Application of Simplex Method in the Radiotherapy Treatment

This work presents an application of the Simplex Method for solving an optimal planning problem for cancer treatment by radiotherapy. Linear Programming can aid the optimal planning for radiation therapy, where the concern is to apply a high enough radiation in the tumor while saving significantly healthy regions or critical organs.

Separability Analysis of Atlantic Forest Patches by Comparing Parametric and Non-Parametric Image Classification Algorithms

The aim of this work was to differentiate Atlantic Forest patches, as well as their spatial distribution, from other tree covers that compose the landscape, by comparing three methods of digital images classification, using techniques of geoprocessing and remote sensing. The study area was a sub-basin of the Iperó River, tributary of the Iperó-Mirim stream, Sarapuí River basin, in Araçoiaba da Serra, State of São Paulo, Brazil. This research has been developed on a Geographic Information System environment platform, using medium resolution images from Sentinel-2 Satellite. Three image classification algorithms: Maximum Likelihood Classification (MLC), Support Vector Machines (SVM) and Random Tree (RT) were applied to verify the separability of forest patches, forestry and other uses. The results were analyzed by means of a confusion matrix, accuracy and kappa index, thus showing that the three algorithms were able to successfully differentiate the targets, with the higher efficiency attributed to MLC and the lowest to RT. Overall, the three classifiers presented errors, but specifically for the forest patches, the highest accuracy was obtained from SVM.

Logarithmic Regge pole

This work presents the subtraction procedure and the Regge cut in the logarithmic Regge pole approach.The subtraction mechanism leads to the same asymptotic behavior as previously obtained in the non-subtraction case.The Regge cut,in contrast,introduces a clear role to the non-leading contributions for the asymptotic behavior of the total cross-section.From these results,some simple parameterization is introduced to fit the experimental data for the proton-proton and antiproton-proton total cross-section above some minimum value up to the cosmic-ray.The fit parameters obtained are used to present predictions for the ρ(s)-parameter as well as to the elastic slope B(s)at high energies.

Optical theorem,crossing property,and derivative dispersion relations:implications on the asymptotic behavior of σ_(tot)(s) and ρ(s)

In this paper,we present some results on the behavior of the total cross section and p-parameter at asymptotic energies in proton-proton(pp) and antiproton-proton(pp) collisions.Hence,we consider three of the main theoretical results in high energy physics:the crossing property,derivative dispersion relation,and optical theorem.The use of such machinery facilitates the derivation of analytic formulas for a wide set of the measured global scattering parameters and some important relations between them.The suggested parameterizations approximate the energy dependence for the total cross section and ρ-parameter for pp and pp with a statistically acceptable quality in the multi-TeV region.Additionally,the qualitative description is obtained for important interrelations,namely difference,sum,and ratio of the antiparticle-particle and particle-particle total cross sections.Despite the reduced number of experimental data for the total cross section and p-parameter at the TeV-scale,which complicates any prediction for the beginning of the asymptotic domain,the fitting procedures indicates that asymptotia occur in the energy range 25.5-130 TeV.Moreover,in the asymptotic regime,we obtain α_(P)=1.A detailed quantitative study of the energy behavior of the measured scattering parameters and their combinations in the ultra-high energy domain indicates that the scenario with the generalized formulation of the Pomeranchuk theorem is more favorable with respect to the original formulation of this theorem.