AI-powered decision making for road safety optimization under probabilistic linguistic Sugeno-Weber aggregation information.

Traffic accidents, a global concern, pose threats to lives and carry substantial economic and societal burdens. This paper explores the innovative integration of artificial intelligence (AI) into the ambiance of Multi Criteria Decision Making (MCDM) to address the challenge. We investigate AI's potential to enhance road safety globally, utilizing data analysis, predictive modeling, and intelligent traffic management systems.

Severity and relation of primary dysmenorrhea and body mass index in undergraduate students of Karachi: A cross sectional survey.

Objective: To determine the frequency of primary dysmenorrhea and its association with body mass index in female students.

Methods: The cross-sectional study was conducted from January to March, 2018, in two districts of Karachi, and comprised female undergraduate students aged 15-25 years who had reached menarche at an appropriate age. A semi-structured questionnaire was used to assess dysmenorrhea while Seca scale was used for nutritional status.