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Browsing by Author "Islam, Rafikul"

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    Antidiabetic and antidiarrheal effects of the methanolic extract of Phyllanthus reticulatus leaves in mice
    (© 2014 Elsevier (Singapore) Pte Ltd, 2014-06) Ripa, Farhana Alam; Khatun, Mst. Hajera; Nesa, Mst. Luthfun; Islam, Rafikul; Al mamum; Kadir, Shahin
    Objective To assess the anti-diabetic and antidiarrheal activity of methanolic extract of Phyllanthus reticulates (P. reticulates) leaves in an animal model. Methods Phytochemical screening of methanolic extract of P. reticulatus leaves has been performed. Antidiabetic activity have been done by OGTT, normoglycemic hyperglycemia and alloxan induced diabetic mice. Plant extracts (150 mg/kg and 300 mg/kg, b.w.) were administered orally in fasting glucose loaded mice with regard to normal control and in alloxan induced (110 mg/kg body weight i.p.) diabetic mice in comparison with reference drug Metformin hydrochloride (100 mg/kg) during 7 day test period. Antidiarrheal test was conducted by castor oil and magnesium sulfate. Results Findings confirmed that the continuous post-treatment for 7 days with both extracts showed significant (P < 0.05) hypoglycemic activity in OGTT, normoglycemic and alloxan induced mouse models. Castor oil and Magnesium sulfate induced diarrheal test of the extract (200 and 400 mg/kg) has given significant effect in compairing to control diarrheal group. Conclusion Methanolic extract of P. reticulatus leaves have shown significant antidiabetic and antidiarrheal properties.
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    Title Identifying the Factors for Reducing Employee Turnover Rate in Aviation Business: Bangladesh Context
    (Australian Academy of Business and Economics, 2017-01) Nahar, Rezbin; Islam, Rafikul; Ullah, Kazi Tareq
    Managing employee turnover is a significant challenge for organizations, particularly in Bangladesh's aviation sector, which faces a persistent shortage of skilled personnel. This study aims to identify factors that can reduce employee turnover in the aviation industry. A survey was conducted among aviation company employees using random sampling. Data were analyzed through descriptive statistics and logistic regression models to determine causal relationships. The findings offer recommendations to help reduce turnover and retain qualified employees, providing valuable insights for human resource professionals and senior management in the sector.

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