The dielectric parameters of the tissue simulating liquids to assess the exposure from mobile phones were determined in a previous study considering the tissue distribution of the exposed regions of the head using a planar layered model and the transmission-line method. Currently, the standards for the compliance testing of wireless devices are being extended to more general exposure situations. This paper uses the same methods considering different locations of the body and the respective variations of the tissue structures and dimensions. The analysis of tissue compositions shows a significant increase of 2.2-4.7 dB of the peak spatial specific absorption rate (SAR) in comparison to the values assessed with current standard liquids. This increase is due to standing-wave effects in tissues with low water content. For a certain distance between the antenna and the body (approximately /spl lambda//3 for a /spl lambda//2 dipole), these standing-wave effects dominate the coupling mechanism, leading to a higher average SAR in layered tissue. The observations were validated using finite-difference time-domain simulations of an anatomical high-resolution human model. Nevertheless, a sound conservative exposure assessment applying phantoms filled with homogeneous standardized liquids is possible if a distance and frequency-dependent scaling factor is applied.

In this work, we present the arrangement of Fe₃O₄magnetic nanoparticles into 3D linear chains and its effect on magnetic particle hyperthermia efficiency. The alignment has been performed under a 40 mT magnetic field in an agarose gel matrix. Two different sizes of magnetite nanoparticles, 10 and 40 nm, have been examined, exhibiting room temperature superparamagnetic and ferromagnetic behavior, in terms of DC magnetic field, respectively. The chain formation is experimentally visualized by scanning electron microscopy images. A molecular Dynamics anisotropic diffusion model that outlines the role of intrinsic particle properties and inter-particle distances on dipolar interactions has been used to simulate the chain formation process. The anisotropic character of the aligned samples is also reflected to ferromagnetic resonance and static magnetometry measurements. Compared to the non-aligned samples, magnetically aligned ones present enhanced heating efficiency increasing specific loss power value by a factor of two. Dipolar interactions are responsible for the chain formation of controllable density and thickness inducing shape anisotropy, which in turn enhances magnetic particle hyperthermia efficiency.

We present unequally spaced linear array synthesis with sidelobe suppression under constraints to beamwidth and null control using a design technique based on a Comprehensive Learning Particle Swarm Optimizer (CLPSO). CLPSO utilizes a new learning strategy that achieves the goal to accelerate the convergence of the classical PSO. Numerical examples are compared to the existing array designs in the literature and to those found by the other evolutionary algorithms. The synthesis examples that are presented show that the CLPSO algorithm outperforms the common PSO algorithms and a real-coded genetic algorithm (GA).