The consistent physic-mathematical model of propagation of an electromagnetic wave in a heterogeneous medium is constructed using the generalized wave equation and the Dirichlet theorem. Twelve conditions at the inter...The consistent physic-mathematical model of propagation of an electromagnetic wave in a heterogeneous medium is constructed using the generalized wave equation and the Dirichlet theorem. Twelve conditions at the interfaces of adjacent media are obtained and justified without using a surface charge and surface current in explicit form. The conditions are fulfilled automatically in each section of counting schemes for calculations. A consistent physicomathematical model of interaction of nonstationary electric and thermal fields in a layered medium with allowance or mass transfer is constructed. The model is based on the methods of thermodynamics and on the equations of an electromagnetic field and is formulated without explicit separation of the charge carriers and the charge of an electric double layer. The influence of a slowly moving medium on the electromagnetic wave propagation is considered. The calculation results show the absence of the influence of the medium’s motion on the phase shift of waves, which is consistent with experimental data.展开更多
In this paper,we use machine learning techniques to form a cancer cell model that displays the growth and promotion of synaptic and electrical signals.Here,such a technique can be applied directly to the spiking neura...In this paper,we use machine learning techniques to form a cancer cell model that displays the growth and promotion of synaptic and electrical signals.Here,such a technique can be applied directly to the spiking neural network of cancer cell synapses.The results show that machine learning techniques for the spiked network of cancer cell synapses have the powerful function of neuron models and potential supervisors for different implementations.The changes in the neural activity of tumor microenvironment caused by synaptic and electrical signals are described.It can be used to cancer cells and tumor training processes of neural networks to reproduce complex spatiotemporal dynamics and to mechanize the association of excitatory synaptic structures which are between tumors and neurons in the brain with complex human health behaviors.展开更多
文摘The consistent physic-mathematical model of propagation of an electromagnetic wave in a heterogeneous medium is constructed using the generalized wave equation and the Dirichlet theorem. Twelve conditions at the interfaces of adjacent media are obtained and justified without using a surface charge and surface current in explicit form. The conditions are fulfilled automatically in each section of counting schemes for calculations. A consistent physicomathematical model of interaction of nonstationary electric and thermal fields in a layered medium with allowance or mass transfer is constructed. The model is based on the methods of thermodynamics and on the equations of an electromagnetic field and is formulated without explicit separation of the charge carriers and the charge of an electric double layer. The influence of a slowly moving medium on the electromagnetic wave propagation is considered. The calculation results show the absence of the influence of the medium’s motion on the phase shift of waves, which is consistent with experimental data.
基金Project supported by the National Natural Science Foundation of China(Nos.11772046 and 81870345)。
文摘In this paper,we use machine learning techniques to form a cancer cell model that displays the growth and promotion of synaptic and electrical signals.Here,such a technique can be applied directly to the spiking neural network of cancer cell synapses.The results show that machine learning techniques for the spiked network of cancer cell synapses have the powerful function of neuron models and potential supervisors for different implementations.The changes in the neural activity of tumor microenvironment caused by synaptic and electrical signals are described.It can be used to cancer cells and tumor training processes of neural networks to reproduce complex spatiotemporal dynamics and to mechanize the association of excitatory synaptic structures which are between tumors and neurons in the brain with complex human health behaviors.
