We propose a derivation of the fluctuating lattice Boltzmann equation that is consistent with both equilibrium statistical mechanics and fluctuating hydrodynamics. The formalism is based on a generalized lattice-gas model, with each velocity direction occupied by many particles. We show that the most probable state of this model corresponds to the usual equilibrium distribution of the lattice Boltzmann equation. Thermal fluctuations about this equilibrium are controlled by the mean number of particles at a lattice site. Stochastic collision rules are described by a Monte Carlo process satisfying detailed balance. This allows for a straightforward derivation of discrete Langevin equations for the fluctuating modes. It is shown that all nonconserved modes should be thermalized, as first pointed out by Adhikari et al. ͓Europhys. Lett. 71, 473 ͑2005͔͒; any other choice violates the condition of detailed balance. A Chapman-Enskog analysis is used to derive the equations of fluctuating hydrodynamics on large length and time scales; the level of fluctuations is shown to be thermodynamically consistent with the equation of state of an isothermal, ideal gas. We believe this formalism will be useful in developing new algorithms for thermal and multiphase flows.

Sinorhizobium meliloti genome sequence determination has provided the basis for different approaches of functional genomics for this symbiotic nitrogen-fixing alpha-proteobacterium. One of these approaches is gene disruption with subsequent analysis of mutant phenotypes. This method is efficient for single genes; however, it is laborious and time-consuming if it is used on a large scale. Here, we used a signature-tagged transposon mutagenesis method that allowed analysis of the survival and competitiveness of many mutants in a single experiment. A novel set of signature tags characterized by similar melting temperatures and G؉C contents of the tag sequences was developed. The efficiencies of amplification of all tags were expected to be similar. Thus, no preselection of the tags was necessary to create a library of 412 signature-tagged transposons. To achieve high specificity of tag detection, each transposon was bar coded by two signature tags. In order to generate defined, nonredundant sets of signature-tagged S. meliloti mutants for subsequent experiments, 12,000 mutants were constructed, and insertion sites for more than 5,000 mutants were determined. One set consisting of 378 mutants was used in a validation experiment to identify mutants showing altered growth patterns.Sinorhizobium meliloti is a model organism for studies of plant-microbe interactions. This gram-negative soil bacterium can enter an endosymbiosis with alfalfa plants through the formation of nitrogen-fixing nodules. The availability of the 6.7-Mb S. meliloti genome sequence, which consists of one chromosome (3.65 Mb) and two megaplasmids, pSymA (1.36 Mb) and pSymB (1.68 Mb) (16), has enabled transcriptome (5, 32), proteome (14), and metabolome (6) studies. These approaches focus on the monitoring of RNA, protein, and metabolite levels. Moreover, a library of mobilizable plasmids carrying all open reading frames of this microorganism has been constructed (36). Another step toward a better functional understanding of the S. meliloti genome is the creation of large libraries of defined mutants by site-directed or random mutagenesis. Such mutant libraries can be used to study each mutant's phenotype under defined conditions. Usually, selection of mutants that can survive under certain conditions is simple and efficient and can be performed using a mixture of different mutants. However, selection of mutants that have an attenuated phenotype in test conditions is problematic, because all mutants have to be checked one by one. A microarray-based signature-tagged mutagenesis (STM) strategy (20; for reviews see references 4, 11, 19, 29, 34, and 38) can overcome this problem.Signature-tagged mutagenesis is based on a collection of mutants split into sets, in which each mutant is modified by one or more different signature tags. The tags are short DNA segments that are unique for each mutant in a set and can be amplified using invariant (for a review see reference 11) or specific (26) priming sites. Tagged mutants from the same set are pooled prior t...

We present a comparative study of two computer simulation methods to obtain static and dynamic properties of dilute polymer solutions. The first approach is a recently established hybrid algorithm based on dissipative coupling between molecular dynamics and lattice Boltzmann ͑LB͒, while the second is standard Brownian dynamics ͑BD͒ with fluctuating hydrodynamic interactions. Applying these methods to the same physical system ͑a single polymer chain in a good solvent in thermal equilibrium͒ allows us to draw a detailed and quantitative comparison in terms of both accuracy and efficiency. It is found that the static conformations of the LB model are distorted when the box length L is too small compared to the chain size. Furthermore, some dynamic properties of the LB model are subject to an L −1 finite-size effect, while the BD model directly reproduces the asymptotic L → ϱ behavior. Apart from these finite-size effects, it is also found that in order to obtain the correct dynamic properties for the LB simulations, it is crucial to properly thermalize all the kinetic modes. Only in this case, the results are in excellent agreement with each other, as expected. Moreover, Brownian dynamics is found to be much more efficient than lattice Boltzmann as long as the degree of polymerization is not excessively large.

We present mesoscopic simulations of the counterion-induced electro-osmotic flow in different electrostatic coupling regimes. Two simulation methods are compared, dissipative particle dynamics (DPD) and coupled lattice-Boltzmann/molecular dynamics (LB/MD). A general mapping scheme to match DPD to LB/MD is developed. For the weak coupling regime, analytic expressions for the flow profiles in the presence of partial-slip as well as no-slip boundary conditions are derived from the Poisson-Boltzmann and Stokes equations, which are in good agreement with the numerical results. The influence of electrofriction and partial slip on the flow profiles is discussed.

We present a validation study comparing results from a patient-specific lattice-Boltzmann simulation to transcranial Doppler (TCD) velocity measurements in four different planes of the middle cerebral artery (MCA). As part of the study, we compared simulations using a Newtonian and a Carreau-Yasuda rheology model. We also investigated the viability of using downscaled velocities to reduce the required resolution. Simulations with unscaled velocities predict the maximum flow velocity with an error of less than 9%, independent of the rheology model chosen. The accuracy of the simulation predictions worsens considerably when simulations are run at reduced velocity, as is for example the case when inflow velocities from healthy individuals are used on a vascular model of a stroke patient. Our results demonstrate the importance of using directly measured and patient-specific inflow velocities when simulating blood flow in MCAs. We conclude that localized TCD measurements together with predictive simulations can be used to obtain flow estimates with high fidelity over a larger region, and reduce the need for more invasive flow measurement procedures.