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809 articles for “future potentials”
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Single-Cell Genomics and its Impact on Understanding Cellular Heterogeneity
Abstract: Single-cell genomics has transformed how we study the differences between individual cells, helping scientists uncover the detailed variety within tissues that traditional methods could not reveal. Traditional methods, such as RNA sequencing, average gene expression across many cells, thereby missing subtle yet important cellular variations. Single-cell technologies, such as single-cell RNA sequencing (scRNA-seq), DNA sequencing, and epigenomics, allow researchers to study individual cells in extraordinary detail like never before. This …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 1, 2025 · pp. 1–5 Read article
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Development of Solar Powered Automatic Cotton Picking Machine Using Movable Robotic Arm: A Review
Abstract: Cotton harvesting is a labor-intensive process, with traditional manual methods being inefficient and costly. Mechanized systems, such as spindle pickers and strippers, offer higher productivity but are expensive, bulky, and prone to crop damage. Robotic cotton-picking systems, integrated with artificial intelligence (AI) and computer vision, provide a promising alternative for selective and precise harvesting. This review examines advancements in robotic arm-based cotton picking, focusing on boll detection using AI, challenges …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 Read article
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Monoclonal antibodies in targeted cancer therapy advances, resistance mechanisms, and next-gen formats (Bispesifics, ADCs)
Abstract: Breast cancer is one of the leading causes of cancer-related morbidity and death worldwide, which emphasizes the need for more effective and focused treatment strategies. antibody-mediated drug delivery techniques. Specifically, antibody–drug conjugates (ADCs) have emerged as a potential approach that combines the specificity of monoclonal antibodies with the potent cytotoxicity of anticancer drugs. By selectively targeting tumor-associated antigens, ADCs enhance drug accumulation within cancer cells while minimizing systemic toxicity associated …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 2, 2026 Read article
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Navigating Polymer Processing: Advances, Challenges, and Future Horizons
Abstract: Polymer processing and composite manufacturing stand as crucial pillars in modern industry, facilitating the creation of materials tailored to specific requirements. This abstract delves into the multifaceted realm of techniques and methodologies governing these processes, essential for ensuring the delivery of materials endowed with desired properties and functionalities. A meticulous examination of extant literature forms the foundation, shedding light on the evolving landscape, challenges encountered, and promising avenues ahead. Traditional …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 179–192 Read article
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Commercialization of Smart Polymers in Advanced Composite Structures for Industrial Applications
Abstract: The commercialization of smart polymers in advanced composite structures represents a significant rise in material science, particularly for industrial applications. These smart polymers show unique properties such as self-healing, shape memory, & responsiveness to environmental disturbances, making them ideal for a wide range of applications. In this paper, the researcher explores the advancements in developing and applying smart polymers within composite structures, focusing on their potential. Revolutionize industries like atmosphere, …
Published in Journal of Polymer & Composites · Vol. 12, Issue 6, 2024 · pp. 70–81 Read article
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Screening of Pharmaceutically Significant Methioninase-Producing Fungi from the Satpura Range of Hoshangabad District and Its Large-Scale Production
Abstract: L-methioninase, an enzyme with notable anticancer properties, has emerged as a promising therapeutic agent due to its ability to selectively degrade methionine, a critical amino acid for the survival of methionine-dependent cancer cells. Methionine dependency, observed in many tumor cells, is a metabolic vulnerability that can be exploited for targeted cancer therapy. The Satpura Range in the Narmadapuram District, India, with its diverse microbial ecosystems, offers a rich reservoir for …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 2, 2025 · pp. 33–43 Read article
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Mathematical Modeling of Epidemics Using Stochastic Differential Equations: A Review
Abstract: The accurate modeling of infectious disease dynamics is crucial for predicting outbreaks and informing public health interventions. While deterministic models such as the SIR (Susceptible-Infected-Recovered) framework have traditionally been used to understand disease transmission, they often fail to account for the randomness inherent in real-world scenarios. Disease spread is influenced by numerous uncertain factors, including individual behavioral changes, environmental fluctuations, and imperfect data reporting. These uncertainties can significantly impact model …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 1–6 Read article
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AI Approaches in Gait and Posture Analysis: A Review
Abstract: This review synthesizes current research on the application of artificial intelligence (AI) in gait and posture analysis, focusing on methodologies, algorithms, and clinical applications. It examines the use of machine learning (ML) and deep learning (DL) techniques to extract relevant features from sensorderived data, offering objective, and automated assessments that surpass traditional methods. A systematic literature review was conducted, analyzing studies that utilized AI for gait and posture analysis with …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 1–3 Read article
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Photovoltaics and Thermal Solar Technologies: Innovations for Sustainable Heating, Cooling, and Energy Efficiency
Abstract: Developments in renewable energy technology, in particular photovoltaics (PV) and solar thermal systems, have been fueled by a rising demand for energy worldwide and the pressing need to slow down climate change. These technologies provide greener options for heating, cooling, and energy production by lowering dependency on fossil fuels and greenhouse gas emissions. This study examines developments in solar thermal and photovoltaic technologies, their uses in commercial, industrial, and residential …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 30–37 Read article
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Revolutionizing Form and Function: Exploring 4D Printing as a Novel Manufacturing Approach for Complex Generative Structures and Customized Formworks
Abstract: This research delves into the transformative potential of 4D printing manufacturing technology, focusing on its innovative application in fabricating intricate generative and computational structures for adaptable formwork in both individualized and mass-customized scenarios. Spanning the interdisciplinary realms of digital design, digital fabrication, and material science, the study comprehensively explores the integration of these diverse fields. Utilizing generative algorithms and parametric design tools, the research employs simulations to realize complex patterns …
Published in International Journal of Manufacturing and Production Engineering · Vol. 1, Issue 2, 2023 · pp. 41–50 Read article
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Reinforcement Learning in Real World Application: A Study on Robotics; Autonomous Vehicles and Industrial Automation
Abstract: This research paper investigates the practical application of reinforcement learning (RL) in three critical domains: robotics, autonomous vehicles, and industrial automation. The study delves into the implementation of RL algorithms to enhance decision-making, adaptability, and autonomy in these real-world scenarios. Through a comprehensive review of existing literature, methodologies, and case studies, the paper addresses the challenges faced and the successes achieved in deploying RL in each domain. The findings offer …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 1, Issue 3, 2023 · pp. 1–15 Read article
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Deep Learning -Based Dental Issue Detection
Abstract: Dentistry is vital for preserving oral health, a key component of overall wellness. Early identification of dental issues is crucial for effective treatment and avoiding further complications. Conventional approaches to diagnosing dental problems typically depend on physical examinations and visual assessments by skilled professionals, which can be both time-intensive and influenced by individual judgment.In recent years, the application of deep learning algorithms has demonstrated significant potential in automating and enhancing …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 1, 2025 · pp. 18–23 Read article
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Recycled Carbon Black Manufacturing and Its Commercialization
Abstract: Recycled Carbon Black (rCB) is emerged as a sustainable alternative to virgin carbon black in the manufacturing of tires, non-tyre rubber products, and various other industrial applications. The increase in demand for this environmentally friendly material, due to the growing issue of waste/scrap tyre management, which has driven the development and commercialization of rCB. This article explores the various processes involved in the production of recycled carbon black, including pyrolysis …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 2, 2025 · pp. 26–32 Read article
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Therapeutic Potential of Plant-Derived Phytochemicals in Targeting Receptor Pathways Related to Non-Enzymatic Glycation: A Meta-Analysis
Abstract: Background: Non-enzymatic glycation, where reducing sugars react with proteins, lipids, and nucleic acids, contributes to various pathological conditions, such as diabetic complications and cardiovascular diseases. This process is facilitated by the receptor for advanced glycation end-products (RAGE), which is pivotal in driving inflammation and causing tissue damage. Objective: This meta-analysis evaluates the effects of plant-derived phytochemicals on RAGE expression and associated signaling pathways, assessing their therapeutic potential in glycation-related diseases. …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 1, 2025 · pp. 60–73 Read article
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Role of Machine Learning Principles for Efficient Nuclear Fuel Management and Design
Abstract: The introduction of machine learning (ML) and evolutionary computation methods in addressing complex nuclear fuel management challenges has brought a significant positive change in the domain of nuclear fuel management. Key applications include fuel assembly design optimization, core loading pattern determination, burnup calculation acceleration, fuel performance prediction, and spent fuel characterization. The analysis reveals significant improvements in computational efficiency, prediction accuracy, and optimization capabilities when ML techniques are properly integrated …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 22–33 Read article
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Comparative Review of Innovations in Self-Compacting Concrete (SCC) Technologies
Abstract: Self-compacting concrete (SCC) is a revolutionary material in contemporary construction, with better workability and lower labor requirements without any sacrifice in strength or durability. The latest advances have been in terms of furthering its environmental and performance attributes by using different materials and methods. One of them is substituting ordinary Portland cement with high-volume fly ash and calcined calcium carbonate (BCC), cutting CO₂ emissions by as much as possible while …
Published in Journal of Construction Engineering, Technology & Management · Vol. 15, Issue 3, 2025 · pp. 99–103 Read article
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A Study on Innovations in Primary Containment Technology for Safer Nuclear Power
Abstract: Nuclear power is a powerful carbon-free energy source that balances enormous potential with widespread public fear. Fear of radioactive leakage, a catastrophic catastrophe that might have long-lasting effects on the environs and human health, is at the core of this anxiety. The future of nuclear energy depends on finding a solution to this issue, and at the heart of that debate is the idea of primary containment, a technological marvel …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 37–44 Read article
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Fuel Cell and Solar Powered Based Renewable Energy Power Generation for Electric Vehicle Charging Station
Abstract: With the recent surge in Electric Vehicles (EVs) adoption, there is an ongoing demand for durable, reliable and green charging infrastructure. Traditional EV charging stations depend on grid electricity (which is produced by fossil fuel power plants) in real time and fail to unleash the full potential of electric mobility. In this study, a hybrid renewable energy system composed of Solar Photovoltaic (PV) arrays and Hydrogen Fuel Cells (FCs) is …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 2, 2026 Read article
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Flaxseed-Based Drug Delivery Systems: Advancing Colon Cancer Treatment
Abstract: Flaxseed (Linum usitatissimum) has long been appreciated for its rich nutritional profile, including essential fatty acids (such as α-linolenic acid), plant fibers, and lignans. Recent research has focused on its potential as a novel drug delivery system (DDS) for the treatment of colon cancer. This review explores the bioactive constituents of flaxseed, their pharmacological activities, and innovative approaches to the use of flaxseed extracts in drug delivery for the treatment …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 1, 2025 · pp. 54–59 Read article
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TensorFlow: Architecture, Applications, and Future Challenges
Abstract: TensorFlow, an open-source machine learning platform created by Google, has revolutionized how artificial intelligence (AI) systems are built and implemented. Designed to support scalable and flexible model training across CPUs, GPUs, and TPUs, TensorFlow enables researchers and developers to construct advanced deep learning models with efficiency and precision. This study provides an in-depth examination of TensorFlow's architecture, including its use of dataflow graphs and tensor-based computation. We explore its adaptability …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 41–50 Read article