This study explored the great potential of endophytic fungi associated with red seaweed Gracilaria sp. and brown seaweed Sargassum sp. of the Bay of Bengal, Bangladesh, for the first time. Endophytic fungi were identified taxonomically by morphologic...
Crop and drought monitoring are vital for sustainable agriculture, as they ensure optimal crop growth, identify stress factors, and enhance productivity, all of which contribute to food security. However, climate projections are equally important as ...
The teacher-student relationship has far-reaching implications for educational outcomes at the tertiary level. Teachers contribute to students' success in various ways, including academic support, career counseling, personal mentoring, etc., that hel...
BACKGROUND: Sustainable Development Goal 3 (SDG 3), focusing on ensuring healthy lives and well-being for all, holds global significance and is particularly vital for Bangladesh. Neonatal Mortality Rate (NMR), Under-5 Mortality Rate (U5MR), Maternal ...
BACKGROUND: Under-5 mortality remains a critical social indicator of a country's development and economic sustainability, particularly in developing nations like Bangladesh. This study employs machine learning models, including Linear Regression, Rid...
BACKGROUND: Child mortality is a reliable and significant indicator of a nation's health. Although the child mortality rate in Bangladesh is declining over time, it still needs to drop even more in order to meet the Sustainable Development Goals (SDG...
BACKGROUND: Bangladesh is facing a formidable challenge in mitigating waterborne diseases risk exacerbated by climate change. However, a comprehensive understanding of the spatio-temporal dynamics of these diseases at the district level remains elusi...
The rapid urban expansion in Dhaka, the capital of Bangladesh, has escalated air pollution levels and led to a significant decrease in green spaces. This study employed machine learning (ML) and deep learning (DL) techniques to examine the relationsh...
Coal mining soils are highly susceptible to heavy metal pollution due to the discharge of mine tailings, overburden dumps, and acid mine drainage. Developing a reliable predictive model for heavy metal concentrations in this region has proven to be a...
This study explores the application of machine learning algorithms in predicting high-risk pregnancy among expectant mothers, aiming to construct an efficient predictive model to improve maternal health management. The study is based on the maternal ...