Generative adversarial reduced order modelling.

In this work, we present GAROM, a new approach for reduced order modeling (ROM) based on generative adversarial networks (GANs). GANs attempt to learn to generate data with the same statistics of the underlying distribution of a dataset, using two neural networks, namely discriminator and generator. While widely applied in many areas of deep learning, little research is done on their application for ROM, i.

Infant botulism during a one year period in San Luis, Argentina.

Five cases of infant botulism which occurred during the period from May 1995 to May 1996 in San Luis, Argentina, are reported. Infant botulism was confirmed in all patients by isolation of Clostridium botulinum type A from stool culture and by the toxin assay. Toxin was found in the serum of one of them.