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344 articles for “Gene prediction”
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Microvita as a Fermi-Boson Hybrid Quantum Excitation: A Statistical Pathway Toward Unified Physics, Chemistry, and Biological Organization
Abstract: This article reformulates Microvita as a hybrid quantum excitation that interpolates continuously between fermionic and bosonic statistical behavior. A generalized operator algebra, a dynamical statistical order parameter, and a Lorentz-covariant field equation are used to frame Microvita as an effective unification scheme rather than a mere philosophical construct. The formalism predicts renormalization-group flow between infrared fermionic and ultraviolet bosonic limits, while numerical profiles suggest vacuum-energy smoothing and topological-defect suppression in …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 115–122 Read article
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Recent Progress in Near-Surface Mounted Fiber-Reinforced Polymer Strengthening Systems: Composite Materials, Adhesive Technologies, and Interfacial Bonding
Abstract: Fiber-reinforced polymer (FRP) composites have emerged as one of the most promising classes of advanced engineering materials for structural strengthening and rehabilitation owing to their high specific strength, excellent corrosion resistance, fatigue durability, and design flexibility. Among various strengthening approaches, near-surface mounted (NSM) systems have gained significant attention because they provide enhanced bond performance, improved protection against environmental exposure, and superior utilization of FRP reinforcement compared with conventional externally bonded …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Remote Monitoring Sensor Systems and Applications in Health Informatics: Fostering Shell Programming
Abstract: The fascination of sensor systems has been promising for health informatics as their direct initiative for real-time information by observing its accuracy that was required at the time for data collection, monitoring and analysis to improve patient well-being and health system administering. By integrating these systems with wearable devices, biomedical sensors, and other IoT-enabled technologies, patients can experience continuous health tracking, early disease detection, and remote patient monitoring. For example, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 Read article
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Computational Study of Sombor Index on Generalized Abid–Waheed Graphs for Polymer Modeling
Abstract: This study investigates the topological properties of generalized Abid Waheed graphs. Development of theoretical models in chemistry, reducing computational complexity while analysing large molecules or networks Abid Waheed graphs play a significant role. Motivated by these findings, the research was extended to encompass generalized Abid Waheed graphs, characterized by r cycles of order s. A notable similarity between Abid Waheed graphs and Jahangir graphs was observed. The potential applications of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 267–274 Read article
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An Efficient LoRa-Enabled Fault Detection Using Self-Powered IoT Device
Abstract: This study describes a revolutionary internet of things (IoT) solution for effective defect detection in a variety of applications. By utilizing an IoT device that generates energy from the surroundings, the suggested solution gets around the drawbacks of conventional battery-operated gadgets. The suggested approach makes use of a self-sustaining IoT gadget that can capture energy from the surroundings to get beyond the drawbacks of conventional battery-powered IoT devices. Longer functioning …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 1–13 Read article
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DFT/Data Guided Predictive Modelling of Absorption Maxima in the OLED Rubrene Derivatives
Abstract: This study investigates the optical properties of rubrene derivatives to develop an accurate predictive model for absorption maxima using computational chemistry and chemoinformatic techniques. We benchmarked various quantum chemical methods, identifying that the M06-2X/aug-cc-pVDZ method in dichloromethane (DCM) provided the strongest correlation with experimental data. Key molecular descriptors such as band gap, ionization potential, and electrophilicity index were calculated and analyzed using principal component analysis (PCA) to identify significant factors …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 41–56 Read article
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Strategic Integration of Machine Learning in Polymer Composite Development: A Framework for R&D Portfolio Management and Technological Adoption
Abstract: The progress of advanced polymer composites is slow, costly and unpredictable due to traditional methods of trial-and-error research. As materials informatics and data-driven modeling speed up the process of discovering technology, there exists a huge disconnect between computational predictions on one hand and strategic decision-making on the other in research and development (R&D). To solve this issue, this paper presents the Agile Materials-Intelligence (AMI) Framework, a systematic combined methodology that …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1272–2286 Read article
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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Fruit Adulteration Detection Utilizing Machine Learning Methods
Abstract: A device utilizing Internet of Things (IoT) technology was developed for the identification of fruit adulteration through machine learning methods, specifically targeting formalin content assessment. The identification of the fruits based on their extracted traits has been accomplished using a variety of machine-learning techniques. The formalin concentration can be detected as an estimate of the generated voltage of any fruit via an Arduino Uno board 3 and a volatile compound …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 32–45 Read article
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Seasonal Variation in the Weibull Parameters from In Situ Measurements and Model: A Case Study in the Bay of Bengal
Abstract: Seasonal variation of wind speed (U10) and its distribution are essential for the design of wind energy converters (WEC). In this study, year-round wind speed observations from a deepwater moored buoy at a location in the Bay of Bengal are used to assess the potential for wind power generation and are used to validate the ERA5 model. Model-U10 distribution is confined to low wind speeds with high occurrence in the …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 15, Issue 1, 2024 · pp. 30–40 Read article
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Nanomedicine in Combination with Artificial Intelligence (AI): Transforming Cancer Treatment
Abstract: The convergence of nanomedicine and artificial intelligence (AI) holds transformative potential for advancing cancer treatment, particularly in liver cancer. Nanomedicine enables the development of targeted drug delivery systems, enhanced imaging modalities, and precise therapeutic interventions, while AI facilitates data-driven decision-making, personalized treatment plans, and predictive analytics. This synergistic approach can significantly improve the diagnosis, treatment, and monitoring of liver cancer by optimizing the use of nanoparticle-based therapies. AI-powered algorithms can …
Published in Trends in Drug Delivery · Vol. 12, Issue 1, 2025 · pp. 27–30 Read article
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Density Functional Theory (DFT): Understanding and Quantifying Molecular Structure of 2-D Materials
Abstract: Density Functional Theory (DFT) has emerged as a cornerstone in computational chemistry and materials science, offering a powerful framework for predicting electronic structures and properties of atoms, molecules, and solids. By focusing on electron density rather than wave functions, DFT simplifies the many-body problem through approximations like the local density approximation (LDA) and generalized-gradient approximations (GGAs). The Hohenberg-Kohn theorems establish the theoretical foundation, proving that ground-state properties are uniquely determined …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 33–40 Read article
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Understanding Leukemogenesis: Challenges and Advancements in Diagnostic Approaches
Abstract: Leukaemia development, or leukemogenesis, is a multifactorial process driven by a complex interplay of environmental, genetic, and epigenetic factors. Despite substantial advancements in technology and medicine, which have enhanced our understanding of the contributing factors, early and accurate diagnosis remains a major challenge due to the overlapping clinical features shared by the various leukaemia subtypes. This study explores the molecular and cellular mechanisms underlying leukemogenesis, while also addressing the difficulties …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 11–22 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Abstract: Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance. This study proposes a Hybrid Quantum-Classical Reinforcement Learning (HQCRL) Enabled Thermal-Aware EDA Framework for next-generation energy- efficient VLSI systems. The proposed framework integrates quantum-inspired optimization techniques with classical reinforcement learning algorithms to address the challenges of placement, routing, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 2, 2026 Read article
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Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning
Abstract: The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Temperature dependence of Schmidt number of composite material based liquid lithium
Abstract: This work presents a simple formalism for Schmidt number and its temperature dependence for liquid lithium. It is explained that the temperature dependence of Schmidt number (Sc = η/ ρD) can be understood through dependence of topological-short-range-order (TSRO) parameter on temperature. Expression for Schmidt number has been deduced in terms of average potential energy US of superficial core, probability of diffusional displacement (P) and the TSRO parameter (x) . Calculations …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 206–212 Read article
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Implementation of Human Gesture Recognition Using CNN
Abstract: A gesture popularity system based entirely on convolutional neural networks (CNNs). Preprocessing techniques include segmentation, polygonal approximation, contour construction, morphological filters, and resource characteristic extraction. Various convolutional neural networks are employed for training and testing, with results compared to existing architectures and protocols. All generated measurements and convergence graphs produced at any point during education are examined and contested in order to verify the reliability of the approach offered. Our …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 2, 2024 · pp. 24–37 Read article
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Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning
Abstract: The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article
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Toward Intelligent Public Transport: Review of Smart Bus Stop Systems with Real-Time Location
Abstract: The increasing demand for efficient, reliable, and sustainable public transportation has driven the evolution of smart bus stop systems worldwide. Traditional bus stops often fail to meet modern commuter expectations, such as real-time service information, accessibility, and integration with smart city frameworks. This review paper provides a comprehensive overview of the technological advancements, design approaches, and global adoption of smart bus stops. Key enabling technologies, including GPS, IoT, wireless communication, …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 1, 2026 · pp. 1–12 Read article