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19 articles for “Analytical Method Development”
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Optimizing Antibiotic Analysis: A Comprehensive Guide to HPLC Process of Assessment and Quantification
Abstract: The history and uses of chromatography are thoroughly covered in this work, with an emphasis on the use of High-Pressure Liquid Chromatography (HPLC) in pharmaceutical analysis. Since its discovery by Russian botanist Mikhail Tswett in the 19th century, chromatography has undergone tremendous developments that have given rise to a variety of chromatography types and applications. The story follows the evolution historically, emphasizing Tswett's groundbreaking breakthrough in plant color classification and …
Published in International Journal of Antibiotics · Vol. 1, Issue 2, 2024 · pp. 27–44 Read article
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An Analytical Review of Machine Learning Methodologies
Abstract: Machine Learning (ML) is a dynamic and rapidly developing area of computer science that enables the system to learn from data and improve its performance without clear programs. Rooted in statistical theory and computer algorithms, ML has become a major technology that progresses in artificial intelligence. It strengthens the detection of the recommendations and speech for extensive applications from autonomous vehicles and medical diagnoses. This paper has reviewed the basics …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 13–21 Read article
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Striking A Balance: Ethical Guidelines for A.I. Integration in Mental Health Services
Abstract: Introduction: Artificial Intelligence (AI) integration in mental health services presents opportunities and challenges. This study examines ethical considerations and proposes guidelines for responsible AI implementation in mental healthcare. The rapid advancement of AI technologies has sparked both excitement and concern within the mental health community, necessitating a thorough examination of their potential benefits and risks. By addressing these ethical considerations, this research aims to contribute to the development of a …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 1, 2025 · pp. 8–15 Read article
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Evaluating the Performance of Test Cricket Players Using Principal Component Analysis and the Weighted Average Method
Abstract: This study evaluates cricket player performance using Principal Component Analysis (PCA) and a weighted average approach. In order to achieve this, we analyzed detailed batting and bowling datasets from the International Cricket Council (ICC) to calculate player performance based on various performance indicators. The datasets included comprehensive statistics from multiple matches and tournaments, allowing for an in-depth evaluation of players’ skills and contributions. PCA ranked players according to their participation …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 20–30 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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Contextualising health-disaster risk reduction pillars for under-resourced rural secondary schools in Limpopo Province, South Africa
Abstract: School communities in under-resourced rural settings face a disproportionate burden of health-related disasters, including outbreaks, water and sanitation failures, food insecurity and compound events that disrupt learning and wellbeing. Yet school based disaster risk reduction (DRR) evidence in Southern Africa is uneven with limited empirically guidance tailored to the organisational and infrastructural realities of disadvantaged schools. Drawing on the Comprehensive School Safety Framework and the World Health Organization's Health Emergency …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 124–135 Read article
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Matriarchal Influence and Spiritual Identity: Exploring Women's Spirituality in Young Sheldon
Abstract: The study analyzes the TV series Young Sheldon (2017–2024) through maternal and spiritual feminism. It is a prequel to The Big Bang Theory, set in the 1980s. It is based on a ten-year-old Sheldon’s struggles to adjust to his environment. It aims to examine the study critically, emphasizing the role of his mother and her maternal and spiritual practices through episodes of seasons one to five. The study works on …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 · pp. 33–43 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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Study of Electrically Conductive Polymer for Antistatic and Sensor Application
Abstract: Electrically conductive polymers (ECPs) are a unique category of smart materials that integrate the mechanical flexibility and ease of processing characteristic of conventional polymers with the electrical conductivity typically associated with metals or semiconductors. In recent years, they have attracted considerable interest due to their promising potential in advanced technological applications, especially in antistatic coatings and electronic sensing devices. The unique ability of these polymers to conduct electricity arises from …
Published in International Journal of Minerals · Vol. 3, Issue 1, 2026 · pp. 46–51 Read article
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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Horizon Scanning and Early Assessment of Health Technologies for the Treatment of Orphan Diseases
Abstract: The theoretical foundations and regulatory framework of the processes of the formation of an effective health technology assessment (HTA) system at the early stages of the life cycle of medicines are analyzed in the article. Particular attention is paid to horizon scanning (HS) and early assessment of expensive innovative drugs utilized for treating rare diseases. In order to inform policymakers, purchasers, and providers (to prioritize MT research, financial, and operational …
Published in International Journal of Brain Sciences · Vol. 1, Issue 1, 2024 · pp. 32–39 Read article
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Studies of Mathematics: A Review of Research Trends, Themes and Implications
Abstract: This review examines contemporary research trends, thematic developments, and emerging implications within the field of mathematics education and mathematical studies. Drawing on a synthesis of recent scholarly literature, it explores how mathematics as both a discipline and a pedagogical practice continues to evolve in response to technological advancements, interdisciplinary applications, and changing educational paradigms. Major research trends reveal a growing emphasis on problem-based learning, mathematical modeling, and the integration of …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 19–24 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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Lamivudine And Dolutegravir Simultaneous Dosage Forms Determined and Validated Using The RP-UPLC Method
Abstract: RP-UPLC has been used to produce a straightforward, precise, and accurate approach for the simultaneous estimation of dolutegravir and lamivudine in a pharmaceutical dose form. A HSS C18 column of 2.8 x 50 mm and featuring particles with a size of 1.6 μm was used to process the chromatogram. A mixture of 70:30 Buffer Na2HPO4 and methanol made up the mobile phase, which was pushed across the column at a …
Published in Emerging Trends in Personalized Medicines · Vol. 1, Issue 1, 2024 · pp. 5–13 Read article
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Topology and Geometry in Data Science: Persistent Homology and Beyond
Abstract: In recent years, the interplay between topology, geometry, and data science has gained substantial momentum, offering powerful frameworks to analyze and interpret complex datasets. Traditional statistical and machine learning methods often rely on linear or metric- based assumptions, which may fail to capture the intrinsic structure of high-dimensional or nonlinear data. In contrast, topological and geometric methods provide shape-oriented, scale- invariant tools that focus on the continuity, connectivity, and global …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 21–27 Read article
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Evaluating an ai-supported experiential learning intervention: a quasi-experimental study of the joyful saturday model for student engagement and holistic development
Abstract: Student disengagement, declining academic motivation, and passive classroom participation remain major challenges in modern higher education systems. Traditional lecture-based teaching methods often fail to accommodate diverse learning styles and do not sufficiently promote active participation or collaborative learning. To address these challenges, the present study evaluates the effectiveness of Joyful Saturday, a structured experiential learning initiative designed to improve student engagement, motivation, and holistic development through interactive academic activities supported …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 79–88 Read article
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Mathematical Approaches to Nonlinear Oscillatory Systems with Damping: Exact and Approximate Solutions
Abstract: The study of nonlinear oscillatory systems with damping is a key area of research in applied mathematics, particularly in the context of dynamical systems, stability analysis, and bifurcation theory. These systems, described by second-order nonlinear differential equations, exhibit a rich variety of behaviors, including periodic, quasi-periodic, and chaotic motions. The introduction of damping—representing energy dissipation—adds a layer of complexity, making the analytical and numerical solution of such systems a challenging …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 7–11 Read article
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The Role of Artificial Intelligence in Enhancing Athlete Performance and Training Strategies
Abstract: Artificial Intelligence (AI) is transforming modern sports by improving athlete performance, training methods, and decision-making processes. The integration of AI technologies such as machine learning, data analytics, wearable sensors, and computer vision has enabled coaches and sports scientists to analyze large amounts of performance data with greater accuracy and efficiency. Athletes' physiological indicators, movement patterns, injury risks, and recuperation processes are all monitored by these technology. Training regimens can therefore …
Published in Recent Trends in Sports · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article
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Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning
Abstract: The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article