scholarly journals Universal inverse power-law distribution for temperature and rainfall in the UK region

2014 ◽  
Vol 66 ◽  
pp. 138-150 ◽  
Author(s):  
A.M. Selvam
2013 ◽  
Vol 104 (11) ◽  
pp. 2540-2552 ◽  
Author(s):  
Bradley M. Palmer ◽  
Bertrand C.W. Tanner ◽  
Michael J. Toth ◽  
Mark S. Miller

Fractals ◽  
2009 ◽  
Vol 17 (03) ◽  
pp. 333-349 ◽  
Author(s):  
A. M. SELVAM

Dynamical systems in nature exhibit self-similar fractal fluctuations and the corresponding power spectra follow inverse power law form signifying long-range space-time correlations identified as self-organized criticality. The physics of self-organized criticality is not yet identified. The Gaussian probability distribution used widely for analysis and description of large data sets underestimates the probabilities of occurrence of extreme events such as stock market crashes, earthquakes, heavy rainfall, etc. The assumptions underlying the normal distribution such as fixed mean and standard deviation, independence of data, are not valid for real world fractal data sets exhibiting a scale-free power law distribution with fat tails. A general systems theory for fractals visualizes the emergence of successively larger scale fluctuations to result from the space-time integration of enclosed smaller scale fluctuations. The model predicts a universal inverse power law incorporating the golden mean for fractal fluctuations and for the corresponding power spectra, i.e., the variance spectrum represents the probabilities, a signature of quantum systems. Fractal fluctuations therefore exhibit quantum-like chaos. The model predicted inverse power law is very close to the Gaussian distribution for small-scale fluctuations, but exhibits a fat long tail for large-scale fluctuations. Extensive data sets of Dow Jones index, human DNA, Takifugu rubripes (Puffer fish) DNA are analyzed to show that the space/time data sets are close to the model predicted power law distribution.


2006 ◽  
Author(s):  
Gerardo Ramirez ◽  
Sonia Perez ◽  
John G. Holden

Optica ◽  
2015 ◽  
Vol 2 (10) ◽  
pp. 877 ◽  
Author(s):  
Amy L. Oldenburg ◽  
Xiao Yu ◽  
Thomas Gilliss ◽  
Oluwafemi Alabi ◽  
Russell M. Taylor ◽  
...  

2013 ◽  
Vol 20 (01) ◽  
pp. 1350002 ◽  
Author(s):  
F. Giraldi ◽  
F. Petruccione

The exact dynamics of a quantum damped harmonic oscillator coupled to a reservoir of boson modes has been formally described in terms of the coupling function, both in weak and strong coupling regime. In this scenario, we provide a further description of the exact dynamics through integral transforms. We focus on a special class of spectral densities, sub-ohmic at low frequencies, and including integrable divergencies referred to as photonic band gaps. The Drude form of the spectral densities is recovered as upper limit. Starting from special distributions of coherent states as external reservoir, the exact time evolution, described through Fox H-functions, shows long time inverse power law decays, departing from the exponential-like relaxations obtained for the Drude model. Different from the weak coupling regime, in the sub-ohmic condition, undamped oscillations plus inverse power law relaxations appear in the long time evolution of the observables position and momentum. Under the same condition, the number of excitations shows trapping of the population of the excited levels and oscillations enveloped in inverse power law relaxations. Similarly to the weak coupling regime, critical configurations give arbitrarily slow relaxations useful for the control of the dynamics. If compared to the value obtained in weak coupling condition, for strong couplings the critical frequency is enhanced by a factor 4.


2019 ◽  
Vol 109 (9) ◽  
pp. 1519-1532 ◽  
Author(s):  
K. F. Andersen ◽  
C. E. Buddenhagen ◽  
P. Rachkara ◽  
R. Gibson ◽  
S. Kalule ◽  
...  

Seed systems are critical for deployment of improved varieties but also can serve as major conduits for the spread of seedborne pathogens. As in many other epidemic systems, epidemic risk in seed systems often depends on the structure of networks of trade, social interactions, and landscape connectivity. In a case study, we evaluated the structure of an informal sweet potato seed system in the Gulu region of northern Uganda for its vulnerability to the spread of emerging epidemics and its utility for disseminating improved varieties. Seed transaction data were collected by surveying vine sellers weekly during the 2014 growing season. We combined data from these observed seed transactions with estimated dispersal risk based on village-to-village proximity to create a multilayer network or “supranetwork.” Both the inverse power law function and negative exponential function, common models for dispersal kernels, were evaluated in a sensitivity analysis/uncertainty quantification across a range of parameters chosen to represent spread based on proximity in the landscape. In a set of simulation experiments, we modeled the introduction of a novel pathogen and evaluated the influence of spread parameters on the selection of villages for surveillance and management. We found that the starting position in the network was critical for epidemic progress and final epidemic outcomes, largely driven by node out-degree. The efficacy of node centrality measures was evaluated for utility in identifying villages in the network to manage and limit disease spread. Node degree often performed as well as other, more complicated centrality measures for the networks where village-to-village spread was modeled by the inverse power law, whereas betweenness centrality was often more effective for negative exponential dispersal. This analysis framework can be applied to provide recommendations for a wide variety of seed systems.[Formula: see text] Copyright © 2019 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .


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