Eduardo Prieto - Academia.edu (original) (raw)
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Papers by Eduardo Prieto
Construction and Building Materials, 2018
Journal of Cleaner Production, 2018
Applied Clay Science, 2017
Construction and Building Materials, 2017
Glycobiology, 2018
Trypanosoma cruzi is a protozoan parasite that causes Chagas disease, a debilitating condition th... more Trypanosoma cruzi is a protozoan parasite that causes Chagas disease, a debilitating condition that affects over 10 million humans in the American continents. In addition to its traditional mode of human entry via the "kissing bug" in endemic areas, the infection can also be spread in non-endemic countries through blood transfusion, organ transplantation, eating food contaminated with the parasites, and from mother to fetus. Previous NMR-based studies established that the parasite expresses a variety of strain-specific and developmentally-regulated O-glycans that may contribute to virulence. In this report, we describe five synthetic O-glycan analytical standards and show their potential to enable a more facile analysis of native O-glycan isomers based on mass spectrometry.
Atmospheric Environment, 2012
Rain is one of the fundamental processes of the hydrologic cycle as it can be the source of wealt... more Rain is one of the fundamental processes of the hydrologic cycle as it can be the source of wealth or natural hazards. This experiment focuses in the relationship between rain occurrence and atmospheric pressure (Patm) and atmospheric water vapor content (PW), GPS estimated. The available nine years time series of each variable were analyzed. It allowed to state the existence of three rain patterns and monthly differences in the Patm-PW combinations. In spite of rain episodes take place only for some of the Patm-PW combinations, only these variables are unable to explain the rain occurrences because of not always they take place. This because a forecast sliding windows model with neural network was developed, to capture nonlinear relations that can not to be fully reflected by the lineal probabilistic ones based on the observed rains, Patm and PW series. This model stated a good correlation between the observed rains and the forecast, with a positive impact of the PW but negative of Patm. This model was able to predict the rain precipitation with a reasonable precision and reliable accuracy up to a 56 hours horizon.
Construction and Building Materials, 2018
Journal of Cleaner Production, 2018
Applied Clay Science, 2017
Construction and Building Materials, 2017
Glycobiology, 2018
Trypanosoma cruzi is a protozoan parasite that causes Chagas disease, a debilitating condition th... more Trypanosoma cruzi is a protozoan parasite that causes Chagas disease, a debilitating condition that affects over 10 million humans in the American continents. In addition to its traditional mode of human entry via the "kissing bug" in endemic areas, the infection can also be spread in non-endemic countries through blood transfusion, organ transplantation, eating food contaminated with the parasites, and from mother to fetus. Previous NMR-based studies established that the parasite expresses a variety of strain-specific and developmentally-regulated O-glycans that may contribute to virulence. In this report, we describe five synthetic O-glycan analytical standards and show their potential to enable a more facile analysis of native O-glycan isomers based on mass spectrometry.
Atmospheric Environment, 2012
Rain is one of the fundamental processes of the hydrologic cycle as it can be the source of wealt... more Rain is one of the fundamental processes of the hydrologic cycle as it can be the source of wealth or natural hazards. This experiment focuses in the relationship between rain occurrence and atmospheric pressure (Patm) and atmospheric water vapor content (PW), GPS estimated. The available nine years time series of each variable were analyzed. It allowed to state the existence of three rain patterns and monthly differences in the Patm-PW combinations. In spite of rain episodes take place only for some of the Patm-PW combinations, only these variables are unable to explain the rain occurrences because of not always they take place. This because a forecast sliding windows model with neural network was developed, to capture nonlinear relations that can not to be fully reflected by the lineal probabilistic ones based on the observed rains, Patm and PW series. This model stated a good correlation between the observed rains and the forecast, with a positive impact of the PW but negative of Patm. This model was able to predict the rain precipitation with a reasonable precision and reliable accuracy up to a 56 hours horizon.