Fast kinetic simulator for relativistic matter.

Relativistic kinetic theory is ubiquitous to several fields of modern physics, finding application at large scales in systems in astrophysical contexts, all of the way down to subnuclear scales and into the realm of quark-gluon plasmas. This motivates the quest for powerful and efficient computational methods that are able to accurately study fluid dynamics in the relativistic regime as well as the transition to beyond hydrodynamics-in principle all of the way down to ballistic regimes. We present a family of relativistic lattice kinetic schemes for the efficient simulation of relativistic flows in both strongly (fluid) and weakly (rarefied gas) interacting regimes.

Probing bulk viscosity in relativistic flows.

We derive an analytical connection between kinetic relaxation rate and bulk viscosity of a relativistic fluid in spatial dimensions, all the way from the ultra-relativistic down to the near non-relativistic regime. Our derivation is based on both Chapman-Enskog asymptotic expansion and Grad's method of moments. We validate our theoretical results against a benchmark flow, providing further evidence of the correctness of the Chapman-Enskog approach; we define the range of validity of this approach and provide evidence of mounting departures at increasing Knudsen number.

Relativistic dissipation obeys Chapman-Enskog asymptotics: Analytical and numerical evidence as a basis for accurate kinetic simulations.

We present an analytical derivation of the transport coefficients of a relativistic gas in (2+1) dimensions for both Chapman-Enskog (CE) asymptotics and Grad's expansion methods. We further develop a systematic calibration method, connecting the relaxation time of relativistic kinetic theory to the transport parameters of the associated dissipative hydrodynamic equations. Comparison of our analytical results and numerical simulations shows that the CE method correctly captures dissipative effects, while Grad's method does not, in agreement with previous analyses performed in the (3+1)-dimensional case.

Antibiotic resistance genes and identification of staphylococci collected from the production chain of swine meat commodities.

Staphylococci harbouring antibiotic resistance (AR) genes may represent a hazard for human health and, as other resistant food-related bacteria, they contribute to the spread of AR. In this study, we isolated resistant staphylococci from an entire swine production chain and investigated the occurrence of 11 genes [aac(6')Ie-aph(2'')Ia, blaZ, mecA, vanA, vanB, ermA, ermB, ermC, tet(M), tet(O) and tet(K)] encoding resistance to some antibiotics largely used in clinical practice. The 66 resistant staphylococcal isolates were identified as Staphylococcus epidermidis (27 isolates), Staphylococcus aureus (12), Staphylococcus xylosus (12), Staphylococcus simulans (5), Staphylococcus pasteuri (4), Staphylococcus carnosus (3), Staphylococcus lentus (2) and Staphylococcus sciuri (1).

Contribution of enterococci to the spread of antibiotic resistance in the production chain of swine meat commodities.

Thirty-six samples, including fecal specimens, dry feedstuffs, raw and processed pork meat products, and dry fermented sausages, were collected from two production chains of swine meat commodities and analyzed for the presence of 11 antibiotic resistance (AR) genes. Specific PCR assays carried out on DNA extracted directly from the samples revealed a high incidence of the genes tet(K) (80.5%), ermB (66.