Volume 14 | Issue 5 | May 2026

 Abstract

This study explores the association between emotional dysregulation and psychological distress among young adults raised in conflict-ridden families, emphasizing the influence of adverse family dynamics on emotional and mental health outcomes. Emotional dysregulation, which involves difficulties in recognizing, managing, and responding appropriately to emotions, is often linked to higher levels of distress, particularly among individuals exposed to ongoing family conflict, instability, and ineffective communication. In this study, data were gathered from young adults using standardized tools to measure emotional dysregulation and psychological distress, including indicators such as anxiety, depression, and stress. The results demonstrated a significant positive relationship between the two variables, suggesting that greater difficulties in emotion regulation are associated with increased psychological distress. Furthermore, the findings underscore the amplifying effect of conflict-ridden family environments on these challenges. Overall, the study highlights the need to focus on improving emotion regulation skills in interventions and adds to the understanding of how family conflict can have lasting effects on the mental health of young adults.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Emotional dysregulation, Psychological distress, Young adults, Conflict-ridden families, Family conflict, Anxiety, Depression, Stress, Emotional regulation, Mental health, Adverse family environment, Coping mechanism

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Agriculture is a part of Indias economy. We need to guess how much crops will grow so we can make sure we have food and plan the economy. In this paper we are talking about a system that uses computers to guess how much crops will grow. This system also uses pictures to show how well crops will do in Indias three growing seasons: Kharif, Rabi and Zaid. Our system uses a method called Linear Regression. It looks at things like how rain falls how hot it is how much pesticide is used and how much fertilizer is used to guess how much crops will grow. We measure how much crops grow in tons per hectare. We are using how much crops grow. Linear Regression to make guesses. We made a website using a tool called Streamlit. It lets people get guesses away. It also shows pictures of the guess results using a tool called Plotly. This is really helpful for people who want to see the results of how much crops grow. Our system is good at guessing how much crops will grow. It also helps farmers and people who plan agriculture by giving them tools to make decisions through dashboards. This means farmers and planners can use our system to make decisions about how much crops will grow. We tested our system with a lot of data. 3,000 Points. The results were good. We were able to guess how 30 crops would grow across three cycles. Our system guessed how much crops would grow. The results were good. Our system is helpful for precision agriculture. This lets farmers and people who plan agriculture make decisions based on facts. This helps them choose the crops and use resources in the way. Precision agriculture and how much crops grow are important, for Indias economy. Index Terms--Crop yield prediction, machine learning, linear regression, precision agriculture, Streamlit, Indian agriculture, seasonal crops, data visualization, agricultural informatics

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Crop yield prediction, machine learning, linear regression, precision agriculture, Streamlit, Indian agriculture, seasonal crops, data visualization, agricultural informatics

  License

Creative Commons Attribution 4.0 and The Open Definition