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224 articles for “Linear”
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Synthesis, Spectral Characterization and Computational Studies of Hydrazine Derivative
Abstract: (E)-1-(2,3-dimethoxy benzylidene)hydrazine (2,3-DMBH) is synthesized by condensation reaction. FT-IR, ¹H NMR, ¹³C NMR spectra were recorded for this compound. The synthesized compounds were evaluated as potential drug candidates through ADME analysis and Lipinski’s rule verification. Molecular docking studies against six proteins using AUTO DOCK software showed promising results. Among them, 2,3-DMBH exhibited strong binding affinities, particularly with 3ERT (-5.44 kcal/mol), followed by 5F90, 7E9B, and 3EWD. These findings suggest that …
Published in Emerging Trends in Chemical Engineering · Vol. 12, Issue 2, 2025 · pp. 1–17 Read article
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Utilizing Machine Learning to Evaluate the Connection between Poisson's Ratio and the Petrophysical Properties of Reservoir Rocks
Abstract: The Poisson's ratio is a crucial cornerstone, illuminating our understanding of geomechanical behaviour in wells during the dynamic drilling process and the inspiring recovery journey. This research rigorously employs machine learning methods to analyse the significant impact of geophysical parameters on the Poisson ratio in hydrocarbon reservoirs found in oil fields. The analysis utilized data from multiple oil and gas fields, highlighting the crucial relationships between the Poisson ratio, the …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 33–43 Read article
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The Onset of Rayleigh-Bénard-Marangoni Convection in a Ferromagnetic Fluid Layer
Abstract: This study examined the implications of magnetic boundary conditions, which are vertical in nature, on buoyancy and surface tension–driven ferrothermal convection (FTC) in a ferrofluid layer. While the upper surface is stress-free and susceptible to general thermal boundary issues, the bottom surface is stiff and insulating against temperature changes. The eigenvalue issue is solved analytically using the regular perturbation method and numerically using the Galerkin technique. According to analysis, raising …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 1, 2025 · pp. 1–9 Read article
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Fracture Toughness in Advanced Materials: A Comparative Review of Testing Methods and Standards
Abstract: Fracture toughness is a key material property used to assess a material's ability to resist crack propagation, which is vital for ensuring the reliability and durability of structures and components in high-performance applications. It is particularly important in advanced materials such as composites, ceramics, and high-strength alloys, which are increasingly used in demanding industries such as aerospace, automotive, and civil engineering. Fracture toughness testing helps determine the material's behavior under …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 1, 2025 · pp. 17–21 Read article
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Enhancing Dimensional Accuracy of Affordable 3D-Printed Objects Via Solid Model Tuning For Industrial Manufacturing
Abstract: In the industrial applications of 3D printing (3DP) technologies, achieving precise dimensional accuracy and precision as well as improving surface quality are essential goals. With a focus on cost-effective engineering applications, this experimental research examines how solid model geometry tuning improves the internal and exterior dimensional accuracy of inexpensive 3DP technologies. Dimensional errors in the X, Y, and Z directions were meticulously measured on 3D parts made using Material Extrusion/Fused …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 201–210 Read article
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Experimental Investigations of EDM Parameters on Machining Square Blind Holes in Maraging Steels
Abstract: Square blind holes have certain qualities that make them useful in fields where accuracy and efficiency are crucial, like aerospace, automotive, molding, and general manufacturing industries where structural integration is required in precise assembly. It is challenging to machine square blind holes with traditional machining due to geometrical complexity as precision is required for sharp corners which is difficult to get at the corners due to tool wear. Electrical discharge …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 390–397 Read article
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Review And Analysis of Application of Conductive Polymer Composites in Power-Efficient RF Circuits For 5G PAPR Reduction
Abstract: The need for low power RF circuits has gained more importance in the background of fifth-generation (5G) wireless communication systems, since the inherent PAPR characteristic of 5G signals—especially when using orthogonal frequency division multiplexing (OFDM) based techniques—becomes high. This high PAPR limits the efficiency of RF power amplifiers, increases power consumption, and induces thermal management challenges. In this context, conductive polymer composites (CPCs), based on advanced polymer matrices integrated with …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 111–125 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 Read article
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Computer Aided Diagnosis of Breast Cancer using Machine Learning Techniques
Abstract: Breast cancer is one of the significant health problems that lead to early mortality in women, especially those between 40 and 55 years of age all over the world. In recent years, the number of breast cancer cases among women has risen significantly, making early and accurate diagnosis more important than ever. Computer-aided diagnostic (CAD) tools have become valuable in supporting radiologists by enhancing the precision of breast cancer detection. …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 2, 2025 · pp. 1–11 Read article
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Modeling Dispersed Count Data: Evaluating the Conway–Maxwell–Poisson Regression with COVID-19 Mortality Data
Abstract: Count data are prevalent in diverse fields such as biology, healthcare, psychology, and marketing, characterized by non-negativity and inherent heteroskedasticity, often exhibiting overdispersion or underdispersion. Traditional Poisson regression, which assumes equal mean and variance, is inadequate for such dispersed data. To address this, various generalized linear models (GLMs) and their extensions, including negative binomial (NB) and Conway–Maxwell–Poisson (CMP) regressions, are utilized. This study evaluates the performance of CMP regression compared …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 18–26 Read article
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QSAR Modeling Techniques: A Comprehensive Review of Tools and Best Practices
Abstract: Quantitative Structure–Activity Relationship (QSAR) modeling has become an essential tool in drug discovery, toxicity assessment, and environmental chemistry. By correlating chemical structure with biological activity or toxicity, QSAR enables the prediction of compound behavior without extensive experimental testing. This approach not only saves time and resources but also supports ethical practices by reducing reliance on animal studies. The evolution of QSAR from basic linear models to advanced machine learning and …
Published in International Journal of Cheminformatics · Vol. 3, Issue 1, 2025 · pp. 56–63 Read article
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An Overview of Artificially Generated Neural Networks Inside the Brain’s Structure in an Alzheimer’s Disease Patient
Abstract: Alzheimer’s disease produces significant neuronal loss, while the precise mechanisms and timing are yet unknown. Other types of cell death, such necroptosis, parthanatosis, ferroptosis, and cuproptosis, need further investigation. Based on brain images of people with mild cognitive impairment, this study assesses artificial neural networks (ANNs) used to diagnose and predict Alzheimer’s disease (AD). This research was conducted considering growing recognition among researchers and medical professionals regarding the importance of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 Read article
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Circular Economy Approach in Wastewater Treatment: Recycling and Recovery
Abstract: The demand for freshwater resources has been greatly raised by the exponential expansion of urbanization, industrialization, and population, therefore causing water scarcity in many different countries. Concerning the safe disposal of sewage to safeguard public health and the environment, traditional wastewater treatment methods have mostly concentrated. These linear solutions, however, sometimes ignore the possibilities of wastewater as a useful resource. Focused on resource recovery and recycling, the circular economy (CE) …
Published in Journal of Water Pollution & Purification Research · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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From Oral to Virtual: The Evolution of Storytelling
Abstract: Storytelling, a timeless art of expressing ideas and emotions, has experienced a revolutionary transformation in the digital era. The emergence of digital platforms like social media, streaming services, podcasts, and interactive apps has completely transformed how stories are created, shared, and experienced. This modern age is marked by accessibility, interactivity, and multimedia convergence, allowing storytellers to reach world audiences in unprecedented fashion. With the advent of the digital era, stories …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
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Analytical Method Development and Validation for Simultaneous Estimation of Paracetamol and Piroxicam by UV Method
Abstract: A new establishment and validation of a simple, precise, accurate and cost effective UV-Visible spectrophotometric method was developed to estimate both Paracetamol and Piroxicam simultaneously in conjoined pharmaceutical dosage forms. This technique was founded on simultaneous equation method of absorbances recorded at 252.0 nm and 282.0 nm of Paracetamol and Piroxicam in methanol respectively and an isosbestic point could be observed at 265.0 nm. It showed very good linearity over …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 3, 2025 · pp. 14–21 Read article
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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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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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The Rise of Fractional Calculus: Novel Applications in Engineering and Biological Systems
Abstract: Fractional calculus (FC) is an advanced mathematical framework that generalizes the classical concepts of differentiation and integration to non-integer, or fractional, orders. This extension of traditional calculus allows for the modeling of complex dynamic systems that exhibit behavior not easily captured by integer-order differential equations. Over the last few decades, fractional calculus has seen a rapid rise in popularity, particularly in applied mathematics, engineering, and biological sciences, due to its …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 7–11 Read article