Analysis of Velocity Fluctuation in Turbulence based on Generalized Statistics

The numerical experiments of turbulence conducted by Gotoh et al. are analyzed precisely with the help of the formulae for the scaling exponents of velocity structure function and for the probability density function (PDF) of velocity fluctuations. These formulae are derived by the present authors with the multifractal aspect based on the statistics that are constructed on the generalized measures of entropy, i.e., the extensive R\'{e}nyi's or the non-extensive Tsallis' entropy. It is revealed that there exist two scaling regions separated by a crossover length, i.e., a definite length approximately of the order of the Taylor microscale. It indicates that the multifractal distribution of singularities in velocity gradient in turbulent flow is robust enough to produce scaling behaviors even for the phenomena out side the inertial range.Comment: 10 Pages, 5 figure

Constitutive equations for granular flow with uniform mean shear and spin fields

Numerical simulations of two-dimensional granular flows under uniform shear and external body torque were performed in order to extract the constitutive equations for the system. The outcome of the numerical simulations is analyzed on the basis of the micropolar fluid model. Uniform mean shear field and mean spin field, which is not subordinate to the vorticity field, are realized in the simulations. The estimates of stresses based on kinetic theory by Lun [Lun, J. Fluid Mech., 1991, 233, 539] are in good agreement with the simulation results for a low area fraction $\nu=0.1$ but the agreement becomes weaker as the area fraction gets higher. However, the estimates in the kinetic theory can be fitted to the simulation results up to $\nu=0.7$ by renormalizing the coefficient of roughness. For a relatively dense granular flow ($\nu=0.8$), the simulation results are also compared with Kanatani's theory [Kanatani, Int. J. Eng. Sci., 1979, 17, 419]. It is found that the dissipation function and its decomposition into the constitutive equations in Kanatani's theory are not consistent with the simulation results.Comment: 22 pages, 10 figure

On observability of Renyi's entropy

Despite recent claims we argue that Renyi's entropy is an observable quantity. It is shown that, contrary to popular belief, the reported domain of instability for Renyi entropies has zero measure (Bhattacharyya measure). In addition, we show the instabilities can be easily emended by introducing a coarse graining into an actual measurement. We also clear up doubts regarding the observability of Renyi's entropy in (multi--)fractal systems and in systems with absolutely continuous PDF's.Comment: 18 pages, 1 EPS figure, REVTeX, minor changes, accepted to Phys. Rev.

Numerical simulation of river channel processes with bank erosion in steep curved channel

River morphodynamics and sediment transportRiver morphology and morphodynamic

Threshold and non-linear behavior of lasers of Λ\Lambda and V - configurations

Dynamic properties of closed three level laser systems are investigated. Two schemes of pumping - $\Lambda$ and V - are considered. It is shown that the non-linear behavior of the photon number as a function of pump both near and far above threshold is crucially different for these two configurations. In particular, it is found that in the high pump regime laser can turn off in a phase-transition-like manner in both $\Lambda$ and V schemes.Comment: 9 pages, 5 figure

Characterization of the binding of botulinum type B 16S toxin to human intestinal epithelial cells

Botulinum neurotoxin produced by Clostridium botulinum type B is a complex of 12S and 16S toxins. 12S toxin consists of a neurotoxin and a nontoxic non-HA (NTNH). The 16S toxin consists of a neurotoxin, an NTNH, and a hemagglutinin (HA). Food-borne botulism is caused by these complex toxins, which are ingested orally and absorbed from the digestive tract across the epithelial barrier lining the gut. Here we show that the type B 16S toxin, but not the 12S toxin or the neurotoxin, binds to the T84 human intestinal epithelial cell line. We also demonstrate that the HA moiety in the 16S toxin mediates the toxin binding to the cells. The carbohydrates containing a galactose moiety inhibited the binding of the 16S toxin to the T84 cells, and neuraminidase treatment of the cells increased the 16S toxin binding. The binding of the 16S toxin to the neuraminidase-treated cells was also inhibited by carbohydrates containing a galactose moiety. These results suggest that the type B 16S toxin binds to human intestinal epithelial cells via the galactose moiety in the carbohydrate chain on the cell surface

Acceleration and vortex filaments in turbulence

We report recent results from a high resolution numerical study of fluid particles transported by a fully developed turbulent flow. Single particle trajectories were followed for a time range spanning more than three decades, from less than a tenth of the Kolmogorov time-scale up to one large-eddy turnover time. We present some results concerning acceleration statistics and the statistics of trapping by vortex filaments.Comment: 10 pages, 5 figure

Joint spatiotemporal models to predict seabird densities at sea

Introduction: Seabirds are abundant, conspicuous members of marine ecosystems worldwide. Synthesis of distribution data compiled over time is required to address regional management issues and understand ecosystem change. Major challenges when estimating seabird densities at sea arise from variability in dispersion of the birds, sampling effort over time and space, and differences in bird detection rates associated with survey vessel type. Methods: Using a novel approach for modeling seabirds at sea, we applied joint dynamic species distribution models (JDSDM) with a vector-autoregressive spatiotemporal framework to survey data collected over nearly five decades and archived in the North Pacific Pelagic Seabird Database. We produced monthly gridded density predictions and abundance estimates for 8 species groups (77% of all birds observed) within Cook Inlet, Alaska. JDSDMs included habitat covariates to inform density predictions in unsampled areas and accounted for changes in observed densities due to differing survey methods and decadal-scale variation in ocean conditions. Results: The best fit model provided a high level of explanatory power (86% of deviance explained). Abundance estimates were reasonably precise, and consistent with limited historical studies. Modeled densities identified seasonal variability in abundance with peak numbers of all species groups in July or August. Seabirds were largely absent from the study region in either fall (e.g., murrelets) or spring (e.g., puffins) months, or both periods (shearwaters). Discussion: Our results indicated that pelagic shearwaters (Ardenna spp.) and tufted puffin (Fratercula cirrhata) have declined over the past four decades and these taxa warrant further investigation into underlying mechanisms explaining these trends. JDSDMs provide a useful tool to estimate seabird distribution and seasonal trends that will facilitate risk assessments and planning in areas affected by human activities such as oil and gas development, shipping, and offshore wind and renewable energy

Dynamical model and nonextensive statistical mechanics of a market index on large time windows

The shape and tails of partial distribution functions (PDF) for a financial signal, i.e. the S&P500 and the turbulent nature of the markets are linked through a model encompassing Tsallis nonextensive statistics and leading to evolution equations of the Langevin and Fokker-Planck type. A model originally proposed to describe the intermittent behavior of turbulent flows describes the behavior of normalized log-returns for such a financial market index, for small and large time windows, both for small and large log-returns. These turbulent market volatility (of normalized log-returns) distributions can be sufficiently well fitted with a $\chi^2$-distribution. The transition between the small time scale model of nonextensive, intermittent process and the large scale Gaussian extensive homogeneous fluctuation picture is found to be at $ca.$ a 200 day time lag. The intermittency exponent ($\kappa$) in the framework of the Kolmogorov log-normal model is found to be related to the scaling exponent of the PDF moments, -thereby giving weight to the model. The large value of $\kappa$ points to a large number of cascades in the turbulent process. The first Kramers-Moyal coefficient in the Fokker-Planck equation is almost equal to zero, indicating ''no restoring force''. A comparison is made between normalized log-returns and mere price increments.Comment: 40 pages, 14 figures; accepted for publication in Phys Rev