scholarly journals Nonequilibrium polarity-induced chemotaxis: Emergent Galilean symmetry and exact scaling exponents

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Saeed Mahdisoltani ◽  
Riccardo Ben Alì Zinati ◽  
Charlie Duclut ◽  
Andrea Gambassi ◽  
Ramin Golestanian
Keyword(s):  
Scaling Exponents ◽  
Galilean Symmetry ◽  
Exact Scaling

The Metabolic Theory of Ecology

2017 ◽  
Author(s):  
Andrew Clarke
Keyword(s):  
Metabolic Rate ◽  
Resting Metabolic Rate ◽  
Effect Of Temperature ◽  
Thermal Ecology ◽  
Model Data ◽  
Metabolic Theory ◽  
Physical Explanation ◽  
Boltzmann Factor ◽  
Scaling Exponents ◽  
Metabolic Theory Of Ecology

The model of West, Brown & Enquist (WBE) is built on the assumption that the metabolic rate of cells is determined by the architecture of the vascular network that supplies them with oxygen and nutrients. For a fractal-like network, and assuming that evolution has minimised cardiovascular costs, the WBE model predicts that s=metabolism should scale with mass with an exponent, b, of 0.75 at infinite size, and ~ 0.8 at realistic larger sizes. Scaling exponents ~ 0.75 for standard or resting metabolic rate are observed widely, but far from universally, including in some invertebrates with cardiovascular systems very different from that assumed in the WBE model. Data for field metabolic rate in vertebrates typically exhibit b ~ 0.8, which matches the WBE prediction. Addition of a simple Boltzmann factor to capture the effects of body temperature on metabolic rate yields the central equation of the Metabolic Theory of Ecology (MTE). The MTE has become an important strand in ecology, and the WBE model is the most widely accepted physical explanation for the scaling of metabolic rate with body mass. Capturing the effect of temperature through a Boltzmann factor is a useful statistical description but too simple to qualify as a complete physical theory of thermal ecology.

scholarly journals Looking for a proxy of the ionospheric turbulence with Swarm data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Paola De Michelis ◽  
Giuseppe Consolini ◽  
Alessio Pignalberi ◽  
Roberta Tozzi ◽  
Igino Coco ◽  
...  
Keyword(s):  
Electron Density ◽  
Geomagnetic Activity ◽  
Density Fluctuations ◽  
Rate Of Change ◽  
Topside Ionosphere ◽  
Joint Probability Distribution ◽  
Activity Levels ◽  
Scaling Exponents ◽  
Electron Density Fluctuations ◽  
Scaling Features

AbstractThe present work focuses on the analysis of the scaling features of electron density fluctuations in the mid- and high-latitude topside ionosphere under different conditions of geomagnetic activity. The aim is to understand whether it is possible to identify a proxy that may provide information on the properties of electron density fluctuations and on the possible physical mechanisms at their origin, as for instance, turbulence phenomena. So, we selected about 4 years (April 2014–February 2018) of 1 Hz electron density measurements recorded on-board ESA Swarm A satellite. Using the Auroral Electrojet (AE) index, we identified two different geomagnetic conditions: quiet (AE < 50 nT) and active (AE > 300 nT). For both datasets, we evaluated the first- and second-order scaling exponents and an intermittency coefficient associated with the electron density fluctuations. Then, the joint probability distribution between each of these quantities and the rate of change of electron density index was also evaluated. We identified two families of plasma density fluctuations characterized by different mean values of both the scaling exponents and the considered ionospheric index, suggesting that different mechanisms (instabilities/turbulent processes) can be responsible for the observed scaling features. Furthermore, a clear different localization of the two families in the magnetic latitude—magnetic local time plane is found and its dependence on geomagnetic activity levels is analyzed. These results may well have a bearing about the capability of recognizing the turbulent character of irregularities using a typical ionospheric plasma irregularity index as a proxy.

Log-Compound-Poisson Distribution Model of Intermittency in Turbulence

1998 ◽  
Vol 53 (10-11) ◽  
pp. 828-832
Author(s):  
Feng Quing-Zeng
Keyword(s):  
Energy Dissipation ◽  
Poisson Distribution ◽  
Turbulent Energy ◽  
Compound Poisson Distribution ◽  
Distribution Model ◽  
Velocity Difference ◽  
Scaling Exponents ◽  
Compound Poisson ◽  
Developed Turbulence ◽  
Experimental Values

Abstract The log-compound-Poisson distribution for the breakdown coefficients of turbulent energy dissipation is proposed, and the scaling exponents for the velocity difference moments in fully developed turbulence are obtained, which agree well with experimental values up to measurable orders. The under-lying physics of this model is directly related to the burst phenomenon in turbulence, and a detailed discussion is given in the last section.

scholarly journals Extended power-law scaling of air permeabilities measured on a block of tuff

2012 ◽  
Vol 16 (1) ◽  
pp. 29-42 ◽  
Author(s):  
M. Siena ◽  
A. Guadagnini ◽  
M. Riva ◽  
S. P. Neuman
Keyword(s):  
Power Law ◽  
Structure Functions ◽  
Self Similarity ◽  
Scaling Exponents ◽  
Multi Scale ◽  
Sample Structure ◽  
Heavy Tailed ◽  
Non Gaussian ◽  
Nonlinear Fashion ◽  
Extended Power

Abstract. We use three methods to identify power-law scaling of multi-scale log air permeability data collected by Tidwell and Wilson on the faces of a laboratory-scale block of Topopah Spring tuff: method of moments (M), Extended Self-Similarity (ESS) and a generalized version thereof (G-ESS). All three methods focus on q-th-order sample structure functions of absolute increments. Most such functions exhibit power-law scaling at best over a limited midrange of experimental separation scales, or lags, which are sometimes difficult to identify unambiguously by means of M. ESS and G-ESS extend this range in a way that renders power-law scaling easier to characterize. Our analysis confirms the superiority of ESS and G-ESS over M in identifying the scaling exponents, ξ(q), of corresponding structure functions of orders q, suggesting further that ESS is more reliable than G-ESS. The exponents vary in a nonlinear fashion with q as is typical of real or apparent multifractals. Our estimates of the Hurst scaling coefficient increase with support scale, implying a reduction in roughness (anti-persistence) of the log permeability field with measurement volume. The finding by Tidwell and Wilson that log permeabilities associated with all tip sizes can be characterized by stationary variogram models, coupled with our findings that log permeability increments associated with the smallest tip size are approximately Gaussian and those associated with all tip sizes scale show nonlinear variations in ξ(q) with q, are consistent with a view of these data as a sample from a truncated version (tfBm) of self-affine fractional Brownian motion (fBm). Since in theory the scaling exponents, ξ(q), of tfBm vary linearly with q we conclude that nonlinear scaling in our case is not an indication of multifractality but an artifact of sampling from tfBm. This allows us to explain theoretically how power-law scaling of our data, as well as of non-Gaussian heavy-tailed signals subordinated to tfBm, are extended by ESS. It further allows us to identify the functional form and estimate all parameters of the corresponding tfBm based on sample structure functions of first and second orders.

scholarly journals Exact scaling solutions in normal and Brans–Dicke models of dark energy

2003 ◽  
Vol 20 (13) ◽  
pp. 2563-2578 ◽  
Author(s):  
Olga Arias ◽  
Tame Gonzalez ◽  
Yoelsy Leyva ◽  
Israel Quiros
Keyword(s):  
Dark Energy ◽  
Exact Scaling
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