Consistency in approximate entropy given by a volumetric estimate

Non-linear methods for estimating variability in time-series are currently of widespread use. Among such methods are approximate entropy (ApEn) and sample approximate entropy (SampEn). The applicability of ApEn and SampEn in analyzing data is evident and their use is increasing. However, consistency is a point of concern in these tools, i.e., the classification of the temporal organization of a data set might indicate a relative less ordered series in relation to another when the opposite is true. As highlighted by their proponents themselves, ApEn and SampEn might present incorrect results due to this lack of consistency. In this study, we present a method which gains consistency by using ApEn repeatedly in a wide range of combinations of window lengths and matching error tolerance. The tool is called volumetric approximate entropy, vApEn. We analyze nine artificially generated prototypical time-series with different degrees of temporal order (combinations of sine waves, logistic maps with different control parameter values, random noises). While ApEn/SampEn clearly fail to consistently identify the temporal order of the sequences, vApEn correctly do. In order to validate the tool we performed shuffled and surrogate data analysis. Statistical analysis confirmed the consistency of the method. (C) 2008 Elsevier Ltd. All rights reserved.

Gaining ligand selectivity in thyroid hormone receptors via entropy

Nuclear receptors are important targets for pharmaceuticals, but similarities between family members cause difficulties in obtaining highly selective compounds. Synthetic ligands that are selective for thyroid hormone (TH) receptor beta (TR beta) vs. TR alpha reduce cholesterol and fat without effects on heart rate; thus, it is important to understand TR beta-selective binding. Binding of 3 selective ligands (GC-1, KB141, and GC-24) is characterized at the atomic level; preferential binding depends on a nonconserved residue (Asn-331 beta) in the TR beta ligand-binding cavity (LBC), and GC-24 gains extra selectivity from insertion of a bulky side group into an extension of the LBC that only opens up with this ligand. Here we report that the natural TH 3,5,3`-triodothyroacetic acid (Triac) exhibits a previously unrecognized mechanism of TR beta selectivity. TR x-ray structures reveal better fit of ligand with the TR alpha LBC. The TR beta LBC, however, expands relative to TR alpha in the presence of Triac (549 angstrom(3) vs. 461 angstrom(3)), and molecular dynamics simulations reveal that water occupies the extra space. Increased solvation compensates for weaker interactions of ligand with TR beta and permits greater flexibility of the Triac carboxylate group in TR beta than in TR alpha. We propose that this effect results in lower entropic restraint and decreases free energy of interactions between Triac and TR beta, explaining subtype-selective binding. Similar effects could potentially be exploited in nuclear receptor drug design.

The Contribution of the Activation Entropy to the Gas-Phase Stability of Modified Nucleic Acid Duplexes

Tricyclo-DNA (tcDNA) is a sugar-modified analogue of DNA currently tested for the treatment of Duchenne muscular dystrophy in an antisense approach. Tandem mass spectrometry plays a key role in modern medical diagnostics and has become a widespread technique for the structure elucidation and quantification of antisense oligonucleotides. Herein, mechanistic aspects of the fragmentation of tcDNA are discussed, which lay the basis for reliable sequencing and quantification of the antisense oligonucleotide. Excellent selectivity of tcDNA for complementary RNA is demonstrated in direct competition experiments. Moreover, the kinetic stability and fragmentation pattern of matched and mismatched tcDNA heteroduplexes were investigated and compared with non-modified DNA and RNA duplexes. Although the separation of the constituting strands is the entropy-favored fragmentation pathway of all nucleic acid duplexes, it was found to be only a minor pathway of tcDNA duplexes. The modified hybrid duplexes preferentially undergo neutral base loss and backbone cleavage. This difference is due to the low activation entropy for the strand dissociation of modified duplexes that arises from the conformational constraint of the tc-sugar-moiety. The low activation entropy results in a relatively high free activation enthalpy for the dissociation comparable to the free activation enthalpy of the alternative reaction pathway, the release of a nucleobase. The gas-phase behavior of tcDNA duplexes illustrates the impact of the activation entropy on the fragmentation kinetics and suggests that tandem mass spectrometric experiments are not suited to determine the relative stability of different types of nucleic acid duplexes.

Design concept evaluation based on rough number and information entropy theory

Concept evaluation at the early phase of product development plays a crucial role in new product development. It determines the direction of the subsequent design activities. However, the evaluation information at this stage mainly comes from experts' judgments, which is subjective and imprecise. How to manage the subjectivity to reduce the evaluation bias is a big challenge in design concept evaluation. This paper proposes a comprehensive evaluation method which combines information entropy theory and rough number. Rough number is first presented to aggregate individual judgments and priorities and to manipulate the vagueness under a group decision-making environment. A rough number based information entropy method is proposed to determine the relative weights of evaluation criteria. The composite performance values based on rough number are then calculated to rank the candidate design concepts. The results from a practical case study on the concept evaluation of an industrial robot design show that the integrated evaluation model can effectively strengthen the objectivity across the decision-making processes.

The relative effects of severe burn injury and pre- and post-natal protein deprivation on mandibular condyle morphology

The mandible has a mixed embryological origin, and its growth is associated with the secondary cartilage of the condyle process (CP). In this area, growth depends on an array of intrinsic and extrinsic factors that influence protein metabolism. In the present study, we used an adolescent rat model to evaluate the growth and development of the CP under conditions of pre- and postnatal protein deficiency, combined with or without the stress of severe burn injury (BI). We found that protein deficiency severely undermined the growth of the CP, by altering the thickness of its constituent layers. BI is also capable of affecting CP growth, although the effect is less severe than protein deficiency. Interestingly, the summed effect of protein deficiency and BI on the CP is less severe than protein deficiency alone. A possible explanation is that the increased carbohydrates in a hypoproteic diet stimulate the production of endogenous insulin and protein synthesis, which partially compensates for the loss of lean body mass caused by BI.

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.

Determination of the molecular weight of proteins in solution from a single small-angle X-ray scattering measurement on a relative scale

This paper describes a new and simple method to determine the molecular weight of proteins in dilute solution, with an error smaller than similar to 10%, by using the experimental data of a single small-angle X-ray scattering (SAXS) curve measured on a relative scale. This procedure does not require the measurement of SAXS intensity on an absolute scale and does not involve a comparison with another SAXS curve determined from a known standard protein. The proposed procedure can be applied to monodisperse systems of proteins in dilute solution, either in monomeric or multimeric state, and it has been successfully tested on SAXS data experimentally determined for proteins with known molecular weights. It is shown here that the molecular weights determined by this procedure deviate from the known values by less than 10% in each case and the average error for the test set of 21 proteins was 5.3%. Importantly, this method allows for an unambiguous determination of the multimeric state of proteins with known molecular weights.

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/.

Thermo-solvatochromism in binary mixtures of water and ionic liquids: on the relative importance of solvophobic interactions

The thermo-solvatochromism of 2,6-dibromo-4-[(E)-2-(1-methylpyridinium-4-yl)ethenyl] phenolate, MePMBr(2), has been studied in mixtures of water, W, with ionic liquids, ILs, in the temperature range of 10 to 60 degrees C, where feasible. The objectives of the study were to test the applicability of a recently introduced solvation model, and to assess the relative importance of solute-solvent solvophobic interactions. The ILs were 1-allyl-3-alkylimidazolium chlorides, where the alkyl groups are methyl, 1-butyl, and 1-hexyl, respectively. The equilibrium constants for the interaction of W and the ILs were calculated from density data; they were found to be linearly dependent on N(C), the number of carbon atoms of the alkyl group; van't Hoff equation (log K versus 1/T) applied satisfactorily. Plots of the empirical solvent polarities, E(T) (MePMBr(2)) in kcal mol(-1), versus the mole fraction of water in the binary mixture, chi(w), showed non-linear, i.e., non-ideal behavior. The dependence of E(T) (MePMBr(2)) on chi(w), has been conveniently quantified in terms of solvation by W, IL, and the ""complex"" solvent IL-W. The non-ideal behavior is due to preferential solvation by the IL and, more efficiently, by IL-W. The deviation from linearity increases as a function of increasing N(C) of the IL, and is stronger than that observed for solvation of MePMBr(2) by aqueous 1-propanol, a solvent whose lipophilicity is 12.8 to 52.1 times larger than those of the ILs investigated. The dependence on N(C) is attributed to solute-solvent solvophobic interactions, whose relative contribution to solvation are presumably greater than that in mixtures of water and 1-propanol.

Quaternary paleoenvironments and relative sea-level changes in Marajo Island (Northern Brazil): Facies, delta(13)C, delta(15)N and C/N

The reconstruction of physical environments of Amazonian areas is of great interest to determine the dynamic evolution of the Amazon drainage basin. However. few studies have emphasized the Quaternary deposits in this region. which is mostly due to the lack of natural exposures imposed by the low topography. This work integrates facies analysis. radiocarbon dating, delta(13)C, delta(15)N, and C/N of an 124 m-thick core from an area located at the mouth of the Amazon River. northeastern Amazonia. The study records deposits up to 50.795 (14)C yr B P. in age. which formed in a variety of depositional environments including fluvial channel, tidal flat, outer estuarine basin to shallow marine. inner estuarine basin, estuarine channel and lagoon. Facies interpretation was significantly improved with the inclusion of delta(13)C, delta(15)N, and C/N analyses of organic matter extracted from the sediments The obtained values conform to a transitional. mostly estuarine paleosetting evolved during successive relative sea-level fluctuations. The results suggest fluvial deposition between 40,950 (+/- 590) and 50.795 (14)C yr B P, with a rise in relative sea level that commenced between 35,567 (+/- 649) and 39,079 (+/- 1114) (14)C yr B P. An overall transgression took place until 29,340 (+/- 340) (14)C yr B P., after which the relative sea level dropped, favoring valley rejuvenation and incision. Following this time up to 10,479 (+/- 34) (14)C yr B.P. a rise in relative sea level filled up the valley with estuarine deposits After 10.479(+/- 34) (14)C yr B.P., the estuary was replaced by a lagoon At the end of the Holocene, the coastline prograided approximately 45 km northward, replaci ng the lagoon by a lake system Despite the influence of eustatic fluctuations. regional tectonics played a significant role to create new space where these Late Pleistocene and Holocene sediments accumulated. (C) 2009 Elsevier B V All rights reserved.

Relative frequency of knowledge of results and task complexity in the motor skill acqusition

The aim of this study was to investigate the effects of knowledge of results (KR) frequency and task complexity on motor skill acquisition. The task consisted of throwing a bocha ball to place it as close as possible to the target ball. 120 students ages 11 to 73 years were assigned to one of eight experimental groups according to knowledge of results frequency (25, 50, 75, and 100%) and task complexity (simple and complex). Subjects performed 90 trials in the acquisition phase and 10 trials in the transfer test. The results showed that knowledge of results given at a frequency of 25% resulted in an inferior absolute error than 50% and inferior variable error than 50, 75, and 100 I frequencies, but no effect of task complexity was found.

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.

Thermodynamic approaches in sliding wear: a review

In this paper, a review of the thermodynamic approaches of sliding wear is presented. These approaches are divided into the friction energy dissipation, the energy balance and the entropy production. A concise and critic account of the approaches is discussed, remarking their relative strength and weakness in explaining the phenomena occurring in the sliding wear.