Basic Medicine
Francis-Dominic Makong Ekpan; Merit Oluchi Ori; Humphrey Sam Samuel; Odii Peter Egwuatu
Abstract
In the face of growing environmental concerns and the need for sustainable energy sources, the production of bioethanol from lignocellulosic waste materials has emerged as a promising solution. This study provides an overview of efforts to enhance the eco-friendly production of bioethanol from lignocellulosic ...
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In the face of growing environmental concerns and the need for sustainable energy sources, the production of bioethanol from lignocellulosic waste materials has emerged as a promising solution. This study provides an overview of efforts to enhance the eco-friendly production of bioethanol from lignocellulosic waste, addressing both the environmental and economic aspects of this renewable energy source. Lignocellulosic waste materials, such as agricultural residues and forest biomass, offer a rich source of raw materials for bioethanol production. Their utilization not only reduces waste accumulation, but also decreases the dependency on finite fossil fuels. However, the challenge lies in the efficient conversion of these materials into bioethanol while minimizing environmental impacts. To achieve this, researchers have been exploring various strategies, including advanced pretreatment techniques, enzymatic hydrolysis, and microbial fermentation. These methods aim to increase bioethanol yields, reduce production costs, and minimize waste generation, thus promoting a more sustainable and eco-friendly approach. In addition, the integration of waste-to-bioethanol processes with existing industries and the development of circular bio-economies hold promise for economic viability. As the world shifts towards a more sustainable energy future, these advancements in bioethanol production from lignocellulosic waste materials play a crucial role in reducing greenhouse gas emissions and mitigating environmental impacts.
Nanosciences
Odii Peter Egwuatu; Merit Oluchi Ori; Humphrey Sam Samuel; Francis-Dominic Makong Ekpan
Abstract
This review article explores the transformative impact of AI in the field of nanomedicine, specifically focusing on AI-enabled diagnostics and monitoring. Nanomedicine has emerged as a promising approach for improving medical imaging, drug delivery, diagnostics, and therapy, and AI has become a disruptive ...
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This review article explores the transformative impact of AI in the field of nanomedicine, specifically focusing on AI-enabled diagnostics and monitoring. Nanomedicine has emerged as a promising approach for improving medical imaging, drug delivery, diagnostics, and therapy, and AI has become a disruptive force that enhances the precision, efficiency, and personalization of healthcare solutions. We delve into the role of AI in designing and optimizing nanomaterials, drug delivery systems, and combinatorial nanomedicine administration. AI's potential to examine vast datasets, discover patterns and predict behaviour in biological systems is discussed. The paper also highlights the vital role of AI-driven nanosensors in the real-time monitoring of biomarkers within the human body. Interdisciplinary collaboration in healthcare is emphasized, as it is essential for addressing complex challenges and achieving global health goals. The article concludes by exploring how AI has revolutionized surgical planning, anatomical modelling, and virtual anatomy education in the context of nanomedicine. Overall, this review demonstrates the significant potential of AI-enabled diagnostics and monitoring in nanomedicine to revolutionize healthcare.
Basic Medicine
Merit Oluchi Ori; Francis-Dominic Makong Ekpan; Humphrey Sam Samuel; Odii Peter Egwuatu
Abstract
The integration of artificial intelligence (AI) and nanotechnology has revolutionized the field of nanomedicine. AI’s large-scale data processing and pattern recognition capabilities can enhance the design of nanotechnologies for diagnosis and therapy. This integration can address challenges in ...
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The integration of artificial intelligence (AI) and nanotechnology has revolutionized the field of nanomedicine. AI’s large-scale data processing and pattern recognition capabilities can enhance the design of nanotechnologies for diagnosis and therapy. This integration can address challenges in fabrication and targeted drug delivery for cancer therapy. AI’s rapid data mining and decision-making capabilities can lead to more innovative solutions. The convergence of biology, AI, and nanotechnology is fostering a scientific and technological revolution. Recent studies show that AI can improve the design of nanotechnologies for diagnostics and treatment by processing large datasets and recognizing complex patterns. AI is also used in nanomedicine design to optimize material properties based on interactions with target medications, biological fluids, immune systems, and cell membranes.
Chemistry
Merit Oluchi Ori; Edet Patience Ime; Francis-dominic Makong Ekpan; Humphrey Sam Samuel; Odii Peter Egwuatu; Ede Joseph Ajor
Abstract
Industrial filters are important components in the manufacturing and processing of polymer products. They are used to remove impurities, contaminants, and foreign particles from polymer materials, ensuring high-quality and consistent products. The polymer industry, which is at the centre of contemporary ...
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Industrial filters are important components in the manufacturing and processing of polymer products. They are used to remove impurities, contaminants, and foreign particles from polymer materials, ensuring high-quality and consistent products. The polymer industry, which is at the centre of contemporary manufacturing, is under increasing pressure to strike a balance between environmental sustainability and the demand for outstanding product quality. In this perspective, industrial filters stand out as unsung heroes who have a significant impact on the polymers manufacture. This in-depth analysis explores the most recent advancements in industrial filtering technology and their strategic uses in the production of polymers. It emphasizes how these filters successfully remove pollutants, impurities, and undesired particles from the polymer feedstock, producing products that stand out for having better mechanical, thermal, and optical qualities. Furthering the cause of sustainability and ecologically responsible production, the elimination of unwanted by-products, and the maintenance of constant polymer compositions greatly reduce waste formation. Analyses of case studies and practical instances provide verifiable proof of the revolutionary advantages offered by industrial filters. These benefits include improved energy efficiency, lower maintenance costs, and the establishment of an unwavering standard for product quality. The research also explores the use of green filtering systems, which not only boost output, but also comply with the growing demand for environmentally responsible manufacturing methods.