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32 articles for “Material Design Interpretability”
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An Evaluation of the Effectiveness of a Self-Instructional Module on First Aid and Safety Measures for School Children (Aged 11–14 years) at PDR VVP Vidyalaya, Loni
Abstract: Background: School children are active youngsters. India is home to nearly 500 million young individuals, with approximately 370 million being children under 15 years old, highlighting their crucial role as the future of the country. Young children often exhibit naughty, defiant, and impulsive behavior. According to the World Health Organization’s Global report, in the South-East Asia Region, road traffic accidents, drowning, burns, and other injuries are leading causes of child …
Published in Journal of Nursing Science & Practice · Vol. 15, Issue 1, 2025 · pp. 17–22 Read article
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Orthostride: An Internet of Medical Things-Enabled Smart Rehabilitation Footwear System for Real-Time Monitor
Abstract: The orthopedic rehabilitation goal of controlled weight bearing, a stable gait progression, and early recognition of hazardous situations for safe mobility is traditionally met through time, scheduled in-clinic observation and clinician induction, and patient report. In this work, Orthostride, a smart rehabilitation footwear prototype intended to augment postoperative and injury-related lower extremity restoration through continuous sensing, embedded decision logic, local feedback, and remote telemetry, is proposed. This system incorporates force …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
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ML-Based Predictive Modeling of Mechanical Properties in 3D-Printed Polymer Composites for IoT Applications
Abstract: This study aims to develop an interpretable and high-accuracy machine learning framework for predicting the mechanical properties of 3D-printed fiber-reinforced polymer composites, with a focus on structure–property correlations relevant to polymer processing and functional performance. Composite specimens based on PLA and ABS matrices were fabricated using FDM with varying weight fractions (5–20 wt%) of carbon and glass fibers. Standardized mechanical testing (ASTM D638, D256, D790) was performed to evaluate tensile …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 61–78 Read article
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AI-Based Discovery of High-Performance Energy Storage Polymer Composites: A Comprehensive Review
Abstract: The accelerating global demand for high-performance energy storage systems has stimulated significant research into advanced polymer composites as next-generation electrolytes, electrode binders, and functional membranes for batteries, supercapacitors, and photovoltaic devices. However, the vast compositional and structural design space of polymer materials presents formidable challenges for conventional trial-and-error discovery strategies, which remain slow, costly, and biased by prior expert knowledge. Machine learning (ML) and artificial intelligence (AI) have emerged as …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1083–1097 Read article
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Debris Flow Kinetics in Planetary Environments: A Systems Perspective
Abstract: Debris flow kinetics in planetary environments represent a critical intersection of geomorphology, fluid mechanics, and planetary science. These gravity-driven flow mixtures of solids, liquids, and gases play a key role in shaping planetary surfaces and recording environmental histories. This study adopts a systems perspective to analyze debris flow behavior across different planetary contexts, emphasizing the interconnected roles of material properties, energy transformations, and environmental forcing. By integrating rheological models with …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 08–17 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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Assessment of exacerbation of Depression in pulmonary tuberculosis patients by using PHQ-9 scale at Tertiary Care Hospital
Abstract: Context: Depression leads to more dysfunction and stress, which could affect the patient's life condition. Tuberculosis is a leading cause of comorbidity with depression. Those suffering from tuberculosis and depression are at higher risk of bad health-seeking nature, resulting in higher morbidities, drug resistance, and mortality. The relationship is not well established. Aims: To identify multiple variables/ dependent factors affecting depression respectively in tuberculosis patients and check the medication adherence …
Published in International Journal of Pathogens · Vol. 1, Issue 2, 2024 · pp. 24–31 Read article
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Modelling -Based Evaluation of Hybrid Natural Synthetic Fiber Polymer Composites for Sustainable Energy Applications
Abstract: The growing need of lightweight, high-performance, and green energy system materials has increased the research on hybrid polymer composites. This paper gives a modelling-based evaluation of polymer matrix composites which are reinforced using natural fibers like jute, sisal, bamboo in a combination with synthetic glass fibers to be used in sustainable energy sources. An analytical model has been used to assess the effect of hybrid fiber composition on mechanical, thermal, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 682–688 Read article
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Tactile Sensing Technologies in Robotics: A Review of Sensors, Materials, and Applications
Abstract: Tactile sensing, which closely resembles the human sense of touch, is an essential capability in modern robotics. It enables robots to detect and interpret physical interactions with objects, surfaces, and living beings, thereby allowing them to operate more intelligently and adaptively in complex environments. Unlike visual or auditory sensors, tactile sensors provide direct feedback about contact, pressure, texture, force, temperature, and even vibration. These sensory cues are vital for improving …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 17–23 Read article
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Artificial intelligence-integrated nanobiotechnology for precision medicine, smart diagnostics, and sustainable environmental applications
Abstract: Background: Nanobiotechnology integrates nanoscale materials with biological systems, enabling breakthroughs in drug delivery, biosensing, and environmental monitoring. However, the complexity of biological interactions and the vast parameter space of nano‑bio interfaces limit conventional design. Artificial intelligence (AI) offers powerful tools for modelling, predicting, and optimising these systems. Objective: This review provides a systematic, STM‑compliant overview of AI‑integrated nanobiotechnology across three domains: precision medicine (AI‑optimised nanocarriers, personalised therapeutics), smart diagnostics (AI‑powered …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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Generative AI-Based Inverse Design of Sustainable Biodegradable Polymers with Target Mechanical and Thermal Properties
Abstract: The escalating global plastic pollution crisis has intensified the urgent need for sustainable biodegradable polymer alternatives that can match or exceed the performance of conventional petroleum-based plastics while minimizing environmental impact. However, traditional polymer discovery approaches are severely constrained by high experimental costs, protracted development cycles spanning years, and fundamental inability to simultaneously optimize multiple conflicting material properties such as mechanical strength, thermal stability, and degradation kinetics. This study presents …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article