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IntroductionToday, the rapid acceleration of urbanization has made it necessary to reconsider the balance among energy consumption, environmental sustainability, and quality of life. Buildings, which account for a signif...

Microbial siderophores are low-molecular-weight compounds with a strong affinity for ferric (FSe3+) ions. They play a pivotal role in plant-microbial interactions by enhancing iron bioavailability to plants, primarily th...

Abstract This paper seeks to investigate the use of Natural Language Processing techniques in analyzing the Bhagavad Gita, a fundamental text in Hindu philosophy that has stood the test of time and centuries of interpret...

           This article explores the ethical and moral implications of scientific discovery in Mary Shelley’s Frankenstein (1818), focusing on the destructive potential of unregulated ambition. Through Victor...

The features of state sovereignty in the dimension of the information age and globalization are considered. The importance of state sovereignty for ensuring effective development and competitiveness of society is emphasi...

Water information systems (ISs) are essential for sustainable water management but are often constrained by fragmented, heterogeneous, and rapidly evolving data. Advances in generative artificial intelligence (GenAI), pa...

Abstract BackgroundMultimodal large language models (MLLMs) capable of integrating visual and textual information represent a promising advancement for clinical applications requiring image interpretation. Wo...

Abstract Amid rising employment challenges, entrepreneurship has emerged as a salient pathway for graduates, and higher education institutions increasingly seek to foster entrepreneurial capabilities that support economi...

Abstract Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems have significantly advanced data modelling capabilities and improved opportunities for extracting knowledge from vast and heterogeneo...

IntroductionReliable classification of lung nodules from computed tomography (CT) images remains a challenging problem due to variations in image intensity, noise, and unstable feature representations during deep network...