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27 articles for “Vector engineering”
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Advancing Gene Therapy: Next-Generation Viral Vector Engineering for Precision, Safety, and Scalability
Abstract: Gene therapy has emerged as a paradigm-shifting modality for the treatment of genetic disorders, malignancies, and rare diseases through the delivery of therapeutic nucleic acids aimed at correcting or modulating dysfunctional gene expression. Among the various delivery systems, viral vectors including adeno-associated viruses (AAVs), lentiviruses, adenoviruses, retroviruses, and herpes simplex viruses have proven indispensable owing to their high transduction efficiencies and adaptability. This review offers a comprehensive assessment of viral …
Published in International Journal of Virus Studies · Vol. 2, Issue 2, 2025 · pp. 37–55 Read article
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The Power of Genetic Engineering in Revolutionizing Vaccines
Abstract: Genetic engineering techniques, including recombinant subunit, viral vector, and nucleic acid vaccines have transformed the landscape of vaccine development. These novel approaches offer precise antigen design, enhanced safety profiles, and rapid adaptability to emerging pathogens. Key advantages include improved efficacy through targeted immune responses, increased safety due to the absence of live pathogens, and the ability to modify vaccines to address new variants or diseases quickly. Notable success stories, such …
Published in International Journal of Vaccines · Vol. 2, Issue 1, 2025 · pp. 18–27 Read article
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Machine Learning-Based Quantification of Polymer Structure Property Relationships for Predictive Material Design
Abstract: Polymer structures exhibit complex, hierarchical arrangements that strongly influence macroscopic properties, yet consistent quantification remains challenging due to nonlinear interactions and limited unified modeling strategies. Existing approaches inadequately capture generalized structure–property mappings across diverse polymer systems. This research aims to establish a machine learning-based quantification model for polymer structure–property relationships to support predictive material design. A Polymer Structure Property Dataset of 5,000 polymer samples includes structural descriptors and experimentally measured …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 737–754 Read article
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Webpage Extraction and Retrieval Chatbot
Abstract: Web scraping is a fundamental technique for automating data extraction in big data applications. While multiple implementations exist, few leverage Python’s Beautiful Soup library for efficient and structured data retrieval. This project aims to develop a web scraper and retrieval system that extracts relevant information from web pages, stores it in a vector database (Milvus), and enables intelligent querying using semantic search and generative AI. The system is designed to …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 1–7 Read article
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A review on Design of Gene Therapy and Its Potential for Craniofacial Regeneration
Abstract: One of the most talked-about topics of the 21st century is gene therapy, which holds the promise of treating many diseases. Current gene therapy research explores a wide range of potential treatments, such as enhancing the body’s immune response to tumors, promoting the formation of new blood vessels in the heart to mitigate heart attacks, and preventing HIV replication in AIDS patients. Gene therapy involves the introduction, alteration, or replacement …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 6–12 Read article
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Log Identification and Monitoring System Using Generative AI
Abstract: In contemporary software ecosystems, application and infrastructure logs play a vital role in ensuring system reliability, performance optimization, fault diagnosis, and security compliance. As applications become increasingly distributed and cloud native, the volume, velocity, and variety of generated log data have grown dramatically. This rapid expansion makes traditional manual log inspection inefficient, error-prone, and largely impractical. To address these challenges, this paper proposes an artificial intelligence (AI) driven log monitoring …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 08–16 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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Kinematic Relations of Particle Motion using Polar Cylindrical Coordinates System: Applications in Robotics and AI
Abstract: This paper explores the motion of a particle in space using the cylindrical polar coordinate system. It presents the physics of particle motion by defining spatial positions in three-dimensional polar coordinates and examining the particle’s kinematics—namely its position, velocity, and acceleration—in vector form. These quantities are mathematically expressed as functions of time, accounting for the changing coordinates in radial, angular, and vertical directions. This coordinate system proves especially useful for …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 1, 2025 · pp. 12–16 Read article
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Advancements in Insect Science: Agricultural, Health, and Biotechnological Applications for Sustainability
Abstract: Insect research is very important for solving problems in agriculture, health, industry, and protecting the environment. This article talks about the many uses of entomology and how new study on insects helps with pest control, pollination, disease vector control, and the creation of bioinspired technologies. There is a lot of talk about integrated pest management (IPM) tactics, using insects in forensic investigations, and the new sector of producing insect- based …
Published in International Journal of Insects · Vol. 2, Issue 2, 2025 · pp. 7–14 Read article
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Aerodynamic Optimization of UAV Wings Using Machine Learning
Abstract: Unmanned Aerial Vehicles (UAVs) are increasingly deployed across defense, transportation, agriculture, and environmental monitoring, demanding improved aerodynamic efficiency to enhance endurance, stability, and payload capacity. Traditional aerodynamic optimization approaches, relying on computational fluid dynamics (CFD) simulations and wind tunnel experiments, are often time-consuming and computationally expensive. This study proposes a machine learning (ML)-driven framework for the aerodynamic optimization of UAV wing geometries, aiming to significantly reduce design cycles while improving …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 1–7 Read article
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Evaluation of composite material based on different phases of Face recognition System
Abstract: Composite materials can indeed play a crucial role in various phases of a face recognition system, offering advantages such as lightweight construction, durability, and tailored mechanical properties. Let's explore how composite materials can be utilized in different phases of a face recognition system. A composite material based different phases of Face recognitions System is software that recognizes or verifies a person based on a digital image or a frame from …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 195–204 Read article
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Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning
Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Implementation of the Tridiagonal Matrix Algorithm (TDMA) in C: A Practical Approach
Abstract: This paper presents a practical implementation of the tridiagonal matrix algorithm (TDMA), also known as the Thomas algorithm, using the C programming language. The TDMA is a commonly used algorithm for solving systems of linear equations where the coefficient matrix is tridiagonal. The paper draws a detailed step-by-step process of the algorithm’s development, from forward elimination to backward substitution, with a focus on minimizing computational difficulty compared to standard Gaussian …
Published in Recent Trends in Programming languages · Vol. 11, Issue 3, 2024 · pp. 36–43 Read article
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A Comprehensive Analysis of Classification Methods for Churn Prediction in Financial Services
Abstract: Persistent issues that affect long-term revenue in the banking sector include excessive client attrition. Customary churn models depend on measures related to customer satisfaction, which often result in low predictive accuracy due to their subjective nature. This study proposes an effective early warning model to address customer churn in financial services. Data is preprocessed through cleaning, one-hot encoding, Z-score normalization, and Min-max scaling. To handle class imbalance, the SMOTE algorithm …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 47–61 Read article
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Detection of Stator and Rotor Winding Faults in Induction Motor using Park’s Vector Approach
Abstract: The Induction Motors in every rotating machine’s heart and it’s a very important component in a much. Almost 90 percent of the Induction Motor use in industry as a prime mover. So Induction Motor is necessary to Condition Monitoring for Economic Running Cost. Condition Based Monitoring of Induction Motor has become an important and difficult task for Engineers and Researchers mainly in Industrial applications. Several Condition Monitoring Methods (Technique) including …
Published in Journal of Control & Instrumentation Read article
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Identifying and Implementing a Machine Learning Model Suitable for Processing Visually Evoked Potential
Abstract: A Brain-Computer Interface (BCI) is a system that translates brain activity patterns into computer commands, bypassing physical movement. Electroencephalography (EEG) is commonly used to acquire signals in BCI research. Visual evoked potentials (VEPs) are brain responses in the visual cortex to visual stimuli. Recent studies show that exposing individuals to flickering at a consistent frequency generates EEG signals synchronized with the stimulation. Efficient extraction of VEP signals begins with preprocessing …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Predicting Student Placement Readiness: A Machine Learning Approach Using Coding Activities and Multi-Dimensional Performance Indicators
Abstract: In the modern information-driven academic world, identifying student employability and placement preparedness has predicted. be made a part and parcel of academic planning and career. development. This study provides a machine learning-based. structure to evaluate and forecast student placement pre-paredness by combining various performance aspects-academic achieve- ment, coding activity, aptitude and behavioral engage-ment metrics. Multi-source was gathered and preprocessed in the study. student information, such as student records (CGPA, attendance), …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 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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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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Machine Learning Framework for Optimizing Polymer–Metal Oxide Composites as Charge Selective Layers in Perovskite Solar Cells
Abstract: To achieve high-performance and stability of perovskite solar cells (PSCs), it was important to incorporate innovative interfacial materials to tune the balanced charge extraction, low recombination, and enhanced operational lifespan. On this note, polymer composites with metal oxides have been proposed as promising candidates as charge selective layers (CSLs), whereby they present a rare combination of tunable energy levels, improved film forming abilities, and better interface engineering capabilities. In this …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1073–1098 Read article