Measuring complexity in three-trophic level systems

This essay is a trial on measuring complexity in a three-trophic level system by using a convex function of the informational entropy. The complexity measure defined here is compatible with the fact that real complexity lies between ordered and disordered states. Applying this measure to the data collected for two three-trophic level systems some hints about their organization are obtained. (C) 2008 Elsevier B.V. All rights reserved.

Isothermal seed germination of Adenanthera pavonina

This work reports aspects of seed germination at different temperatures of Adenanthera pavonina L., a woody Southeast Asian Leguminosae. Germination was studied by measuring the final percentages, the rate, the rate variance and the synchronisation of the individual seeds calculated by the minimal informational entropy of frequencies distribution of seed germination. Overlapping the germinability range with the range for the highest values of germination rates and the minimal informational entropy of frequencies distribution of seed germination, we found that the best temperature for the germination of A. pavonina seeds is 35 ºC. The slope µ of the Arrhenius plot of the germination rates is positive for T < 35 ºC and negative for T > 35 ºC. The activation enthalpies, estimated from closely-spaced points, shows that |ΔH-| < 12 Cal mol-1 occur for temperatures in the range between 25 ºC and 40 ºC. The ecological implication of these results are that this species may germinate very fast in tropical areas during the summer season. This may be an advantage to the establishment of this species under the climatic conditions in those areas.

Isothermal seed germination of Adenanthera pavonina

(Isothermal seed germination of Adenanthera pavonina). This work reports aspects of seed germination at different temperatures of Adenanthera pavonina L., a woody Southeast Asian Leguminosae. Germination was studied by measuring the final percentages, the rate, the rate variance and the synchronisation of the individual seeds calculated by the minimal informational entropy of frequencies distribution of seed germination. Overlapping the germinability range with the range for the highest values of germination rates and the minimal informational entropy of frequencies distribution of seed germination, we found that the best temperature for the germination of A. pavonina seeds is 35 degrees C. The slope mu of the Arrhenius plot of the germination rates is positive for T < 35 degrees C and negative for T > 35 degrees C. The activation enthalpies, estimated from closely-spaced points, shows that vertical bar Delta H-vertical bar < 12 Cal mol(-1) occur for temperatures in the range between 25 degrees C and 40 degrees C. The ecological implication of these results are that this species may germinate very fast in tropical areas during the summer season. This may be an advantage to the establishment of this species under the climatic conditions in those areas.

Isothermal seed germination of Adenanthera pavonina

This work reports aspects of seed germination at different temperatures of Adenanthera pavonina L., a woody Southeast Asian Leguminosae. Germination was studied by measuring the final percentages, the rate, the rate variance and the synchronisation of the individual seeds calculated by the minimal informational entropy of frequencies distribution of seed germination. Overlapping the germinability range with the range for the highest values of germination rates and the minimal informational entropy of frequencies distribution of seed germination, we found that the best temperature for the germination of A. pavonina seeds is 35 ºC. The slope µ of the Arrhenius plot of the germination rates is positive for T < 35 ºC and negative for T > 35 ºC. The activation enthalpies, estimated from closely-spaced points, shows that |ΔH-| < 12 Cal mol-1 occur for temperatures in the range between 25 ºC and 40 ºC. The ecological implication of these results are that this species may germinate very fast in tropical areas during the summer season. This may be an advantage to the establishment of this species under the climatic conditions in those areas.

Topological entropy of catalytic sets: Hypercycles revisited

The dynamics of catalytic networks have been widely studied over the last decades because of their implications in several fields like prebiotic evolution, virology, neural networks, immunology or ecology. One of the most studied mathematical bodies for catalytic networks was initially formulated in the context of prebiotic evolution, by means of the hypercycle theory. The hypercycle is a set of self-replicating species able to catalyze other replicator species within a cyclic architecture. Hypercyclic organization might arise from a quasispecies as a way to increase the informational containt surpassing the so-called error threshold. The catalytic coupling between replicators makes all the species to behave like a single and coherent evolutionary multimolecular unit. The inherent nonlinearities of catalytic interactions are responsible for the emergence of several types of dynamics, among them, chaos. In this article we begin with a brief review of the hypercycle theory focusing on its evolutionary implications as well as on different dynamics associated to different types of small catalytic networks. Then we study the properties of chaotic hypercycles with error-prone replication with symbolic dynamics theory, characterizing, by means of the theory of topological Markov chains, the topological entropy and the periods of the orbits of unimodal-like iterated maps obtained from the strange attractor. We will focus our study on some key parameters responsible for the structure of the catalytic network: mutation rates, autocatalytic and cross-catalytic interactions.

Informational institutions in the agrifood sector:meta-information and meta-governance of environmental sustainability

In the agrifood sector, the explosive increase in information about environmental sustainability, often in uncoordinated information systems, has created a new form of ignorance ('meta-ignorance') that diminishes the effectiveness of information on decision-makers. Flows of information are governed by informal and formal social arrangements that we can collectively call Informational Institutions. In this paper, we have reviewed the recent literature on such institutions. From the perspectives of information theory and new institutional economics, current informational institutions are increasing the information entropy of communications concerning environmental sustainability and stakeholders' transaction costs of using relevant information. In our view this reduces the effectiveness of informational governance. Future research on informational governance should explicitly address these aspects.

Entropy production in irreversible systems described by a Fokker-Planck equation

We analyze the irreversibility and the entropy production in nonequilibrium interacting particle systems described by a Fokker-Planck equation by the use of a suitable master equation representation. The irreversible character is provided either by nonconservative forces or by the contact with heat baths at distinct temperatures. The expression for the entropy production is deduced from a general definition, which is related to the probability of a trajectory in phase space and its time reversal, that makes no reference a priori to the dissipated power. Our formalism is applied to calculate the heat conductance in a simple system consisting of two Brownian particles each one in contact to a heat reservoir. We show also the connection between the definition of entropy production rate and the Jarzynski equality.

Probability currents and entropy production in nonequilibrium lattice systems

The structure of probability currents is studied for the dynamical network after consecutive contraction on two-state, nonequilibrium lattice systems. This procedure allows us to investigate the transition rates between configurations on small clusters and highlights some relevant effects of lattice symmetries on the elementary transitions that are responsible for entropy production. A method is suggested to estimate the entropy production for different levels of approximations (cluster sizes) as demonstrated in the two-dimensional contact process with mutation.

Renyi entropy and parity oscillations of anisotropic spin-s Heisenberg chains in a magnetic field

Using the density matrix renormalization group, we investigate the Renyi entropy of the anisotropic spin-s Heisenberg chains in a z-magnetic field. We considered the half-odd-integer spin-s chains, with s = 1/2, 3/2, and 5/2, and periodic and open boundary conditions. In the case of the spin-1/2 chain we were able to obtain accurate estimates of the new parity exponents p(alpha)((p)) and p(alpha)((o)) that gives the power-law decay of the oscillations of the alpha-Renyi entropy for periodic and open boundary conditions, respectively. We confirm the relations of these exponents with the Luttinger parameter K, as proposed by Calabrese et al. [Phys. Rev. Lett. 104, 095701 (2010)]. Moreover, the predicted periodicity of the oscillating term was also observed for some nonzero values of the magnetization m. We show that for s > 1/2 the amplitudes of the oscillations are quite small and get accurate estimates of p(alpha)((p)) and p(alpha)((o)) become a challenge. Although our estimates of the new universal exponents p(alpha)((p)) and p(alpha)((o)) for the spin-3/2 chain are not so accurate, they are consistent with the theoretical predictions.

Inference of gene regulatory networks from time series by Tsallis entropy

Background: The inference of gene regulatory networks (GRNs) from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information), a new criterion function is here proposed. Results: In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN) model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions: A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5 <= q <= 3.5 (hence, subextensive entropy), which opens new perspectives for GRNs inference methods based on information theory and for investigation of the nonextensivity of such networks. The inference algorithm and criterion function proposed here were implemented and included in the DimReduction software, which is freely available at http://sourceforge.net/projects/dimreduction and http://code.google.com/p/dimreduction/.

Adaptive Approach for a Maximum Entropy Algorithm in Ecological Niche Modeling

This paper presents an Adaptive Maximum Entropy (AME) approach for modeling biological species. The Maximum Entropy algorithm (MaxEnt) is one of the most used methods in modeling biological species geographical distribution. The approach presented here is an alternative to the classical algorithm. Instead of using the same set features in the training, the AME approach tries to insert or to remove a single feature at each iteration. The aim is to reach the convergence faster without affect the performance of the generated models. The preliminary experiments were well performed. They showed an increasing on performance both in accuracy and in execution time. Comparisons with other algorithms are beyond the scope of this paper. Some important researches are proposed as future works.

Effects of temperature-dependent viscosity variation on entropy generation, heat and fluid flow through a porous-saturated duct of rectangular cross-section

Effect of temperature-dependent viscosity on fully developed forced convection in a duct of rectangular cross-section occupied by a fluid-saturated porous medium is investigated analytically. The Darcy flow model is applied and the viscosity-temperature relation is assumed to be an inverse-linear one. The case of uniform heat flux on the walls, i.e. the H boundary condition in the terminology of Kays and Crawford, is treated. For the case of a fluid whose viscosity decreases with temperature, it is found that the effect of the variation is to increase the Nusselt number for heated walls. Having found the velocity and the temperature distribution, the second law of thermodynamics is invoked to find the local and average entropy generation rate. Expressions for the entropy generation rate, the Bejan number, the heat transfer irreversibility, and the fluid flow irreversibility are presented in terms of the Brinkman number, the Péclet number, the viscosity variation number, the dimensionless wall heat flux, and the aspect ratio (width to height ratio). These expressions let a parametric study of the problem based on which it is observed that the entropy generated due to flow in a duct of square cross-section is more than those of rectangular counterparts while increasing the aspect ratio decreases the entropy generation rate similar to what previously reported for the clear flow case.

Heat transfer and entropy generation optimization of forced convection in a porous-saturated duct of rectangular cross-section

We investigate analytically the first and the second law characteristics of fully developed forced convection inside a porous-saturated duct of rectangular cross-section. The Darcy-Brinkman flow model is employed. Three different types of thermal boundary conditions are examined. Expressions for the Nusselt number, the Bejan number, and the dimensionless entropy generation rate are presented in terms of the system parameters. The conclusions of this analytical study will make it possible to compare, evaluate, and optimize alternative rectangular duct design options in terms of heat transfer, pressure drop, and entropy generation. (c) 2006 Elsevier Ltd. All rights reserved.

Entropy generation for forced convection in a porous saturated circular tube with uniform wall temperature

A numerical study is reported to investigate both the First and the Second Law of Thermodynamics for thermally developing forced convection in a circular tube filled by a saturated porous medium, with uniform wall temperature, and with the effects of viscous dissipation included. A theoretical analysis is also presented to study the problem for the asymptotic region applying the perturbation solution of the Brinkman momentum equation reported by Hooman and Kani [1]. Expressions are reported for the temperature profile, the Nusselt number, the Bejan number, and the dimensionless entropy generation rate in the asymptotic region. Numerical results are found to be in good agreement with theoretical counterparts.