323 research outputs found
Percolation Threshold, Fisher Exponent, and Shortest Path Exponent for 4 and 5 Dimensions
We develop a method of constructing percolation clusters that allows us to
build very large clusters using very little computer memory by limiting the
maximum number of sites for which we maintain state information to a number of
the order of the number of sites in the largest chemical shell of the cluster
being created. The memory required to grow a cluster of mass s is of the order
of bytes where ranges from 0.4 for 2-dimensional lattices
to 0.5 for 6- (or higher)-dimensional lattices. We use this method to estimate
, the exponent relating the minimum path to the
Euclidean distance r, for 4D and 5D hypercubic lattices. Analyzing both site
and bond percolation, we find (4D) and
(5D). In order to determine
to high precision, and without bias, it was necessary to
first find precise values for the percolation threshold, :
(4D) and (5D) for site and
(4D) and (5D) for bond
percolation. We also calculate the Fisher exponent, , determined in the
course of calculating the values of : (4D) and
(5D)
Economic results of the integrated crop-livestock systems implementation in degraded pastures in Pium, TO, Brazil.
In Pium, Tocantins state, Brazil, in 2012 Embrapa developed a technology transference project in partnership with the state?s rural extension service for the consolidation of low carbon emissions agriculture. The goal was to recover the degraded grasslands of the Trigueira farm (49°1'37.44"W and 10°24'58.84"S) with low cost using a crop-livestock system
Bovinocultura leiteira sustentável.
A bovinocultura leiteira e a cadeia do leite estão em desenvolvimento na região do MATOPIBA, que engloba parcelas dos Estados do Maranhão, Tocantins, Piauà e Bahia.bitstream/item/162178/1/CNPASA-2017-fd.pd
Master Operators Govern Multifractality in Percolation
Using renormalization group methods we study multifractality in percolation
at the instance of noisy random resistor networks. We introduce the concept of
master operators. The multifractal moments of the current distribution (which
are proportional to the noise cumulants of the
resistance between two sites x and located on the same cluster) are
related to such master operators. The scaling behavior of the multifractal
moments is governed exclusively by the master operators, even though a myriad
of servant operators is involved in the renormalization procedure. We calculate
the family of multifractal exponents for the scaling behavior of the
noise cumulants, ,
where is the correlation length exponent for percolation, to two-loop
order.Comment: 6 page
Relative water content in two grass cultivars in crop-livestock system in the State of Tocantins, Brazil.
In this presentation, we report the results of two grasses on Integrated Crop-Livestock System in the Tocantins Cerrado
Advances in technology transference: the experience of integrated crop-livestock-forestry (ICLF) adoption in Tocantins State.
In 2010 the Brazilian Government established a goal to reduce the emissions of greenhouse gases (GHG) by agriculture from 36.1 up to 38.9% in ten years (2010 -2020). To contribute for reaching part of this purpose in Tocantins State, Embrapa and other research and extension services partners have been conducting a project of technology transference on sustainable agricultural practices, including integrated crop-livestock-forestry (ICLF), since 2012
Logarithmic Corrections in Dynamic Isotropic Percolation
Based on the field theoretic formulation of the general epidemic process we
study logarithmic corrections to scaling in dynamic isotropic percolation at
the upper critical dimension d=6. Employing renormalization group methods we
determine these corrections for some of the most interesting time dependent
observables in dynamic percolation at the critical point up to and including
the next to leading correction. For clusters emanating from a local seed at the
origin we calculate the number of active sites, the survival probability as
well as the radius of gyration.Comment: 9 pages, 3 figures, version to appear in Phys. Rev.
Diluted Networks of Nonlinear Resistors and Fractal Dimensions of Percolation Clusters
We study random networks of nonlinear resistors, which obey a generalized
Ohm's law, . Our renormalized field theory, which thrives on an
interpretation of the involved Feynman Diagrams as being resistor networks
themselves, is presented in detail. By considering distinct values of the
nonlinearity r, we calculate several fractal dimensions characterizing
percolation clusters. For the dimension associated with the red bonds we show
that at least to order {\sl O} (\epsilon^4),
with being the correlation length exponent, and , where d
denotes the spatial dimension. This result agrees with a rigorous one by
Coniglio. Our result for the chemical distance, d_{\scriptsize min} = 2 -
\epsilon /6 - [ 937/588 + 45/49 (\ln 2 -9/10 \ln 3)] (\epsilon /6)^2 + {\sl O}
(\epsilon^3) verifies a previous calculation by one of us. For the backbone
dimension we find D_B = 2 + \epsilon /21 - 172 \epsilon^2 /9261 + 2 (- 74639 +
22680 \zeta (3))\epsilon^3 /4084101 + {\sl O} (\epsilon^4), where , in agreement to second order in with a two-loop
calculation by Harris and Lubensky.Comment: 29 pages, 7 figure
On the relevance of percolation theory to the vulcanization transition
The relationship between vulcanization and percolation is explored from the
perspective of renormalized local field theory. We show rigorously that the
vulcanization and percolation correlation functions are governed by the same
Gell--Mann-Low renormalization group equation. Hence, all scaling aspects of
the vulcanization transition are reigned by the critical exponents of the
percolation universality class.Comment: 9 pages, 2 figure
The risk analysis use supporting decision-making process on crop-livestock systems in Tocantins State, Brazil.
Decision-making about which crops will compose the crop-livestock system is an extremely important process for success integrated production. This case study aims to present the Monte Carlo (Boyle, 1977) risk analysis as a tool to support this process
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