BRAC University Institutional Repository
Preserving Knowledge, Advancing Research, Sharing Scholarship
A digital platform for collecting, preserving, and sharing BRAC University’s scholarly, academic, and institutional outputs.
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Faculty members and students are invited to submit their research publications, theses, dissertations, and scholarly works to increase visibility, access, and long-term preservation.
Recent Submissions
GC-MS-employed phytochemical characterization and anticancer, antidiabetic, and antioxidant activity screening of Lagerstroemia thorelli
(John Wiley and Sons Inc., 2024-12-01) Akter, Raushanara; Maknun Fariha, Luluel; Halder S.; Sharmin, Shahana; Sabet Taki, Ehtesham; Kabir Lihu, Imanul; Hamja Tipu, Amir; Rubaiyat Muntasir Meem M.M.; Alam Ripa, Farhana; Sharmin, Sabrina; School of Pharmacy
Lagerstroemia thorelli (L. thorelli) is a member of the Lythraceae family and has not been previously researched. Thus, this study aimed to investigate its unexplored potential and identify novel therapeutic prospects. This research evaluated antioxidant, antidiabetic, and cytotoxic potentials along with compound characterization of the ethanolic leaf extract of L. thorelli. The antioxidant potential was assessed using 1, 1-diphenyl-2-picrylhydrazyl (DPPH) free radical and hydrogen peroxide (H2O2) scavenging assays, total antioxidant capacity (TAC), total phenolic content (TPC), total flavonoid content (TFC) determination, antidiabetic property was assessed using α-amylase inhibition, and the cytotoxic effect was examined on HeLa and Vero cells using MTT colorimetric assay. Chemical characterization was performed using gas chromatography-mass spectrometry (GC-MS). The findings demonstrated strong antioxidant, strong antidiabetic, and moderate cytotoxic activities. Comprehensive phytochemical analysis revealed its abundance in flavonoids, phenols/phenolics, tannins, glycosides, steroids, resin, etc. GC-MS analysis of the L. thorelli extract identified 80 important compounds including cis-11-eicosenamide, beta-D-glucopyranoside, methyl-, alpha-D-glucopyranoside, methyl-, phthalic acid, gamma-sitosterol, phytol, silicic acid, squalene, butanoic acid, cyclobarbital, etc. which are well-documented for their antioxidant, antidiabetic, and anticancer effects. Thus, it can be inferred that L. thorelli could hold new promises in treating diseases like diabetes and free radical-induced conditions, including neurodegenerative diseases.
The role of the private sector in the COVID-19 pandemic: Experiences from four health systems
(Frontiers Media S.A., 2022-05-27) Wallace L.J.; Agyepong I.; Baral S.; Barua D.; Das M.; Huque R.; Joshi D.; Mbachu C.; Naznin, Baby; Nonvignon J.; Ofosu A.; Onwujekwe O.; Sharma S.; Quayyum, Zahidul; Ensor T.; Elsey H.; BRAC James P Grant School of Public Health
As societies urbanize, their populations have become increasingly dependent on the private sector for essential services. The way the private sector responds to health emergencies such as the COVID-19 pandemic can determine the health and economic wellbeing of urban populations, an effect amplified for poorer communities. Here we present a qualitative document analysis of media reports and policy documents in four low resource settings-Bangladesh, Ghana, Nepal, Nigeria-between January and September 2020. The review focuses on two questions: (i) Who are the private sector actors who have engaged in the COVID-19 first wave response and what was their role?; and (ii) How have national and sub-national governments engaged in, and with, the private sector response and what have been the effects of these engagements? Three main roles of the private sector were identified in the review. (1) Providing resources to support the public health response. (2) Mitigating the financial impact of the pandemic on individuals and businesses. (3) Adjustment of services delivered by the private sector, within and beyond the health sector, to respond to pandemic-related business challenges and opportunities. The findings suggest that a combination of public-private partnerships, contracting, and regulation have been used by governments to influence private sector involvement. Government strategies to engage the private sector developed quickly, reflecting the importance of private services to populations. However, implementation of regulatory responses, especially in the health sector, has often been weak reflecting the difficulty governments have in ensuring affordable, quality private services. Lessons for future pandemics and other health emergencies include the need to ensure that essential non-pandemic health services in the government and non-government sector can continue despite elevated risks, surge capacity to minimize shortages of vital public health supplies is available, and plans are in place to ensure private workplaces remain safe and livelihoods protected.
Multi-task deep learning framework for leukemia cell classification and segmentation: A joint learning approach
(Institute of Electrical and Electronics Engineers Inc., 2025-01-01) Suma I.J.; Islam, M.D. Ashikul; Tihami, Ahmad Nafees; Akter M.; Department of Computer Science and Engineering
The classification of leukemia and segmentation of cells are tasks that have medical image analysis with the potential to enable early diagnosis and treatment. This paper propose a novel multi-task deep learning framework for leukemia cell classification and segmentation via a shared convolutional neural network backbone. We design a singular architecture that overcomes the inefficiencies of traditional single-task methods by jointly optimizing both tasks. The model proposed provides incredibly good performance with a macro-averaged F1-score of 95.09% for classification across four leukemia classes (Benign, Early, Pre, Pro). It also provides segmentation performance with IoU of 55.12% and Dice score of 67.70% on test data. The model achieves 1.87 GFLOPs indicating its computational effectiveness and high accuracy for both tasks. In tests on a comprehensive leukemia dataset, our multitask method not only saves on computing time but also enhances generalization through shared features making it suitable for real-time clinical use.
Enhancing medical image segmentation with parameter-efficient involutional neural networks and diverse datasets
(Institute of Electrical and Electronics Engineers Inc., 2025-01-01) Ahmed, Saif; Teertho, Raahim Rubaiy; Reza, Ahnaf Ahmad Safwat; Karim, Dewan Ziaul; Department of Computer Science and Engineering
Medical image segmentation is crucial for precise analysis and efficient treatment schemes. The utilization of Involutional Neural Networks for the enhancement of executing segmentation by lessening parameter complexity and enhancing feature extraction adaptability is initiated by this research. Traditional convolutional techniques are surpassed by Involutional Neural Networks as it offers dynamic adjustments which makes involution more suitable for tasks where computational efficiency is critical. The potential of Involutional Neural Networks and diversified datasets in improving medical image processing and introducing more definitive and efficient medical aid systems is highlighted in this research. Grad-CAM visualization has been integrated as a part of this model which generated heatmaps to focus on the critical regions, clarifying its decision-making process. In this research four datasets were used, which were the BUSI dataset for breast cancer segmentation, the DRIVE dataset for retinal vessel segmentation, the Lung Image Segmentation dataset for segmenting the human lungs, and the HAM-10000 dataset for skin lesion segmentation. Out of these four datasets, the model performed the best with the DRIVE dataset scoring an IoU of 97.07% and an accuracy of 96.76%. The HAM-10000 dataset scored an IoU of 77.71% with an accuracy of 97.85%, the BUSI dataset scored an IoU of 70.23% with an accuracy of 93.5% and finally, the Lung Image Segmentation dataset scored an IoU of 78.68% with an accuracy of 98.01%.
Female community health workers and health system navigation in a conflict zone: The case of Afghanistan
(Frontiers Media S.A., 2021-08-11) Parray, Ateeb Ahmad; Dash S.; Ullah M.I.K.; Inam, Zuhrat Mahfuza; Kaufman S.; BRAC James P Grant School of Public Health
Afghanistan ranked 171st among 188 countries in the Gender Inequality Index of 2011 and has only 16% of its women participating in the labor force. The country has been mired in violence for decades which has resulted in the destruction of the social infrastructure including the health sector. Recently, Afghanistan has deployed community health workers (CHW) who make up majority of the health workforce in the remote areas of this country. This paper aims to bring the plight of the CHWs to the forefront of discussion and shed light on the challenges they face as they attempt to bring basic healthcare to people living in a conflict zone. The paper discusses the motivations of Afghani women to become CHWs, their status in the community and within the health system, the threatening situations under which they operate, and the challenges they face as working women in a deeply patriarchal society within a conflict zone. The paper argues that female CHWs should be provided proper accreditation for their work, should be allowed and encouraged to progress in their careers, and should be instilled at the heart of healthcare program planning because they have the field experience to make the most effective and community oriented programmatic decisions.