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Streptococcus dysgalactiae subspecies equisimilis (SDSE) is a β-hemolytic Streptococcus that possesses genetic and clinical similarities to Streptococcus pyogenes. It is
increasingly recognized as the etiological microorganism of invasive diseases.
We report a case of a 74-year-old male who was admitted to this hospital with
lower back and neck pain and infected with leg ulcer. The diagnosis of spondylodiscitis C2-C3 and L1-L3 caused by Streptococcus dysgalactiae subsp. equisimilis was made. The present case
demonstrates the risk of older patients of developing invasive disease upon
skin infection with Streptococcus
dysgalactiae subsp. equisimilis, even when risk factors are absent or well controlled (as was diabetes mellitus
in this case), suggesting that the pathogenic potential of SDSE should not be
A scrutiny of the contributions of key mathematicians and scientists
shows that there has been much controversy (throughout the development of
mathematics and science) concerning the use of mathematics and the nature of
mathematics too. In this work, we try to show that arithmetical operations of approximation lead to
the existence of a numerical uncertainty, which is quantic, path dependent and
also dependent on the number system used, with mathematical and physical implications.
When we explore the algebraic equations for the fine structure constant, the
conditions exposed in this work generate paradoxical physical conditions, where
the solution to the paradox may be in the fact that the fine-structure constant
is calculated through different ways in order to obtain the same value, but
there is no relationship between the fundamental physical processes which
underlie the calculations, since we are merely dealing with algebraic
relations, despite the expressions having the same physical dimensions.
Artificial Neural Network (ANN) equalizers have been successfully
applied to mitigate Inter symbolic Interference (ISI) due to distortions introduced
by linear or nonlinear communication channels. The ANN architecture is chosen
according to the type of ISI produced by fixed, fast or slow fading channels. In
this work, we propose a combination of two techniques in order to minimize ISI
yield by fast fading channels, i.e.,
pulse shape filtering and ANN equalizer. Levenberg-Marquardt algorithm is used
to update the synaptic weights of an ANN comprise only by two recurrent
perceptrons. The proposed system outperformed more complex structures such as
those based on Kalman filtering approach.