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5. Pharmacological effect of Heritiera fomes on Long Evans rats against Postprandial Hyperglycemia and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\left(\varvec{C}{\varvec{H}}_{2}\varvec{O}\right)}_{\varvec{n}}$$\end{document} adsorption in vitro

11. Application of a count regression model to identify the risk factors of under-five child morbidity in Bangladesh.

14. Individual- and community-level factors associated with the presence of adequate iodized salt in households in Bangladesh: a multilevel modelling approach

21. Performance Evaluation of Machine Learning-Based Algorithms to Predict the Early Childhood Development Among Under Five Children in Bangladesh

29. Individual and community-level factors associated with discrimination among women aged 15–49 years in Bangladesh: Evidence based on multiple indicator cluster survey.

30. Growth Performance and Economic Analysis of Swamp Eel (Monopterus cuchia): An Application of Cobb-Douglas Production Function.

31. Pharmacological effect of Heritiera fomes on Long Evans rats against Postprandial Hyperglycemia and adsorption in vitro.

33. Performance Evaluation of Machine Learning Algorithm for Classification of Unintended Pregnancy among Married Women in Bangladesh

36. Comparison of the performance of machine learning-based algorithms for predicting depression and anxiety among University Students in Bangladesh: A result of the first wave of the COVID-19 pandemic

41. Determinants of quality of life among COVID-19 patients in Southwestern region of Bangladesh

46. Determinants of regional prevalence and variations in handwashing practices among households in Bangladesh: An application of generalized mixed-effects model.

47. Comparison of the Performance of Machine Learning-based Algorithms for Predicting Depression and Anxiety among University Students in Bangladesh: A Result of the First Wave of the COVID-19 Pandemic.

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