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1983 articles for “failure-prediction AUROC of 0.967” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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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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Challenges in Diabetes Management Barriers and Support Systems in North India
Abstract: Background: The prevalence of Diabetes mellitus is ever growing in India and management of the disease is hindered by socio-economic, healthcare, and psychosocial barriers. Insofar as economic and social barriers pose challenges ranging from limited access to medical care, social stigma, specialist support leading to improper glycemic control, which is a strong predictor for diabetes complications, morbidity and mortality. Moreover, developing an understanding of systemic challenges and available supports is …
Published in Emerging Trends in Metabolites · Vol. 2, Issue 2, 2025 Read article
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Process Parameters Optimization of Fiber Laser Cladded SS316 Surface Using RSM Analysis
Abstract: This paper presents the laser cladding experiments on the surface of SS316 to study the variations in process parameters, such as scanning speed (100-250 mm/min), laser power (50-250 W), and % volume of B4C (5- 25%) + SS316 powder on the mechanical, metallurgical and tribological performance of the modified surface. A central composite design (CCD) was used to develop the response surface methodology (RSM) to design the experiments and for …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 186–201 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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A Single Case Report of Sacral Nerve Stimulation in Neurogenic Bladder Dysfunction: A Physiotherapeutic Perspective
Abstract: Background: This case study evaluates the effectiveness of sacral nerve stimulation (SNS) for improving neurological bladder function in a 34-year-old male patient, who underwent surgical intervention at the level of L4 for Conus Medullaris Syndrome. The patient presented with severe neurological deficits including bladder dysfunction. Method: Post-surgery, a targeted physiotherapy regimen, including faradic current stimulation to the sacral nerves (S2-S4) and conventional exercises was implemented to address bladder function. Pre- …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 3, Issue 1, 2025 · pp. 1–9 Read article
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A Study to Evaluate Nurse Led Intervention Regarding Home Care Management Among Tuberculosis Patients Attending Chest and TB OPD at PGIMS Rohtak
Abstract: Introduction: Tuberculosis is an infectious bacterial pathogen caused by the bacillus called Mycobacteriumtuberculosis, an acid-fast rode shaped bacillus 0.8–5 μm in length and 0.2–0.6 μm in thickness. Tuberculosis (TB) primarily impacts the lungs (pulmonary TB), but it can also affect other parts of the body (extra-pulmonary TB). It spreads through the air and causes damage to the lungs and various other organs. TB is a significant public health issue in …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 3, Issue 1, 2025 · pp. 31–36 Read article
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Progression of Health and Wellness: Artificial Intelligence (AI) and Deep Learning (DL) for Precision Medicines
Abstract: Deep learning and artificial intelligence in the field of precision medicine is revolutionizing healthcare to make personalized therapeutic approaches desirable based on the unique characteristics of the patient. AI technologies improve diagnostic accuracy by analyzing medical data, spotting patterns and anomalies that human experts may miss. AI-driven models are instrumental in precision medicine, where they can predict patient response to therapies to tailor treatment plans, enhancing outcomes and reducing adverse …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
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Study of a Western Disturbance of 2023 Using Satellite-Based Observation, Reanalysis Data, and Numerical Simulation
Abstract: Western Disturbances (WDs) are synoptic-scale, extratropical storm systems that influence winter precipitation across northwest India. This study focuses on a specific WD event that occurred from 24– 25 March 2023, affecting Jammu & Kashmir, Himachal Pradesh, Uttarakhand, and Punjab. The analysis integrates satellite observations, ERA-5 reanalysis data, and simulations from the Weather Research and Forecasting (WRF) model to evaluate the model's performance. The novelty of this study lies in its …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 16–38 Read article
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Chemical Reactor Design and Analysis: A Review
Abstract: Chemical reactors play a critical role in industries such as oil and gas, chemical processing, and power generation, where they operate under extreme pressure and handle highly toxic, compressible fluids. The growing need for alternative energy sources has led to an increased demand for vessels capable of withstanding high pressure and temperature, especially in the chemical and petroleum industries. Recent innovations in chemical reactor technology have concentrated on creating new …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 49–59 Read article
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Analytical Method Development and Validation of Simultaneous Estimation of Natural Active Constituents Andrographolide and Piperine by UV Method.
Abstract: A simple, accurate, precise, and robust UV-Visible spectrophotometric method was developed and validated for the simultaneous estimation of Andrographolide and Piperine in bulk and combined pharmaceutical dosage forms. Preformulation studies confirmed favorable physicochemical properties for both drugs, including acceptable solubility profiles, melting points, pH values, and partition coefficients. The method development involved determination of λmax values at 224 nm for Andrographolide and 288 nm for Piperine using ethanol as solvent. …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 12, Issue 3, 2025 · pp. 33–41 Read article
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Dynamic Mechanical Analysis of Carbon Fiber Reinforced Polymer Composites
Abstract: This study investigates the thermal decomposition and mechanical properties of Fiber-Reinforced Polymer Composites (FRPCs) using Dynamic Mechanical Analysis (DMA). The research focuses on improving the recycling and recovery process of Carbon Fiber-Reinforced Polymers (CFRPs), addressing environmental concerns regarding their disposal. By analyzing the effects of different heating rates (5°C and 10°C per minute) and atmospheric conditions (nitrogen, oxygen, and a combination of both), the study identifies optimal parameters for maximizing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 386–393 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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Epipelic Algae Assemblage and Nutrient Status as Indicators of Pollution in Alice Creek, Rivers State, Nigeria
Abstract: Background and Objective: Alice creek is a tributary of the Sombreiro River, Akuku-Toru Local Government Area, Rivers State, Nigeria, receiving various anthropogenic wastes. The study investigated the species composition, diversity, abundance, and distribution of epipelic algae, and the nutrient status of Alice creek, a tributary of Sombreiro river, Rivers State, Nigeria. Materials and Methods: Epipelic and nutrients samples were collected monthly between February and May 2020 from three (3) stations …
Published in International Journal of Marine Life · Vol. 2, Issue 2, 2025 · pp. 12–20 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Integrated, Geospatial Risk Assessment of Air, Water, and Soil Pollution Impacts on Agricultural Sustainability using Advanced Digital Technologies
Abstract: The systemic threat posed by the convergence of air, water, and soil contaminants represents a critical challenge to global agricultural resilience and food security. Traditional, site-specific pollutant monitoring methods are insufficient for capturing the dynamic, diffuse, and often nonlinear nature of environmental risk pathways that permeate agrarian landscapes. This study presents a robust framework for comprehensive risk assessment utilizing a synergistic suite of modern tools designed for spatial, temporal, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 28–37 Read article
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Revolutionizing Vaccine Development:The Transformative Role of Bioinformatics in Designing Next-Generation Immunotherapies
Abstract: Vaccines have long been central to the prevention and control of infectious diseases, dramatically reducing morbidity and mortality worldwide. In the modern era, the integration of bioinformatics has revolutionized vaccine development by enabling rapid, precise, and cost-effective identification of potential vaccine targets. This seminar explores the multifaceted applications of bioinformatics in vaccinology, including antigen discovery, epitope prediction, structural modeling, molecular docking, and immunoinformatics-driven vaccine design. Special emphasis is placed on …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 19–33 Read article
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Dielectric Breakdown and Electrical Aging of Insulating Polymer Materials in High Voltage Systems
Abstract: In this paper, a detailed analysis of dielectric breakdown and electrical aging behavior of high-voltage insulating polymer material has been proposed through sophisticated MATLAB simulation. The research involves electric field modeling, aging life prediction, partial discharge (PD) behavior and uncertainty modeling using Monte Carlo analysis. Electric field hotspots causing critical behavior, sensitivity of the lifespan to electric stress, and the stochastic PD build-up allow predictive diagnostics of the health of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 173–187 Read article
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An Experimental Investigation of Polyethylene Terephthalate Fibers in the Properties of Concrete
Abstract: In India near about every year 45 million tons of solid waste is generated. The solid waste rate is increasing of 1.5 to 2% every year. In that total solid waste, Plastics contains 12.3% waste generated in which most common are the water bottles. Now the present worldwide situation, the production of PET (Polyethylene Terephthalate) exceeds 6.9 million tons per year. So that it is necessary to reusing of PET …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1063–1072 Read article
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The Convergence of AI and Composites - A Review Anchored in Patent Trends
Abstract: The integration of artificial intelligence (AI) and machine learning (ML) techniques is revolutionizing the design, analysis, and optimization of polymer (PC/FRP), metal (MC), and ceramic matrix composites (CC). Techniques such as artificial neural networks (ANN), deep learning (DL), genetic algorithms (GA), and physics-informed machine learning (PIML) are employed to enhance property estimation, process optimization, and predictive modeling. These AI-driven frameworks enable virtual testing, application-specific material design, and real-time decision-making, while …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 182–198 Read article
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AI-Powered Solutions for Sustainable Waste Management in Construction Projects
Abstract: The construction industry is a significant contributor to global waste, posing challenges to sustainability and environmental health. This research explores AI-powered solutions for sustainable waste management in construction projects, focusing on optimizing waste reduction, recycling, and resource efficiency. By integrating machine learning algorithms and IoT-enabled sensors, real-time monitoring of waste generation and segregation can be achieved. Predictive analytics and AI-driven decision-making tools are employed to enhance material reuse and minimize …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 1–5 Read article