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502 articles for “LCMS/MS”
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The Anhadnaad Universe
Abstract: Current Science considers that 95% universe is made of Dark energy and Dark Matter which are completely unknown entities and can’t be detected directly. Current Science also does not believe in independent existence of Consciousness on its own. It rather consider it as an outcome of electrical interaction in brain cells which means there are as many consciousnesses as the number of brains in the entire universe. But my theory …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 2, 2025 · pp. 19–29 Read article
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Advances in Analytical Chemistry Research Methodology: Trends and Applications
Abstract: Analytical chemistry is critical to scientific study because it allows for the accurate identification, measurement, and characterization of chemical compounds. Recent advances in methodology have improved accuracy, sensitivity, and efficiency, with techniques such as High-Performance Liquid Chromatography (HPLC), Gas Chromatography (GC), Mass Spectrometry (MS), and Nuclear Magnetic Resonance (NMR) spectroscopy transforming analytical procedures. The combination of Artificial Intelligence (AI) and Machine Learning (ML) has enhanced data processing, pattern recognition, and …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 2, 2025 · pp. 10–18 Read article
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Building Scalable Microservices with Micronaut, Kotlin, and AWS DynamoDB: A Comprehensive Architecture Study
Abstract: The evolution of enterprise software has trended steadily toward microservice architectures due to their inherent scalability and resilience advantages over monolithic systems. This research explores a comprehensive implementation approach using Micronaut, an innovative JVM-based framework specifically designed for resource-efficient microservices. The study combines Micronaut with Kotlin programming language and leverages AWS DynamoDB as a scalable NoSQL persistence layer, with Apache Kafka providing event-driven communication capabilities. We explore the critical role …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 40–57 Read article
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Facile Synthesis and Characterization of Cd²⁺ Doped NiAl₂O₄ Nanoparticles for Advanced Polymer Composite Integration
Abstract: Ni1-xCdxAl2O4, where 0 ≤ x ≤ 0.5, was successfully synthesized using the chemical co-precipitation technique, a scalable and cost-effective route suitable for composite material applications. X-ray diffraction (XRD) analysis revealed a crystalline cubic spinel structure for the resulting nanoparticles, with determined crystallite sizes ranging from 36 to 12 nm for NiAl2O4 and Cd-doped NiAl2O4. The respective band gaps for the materials were found to be 3.51 and 4.18 eV. Infrared …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 59–72 Read article
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Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation
Abstract: Machine fault detection is of immense significance in industrial automation to achieve efficient operations, reduced downtime, and reduced economic losses. Sugeno fuzzy logic and Gated Recurrent Unit (GRU) networks are used in this research to provide a new hybrid solution that addresses problems such as noisy data, evolving defect patterns, and real-time detection. To improve readability and reliability, the Sugeno fuzzy logic unit preprocesses fuzzy and uncertain input data into …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 17–26 Read article
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Tribological Performance and Wear Coefficient Prediction of AA2024–TiC Composites via Python-Based Machine Learning
Abstract: Determining wear coefficient accurately serves as a critical factor to maximize engineering materials' tribological characteristics. The experiment examines the wear characteristics of TiC-reinforced AA2024 aluminum alloy subjected to different tribological operating conditions. A pin-on-disc tribometer performed wear tests under different conditions of load and TiC weight fraction and sliding speed and duration. ANOVA statistical results show that load intensity and TiC reinforcement density stand out as principal variables that affect …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1099–1112 Read article
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Harnessing Machine Learning for Stock Movement Prediction: A Review of Current Approaches
Abstract: Stock price prediction is a crucial task in financial analysis, aiding investors and traders in making informed decisions. This study investigates the use of deep learning methods, particularly Long Short-Term Memory (LSTM) networks, for predicting stock prices based on historical market data. The dataset, sourced from Yahoo Finance, consists of time-series stock price data, which is preprocessed, feature-engineered, and visualized to improve prediction accuracy. The model's performance is assessed using …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 29–40 Read article
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Optimized Text Extraction and E-Repository Development of Hindi and Punjabi Documents Using OCR and NLP Techniques
Abstract: Increase in digitalization of content in the form of text content necessitates powerful document and text extraction systems, particularly for Indian languages such as Hindi and Punjabi. The existing Optical Character Recognition (OCR) solutions support major scripts such as English, leaving a research opportunity for effective recognition of Devanagari and Gurmukhi scripts. This study recommends a modified text extraction algorithm based on Tesseract OCR, accompanied by preprocessing steps of conversion …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 3, 2025 · pp. 35–43 Read article
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ML-Enhanced Smart Sensing Framework for IoT- Based Structural Health Monitoring Using Conductive Polymer Composites
Abstract: The growing demand for intelligent structural health monitoring (SHM) in dynamic infrastructures necessitates flexible sensing systems that are not only mechanically robust but also capable of real-time interpretation. Conventional SHM frameworks often rely on brittle sensor configurations and cloud-dependent processing pipelines, which suffer from latency, limited durability, and poor adaptability under variable loading conditions. Despite recent advances in composite materials and machine learning, current approaches lack a unified framework that …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 348–369 Read article
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Temperature-Dependent Viscoelastic Response of Magnetorheological Grease with Varying Particle Shapes
Abstract: This study examines the effect of temperatures on the magnetic and rheological properties of magnetorheological greases (MRGs) comprised of different particle shapes, under oscillatory shear mode test. Two samples were prepared with 70 wt.% flake-shaped electrolytic iron particles (EIP) and spherical carbonyl iron particles (CIP) which dispersed in 30 wt.% lithium-based grease, separately. Respective to magnetic properties test, the vibrating sample magnetometry (VSM) revealed that MRG-EIP exhibited 11.4% higher magnetic …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 139–147 Read article
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An Integrated Autonomous Rover-Drone System for Intelligent Exploration and Environmental Monitoring
Abstract: This paper presents a hybrid autonomous exploration platform integrating a ground rover and aerial drone, enhanced by swarm intelligence and a custom-trained YOLO V8 object detection model. The rover is equipped with GPS, IMU, and environmental sensors (DHT11, MQ135, BMP180), while the drone performs real-time aerial mapping and obstacle prediction. A YOLO V8 model, trained on 500 annotated terrain images (six classes: rocks, pits, trees, water, animals, vegetation), achieves a …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 43–61 Read article
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Heavy Metal Exposure in Industrial Workers of Punjab
Abstract: Background: Particularly for those in sectors such textiles, metallurgy, and electronics, heavy metal exposure in industrial environments is a major health issue. A range of negative health effects can result from metal exposure including lead (Pb), cadmium (Cd), chromium (Cr), arsenic (As), and nickel (Ni), including neurological, pulmonary, and renal ones. There is little information available on the degree of heavy metal exposure industrial workers in Punjab, India experience. Objective: …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 · pp. 1–7 Read article
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Comparative Evaluation of Hibiscus Cannabinus and Solanum Trilobatum Extracts as Inhibitors for C- Steel Corrosion protection in Acidic Medium
Abstract: This study analyzed the efficacy of various inhibitors in safeguarding carbon steel against corrosion in hydrochloric acid. The compounds that were subjected to testing included Acalypha indica root extract (AIRE), Hibiscus cannabinus (HC), and Solanum trilobatum (ST) leaf extracts. The investigation focused on the inhibitory efficacy through the application of gravimetric and electrochemical impedance methods. GC-MS and FTIR were employed to investigate the features of the inhibitors and co-inhibitors. Tafel …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 555–565 Read article
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IoT-Enabled Flexible Polymer Sensors for On-Body Health Monitoring and Real-Time Data Transmission
Abstract: Wearable health monitoring systems have grown increasingly vital in shifting care beyond clinical settings, yet many existing technologies remain hamstrung by rigid substrates and unreliable data streaming, impeding continuous and comfortable physiological assessment. Despite advances in flexible materials, most current sensor platforms suffer from limited mechanical endurance, signal instability under dynamic conditions, or an inability to sustain real-time wireless transmission. This work addresses those deficiencies by introducing a fully integrated, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 188–200 Read article
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Technometric Portrait of Sri Vinod Dham, an Indo-US Engineer, Father of Intel Pentium Process: A Quantitative Analysis
Abstract: Vinod Dham is recognized as the ‘Father of Pentium Chip’ or ‘Father of Intel Pentium Process’ in the field of the computer industry, and as an Indo-American pioneer from Silicon Valley. He has contributed 10 research papers during 1982–1986, with an average of two papers per year. This study tries to analyze his contributions through a bibliometric study and draw his familiarity as a world-famous electronic technologist. Data has been …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 3, 2025 · pp. 16–25 Read article
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Machine Learning-Driven Polymer Composite Smart Skin for Integrated Sensing in Soft Robotic Systems
Abstract: Soft robotics has grown rapidly, but its progress is still constrained by the limitations of current sensing skins. Most polymer-based sensors provide either flexibility or sensitivity, yet they struggle to deliver real-time communication and adaptive intelligence when deployed in complex robotic environments. This disconnect between material performance and system-level responsiveness forms a critical bottleneck for practical deployment. Existing approaches often treat tactile sensing and wireless communication as separate problems. As …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 121–136 Read article
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ML-Enhanced Self-Healing Fiber-Reinforced Polymer Composites with Embedded IoT Sensors for Damage Prediction
Abstract: Fiber-reinforced polymer (FRP) composites are widely used in aerospace and structural systems; nevertheless, the potential for microcracking and fatigue-induced performance degradation remains an obstacle with respect to improved service life. Traditional self-healing methods, while performing well on a chemical level, often lack real-time diagnostic awareness and adaptive control. To circumvent this, we developed a machine-learning augmented self-healing FRP composite, in which a DCPD–Grubbs catalytic matrix was combined with IoT sensor …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 188–208 Read article
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Reimagining Solid Waste Management in India: A case of Circular approach in C&D Waste Management
Abstract: Construction and demolition (C&D) waste, which accounts for an estimated 150–500 MT yearly and about 10–20% of the nation's total municipal solid waste (MSW) generation, is a significant management challenge for India. Accelerated urbanization, population increase, infrastructural expansion, and urban redevelopment initiatives are the main causes of this quickly expanding waste stream. Much of this waste is disposed of through uncontrolled dumping, encroachment on low-lying areas, and overcrowded landfills in …
Published in Journal of Construction Engineering, Technology & Management · Vol. 16, Issue 1, 2026 · pp. 1–10 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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Harnessing AI in the library of IITs: A Journey Towards Automation to Intelligence
Abstract: This study carries out an in-depth analysis of the impact and execution of Artificial Intelligence (AI) technologies in one of the noteworthy libraries in the twenty-three (23) Indian Institutes of Technology (IITs). It would be pertinent to mention that there is hardly any doubt that one of the most radiating technologies in the field of computing technologies is Artificial Intelligence which in turn is rendering a profound impact on the …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 95–105 Read article