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1930 articles for “identifying” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Dynamic Mechanical Analysis of Carbon Fiber Reinforced Polymer Composites
Abstract: This study investigates the thermal decomposition and mechanical properties of Fiber-Reinforced Polymer Composites (FRPCs) using Dynamic Mechanical Analysis (DMA). The research focuses on improving the recycling and recovery process of Carbon Fiber-Reinforced Polymers (CFRPs), addressing environmental concerns regarding their disposal. By analyzing the effects of different heating rates (5°C and 10°C per minute) and atmospheric conditions (nitrogen, oxygen, and a combination of both), the study identifies optimal parameters for maximizing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 386–393 Read article
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Carbon-Al Synergy: Investigation of Fiber Stacking and Orientation on the Mechanical Properties of Al-CFRP Metal Matrix Composites
Abstract: The current study examines the mechanical behaviour of Aluminum-Carbon Fiber Reinforced Polymer (Al-CFRP) composites fabricated using compression moulding technique, a novel approach combining lightweight aluminium’s ductility with CFRP’s high strength-to-weight ratio. The polymer composites were fabricated by stacking aluminum alloy sheet of 0.5mm thickness and pre-impregnated by 12 layers of carbon fiber cloth of 200 gsm, with epoxy resin between layers, followed by consolidation under controlled temperature and pressure in …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 340–354 Read article
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Exploring Oroxylum indicum Phytochemicals as VEGFR-2 Inhibitors: A Molecular Docking Approach for Cancer Management
Abstract: Cancer is still a major health problem around the world and is one of the top causes of death. A protein called VEGFR-2 (vascular endothelial growth factor receptor 2) is important because it helps blood vessels grow by supporting the survival, movement, and growth of certain cells. This process is essential for tumors to grow and spread to other parts of the body. This study focused on evaluating the binding …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 2, 2025 · pp. 48–62 Read article
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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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The Future of Mathematics Education in the Era of Artificial Intelligence
Abstract: The rapid integration of Artificial Intelligence (AI) into education is fundamentally reshaping the landscape of mathematics teaching and learning. This study examines how AI-powered tools are converting conventional math training into inclusive, individualized, and data-driven learning environments. Through an in-depth examination of global case studies—including Squirrel AI, Carnegie Learning’s MATHia, Khan Academy, Microsoft Math Solver, DIKSHA, Photomath, ALEKS, and BYJU’S—the study highlights AI’s ability to tailor content, deliver real-time feedback, …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 2, 2025 · pp. 37–44 Read article
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Hybrid Material Systems for Flexible Electronics Electro-Mechanical Performance and Future Prospects
Abstract: Flexible electronics are transforming the landscape of modern electronic systems, enabling devices that are lightweight, stretchable, and adaptable to complex surfaces. These technologies are particularly impactful in applications such as wearable health monitors, soft robotics, energy harvesting systems, and implantable biomedical devices. At the heart of this evolution are hybrid material systems—engineered composites that combine organic polymers and inorganic nanomaterials to achieve synergistic electro-mechanical properties. These materials address the limitations …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 7–12 Read article
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Innovations in Targeted Drug Discovery for Personalized Medicine
Abstract: Personalized medicine is revolutionizing modern healthcare by custoizing treatment plans to match an individual’s genetic makeup, protein expression, and metabomlic characteristics. Also referred to as precision medicine, this approach seeks to improve therapeutic outcomes, reduce adverse effects, and make efficient use of healthcare resources. The incorporation of various omics technologies—including genomics, proteomics, transcriptomics, metabolomics, and epigenomics—has greatly advanced our ability to understand disease biology and molecular variations specific to each …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 3, 2025 · pp. 19–41 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Optimizing Marketing Campaigns Using Random Forest and A/B Testing
Abstract: Marketing initiatives play a vital role in driving business growth by reaching targeted consumer segments through tailored strategies across multiple channels. The success of these initiatives is influenced by various factors, including the type and duration of the campaign, the characteristics of the target audience, the communication channels employed, and the overall efficiency of each strategy. These factors collectively impact key performance metrics such as conversion rates, customer acquisition costs, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article
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Analysis of a Battery Pack Module for a Formula Student Car
Abstract: This research aims to evaluate the development of a high-voltage accumulator system that meets established standards of safety and operation. It examines key components, protocols, and techniques used in its creation while assessing performance in electronic cooling and structural integrity. Polymers, serving as electrical insulators and flame retarders, have found an interesting application in EV battery packs. This study focuses on polycarbonate materials' ability to withstand thermal and structural loads …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 320–339 Read article
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Effect of 3D Printing Process Parameters on the Tensile Strength of Polylactic Acid (PLA)
Abstract: This study employs the Taguchi approach to systematically analyze and optimize critical Fused Deposition Modeling (FDM) parameters, focusing on their effect on the tensile strength of 3D-printed Polylactic Acid (PLA) components. The study explores three levels of layer thickness (0.15 mm, 0.25 mm, and 0.3 mm), infill densities (25%, 50%, and 75%), and nozzle temperatures (200°C, 205°C, and 210°C) across three infill patterns: Triangular, Gyroid, and Zig-zag. A total of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 128–140 Read article
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A Comprehensive Review of Metabolite
Abstract: Metabolites, tiny chemicals, are essential to physiology, signalling, and biological function. This extensive review classifies metabolites into primary and secondary categories by biological relevance. Alkaloids, flavonoids, and terpenoids contribute to ecological interactions and defence systems, while amino acids, nucleotides, and carbohydrates directly affect development and cellular function. The article examines metabolic pathways, mass spectrometry, NMR, and metabolomics, a growing field. Metabolites play a crucial role in various scientific and practical …
Published in Emerging Trends in Metabolites · Vol. 2, Issue 2, 2025 Read article
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Trichoderma: beneficial fungus for sustainable agriculture
Abstract: As environmentally beneficial substitutes for chemical pesticides, Trichoderma species are being utilized in agriculture more and more. Disease suppression, increased plant growth, and increased tolerance to environmental stress are just a few advantages they provide. These fungi are used in a wide range of cropping systems and formulations around the world. Their use is growing worldwide, particularly in Asia and Europe. In contemporary crop management, items derived from Trichoderma are …
Published in International Journal of Fungi · Vol. 2, Issue 2, 2025 · pp. 25–29 Read article
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Epipelic Algae Assemblage and Nutrient Status as Indicators of Pollution in Alice Creek, Rivers State, Nigeria
Abstract: Background and Objective: Alice creek is a tributary of the Sombreiro River, Akuku-Toru Local Government Area, Rivers State, Nigeria, receiving various anthropogenic wastes. The study investigated the species composition, diversity, abundance, and distribution of epipelic algae, and the nutrient status of Alice creek, a tributary of Sombreiro river, Rivers State, Nigeria. Materials and Methods: Epipelic and nutrients samples were collected monthly between February and May 2020 from three (3) stations …
Published in International Journal of Marine Life · Vol. 2, Issue 2, 2025 · pp. 12–20 Read article
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Pharmacogenomics: Unlocking the Genetic Basis of Drug Response for Precision Medicine
Abstract: Pharmacogenomics, a fusion of pharmacology and genomics, explores how genetic variations influence individual responses to medications. This field is revolutionizing modern medicine by moving away from a one-size-fits-all approach toward personalized treatment strategies. By identifying specific genetic markers, pharmacogenomics aims to enhance drug efficacy, minimize adverse drug reactions, and improve overall patient outcomes. Key methodologies in this discipline include candidate gene analysis, genome-wide association studies, and haplotype analysis, all of …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 52–59 Read article
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Codal Validation and Optimization of Gantry Girders Under Variable Wheelbase and Impact Loads: A Review of Analytical, Numerical, and Codal Approaches
Abstract: Gantry girders serve as critical structural elements in industrial facilities such as steel plants, workshops, and heavy manufacturing units, where electric overhead traveling (EOT) cranes operate. The design of these girders is governed by stringent codal provisions to ensure safety under bending, shear, and deflection. However, discrepancies between codal predictions, analytical formulations, and finite element analysis (FEA) results, particularly under variable wheelbase and dynamic impact loads, have been widely reported. …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 3, 2025 · pp. 23–29 Read article
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Review of Diagrid and Conventional Frame Systems for Modern Building Design
Abstract: The demand for high-rise buildings in modern cities has accelerated the development of structural systems that balance safety, efficiency, and architectural innovation. Conventional moment-resisting frames, though widely adopted, often become inefficient in tall structures due to higher material consumption and greater lateral displacements under seismic and wind loading. Diagrid systems, defined by their diagonally inclined members forming triangulated grids, provide an alternative approach with enhanced lateral stiffness, reduced drift, and …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 47–53 Read article
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Advancing Gene Therapy: Next-Generation Viral Vector Engineering for Precision, Safety, and Scalability
Abstract: Gene therapy has emerged as a paradigm-shifting modality for the treatment of genetic disorders, malignancies, and rare diseases through the delivery of therapeutic nucleic acids aimed at correcting or modulating dysfunctional gene expression. Among the various delivery systems, viral vectors including adeno-associated viruses (AAVs), lentiviruses, adenoviruses, retroviruses, and herpes simplex viruses have proven indispensable owing to their high transduction efficiencies and adaptability. This review offers a comprehensive assessment of viral …
Published in International Journal of Virus Studies · Vol. 2, Issue 2, 2025 · pp. 37–55 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article