Search
91 articles for “structural and functional networks”
-
Optimizing Solar System Efficiency: A Study on Varied Control Grid Configurations
Abstract: This scholarly investigation delves into the multifaceted domain of regulatory matrices within solar photovoltaic (PV) structures, with a paramount emphasis on their pivotal function in optimizing the generation and amalgamation of solar energy. In contrast to the preceding abstract, which accentuated the fundamental constituents of PV structures and their interaction with the electrical network, this scholarly work delves profoundly into the diverse strategies employed in solar configurations to amplify efficiency …
Published in Journal of Thermal Engineering and Applications · Vol. 10, Issue 2, 2023 · pp. 1–9 Read article
-
Artificial Intelligence in Cerebellum Activation
Abstract: Neuroscience plays a significant function during the progression of artificial intelligence. It provided inspiration for the development of human-like AI. There are two ways that neuroscience encourages us to develop AI systems. Neural networks that replicate human cognition and those that match the structure of the brain are the two objectives. Neural networks, which draw inspiration from the architecture of the human brain, are the engine behind contemporary artificial intelligence …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 14–26 Read article
-
In Silico Drug Design for Mycobacterium tuberculosis and Development of Host–Pathogen Interaction Network and Molecular Docking Procedures
Abstract: Objective: A leading cause of illness is the contagious disease tuberculosis (TB), this infection with Mycobacterium tuberculosis complex (MTBC) particularly M. tuberculosis and M. africanum, is what causes tuberculosis. Diverse receptor proteins (mycobacterial proteins) with various 3D structures and functions were evaluated to access the multi-domain antimycobacterial action of ligands. The specific receptor proteins PDB ID: 3PTY, PDB ID: 4OW8, PDB ID: 5KWA, and PDB ID: 3ZXR, were opted for …
Published in International Journal of Molecular Biotechnological Research · Vol. 1, Issue 1, 2023 · pp. 1–19 Read article
-
Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
-
Comprehensive In silico Analysis of Single Nucleotide Polymorphisms (SNPs) in Human BDNF Gene
Abstract: Since a number of single nucleotide polymorphisms (SNPs) are associated with the BDNF gene mutations involved in different diseases. Hence, it is important to find out the probable functional SNPs before planning a larger population study. So, to look out for the functional nsSNPs (non-synonymous single nucleotide polymorphisms) in BDNF gene, existing data present in the dbSNP database and different bioinformatics tools like SIFT, PolyPhen, nsSNPAnalyzer, F-SNP, I-mutant, Pymol were …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 8, Issue 3, 2018 · pp. 128–139 Read article
-
Synthesis and Characterization of pH-Sensitive Poly (N-isopropylacrylamide-co-acrylic Acid) Hydrogels for Controlled Release of Doxorubicin
Abstract: pH-responsive polymeric hydrogels have attracted significant attention as intelligent biomaterials for site-specific and controlled drug delivery in cancer therapy due to their ability to respond to the acidic tumor microenvironment. In the present study, poly (N-isopropylacrylamide-co-acrylic acid) [P(NIPAM-co-AAc)] hydrogels were synthesized via free radical copolymerization and systematically characterized to evaluate their suitability for controlled delivery of doxorubicin, a widely used chemotherapeutic agent. The copolymer hydrogels were prepared using N-isopropylacrylamide and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 449–458 Read article
-
Recombinant Proteins and Nested Gene Regulation: Nutrient Driven Immune Response and Disease Resistance in Livestock
Abstract: Livestock production systems are increasingly challenged by infectious diseases, metabolic disorders, and environmental stressors that reduce productivity and compromise animal health. Advances in molecular biology and animal nutrition now offer new opportunities to strengthen disease resistance through integrated strategies that combine recombinant protein technologies, gene regulatory mechanisms, and nutrient mediated immune modulation. This review examines how recombinant proteins and nested gene regulation interact to shape nutrient driven immune responses in …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 16, Issue 1, 2026 · pp. 84–97 Read article
-
Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 386–407 Read article
-
Spectral Intuitionistic Fuzzy Hypergraph Operators and Dominance Kernels for Resilient Discrete Network Design
Abstract: A new discrete-mathematical framework is developed for resilient network design on intuitionistic fuzzy hypergraphs, where uncertainty is explicitly represented through membership, non-membership, and hesitation degrees associated with both vertices and hyperedges. These three components are systematically integrated into an effective incidence operator that captures the underlying uncertain relationships within complex hypergraph structures. Based on this operator, both un-normalised and normalized Laplacian matrices are formulated to characterize the spectral properties and …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 41–48 Read article
-
Integration of 5G and Low Earth Orbit (LEO) Satellite Communication for Global Connectivity
Abstract: This integration revolutionizes global connectivity by merging 5G's urban capabilities with LEO's wilderness coverage. This research examines how LEO satellite constellations can complement terrestrial 5G networks to extend high-speed, low-latency connectivity to underserved regions including rural areas, oceans, and airspace. Recent breakthroughs in LEO satellite technology and successful demonstrations of 5G-satellite integration point to a rapidly evolving ecosystem with significant market growth potential. To fully realize the potential of advanced …
Published in Journal of Thermal Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 15–32 Read article
-
Physics-Informed Generative and Tensor-Based Framework for DNA Sequence Simulation and Genomic Structure Discovery
Abstract: In this paper, we explore the intersection of artificial intelligence (AI) and mathematical physics to propose advanced methods for DNA sequence generation and analysis. Specifically, we investigate how physics-informed Generative Adversarial Networks (GANs) and tensor network representations can be harnessed to restructure DNA for applications in genetic science. The proposed methodology offers a unique integration of concepts of thermodynamic modeling with innovative GAN architecture in order to allow the creation …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
-
Role of Nasya in Pakshaghata: An Evidence-Based Review Study on Its Anatomical Pathway and Therapeutic Action
Abstract: Introduction: Intranasal administration (Nasya), a time-honoured Ayurvedic procedure, offers a unique advantage in treating pathology of neurological and systemic diseases due to its targeted and non-invasive nature. Pakshaghata, a neurological disorder characterized by hemiplegia in ancient Ayurvedic literature, where it is classified as a Vatavyadhi. Methods: By going through all the available literatures and information, this review study explores the concept of Nasya in the context of Pakshaghata management, investigating …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 2, 2025 · pp. 1–8 Read article
-
Nutrition Induced Remodeling Dynamics of Cell Membranes: Implications for Performance, Health, and Welfare Issues in Food Animals
Abstract: Cell membranes represent dynamic structural and functional platforms that integrate nutritional signals with cellular metabolism, immune competence, and physiological adaptation in food animals. Beyond their classical role as selective barriers, membranes actively regulate nutrient transport, signal transduction, and bioenergetics through highly responsive lipid and protein networks. Dietary components, particularly fatty acids, vitamins, minerals, amino acids, and bioactive compounds, critically influence membrane composition, fluidity, and stability, thereby shaping cellular function and …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 25–37 Read article
-
A Comprehensive Review on Piezoelectric Composites for Energy Harvesting and Sensing
Abstract: The capacity of piezoelectric composites to transform mechanical energy into electrical energy and vice versa has drawn a lot of interest recently. This property makes them very appealing for use in energy harvesting and sensing applications. These materials combine the high piezoelectric performance of ceramics with the mechanical flexibility and processability of polymers or other matrices, enabling a wide range of practical uses in flexible electronics, wearable systems, and embedded …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 19–24 Read article
-
Deep Learning Approaches for Nanoplasmonics: Expanding Horizons
Abstract: Deep learning, a subfield of machine learning, has revolutionized various domains by providing powerful tools to process and analyze complex data. In the realm of nanoplasmonics, deep learning techniques have emerged as promising approaches to tackle the challenges associated with large-scaledata analysis, modeling, and optimization of plasmonic systems. This article presents an in-depth exploration of deep learning approaches applied to nanoplasmonics research, focusing on the advances, opportunities, and future directions …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 13, Issue 1, 2023 · pp. 30–38 Read article
-
LoRa and LoRaWAN in the IoT: Performance, Challenges, and Future Opportunities
Abstract: This paper provides a broad overview of both LoRa and LoRaWAN technologies in the context of Internet of Things (IoT). The market need for communication technology to be low-power and long-range continues to grow, and LoRa and LoRaWAN are emerging as viable options for enabling widespread IoT applications in a variety of applications. This review offers structured and comparative assessment of their functionality in different environments, such as urban, rural, …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 2, 2026 Read article
-
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
-
Reduction of Abusive Words on Social Network: A Probabilistic Approach
Abstract: We are presenting a structured resource for abusive slang words that are freely exchanged over the social media. The dynamism of these words indicates that today’s technological tools are insufficient to process and reduce such abusive slang words on the social platforms. Proposed work could help applications to better understand the current trending abusive slangs that are commonly being used by users. We have initially taken only six abusive slangs …
Published in E-Commerce for Future & Trends · Vol. 6, Issue 1, 2019 · pp. 31–36 Read article
-
The Impact of MEMS on the Internet of Things (IoT)
Abstract: Our daily lives, workdays, and connections with the external world are all being impacted by theInternet of Things (IoT). Micro Electro-Mechanical Systems (MEMS) are tiny, economical, andpretty accurate sensors that can measure a variety of physical variables, including temperature,pressure, humidity, acceleration, and more. They are a fundamental enabler of this technology. Inthis article, we examine the effects of MEMS on the IoT and the ways in which these incrediblysmall sensors …
Published in Trends in Mechanical Engineering & Technology · Vol. 12, Issue 3, 2022 · pp. 34–38 Read article
-
AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article