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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Journal of Information Systems and Informatics Makara Journal of Health Research Journal of Fibers and Polymer Composites
Jahan, Nusrat
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Computer Science & IT Engineering Materials Science & Nanotechnology

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Evaluation of Biochemical and Pathological Parameters at Different Doses of Cisplatin in Experimental Animal Model: Toxicological Study on an Antineoplastic Drug Sultana, Farhana; Islam, Muhammed Mohibul; Amin, Mohammad Nurul; Jahan, Nusrat; Kabir, Asma; Emran, Talha Bin; Sutradhar, Bibek Chandra; Banik, Sujan
Makara Journal of Health Research Vol. 26, No. 1
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Background: This study aimed to assess the effect of cisplatin-induced toxicities on biochemical and pathological parameters such as body, liver, and kidney weights, blood urea nitrogen (BUN), creatinine, alanine aminotransferase (ALT), and blood cells (RBCs and WBCs) in white Swiss albino mice. Methods: Cisplatin’s potential toxic effects on body, liver, and kidney weights were evaluated using standard laboratory methods. Blood biochemical levels such as BUN, creatinine, and ALT levels were determined by an auto-hemolyzer using commercial diagnostic kits. Blood cells (RBCs and WBCs) were counted under a microscope by a hemocytometer. Results: Cisplatin’s potential toxic effects on body, liver, and kidney weights were evaluated using standard laboratory methods. Blood biochemical levels such as BUN, creatinine, and ALT levels were determined by an auto-hemolyzer using commercial diagnostic kits. Blood cells (RBCs and WBCs) were counted under a microscope by a hemocytometer. Conclusions: This study suggested to increase caution when using cisplatin, particularly at high doses. Further investigation shall be performed to minimize its toxic effect and optimize its use.
Bestow Pre-Garments Waste Second Life by Converting into a Composite Hossain, Sajid; Ahtasum, Nafis; Hasan, MD Mahmudul; Jahan, Nusrat; Jim, Monjur E Mowla; Roy, Krishno; Jakaria, Md
Journal of Fibers and Polymer Composites Vol. 3 No. 2 (2024): Journal of Fibers and Polymer Composites
Publisher : Green Engineering Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55043/jfpc.v3i2.212

Abstract

The pre garments waste consisting of offcuts, trimmings, rejected materials are generated from the garments industry is growing concern nowadays. The recent trend of sustainability practice finds a way to convert this garment waste into composite materials by giving second life. The composites material from garment waste has proven that it is while effective alternative of conventional wood-based materials through the series of mechanical property analysis. The reinforcing garments waste with the help of virgin polypropylene matrix symbolizes the composite material. The amount of fiber reinforcement material and matrix used affects the mechanical and physical characteristics of the composite samples made from textile waste, including tensile strength, elongation, density, and water absorption. The waste-based composite panel board displayed a maximum strength of 31.6 N/mm2, with 40% of its volume taken up by fiber reinforcement components and 60% volume by the matrix. The present study demonstrate that the mechanical and physical characteristics of waste-based composite panel boards are comparable to those of current oriented strand boards and commercial plywood. This waste base composite board can be used for false ceilings, hardboard, wall covering, and fashion purposes also. The results of this study can significantly reduce environmental pollution and offer a practical method for recycling garments waste.
The Role of Non-State Actors in Climate Governance: Contributions, Challenges and Future Directions Islam, Md Mujahidul; Jahan, Nusrat
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1054

Abstract

Since anthropogenic causes accelerate rapid climate change with intensifying the adverse impacts of climate induce hazards, Non-State Actors (NSAs) have emerged as pivotal actors in climate governance. The aim of this research is to explore the diverse roles and contributions of NSAs in climate governance and analyze the challenges and institutional barriers they encounter with proposing some recommendations to strengthen their impact. It employs a qualitative approach where data were collected through KII method. Thematic analysis reveals some meaningful role of NSAs in climate governance including advocating for climate justice, raising awareness, promoting sustainable technologies, enhancing community adaptation and resilience, and collaborating across sectors. Digital awareness campaign of Greenpeace during the Copenhagen and Paris Conference and BRAC's climate-resilient housing and rainwater harvesting initiatives in Bangladesh can be placed as notable examples of NSAs’ roles. Despite their significant contributions, several persistent challenges such as poor coordination among NSAs and with state actors, legitimacy deficits, governance gaps, lack of institutional support and insufficient financing impedes them to realize their full potential. To overcome these challenges, this study recommends the need for legal inclusion of NSAs’ roles, inclusive participation, incorporating intersectionality, stronger accountability mechanisms and sustainable financial frameworks. Furthermore, this study offers actionable recommendations for policymakers and practitioners seeking to enhance the effectiveness of non-state engagement in climate action.
BonoNet: a deep convolutional neural network for recognizing bangla compound characters Ahmed, Kazi Rifat; Jahan, Nusrat; Masud, Adiba; Tasnim, Nusrat; Sharmin, Sazia; Mim, Nusrat Jahan; Mahmud, Imran
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i5.pp4171-4180

Abstract

The bangla alphabet includes vowels, consonants, and compound symbols. The compound nature of bangla is a product of combining two or more root bangla characters into one graph. They are difficult to differentiate because they have a sophisticated geometric shape and an immense variety of scripts used by different places and individuals. This is one of the greatest challenges in creating effective optical character recognition (OCR) systems for bangla. In this paper, a deep convolutional neural network (DCNN)-based system is presented to identify bangla compound characters with high precision. The model was trained using the AIBangla dataset. It has about 171 classes of bangla compound characters. A DCNN system, BonoNet, was designed to classify compound characters. BonoNet outperformed all other state-of-the-art architecture on the test set and improved over current state-of-the-art architecture methods. BonoNet will greatly improve the automation and analysis of the bangla language by accurately identifying these compound complex characters.
Co-Authors Ahmed, Kazi Rifat Ahtasum, Nafis Amin, Mohammad Nurul Banik, Sujan Emran, Talha Bin Hasan, Md Mahmudul Hossain, Sajid Islam, Md Mujahidul Islam, Muhammed Mohibul Jakaria, Md Jim, Monjur E Mowla Kabir, Asma Mahmud, Imran Masud, Adiba Mim, Nusrat Jahan Roy, Krishno Sharmin, Sazia Sultana, Farhana Sutradhar, Bibek Chandra Tasnim, Nusrat