Accumulation and metabolism of uneven fatty acids present in single cell protein

Liquipron and Toprina, obtained by growing yeasts (Candida maltosa and Candida lipolytica) on n-hydrocarbons, were investigated to ascertain the biological significance and possible toxicological implications of their high content of uneven fatty acids (UFA). It was confirmed that the extent to which UFA accumulate in adipose tissue of rats fed the 2 products reflects only partially their UFA contents. The presence of UFA in rat tissues does not appear to alter intermediate metabolism. The capacity of liver mitochondria ot oxidize palmitic acid was similar in control and in Liquipron-treated rats. Palmitic acid and heptadecanoic acid did not compete for oxidation when mixed at concentrations which reflect their presence in the tissues of animals fed high levels of Liquipron.     

Nanoscale reinforcement of polypropylene composites with carbon nanotubes and clay: Dispersion state,electromagnetic and nanomechanical properties

In the present study, the bifiller system incorporating various amount of multiwalled carbon nanotubes (MWCNTs) and 3 wt% clay in polypropylene is investigated to obtain composites with multifunctional performance. The dispersion state of two nanofillers in the polypropylene matrix was characterized by applying TEM and Raman spectroscopy. Both composites demonstrate similar rheological behavior with a rheological percolation threshold of ?_p1 = 1.5 wt% for the monofiller (MWCNTs) and ?_p2 = 2 wt% for the bifiller systems (MWCNTs and 3% clay). The effect of two nanofillers on electromagnetic and nanomechanical properties was evaluated. Above rheological percolation both type composites show considerable electromagnetic shielding efficiency at small layer thickness due mostly to the addition of MWCNTs. The nanomechanical properties improvement is strongly dependent on the structure formed by MWCNTs in the polymer. The hardness and Young's modulus, measured by nanoindentation, is higher for the bifiller systems in comparison with the monofiller one above the rheological percolation threshold. This was attributed to the continuous network structure formed by interacted MWCNTs and infiltrated fine clay stacks. POLYM. ENG. SCI., 56:269–277, 2016. © 2015 Society of Plastics Engineers     

TINYCD: a (not so) deep learning model for change detection

Neural Computing and Applications - In this paper, we present a lightweight and effective change detection model, called TinyCD. This model has been designed to be faster and smaller than current...