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36 articles for “Mixed-Mode Drying”
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Investigations of A Solar Dryer With Thermal Storage
Abstract: This study presents the design, building, and performance evaluation of a low-cost mixed-mode natural convection solar cabinet dryer in conjunction with a latent heat thermal energy storage system. The work's goal is to reduce post-harvest losses in rural and semi-urban areas by offering an effective and reasonably priced method of preserving agricultural goods. The dryer is made out of a transparent polycarbonate lid to allow for solar heat gain, an …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 13, Issue 1, 2026 Read article
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Genetic Variability and Statistical Methods: Key Insights for Computational Genetics Research
Abstract: Genetic variability, defined as the differences in DNA sequences among individuals, serves as the foundation of evolutionary biology and plays a pivotal role in species’ adaptability, resilience, and overall survival. Advances in genomic technologies, particularly high-throughput sequencing, have enabled unprecedented exploration of genetic diversity, fostering the growth of computational genetics. This interdisciplinary field combines statistical methods and computational tools to analyze genetic data, identify patterns, and link phenotypes to genotypes. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 19–23 Read article
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Kick Tolerance Modeling in Well Design and Drilling: A Comprehensive Technical Review
Abstract: Kick and blowout events in drilling operations can lead to significant losses of equipment, and in some cases, human lives. Oil and gas companies, along with oilfield service providers involved in drilling operations, face severe penalties and sanctions following such incidents. Research has demonstrated that incorporating kick tolerance models during the well planning and drilling stages can mitigate the risk of blowouts during secondary well control operations. This study reviews …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 33–58 Read article
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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
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Advances in Simulation and Surgical Skill Training Evolution: Narrative Integrative Review
Abstract: Simulation-based education has emerged as a cornerstone of contemporary general surgery training, driven by increasing emphasis on patient safety, competency-based education, and rapid technological innovation. Traditional apprenticeship models, while foundational, are constrained by reduced operative exposure, work-hour limitations, and variability in clinical case mix. In this context, simulation provides a structured, reproducible, and safe environment for acquisition, assessment, and refinement of surgical skills across the training continuum. This narrative review …
Published in Research and Reviews : Journal of Surgery · Vol. 15, Issue 1, 2026 · pp. 7–13 Read article
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Optimizing Mechanical and Durability Properties of Eco-Friendly Composite Materials Using Recycled Fillers and ML Techniques
Abstract: The increasing demand for sustainable construction materials has intensified the exploration of recycled fillers as partial or full replacements for natural aggregates in composite materials. This study investigates the mechanical and durability performance of polymer matrix composites incorporating processed recycled fillers derived from construction and demolition (C&D) waste. Three distinct processing methods were employed to prepare the recycled fillers: untreated (URF), single processed (SPRF), and double processed (DPRF), with replacement …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 269–309 Read article
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Analysis of Hybrid Photovoltaic Thermal (PV/T) Integrated Solar Dryer: An Experimental Validation
Abstract: In this study, a hybrid photovoltaic thermal (PV/T) integrated solar dryer has been designed, developed, and experimentally analyzed to evaluate its performance in real-world climatic conditions. The system incorporates a UV-stabilized sheet mixed-mode tent house structure, installed on the rooftop of a building located in Bhilai, Chhattisgarh, India. The dryer is equipped with a thermal collector directly connected to the drying chamber to enhance heat transfer efficiency. Experiments were conducted …
Published in Journal of Thermal Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 1–6 Read article
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Smart Energy Systems as a Solution for Sustainability
Abstract: This study examines the critical function of smart energy networks (SENs) in addressing the urgent global challenge of climate change. The study begins by elucidating the significant contributors to climate change, emphasizing the role of traditional energy sources, and underscores the need for a paradigm shift towards sustainable and cleaner alternatives. It explores the many facets of smart energy networks (SENs), including demand-side management, energy storage, smart grids, and the …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 1, Issue 2, 2023 · pp. 18–31 Read article
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AI and ML-Driven Immersive Technologies: A New Era in Education
Abstract: The very fast adoption of Artificial Intelligence (AI) and Machine Learning (ML) in education has transformed contemporary teaching and learning ecosystems driven by advances in immersive technologies and the growing engagement of global technology leaders with virtual environments. AI-powered educational platforms enable adaptive and personalized learning pathways by dynamically adjusting content, pace and instructional strategies to learners’ preferences, abilities and learning styles by improving engagement, retention and academic outcomes. Deep …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 116–123 Read article
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Optimized Utilization of Kota Stone Slurry Waste in Fly Ash–Based Geopolymer Mortar: A Taguchi-Driven Approach
Abstract: The large-scale generation of stone-processing wastes presents a critical sustainability challenge and an opportunity for value-added reuse in construction materials. This study develops a high-performance fly ash geopolymer mortar by partially replacing Class F fly ash with Kota stone slurry waste (KSSW) and optimizing the key mix parameters using a Taguchi design framework. Five governing factors—binder replacement level, NaOH molarity, sodium silicate–to–sodium hydroxide ratio (SS/SH), curing temperature, and alkaline solution-to-binder …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 426–445 Read article
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Sustainable Supply Chain Models for Polymer and Composite Manufacturing: A Data-Driven Assessment of Circular Material Flows
Abstract: Polymer and composite manufacturing is faced with growing demands in waste reduction, resource management, and making a shift towards circular economy principles. Although urgent, the adoption of data-driven tools in each step of a supply chain to facilitate efficient cyclic material flows is low. This paper designs and empirically analyzes sustainable supply chain design in polymer and composite production with a focus on digital traceability, closed-loop and material recovery, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 54–71 Read article
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A study on CMOS Operational Amplifier in Sensor Development
Abstract: CMOS operational amplifiers (op-amps) have emerged as pivotal components in modern sensor development, enabling the amplification and conditioning of weak signals with high precision and efficiency. Their inherent advantages low power consumption, compact size, and seamless integration with digital circuits make them ideal for advancing miniaturized, battery-powered sensor systems in fields ranging from biomedical devices to IoT networks. By delivering precision, power efficiency, and integration, CMOS op-amps are not just …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 1, 2026 · pp. 01–07 Read article
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A Study on AI-Enhanced Environmental Toxicology: Sensor-Driven Predictive Framework
Abstract: Traditional environmental toxicology relies heavily on labor-intensive, often retrospective, sampling and analysis, limiting our understanding of dynamic pollutant behaviors and their real-time impact on ecosystems and human health. This study presents a novel, integrated framework leveraging advanced sensor networks and artificial intelligence (AI) to revolutionize the monitoring, assessment, and predictive modeling of environmental contaminants. We deployed a sophisticated array of multi-parameter sensors (e.g., electrochemical, optical, biosensors for heavy metals, organic …
Published in Research and Reviews: A Journal of Toxicology · Vol. 15, Issue 3, 2025 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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Bridging the Theory-Practice Gap in Nursing Education in India: Exploring the Role of Simulation-Based Learning and AI-Driven Education
Abstract: The theory-practice gap in nursing education is a persistent issue that hinders the effective application of theoretical knowledge in clinical practice, ultimately affecting the clinical competence and decision-making skills of nursing graduates. This study explores the factors contributing to the theory-practice gap in nursing education in India and evaluates the potential of simulation-based learning (SBL) and artificial intelligence (AI)-driven education in bridging this gap. A mixed-methods approach was employed, involving …
Published in Journal of Nursing Science & Practice · Vol. 15, Issue 2, 2025 Read article
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Mechanical Strength Prediction of Nano-Silica Concrete Composites Using Machine Learning Techniques
Abstract: Nano-silica, or nanosilica, refers to silicon dioxide nanoparticles, which are a kind of silica (SiO₂) with diameters that often fall below 100 nanometers. This nanomaterial has attracted considerable attention because of its distinctive characteristics and diverse array of uses, notably in augmenting the performance of materials such as concrete. The integration of nanoparticles with cementitious matrix in nano-silica concrete offers a viable approach to improving the mechanical characteristics and longevity …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 963–973 Read article
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Machine Learning for Finding Materials for Membranes
Abstract: Traditionally, finding and improving membrane materials has depended on trial-and-error experiments, which can take a long time, cost a lot of money, and only cover a small area. Recent improvements in machine learning (ML) have the potential to change the way membrane materials are designed by making it possible to make predictions about performance, selectivity, and stability based on data. ML algorithms can find hidden links between the structure, composition, …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article
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A Reviewed Study On Cpu-Optimized Parameter-Efficient Fine- Tuning For Large Language Models To Increase Accuracy Using Lora
Abstract: The fast proliferation of Large Language Models (LLMs) has increased the need to optimize the process of fine-tuning but the existing workflows that require a GPU are still expensive, intensive, and unavailable to most researchers. This paper is driven by the desire to have a more cost-efficient and democratized version by examining a CPU-efficient implementation of Parameter-Efficient Fine-Tuning (PEFT) based on Low-Rank Adaptation (LoRA). The major purpose of the study …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Biopolymer–Cement Hybrid Panels from Recycled Paper Mill Reject: Experimental Characterisation and Machine Learning Optimization
Abstract: The increased rate of the accumulation of industrial residues in the developing countries is a major cause of concern for the environment. The current study brings forth the use of industrial residues in the form of the production of eco-friendly building materials as a sustainable approach to their valorization. The valorization of recycled paper mill reject, a cellulose-based biopolymeric industrial residue, is being addressed in this study as a reinforcement …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 67–90 Read article
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Graphene-Derived Reinforced Polymer Composites for Self-Healing and Durability Enhancement in Concrete Structures
Abstract: This study presents a matrix-centric polymer-composite repair binder: an epoxy–polyamide network reinforced with graphene derivatives (GO/rGO, 0.1–1.0 wt%). The polymer drives function via segmental mobility that closes microcracks, while 2D-filler topology densifies the interphase, improves load transfer, and enforces tortuous moisture pathways. Adhesion was high: pull-off (ASTM D4541) reached 13.5 MPa at 2.0 mm displacement; slant-shear (ASTM C882) reached 12.1 MPa at 2.8 mm, with greater deformation capacity (zero stress …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 77–91 Read article