Summary: Inspired by biological systems, artificial neural networks (ANN) have demonstrated to be powerful tools to model non‐linear systems, such as high solid content latexes produced by emulsion polymerization which have a great importance in the polymeric industry, essentially for environmental reasons, since they usually have water as a continuous phase. The quality of the produced polymer is closely related to the structure of the polymeric chain. In order to propose technical and economically feasible alternatives to control a polymeric structure, this work is aimed to develop a new methodology based on ANN associated with calorimetry to predict the polymeric structure. The designed ANN presented excellent results when tested with process condition variations (such as temperature and reaction time) as well as when they were submitted to test concerning the variation on the proportion of monomers in the latex formulation. Hence, it was possible to conclude that ANN, associated to calorimetry, lead to an efficient method to predict the polymer composition in emulsion copolymerizations.
The induction of apoptosis is one of the main goals of the designed anti-cancer therapies. In recent years, increased attention has been paid to the physical factors such as magnetic fields and to the natural bioactive compounds and the possibilities using them in medicine. Hence, the aim of this study was to evaluate the anti-tumor effect of caffeic or chlorogenic acid in combination with a moderate-strength static magnetic field on C32 melanoma cells by assessing the effect of both factors on the apoptotic process. The apoptosis of the C32 cells was evaluated using a flow cytometry analysis. The expression of the apoptosis-associated genes was determined using the RT-qPCR technique. The caspase activity and the concentration of the oxidative damage markers were also measured. It was found that phenolic acids and a static magnetic field trigger the apoptosis of the C32 cells and also affect the expression of the genes encoding the apoptosis regulatory proteins. In conclusion, our study indicated that both of the phenolic acids and a static magnetic field can be used supportively in the treatment of melanoma and that caffeic acid is more pro-apoptotic than chlorogenic acid. 相似文献
The surface coverage analysis derived from two formal steady-state kinetic models is compared to values directly obtained
from steady-state isotopic transient analysis (SSITKA) for the selective catalytic reduction (SCR) of NO by CH4 over Co-ZSM-5 catalysts. It is shown that the most abundant reacting intermediates are NOx adspecies, though no clear differentiation between the various adspecies identified by DRIFT spectroscopy was achieved. Less
numerous carbon containing adspecies were identified and quantified in the reacting system, essentially as methoxy species.
Nitromethane-like intermediates remained undetectable due to a very rapid transformation into N2 and CO2. On the basis of these converging kinetic analyses related to each elementary step of the SCR process, a microkinetic model
can be derived, which allows describing transient operation, in view of a non steady-state application. 相似文献