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In clinical treatments of a class of tumors, e.g. skin tumors, the drug uptake of tumor tissue is helped by means of a pulsed electric field, which permeabilizes the cell membranes. This technique, which is called electroporation, exploits the conductivity of the tissues: however, the tumor tissue could be characterized by inhomogeneous areas, eventually causing a non-uniform distribution of current. In this paper, the authors propose a field model to predict the effect of tissue inhomogeneity, which can affect the current density distribution. In particular, finite-element simulations, considering non-linear conductivity against field relationship, are developed. Measurements on a set of samples subject to controlled inhomogeneity make it possible to assess the numerical model in view of identifying the equivalent resistance between pairs of electrodes.

In this paper, an innovative approach for the fast estimation of the mutual inductance between transmitting and receiving coils for Dynamic Wireless Power Transfer Systems (DWPTSs) is implemented. To this end, a Convolutional Neural Network (CNN) is used; an image representing the geometry of two coils that are partially misaligned is the input of the CNN, while the output is the corresponding inductance value. Finite Element Analyses are used for the computation of the inductance values needed for CNN training. This way, thanks to a fast and accurate inductance estimated by the CNN, it is possible to properly manage the power converter devoted to charge the battery, avoiding the wind up of its controller when it attempts to transfer power in poor coupling conditions. [ABSTRACT FROM AUTHOR]

In recent years, superficial chest wall recurrence from breast cancer can be effectively treated by means of electrochemotherapy, with the majority of patients achieving response to treatment. Nevertheless, tumor spread along superficial lymphatic vessels makes this peculiar type of tumor recurrence prone to involve large skin areas and difficult to treat. In these cases, electroporation with standard, small size needle electrodes can be time-consuming and produce an inhomogeneous coverage of the target area, ultimately resulting in patient under treatment.

The text is an introduction to the selected papers from the HES-2023 conference, which focuses on the application of electromagnetic fields for materials processing. The conference was postponed by a year due to the pandemic and the war in Ukraine. The main developments in electroheat involve a multi-physics approach to modeling and simulation, with a focus on coupling different physical domains. The use of AI-based methods, such as digital twins and machine learning, in electrothermal systems is a current topic of research. The conference also covered topics such as induction heating, induction hardening, and inverse problems in induction heating. Overall, 52 papers were presented at the conference, and the 10 selected papers cover the main topics discussed. [Extracted from the article]