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1988 articles for “di-” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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A Study to Find the Relation Between School Bag Weight and Musculoskeletal Discomfort in School Going Children
Abstract: Background: School bags are one of the several forms of manual load carriage used by school children. Carrying school bags that exceed 10% of body weight can lead to heightened energy expenditure, causing increased forward lean of the neck and trunk, reduced lung capacity, and elevated cardio-respiratory measures. Musculoskeletal disorders (MSDs) are characterized by injuries or disorders affecting muscles, tendons, ligaments, cartilage, or spinal discs, as diagnosed by healthcare providers, …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 49–58 Read article
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Enhancing Crop Health: A Review of Image Processing Methods for Leaf Disease Identification
Abstract: This research presents an overview of different image processing techniques for the identification of leaf disease. Many algorithms can be used to identify and categorize leaf diseases in plants, and digital image processing provides a quick, dependable, and accurate method of disease detection. This paper presents various techniques used on multiple crops and the achieved accuracy for each model. Leaf disease detection is a critical task in agriculture to ensure …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 10–14 Read article
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Analysis of Market Growth of Digital Payment Tools in India with Special Reference to UPI
Abstract: Digital transaction provides a transparent and easy way for customers; this new paradigm of financial transactions leads to an increment in the trust of customers. The Indian retail market has completely shifted to the Unified Payment Interface (UPI) for digital payment transactions. The Internet and Mobile Association of India report forecasts that the number will reach 900 million by 2025. Digital transactions facilitate numerous benefits over cash transactions, including convenience, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 1–12 Read article
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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Diabetes Prediction Using ML Techniques
Abstract: Diabetes mellitus, commonly referred to as diabetes, denotes a cluster of prevalent endocrine disorders characterized by persistent elevated levels of blood sugar. Diabetes is classified into two main types: type 1 and type 2. Type 1 diabetes arises when the body is unable to produce insulin, while type 2 diabetes involves either insulin resistance or insufficient insulin production. Early detection and intervention are essential to reduce its harmful impacts. The …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Sustainable Rural Development through Geospatial Technology – A Case of Keonjhar District of Odisha
Abstract: The 2030 Agenda for Sustainable Development emphasizes that sustainability encompasses three dimensions: economic, social, and environmental. Monitoring society's impact on natural resources involves identifying activities that affect ecosystem processes. Geospatial technology plays a key role in detecting community-level development projects and evaluating sustainable development outcomes at the district level. The main objective of the study is to show the impact of implementation of SDGs on the development of community livelihood …
Published in Journal of Geotechnical Engineering · Vol. 11, Issue 3, 2024 · pp. 30–46 Read article
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Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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Advances in Biological Systems Modeling for Predicting Drug Effects in Chronic Disease
Abstract: Biological systems modeling has emerged as a promising tool for understanding and predicting the effects of drugs in the treatment of chronic diseases. Chronic diseases, such as diabetes, cardiovascular diseases, and neurodegenerative disorders pose significant challenges to traditional drug development due to their complex, multifactorial nature. Systems biology approaches, which integrate computational modeling with experimental data, provide a holistic view of disease mechanisms and treatment responses. This review explores recent …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 17–22 Read article
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Fabrication and Characterization of Diacerein Loaded Nanosponge for Topical Delivery
Abstract: Diacerein, an anti-inflammatory drug, which comes under BCS class II, commonly used in treatment of osteoarthritis has limited by its poor solubility and bioavailability when administered topically. This study aimed to develop and evaluate diacerein-loaded nanosponges gel using varying concentrations of ethyl cellulose and polyvinyl alcohol (PVA) to enhance its delivery. Nanosponges were prepared using an emulsion solvent evaporation technique, with different ratios of ethyl cellulose (0.05-0.250%) and PVA (0.2-0.3%). …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 2, 2025 · pp. 26–46 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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Pathophysiology Reimagined: Integrating Systems Biology and AI for Disease Understanding
Abstract: Pathophysiology, the study of disease mechanisms at molecular, cellular, and systemic levels, has traditionally relied on reductionist approaches that often fail to capture the complex, dynamic, and interconnected nature of biological systems. Diseases such as cancer, neurodegenerative disorders, and infectious diseases arise from intricate interactions among genetic, epigenetic, metabolic, and environmental factors, necessitating integrative, data-driven methodologies for a deeper understanding. Systems biology has emerged as a powerful approach by leveraging …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 63–71 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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Enhanced Diabetes Prediction: A Comparative Study of Machine Learning Models
Abstract: Excessively high blood glucose levels lead to diabetes, a condition that can be better managed with early detection, resulting in a longer life and improved health. Machine learning models are essential tools in diagnosing diabetes, especially when trained on appropriate and relevant datasets. In this study, a combination of ensemble methods and nine distinct machine learning algorithms were utilized to develop a predictive model for diabetes diagnosis based on a …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article
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The Role of Artificial Intelligence in Mental Health: Applications in Neurodegenerative Disorders
Abstract: Artificial intelligence (AI) has significantly changed many aspects of medical care, particularly the early evaluation, therapy, and management of neurodegenerative illnesses like Alzheimer's, disease, Parkinson's diseases, and Huntington's diseases. The current research explores the application of AI in mental health with respect to neurological disorders, especially advancements in cognitive examination, neuroimaging analysis, predictive modeling, and customized therapy modalities. Artificial intelligence (AI) systems have shown enormous potential in detecting minute biomarkers …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 3, 2025 · pp. 34–40 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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Intergenerational Trauma and Cultural Resilience: Exploring the Impact of Family Norms on Mental Health Disclosure
Abstract: This comprehensive review examines how intergenerational trauma and cultural resilience influence individuals' choices to disclose or conceal their mental health challenges in family contexts. This paper utilizes 50 peer-reviewed studies out of 80 in total from various cultural contexts, this paper explores how family norms, especially in collectivist cultures, impact the disclosure of mental health issues. This review paper uses a thematic analysis strategy, systematically integrating qualitative, quantitative, and mixed-method …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 · pp. 53–58 Read article
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Swift Solutions: The Science and Innovation Behind Fast-Dissolving Tablets
Abstract: Swift solutions in the context of fast dissolving tablets (FDTs) represent an innovative breakthrough in pharmaceutical science, aiming to provide rapid and effective drug delivery for patients who face difficulty swallowing conventional dosage forms. The science and innovation behind FDTs are rooted in advanced formulation techniques, material science, and drug delivery mechanisms that prioritize speed, convenience, and patient compliance. These tablets are formulated to dissolve quickly in the mouth, removing …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 3, 2025 · pp. 26–36 Read article
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Role of Strontium in Structural and Dielectric characterstics of Barium Titanate
Abstract: Ba₀.₇₅Sr₀.₂₅TiO₃ (BST) compound was synthesized through the conventional solid-state reaction methodology, aimed at investigating its structural, microstructural, and dielectric characteristics. The structural characterization was executed employing X-ray diffraction (XRD), and the resultant diffraction patterns were refined utilizing the Rietveld method, which substantiated the establishment of a single-phase perovskite configuration exhibiting tetragonal symmetry and belonging to the P4mm space group. The refined lattice parameters revealed subtle distortions correlating with the substitution …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1157–1163 Read article
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Optimization of Direct Ink Writing Process Parameters for Liquid Silicone Rubber/TiO2 Composite Ink
Abstract: The purpose of this research is to develop and optimize the Liquid Silicone Rubber (LSR)/Titanium Dioxide (TiO₂) composite inks in Direct Ink Writing (DIW)-based 3D printing systems. The primary research objective was to use enhancement of mechanical, rheological, and dielectric characteristics of LSR using TiO₂ reinforcement but still retain extrusion stability and dimensional consistency. TiO₂ content (0, 5, 10, and 15 wt%) and catalyst and glycerol ratios were regulated and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 240–259 Read article