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Digital Twins (DT) are transforming the Industrial Internet of Things (IIoT) by providing virtual replicas of physical assets, enabling enhanced predictive analytics and data-driven decision-making. However, as Industry 5.0 integrates DT with generative AI technologies via APIs and tokens, security risks increase. Outdated modeling tools, coupled with vulnerabilities in resource-constrained environments, such as limited computational […]

The aim of this work is the data generation of aged mechanical properties following the Arrhenius equation and large deformation theory for a transversely isotropic bio-based polyurethane foam, and the application of this dataset in the training process of different deep neural network architectures to evaluate their capacity to predict the full stress–strain behavior of […]

In industrial finance, portfolio selection has emerged as a critical challenge that has received considerable attention over the past few decades. The standard approach to this problem is the Markowitz mean–variance model, which seeks to balance two inherently conflicting objectives: maximizing returns and minimizing risk. This study investigates portfolio optimization under realistic constraints, including cardinality, […]