When the Keller-Segel equation is treated in a semiclassical scenario of electrodynamics involving Quantum Mechanics measurements, it is possible to implement the formalism of input-output in a nature manner without ...

The goal of this paper is the presentation of the elementary procedures that normally are done in nonrelativistic Quantum Mechanics in terms of the principles of Machine Learning. In essence, this paper discusses Mitchell's ...

One of the most prominent techniques to search for new resonances and masses of elementary and composed particles is called the Dalitz’s plot [1][2]. The technique is used on the decays of up to three bodies. In this manner, ...

The processes of angiogenesis have among their initial phases the processes such as the vascular endothelial growth (VEG) in order to guarantee the consistent sprouting and splitting of new blood vessels whose main purpose ...

In a prospective scenario of nanomedicine, an engineered cargo of nanoparticles would be crucial to alleviate diseases that might to require of a precise doses of biochemical compounds in situ. In this paper, the technique ...

It is well-known that Nanomedicine will use all those available techniques of Nanotechnology to alleviate and surpass critic scenarios of diseases by the which current Medicine might be limited. In this paper, we explore ...

Because bitcoins processes depend on Internet transactions, one can argue that the dynamics of flux and volume of bitcoins might be subject to stochastic instead of a pure determinism event. By knowing that Quantum Mechanics ...

This paper presents a theoretical approach of a prospective scheme inside Nanomedicine known as Targeted Drug Delivery (TDD) based entirely on Classical Electrodynamics. Under the assumption that nanoparticles can be ...

The field of Machine Learning through the technique of artificial neural network is used to determine in a straightforward manner the quantized energies of a particle in an infinite well. To accomplish this, unphysical ...

A computational methodology based at Machine Learning in order to identify quantum effects at Dirac-Lorentz electrodynamics, is proposed. Essentially, the present contribution is based in an algorithm that employs the ...