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117 articles for “matching”
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Gene Expression Profiling in Autism Spectrum Disorder: A Microarray Analysis Using Gse42133
Abstract: Autism Spectrum Disorder (ASD) is a diverse neurodevelopmental disorder characterized by difficulties in social interaction, communication impairments, and restricted or repetitive patterns of behavior. Despite its increasing prevalence, the underlying molecular mechanisms remain poorly understood. Advances in transcriptomics offer opportunities to investigate the gene expression changes that may contribute to ASD pathophysiology. In this study, the microarray dataset GSE42133 was analyzed, which comprises gene expression profiles from peripheral blood samples …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 37–48 Read article
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Exploring the Intersection of AI Network Pharmacology and Ayurveda: Innovations in Traditional Medicine
Abstract: Integrative frameworks that integrate traditional medicine and modern computer research are increasingly important for advancing evidence-based, individualized healthcare. One interesting strategy is the combination of Ayurveda, network pharmacology, and artificial intelligence (AI). AI expands the capability by allowing for the quick analysis of biomedical big data, the identification of therapeutic trends, and the optimization of treatment plans. Ayurveda, with its long-standing emphasis on individualized care, holistic balance, and natural remedies, …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 3, 2025 · pp. 92–98 Read article
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Footstep Power Generation Using Piezoelectric Materials: A Renewable Approach for Smart Infrastructure
Abstract: The rapid depletion of fossil fuels and the increasing global demand for sustainable energy have necessitated the development of decentralized energy harvesting systems. This paper presents a comprehensive study on footstep-based power generation using piezoelectric materials as a viable renewable energy solution for smart infrastructure. The proposed system converts mechanical energy generated from human locomotion into electrical energy using optimized piezoelectric transducer arrays integrated beneath floor tiles. The study covers …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 Read article
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IoT-Based Automated Crop Protection System for Smart Farming
Abstract: The development of current technological advancements produces expanded capabilities for agricultural farming production alongside pest management techniques. The Automatic Crop Protection System requires an Arduino controller and Blynk IoT application for monitoring and managing essential environmental parameters including temperature along with humidity as well as soil moisture and pest behavior. Real-time environmental and soil data obtained by the suggested system's sensor array gets analyzed and controlled by an Arduino controller. …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 1–8 Read article
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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Intelligent Electromagnetic Synthesis: An AI-Driven IoT Framework for Adaptive Antenna Design in Missile Navigation
Abstract: The rapid evolution of hypersonic and long-range tactical missile systems necessitates antenna architecture capable of maintaining robust communication links under extreme thermal, mechanical, and signal-jamming environments. Traditional antenna design methodologies often relying on iterative simulation cycles and static optimization are increasingly insufficient for the real-time requirements of modern aerospace navigation. This paper proposes an AI-driven, IoT- integrated framework that facilitates autonomous antenna design and performance optimization. By deploying a distributed …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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RF Energy Harvesting Techniques for Wireless Sensor Networks
Abstract: In contemporary applications like environmental monitoring, healthcare systems, industrial automation, agriculture, military surveillance, and smart cities, Wireless Sensor Networks (WSNs) are crucial. However, the limited battery life of sensor nodes remains a major challenge because many sensor devices are deployed in remote or difficult-to-access locations. Frequent battery replacement or recharging increases maintenance cost, reduces network reliability, and limits long-term operation. In contemporary applications like environmental monitoring, healthcare systems, industrial automation, …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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Mass Spectrometry–Based Phosphoproteomic Markers to Predict Kinase Inhibitor Response in Solid Tumors
Abstract: Mass spectrometry-based phosphoproteomics has emerged as a powerful tool for predicting kinase inhibitor responses in solid tumors, offering direct functional insights into signaling pathways that surpass traditional genomic profiling by capturing dynamic kinase activities and adaptive resistance mechanisms. Technological breakthroughs, including data- independent acquisition (DIA), trapped ion mobility spectrometry (timsTOF), and efficient enrichment methods like TiO2 or IMAC, now enable comprehensive profiling of over 40,000 phosphorylation sites from limited clinical …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 Read article
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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High-Gain Microstrip Patch Antenna for Satellite and Radar Applications
Abstract: The growing demand for high-speed wireless communication, satellite connectivity, and advanced radar systems has increased the necessity for compact and high-performance antenna designs. This study presents the design and analysis of a high-gain microstrip patch antenna intended for satellite and radar applications operating in the microwave frequency range. The proposed antenna structure is developed using a low-loss dielectric substrate to enhance radiation efficiency, bandwidth, and gain characteristics while maintaining a …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 2, 2026 Read article
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Artificial Intelligence and Edge Computing in Oil and Gas: Applications, Architectures, and Operational Realities
Abstract: Artificial intelligence has arrived in oil and gas, and unlike some previous waves of digital enthusiasm in the sector, this one is sticking. Saudi Aramco analyses approximately 10 billion data point every day and reported USD 4 billion in technology-driven operational gains in 2024. ExxonMobil uses AI to increase shale well output by more than 5 percent. Shell has deployed machine learning across more than 10,000 assets using C3.ai to …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 01–06 Read article
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AI-Based Outfit Rating and Suggestion System
Abstract: The increasing demand for personalised fashion advice in the digital era has highlighted the need for intelligent, automated styling solutions. The AI-Based Outfit Rating and Suggestion System is a web- based platform that assists users in evaluating and improving their clothing choices through intelligent image analysis. Unlike conventional fashion applications that merely identify garment categories or suggest purchases, this system performs a holistic assessment of complete outfits by analysing colour …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 2, 2026 Read article
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An Empirical Analysis of Bluetooth Low Energy Reliability Challenges for Offline Messaging Applications
Abstract: In today's hyper-connected world, modern communication relies heavily on centralised internet infrastructure, making robust offline messaging solutions increasingly essential. A crucial vulnerability is revealed by network failures, natural disasters, and distant region deployments: communication breaks down when internet connectivity does. Due to its low power consumption and almost ubiquitous availability in contemporary smartphones, Bluetooth Low Energy (BLE) has become a promising candidate for offline, device-to-device communications. This study presents an …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 2, 2026 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
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Idempotent Semiring Path Algebras and Fuzzy Dominance Automata for Multi-State Communication Reliability
Abstract: A semiring-based theory is proposed for multi-state communication reliability with fuzzy dominance constraints. Links are weighted in the max-product semiring, while nodes carry dominance coefficients and operating states that modulate admissible transitions in a weighted automaton. The paper derives semiring matrix products, Kleene closures, fixed point equations, congestion-regularized path scores, and reliability inequalities. A fuzzy dominance automaton is introduced so that route selection depends not only on link reliability but …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 07–14 Read article
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Smile Perfection with Veneers: Current Concepts and Techniques
Abstract: Veneers represent one of the most remarkable developments in dentistry over the last 25 years. The breakthrough that porcelain could be bonded to composite materials and subsequently to the tooth surface has transformed aesthetic dental treatment. Veneers not only improve facial aesthetics but also enhance self-esteem, positively influence personal interactions, and can even play a role in professional advancement. These restorations offer excellent cosmetic outcomes while maintaining a significant portion …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 2, 2025 · pp. 12–18 Read article
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Genomic Selection for Grain Yield in Wheat Using Machine Learning on DArT Molecular Markers: A Comparative Evaluation Across Multi-Environment Trials
Abstract: Genomic selection (GS) predicts complex quantitative traits directly from genome-wide molecular markers, bypassing the need for extensive phenotypic trials and accelerating plant breeding cycles. We conducted a comparative evaluation of seven regression approaches — ridge regression (the machine-learning equivalent of RR-BLUP), Lasso, Elastic Net, Partial Least Squares, linear Support Vector Regression, Random Forest, and Gradient Boosting — for predicting grain yield from 1,279 Diversity Array Technology (DArT) molecular markers genotyped …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article