Our objective was to study the effect of dorzolamide on corneal hydration in an 18-week controlled experiment using ultrasonic pachymetry. Twenty-eight male rabbits were divided randomly into four groups. The 7 rabbits in each group received eye drops containing either 2% (w/v) dorzolamide or placebo in their right eye, or in their left eye. The 2% dorzolamide rabbits were treated every 8 h. Fellow eyes are defined as eyes which did not receive either dorzolamide or placebo. The study was blind for both the person who applied the drug and the one who performed the pachymetry. The effect of treatments is reported on the basis of the percentage of pachymetric variation compared to the measurement made before drug application. There was no significant difference (P = 0.061) in pachymetric variation between dorzolamide (-4.42 ± 11.71%) and placebo (2.48 ± 9.63%). However, there was a significant difference (P = 0.0034) in pachymetric variation between the dorzolamide fellow eyes (-7.56 ± 10.50%) and the placebo (-4.42 ± 11.71%). In conclusion, dorzolamide did not increase the corneal thickness in rabbits.
In this chapter we discuss about the use of Paraconsistent Artificial Neural Network on computer pattern recognition. Computer pattern recognition is one of the most important Artificial Intelligence tools present in numerous knowledge areas with applications in several themes, including character recognition. Our focus is the investigation of an automated computational process able to recognize numeric characters furnishing a technical basis to recognize digital images and documents. The methodology employed for the task is based on Paraconsistent Artificial Neural Networks for being a tool with the ability to work with imprecise, inconsistent and paracomplete data without trivialization.
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