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"Rahman, Abdur"
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A review of environmental friendly green composites: production methods, current progresses, and challenges
The growing concern about environmental damage and the inability to meet the demand for more versatile, environmentally friendly materials has sparked increasing interest in polymer composites derived from renewable and biodegradable plant-based materials, mainly from forests. These composites are mostly referred to as “green” and they can be widely employed in many industrial applications. Green composites are less harmful to the environment and could be potential substitutes for petroleum-based polymeric materials. It is helpful to limit usage of fossil oil assets by developing biopolymer matrices such as cellulose-reinforced biocomposites using renewable assets such as plant oils, carbohydrates, and proteins. This paper focuses on green composites processing utilizing a variety of naturally available resources, sustainable materials which are not detrimental to the environment, new scientific signs of progress in achieving green sustainable development, as well as nanotechnology and its environmental consequences. Additionally, the environmental impacts of different composite materials are examined in this paper, along with their production from eco-friendly materials. Moreover, the manufacturing aspects of green composites and some concerns related to their production are also discussed. The merits of green composite materials and valid reasons why they are a valuable substitute for the traditionally used composite materials are also covered.
Journal Article
Heterogeneity-preserving discriminative feature selection for disease-specific subtype discovery
Disease-specific subtype identification can deepen our understanding of disease progression and pave the way for personalized therapies, given the complexity of disease heterogeneity. Large-scale transcriptomic, proteomic, and imaging datasets create opportunities for discovering subtypes but also pose challenges due to their high dimensionality. To mitigate this, many feature selection methods focus on selecting features that distinguish known diseases or cell states, yet often miss features that preserve heterogeneity and reveal new subtypes. To overcome this gap, we develop Preserving Heterogeneity (PHet), a statistical methodology that employs iterative subsampling and differential analysis of interquartile range, in conjunction with Fisher’s method, to identify a small set of features that enhance subtype clustering quality. Here, we show that this method can maintain sample heterogeneity while distinguishing known disease/cell states, with a tendency to outperform previous differential expression and outlier-based methods, indicating its potential to advance our understanding of disease mechanisms and cell differentiation.
Complex diseases often involve subtle subtypes, making their detection vital for personalized medicine. Here, the authors show that the PHet (Preserving Heterogeneity) method reliably uncovers disease-specific subtypes using small sets of features
Journal Article
What makes a difference for further advancement of engineers: socioeconomic background or education programs?
Education is considered to be the most effective tool that people can use to lift themselves out of poor socioeconomic backgrounds and lead to professional success, which in turn improves society. Since an education system often supports individuals with a higher socioeconomic status (SES), it may not resolve the issue of socioeconomic background impacting on career outcomes. Given the nature of the research questions, an individualistic approach is used for selecting tools. Using qualitative and quantitative analysis methods, we argue that graduates studying an 8-year engineering program fail to succeed compared to counterparts who studied a 4-year engineering program. Findings suggest that engineering graduates’ socioeconomic backgrounds help them with their career advancement. A policy intervention may help to address the influence of SES on engineering education and professional employment.
Journal Article
A Comprehensive Account on Recent Progress in Pharmacological Activities of Benzimidazole Derivatives
Nowadays, nitrogenous heterocyclic molecules have attracted a great deal of interest among medicinal chemists. Among these potential heterocyclic drugs, benzimidazole scaffolds are considerably prevalent. Due to their isostructural pharmacophore of naturally occurring active biomolecules, benzimidazole derivatives have significant importance as chemotherapeutic agents in diverse clinical conditions. Researchers have synthesized plenty of benzimidazole derivatives in the last decades, amidst a large share of these compounds exerted excellent bioactivity against many ailments with outstanding bioavailability, safety, and stability profiles. In this comprehensive review, we have summarized the bioactivity of the benzimidazole derivatives reported in recent literature (2012–2021) with their available structure-activity relationship. Compounds bearing benzimidazole nucleus possess broad-spectrum pharmacological properties ranging from common antibacterial effects to the world’s most virulent diseases. Several promising therapeutic candidates are undergoing human trials, and some of these are going to be approved for clinical use. However, notable challenges, such as drug resistance, costly and tedious synthetic methods, little structural information of receptors, lack of advanced software, and so on, are still viable to be overcome for further research.
Journal Article
Risk factors of the severity of COVID‐19: A meta‐analysis
Objective We intend to identify some probable risk factors that are responsible for the severity of COVID‐19 using a meta‐analysis. Methods The literature exploration lasted up to 18 April 2020 and through PubMed, Google Scholar, EMBASE and Cochrane Library we have identified 10 pertinent publications. To paraphrase the outcomes of autonomous researches, we have performed a random‐effect meta‐analysis. Results A total of 2272 patients’ information was extracted from the selected literature. We have found gender (male) (Risk ratio [RR] = 1.29, 95% Confidence Interval [CI] 1.07 to 1.54), hypertension (RR = 1.79, 95% CI 1.57 to 2.04), diabetes (RR = 1.57, 95% CI 1.25 to 1.98), fatigue or myalgia (RR = 1.17, 95% CI 1.02 to 1.35), and smoking history (RR = 1.71, 95% CI 1.25 to 2.35) are potential risk factors for the severity of COVID‐19. We found fever (RR = 1.21, 95% CI 0.66 to 2.22), cough (1.13, 95% CI 0.98 to 1.30) and diarrhoea (RR = 1.14, 95% CI 0.93 to 1.40) as insignificant risk factors for COVID‐19 severity. Conclusions The findings of this research may be beneficial to identify patients with higher risks to provide additional medical attention from the very beginning of the treatment.
Journal Article