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Graphical abstract Hghlights • The HEPrB showed direct antibacterial activity. • The HEPrB showed no bacterial resistance modifying activity. • This negative effect must be due the antioxidant effect of phenolic compounds., Bacterial resistance is interfering with the action of antibiotics for clinical use in treating pathologies. The search for new substances capable of combating this resistance is necessary. An alternative to the search for these substances is in the extract of medicinal plants. Plathymenia reticulata, plant of the Fabaceae family, is a common tree species from the Brazilian cerrado, and is commonly used in areas of environmental degradation. This species is rich in phenolic compounds, such as flavonoids and tannins, compounds that are associated with various biological effects. A hydroethanolic extract from the bark of Plathymenia reticulata (HEPrB) was produced and then tests were carried out to verify the direct antibacterial activity, the modulatory effect of antibiotics for clinical use and their toxicity in Drosophila melanogaster flies. Through the analysis with UPLC, a wide variety of flavonoids contained in the HEPrB was observed. Direct antibacterial activity was observed for the standard strain of Staphylococcus aureus, however, the extract showed antagonistic activity or no significance in relation to the antibiotics tested in this study. As for toxicity, the HEPrB did not show significant damage in the proposed model. The results emphasize care when associating the consumption of teas with treatments with antibiotics for clinical use.

The computational treatment of detailed kinetic reaction mechanisms for combustion is expensive, especially in the case of biodiesel fuels. In this way, great efforts in the search of techniques for the development of reduced kinetic mechanisms have been observed. As Methyl Butanoate (MB, $$C_3H_7COOCH_3$$ ) is an essential model frequently used to represent the ester group of reactions in saturated methyl esters of large chain, this paper proposes a reduction strategy and uses it to obtain a reduced kinetic mechanism for the MB. The reduction strategy consists in the use of artificial intelligence to define the main chain and produce a skeletal mechanism, apply the traditional hypotheses of steady-state and partial equilibrium, and justify these assumptions through an asymptotic analysis. The main advantage of the strategy employed here is to reduce the work required to solve the system of chemical equations by two orders of magnitude for MB, since the number of reactions is decreased in the same order.

The processes of conversion of energy by combustion tend to increasingly consider the economic and environmental constraints, making it necessary to understand the interaction between combustion and turbulence. This work aims to develop a new mechanism for a jet diffusion flame of ethanol considering NO x formation. As a result, a reduced mechanism of 43 steps was achieved for combustion of ethanol by applying an Artificial Neural Network (ANN) for chemical kinetics. The results obtained agree satisfactorily with data found in the literature.

The hydrogen fuel is considered to be an ideal source of energy, because its complete combustion generates no pollutants, only water vapor. Therefore, the hydrogen has been suggested as a clean fuel. A detailed kinetic mechanism for the combustion of hydrogen that comprises eight species ( H 2 , O 2 , O , OH , H 2 O , H , HO 2 and H 2 O 2 ) and 20 elementary reactions, was reduced to two-step mechanism for nonpremixed flames involving four reactive species ( H 2 , O 2 , H , H 2 O ). We performed, for this mechanism, a numerical analysis of the equations, including the velocity, mixture fraction, mass fractions and temperature. To quantify the components of intermediary reactions, the mixture fraction is decomposed into three parts, each part directly related to the mass fraction of each species. The results compare favorably with data in the literature for a jet diffusion flame of 50/50% in volume of H 2 - N 2 . The main advantage of the strategy employed here is to decrease the work needed to solve the system of equations of the reactive flow.

Major efforts in the search for techniques for the development of reduced kinetic mechanisms for biodiesel have been observed, since these mechanisms may have thousands of species. This paper proposes a reduction strategy and presents the development of a reduced kinetic mechanism for piloted jet diffusion flame of methyl decanoate (MD). The strategy consists of applying the DRG, Directed Relation Graph, technique for initial reduction, and the use of Layerless Neural Network (LNN) to define the main chain and obtain a skeletal mechanism. Hence the hypotheses of steady-state and partial equilibrium are applied, and the assumptions are justified by an asymptotic analysis. The main advantage of the strategy is to reduce the work required to solve the system of chemical equations by at least two orders of magnitude for MD, since the number of species is decreased in the same order.

The hydrogen fuel seems to be a good candidate to replace the energy obtained from some fossil fuels. Therefore this work explains the process of obtaining a two-step reduced chemical kinetic mechanism for the hydrogen combustion. The development of a reduced mechanism consists in eliminating reactions that produce negligible influence on the combustion process. Moreover, for this mechanism, we obtain an analytical-numerical solution for a turbulent jet diffusion flame. To quantify the intermediate species, the mixture fraction is decomposed into three parts, each part directly related to the mass fraction of a species. The governing equations are discretized using the second order finite-difference approach and are integrated in time using the second order simplified three-step Runge-Kutta scheme. Obtained results compare favorably with data in the literature for a 50/50 % volume H2−N2 jet diffusion flame. The main advantage of this strategy is the decrease of the work needed to solve the system of governing equations, by one order of magnitude for the hydrogen.

In this chapter, some techniques are presented for obtaining reduced kinetic mechanisms as the Direct Relation Graph (DRG) the sensitivity analysis based on the eigenvalues and eigenvectors of the Jacobian matrix of the chemical system, and techniques such as Intrinsic Low Dimensional manifolds (ILDM), Reaction Diffusion manifolds (REDIM), and flamelet. For premixed flames, laminar burning velocity and the basic equations are obtained, and the length and time scales are discussed. In order to represent the flame front, the G equation is discussed. For diffusion flames, flamelet equations are presented with the introduction of the probability density function and the scalar dissipation rate. The Burke-Schumann solution and an analytical solution for jet diffusion flames and for plumes are also illustrated. Then, models are presented for reactive flows in porous media. Initially, we discuss the model of Darcy and appropriate equations for precipitation and dissociation of minerals without combustion. Finally, the equations are presented for combustion in porous media and a discussion about ion precipitation is made.

This chapter presents the basics of mixing in turbulent flow, starting with the notion of mixture fraction. This formulation can be extended to flows with various mixture fractions, when the number of reactions is small. Following is presented the basics of turbulent flows, such as turbulence scales, and the averages of Reynolds and Favre, which are useful for writing the reactive Navier equations. Notions of turbulence and models for the turbulent viscosity to be used with large-eddy simulation (LES) are presented. LES is the preferred technique, because there are no conditions for solving realistic Reynolds numbers, encountered in practice, using direct numerical simulation techniques.

First, the Cartesian and generalized coordinate systems and the coordinate transformation are introduced. We also discuss the method of virtual boundaries and the need to introduce a forcing term to represent the geometry. Next, we present the formulation for low Mach number, valid for most cases of reactive flows. Then the large-eddy simulations formulation is discussed as an improvement of Reynolds averaged Navier-Stokes (RANS) formulation, which is less expensive than direct numerical simulations (DNS) formulation. Subsequently, for a reactive flow model, the equations of momentum, energy, enthalpy, and chemical species are written as a general equation, which is approximated by methods of finite difference, finite volume, and finite element, to be integrated by Runge-Kutta methods. After that, approximations of order 3 and 4 are given, as well as some compact schemes of order of approximation 6. Then, we discuss some of the main methods used in the flow solution such as Gauss-Seidel, simplified Runge-Kutta, tridiagonal matrix algorithm (TDMA), Newton, strongly modified implicit procedure (MSI), and LU-SSOR, which is an LU decomposition with the introduction of dissipation. Then, we indicate some methods for solving stiff systems of equations, such as Newton’s method and Rosenbrock’s method, which can be seen as a combination of the methods of Newton and Runge-Kutta. After that, the principal boundary conditions, such as permeable and impermeable wall, symmetry and cut, far field and periodic are given, which are common in jet diffusion flames, and in reactive flows in porous media. Finally, some techniques for the acceleration of convergence as local time-stepping, residual smoothing, and the multigrid technique are introduced. Moreover, some numerical implementation details and the analysis of uncertainties for the solution of reactive flows is discussed.

This chapter presents the basic equations of fluid dynamics for reactive and nonreactive flows in Cartesian coordinates. The equations are based on the balance obtained for mass, momentum, and energy. It also presents the derivation of the equation for the mass fraction of the chemical species, and shows the terms to be added to the equations of momentum and energy. The reactive term is proportional to the species concentration and follows the Arrhenius kinetics. The set of equations is presented using Einstein notation, which allows simplification of writing the equations system, in order to facilitate the numerical implementation.

A bacterin from enterotoxigenic Escherichia coli (ETEC), containing fimbriae K99 and F41, was produced and its capacity to induce anti-K99 and anti-F41 antibodies in colostrum of vaccinated cows and in calf serum, and the persistence of these antibodies in neonates were determined. Three experiments were performed on two commercial farms. In all experiments animals were allotted randomly to the blocks, each block consisting of two pregnant females (a vaccinated one and a control one) and their respective calves. In experiment A (farm 1), comprised of 18 blocks, the animals received a vaccine dose 30 days before delivery. In experiment B (farm 1), consisted of 26 blocks, the animals received two vaccine doses (60 and 30 days before delivery). In experiment C (farm 2), consisted of 22 blocks, the animals received two vaccine doses (60 and 30 days before delivery). In experiments A and B pregnant cows and heifers were used and colostrum and serum from 24- to 36-hour-old calves were collected. In experiment C, pregnant embryo-recipient heifers were used and colostrum and sera from calves at 7, 14, 28 and 42 days of age were collected. Anti-K99 and anti-F41 antibodies were detected by ELISA using purified K99 and F41 fimbrial antigens. In experiment A no difference between treated and control groups was observed for the concentration of anti-K99 and anti-F41 antibodies in colostrum and calf serum. In experiment B a difference (P

O presente trabalho teve como objetivos elaborar um processamento de requeijão em barra com teor reduzido de gordura utilizando-se concentrado protéico de soro como substituto da gordura e avaliar suas características físico-químicas. O requeijão foi fabricado a partir da adição de três níveis (tratamentos) do concentrado, 0,2, 1,0 e 2,0%, e um com teor integral de gordura (controle). As amostras foram analisadas na primeira semana de fabricação para pH, acidez (% de ácido lático), teor de umidade (g/100 g), teor de gordura (g/100 g), teor de proteína (g/100 g) e teor de cinzas (g/100 g). Somente o teor de gordura apresentou diferença significativa entre o grupo-controle e os demais tratamentos (P