Breaking Oil-in-water Emulsions Stabilized By Yeast.

Several biotechnological processes can show an undesirable formation of emulsions making difficult phase separation and product recovery. The breakup of oil-in-water emulsions stabilized by yeast was studied using different physical and chemical methods. These emulsions were composed by deionized water, hexadecane and commercial yeast (Saccharomyces cerevisiae). The stability of the emulsions was evaluated varying the yeast concentration from 7.47 to 22.11% (w/w) and the phases obtained after gravity separation were evaluated on chemical composition, droplet size distribution, rheological behavior and optical microscopy. The cream phase showed kinetic stability attributed to mechanisms as electrostatic repulsion between the droplets, a possible Pickering-type stabilization and the viscoelastic properties of the concentrated emulsion. Oil recovery from cream phase was performed using gravity separation, centrifugation, heating and addition of demulsifier agents (alcohols and magnetic nanoparticles). Long centrifugation time and high centrifugal forces (2h/150,000×g) were necessary to obtain a complete oil recovery. The heat treatment (60°C) was not enough to promote a satisfactory oil separation. Addition of alcohols followed by centrifugation enhanced oil recovery: butanol addition allowed almost complete phase separation of the emulsion while ethanol addition resulted in 84% of oil recovery. Implementation of this method, however, would require additional steps for solvent separation. Addition of charged magnetic nanoparticles was effective by interacting electrostatically with the interface, resulting in emulsion destabilization under a magnetic field. This method reached almost 96% of oil recovery and it was potentially advantageous since no additional steps might be necessary for further purifying the recovered oil.

Combined Analysis Of νμ Disappearance And νμ→νe Appearance In Minos Using Accelerator And Atmospheric Neutrinos.

We report on a new analysis of neutrino oscillations in MINOS using the complete set of accelerator and atmospheric data. The analysis combines the ν(μ) disappearance and ν(e) appearance data using the three-flavor formalism. We measure |Δm(32)(2)| = [2.28-2.46] × 10(-3) eV(2) (68% C.L.) and sin(2)θ(23) = 0.35-0.65 (90% C.L.) in the normal hierarchy, and |Δm(32)(2)| = [2.32-2.53] × 10(-3) eV(2) (68% C.L.) and sin(2)θ(23) = 0.34-0.67 (90% C.L.) in the inverted hierarchy. The data also constrain δ(CP), the θ(23} octant degeneracy and the mass hierarchy; we disfavor 36% (11%) of this three-parameter space at 68% (90%) C.L.

Extraction, purification and biochemical characterization of a peroxidase from Copaifera langsdorffii leaves

The aim of this work is to obtain, purify and characterize biochemically a peroxidase from Copaifera langsdorffii leaves (COP). COP was obtained by acetone precipitation followed by ion-exchange chromatography. Purification yielded 3.5% of peroxidase with the purification factor of 46.86. The COP optimum pH is 6.0 and the temperature is 35 ºC. COP was stable in the pH range of 4.5 to 9.3 and at temperatures below 50.0 ºC. The apparent Michaelis-Menten constants (Km) for guaiacol and H2O2 were 0.04 mM and 0.39 mM respectively. Enzyme turnover was 0.075 s-1 for guaiacol and 0.28 s-1 for hydrogen peroxide. Copaifera langsdorffii leaves showed to be a rich source of active peroxidase (COP) during the whole year. COP could replace HRP, the most used peroxidase, in analytical determinations and treatment of industrial effluents at low cost.

Wavelets And Adaptive Grids For The Discontinuous Galerkin Method

In this paper, space adaptivity is introduced to control the error in the numerical solution of hyperbolic systems of conservation laws. The reference numerical scheme is a new version of the discontinuous Galerkin method, which uses an implicit diffusive term in the direction of the streamlines, for stability purposes. The decision whether to refine or to unrefine the grid in a certain location is taken according to the magnitude of wavelet coefficients, which are indicators of local smoothness of the numerical solution. Numerical solutions of the nonlinear Euler equations illustrate the efficiency of the method. © Springer 2005.