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The purpose of this paper is to determine the electric field and specific absorption rate (SAR) distribution within biological tissues in the vicinity of dental implants, exposed to the mobile phone radiation.

This research was performed for the frequency of 2.6 GHz, which corresponds to 4G mobile network. The adequate 3D realistic numerical models of the mobile phone user’s head, dental implants and actual smartphone model are created using packages based on the finite integral technique numerical method.

The obtained results yield to a conclusion that the presence of dental implants affects the increase in electric field intensity and SAR values within biological tissues in its vicinity.

The presented procedure is limited to the 4G mobile network frequency of 2.6 MHz. The study should be extended to other mobile network frequencies to be more general.

The criteria for selection of the materials used for dental implants production should be extended with the recommended material characteristics related to their influence on the electric field and SAR distribution, to keep their values in the limits prescribed by standards.

The obtained results provide the foundation for future research in mobile devices’ electromagnetic fields’ influence on human health.

The accurate determination of the electric field and SAR values within different biological tissues and organs in the vicinity of dental implants exposed to mobile phone electromagnetic radiation, demands highly realistic model of observed biological structures. For purposes of the current study, the procedure for modeling of highly nonhomogeneous structure with finite number of homogenous domains having known electromagnetic parameters is described in the paper. As a result, the 3D complex users’ head model formed of 16 homogeneous domains of different electromagnetic parameters is created.

The purpose of this paper is to determine the impact of human age on the distribution of electric field and absorbed energy that originates from a mobile phone.

This research was performed for frequencies of 900, 1800 and 2100 MHz, which are used in a mobile communication system. To obtain the most accurate results, 3 D realistic model of the child’s head has been created whereby the dimensions of this model correspond to the dimensions of a seven-year-old child. Distribution of the electric field and specific absorption rate (SAR) through the child’s head was obtained by numerical analysis based on the finite integration technique.

The results discover that amount of absorbed energy is greater in the surface layers of the child’s head model when the electromagnetic (EM) characteristics of tissues are adjusted for the child. This deviation corresponds to different EM characteristics of biological tissues and organs of an adult person compared to a child.

The study deals with penetrated electrical field and absorbed EM field energy. There is space for further studies of other EM field effects (e.g. thermal effects).

The analysis of obtained results leads to idea that mobile phones and devices aimed for children using should be modified to provide SAR values inside prescribed standards.

The obtained results are foundation for future research on influence of EM fields of mobile devices on human health.

The proposed procedure offers the model for accurate estimation and quality analysis of SAR and EM field distribution inside child head tissue.

The purpose of this paper is to estimate influence of the pillar concrete foundation approximated by a semiconducting semi‐sphere on the pillar grounding system.

Unknown current distributions and impedance of pillar grounding system, which consists of a ferro armature modelled as a single electrode inside concrete foundation, ring electrode and two earthing conductors, are determined in this paper. Concrete foundation is approximated by a semi‐spherical semiconducting inhomogeneity. The expressions for electric scalar potential are formed using the quasi‐stationary image theory, including a recently proposed Green's function for the point source in the presence of a semiconducting sphere. Based on the quasi‐stationary antenna model, unknown currents are determined solving the system of integral equations using the moment method and polynomial approximation for current distributions.

The influence of inhomogeneity is not negligible for real values of specific conductivity of the inhomogeneity domain. The same goes for earthing conductor influence, especially the one on electric scalar potential distribution on the ground surface.

Besides the analyzed system, the model is applicable for solving for example a grounding system in the vicinity of large holes in the ground (pond and small lake) filled with water, treated as semi‐sphere or near vertical container (silage and reservoir) having semi‐spherical basis with a lower one buried in the ground.

Obtained results give possibility to analyze influence of semiconducting ground inhomogenities, which can be treated as semi‐spherically shaped ones, on grounding system. It results in better accordance of projected and real grounding system's characteristics.

The incidence of prostate cancer is increasing from the past few decades. Various studies have tried to determine the survival of patients, but metastatic prostate cancer is still not extensively explored. The survival rate of metastatic prostate cancer is very less compared to the earlier stages. The study aims to investigate the survivability of metastatic prostate cancer based on the age group to which a patient belongs, and the difference between the significance of the attributes for different age groups.

Data of metastatic prostate cancer patients was collected from a cancer hospital in India. Two predictive models were built for the analysis-one for the complete dataset, and the other for separate age groups. Machine learning was applied to both the models and their accuracies were compared for the analysis. Also, information gain for each model has been evaluated to determine the significant predictors for each age group.

The ensemble approach gave the best results of 81.4% for the complete dataset, and thus was used for the age-specific models. The results concluded that the age-specific model had the direct average accuracy of 83.74% and weighted average accuracy of 79.9%, with the highest accuracy levels for age less than 60.

The study developed a model that predicts the survival of metastatic prostate cancer based on age. The study will be able to assist the clinicians in determining the best course of treatment for each patient based on ECOG, age and comorbidities.