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302 articles for “analytical method”
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Bioanalytical Method Development and Validation for the Estimation of Levothyroxine in Human K₃EDTA Plasma by Using UPLC-MS/MS
Abstract: A rapid, sensitive, and highly selective UPLC-MS/MS method was developed and validated for the quantitative estimation of Levothyroxine in human plasma using Levothyroxine-D₃ as the internal standard (IS). Chromatographic separation was achieved on a Gemini NX-C18 column (50 × 3.0 mm, 3 µm) with a mobile phase consisting of acetonitrile and water (70:30, v/v) containing 0.015% formic acid at a flow rate of 0.5 mL/min. The total run time was …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 3, 2025 · pp. 32–46 Read article
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Green Analytical Chemistry in Pharmaceuticals: Pathways to Sustainability and Compliance
Abstract: This review paper explores the integration of green analytical chemistry (GAC) in the pharmaceutical industry as a pathway to EU compliance and environmental sustainability. The review highlights a range of studies that focus on the application of green solvents, green extraction methods, biocatalysts, and energy-efficient techniques. Key findings suggest that employ eco-friendly solvents, such as ethanol and water and methods, like ultrasound-assisted extraction (UAE) and supercritical fluid extraction (SFE), significantly …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 1, 2025 · pp. 7–12 Read article
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Characterization and Fabrication of Hybrid Matrix Composites of AZ91E Metal with Distinct Reinforcements of Fly Ash and ZrO2
Abstract: The current work choose the characteristics of (Magnesium composite) AZ91E-ZrO2-Fly ash Hybrid Metal Matrix using the regular analytic system. The chosen materials for this purpose are fly ash and ZrO2 in equivalent load extents, Stir casting uses a vortex technique to produce composite materials. A comprehensive experimental investigation was conducted to assess the performance characteristics of AZ91E-ZrO2-Fly ash during the cold upsetting process. The study involved utilizing AZ91E magnesium alloy …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 Read article
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Planktonic Organisms as Bio-indicators of Pollution in Aquatic Environments
Abstract: Planktonic organisms play a pivotal role in aquatic ecosystems, serving as vital bio indicators of pollution levels. This review offers a thorough exploration of their significance in assessing environmental health in aquatic environments. We delve into the diverse array of planktonic taxa, encompassing phytoplankton, zooplankton, and bacterioplankton, and examine their responses to various pollutants such as nutrient enrichment, chemical contaminants, and microplastics. These organisms exhibit remarkable sensitivity to environmental changes, …
Published in International Journal of Marine Life · Vol. 1, Issue 2, 2024 · pp. 21–26 Read article
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Ranking of Epoxy/Kota Stone Dust/Fly Ash Composite Using Integrated AHP-TOPSIS Approach
Abstract: The generation of industrial waste is a significant contributor to environmental pollution. The stone industry is no exception to this, and it is known to produce a significant amount of waste. The Kota Stone Industry in India is one such industry that generates waste. This research article focuses on composite material selection for mechanical and structural applications by fabricating epoxy composites reinforced with Kota stone dust and fly ash using …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 36–42 Read article
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Seismic-Resilient Structural Systems: Geotechnical Engineering
Abstract: Earthquakes represent one of the most destructive natural hazards, capable of causing severe structural damage, loss of life, and substantial economic disruption. Seismic waves propagating through the ground can induce excessive forces and deformations in buildings, often leading to partial or complete collapse. Statistical records indicate that thousands of earthquakes occur globally each year, including several major events that result in significant damage. Past earthquake disasters have repeatedly demonstrated that …
Published in Journal of Geotechnical Engineering · Vol. 13, Issue 1, 2026 · pp. 55–63 Read article
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A Monte Carlo Simulation Approach to Decision Analytics in Manufacturing and Industrial Automation Project Management
Abstract: Manufacturing and industrial automation projects face high uncertainty and risk arising from factors such as complex supply chains, equipment variability, and fluctuating production demands. If not properly managed, these uncertainties can lead to costly delays, unplanned downtime, and budget overruns that jeopardize project success. Given the shortcomings of deterministic planning in such volatile environments. If not properly managed, it can lead to costly delays and failures if not properly managed. …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 1–12 Read article
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Survey Paper on Multilingual Live Call Translation Using Deep Learning
Abstract: This research work surveys cutting-edge language translation technologies, including multi-lingual, real-time translation, voice recognition, speech-to-text conversion, and transcription in the hearing process. The study explores the complex mechanisms behind voice call language translation, focusing on sophisticated machine learning models integrated with cloud-based or local applications to facilitate seamless communication across language barriers. Furthermore, conducting research in live communication analyzes the complexity of text and voice techniques to deliver translated content …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 13–21 Read article
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Detection and Control of Adulterants in Milk
Abstract: Milk is one of the most essential and widely consumed staple foods, valued for its rich nutritional composition, including proteins, fats, vitamins, and minerals necessary for human growth and health. However, the increasing demand for milk, coupled with economic incentives, has led to the widespread issue of milk adulteration, posing serious concerns for food safety and public health. Adulteration involves the addition of harmful or inferior substances to milk, either …
Published in Research and Reviews : Journal of Dairy Science and Technology · Vol. 15, Issue 1, 2026 · pp. 1–6 Read article
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A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
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Selection of Maintenance Strategy Using Hybrid AHP-VIKOR Approach for a Smart Manufacturing Application in Industry 4.0
Abstract: In Industry 4.0, choosing the right maintenance strategy is important for improving machine performance, reducing downtime, and ensuring smooth operation in smart manufacturing systems. This study aims to find the most suitable maintenance strategy for a customized machine-making company by using a combination of AHP and VIKOR methods. In this study, four types of maintenance strategies are considered: breakdown maintenance, time-based maintenance, condition-based maintenance, and predictive maintenance. First, the AHP …
Published in Journal of Production Research & Management · Vol. 16, Issue 2, 2026 Read article
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The Contribution of Mathematics to Make Developed India
Abstract: This research paper explores the significant contributions of mathematics to the development of India, tracing its influence from ancient innovations to modern applications across diverse sectors. India has a long-standing mathematical tradition, with foundational achievements such as the invention of zero, the decimal system, and advancements in algebra, trigonometry, and geometry, which profoundly shaped global knowledge systems. These early contributions established India as a pioneering hub of mathematical thought and …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 3, 2025 · pp. 08–15 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Comparison of Models of Machine Learning and Hyperparameter optimization methods on various datasets
Abstract: The most likely phase in achieving powerful and robust machine learning models is probably the hyperparameters tuning step. The traditional exhaustive methods of search (Grid Search and others) ensure that the search space is covered, but are computationally very inexpensive; random search is less expensive and can still miss good regions; and lastly, the modern model-based and population-based methods (Bayesian Optimization, Tree-structured Parzen Estimator (TPE), Genetic Algorithms) are thought to …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
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Recent Advances in Quality Control and Quality Assurance: Enhancing Pharmaceutical Product Integrity and Compliance
Abstract: The pharmaceutical industry is undergoing a paradigm shift driven by stringent regulatory expectations and the demand for high-quality, safe, and efficacious drug products. Quality Control (QC) and Quality Assurance (QA) serve as the two foundational pillars that ensure pharmaceutical integrity from raw material acquisition through to product release. Traditional QC and QA practices, while effective, have been challenged by complex formulations, biologics, and personalized medicine, requiring innovative methodologies and technologies. …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 54–62 Read article
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Data Privacy in AI: Securing the Sensitive Information Through Homomorphic Encryption
Abstract: Artificial intelligence (AI) technology increasingly relies on sensitive user data, particularly finance and healthcare. While legacy encryption technologies safeguard data in transit and at rest, they are of no use when data must be decrypted to be processed. This is a bleak privacy threat, particularly in AI applications that call for constant processing of data. The objective of this study is to apply homomorphic encryption, a feature in which operations …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 2, 2025 · pp. 25–30 Read article
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Analytical Study on DNA-based Modern Cryptographic Techniques
Abstract: Today, as the amount of information being stored and shared continues to grow rapidly, ensuring the security of that information has become more important than ever.To ensure information security, a variety of techniques are employed, including traditional cryptographic methods such as substitution and transposition techniques, hashing functions, and encryption algorithms like DES, RSA, AES, IDEA, and ECC. DNA cryptography is also new emerging technique for providing security to data and …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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A Comprehensive Investigation of Bagging-Based Ensemble Methods for Improving Machine Learning Model Robustness
Abstract: Machine learning models such as Decision Trees, Logistic Regression, and K-Nearest Neighbors are widely used for classification tasks due to their simplicity and interpretability. However, these models often suffer from high variance, overfitting, and poor generalization when applied to real-world datasets, particularly those that are small, noisy, or imbalanced, as commonly encountered in healthcare, finance, and cybersecurity applications. To address these limitations, this research proposes a Bagging (Bootstrap Aggregating)-based ensemble …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 24–34 Read article