

Fake news and disinformation (FNaD) are increasingly being circulated through various online and social networking platforms, causing widespread disruptions and influencing decision-making perceptions. Despite the growing importance of detecting fake news in politics, relatively limited research efforts have been made to develop artificial intelligence (AI) and machine learning (ML) oriented FNaD detection models suited to minimize supply chain disruptions (SCDs). Using a combination of AI and ML, and case studies based on data collected from Indonesia, Malaysia, and Pakistan, we developed a FNaD detection model aimed at preventing SCDs.

Predicting eco-conscious consumer behavior using theory of planned behavior in Pakistan.

Sustainability of the environment has become pivotal in the modern world, and there have been enormous efforts by the world leaders and organizations to reduce the effects of hazardous production on the environment. This has led companies to implement pro-environment programs and work on sustainability to shift consumption from conventional products to green products. This study incorporates green trust, environmental concerns, and intrinsic religious orientation as a moderator into the theory of planned behavior.

Effect of 90 decibel noise of 4000 hertz on blood pressure in young adults.

Background: Almost every individual dislikes excessive and unnecessary noise. Noise exerts various adverse psychological and physiological effects, on human body including a rise in blood pressure.

Methods: 117 volunteer medical students, aged 18-23 years were exposed to 90 decibel noise of 4000 hertz for 10 minutes, produced by audiometer in a sound-proof room.