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1850 articles for “extractant”
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Enhanced Biodiesel Production Via Encapsulation of Yeast Cells in Biocompatible Polymers
Abstract: Yeast-based biodiesel production offers a sustainable alternative to conventional fossil fuels. However, factors like harsh environmental conditions and shear stress during processing can limit yeast cell viability and overall biodiesel yield. This study explores the potential of encapsulation technology using biocompatible polymers to improve yeast performance in biodiesel production. Encapsulation can create a protective barrier for yeast cells, shielding them from harsh environments and shear stress during processing. This protection …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 57–62 Read article
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Comparative Study of AI-Driven Fashion Trend Prediction System Using AI and ML: A Review
Abstract: To overcome the challenges in fashion trend forecasting, researchers have introduced several advanced and data-driven approaches. One such method uses a long short-term memory (LSTM) model combined with an encoder-decoder architecture to extract meaningful fashion content and recognize styles from product images. This model achieves higher accuracy in predicting upcoming fashion trends by incorporating varying price intervals and has shown impressive results when evaluated on the Amazon fashion dataset. Another …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 35–41 Read article
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Advances in Multiclass Oral Cancer Detection Using Spectroscopic and AI Techniques
Abstract: Oral cancer, primarily OSCC, is still a major health issue worldwide, especially in low-HDI countries. Early diagnosis is essential since survival rates for early detection are much higher than for late-stage detection. However, traditional methods like visual inspection and biopsy are time-consuming, invasive, and rely on the clinician's skill, which is a limitation in accessibility and efficiency. Oral cancer detection has just been revolutionized by recent advances in spectroscopic techniques, …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 39–48 Read article
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The Silent Mineral: Structural Complexity and Industrial Utility of Natural Kaolin
Abstract: Kaolin, a naturally occurring aluminosilicate clay predominantly comprising the mineral kaolinite (Al₂Si₂O₅(OH)₄), exhibits a 1:1 layered silicate structure that imparts distinctive physicochemical properties suitable for extensive industrial utilization. Deposits of kaolin are broadly classified into primary (residual) and secondary (sedimentary) categories, each defined by their geological origin and mineralogical features. The industrial processing of kaolin encompasses stages such as raw material extraction, beneficiation, and purification, aiming to optimize parameters including …
Published in International Journal of Crystalline Materials · Vol. 2, Issue 1, 2025 · pp. 52–61 Read article
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Big Data in Chemistry: Problems and Answers
Abstract: The rapid growth of experimental and computational chemistry data, researchers now have access to vast datasets, presenting both significant opportunities and challenges. This paper explores the primary challenges associated with managing, processing, and utilizing big data in chemistry, including data heterogeneity, integration across various scales and systems, lack of standardized formats, and the need for advanced tools for data analysis. Additionally, the paper discusses the ethical concerns of data ownership, …
Published in International Journal of Cheminformatics · Vol. 2, Issue 1, 2024 · pp. 9–14 Read article
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A Multi-Criteria Analysis Based on Various Factors for Evaluation of Organic-Mineral Fertilizer Components
Abstract: This study explores the potential of organic-mineral fertilizers as sustainable alternatives to synthetic options, evaluating ten such fertilizers, including coffee grounds, poultry eggshells, bone meal, Fish Emulsion, compost, cow manure, wood ash, biochar, seaweed extract, and green manure. A multi-criteria analysis assessed factors like effectiveness, cost, environmental impact, availability, and waste potential. Coffee grounds and poultry eggshells performed best due to their high nutrient content and positive soil effects, with …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 32–44 Read article
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U-Net Based Approach for Automated Brain Tumor Classification
Abstract: Brain tumor detection and identification play vital roles in diagnostic procedures in the field of medicine, with the conventional analysis of MRI images requiring a lot of time and also subject to variability. The proposed study involves the use of a CNN-U-Net based approach for brain tumor detection and identification automatically. The study uses a database of 3,064 contrast-enhanced T1-weighted MRI images from 233 patients with the tumors of meningioma, …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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First Insights into Whole Genome Sequencing of the Mycobacterium tuberculosis Complex: Molecular Diversity and Drug Susceptibility Patterns in Senegal
Abstract: Background: We conducted a bibliographic analysis of the Mycobacterium tuberculosis complex (MTBC) in sub-Saharan Africa, which included the analysis of 8,139 genomic sequences from 34 of the 49 sub-Saharan African countries. Notably, only one complete sequence from Senegal was identified, which had been generated in the United States. Our primary objective was to utilize whole genome sequencing (WGS) to detect resistance in anti-tuberculous strains of the MTBC in Senegal. This …
Published in Recent Trends in Infectious Diseases · Vol. 2, Issue 1, 2025 · pp. 1–14 Read article
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Role of Generative AI in Redefining Data Analytics
Abstract: The rapid evolution of data-driven technologies has introduced both significant challenges and promising opportunities within the field of data analytics. Among the most impactful advancements is Generative Artificial Intelligence (Generative AI), a groundbreaking subset of AI that is reshaping how data is interpreted, generated, and utilized. Unlike traditional analytical tools that rely solely on existing data patterns, generative AI possesses the capability to create synthetic data, simulate complex scenarios, and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 01–07 Read article
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Cutting- Edge Gravitational-Wave Detectors: Technology & Innovations
Abstract: Gravitational wave detectors using laser interferometry are sophisticated instruments designed to measure the ripples in spacetime caused by cosmic events such as the merging of black holes or neutron stars. This schematic outlines the fundamental components and working principle of a typical laser interferometric gravitational wave detector, such as those used in the LIGO and Virgo observatories. The core of the detector is an interferometer, typically a Michelson interferometer, with …
Published in International Journal of Universe · Vol. 1, Issue 1, 2025 · pp. 23–29 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 Read article
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Effect of Steam Flash Explosion Conditions on Preparation of Reed Pulp
Abstract: The effects of different steam explosion conditions on preparation of reed pulp by steam flash explosion were analyzed. Because the main factors affecting steam explosion are steam pressure, retention time and liquid-to-reed ratio, so that the effects of these conditions on the steam explosion pretreated reed straw, and constituent of reed pulp were analyzed. Reed straw samples, 2~3cm in length, were loaded into a 5L stainless steel reactor and treated …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 2, 2025 · pp. 115–128 Read article
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Smart Agriculture in India: Advancements in Image Processing for Automated Plant Disease Detection and Crop Analysis
Abstract: The adoption of image processing technologies in agriculture is emerging as a revolutionary method for tackling persistent challenges in the farming industry. These techniques are increasingly used for different tasks such as detecting plant diseases, assessing crop health, and predicting yields, especially in the framework of smart agriculture systems. This study paints a detailed picture of the latest progress in image processing techniques applied to automated disease detection and detailed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 13–19 Read article
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Leveraging Large Language Models for Personalized Document Summarization and Question Answering: An Architecture for Stoner-Friendly Chatbots
Abstract: This study presents a detailed framework for developing personalized chatbots that utilize large language models (LLMs) to process and extract information from extensive documents while effectively responding to user inquiries. The proposed system is designed to mitigate information overload by employing advanced natural language processing techniques, leveraging technologies such as OpenAI, LangChain, and Streamlit. By integrating these tools, the framework enhances knowledge retrieval, simplifies document comprehension, and improves overall productivity. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 88–93 Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
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High-Performance Biodegradable Films from Bamboo Derived Cellulose Nanofibers and Silk Fibroin: Engineering Sustainable Polymer Composites
Abstract: This research presents the advancement of biodegradable composite films from cellulose nanofibers (CNFs) extracted from bamboo and silk fibroin (SF) derived from Bombyx mori cocoons. CNF/SF composites were fabricated in three different compositions—CS10, CS30, and CS50—via aqueous blending and solution casting, followed by ethanol-induced β-sheet stabilization. Mechanical testing confirmed a considerable enhancement in tensile strength from 72 MPa (CS10) to 112 MPa (CS50), while Young’s modulus improved from 2.4 GPa …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 256–265 Read article
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Harnessing Marine and Agro-Waste Resources: Bioengineered Seaweed Polysaccharide–Coconut Films for Next-Generation Sustainable Packaging
Abstract: The increasing demand for biodegradable alternatives to petroleum-based plastics has led to significant interest in marine biopolymer-based packaging materials. This study focuses on the development of eco-friendly biocomposite films by reinforcing carrageenan, extracted from Kappaphycus alvarezii, with alkali-treated coconut at varying loadings (5%, 10%, and 15% w/w). The films were fabricated via solvent casting and subjected to comprehensive characterization. Mechanical analysis revealed substantial enhancement in tensile strength from 21.3 MPa …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 217–227 Read article
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Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article