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501 articles for “Data Insights”
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Comprehensive Analysis of MRSA Peptides Via Maldi
Abstract: The present study employed Matrix-Assisted Laser Desorption/Ionization Time-of-Flight mass spectrometry to analyze methicillin-resistant Staphylococcus aureus peptides, focusing on various parameters associated with mass-to-charge (m/z) values. Through systematic data collection and analysis, including time, intensity, signal-to-noise ratios, quality factors, resolutions, areas under the peaks, relative intensities, full widths at half maximum, Chi-squared values, and background peaks, comprehensive insights into the spectral characteristics of methicillin-resistant Staphylococcus aureus peptides were obtained. Methicillin-resistant Staphylococcus …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 98–101 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article
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Productivity Improvement Using Kaizen-Muda Elimination
Abstract: In today's fiercely competitive business environment, achieving operational excellence and sustainable growth is paramount for organizations across diverse industries. The Kaizen philosophy, rooted in Japanese principles, offers a powerful framework for driving continuous improvement by systematically identifying and eliminating waste, or "muda." This paper explores the concept of Kaizen and its application in eradicating muda, paving the way for enhanced productivity, cost reduction, and a competitive advantage. Kaizen, which translates …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 1, 2024 · pp. 1–6 Read article
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Renewable Solar Energy Prediction in India : 2025-2030
Abstract: As India endeavors to realize its objective of achieving 500 GW of renewable energy capacity by the year 2030, the precise forecasting of solar power generation is rendered increasingly essential. This scholarly article conducts a comprehensive review of the utilization of machine learning (ML) methodologies in the prediction of solar energy across diverse Indian states, underscoring their potential to address the complexities associated with the variability of solar irradiance. Conventional …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 3, 2024 · pp. 41–46 Read article
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REVIEW OF PHARMACOEPIGENETICS: BRIDGING EPIGENETICS AND PERSONALIZED MEDICINE
Abstract: Pharmacoepigenetics is an emerging field that explores how alterations in gene expression, independent of DNA sequence changes, influence individual responses to drugs. Unlike pharmacogenetics, which focuses primarily on genetic variation, pharmacoepigenetics integrates genetic, environmental, and lifestyle factors to explain interindividual differences in drug efficacy, toxicity, and resistance. Key epigenetic mechanisms including DNA methylation, histone modifications, non-coding RNAs, and RNA methylation play critical roles in regulating drug metabolism and therapeutic outcomes. …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 1, 2026 Read article
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Blockchain from the Cryptographic Perspective of Privacy and Anonymization for Sustainability
Abstract: This paper delves into the fascinating intersection of cryptography and blockchain technology. It explores the implementation of blockchain in cryptography, highlighting how cryptographic algorithms improve the security of blockchain systems. This paper looks at various issues such as why cryptographic methods in use with blockchain networks guarantee data security, confidentiality, and credibility. It also examines the relationship between consensus algorithms and cryptography, shedding light on how these elements work together …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 13–30 Read article
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STRUCTURAL–EPIGENOMIC ATLAS: CNV/SV- DRIVEN PROGNOSTIC REFINEMENT ACROSS CANCERS
Abstract: Structural genomic alterations, including copy number variations (CNVs) and structural variants (SVs), play a central role in cancer initiation and progression. These alterations extend beyond gene dosage effects and interact dynamically with epigenomic mechanisms such as DNA methylation, histone modifications, and three-dimensional chromatin organization. Recent pan-cancer studies have demonstrated that CNV burden and SV signatures reflect key oncogenic processes including chromothripsis, homologous recombination deficiency, enhancer hijacking, and extrachromosomal DNA (ecDNA) …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 Read article
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Blockchain Adoption in Indian Public Services: A Holistic Empirical Investigation
Abstract: The Indian public sector is pivotal in the country’s governance and public welfare. It is worth noting that there is a significant number of intermediaries involved in the execution of tasks that are compromising data transparency. Currently, the public sector banks lack standardization and validation as major obstacles in the deployment of blockchain technology. The research paper explores the scope and effectiveness of blockchain technology in India’s public sector through …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 48–57 Read article
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Quantum Mechanics: Revolutionizing Pharmaceutical Sciences
Abstract: Quantum physics and pharmacy have generally been regarded as distinct areas—one investigates the microlevel behavior of non-living matter while the other concentrates on intricate biological systems. Nevertheless, progress in life sciences has increasingly depended on molecular-level insights, whereas quantum physics has advanced beyond basic principles to impact real-world uses. This intersection provides new opportunities for, pharmacy. Quantum entanglement, which allows for instantaneous relationships between particles, can be utilized for secure …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 1, 2025 · pp. 72–77 Read article
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Deciphering Th-Related Gene Interactions in Chronic Spontaneous Urticaria: Bioinformatics Insights and Drug Affinity Exploration
Abstract: Objective: There has been a great deal of interest in how inflammatory dermatosis and The cell interact, but the etiopathogenesis of chronic spontaneous urticaria (CSU) is still inadequately comprehended. Through bioinformatics techniques, the purpose of this work is to elucdate the molecular mechanism underlying Th-related genes in CSU and seeks to find the highest affinity drug. Methods: The CSU RNA expression profiling dataset provided the basis for the investigation. The …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 2, Issue 1, 2024 · pp. 1–15 Read article
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Genetic Variability and Statistical Methods: Key Insights for Computational Genetics Research
Abstract: Genetic variability, defined as the differences in DNA sequences among individuals, serves as the foundation of evolutionary biology and plays a pivotal role in species’ adaptability, resilience, and overall survival. Advances in genomic technologies, particularly high-throughput sequencing, have enabled unprecedented exploration of genetic diversity, fostering the growth of computational genetics. This interdisciplinary field combines statistical methods and computational tools to analyze genetic data, identify patterns, and link phenotypes to genotypes. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 19–23 Read article
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A Thorough Examination of How Artificial Intelligence is Affecting the Transformation of Agriculture in India and Throughout the World
Abstract: By providing creative ways to increase crop yields, maximize resource usage, and advance sustainability, artificial intelligence (AI) is revolutionizing agriculture. AI technologies, such as machine learning, computer vision, and robotics, are being increasingly used in precision farming, crop monitoring, disease detection, and decision-making as the global agricultural sector faces pressing challenges like food security, population growth, and climate change. AI enables farmers to make data-driven decisions, optimize irrigation systems, monitor …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 39–45 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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Detection and Classification of Diabetic Retinopathy Using Deep Learning Techniques
Abstract: This project delves into the evaluation of three prominent deep learning architectures Basic CNN, ResNet, and DenseNet for their efficacy in detecting diabetic retinopathy from retinal images. Utilizing a diverse dataset, the study employs standard deep learning frameworks to train and validate each model. The focus extends to exploring the potential benefits of transfer learning on a limited dataset. Evaluation metrics like specificity, sensitivity, and accuracy are employed for a …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 64–69 Read article
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Machine Learning Pipelines: A Survey on Automation, Scalability, and Deployment Strategies
Abstract: Machine learning (ML) has become a critical enabler of intelligent applications across domains, requiring robust, efficient, and scalable deployment workflows. This review paper provides an in-depth overview of machine learning pipelines, emphasizing three key dimensions: automation, scalability, and deployment methodologies. It begins by exploring automation techniques that reduce manual effort in data ingestion, preprocessing, model selection, and hyperparameter tuning. Tools such as AutoML, TFX, and workflow orchestration platforms are examined …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
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A Comprehensive Analysis of Various Payment Gateways for Web-based Food Ordering
Abstract: The digital revolution has ushered in profound transformations across industries, and the online food sector stands at the forefront of this evolution. With consumers increasingly prioritizing convenience and accessibility, the online food industry has witnessed unprecedented growth. In this dynamic landscape, payment gateways have emerged as indispensable components, facilitating seamless transactions and driving operational efficiency for online food restaurant websites. This research article endeavors to conduct a comprehensive analysis of …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 2, 2024 · pp. 1–6 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Transforming Digital Health Card Healthcare in India: An Integrated IT Solution
Abstract: India's healthcare sector faces critical challenges, including fragmented medical records, limited access to quality care in rural areas, and inefficiencies in patient engagement and insurance processes. This study proposes an innovative IT-driven healthcare model integrating a digital health card, web application, and NFC-enabled mobile platform. The system aims to streamline medical record management, enable telemedicine consultations, and provide seamless prescription and insurance integration. Advanced digital capabilities ranging from AI-driven recommendations …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 11–15 Read article
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Emotions and Artificial Intelligence in Finance: Exploring the Relationship
Abstract: The integration of Artificial Intelligence (AI) into financial systems has profoundly transformed the industry, providing unprecedented efficiency, accuracy, and speed in decision-making processes. These technological advancements have streamlined operations, reduced human errors, and enabled more informed decision-making based on vast datasets analyzed in real-time. However, the role of emotions in finance remains a critical factor that cannot be ignored. Human emotions, such as fear, greed, and optimism, frequently drive market …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 1, 2025 · pp. 11–17 Read article
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MentaLLaMA: Advancing Mental Health Insights with Instruction-Finetuned Large Language Models
Abstract: The growing prevalence of mental health challenges in contemporary society has highlighted the urgent need for advanced, interpretable, and reliable artificial intelligence solutions that can support mental health assessment and intervention. In response to this need, this research introduces a novel collection of open-source, instruction-tuned large language models (LLMs) specifically designed to facilitate transparent and accurate mental health evaluations. Leveraging a newly developed dataset, which integrates multiple tasks and diverse …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 08–15 Read article