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Summary Background: Nanoparticles can be used in biomedical applications, such as contrast agents for magnetic resonance imaging, in tumor therapy or against cardiovascular diseases. Single-domain nanoparticles dissipate heat through susceptibility losses in two modes: Néel relaxation and Brownian relaxation. Results: Since a consistent theory for the Néel relaxation time that is applicable to systems of interacting nanoparticles has not yet been developed, we adapted the Coffey theoretical model for the Néel relaxation time in external magnetic fields in order to consider local dipolar magnetic fields. Then, we obtained the effective relaxation time. The effective relaxation time is further used for obtaining values of specific loss power (SLP) through linear response theory (LRT). A comparative analysis between our model and the discrete orientation model, more often used in literature, and a comparison with experimental data from literature have been carried out, in order to choose the optimal magnetic parameters of a nanoparticle system. Conclusion: In this way, we can study effects of the nanoparticle concentration on SLP in an acceptable range of frequencies and amplitudes of external magnetic fields for biomedical applications, especially for tumor therapy by magnetic hyperthermia.

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Abstract-Eddy Current Techniques (ECT) for Non-DestructiveTesting and Evaluation (NDT/NDE) of conducting materials is one of the most application-oriented field of research within electromagnetism. In this work, a novel approach is proposed in order to characterize defects on metallic plates in terms of their depth and shape, starting from a set of experimental measurements. The problem is solved by means of a hybrid classification system based on Computation with Words (CWs) and Fuzzy Entropy (FE). They extract information about the specimen under test from the measurements.Main advantages of proposed approach are the introduction of CWs as well as the usage of the FE based minimization module, in order to improve flaw characterization by a low computational complexity system.