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Analysis of an innovative sampling strategy based on k-means clustering algorithm for POD and POD-DEIM reduced order models of a 2-D reaction-diffusion system

Physics-Enhanced Digital Twin based solution to control process state in a Steel Manufacturing plant

Industrial Maintenance activities are currently sustaining the continuous, local and remote, monitoring of critical facilities by determining cumulative damage and, consequently, by enabling fault diagnosis. Applying data driven models is possible to correlate features, consequently, to predict downtime and to manage, direct and indirect, costs (relevant for large scale processes) of stoppages. In this context, the timely monitoring of the relevant features, “sustained” and “populated” by phy...

Sorafenib-Loaded PLGA Carriers for Enhanced Drug Delivery and Cellular Uptake in Liver Cancer Cells

Introduction: Currently, conventional treatments of hepatocellular carcinoma (HCC) are not selective enough for tumor tissue and lead to multidrug resistance and drug toxicity. Although sorafenib (SOR) is the standard first-line systemic therapy approved for the clinical treatment of HCC, its poor aqueous solubility and rapid clearance result in low absorption efficiency and severely limit its use for local treatment. Methods: Herein, we present the synthesis of biodegradable polymeric Poly (...

Ultrasound waves in tumors via needle irradiation for precise medicine

Grounded in the interdisciplinary crosstalk among physics and biological sciences, precision medicine-based diagnosis and treatment strategies have recently gained great attention for the actual applicability of new engineered approaches in many medical fields, particularly in oncology. Within this framework, the use of ultrasounds employed to attack cancer cells in tumors to induce possible mechanical damage at different scales has received growing attention from scholars and scientists worl...

On Exact Embedding Framework for Optimal Control of Markov Decision Processes

This article deals with the embedding framework of Markov decision processes (MDPs) with discrete state and action space to find optimal actions. The optimal control problem of MDPs can be efficiently tackled by restructuring the same into an equivalent linearly-solvable Markov decision processes (LMDPs) through the method called embedding. However, state costs under the embedding may not exactly match the original costs and even assume unrealistic values. In this work, we derive a constructi...

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Prodotti recenti

Analysis of an innovative sampling strategy based on k-means clustering algorithm for POD and POD-DEIM reduced order models of a 2-D reaction-diffusion system

Physics-Enhanced Digital Twin based solution to control process state in a Steel Manufacturing plant

Sorafenib-Loaded PLGA Carriers for Enhanced Drug Delivery and Cellular Uptake in Liver Cancer Cells

Ultrasound waves in tumors via needle irradiation for precise medicine

On Exact Embedding Framework for Optimal Control of Markov Decision Processes

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