Plasma Transport and Magnetic Flux Circulation in Saturn's Magnetosphere

NASA Astrophysics Data System (ADS)

Neupane, B. R.; Delamere, P. A.; Ma, X.; Wilson, R. J.

2017-12-01

Radial transport of plasma in the rapidly rotating magnetospheres is an important dynamical process. Radial transport is due to the centrifugally driven interchange instability and magnetodisc reconnection, allowing net mass to be transported outward while conserving magnetic flux. Using Cassini Plasma Spectrometer instrument (CAPS) data products (e.g., Thomsen et al., [2010]; Wilson et al., [2017]) we estimate plasma mass and magnetic flux transport rates as functions of radial distance and local time. The physical requirement for zero net magnetic flux transport provides a key benchmark for assessing the validity of our mass transport estimate. We also evaluate magnetodisc stability using a two-dimensional axisymmetric equilibrium model [Caudal, 1986]. Observed local properties (e.g., specific entropy and estimates of flux tube mass and entropy content) are compared with modeled equilibrium conditions such that departures from equilibrium can be correlated with radial flows and local magnetic field structure. Finally, observations of specific entropy indicate that plasma is non-adiabatic heated during transport. However, the values of specific entropy are well organized in inner magnetosphere (i.e. L<10), and become widely scattered in the middle magnetosphere, suggesting that the transport dynamics of the inner and middle magnetosphere are different.

Minimal entropy probability paths between genome families.

PubMed

Ahlbrandt, Calvin; Benson, Gary; Casey, William

2004-05-01

We develop a metric for probability distributions with applications to biological sequence analysis. Our distance metric is obtained by minimizing a functional defined on the class of paths over probability measures on N categories. The underlying mathematical theory is connected to a constrained problem in the calculus of variations. The solution presented is a numerical solution, which approximates the true solution in a set of cases called rich paths where none of the components of the path is zero. The functional to be minimized is motivated by entropy considerations, reflecting the idea that nature might efficiently carry out mutations of genome sequences in such a way that the increase in entropy involved in transformation is as small as possible. We characterize sequences by frequency profiles or probability vectors, in the case of DNA where N is 4 and the components of the probability vector are the frequency of occurrence of each of the bases A, C, G and T. Given two probability vectors a and b, we define a distance function based as the infimum of path integrals of the entropy function H( p) over all admissible paths p(t), 0 < or = t< or =1, with p(t) a probability vector such that p(0)=a and p(1)=b. If the probability paths p(t) are parameterized as y(s) in terms of arc length s and the optimal path is smooth with arc length L, then smooth and "rich" optimal probability paths may be numerically estimated by a hybrid method of iterating Newton's method on solutions of a two point boundary value problem, with unknown distance L between the abscissas, for the Euler-Lagrange equations resulting from a multiplier rule for the constrained optimization problem together with linear regression to improve the arc length estimate L. Matlab code for these numerical methods is provided which works only for "rich" optimal probability vectors. These methods motivate a definition of an elementary distance function which is easier and faster to calculate, works on non-rich vectors, does not involve variational theory and does not involve differential equations, but is a better approximation of the minimal entropy path distance than the distance //b-a//(2). We compute minimal entropy distance matrices for examples of DNA myostatin genes and amino-acid sequences across several species. Output tree dendograms for our minimal entropy metric are compared with dendograms based on BLAST and BLAST identity scores.

Correlation as a Determinant of Configurational Entropy in Supramolecular and Protein Systems

PubMed Central

2015-01-01

For biomolecules in solution, changes in configurational entropy are thought to contribute substantially to the free energies of processes like binding and conformational change. In principle, the configurational entropy can be strongly affected by pairwise and higher-order correlations among conformational degrees of freedom. However, the literature offers mixed perspectives regarding the contributions that changes in correlations make to changes in configurational entropy for such processes. Here we take advantage of powerful techniques for simulation and entropy analysis to carry out rigorous in silico studies of correlation in binding and conformational changes. In particular, we apply information-theoretic expansions of the configurational entropy to well-sampled molecular dynamics simulations of a model host–guest system and the protein bovine pancreatic trypsin inhibitor. The results bear on the interpretation of NMR data, as they indicate that changes in correlation are important determinants of entropy changes for biologically relevant processes and that changes in correlation may either balance or reinforce changes in first-order entropy. The results also highlight the importance of main-chain torsions as contributors to changes in protein configurational entropy. As simulation techniques grow in power, the mathematical techniques used here will offer new opportunities to answer challenging questions about complex molecular systems. PMID:24702693

Entanglement Entropy in Two-Dimensional String Theory.

PubMed

Hartnoll, Sean A; Mazenc, Edward A

2015-09-18

To understand an emergent spacetime is to understand the emergence of locality. Entanglement entropy is a powerful diagnostic of locality, because locality leads to a large amount of short distance entanglement. Two-dimensional string theory is among the very simplest instances of an emergent spatial dimension. We compute the entanglement entropy in the large-N matrix quantum mechanics dual to two-dimensional string theory in the semiclassical limit of weak string coupling. We isolate a logarithmically large, but finite, contribution that corresponds to the short distance entanglement of the tachyon field in the emergent spacetime. From the spacetime point of view, the entanglement is regulated by a nonperturbative "graininess" of space.

Renyi Entropies of a Black Hole

NASA Astrophysics Data System (ADS)

Bialas, A.; Czyz, W.

2008-08-01

The Renyi entropies, Hl, of Hawking radiation contained in a thin shell surrounding the black hole are evaluated. When the width of the shell is adjusted to the energy content corresponding to the mass defect, the Bekenstein-Hawking formula for the Shannon (S=H1) entropy of a black hole is reproduced. This result does not depend on the distance of the shell from the horizon. The Renyi entropies of higher order, however, are sensitive to it.

Casimir Interaction from Magnetically Coupled Eddy Currents

DOE Office of Scientific and Technical Information (OSTI.GOV)

Intravaia, Francesco; Henkel, Carsten

2009-09-25

We study the quantum and thermal fluctuations of eddy (Foucault) currents in thick metallic plates. A Casimir interaction between two plates arises from the coupling via quasistatic magnetic fields. As a function of distance, the relevant eddy current modes cross over from a quantum to a thermal regime. These modes alone reproduce previously discussed thermal anomalies of the electromagnetic Casimir interaction between good conductors. In particular, they provide a physical picture for the Casimir entropy whose nonzero value at zero temperature arises from a correlated, glassy state.

RED: a set of molecular descriptors based on Renyi entropy.

PubMed

Delgado-Soler, Laura; Toral, Raul; Tomás, M Santos; Rubio-Martinez, Jaime

2009-11-01

New molecular descriptors, RED (Renyi entropy descriptors), based on the generalized entropies introduced by Renyi are presented. Topological descriptors based on molecular features have proven to be useful for describing molecular profiles. Renyi entropy is used as a variability measure to contract a feature-pair distribution composing the descriptor vector. The performance of RED descriptors was tested for the analysis of different sets of molecular distances, virtual screening, and pharmacological profiling. A free parameter of the Renyi entropy has been optimized for all the considered applications.

Relating quantum coherence and correlations with entropy-based measures.

PubMed

Wang, Xiao-Li; Yue, Qiu-Ling; Yu, Chao-Hua; Gao, Fei; Qin, Su-Juan

2017-09-21

Quantum coherence and quantum correlations are important quantum resources for quantum computation and quantum information. In this paper, using entropy-based measures, we investigate the relationships between quantum correlated coherence, which is the coherence between subsystems, and two main kinds of quantum correlations as defined by quantum discord as well as quantum entanglement. In particular, we show that quantum discord and quantum entanglement can be well characterized by quantum correlated coherence. Moreover, we prove that the entanglement measure formulated by quantum correlated coherence is lower and upper bounded by the relative entropy of entanglement and the entanglement of formation, respectively, and equal to the relative entropy of entanglement for all the maximally correlated states.

Holographic definition of points and distances

NASA Astrophysics Data System (ADS)

Czech, Bartłomiej; Lamprou, Lampros

2014-11-01

We discuss the way in which field theory quantities assemble the spatial geometry of three-dimensional anti-de Sitter space (AdS3). The field theory ingredients are the entanglement entropies of boundary intervals. A point in AdS3 corresponds to a collection of boundary intervals which is selected by a variational principle we discuss. Coordinates in AdS3 are integration constants of the resulting equation of motion. We propose a distance function for this collection of points, which obeys the triangle inequality as a consequence of the strong subadditivity of entropy. Our construction correctly reproduces the static slice of AdS3 and the Ryu-Takayanagi relation between geodesics and entanglement entropies. We discuss how these results extend to quotients of AdS3 —the conical defect and the BTZ geometries. In these cases, the set of entanglement entropies must be supplemented by other field theory quantities, which can carry the information about lengths of nonminimal geodesics.

Towards a unifying approach to diversity measures: bridging the gap between the Shannon entropy and Rao's quadratic index.

PubMed

Ricotta, Carlo; Szeidl, Laszlo

2006-11-01

The diversity of a species assemblage has been studied extensively for many decades in relation to its possible connection with ecosystem functioning and organization. In this view most diversity measures, such as Shannon's entropy, rely upon information theory as a basis for the quantification of diversity. Also, traditional diversity measures are computed using species relative abundances and cannot account for the ecological differences between species. Rao first proposed a diversity index, termed quadratic diversity (Q) that incorporates both species relative abundances and pairwise distances between species. Quadratic diversity is traditionally defined as the expected distance between two randomly selected individuals. In this paper, we show that quadratic diversity can be interpreted as the expected conflict among the species of a given assemblage. From this unusual interpretation, it naturally follows that Rao's Q can be related to the Shannon entropy through a generalized version of the Tsallis parametric entropy.

Entanglement of purification in free scalar field theories

NASA Astrophysics Data System (ADS)

Bhattacharyya, Arpan; Takayanagi, Tadashi; Umemoto, Koji

2018-04-01

We compute the entanglement of purification (EoP) in a 2d free scalar field theory with various masses. This quantity measures correlations between two subsystems and is reduced to the entanglement entropy when the total system is pure. We obtain explicit numerical values by assuming minimal gaussian wave functionals for the purified states. We find that when the distance between the subsystems is large, the EoP behaves like the mutual information. However, when the distance is small, the EoP shows a characteristic behavior which qualitatively agrees with the conjectured holographic computation and which is different from that of the mutual information. We also study behaviors of mutual information in purified spaces and violations of monogamy/strong superadditivity.

Extension and Application of High-Speed Digital Imaging Analysis Via Spatiotemporal Correlation and Eigenmode Analysis of Vocal Fold Vibration Before and After Polyp Excision.

PubMed

Wang, Jun-Sheng; Olszewski, Emily; Devine, Erin E; Hoffman, Matthew R; Zhang, Yu; Shao, Jun; Jiang, Jack J

2016-08-01

To evaluate the spatiotemporal correlation of vocal fold vibration using eigenmode analysis before and after polyp removal and explore the potential clinical relevance of spatiotemporal analysis of correlation length and entropy as quantitative voice parameters. We hypothesized that increased order in the vibrating signal after surgical intervention would decrease the eigenmode-based entropy and increase correlation length. Prospective case series. Forty subjects (23 males, 17 females) with unilateral (n = 24) or bilateral (n = 16) polyps underwent polyp removal. High-speed videoendoscopy was performed preoperatively and 2 weeks postoperatively. Spatiotemporal analysis was performed to determine entropy, quantification of signal disorder, correlation length, size, and spatially ordered structure of vocal fold vibration in comparison to full spatial consistency. The signal analyzed consists of the vibratory pattern in space and time derived from the high-speed video glottal area contour. Entropy decreased (Z = -3.871, P < .001) and correlation length increased (t = -8.913, P < .001) following polyp excision. The intraclass correlation coefficients (ICC) for correlation length and entropy were 0.84 and 0.93. Correlation length and entropy are sensitive to mass lesions. These parameters could potentially be used to augment subjective visualization after polyp excision when evaluating procedural efficacy. © The Author(s) 2016.

CLUSFAVOR 5.0: hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles

PubMed Central

Peterson, Leif E

2002-01-01

CLUSFAVOR (CLUSter and Factor Analysis with Varimax Orthogonal Rotation) 5.0 is a Windows-based computer program for hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles. CLUSFAVOR 5.0 standardizes input data; sorts data according to gene-specific coefficient of variation, standard deviation, average and total expression, and Shannon entropy; performs hierarchical cluster analysis using nearest-neighbor, unweighted pair-group method using arithmetic averages (UPGMA), or furthest-neighbor joining methods, and Euclidean, correlation, or jack-knife distances; and performs principal-component analysis. PMID:12184816

Evaluation of entropy and JM-distance criterions as features selection methods using spectral and spatial features derived from LANDSAT images

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Dutra, L. V.; Mascarenhas, N. D. A.; Mitsuo, Fernando Augusta, II

1984-01-01

A study area near Ribeirao Preto in Sao Paulo state was selected, with predominance in sugar cane. Eight features were extracted from the 4 original bands of LANDSAT image, using low-pass and high-pass filtering to obtain spatial features. There were 5 training sites in order to acquire the necessary parameters. Two groups of four channels were selected from 12 channels using JM-distance and entropy criterions. The number of selected channels was defined by physical restrictions of the image analyzer and computacional costs. The evaluation was performed by extracting the confusion matrix for training and tests areas, with a maximum likelihood classifier, and by defining performance indexes based on those matrixes for each group of channels. Results show that in spatial features and supervised classification, the entropy criterion is better in the sense that allows a more accurate and generalized definition of class signature. On the other hand, JM-distance criterion strongly reduces the misclassification within training areas.

Energy, entropy and mass scaling relations for elliptical galaxies. Towards a physical understanding of their photometric properties

NASA Astrophysics Data System (ADS)

Márquez, I.; Lima Neto, G. B.; Capelato, H.; Durret, F.; Lanzoni, B.; Gerbal, D.

2001-12-01

In the present paper, we show that elliptical galaxies (Es) obey a scaling relation between potential energy and mass. Since they are relaxed systems in a post violent-relaxation stage, they are quasi-equilibrium gravitational systems and therefore they also have a quasi-constant specific entropy. Assuming that light traces mass, these two laws imply that in the space defined by the three Sérsic law parameters (intensity Sigma0 , scale a and shape nu ), elliptical galaxies are distributed on two intersecting 2-manifolds: the Entropic Surface and the Energy-Mass Surface. Using a sample of 132 galaxies belonging to three nearby clusters, we have verified that ellipticals indeed follow these laws. This also implies that they are distributed along the intersection line (the Energy-Entropy line), thus they constitute a one-parameter family. These two physical laws (separately or combined), allow to find the theoretical origin of several observed photometrical relations, such as the correlation between absolute magnitude and effective surface brightness, and the fact that ellipticals are located on a surface in the [log Reff, -2.5 log Sigma0, log nu ] space. The fact that elliptical galaxies are a one-parameter family has important implications for cosmology and galaxy formation and evolution models. Moreover, the Energy-Entropy line could be used as a distance indicator.

The Role of the Total Entropy Production in the Dynamics of Open Quantum Systems in Detection of Non-Markovianity

NASA Astrophysics Data System (ADS)

Salimi, S.; Haseli, S.; Khorashad, A. S.; Adabi, F.

2016-09-01

The interaction between system and environment is a fundamental concept in the theory of open quantum systems. As a result of the interaction, an amount of correlation (both classical and quantum) emerges between the system and the environment. In this work, we recall the quantity that will be very useful to describe the emergence of the correlation between the system and the environment, namely, the total entropy production. Appearance of total entropy production is due to the entanglement production between the system and the environment. In this work, we discuss about the role of the total entropy production for detecting the non-Markovianity. By utilizing the relation between the total entropy production and total correlation between subsystems, one can see a temporary decrease of total entropy production is a signature of non-Markovianity. We apply our criterion for the special case, where the composite system has initial correlation with environment.

Multiscale Shannon's Entropy Modeling of Orientation and Distance in Steel Fiber Micro-Tomography Data.

PubMed

Chiverton, John P; Ige, Olubisi; Barnett, Stephanie J; Parry, Tony

2017-11-01

This paper is concerned with the modeling and analysis of the orientation and distance between steel fibers in X-ray micro-tomography data. The advantage of combining both orientation and separation in a model is that it helps provide a detailed understanding of how the steel fibers are arranged, which is easy to compare. The developed models are designed to summarize the randomness of the orientation distribution of the steel fibers both locally and across an entire volume based on multiscale entropy. Theoretical modeling, simulation, and application to real imaging data are shown here. The theoretical modeling of multiscale entropy for orientation includes a proof showing the final form of the multiscale taken over a linear range of scales. A series of image processing operations are also included to overcome interslice connectivity issues to help derive the statistical descriptions of the orientation distributions of the steel fibers. The results demonstrate that multiscale entropy provides unique insights into both simulated and real imaging data of steel fiber reinforced concrete.

A novel encoding scheme for effective biometric discretization: Linearly Separable Subcode.

PubMed

Lim, Meng-Hui; Teoh, Andrew Beng Jin

2013-02-01

Separability in a code is crucial in guaranteeing a decent Hamming-distance separation among the codewords. In multibit biometric discretization where a code is used for quantization-intervals labeling, separability is necessary for preserving distance dissimilarity when feature components are mapped from a discrete space to a Hamming space. In this paper, we examine separability of Binary Reflected Gray Code (BRGC) encoding and reveal its inadequacy in tackling interclass variation during the discrete-to-binary mapping, leading to a tradeoff between classification performance and entropy of binary output. To overcome this drawback, we put forward two encoding schemes exhibiting full-ideal and near-ideal separability capabilities, known as Linearly Separable Subcode (LSSC) and Partially Linearly Separable Subcode (PLSSC), respectively. These encoding schemes convert the conventional entropy-performance tradeoff into an entropy-redundancy tradeoff in the increase of code length. Extensive experimental results vindicate the superiority of our schemes over the existing encoding schemes in discretization performance. This opens up possibilities of achieving much greater classification performance with high output entropy.

Shock heating of the solar wind plasma

NASA Technical Reports Server (NTRS)

Whang, Y. C.; Liu, Shaoliang; Burlaga, L. F.

1990-01-01

The role played by shocks in heating solar-wind plasma is investigated using data on 413 shocks which were identified from the plasma and magnetic-field data collected between 1973 and 1982 by Pioneer and Voyager spacecraft. It is found that the average shock strength increased with the heliocentric distance outside 1 AU, reaching a maximum near 5 AU, after which the shock strength decreased with the distance; the entropy of the solar wind protons also reached a maximum at 5 AU. An MHD simulation model in which shock heating is the only heating mechanism available was used to calculate the entropy changes for the November 1977 event. The calculated entropy agreed well with the value calculated from observational data, suggesting that shocks are chiefly responsible for heating solar wind plasma between 1 and 15 AU.

Coherence and entanglement measures based on Rényi relative entropies

NASA Astrophysics Data System (ADS)

Zhu, Huangjun; Hayashi, Masahito; Chen, Lin

2017-11-01

We study systematically resource measures of coherence and entanglement based on Rényi relative entropies, which include the logarithmic robustness of coherence, geometric coherence, and conventional relative entropy of coherence together with their entanglement analogues. First, we show that each Rényi relative entropy of coherence is equal to the corresponding Rényi relative entropy of entanglement for any maximally correlated state. By virtue of this observation, we establish a simple operational connection between entanglement measures and coherence measures based on Rényi relative entropies. We then prove that all these coherence measures, including the logarithmic robustness of coherence, are additive. Accordingly, all these entanglement measures are additive for maximally correlated states. In addition, we derive analytical formulas for Rényi relative entropies of entanglement of maximally correlated states and bipartite pure states, which reproduce a number of classic results on the relative entropy of entanglement and logarithmic robustness of entanglement in a unified framework. Several nontrivial bounds for Rényi relative entropies of coherence (entanglement) are further derived, which improve over results known previously. Moreover, we determine all states whose relative entropy of coherence is equal to the logarithmic robustness of coherence. As an application, we provide an upper bound for the exact coherence distillation rate, which is saturated for pure states.

Random versus maximum entropy models of neural population activity

NASA Astrophysics Data System (ADS)

Ferrari, Ulisse; Obuchi, Tomoyuki; Mora, Thierry

2017-04-01

The principle of maximum entropy provides a useful method for inferring statistical mechanics models from observations in correlated systems, and is widely used in a variety of fields where accurate data are available. While the assumptions underlying maximum entropy are intuitive and appealing, its adequacy for describing complex empirical data has been little studied in comparison to alternative approaches. Here, data from the collective spiking activity of retinal neurons is reanalyzed. The accuracy of the maximum entropy distribution constrained by mean firing rates and pairwise correlations is compared to a random ensemble of distributions constrained by the same observables. For most of the tested networks, maximum entropy approximates the true distribution better than the typical or mean distribution from that ensemble. This advantage improves with population size, with groups as small as eight being almost always better described by maximum entropy. Failure of maximum entropy to outperform random models is found to be associated with strong correlations in the population.

Entropy of spatial network ensembles

NASA Astrophysics Data System (ADS)

Coon, Justin P.; Dettmann, Carl P.; Georgiou, Orestis

2018-04-01

We analyze complexity in spatial network ensembles through the lens of graph entropy. Mathematically, we model a spatial network as a soft random geometric graph, i.e., a graph with two sources of randomness, namely nodes located randomly in space and links formed independently between pairs of nodes with probability given by a specified function (the "pair connection function") of their mutual distance. We consider the general case where randomness arises in node positions as well as pairwise connections (i.e., for a given pair distance, the corresponding edge state is a random variable). Classical random geometric graph and exponential graph models can be recovered in certain limits. We derive a simple bound for the entropy of a spatial network ensemble and calculate the conditional entropy of an ensemble given the node location distribution for hard and soft (probabilistic) pair connection functions. Under this formalism, we derive the connection function that yields maximum entropy under general constraints. Finally, we apply our analytical framework to study two practical examples: ad hoc wireless networks and the US flight network. Through the study of these examples, we illustrate that both exhibit properties that are indicative of nearly maximally entropic ensembles.

The External Performance Appraisal of China Energy Regulation: An Empirical Study Using a TOPSIS Method Based on Entropy Weight and Mahalanobis Distance.

PubMed

Wang, Zheng-Xin; Li, Dan-Dan; Zheng, Hong-Hao

2018-01-30

In China's industrialization process, the effective regulation of energy and environment can promote the positive externality of energy consumption while reducing negative externality, which is an important means for realizing the sustainable development of an economic society. The study puts forward an improved technique for order preference by similarity to an ideal solution based on entropy weight and Mahalanobis distance (briefly referred as E-M-TOPSIS). The performance of the approach was verified to be satisfactory. By separately using traditional and improved TOPSIS methods, the study carried out the empirical appraisals on the external performance of China's energy regulation during 1999~2015. The results show that the correlation between the performance indexes causes the significant difference between the appraisal results of E-M-TOPSIS and traditional TOPSIS. The E-M-TOPSIS takes the correlation between indexes into account and generally softens the closeness degree compared with traditional TOPSIS. Moreover, it makes the relative closeness degree fluctuate within a small-amplitude. The results conform to the practical condition of China's energy regulation and therefore the E-M-TOPSIS is favorably applicable for the external performance appraisal of energy regulation. Additionally, the external economic performance and social responsibility performance (including environmental and energy safety performances) based on the E-M-TOPSIS exhibit significantly different fluctuation trends. The external economic performance dramatically fluctuates with a larger fluctuation amplitude, while the social responsibility performance exhibits a relatively stable interval fluctuation. This indicates that compared to the social responsibility performance, the fluctuation of external economic performance is more sensitive to energy regulation.

Correlations of multiscale entropy in the FX market

NASA Astrophysics Data System (ADS)

Stosic, Darko; Stosic, Dusan; Ludermir, Teresa; Stosic, Tatijana

2016-09-01

The regularity of price fluctuations in exchange rates plays a crucial role in FX market dynamics. Distinct variations in regularity arise from economic, social and political events, such as interday trading and financial crisis. This paper applies a multiscale time-dependent entropy method on thirty-three exchange rates to analyze price fluctuations in the FX. Correlation matrices of entropy values, termed entropic correlations, are in turn used to describe global behavior of the market. Empirical results suggest a weakly correlated market with pronounced collective behavior at bi-weekly trends. Correlations arise from cycles of low and high regularity in long-term trends. Eigenvalues of the correlation matrix also indicate a dominant European market, followed by shifting American, Asian, African, and Pacific influences. As a result, we find that entropy is a powerful tool for extracting important information from the FX market.

Some New Properties of Quantum Correlations

NASA Astrophysics Data System (ADS)

Liu, Feng; Li, Fei; Wei, Yunxia

2017-02-01

Quantum coherence measures the correlation between different measurement results in a single-system, while entanglement and quantum discord measure the correlation among different subsystems in a multipartite system. In this paper, we focus on the relative entropy form of them, and obtain three new properties of them as follows: 1) General forms of maximally coherent states for the relative entropy coherence, 2) Linear monogamy of the relative entropy entanglement, and 3) Subadditivity of quantum discord. Here, the linear monogamy is defined as there is a small constant as the upper bound on the sum of the relative entropy entanglement in subsystems.

Action and entanglement in gravity and field theory.

PubMed

Neiman, Yasha

2013-12-27

In nongravitational quantum field theory, the entanglement entropy across a surface depends on the short-distance regularization. Quantum gravity should not require such regularization, and it has been conjectured that the entanglement entropy there is always given by the black hole entropy formula evaluated on the entangling surface. We show that these statements have precise classical counterparts at the level of the action. Specifically, we point out that the action can have a nonadditive imaginary part. In gravity, the latter is fixed by the black hole entropy formula, while in nongravitating theories it is arbitrary. From these classical facts, the entanglement entropy conjecture follows by heuristically applying the relation between actions and wave functions.

Entropy and long-range memory in random symbolic additive Markov chains

NASA Astrophysics Data System (ADS)

Melnik, S. S.; Usatenko, O. V.

2016-06-01

The goal of this paper is to develop an estimate for the entropy of random symbolic sequences with elements belonging to a finite alphabet. As a plausible model, we use the high-order additive stationary ergodic Markov chain with long-range memory. Supposing that the correlations between random elements of the chain are weak, we express the conditional entropy of the sequence by means of the symbolic pair correlation function. We also examine an algorithm for estimating the conditional entropy of finite symbolic sequences. We show that the entropy contains two contributions, i.e., the correlation and the fluctuation. The obtained analytical results are used for numerical evaluation of the entropy of written English texts and DNA nucleotide sequences. The developed theory opens the way for constructing a more consistent and sophisticated approach to describe the systems with strong short-range and weak long-range memory.

Entropy and long-range memory in random symbolic additive Markov chains.

PubMed

Melnik, S S; Usatenko, O V

2016-06-01

The goal of this paper is to develop an estimate for the entropy of random symbolic sequences with elements belonging to a finite alphabet. As a plausible model, we use the high-order additive stationary ergodic Markov chain with long-range memory. Supposing that the correlations between random elements of the chain are weak, we express the conditional entropy of the sequence by means of the symbolic pair correlation function. We also examine an algorithm for estimating the conditional entropy of finite symbolic sequences. We show that the entropy contains two contributions, i.e., the correlation and the fluctuation. The obtained analytical results are used for numerical evaluation of the entropy of written English texts and DNA nucleotide sequences. The developed theory opens the way for constructing a more consistent and sophisticated approach to describe the systems with strong short-range and weak long-range memory.

Correlation and agreement between the bispectral index vs. state entropy during hypothermic cardio-pulmonary bypass.

PubMed

Meybohm, P; Gruenewald, M; Höcker, J; Renner, J; Graesner, J-T; Ilies, C; Scholz, J; Bein, B

2010-02-01

The bispectral index (BIS) and spectral entropy enable monitoring the depth of anaesthesia. Mild hypothermia has been shown to affect the ability of electroencephalography monitors to reflect the anaesthetic drug effect. The purpose of this study was to investigate the effect of hypothermia during a cardio-pulmonary bypass on the correlation and agreement between the BIS and entropy variables compared with normothermic conditions. This prospective clinical study included coronary artery bypass grafting patients (n=25) evaluating correlation and agreement (Bland-Altman analysis) between the BIS and both spectral and response entropy during a hypothermic cardio-pulmonary bypass (31-34 degrees C) compared with nomothermic conditions (34-37.5 degrees C). Anaesthesia was maintained with propofol and sufentanil and adjusted clinically, while the anaesthetist was blinded to the monitors. The BIS and entropy values decreased during cooling (P<0.05), but the decrease was more pronounced for entropy variables compared with BIS (P<0.05). The correlation coefficients (bias+/-SD; percentage error) between the BIS vs. spectral state entropy and response entropy were r(2)=0.56 (1+/-11; 42%) and r(2)=0.58 (-2+/-11; 43%) under normothermic conditions, and r(2)=0.17 (10+/-12; 77%) and r(2)=0.18 (9+/-11; 68%) under hypothermic conditions, respectively. Bias was significantly increased under hypothermic conditions (P<0.001 vs. normothermia). Acceptable agreement was observed between the BIS and entropy variables under normothermic but not under hypothermic conditions. The BIS and entropy variables may therefore not be interchangeable during a hypothermic cardio-pulmonary bypass.

From atomic structure to excess entropy: a neutron diffraction and density functional theory study of CaO-Al2O3-SiO2 melts

NASA Astrophysics Data System (ADS)

Liu, Maoyuan; Jacob, Aurélie; Schmetterer, Clemens; Masset, Patrick J.; Hennet, Louis; Fischer, Henry E.; Kozaily, Jad; Jahn, Sandro; Gray-Weale, Angus

2016-04-01

Calcium aluminosilicate \\text{CaO}-\\text{A}{{\\text{l}}2}{{\\text{O}}3}-\\text{Si}{{\\text{O}}2} (CAS) melts with compositions {{≤ft(\\text{CaO}-\\text{Si}{{\\text{O}}2}\\right)}x}{{≤ft(\\text{A}{{\\text{l}}2}{{\\text{O}}3}\\right)}1-x} for x  <  0.5 and {{≤ft(\\text{A}{{\\text{l}}2}{{\\text{O}}3}\\right)}x}{{≤ft(\\text{Si}{{\\text{O}}2}\\right)}1-x} for x≥slant 0.5 are studied using neutron diffraction with aerodynamic levitation and density functional theory molecular dynamics modelling. Simulated structure factors are found to be in good agreement with experimental structure factors. Local atomic structures from simulations reveal the role of calcium cations as a network modifier, and aluminium cations as a non-tetrahedral network former. Distributions of tetrahedral order show that an increasing concentration of the network former Al increases entropy, while an increasing concentration of the network modifier Ca decreases entropy. This trend is opposite to the conventional understanding that increasing amounts of network former should increase order in the network liquid, and so decrease entropy. The two-body correlation entropy S 2 is found to not correlate with the excess entropy values obtained from thermochemical databases, while entropies including higher-order correlations such as tetrahedral order, O-M-O or M-O-M bond angles and Q N environments show a clear linear correlation between computed entropy and database excess entropy. The possible relationship between atomic structures and excess entropy is discussed.

Measuring Gaussian quantum information and correlations using the Rényi entropy of order 2.

PubMed

Adesso, Gerardo; Girolami, Davide; Serafini, Alessio

2012-11-09

We demonstrate that the Rényi-2 entropy provides a natural measure of information for any multimode Gaussian state of quantum harmonic systems, operationally linked to the phase-space Shannon sampling entropy of the Wigner distribution of the state. We prove that, in the Gaussian scenario, such an entropy satisfies the strong subadditivity inequality, a key requirement for quantum information theory. This allows us to define and analyze measures of Gaussian entanglement and more general quantum correlations based on such an entropy, which are shown to satisfy relevant properties such as monogamy.

Contraction coefficients for noisy quantum channels

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hiai, Fumio, E-mail: hiai.fumio@gmail.com; Ruskai, Mary Beth, E-mail: ruskai@member.ams.org

Generalized relative entropy, monotone Riemannian metrics, geodesic distance, and trace distance are all known to decrease under the action of quantum channels. We give some new bounds on, and relationships between, the maximal contraction for these quantities.

Binarized cross-approximate entropy in crowdsensing environment.

PubMed

Skoric, Tamara; Mohamoud, Omer; Milovanovic, Branislav; Japundzic-Zigon, Nina; Bajic, Dragana

2017-01-01

Personalised monitoring in health applications has been recognised as part of the mobile crowdsensing concept, where subjects equipped with sensors extract information and share them for personal or common benefit. Limited transmission resources impose the use of local analyses methodology, but this approach is incompatible with analytical tools that require stationary and artefact-free data. This paper proposes a computationally efficient binarised cross-approximate entropy, referred to as (X)BinEn, for unsupervised cardiovascular signal processing in environments where energy and processor resources are limited. The proposed method is a descendant of the cross-approximate entropy ((X)ApEn). It operates on binary, differentially encoded data series split into m-sized vectors. The Hamming distance is used as a distance measure, while a search for similarities is performed on the vector sets. The procedure is tested on rats under shaker and restraint stress, and compared to the existing (X)ApEn results. The number of processing operations is reduced. (X)BinEn captures entropy changes in a similar manner to (X)ApEn. The coding coarseness yields an adverse effect of reduced sensitivity, but it attenuates parameter inconsistency and binary bias. A special case of (X)BinEn is equivalent to Shannon's entropy. A binary conditional entropy for m =1 vectors is embedded into the (X)BinEn procedure. (X)BinEn can be applied to a single time series as an auto-entropy method, or to a pair of time series, as a cross-entropy method. Its low processing requirements makes it suitable for mobile, battery operated, self-attached sensing devices, with limited power and processor resources. Copyright © 2016 Elsevier Ltd. All rights reserved.

Entropy Driven Self-Assembly in Charged Lock-Key Particles.

PubMed

Odriozola, Gerardo; Lozada-Cassou, Marcelo

2016-07-07

In this work we study the lock-key model successfully used in supramolecular chemistry and particles self-assembly and gain further insight into the infinite diluted limit of the lock and key, depletant mediated, effective attraction. We discuss the depletant forces and entropy approaches to self-assembly and give details on the different contributions to the net force for a charged lock and key pair immersed in a solvent plus a primitive model electrolyte. We show a strong correlation of the force components behavior and the underlying processes of co-ion and solvent release from the cavity. In addition, we put into context the universal behavior observed for the energy-distance curves when changing the lock and key to solvent size ratio. Basically, we now show that this behavior is not always achieved and depends on the particular system geometry. Finally, we present a qualitative good agreement with experiments when changing the electrolyte concentration, valence, and cavity-key size ratio.

Use of mutual information to decrease entropy: Implications for the second law of thermodynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lloyd, S.

1989-05-15

Several theorems on the mechanics of gathering information are proved, and the possibility of violating the second law of thermodynamics by obtaining information is discussed in light of these theorems. Maxwell's demon can lower the entropy of his surroundings by an amount equal to the difference between the maximum entropy of his recording device and its initial entropy, without generating a compensating entropy increase. A demon with human-scale recording devices can reduce the entropy of a gas by a negligible amount only, but the proof of the demon's impracticability leaves open the possibility that systems highly correlated with their environmentmore » can reduce the environment's entropy by a substantial amount without increasing entropy elsewhere. In the event that a boundary condition for the universe requires it to be in a state of low entropy when small, the correlations induced between different particle modes during the expansion phase allow the modes to behave like Maxwell's demons during the contracting phase, reducing the entropy of the universe to a low value.« less

Group entropies, correlation laws, and zeta functions.

PubMed

Tempesta, Piergiulio

2011-08-01

The notion of group entropy is proposed. It enables the unification and generaliztion of many different definitions of entropy known in the literature, such as those of Boltzmann-Gibbs, Tsallis, Abe, and Kaniadakis. Other entropic functionals are introduced, related to nontrivial correlation laws characterizing universality classes of systems out of equilibrium when the dynamics is weakly chaotic. The associated thermostatistics are discussed. The mathematical structure underlying our construction is that of formal group theory, which provides the general structure of the correlations among particles and dictates the associated entropic functionals. As an example of application, the role of group entropies in information theory is illustrated and generalizations of the Kullback-Leibler divergence are proposed. A new connection between statistical mechanics and zeta functions is established. In particular, Tsallis entropy is related to the classical Riemann zeta function.

On the relation between correlation dimension, approximate entropy and sample entropy parameters, and a fast algorithm for their calculation

NASA Astrophysics Data System (ADS)

Zurek, Sebastian; Guzik, Przemyslaw; Pawlak, Sebastian; Kosmider, Marcin; Piskorski, Jaroslaw

2012-12-01

We explore the relation between correlation dimension, approximate entropy and sample entropy parameters, which are commonly used in nonlinear systems analysis. Using theoretical considerations we identify the points which are shared by all these complexity algorithms and show explicitly that the above parameters are intimately connected and mutually interdependent. A new geometrical interpretation of sample entropy and correlation dimension is provided and the consequences for the interpretation of sample entropy, its relative consistency and some of the algorithms for parameter selection for this quantity are discussed. To get an exact algorithmic relation between the three parameters we construct a very fast algorithm for simultaneous calculations of the above, which uses the full time series as the source of templates, rather than the usual 10%. This algorithm can be used in medical applications of complexity theory, as it can calculate all three parameters for a realistic recording of 104 points within minutes with the use of an average notebook computer.

Entanglement of two blocks of spins in the critical Ising model

NASA Astrophysics Data System (ADS)

Facchi, P.; Florio, G.; Invernizzi, C.; Pascazio, S.

2008-11-01

We compute the entropy of entanglement of two blocks of L spins at a distance d in the ground state of an Ising chain in an external transverse magnetic field. We numerically study the von Neumann entropy for different values of the transverse field. At the critical point we obtain analytical results for blocks of size L=1 and 2. In the general case, the critical entropy is shown to be additive when d→∞ . Finally, based on simple arguments, we derive an expression for the entropy at the critical point as a function of both L and d . This formula is in excellent agreement with numerical results.

Conflict management based on belief function entropy in sensor fusion.

PubMed

Yuan, Kaijuan; Xiao, Fuyuan; Fei, Liguo; Kang, Bingyi; Deng, Yong

2016-01-01

Wireless sensor network plays an important role in intelligent navigation. It incorporates a group of sensors to overcome the limitation of single detection system. Dempster-Shafer evidence theory can combine the sensor data of the wireless sensor network by data fusion, which contributes to the improvement of accuracy and reliability of the detection system. However, due to different sources of sensors, there may be conflict among the sensor data under uncertain environment. Thus, this paper proposes a new method combining Deng entropy and evidence distance to address the issue. First, Deng entropy is adopted to measure the uncertain information. Then, evidence distance is applied to measure the conflict degree. The new method can cope with conflict effectually and improve the accuracy and reliability of the detection system. An example is illustrated to show the efficiency of the new method and the result is compared with that of the existing methods.

Histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging can predict histopathological findings including proliferation potential, cellularity, and nucleic areas in head and neck squamous cell carcinoma.

PubMed

Surov, Alexey; Meyer, Hans Jonas; Leifels, Leonard; Höhn, Anne-Kathrin; Richter, Cindy; Winter, Karsten

2018-04-20

Our purpose was to analyze possible associations between histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging DCE MRI and histopathological findings like proliferation index, cell count and nucleic areas in head and neck squamous cell carcinoma (HNSCC). 30 patients (mean age 57.0 years) with primary HNSCC were included in the study. In every case, histogram analysis parameters of K trans , V e , and K ep were estimated using a mathlab based software. Tumor proliferation index, cell count, and nucleic areas were estimated on Ki 67 antigen stained specimens. Spearman's non-parametric rank sum correlation coefficients were calculated between DCE and different histopathological parameters. KI 67 correlated with K trans min ( p = -0.386, P = 0.043) and s K trans skewness ( p = 0.382, P = 0.045), V e min ( p = -0.473, P = 0.011), Ve entropy ( p = 0.424, P = 0.025), and K ep entropy ( p = 0.464, P = 0.013). Cell count correlated with K trans kurtosis ( p = 0.40, P = 0.034), V e entropy ( p = 0.475, P = 0.011). Total nucleic area correlated with V e max ( p = 0.386, P = 0.042) and V e entropy ( p = 0.411, P = 0.030). In G1/2 tumors, only K trans entropy correlated well with total ( P =0.78, P =0.013) and average nucleic areas ( p = 0.655, P = 0.006). In G3 tumors, KI 67 correlated with Ve min ( p = -0.552, P = 0.022) and V e entropy ( p = 0.524, P = 0.031). Ve max correlated with total nucleic area ( p = 0.483, P = 0.049). Kep max correlated with total area ( p = -0.51, P = 0.037), and K ep entropy with KI 67 ( p = 0.567, P = 0.018). We concluded that histogram-based parameters skewness, kurtosis and entropy of K trans , V e , and K ep can be used as markers for proliferation activity, cellularity and nucleic content in HNSCC. Tumor grading influences significantly associations between perfusion and histopathological parameters.

Whole-Lesion Apparent Diffusion Coefficient-Based Entropy-Related Parameters for Characterizing Cervical Cancers: Initial Findings.

PubMed

Guan, Yue; Li, Weifeng; Jiang, Zhuoran; Chen, Ying; Liu, Song; He, Jian; Zhou, Zhengyang; Ge, Yun

2016-12-01

This study aimed to develop whole-lesion apparent diffusion coefficient (ADC)-based entropy-related parameters of cervical cancer to preliminarily assess intratumoral heterogeneity of this lesion in comparison to adjacent normal cervical tissues. A total of 51 women (mean age, 49 years) with cervical cancers confirmed by biopsy underwent 3-T pelvic diffusion-weighted magnetic resonance imaging with b values of 0 and 800 s/mm 2 prospectively. ADC-based entropy-related parameters including first-order entropy and second-order entropies were derived from the whole tumor volume as well as adjacent normal cervical tissues. Intraclass correlation coefficient, Wilcoxon test with Bonferroni correction, Kruskal-Wallis test, and receiver operating characteristic curve were used for statistical analysis. All the parameters showed excellent interobserver agreement (all intraclass correlation coefficients  > 0.900). Entropy, entropy(H) 0 , entropy(H) 45 , entropy(H) 90 , entropy(H) 135 , and entropy(H) mean were significantly higher, whereas entropy(H) range and entropy(H) std were significantly lower in cervical cancers compared to adjacent normal cervical tissues (all P <.0001). Kruskal-Wallis test showed that there were no significant differences among the values of various second-order entropies including entropy(H) 0, entropy(H) 45 , entropy(H) 90 , entropy(H) 135 , and entropy(H) mean. All second-order entropies had larger area under the receiver operating characteristic curve than first-order entropy in differentiating cervical cancers from adjacent normal cervical tissues. Further, entropy(H) 45 , entropy(H) 90 , entropy(H) 135 , and entropy(H) mean had the same largest area under the receiver operating characteristic curve of 0.867. Whole-lesion ADC-based entropy-related parameters of cervical cancers were developed successfully, which showed initial potential in characterizing intratumoral heterogeneity in comparison to adjacent normal cervical tissues. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

The External Performance Appraisal of China Energy Regulation: An Empirical Study Using a TOPSIS Method Based on Entropy Weight and Mahalanobis Distance

PubMed Central

Li, Dan-Dan; Zheng, Hong-Hao

2018-01-01

In China’s industrialization process, the effective regulation of energy and environment can promote the positive externality of energy consumption while reducing negative externality, which is an important means for realizing the sustainable development of an economic society. The study puts forward an improved technique for order preference by similarity to an ideal solution based on entropy weight and Mahalanobis distance (briefly referred as E-M-TOPSIS). The performance of the approach was verified to be satisfactory. By separately using traditional and improved TOPSIS methods, the study carried out the empirical appraisals on the external performance of China’s energy regulation during 1999~2015. The results show that the correlation between the performance indexes causes the significant difference between the appraisal results of E-M-TOPSIS and traditional TOPSIS. The E-M-TOPSIS takes the correlation between indexes into account and generally softens the closeness degree compared with traditional TOPSIS. Moreover, it makes the relative closeness degree fluctuate within a small-amplitude. The results conform to the practical condition of China’s energy regulation and therefore the E-M-TOPSIS is favorably applicable for the external performance appraisal of energy regulation. Additionally, the external economic performance and social responsibility performance (including environmental and energy safety performances) based on the E-M-TOPSIS exhibit significantly different fluctuation trends. The external economic performance dramatically fluctuates with a larger fluctuation amplitude, while the social responsibility performance exhibits a relatively stable interval fluctuation. This indicates that compared to the social responsibility performance, the fluctuation of external economic performance is more sensitive to energy regulation. PMID:29385781

The predictive power of singular value decomposition entropy for stock market dynamics

NASA Astrophysics Data System (ADS)

Caraiani, Petre

2014-01-01

We use a correlation-based approach to analyze financial data from the US stock market, both daily and monthly observations from the Dow Jones. We compute the entropy based on the singular value decomposition of the correlation matrix for the components of the Dow Jones Industrial Index. Based on a moving window, we derive time varying measures of entropy for both daily and monthly data. We find that the entropy has a predictive ability with respect to stock market dynamics as indicated by the Granger causality tests.

Inability of the entropy vector method to certify nonclassicality in linelike causal structures

NASA Astrophysics Data System (ADS)

Weilenmann, Mirjam; Colbeck, Roger

2016-10-01

Bell's theorem shows that our intuitive understanding of causation must be overturned in light of quantum correlations. Nevertheless, quantum mechanics does not permit signaling and hence a notion of cause remains. Understanding this notion is not only important at a fundamental level, but also for technological applications such as key distribution and randomness expansion. It has recently been shown that a useful way to decide which classical causal structures could give rise to a given set of correlations is to use entropy vectors. These are vectors whose components are the entropies of all subsets of the observed variables in the causal structure. The entropy vector method employs causal relationships among the variables to restrict the set of possible entropy vectors. Here, we consider whether the same approach can lead to useful certificates of nonclassicality within a given causal structure. Surprisingly, we find that for a family of causal structures that includes the usual bipartite Bell structure they do not. For all members of this family, no function of the entropies of the observed variables gives such a certificate, in spite of the existence of nonclassical correlations. It is therefore necessary to look beyond entropy vectors to understand cause from a quantum perspective.

A diameter-sensitive flow entropy method for reliability consideration in water distribution system design

NASA Astrophysics Data System (ADS)

Liu, Haixing; Savić, Dragan; Kapelan, Zoran; Zhao, Ming; Yuan, Yixing; Zhao, Hongbin

2014-07-01

Flow entropy is a measure of uniformity of pipe flows in water distribution systems. By maximizing flow entropy one can identify reliable layouts or connectivity in networks. In order to overcome the disadvantage of the common definition of flow entropy that does not consider the impact of pipe diameter on reliability, an extended definition of flow entropy, termed as diameter-sensitive flow entropy, is proposed. This new methodology is then assessed by using other reliability methods, including Monte Carlo Simulation, a pipe failure probability model, and a surrogate measure (resilience index) integrated with water demand and pipe failure uncertainty. The reliability assessment is based on a sample of WDS designs derived from an optimization process for each of the two benchmark networks. Correlation analysis is used to evaluate quantitatively the relationship between entropy and reliability. To ensure reliability, a comparative analysis between the flow entropy and the new method is conducted. The results demonstrate that the diameter-sensitive flow entropy shows consistently much stronger correlation with the three reliability measures than simple flow entropy. Therefore, the new flow entropy method can be taken as a better surrogate measure for reliability and could be potentially integrated into the optimal design problem of WDSs. Sensitivity analysis results show that the velocity parameters used in the new flow entropy has no significant impact on the relationship between diameter-sensitive flow entropy and reliability.

Learning Probabilities From Random Observables in High Dimensions: The Maximum Entropy Distribution and Others

NASA Astrophysics Data System (ADS)

Obuchi, Tomoyuki; Cocco, Simona; Monasson, Rémi

2015-11-01

We consider the problem of learning a target probability distribution over a set of N binary variables from the knowledge of the expectation values (with this target distribution) of M observables, drawn uniformly at random. The space of all probability distributions compatible with these M expectation values within some fixed accuracy, called version space, is studied. We introduce a biased measure over the version space, which gives a boost increasing exponentially with the entropy of the distributions and with an arbitrary inverse `temperature' Γ . The choice of Γ allows us to interpolate smoothly between the unbiased measure over all distributions in the version space (Γ =0) and the pointwise measure concentrated at the maximum entropy distribution (Γ → ∞ ). Using the replica method we compute the volume of the version space and other quantities of interest, such as the distance R between the target distribution and the center-of-mass distribution over the version space, as functions of α =(log M)/N and Γ for large N. Phase transitions at critical values of α are found, corresponding to qualitative improvements in the learning of the target distribution and to the decrease of the distance R. However, for fixed α the distance R does not vary with Γ which means that the maximum entropy distribution is not closer to the target distribution than any other distribution compatible with the observable values. Our results are confirmed by Monte Carlo sampling of the version space for small system sizes (N≤ 10).

Entanglement entropy and correlations in loop quantum gravity

NASA Astrophysics Data System (ADS)

Feller, Alexandre; Livine, Etera R.

2018-02-01

Black hole entropy is one of the few windows into the quantum aspects of gravitation, and its study over the years has highlighted the holographic nature of gravity. At the non-perturbative level in quantum gravity, promising explanations are being explored in terms of the entanglement entropy between regions of space. In the context of loop quantum gravity, this translates into an analysis of the correlations between the regions of the spin network states defining the quantum state of the geometry of space. In this paper, we explore a class of states, motivated by results in condensed matter physics, satisfying an area law for entanglement entropy and having non-trivial correlations. We highlight that entanglement comes from holonomy operators acting on loops crossing the boundary of the region.

Entropy, complexity, and Markov diagrams for random walk cancer models.

PubMed

Newton, Paul K; Mason, Jeremy; Hurt, Brian; Bethel, Kelly; Bazhenova, Lyudmila; Nieva, Jorge; Kuhn, Peter

2014-12-19

The notion of entropy is used to compare the complexity associated with 12 common cancers based on metastatic tumor distribution autopsy data. We characterize power-law distributions, entropy, and Kullback-Liebler divergence associated with each primary cancer as compared with data for all cancer types aggregated. We then correlate entropy values with other measures of complexity associated with Markov chain dynamical systems models of progression. The Markov transition matrix associated with each cancer is associated with a directed graph model where nodes are anatomical locations where a metastatic tumor could develop, and edge weightings are transition probabilities of progression from site to site. The steady-state distribution corresponds to the autopsy data distribution. Entropy correlates well with the overall complexity of the reduced directed graph structure for each cancer and with a measure of systemic interconnectedness of the graph, called graph conductance. The models suggest that grouping cancers according to their entropy values, with skin, breast, kidney, and lung cancers being prototypical high entropy cancers, stomach, uterine, pancreatic and ovarian being mid-level entropy cancers, and colorectal, cervical, bladder, and prostate cancers being prototypical low entropy cancers, provides a potentially useful framework for viewing metastatic cancer in terms of predictability, complexity, and metastatic potential.

Entropy, complexity, and Markov diagrams for random walk cancer models

NASA Astrophysics Data System (ADS)

Newton, Paul K.; Mason, Jeremy; Hurt, Brian; Bethel, Kelly; Bazhenova, Lyudmila; Nieva, Jorge; Kuhn, Peter

2014-12-01

The notion of entropy is used to compare the complexity associated with 12 common cancers based on metastatic tumor distribution autopsy data. We characterize power-law distributions, entropy, and Kullback-Liebler divergence associated with each primary cancer as compared with data for all cancer types aggregated. We then correlate entropy values with other measures of complexity associated with Markov chain dynamical systems models of progression. The Markov transition matrix associated with each cancer is associated with a directed graph model where nodes are anatomical locations where a metastatic tumor could develop, and edge weightings are transition probabilities of progression from site to site. The steady-state distribution corresponds to the autopsy data distribution. Entropy correlates well with the overall complexity of the reduced directed graph structure for each cancer and with a measure of systemic interconnectedness of the graph, called graph conductance. The models suggest that grouping cancers according to their entropy values, with skin, breast, kidney, and lung cancers being prototypical high entropy cancers, stomach, uterine, pancreatic and ovarian being mid-level entropy cancers, and colorectal, cervical, bladder, and prostate cancers being prototypical low entropy cancers, provides a potentially useful framework for viewing metastatic cancer in terms of predictability, complexity, and metastatic potential.

CT Texture Analysis of Ex Vivo Renal Stones Predicts Ease of Fragmentation with Shockwave Lithotripsy.

PubMed

Cui, Helen W; Devlies, Wout; Ravenscroft, Samuel; Heers, Hendrik; Freidin, Andrew J; Cleveland, Robin O; Ganeshan, Balaji; Turney, Benjamin W

2017-07-01

Understanding the factors affecting success of extracorporeal shockwave lithotripsy (SWL) would improve informed decision-making on the most appropriate treatment modality for an individual patient. Although stone size and skin-to-stone distance do correlate with fragmentation efficacy, it has been shown that stone composition and architecture, as reflected by structural heterogeneity on CT, are also important factors. This study aims to determine if CT texture analysis (CTTA), a novel, nondestructive, and objective tool that generates statistical metrics reflecting stone heterogeneity, could have utility in predicting likelihood of SWL success. Seven spontaneously passed, intact renal tract stones, were scanned ex vivo using standard CT KUB and micro-CT. The stones were then fragmented in vitro using a clinical lithotripter, after which, chemical composition analysis was performed. CTTA was used to generate a number of metrics that were correlated to the number of shocks needed to fragment the stone. CTTA metrics reflected stone characteristics and composition, and predicted ease of SWL fragmentation. The strongest correlation with number of shocks required to fragment the stone was mean Hounsfield unit (HU) density (r = 0.806, p = 0.028) and a CTTA metric measuring the entropy of the pixel distribution of the stone image (r = 0.804, p = 0.039). Using multiple linear regression analysis, the best model showed that CTTA metrics of entropy and kurtosis could predict 92% of the outcome of number of shocks needed to fragment the stone. This was superior to using stone volume or density. CTTA metrics entropy and kurtosis have been shown in this experimental ex vivo setting to strongly predict fragmentation by SWL. This warrants further investigation in a larger clinical study for the contribution of CT textural metrics as a measure of stone heterogeneity, along with other known clinical factors, to predict likelihood of SWL success.

Refined two-index entropy and multiscale analysis for complex system

NASA Astrophysics Data System (ADS)

Bian, Songhan; Shang, Pengjian

2016-10-01

As a fundamental concept in describing complex system, entropy measure has been proposed to various forms, like Boltzmann-Gibbs (BG) entropy, one-index entropy, two-index entropy, sample entropy, permutation entropy etc. This paper proposes a new two-index entropy Sq,δ and we find the new two-index entropy is applicable to measure the complexity of wide range of systems in the terms of randomness and fluctuation range. For more complex system, the value of two-index entropy is smaller and the correlation between parameter δ and entropy Sq,δ is weaker. By combining the refined two-index entropy Sq,δ with scaling exponent h(δ), this paper analyzes the complexities of simulation series and classifies several financial markets in various regions of the world effectively.

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities.

PubMed

Sik, Hin Hung; Gao, Junling; Fan, Jicong; Wu, Bonnie Wai Yan; Leung, Hang Kin; Hung, Yeung Sam

2017-05-10

In both the East and West, traditional teachings say that the mind and heart are somehow closely correlated, especially during spiritual practice. One difficulty in proving this objectively is that the natures of brain and heart activities are quite different. In this paper, we propose a methodology that uses wavelet entropy to measure the chaotic levels of both electroencephalogram (EEG) and electrocardiogram (ECG) data and show how this may be used to explore the potential coordination between the mind and heart under different experimental conditions. Furthermore, Statistical Parametric Mapping (SPM) was used to identify the brain regions in which the EEG wavelet entropy was the most affected by the experimental conditions. As an illustration, the EEG and ECG were recorded under two different conditions (normal rest and mindful breathing) at the beginning of an 8-week standard Mindfulness-based Stress Reduction (MBSR) training course (pretest) and after the course (posttest). Using the proposed method, the results consistently showed that the wavelet entropy of the brain EEG decreased during the MBSR mindful breathing state as compared to that during the closed-eye resting state. Similarly, a lower wavelet entropy of heartrate was found during MBSR mindful breathing. However, no difference in wavelet entropy during MBSR mindful breathing was found between the pretest and posttest. No correlation was observed between the entropy of brain waves and the entropy of heartrate during normal rest in all participants, whereas a significant correlation was observed during MBSR mindful breathing. Additionally, the most well-correlated brain regions were located in the central areas of the brain. This study provides a methodology for the establishment of evidence that mindfulness practice (i.e., mindful breathing) may increase the coordination between mind and heart activities.

Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

PubMed Central

Sik, Hin Hung; Gao, Junling; Fan, Jicong; Wu, Bonnie Wai Yan; Leung, Hang Kin; Hung, Yeung Sam

2017-01-01

In both the East and West, traditional teachings say that the mind and heart are somehow closely correlated, especially during spiritual practice. One difficulty in proving this objectively is that the natures of brain and heart activities are quite different. In this paper, we propose a methodology that uses wavelet entropy to measure the chaotic levels of both electroencephalogram (EEG) and electrocardiogram (ECG) data and show how this may be used to explore the potential coordination between the mind and heart under different experimental conditions. Furthermore, Statistical Parametric Mapping (SPM) was used to identify the brain regions in which the EEG wavelet entropy was the most affected by the experimental conditions. As an illustration, the EEG and ECG were recorded under two different conditions (normal rest and mindful breathing) at the beginning of an 8-week standard Mindfulness-based Stress Reduction (MBSR) training course (pretest) and after the course (posttest). Using the proposed method, the results consistently showed that the wavelet entropy of the brain EEG decreased during the MBSR mindful breathing state as compared to that during the closed-eye resting state. Similarly, a lower wavelet entropy of heartrate was found during MBSR mindful breathing. However, no difference in wavelet entropy during MBSR mindful breathing was found between the pretest and posttest. No correlation was observed between the entropy of brain waves and the entropy of heartrate during normal rest in all participants, whereas a significant correlation was observed during MBSR mindful breathing. Additionally, the most well-correlated brain regions were located in the central areas of the brain. This study provides a methodology for the establishment of evidence that mindfulness practice (i.e., mindful breathing) may increase the coordination between mind and heart activities. PMID:28518101

Influence of model errors in optimal sensor placement

NASA Astrophysics Data System (ADS)

Vincenzi, Loris; Simonini, Laura

2017-02-01

The paper investigates the role of model errors and parametric uncertainties in optimal or near optimal sensor placements for structural health monitoring (SHM) and modal testing. The near optimal set of measurement locations is obtained by the Information Entropy theory; the results of placement process considerably depend on the so-called covariance matrix of prediction error as well as on the definition of the correlation function. A constant and an exponential correlation function depending on the distance between sensors are firstly assumed; then a proposal depending on both distance and modal vectors is presented. With reference to a simple case-study, the effect of model uncertainties on results is described and the reliability and the robustness of the proposed correlation function in the case of model errors are tested with reference to 2D and 3D benchmark case studies. A measure of the quality of the obtained sensor configuration is considered through the use of independent assessment criteria. In conclusion, the results obtained by applying the proposed procedure on a real 5-spans steel footbridge are described. The proposed method also allows to better estimate higher modes when the number of sensors is greater than the number of modes of interest. In addition, the results show a smaller variation in the sensor position when uncertainties occur.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Maoyuan; Besford, Quinn Alexander; Mulvaney, Thomas

The entropy of hydrophobic solvation has been explained as the result of ordered solvation structures, of hydrogen bonds, of the small size of the water molecule, of dispersion forces, and of solvent density fluctuations. We report a new approach to the calculation of the entropy of hydrophobic solvation, along with tests of and comparisons to several other methods. The methods are assessed in the light of the available thermodynamic and spectroscopic information on the effects of temperature on hydrophobic solvation. Five model hydrophobes in SPC/E water give benchmark solvation entropies via Widom’s test-particle insertion method, and other methods and modelsmore » are tested against these particle-insertion results. Entropies associated with distributions of tetrahedral order, of electric field, and of solvent dipole orientations are examined. We find these contributions are small compared to the benchmark particle-insertion entropy. Competitive with or better than other theories in accuracy, but with no free parameters, is the new estimate of the entropy contributed by correlations between dipole moments. Dipole correlations account for most of the hydrophobic solvation entropy for all models studied and capture the distinctive temperature dependence seen in thermodynamic and spectroscopic experiments. Entropies based on pair and many-body correlations in number density approach the correct magnitudes but fail to describe temperature and size dependences, respectively. Hydrogen-bond definitions and free energies that best reproduce entropies from simulations are reported, but it is difficult to choose one hydrogen bond model that fits a variety of experiments. The use of information theory, scaled-particle theory, and related methods is discussed briefly. Our results provide a test of the Frank-Evans hypothesis that the negative solvation entropy is due to structured water near the solute, complement the spectroscopic detection of that solvation structure by identifying the structural feature responsible for the entropy change, and point to a possible explanation for the observed dependence on length scale. Our key results are that the hydrophobic effect, i.e. the signature, temperature-dependent, solvation entropy of nonpolar molecules in water, is largely due to a dispersion force arising from correlations between rotating permanent dipole moments, that the strength of this force depends on the Kirkwood g-factor, and that the strength of this force may be obtained exactly without simulation.« less

Entropy as an indicator of cerebral perfusion in patients with increased intracranial pressure.

PubMed

Khan, James; Mariappan, Ramamani; Venkatraghavan, Lashmi

2014-07-01

Changes in electroencephalogram (EEG) patterns correlate well with changes in cerebral perfusion pressure (CPP) and hence entropy and bispectral index values may also correlate with CPP. To highlight the potential application of entropy, an EEG-based anesthetic depth monitor, on indicating cerebral perfusion in patients with increased intracranial pressure (ICP), we report two cases of emergency neurosurgical procedure in patients with raised ICP where anesthesia was titrated to entropy values and the entropy values suddenly increased after cranial decompression, reflecting the increase in CPP. Maintaining systemic blood pressure in order to maintain the CPP is the anesthetic goal while managing patients with raised ICP. EEG-based anesthetic depth monitors may hold valuable information on guiding anesthetic management in patients with decreased CPP for better neurological outcome.

RNA Thermodynamic Structural Entropy

PubMed Central

Garcia-Martin, Juan Antonio; Clote, Peter

2015-01-01

Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV absorption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs). However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, such as the repression of heat shock gene expression (ROSE) element, we determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and we plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner’99 and Turner’04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. Source code is available at https://github.com/clotelab/RNAentropy/; a full web server is available at http://bioinformatics.bc.edu/clotelab/RNAentropy, including source code and ancillary programs. PMID:26555444

RNA Thermodynamic Structural Entropy.

PubMed

Garcia-Martin, Juan Antonio; Clote, Peter

2015-01-01

Conformational entropy for atomic-level, three dimensional biomolecules is known experimentally to play an important role in protein-ligand discrimination, yet reliable computation of entropy remains a difficult problem. Here we describe the first two accurate and efficient algorithms to compute the conformational entropy for RNA secondary structures, with respect to the Turner energy model, where free energy parameters are determined from UV absorption experiments. An algorithm to compute the derivational entropy for RNA secondary structures had previously been introduced, using stochastic context free grammars (SCFGs). However, the numerical value of derivational entropy depends heavily on the chosen context free grammar and on the training set used to estimate rule probabilities. Using data from the Rfam database, we determine that both of our thermodynamic methods, which agree in numerical value, are substantially faster than the SCFG method. Thermodynamic structural entropy is much smaller than derivational entropy, and the correlation between length-normalized thermodynamic entropy and derivational entropy is moderately weak to poor. In applications, we plot the structural entropy as a function of temperature for known thermoswitches, such as the repression of heat shock gene expression (ROSE) element, we determine that the correlation between hammerhead ribozyme cleavage activity and total free energy is improved by including an additional free energy term arising from conformational entropy, and we plot the structural entropy of windows of the HIV-1 genome. Our software RNAentropy can compute structural entropy for any user-specified temperature, and supports both the Turner'99 and Turner'04 energy parameters. It follows that RNAentropy is state-of-the-art software to compute RNA secondary structure conformational entropy. Source code is available at https://github.com/clotelab/RNAentropy/; a full web server is available at http://bioinformatics.bc.edu/clotelab/RNAentropy, including source code and ancillary programs.

Entropy Transfer between Residue Pairs and Allostery in Proteins: Quantifying Allosteric Communication in Ubiquitin.

PubMed

Hacisuleyman, Aysima; Erman, Burak

2017-01-01

It has recently been proposed by Gunasakaran et al. that allostery may be an intrinsic property of all proteins. Here, we develop a computational method that can determine and quantify allosteric activity in any given protein. Based on Schreiber's transfer entropy formulation, our approach leads to an information transfer landscape for the protein that shows the presence of entropy sinks and sources and explains how pairs of residues communicate with each other using entropy transfer. The model can identify the residues that drive the fluctuations of others. We apply the model to Ubiquitin, whose allosteric activity has not been emphasized until recently, and show that there are indeed systematic pathways of entropy and information transfer between residues that correlate well with the activities of the protein. We use 600 nanosecond molecular dynamics trajectories for Ubiquitin and its complex with human polymerase iota and evaluate entropy transfer between all pairs of residues of Ubiquitin and quantify the binding susceptibility changes upon complex formation. We explain the complex formation propensities of Ubiquitin in terms of entropy transfer. Important residues taking part in allosteric communication in Ubiquitin predicted by our approach are in agreement with results of NMR relaxation dispersion experiments. Finally, we show that time delayed correlation of fluctuations of two interacting residues possesses an intrinsic causality that tells which residue controls the interaction and which one is controlled. Our work shows that time delayed correlations, entropy transfer and causality are the required new concepts for explaining allosteric communication in proteins.

Relationship between structural and dynamic properties of Al-rich Al-Cu melts: Beyond the Stokes-Einstein relation

NASA Astrophysics Data System (ADS)

Jakse, N.; Pasturel, A.

2016-12-01

We perform ab initio molecular dynamics simulations to study structural and transport properties in liquid A l1 -xC ux alloys, with copper composition x ≤0.4 , in relation to the applicability of the Stokes-Einstein (SE) equation in these melts. To begin, we find that self-diffusion coefficients and viscosity are composition dependent, while their temperature dependence follows an Arrhenius-type behavior, except for x =0.4 at low temperature. Then, we find that the applicability of the SE equation is also composition dependent, and its breakdown in the liquid regime above the liquidus temperature can be related to different local ordering around each species. In this case, we emphasize the difficulty of extracting effective atomic radii from interatomic distances found in liquid phases, but we see a clear correlation between transport properties and local ordering described through the structural entropy approximated by the two-body contribution. We use these findings to reformulate the SE equation within the framework of Rosenfeld's scaling law in terms of partial structural entropies, and we demonstrate that the breakdown of the SE relation can be related to their temperature dependence. Finally, we also use this framework to derive a simple relation between the ratio of the self-diffusivities of the components and the ratio of their partial structural entropies.

Generalized sample entropy analysis for traffic signals based on similarity measure

NASA Astrophysics Data System (ADS)

Shang, Du; Xu, Mengjia; Shang, Pengjian

2017-05-01

Sample entropy is a prevailing method used to quantify the complexity of a time series. In this paper a modified method of generalized sample entropy and surrogate data analysis is proposed as a new measure to assess the complexity of a complex dynamical system such as traffic signals. The method based on similarity distance presents a different way of signals patterns match showing distinct behaviors of complexity. Simulations are conducted over synthetic data and traffic signals for providing the comparative study, which is provided to show the power of the new method. Compared with previous sample entropy and surrogate data analysis, the new method has two main advantages. The first one is that it overcomes the limitation about the relationship between the dimension parameter and the length of series. The second one is that the modified sample entropy functions can be used to quantitatively distinguish time series from different complex systems by the similar measure.

Entropy, energy, and entanglement of localized states in bent triatomic molecules

NASA Astrophysics Data System (ADS)

Yuan, Qiang; Hou, Xi-Wen

2017-05-01

The dynamics of quantum entropy, energy, and entanglement is studied for various initial states in an important spectroscopic Hamiltonian of bent triatomic molecules H2O, D2O, and H2S. The total quantum correlation is quantified in terms of the mutual information and the entanglement by the concurrence borrowed from the theory of quantum information. The Pauli entropy and the intramolecular energy usually used in the theory of molecules are calculated to establish a possible relationship between both theories. Sections of two quantities among these four quantities are introduced to visualize such relationship. Analytic and numerical simulations demonstrate that if an initial state is taken to be the stretch- or the bend-vibrationally localized state, the mutual information, the Pauli entropy, and the concurrence are dominant-positively correlated while they are dominantly anti-correlated with the interacting energy among three anharmonic vibrational modes. In particular, such correlation is more distinct for the localized state with high excitations in the bending mode. The nice quasi-periodicity of those quantities in D2O molecule reveals that this molecule prepared in the localized state in the stretching or the bending mode can be more appreciated for molecular quantum computation. However, the dynamical correlations of those quantities behave irregularly for the dislocalized states. Moreover, the hierarchy of the mutual information and the Pauli entropy is explicitly proved. Quantum entropy and energy in every vibrational mode are investigated. Thereby, the relation between bipartite and tripartite entanglements is discussed as well. Those are useful for the understanding of quantum correlations in high-dimensional states in polyatomic molecules from quantum information and intramolecular dynamics.

Germinal center texture entropy as possible indicator of humoral immune response: immunophysiology viewpoint.

PubMed

Pantic, Igor; Pantic, Senka

2012-10-01

In this article, we present the results indicating that spleen germinal center (GC) texture entropy determined by gray-level co-occurrence matrix (GLCM) method is related to humoral immune response. Spleen tissue was obtained from eight outbred male short-haired guinea pigs previously immunized by sheep red blood cells (SRBC). A total of 312 images from 39 germinal centers (156 GC light zone images and 156 GC dark zone images) were acquired and analyzed by GLCM method. Angular second moment, contrast, correlation, entropy, and inverse difference moment were calculated for each image. Humoral immune response to SRBC was measured using T cell-dependent antibody response (TDAR) assay. Statistically highly significant negative correlation was detected between light zone entropy and the number of TDAR plaque-forming cells (r (s) = -0.86, p < 0.01). The entropy decreased as the plaque-forming cells increased and vice versa. A statistically significant negative correlation was also detected between dark zone entropy values and the number of plaque-forming cells (r (s) = -0.69, p < 0.05). Germinal center texture entropy may be a powerful indicator of humoral immune response. This study is one of the first to point out the potential scientific value of GLCM image texture analysis in lymphoid tissue cytoarchitecture evaluation. Lymphoid tissue texture analysis could become an important and affordable addition to the conventional immunophysiology techniques.

Entropy, complexity, and Markov diagrams for random walk cancer models

PubMed Central

Newton, Paul K.; Mason, Jeremy; Hurt, Brian; Bethel, Kelly; Bazhenova, Lyudmila; Nieva, Jorge; Kuhn, Peter

2014-01-01

The notion of entropy is used to compare the complexity associated with 12 common cancers based on metastatic tumor distribution autopsy data. We characterize power-law distributions, entropy, and Kullback-Liebler divergence associated with each primary cancer as compared with data for all cancer types aggregated. We then correlate entropy values with other measures of complexity associated with Markov chain dynamical systems models of progression. The Markov transition matrix associated with each cancer is associated with a directed graph model where nodes are anatomical locations where a metastatic tumor could develop, and edge weightings are transition probabilities of progression from site to site. The steady-state distribution corresponds to the autopsy data distribution. Entropy correlates well with the overall complexity of the reduced directed graph structure for each cancer and with a measure of systemic interconnectedness of the graph, called graph conductance. The models suggest that grouping cancers according to their entropy values, with skin, breast, kidney, and lung cancers being prototypical high entropy cancers, stomach, uterine, pancreatic and ovarian being mid-level entropy cancers, and colorectal, cervical, bladder, and prostate cancers being prototypical low entropy cancers, provides a potentially useful framework for viewing metastatic cancer in terms of predictability, complexity, and metastatic potential. PMID:25523357

Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods

NASA Astrophysics Data System (ADS)

He, Jiayi; Shang, Pengjian; Xiong, Hui

2018-06-01

Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.

Defense Standardization Program Journal, January/March 2013

DTIC Science & Technology

2013-03-01

image plane , representing half the distance across the iris along the horizontal Pupil-to-iris ratio Degree to which the pupil is dilated or constricted... the Poincare indices, ori- entation zone coherences, entropy of local orientations, and core orien- tation field masks Number of deltas Detected deltas...based on the combination of the Poincare indices, ori- entation zone coherences, entropy of local orientations, and delta ori- entation field masks

Thermodynamics of an ideal generalized gas: II. Means of order alpha.

PubMed

Lavenda, B H

2005-11-01

The property that power means are monotonically increasing functions of their order is shown to be the basis of the second laws not only for processes involving heat conduction, but also for processes involving deformations. This generalizes earlier work involving only pure heat conduction and underlines the incomparability of the internal energy and adiabatic potentials when expressed as powers of the adiabatic variable. In an L-potential equilibration, the final state will be one of maximum entropy, whereas in an entropy equilibration, the final state will be one of minimum L. Unlike classical equilibrium thermodynamic phase space, which lacks an intrinsic metric structure insofar as distances and other geometrical concepts do not have an intrinsic thermodynamic significance in such spaces, a metric space can be constructed for the power means: the distance between means of different order is related to the Carnot efficiency. In the ideal classical gas limit, the average change in the entropy is shown to be proportional to the difference between the Shannon and Rényi entropies for nonextensive systems that are multifractal in nature. The L potential, like the internal energy, is a Schur convex function of the empirical temperature, which satisfies Jensen's inequality, and serves as a measure of the tendency to uniformity in processes involving pure thermal conduction.

Entropy Transfer between Residue Pairs and Allostery in Proteins: Quantifying Allosteric Communication in Ubiquitin

PubMed Central

2017-01-01

It has recently been proposed by Gunasakaran et al. that allostery may be an intrinsic property of all proteins. Here, we develop a computational method that can determine and quantify allosteric activity in any given protein. Based on Schreiber's transfer entropy formulation, our approach leads to an information transfer landscape for the protein that shows the presence of entropy sinks and sources and explains how pairs of residues communicate with each other using entropy transfer. The model can identify the residues that drive the fluctuations of others. We apply the model to Ubiquitin, whose allosteric activity has not been emphasized until recently, and show that there are indeed systematic pathways of entropy and information transfer between residues that correlate well with the activities of the protein. We use 600 nanosecond molecular dynamics trajectories for Ubiquitin and its complex with human polymerase iota and evaluate entropy transfer between all pairs of residues of Ubiquitin and quantify the binding susceptibility changes upon complex formation. We explain the complex formation propensities of Ubiquitin in terms of entropy transfer. Important residues taking part in allosteric communication in Ubiquitin predicted by our approach are in agreement with results of NMR relaxation dispersion experiments. Finally, we show that time delayed correlation of fluctuations of two interacting residues possesses an intrinsic causality that tells which residue controls the interaction and which one is controlled. Our work shows that time delayed correlations, entropy transfer and causality are the required new concepts for explaining allosteric communication in proteins. PMID:28095404

A dipole moment of the microwave background as a cosmological effect

NASA Astrophysics Data System (ADS)

Paczynski, Bohdan; Piran, Tsvi

1990-12-01

A spherically symmetrical Tolman-Bondi cosmological model is presented in which the curvature of space and the entropy variety with distance from the center. The dipole and quadrupole moments in the distribution of the microwave background radiation are calculated as a function of cosmic time and position of an observer, assuming that the distance to the horizon is much smaller than any characteristic scale in the model. The quadrupole moment is found to be affected mostly by the gradient in the curvature of space while the dipole moment is dominated by the gradient of entropy. The results indicate that the observed dipole in the microwave background may be cosmological in origin. Observational tests of this argument are suggested.

Chemical complexity induced local structural distortion in NiCoFeMnCr high-entropy alloy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Fuxiang; Tong, Yang; Jin, Ke

In order to study chemical complexity-induced lattice distortion in high-entropy alloys, the static Debye–Waller (D-W) factor of NiCoFeMnCr solid solution alloy is measured with low temperature neutron diffraction, ambient X-ray diffraction, and total scattering methods. Here, the static atomic displacement parameter of the multi-element component alloy at 0 K is 0.035–0.041 Å, which is obvious larger than that of element Ni (~0 Å). The atomic pair distance between individual atoms in the alloy investigated with extended X-ray absorption fine structure (EXAFS) measurements indicates that Mn has a slightly larger bond distance (~0.4%) with neighbor atoms than that of others.

Chemical complexity induced local structural distortion in NiCoFeMnCr high-entropy alloy

DOE PAGES

Zhang, Fuxiang; Tong, Yang; Jin, Ke; ...

2018-06-16

In order to study chemical complexity-induced lattice distortion in high-entropy alloys, the static Debye–Waller (D-W) factor of NiCoFeMnCr solid solution alloy is measured with low temperature neutron diffraction, ambient X-ray diffraction, and total scattering methods. Here, the static atomic displacement parameter of the multi-element component alloy at 0 K is 0.035–0.041 Å, which is obvious larger than that of element Ni (~0 Å). The atomic pair distance between individual atoms in the alloy investigated with extended X-ray absorption fine structure (EXAFS) measurements indicates that Mn has a slightly larger bond distance (~0.4%) with neighbor atoms than that of others.

A dipole moment of the microwave background as a cosmological effect

NASA Technical Reports Server (NTRS)

Paczynski, Bohdan; Piran, Tsvi

1990-01-01

A spherically symmetrical Tolman-Bondi cosmological model is presented in which the curvature of space and the entropy variety with distance from the center. The dipole and quadrupole moments in the distribution of the microwave background radiation are calculated as a function of cosmic time and position of an observer, assuming that the distance to the horizon is much smaller than any characteristic scale in the model. The quadrupole moment is found to be affected mostly by the gradient in the curvature of space while the dipole moment is dominated by the gradient of entropy. The results indicate that the observed dipole in the microwave background may be cosmological in origin. Observational tests of this argument are suggested.

Entanglement entropy in the long-range Kitaev chain

NASA Astrophysics Data System (ADS)

Ares, Filiberto; Esteve, José G.; Falceto, Fernando; de Queiroz, Amilcar R.

2018-06-01

In this paper we complete the study on the asymptotic behavior of the entanglement entropy for Kitaev chains with long-range pairing. We discover that when the couplings decay with the distance with a critical exponent new properties for the asymptotic growth of the entropy appear. The coefficient of the leading term is not universal any more and the connection with conformal field theories is lost. We perform a numerical and analytical approach to the problem showing a perfect agreement. In order to carry out the analytical study, a technique for computing the asymptotic behavior of block Toeplitz determinants with discontinuous symbols has been developed.

Entropy-Based Registration of Point Clouds Using Terrestrial Laser Scanning and Smartphone GPS.

PubMed

Chen, Maolin; Wang, Siying; Wang, Mingwei; Wan, Youchuan; He, Peipei

2017-01-20

Automatic registration of terrestrial laser scanning point clouds is a crucial but unresolved topic that is of great interest in many domains. This study combines terrestrial laser scanner with a smartphone for the coarse registration of leveled point clouds with small roll and pitch angles and height differences, which is a novel sensor combination mode for terrestrial laser scanning. The approximate distance between two neighboring scan positions is firstly calculated with smartphone GPS coordinates. Then, 2D distribution entropy is used to measure the distribution coherence between the two scans and search for the optimal initial transformation parameters. To this end, we propose a method called Iterative Minimum Entropy (IME) to correct initial transformation parameters based on two criteria: the difference between the average and minimum entropy and the deviation from the minimum entropy to the expected entropy. Finally, the presented method is evaluated using two data sets that contain tens of millions of points from panoramic and non-panoramic, vegetation-dominated and building-dominated cases and can achieve high accuracy and efficiency.

Hidden messenger revealed in Hawking radiation: A resolution to the paradox of black hole information loss

NASA Astrophysics Data System (ADS)

Zhang, Baocheng; Cai, Qing-yu; You, Li; Zhan, Ming-sheng

2009-05-01

Using standard statistical method, we discover the existence of correlations among Hawking radiations (of tunneled particles) from a black hole. The information carried by such correlations is quantified by mutual information between sequential emissions. Through a careful counting of the entropy taken out by the emitted particles, we show that the black hole radiation as tunneling is an entropy conservation process. While information is leaked out through the radiation, the total entropy is conserved. Thus, we conclude the black hole evaporation process is unitary.

Archaeon and archaeal virus diversity classification via sequence entropy and fractal dimension

NASA Astrophysics Data System (ADS)

Tremberger, George, Jr.; Gallardo, Victor; Espinoza, Carola; Holden, Todd; Gadura, N.; Cheung, E.; Schneider, P.; Lieberman, D.; Cheung, T.

2010-09-01

Archaea are important potential candidates in astrobiology as their metabolism includes solar, inorganic and organic energy sources. Archaeal viruses would also be expected to be present in a sustainable archaeal exobiological community. Genetic sequence Shannon entropy and fractal dimension can be used to establish a two-dimensional measure for classification and phylogenetic study of these organisms. A sequence fractal dimension can be calculated from a numerical series consisting of the atomic numbers of each nucleotide. Archaeal 16S and 23S ribosomal RNA sequences were studied. Outliers in the 16S rRNA fractal dimension and entropy plot were found to be halophilic archaea. Positive correlation (R-square ~ 0.75, N = 18) was observed between fractal dimension and entropy across the studied species. The 16S ribosomal RNA sequence entropy correlates with the 23S ribosomal RNA sequence entropy across species with R-square 0.93, N = 18. Entropy values correspond positively with branch lengths of a published phylogeny. The studied archaeal virus sequences have high fractal dimensions of 2.02 or more. A comparison of selected extremophile sequences with archaeal sequences from the Humboldt Marine Ecosystem database (Wood-Hull Oceanography Institute, MIT) suggests the presence of continuous sequence expression as inferred from distributions of entropy and fractal dimension, consistent with the diversity expected in an exobiological archaeal community.

Noise and complexity in human postural control: interpreting the different estimations of entropy.

PubMed

Rhea, Christopher K; Silver, Tobin A; Hong, S Lee; Ryu, Joong Hyun; Studenka, Breanna E; Hughes, Charmayne M L; Haddad, Jeffrey M

2011-03-17

Over the last two decades, various measures of entropy have been used to examine the complexity of human postural control. In general, entropy measures provide information regarding the health, stability and adaptability of the postural system that is not captured when using more traditional analytical techniques. The purpose of this study was to examine how noise, sampling frequency and time series length influence various measures of entropy when applied to human center of pressure (CoP) data, as well as in synthetic signals with known properties. Such a comparison is necessary to interpret data between and within studies that use different entropy measures, equipment, sampling frequencies or data collection durations. The complexity of synthetic signals with known properties and standing CoP data was calculated using Approximate Entropy (ApEn), Sample Entropy (SampEn) and Recurrence Quantification Analysis Entropy (RQAEn). All signals were examined at varying sampling frequencies and with varying amounts of added noise. Additionally, an increment time series of the original CoP data was examined to remove long-range correlations. Of the three measures examined, ApEn was the least robust to sampling frequency and noise manipulations. Additionally, increased noise led to an increase in SampEn, but a decrease in RQAEn. Thus, noise can yield inconsistent results between the various entropy measures. Finally, the differences between the entropy measures were minimized in the increment CoP data, suggesting that long-range correlations should be removed from CoP data prior to calculating entropy. The various algorithms typically used to quantify the complexity (entropy) of CoP may yield very different results, particularly when sampling frequency and noise are different. The results of this study are discussed within the context of the neural noise and loss of complexity hypotheses.

The Impact of Entropy on the Spatial Organization of Synaptonemal Complexes within the Cell Nucleus

PubMed Central

Fritsche, Miriam; Reinholdt, Laura G.; Lessard, Mark; Handel, Mary Ann; Bewersdorf, Jörg; Heermann, Dieter W.

2012-01-01

We employ 4Pi-microscopy to study SC organization in mouse spermatocyte nuclei allowing for the three-dimensional reconstruction of the SC's backbone arrangement. Additionally, we model the SCs in the cell nucleus by confined, self-avoiding polymers, whose chain ends are attached to the envelope of the confining cavity and diffuse along it. This work helps to elucidate the role of entropy in shaping pachytene SC organization. The framework provided by the complex interplay between SC polymer rigidity, tethering and confinement is able to qualitatively explain features of SC organization, such as mean squared end-to-end distances, mean squared center-of-mass distances, or SC density distributions. However, it fails in correctly assessing SC entanglement within the nucleus. In fact, our analysis of the 4Pi-microscopy images reveals a higher ordering of SCs within the nuclear volume than what is expected by our numerical model. This suggests that while effects of entropy impact SC organization, the dedicated action of proteins or actin cables is required to fine-tune the spatial ordering of SCs within the cell nucleus. PMID:22574147

On the relationship between NMR-derived amide order parameters and protein backbone entropy changes

PubMed Central

Sharp, Kim A.; O’Brien, Evan; Kasinath, Vignesh; Wand, A. Joshua

2015-01-01

Molecular dynamics simulations are used to analyze the relationship between NMR-derived squared generalized order parameters of amide NH groups and backbone entropy. Amide order parameters (O2NH) are largely determined by the secondary structure and average values appear unrelated to the overall flexibility of the protein. However, analysis of the more flexible subset (O2NH < 0.8) shows that these report both on the local flexibility of the protein and on a different component of the conformational entropy than that reported by the side chain methyl axis order parameters, O2axis. A calibration curve for backbone entropy vs. O2NH is developed which accounts for both correlations between amide group motions of different residues, and correlations between backbone and side chain motions. This calibration curve can be used with experimental values of O2NH changes obtained by NMR relaxation measurements to extract backbone entropy changes, e.g. upon ligand binding. In conjunction with our previous calibration for side chain entropy derived from measured O2axis values this provides a prescription for determination of the total protein conformational entropy changes from NMR relaxation measurements. PMID:25739366

On the relationship between NMR-derived amide order parameters and protein backbone entropy changes.

PubMed

Sharp, Kim A; O'Brien, Evan; Kasinath, Vignesh; Wand, A Joshua

2015-05-01

Molecular dynamics simulations are used to analyze the relationship between NMR-derived squared generalized order parameters of amide NH groups and backbone entropy. Amide order parameters (O(2) NH ) are largely determined by the secondary structure and average values appear unrelated to the overall flexibility of the protein. However, analysis of the more flexible subset (O(2) NH  < 0.8) shows that these report both on the local flexibility of the protein and on a different component of the conformational entropy than that reported by the side chain methyl axis order parameters, O(2) axis . A calibration curve for backbone entropy vs. O(2) NH is developed, which accounts for both correlations between amide group motions of different residues, and correlations between backbone and side chain motions. This calibration curve can be used with experimental values of O(2) NH changes obtained by NMR relaxation measurements to extract backbone entropy changes, for example, upon ligand binding. In conjunction with our previous calibration for side chain entropy derived from measured O(2) axis values this provides a prescription for determination of the total protein conformational entropy changes from NMR relaxation measurements. © 2015 Wiley Periodicals, Inc.

Entanglement entropy between real and virtual particles in ϕ4 quantum field theory

NASA Astrophysics Data System (ADS)

Ardenghi, Juan Sebastián

2015-04-01

The aim of this work is to compute the entanglement entropy of real and virtual particles by rewriting the generating functional of ϕ4 theory as a mean value between states and observables defined through the correlation functions. Then the von Neumann definition of entropy can be applied to these quantum states and in particular, for the partial traces taken over the internal or external degrees of freedom. This procedure can be done for each order in the perturbation expansion showing that the entanglement entropy for real and virtual particles behaves as ln (m0). In particular, entanglement entropy is computed at first order for the correlation function of two external points showing that mutual information is identical to the external entropy and that conditional entropies are negative for all the domain of m0. In turn, from the definition of the quantum states, it is possible to obtain general relations between total traces between different quantum states of a ϕr theory. Finally, discussion about the possibility of taking partial traces over external degrees of freedom is considered, which implies the introduction of some observables that measure space-time points where an interaction occurs.

Entropic criterion for model selection

NASA Astrophysics Data System (ADS)

Tseng, Chih-Yuan

2006-10-01

Model or variable selection is usually achieved through ranking models according to the increasing order of preference. One of methods is applying Kullback-Leibler distance or relative entropy as a selection criterion. Yet that will raise two questions, why use this criterion and are there any other criteria. Besides, conventional approaches require a reference prior, which is usually difficult to get. Following the logic of inductive inference proposed by Caticha [Relative entropy and inductive inference, in: G. Erickson, Y. Zhai (Eds.), Bayesian Inference and Maximum Entropy Methods in Science and Engineering, AIP Conference Proceedings, vol. 707, 2004 (available from arXiv.org/abs/physics/0311093)], we show relative entropy to be a unique criterion, which requires no prior information and can be applied to different fields. We examine this criterion by considering a physical problem, simple fluids, and results are promising.

Excess entropy scaling for the segmental and global dynamics of polyethylene melts.

PubMed

Voyiatzis, Evangelos; Müller-Plathe, Florian; Böhm, Michael C

2014-11-28

The range of validity of the Rosenfeld and Dzugutov excess entropy scaling laws is analyzed for unentangled linear polyethylene chains. We consider two segmental dynamical quantities, i.e. the bond and the torsional relaxation times, and two global ones, i.e. the chain diffusion coefficient and the viscosity. The excess entropy is approximated by either a series expansion of the entropy in terms of the pair correlation function or by an equation of state for polymers developed in the context of the self associating fluid theory. For the whole range of temperatures and chain lengths considered, the two estimates of the excess entropy are linearly correlated. The scaled bond and torsional relaxation times fall into a master curve irrespective of the chain length and the employed scaling scheme. Both quantities depend non-linearly on the excess entropy. For a fixed chain length, the reduced diffusion coefficient and viscosity scale linearly with the excess entropy. An empirical reduction to a chain length-independent master curve is accessible for both dynamic quantities. The Dzugutov scheme predicts an increased value of the scaled diffusion coefficient with increasing chain length which contrasts physical expectations. The origin of this trend can be traced back to the density dependence of the scaling factors. This finding has not been observed previously for Lennard-Jones chain systems (Macromolecules, 2013, 46, 8710-8723). Thus, it limits the applicability of the Dzugutov approach to polymers. In connection with diffusion coefficients and viscosities, the Rosenfeld scaling law appears to be of higher quality than the Dzugutov approach. An empirical excess entropy scaling is also proposed which leads to a chain length-independent correlation. It is expected to be valid for polymers in the Rouse regime.

A scale-entropy diffusion equation to describe the multi-scale features of turbulent flames near a wall

NASA Astrophysics Data System (ADS)

Queiros-Conde, D.; Foucher, F.; Mounaïm-Rousselle, C.; Kassem, H.; Feidt, M.

2008-12-01

Multi-scale features of turbulent flames near a wall display two kinds of scale-dependent fractal features. In scale-space, an unique fractal dimension cannot be defined and the fractal dimension of the front is scale-dependent. Moreover, when the front approaches the wall, this dependency changes: fractal dimension also depends on the wall-distance. Our aim here is to propose a general geometrical framework that provides the possibility to integrate these two cases, in order to describe the multi-scale structure of turbulent flames interacting with a wall. Based on the scale-entropy quantity, which is simply linked to the roughness of the front, we thus introduce a general scale-entropy diffusion equation. We define the notion of “scale-evolutivity” which characterises the deviation of a multi-scale system from the pure fractal behaviour. The specific case of a constant “scale-evolutivity” over the scale-range is studied. In this case, called “parabolic scaling”, the fractal dimension is a linear function of the logarithm of scale. The case of a constant scale-evolutivity in the wall-distance space implies that the fractal dimension depends linearly on the logarithm of the wall-distance. We then verified experimentally, that parabolic scaling represents a good approximation of the real multi-scale features of turbulent flames near a wall.

Detection of biomarkers for Hepatocellular Carcinoma using a hybrid univariate gene selection methods

PubMed Central

2012-01-01

Background Discovering new biomarkers has a great role in improving early diagnosis of Hepatocellular carcinoma (HCC). The experimental determination of biomarkers needs a lot of time and money. This motivates this work to use in-silico prediction of biomarkers to reduce the number of experiments required for detecting new ones. This is achieved by extracting the most representative genes in microarrays of HCC. Results In this work, we provide a method for extracting the differential expressed genes, up regulated ones, that can be considered candidate biomarkers in high throughput microarrays of HCC. We examine the power of several gene selection methods (such as Pearson’s correlation coefficient, Cosine coefficient, Euclidean distance, Mutual information and Entropy with different estimators) in selecting informative genes. A biological interpretation of the highly ranked genes is done using KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, ENTREZ and DAVID (Database for Annotation, Visualization, and Integrated Discovery) databases. The top ten genes selected using Pearson’s correlation coefficient and Cosine coefficient contained six genes that have been implicated in cancer (often multiple cancers) genesis in previous studies. A fewer number of genes were obtained by the other methods (4 genes using Mutual information, 3genes using Euclidean distance and only one gene using Entropy). A better result was obtained by the utilization of a hybrid approach based on intersecting the highly ranked genes in the output of all investigated methods. This hybrid combination yielded seven genes (2 genes for HCC and 5 genes in different types of cancer) in the top ten genes of the list of intersected genes. Conclusions To strengthen the effectiveness of the univariate selection methods, we propose a hybrid approach by intersecting several of these methods in a cascaded manner. This approach surpasses all of univariate selection methods when used individually according to biological interpretation and the examination of gene expression signal profiles. PMID:22867264

Information Entropy Production of Maximum Entropy Markov Chains from Spike Trains

NASA Astrophysics Data System (ADS)

Cofré, Rodrigo; Maldonado, Cesar

2018-01-01

We consider the maximum entropy Markov chain inference approach to characterize the collective statistics of neuronal spike trains, focusing on the statistical properties of the inferred model. We review large deviations techniques useful in this context to describe properties of accuracy and convergence in terms of sampling size. We use these results to study the statistical fluctuation of correlations, distinguishability and irreversibility of maximum entropy Markov chains. We illustrate these applications using simple examples where the large deviation rate function is explicitly obtained for maximum entropy models of relevance in this field.

EEG artifacts reduction by multivariate empirical mode decomposition and multiscale entropy for monitoring depth of anaesthesia during surgery.

PubMed

Liu, Quan; Chen, Yi-Feng; Fan, Shou-Zen; Abbod, Maysam F; Shieh, Jiann-Shing

2017-08-01

Electroencephalography (EEG) has been widely utilized to measure the depth of anaesthesia (DOA) during operation. However, the EEG signals are usually contaminated by artifacts which have a consequence on the measured DOA accuracy. In this study, an effective and useful filtering algorithm based on multivariate empirical mode decomposition and multiscale entropy (MSE) is proposed to measure DOA. Mean entropy of MSE is used as an index to find artifacts-free intrinsic mode functions. The effect of different levels of artifacts on the performances of the proposed filtering is analysed using simulated data. Furthermore, 21 patients' EEG signals are collected and analysed using sample entropy to calculate the complexity for monitoring DOA. The correlation coefficients of entropy and bispectral index (BIS) results show 0.14 ± 0.30 and 0.63 ± 0.09 before and after filtering, respectively. Artificial neural network (ANN) model is used for range mapping in order to correlate the measurements with BIS. The ANN method results show strong correlation coefficient (0.75 ± 0.08). The results in this paper verify that entropy values and BIS have a strong correlation for the purpose of DOA monitoring and the proposed filtering method can effectively filter artifacts from EEG signals. The proposed method performs better than the commonly used wavelet denoising method. This study provides a fully adaptive and automated filter for EEG to measure DOA more accuracy and thus reduce risk related to maintenance of anaesthetic agents.

Analysis of Microstructure and Sliding Wear Behavior of Co1.5CrFeNi1.5Ti0.5 High-Entropy Alloy

NASA Astrophysics Data System (ADS)

Lentzaris, K.; Poulia, A.; Georgatis, E.; Lekatou, A. G.; Karantzalis, A. E.

2018-04-01

Α Co1.5CrFeNi1.5Ti0.5 high-entropy alloy (HEA) of the well-known family of CoCrFeNiTi has been designed using empirical parameters. The aim of this design was the production of a HEA with fcc structure that gives ductile behavior and also high strength because of the solid solution effect. The VEC calculations (8.1) supported the fcc structure while the δ factor calculations (4.97) not being out of the limit values, advised a significant lattice distortion. From the other hand, the ΔΗ mix calculations (- 9.64 kJ/mol) gave strong indications that no intermetallic would be formed. In order to investigate its potential application, the Co1.5CrFeNi1.5Ti0.5 HEA was prepared by vacuum arc melting and a primary assessment of its surface degradation response was conducted by means of sliding wear testing using different counterbody systems for a total sliding distance of 1000 m. An effort to correlate the alloy's wear response with the microstructural characteristics was attempted. Finally, the wear behavior of the Co1.5CrFeNi1.5Ti0.5 HEA was compared with that of two commercially used wear-resistant alloys. The results obtained provided some first signs of the high-entropy alloys' better wear performance when tested under sliding conditions against a steel ball.

Time-series analysis of sleep wake stage of rat EEG using time-dependent pattern entropy

NASA Astrophysics Data System (ADS)

Ishizaki, Ryuji; Shinba, Toshikazu; Mugishima, Go; Haraguchi, Hikaru; Inoue, Masayoshi

2008-05-01

We performed electroencephalography (EEG) for six male Wistar rats to clarify temporal behaviors at different levels of consciousness. Levels were identified both by conventional sleep analysis methods and by our novel entropy method. In our method, time-dependent pattern entropy is introduced, by which EEG is reduced to binary symbolic dynamics and the pattern of symbols in a sliding temporal window is considered. A high correlation was obtained between level of consciousness as measured by the conventional method and mean entropy in our entropy method. Mean entropy was maximal while awake (stage W) and decreased as sleep deepened. These results suggest that time-dependent pattern entropy may offer a promising method for future sleep research.

Entanglement entropy of dispersive media from thermodynamic entropy in one higher dimension.

PubMed

Maghrebi, M F; Reid, M T H

2015-04-17

A dispersive medium becomes entangled with zero-point fluctuations in the vacuum. We consider an arbitrary array of material bodies weakly interacting with a quantum field and compute the quantum mutual information between them. It is shown that the mutual information in D dimensions can be mapped to classical thermodynamic entropy in D+1 dimensions. As a specific example, we compute the mutual information both analytically and numerically for a range of separation distances between two bodies in D=2 dimensions and find a logarithmic correction to the area law at short separations. A key advantage of our method is that it allows the strong subadditivity property to be easily verified.

Classic maximum entropy recovery of the average joint distribution of apparent FRET efficiency and fluorescence photons for single-molecule burst measurements.

PubMed

DeVore, Matthew S; Gull, Stephen F; Johnson, Carey K

2012-04-05

We describe a method for analysis of single-molecule Förster resonance energy transfer (FRET) burst measurements using classic maximum entropy. Classic maximum entropy determines the Bayesian inference for the joint probability describing the total fluorescence photons and the apparent FRET efficiency. The method was tested with simulated data and then with DNA labeled with fluorescent dyes. The most probable joint distribution can be marginalized to obtain both the overall distribution of fluorescence photons and the apparent FRET efficiency distribution. This method proves to be ideal for determining the distance distribution of FRET-labeled biomolecules, and it successfully predicts the shape of the recovered distributions.

Machine learning with quantum relative entropy

NASA Astrophysics Data System (ADS)

Tsuda, Koji

2009-12-01

Density matrices are a central tool in quantum physics, but it is also used in machine learning. A positive definite matrix called kernel matrix is used to represent the similarities between examples. Positive definiteness assures that the examples are embedded in an Euclidean space. When a positive definite matrix is learned from data, one has to design an update rule that maintains the positive definiteness. Our update rule, called matrix exponentiated gradient update, is motivated by the quantum relative entropy. Notably, the relative entropy is an instance of Bregman divergences, which are asymmetric distance measures specifying theoretical properties of machine learning algorithms. Using the calculus commonly used in quantum physics, we prove an upperbound of the generalization error of online learning.

Markov and non-Markov processes in complex systems by the dynamical information entropy

NASA Astrophysics Data System (ADS)

Yulmetyev, R. M.; Gafarov, F. M.

1999-12-01

We consider the Markov and non-Markov processes in complex systems by the dynamical information Shannon entropy (DISE) method. The influence and important role of the two mutually dependent channels of entropy alternation (creation or generation of correlation) and anti-correlation (destroying or annihilation of correlation) have been discussed. The developed method has been used for the analysis of the complex systems of various natures: slow neutron scattering in liquid cesium, psychology (short-time numeral and pattern human memory and effect of stress on the dynamical taping-test), random dynamics of RR-intervals in human ECG (problem of diagnosis of various disease of the human cardio-vascular systems), chaotic dynamics of the parameters of financial markets and ecological systems.

DNA viewed as an out-of-equilibrium structure

NASA Astrophysics Data System (ADS)

Provata, A.; Nicolis, C.; Nicolis, G.

2014-05-01

The complexity of the primary structure of human DNA is explored using methods from nonequilibrium statistical mechanics, dynamical systems theory, and information theory. A collection of statistical analyses is performed on the DNA data and the results are compared with sequences derived from different stochastic processes. The use of χ2 tests shows that DNA can not be described as a low order Markov chain of order up to r =6. Although detailed balance seems to hold at the level of a binary alphabet, it fails when all four base pairs are considered, suggesting spatial asymmetry and irreversibility. Furthermore, the block entropy does not increase linearly with the block size, reflecting the long-range nature of the correlations in the human genomic sequences. To probe locally the spatial structure of the chain, we study the exit distances from a specific symbol, the distribution of recurrence distances, and the Hurst exponent, all of which show power law tails and long-range characteristics. These results suggest that human DNA can be viewed as a nonequilibrium structure maintained in its state through interactions with a constantly changing environment. Based solely on the exit distance distribution accounting for the nonequilibrium statistics and using the Monte Carlo rejection sampling method, we construct a model DNA sequence. This method allows us to keep both long- and short-range statistical characteristics of the native DNA data. The model sequence presents the same characteristic exponents as the natural DNA but fails to capture spatial correlations and point-to-point details.

DNA viewed as an out-of-equilibrium structure.

PubMed

Provata, A; Nicolis, C; Nicolis, G

2014-05-01

The complexity of the primary structure of human DNA is explored using methods from nonequilibrium statistical mechanics, dynamical systems theory, and information theory. A collection of statistical analyses is performed on the DNA data and the results are compared with sequences derived from different stochastic processes. The use of χ^{2} tests shows that DNA can not be described as a low order Markov chain of order up to r=6. Although detailed balance seems to hold at the level of a binary alphabet, it fails when all four base pairs are considered, suggesting spatial asymmetry and irreversibility. Furthermore, the block entropy does not increase linearly with the block size, reflecting the long-range nature of the correlations in the human genomic sequences. To probe locally the spatial structure of the chain, we study the exit distances from a specific symbol, the distribution of recurrence distances, and the Hurst exponent, all of which show power law tails and long-range characteristics. These results suggest that human DNA can be viewed as a nonequilibrium structure maintained in its state through interactions with a constantly changing environment. Based solely on the exit distance distribution accounting for the nonequilibrium statistics and using the Monte Carlo rejection sampling method, we construct a model DNA sequence. This method allows us to keep both long- and short-range statistical characteristics of the native DNA data. The model sequence presents the same characteristic exponents as the natural DNA but fails to capture spatial correlations and point-to-point details.

Gauge field entanglement in Kitaev's honeycomb model

NASA Astrophysics Data System (ADS)

Dóra, Balázs; Moessner, Roderich

2018-01-01

A spin fractionalizes into matter and gauge fermions in Kitaev's spin liquid on the honeycomb lattice. This follows from a Jordan-Wigner mapping to fermions, allowing for the construction of a minimal entropy ground-state wave function on the cylinder. We use this to calculate the entanglement entropy by choosing several distinct partitionings. First, by partitioning an infinite cylinder into two, the -ln2 topological entanglement entropy is reconfirmed. Second, the reduced density matrix of the gauge sector on the full cylinder is obtained after tracing out the matter degrees of freedom. This allows for evaluating the gauge entanglement Hamiltonian, which contains infinitely long-range correlations along the symmetry axis of the cylinder. The matter-gauge entanglement entropy is (Ny-1 )ln2 , with Ny the circumference of the cylinder. Third, the rules for calculating the gauge sector entanglement of any partition are determined. Rather small correctly chosen gauge partitions can still account for the topological entanglement entropy in spite of long-range correlations in the gauge entanglement Hamiltonian.

Information Entropy Analysis of the H1N1 Genetic Code

NASA Astrophysics Data System (ADS)

Martwick, Andy

2010-03-01

During the current H1N1 pandemic, viral samples are being obtained from large numbers of infected people world-wide and are being sequenced on the NCBI Influenza Virus Resource Database. The information entropy of the sequences was computed from the probability of occurrence of each nucleotide base at every position of each set of sequences using Shannon's definition of information entropy, [ H=∑bpb,2( 1pb ) ] where H is the observed information entropy at each nucleotide position and pb is the probability of the base pair of the nucleotides A, C, G, U. Information entropy of the current H1N1 pandemic is compared to reference human and swine H1N1 entropy. As expected, the current H1N1 entropy is in a low entropy state and has a very large mutation potential. Using the entropy method in mature genes we can identify low entropy regions of nucleotides that generally correlate to critical protein function.

Resting state fMRI entropy probes complexity of brain activity in adults with ADHD.

PubMed

Sokunbi, Moses O; Fung, Wilson; Sawlani, Vijay; Choppin, Sabine; Linden, David E J; Thome, Johannes

2013-12-30

In patients with attention deficit hyperactivity disorder (ADHD), quantitative neuroimaging techniques have revealed abnormalities in various brain regions, including the frontal cortex, striatum, cerebellum, and occipital cortex. Nonlinear signal processing techniques such as sample entropy have been used to probe the regularity of brain magnetoencephalography signals in patients with ADHD. In the present study, we extend this technique to analyse the complex output patterns of the 4 dimensional resting state functional magnetic resonance imaging signals in adult patients with ADHD. After adjusting for the effect of age, we found whole brain entropy differences (P=0.002) between groups and negative correlation (r=-0.45) between symptom scores and mean whole brain entropy values, indicating lower complexity in patients. In the regional analysis, patients showed reduced entropy in frontal and occipital regions bilaterally and a significant negative correlation between the symptom scores and the entropy maps at a family-wise error corrected cluster level of P<0.05 (P=0.001, initial threshold). Our findings support the hypothesis of abnormal frontal-striatal-cerebellar circuits in ADHD and the suggestion that sample entropy is a useful tool in revealing abnormalities in the brain dynamics of patients with psychiatric disorders. © 2013 Elsevier Ireland Ltd. All rights reserved.

Characterizing time series via complexity-entropy curves

NASA Astrophysics Data System (ADS)

Ribeiro, Haroldo V.; Jauregui, Max; Zunino, Luciano; Lenzi, Ervin K.

2017-06-01

The search for patterns in time series is a very common task when dealing with complex systems. This is usually accomplished by employing a complexity measure such as entropies and fractal dimensions. However, such measures usually only capture a single aspect of the system dynamics. Here, we propose a family of complexity measures for time series based on a generalization of the complexity-entropy causality plane. By replacing the Shannon entropy by a monoparametric entropy (Tsallis q entropy) and after considering the proper generalization of the statistical complexity (q complexity), we build up a parametric curve (the q -complexity-entropy curve) that is used for characterizing and classifying time series. Based on simple exact results and numerical simulations of stochastic processes, we show that these curves can distinguish among different long-range, short-range, and oscillating correlated behaviors. Also, we verify that simulated chaotic and stochastic time series can be distinguished based on whether these curves are open or closed. We further test this technique in experimental scenarios related to chaotic laser intensity, stock price, sunspot, and geomagnetic dynamics, confirming its usefulness. Finally, we prove that these curves enhance the automatic classification of time series with long-range correlations and interbeat intervals of healthy subjects and patients with heart disease.

Canonical ensemble ground state and correlation entropy of Bose-Einstein condensate

NASA Astrophysics Data System (ADS)

Svidzinsky, Anatoly; Kim, Moochan; Agarwal, Girish; Scully, Marlan O.

2018-01-01

Constraint of a fixed total number of particles yields a correlation between the fluctuation of particles in different states in the canonical ensemble. Here we show that, below the temperature of Bose-Einstein condensation (BEC), the correlation part of the entropy of an ideal Bose gas is cancelled by the ground-state contribution. Thus, in the BEC region, the thermodynamic properties of the gas in the canonical ensemble can be described accurately in a simplified model which excludes the ground state and assumes no correlation between excited levels.

Entropy of network ensembles

NASA Astrophysics Data System (ADS)

Bianconi, Ginestra

2009-03-01

In this paper we generalize the concept of random networks to describe network ensembles with nontrivial features by a statistical mechanics approach. This framework is able to describe undirected and directed network ensembles as well as weighted network ensembles. These networks might have nontrivial community structure or, in the case of networks embedded in a given space, they might have a link probability with a nontrivial dependence on the distance between the nodes. These ensembles are characterized by their entropy, which evaluates the cardinality of networks in the ensemble. In particular, in this paper we define and evaluate the structural entropy, i.e., the entropy of the ensembles of undirected uncorrelated simple networks with given degree sequence. We stress the apparent paradox that scale-free degree distributions are characterized by having small structural entropy while they are so widely encountered in natural, social, and technological complex systems. We propose a solution to the paradox by proving that scale-free degree distributions are the most likely degree distribution with the corresponding value of the structural entropy. Finally, the general framework we present in this paper is able to describe microcanonical ensembles of networks as well as canonical or hidden-variable network ensembles with significant implications for the formulation of network-constructing algorithms.

An entropy-assisted musculoskeletal shoulder model.

PubMed

Xu, Xu; Lin, Jia-Hua; McGorry, Raymond W

2017-04-01

Optimization combined with a musculoskeletal shoulder model has been used to estimate mechanical loading of musculoskeletal elements around the shoulder. Traditionally, the objective function is to minimize the summation of the total activities of the muscles with forces, moments, and stability constraints. Such an objective function, however, tends to neglect the antagonist muscle co-contraction. In this study, an objective function including an entropy term is proposed to address muscle co-contractions. A musculoskeletal shoulder model is developed to apply the proposed objective function. To find the optimal weight for the entropy term, an experiment was conducted. In the experiment, participants generated various 3-D shoulder moments in six shoulder postures. The surface EMG of 8 shoulder muscles was measured and compared with the predicted muscle activities based on the proposed objective function using Bhattacharyya distance and concordance ratio under different weight of the entropy term. The results show that a small weight of the entropy term can improve the predictability of the model in terms of muscle activities. Such a result suggests that the concept of entropy could be helpful for further understanding the mechanism of muscle co-contractions as well as developing a shoulder biomechanical model with greater validity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Holographic entropy and real-time dynamics of quarkonium dissociation in non-Abelian plasma

DOE PAGES

Iatrakis, Ioannis; Kharzeev, Dmitri E.

2016-04-26

The peak of the heavy quark pair entropy at the deconfinement transition, observed in lattice QCD, suggests that the transition is effectively driven by the increase of the entropy of bound states. The growth of the entropy with the interquark distance leads to the emergent entropic force that induces dissociation of quarkonium states. Since the quark-gluon plasma around the transition point is a strongly coupled system, we use the gauge-gravity duality to study the entropy of heavy quarkonium and the real-time dynamics of its dissociation. In particular, we employ the improved holographic QCD model as a dual description of largemore » N c Yang-Mills theory. Studying the dynamics of the fundamental string between the quarks placed on the boundary, we find that the entropy peaks at the transition point. We also study the real-time dynamics of the system by considering the holographic string falling in the black hole horizon where it equilibrates. As a result, in the vicinity of the deconfinement transition, the dissociation time is found to be less than a fermi, suggesting that the entropic destruction is the dominant dissociation mechanism in this temperature region.« less

ECG contamination of EEG signals: effect on entropy.

PubMed

Chakrabarti, Dhritiman; Bansal, Sonia

2016-02-01

Entropy™ is a proprietary algorithm which uses spectral entropy analysis of electroencephalographic (EEG) signals to produce indices which are used as a measure of depth of hypnosis. We describe a report of electrocardiographic (ECG) contamination of EEG signals leading to fluctuating erroneous Entropy values. An explanation is provided for mechanism behind this observation by describing the spread of ECG signals in head and neck and its influence on EEG/Entropy by correlating the observation with the published Entropy algorithm. While the Entropy algorithm has been well conceived, there are still instances in which it can produce erroneous values. Such erroneous values and their cause may be identified by close scrutiny of the EEG waveform if Entropy values seem out of sync with that expected at given anaesthetic levels.

The structure and resilience of financial market networks

NASA Astrophysics Data System (ADS)

Kauê Dal'Maso Peron, Thomas; da Fontoura Costa, Luciano; Rodrigues, Francisco A.

2012-03-01

Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience.

Noise and Complexity in Human Postural Control: Interpreting the Different Estimations of Entropy

PubMed Central

Rhea, Christopher K.; Silver, Tobin A.; Hong, S. Lee; Ryu, Joong Hyun; Studenka, Breanna E.; Hughes, Charmayne M. L.; Haddad, Jeffrey M.

2011-01-01

Background Over the last two decades, various measures of entropy have been used to examine the complexity of human postural control. In general, entropy measures provide information regarding the health, stability and adaptability of the postural system that is not captured when using more traditional analytical techniques. The purpose of this study was to examine how noise, sampling frequency and time series length influence various measures of entropy when applied to human center of pressure (CoP) data, as well as in synthetic signals with known properties. Such a comparison is necessary to interpret data between and within studies that use different entropy measures, equipment, sampling frequencies or data collection durations. Methods and Findings The complexity of synthetic signals with known properties and standing CoP data was calculated using Approximate Entropy (ApEn), Sample Entropy (SampEn) and Recurrence Quantification Analysis Entropy (RQAEn). All signals were examined at varying sampling frequencies and with varying amounts of added noise. Additionally, an increment time series of the original CoP data was examined to remove long-range correlations. Of the three measures examined, ApEn was the least robust to sampling frequency and noise manipulations. Additionally, increased noise led to an increase in SampEn, but a decrease in RQAEn. Thus, noise can yield inconsistent results between the various entropy measures. Finally, the differences between the entropy measures were minimized in the increment CoP data, suggesting that long-range correlations should be removed from CoP data prior to calculating entropy. Conclusions The various algorithms typically used to quantify the complexity (entropy) of CoP may yield very different results, particularly when sampling frequency and noise are different. The results of this study are discussed within the context of the neural noise and loss of complexity hypotheses. PMID:21437281

Quantum Discord for d⊗2 Systems

PubMed Central

Ma, Zhihao; Chen, Zhihua; Fanchini, Felipe Fernandes; Fei, Shao-Ming

2015-01-01

We present an analytical solution for classical correlation, defined in terms of linear entropy, in an arbitrary system when the second subsystem is measured. We show that the optimal measurements used in the maximization of the classical correlation in terms of linear entropy, when used to calculate the quantum discord in terms of von Neumann entropy, result in a tight upper bound for arbitrary systems. This bound agrees with all known analytical results about quantum discord in terms of von Neumann entropy and, when comparing it with the numerical results for 106 two-qubit random density matrices, we obtain an average deviation of order 10−4. Furthermore, our results give a way to calculate the quantum discord for arbitrary n-qubit GHZ and W states evolving under the action of the amplitude damping noisy channel. PMID:26036771

Diffusivity anomaly in modified Stillinger-Weber liquids

NASA Astrophysics Data System (ADS)

Sengupta, Shiladitya; Vasisht, Vishwas V.; Sastry, Srikanth

2014-01-01

By modifying the tetrahedrality (the strength of the three body interactions) in the well-known Stillinger-Weber model for silicon, we study the diffusivity of a series of model liquids as a function of tetrahedrality and temperature at fixed pressure. Previous work has shown that at constant temperature, the diffusivity exhibits a maximum as a function of tetrahedrality, which we refer to as the diffusivity anomaly, in analogy with the well-known anomaly in water upon variation of pressure at constant temperature. We explore to what extent the structural and thermodynamic changes accompanying changes in the interaction potential can help rationalize the diffusivity anomaly, by employing the Rosenfeld relation between diffusivity and the excess entropy (over the ideal gas reference value), and the pair correlation entropy, which provides an approximation to the excess entropy in terms of the pair correlation function. We find that in the modified Stillinger-Weber liquids, the Rosenfeld relation works well above the melting temperatures but exhibits deviations below, with the deviations becoming smaller for smaller tetrahedrality. Further we find that both the excess entropy and the pair correlation entropy at constant temperature go through maxima as a function of the tetrahedrality, thus demonstrating the close relationship between structural, thermodynamic, and dynamical anomalies in the modified Stillinger-Weber liquids.

Increased signaling entropy in cancer requires the scale-free property of protein interaction networks.

PubMed

Teschendorff, Andrew E; Banerji, Christopher R S; Severini, Simone; Kuehn, Reimer; Sollich, Peter

2015-04-28

One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology.

Increased signaling entropy in cancer requires the scale-free property of protein interaction networks

PubMed Central

Teschendorff, Andrew E.; Banerji, Christopher R. S.; Severini, Simone; Kuehn, Reimer; Sollich, Peter

2015-01-01

One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology. PMID:25919796

Spatial Decomposition of Translational Water–Water Correlation Entropy in Binding Pockets

PubMed Central

2015-01-01

A number of computational tools available today compute the thermodynamic properties of water at surfaces and in binding pockets by using inhomogeneous solvation theory (IST) to analyze explicit-solvent simulations. Such methods enable qualitative spatial mappings of both energy and entropy around a solute of interest and can also be applied quantitatively. However, the entropy estimates of existing methods have, to date, been almost entirely limited to the first-order terms in the IST’s entropy expansion. These first-order terms account for localization and orientation of water molecules in the field of the solute but not for the modification of water–water correlations by the solute. Here, we present an extension of the Grid Inhomogeneous Solvation Theory (GIST) approach which accounts for water–water translational correlations. The method involves rewriting the two-point density of water in terms of a conditional density and utilizes the efficient nearest-neighbor entropy estimation approach. Spatial maps of this second order term, for water in and around the synthetic host cucurbit[7]uril and in the binding pocket of the enzyme Factor Xa, reveal mainly negative contributions, indicating solute-induced water–water correlations relative to bulk water; particularly strong signals are obtained for sites at the entrances of cavities or pockets. This second-order term thus enters with the same, negative, sign as the first order translational and orientational terms. Numerical and convergence properties of the methodology are examined. PMID:26636620

Preserved Entropy, quantum criticality and fragile magnetism

NASA Astrophysics Data System (ADS)

Canfield, Paul

A large swath of strongly correlated electron systems can be associated with the phenomenon of preserved entropy and fragile magnetism. In this talk I will present our thoughts and plans for the discovery and development of lanthanide and transition metal based, strongly correlated systems that are revealed by suppressed, fragile magnetism or grow out of preserved entropy. This talk is based on work published in This work was supported by the U.S. Dept. of Energy, Basic Energy Science, Division of Materials Sciences and Engineering under Contract No. DE-AC02-07CH11358 as well as by the Gordon and Betty Moore Foundations EPiQS Initiative through Grant GBMF4411.

Text mining by Tsallis entropy

NASA Astrophysics Data System (ADS)

Jamaati, Maryam; Mehri, Ali

2018-01-01

Long-range correlations between the elements of natural languages enable them to convey very complex information. Complex structure of human language, as a manifestation of natural languages, motivates us to apply nonextensive statistical mechanics in text mining. Tsallis entropy appropriately ranks the terms' relevance to document subject, taking advantage of their spatial correlation length. We apply this statistical concept as a new powerful word ranking metric in order to extract keywords of a single document. We carry out an experimental evaluation, which shows capability of the presented method in keyword extraction. We find that, Tsallis entropy has reliable word ranking performance, at the same level of the best previous ranking methods.

Tsallis entropy and general polygamy of multiparty quantum entanglement in arbitrary dimensions

NASA Astrophysics Data System (ADS)

Kim, Jeong San

2016-12-01

We establish a unified view of the polygamy of multiparty quantum entanglement in arbitrary dimensions. Using quantum Tsallis-q entropy, we provide a one-parameter class of polygamy inequalities of multiparty quantum entanglement. This class of polygamy inequalities reduces to the known polygamy inequalities based on tangle and entanglement of assistance for a selective choice of the parameter q . We further provide one-parameter generalizations of various quantum correlations based on Tsallis-q entropy. By investigating the properties of the generalized quantum correlations, we provide a sufficient condition on which the Tsallis-q polygamy inequalities hold in multiparty quantum systems of arbitrary dimensions.

A new phylogenetic diversity measure generalizing the shannon index and its application to phyllostomid bats.

PubMed

Allen, Benjamin; Kon, Mark; Bar-Yam, Yaneer

2009-08-01

Protecting biodiversity involves preserving the maximum number and abundance of species while giving special attention to species with unique genetic or morphological characteristics. In balancing different priorities, conservation policymakers may consider quantitative measures that compare diversity across ecological communities. To serve this purpose, a measure should increase or decrease with changes in community composition in a way that reflects what is valued, including species richness, evenness, and distinctness. However, counterintuitively, studies have shown that established indices, including those that emphasize average interspecies phylogenetic distance, may increase with the elimination of species. We introduce a new diversity index, the phylogenetic entropy, which generalizes in a natural way the Shannon index to incorporate species relatedness. Phylogenetic entropy favors communities in which highly distinct species are more abundant, but it does not advocate decreasing any species proportion below a community structure-dependent threshold. We contrast the behavior of multiple indices on a community of phyllostomid bats in the Selva Lacandona. The optimal genus distribution for phylogenetic entropy populates all genera in a linear relationship to their total phylogenetic distance to other genera. Two other indices favor eliminating 12 out of the 23 genera.

Classic Maximum Entropy Recovery of the Average Joint Distribution of Apparent FRET Efficiency and Fluorescence Photons for Single-molecule Burst Measurements

PubMed Central

DeVore, Matthew S.; Gull, Stephen F.; Johnson, Carey K.

2012-01-01

We describe a method for analysis of single-molecule Förster resonance energy transfer (FRET) burst measurements using classic maximum entropy. Classic maximum entropy determines the Bayesian inference for the joint probability describing the total fluorescence photons and the apparent FRET efficiency. The method was tested with simulated data and then with DNA labeled with fluorescent dyes. The most probable joint distribution can be marginalized to obtain both the overall distribution of fluorescence photons and the apparent FRET efficiency distribution. This method proves to be ideal for determining the distance distribution of FRET-labeled biomolecules, and it successfully predicts the shape of the recovered distributions. PMID:22338694

Kinetic equation and nonequilibrium entropy for a quasi-two-dimensional gas.

PubMed

Brey, J Javier; Maynar, Pablo; García de Soria, M I

2016-10-01

A kinetic equation for a dilute gas of hard spheres confined between two parallel plates separated a distance smaller than two particle diameters is derived. It is a Boltzmann-like equation, which incorporates the effect of the confinement on the particle collisions. A function S(t) is constructed by adding to the Boltzmann expression a confinement contribution. Then it is shown that for the solutions of the kinetic equation, S(t) increases monotonically in time, until the system reaches a stationary inhomogeneous state, when S becomes the equilibrium entropy of the confined system as derived from equilibrium statistical mechanics. From the entropy, other equilibrium properties are obtained, and molecular dynamics simulations are used to verify some of the theoretical predictions.

Calculation of heat transfer on shuttle type configurations including the effects of variable entropy at boundary layer edge

NASA Technical Reports Server (NTRS)

Dejarnette, F. R.

1972-01-01

A relatively simple method is presented for including the effect of variable entropy at the boundary-layer edge in a heat transfer method developed previously. For each inviscid surface streamline an approximate shockwave shape is calculated using a modified form of Maslen's method for inviscid axisymmetric flows. The entropy for the streamline at the edge of the boundary layer is determined by equating the mass flux through the shock wave to that inside the boundary layer. Approximations used in this technique allow the heating rates along each inviscid surface streamline to be calculated independent of the other streamlines. The shock standoff distances computed by the present method are found to compare well with those computed by Maslen's asymmetric method. Heating rates are presented for blunted circular and elliptical cones and a typical space shuttle orbiter at angles of attack. Variable entropy effects are found to increase heating rates downstream of the nose significantly higher than those computed using normal-shock entropy, and turbulent heating rates increased more than laminar rates. Effects of Reynolds number and angles of attack are also shown.

GABAergic excitation of spider mechanoreceptors increases information capacity by increasing entropy rather than decreasing jitter.

PubMed

Pfeiffer, Keram; French, Andrew S

2009-09-02

Neurotransmitter chemicals excite or inhibit a range of sensory afferents and sensory pathways. These changes in firing rate or static sensitivity can also be associated with changes in dynamic sensitivity or membrane noise and thus action potential timing. We measured action potential firing produced by random mechanical stimulation of spider mechanoreceptor neurons during long-duration excitation by the GABAA agonist muscimol. Information capacity was estimated from signal-to-noise ratio by averaging responses to repeated identical stimulation sequences. Information capacity was also estimated from the coherence function between input and output signals. Entropy rate was estimated by a data compression algorithm and maximum entropy rate from the firing rate. Action potential timing variability, or jitter, was measured as normalized interspike interval distance. Muscimol increased firing rate, information capacity, and entropy rate, but jitter was unchanged. We compared these data with the effects of increasing firing rate by current injection. Our results indicate that the major increase in information capacity by neurotransmitter action arose from the increased entropy rate produced by increased firing rate, not from reduction in membrane noise and action potential jitter.

Interatomic potentials in condensed matter via the maximum-entropy principle

NASA Astrophysics Data System (ADS)

Carlsson, A. E.

1987-09-01

A general method is described for the calculation of interatomic potentials in condensed-matter systems by use of a maximum-entropy Ansatz for the interatomic correlation functions. The interatomic potentials are given explicitly in terms of statistical correlation functions involving the potential energy and the structure factor of a ``reference medium.'' Illustrations are given for Al-Cu alloys and a model transition metal.

Noise reduction algorithm with the soft thresholding based on the Shannon entropy and bone-conduction speech cross- correlation bands.

PubMed

Na, Sung Dae; Wei, Qun; Seong, Ki Woong; Cho, Jin Ho; Kim, Myoung Nam

2018-01-01

The conventional methods of speech enhancement, noise reduction, and voice activity detection are based on the suppression of noise or non-speech components of the target air-conduction signals. However, air-conduced speech is hard to differentiate from babble or white noise signals. To overcome this problem, the proposed algorithm uses the bone-conduction speech signals and soft thresholding based on the Shannon entropy principle and cross-correlation of air- and bone-conduction signals. A new algorithm for speech detection and noise reduction is proposed, which makes use of the Shannon entropy principle and cross-correlation with the bone-conduction speech signals to threshold the wavelet packet coefficients of the noisy speech. The proposed method can be get efficient result by objective quality measure that are PESQ, RMSE, Correlation, SNR. Each threshold is generated by the entropy and cross-correlation approaches in the decomposed bands using the wavelet packet decomposition. As a result, the noise is reduced by the proposed method using the MATLAB simulation. To verify the method feasibility, we compared the air- and bone-conduction speech signals and their spectra by the proposed method. As a result, high performance of the proposed method is confirmed, which makes it quite instrumental to future applications in communication devices, noisy environment, construction, and military operations.

High-lying single-particle modes, chaos, correlational entropy, and doubling phase transition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stoyanov, Chavdar; Zelevinsky, Vladimir

Highly excited single-particle states in nuclei are coupled with the excitations of a more complex character, first of all with collective phononlike modes of the core. In the framework of the quasiparticle-phonon model, we consider the structure of resulting complex configurations, using the 1k{sub 17/2} orbital in {sup 209}Pb as an example. Although, on the level of one- and two-phonon admixtures, the fully chaotic Gaussian orthogonal ensemble regime is not reached, the eigenstates of the model carry a significant degree of complexity that can be quantified with the aid of correlational invariant entropy. With artificially enhanced particle-core coupling, the systemmore » undergoes the doubling phase transition with the quasiparticle strength concentrated in two repelling peaks. This phase transition is clearly detected by correlational entropy.« less

Tsirelson's bound from a generalized data processing inequality

NASA Astrophysics Data System (ADS)

Dahlsten, Oscar C. O.; Lercher, Daniel; Renner, Renato

2012-06-01

The strength of quantum correlations is bounded from above by Tsirelson's bound. We establish a connection between this bound and the fact that correlations between two systems cannot increase under local operations, a property known as the data processing inequality (DPI). More specifically, we consider arbitrary convex probabilistic theories. These can be equipped with an entropy measure that naturally generalizes the von Neumann entropy, as shown recently in Short and Wehner (2010 New J. Phys. 12 033023) and Barnum et al (2010 New J. Phys. 12 033024). We prove that if the DPI holds with respect to this generalized entropy measure then the underlying theory necessarily respects Tsirelson's bound. We, moreover, generalize this statement to any entropy measure satisfying certain minimal requirements. A consequence of our result is that not all the entropic relations used for deriving Tsirelson's bound via information causality in Pawlowski et al (2009 Nature 461 1101-4) are necessary.

Shannon entropies and Fisher information of K-shell electrons of neutral atoms

NASA Astrophysics Data System (ADS)

Sekh, Golam Ali; Saha, Aparna; Talukdar, Benoy

2018-02-01

We represent the two K-shell electrons of neutral atoms by Hylleraas-type wave function which fulfils the exact behavior at the electron-electron and electron-nucleus coalescence points and, derive a simple method to construct expressions for single-particle position- and momentum-space charge densities, ρ (r) and γ (p) respectively. We make use of the results for ρ (r) and γ (p) to critically examine the effect of correlation on bare (uncorrelated) values of Shannon information entropies (S) and of Fisher information (F) for the K-shell electrons of atoms from helium to neon. Due to inter-electronic repulsion the values of the uncorrelated Shannon position-space entropies are augmented while those of the momentum-space entropies are reduced. The corresponding Fisher information are found to exhibit opposite behavior in respect of this. Attempts are made to provide some plausible explanation for the observed response of S and F to electronic correlation.

Entropy/information flux in Hawking radiation

NASA Astrophysics Data System (ADS)

Alonso-Serrano, Ana; Visser, Matt

2018-01-01

Blackbody radiation contains (on average) an entropy of 3.9 ± 2.5 bits per photon. If the emission process is unitary, then this entropy is exactly compensated by "hidden information" in the correlations. We extend this argument to the Hawking radiation from GR black holes, demonstrating that the assumption of unitarity leads to a perfectly reasonable entropy/information budget. The key technical aspect of our calculation is a variant of the "average subsystem" approach developed by Page, which we extend beyond bipartite pure systems, to a tripartite pure system that considers the influence of the environment.

Modified cross sample entropy and surrogate data analysis method for financial time series

NASA Astrophysics Data System (ADS)

Yin, Yi; Shang, Pengjian

2015-09-01

For researching multiscale behaviors from the angle of entropy, we propose a modified cross sample entropy (MCSE) and combine surrogate data analysis with it in order to compute entropy differences between original dynamics and surrogate series (MCSDiff). MCSDiff is applied to simulated signals to show accuracy and then employed to US and Chinese stock markets. We illustrate the presence of multiscale behavior in the MCSDiff results and reveal that there are synchrony containing in the original financial time series and they have some intrinsic relations, which are destroyed by surrogate data analysis. Furthermore, the multifractal behaviors of cross-correlations between these financial time series are investigated by multifractal detrended cross-correlation analysis (MF-DCCA) method, since multifractal analysis is a multiscale analysis. We explore the multifractal properties of cross-correlation between these US and Chinese markets and show the distinctiveness of NQCI and HSI among the markets in their own region. It can be concluded that the weaker cross-correlation between US markets gives the evidence for the better inner mechanism in the US stock markets than that of Chinese stock markets. To study the multiscale features and properties of financial time series can provide valuable information for understanding the inner mechanism of financial markets.

Entanglement entropy in a boundary impurity model.

PubMed

Levine, G C

2004-12-31

Boundary impurities are known to dramatically alter certain bulk properties of (1+1)-dimensional strongly correlated systems. The entanglement entropy of a zero temperature Luttinger liquid bisected by a single impurity is computed using a novel finite size scaling or bosonization scheme. For a Luttinger liquid of length 2L and UV cutoff epsilon, the boundary impurity correction (deltaSimp) to the logarithmic entanglement entropy (Sent proportional, variant lnL/epsilon scales as deltaSimp approximately yrlnL/epsilon, where yr is the renormalized backscattering coupling constant. In this way, the entanglement entropy within a region is related to scattering through the region's boundary. In the repulsive case (g<1), deltaSimp diverges (negatively) suggesting that the entropy vanishes. Our results are consistent with the recent conjecture that entanglement entropy decreases irreversibly along renormalization group flow.

The increase of the functional entropy of the human brain with age.

PubMed

Yao, Y; Lu, W L; Xu, B; Li, C B; Lin, C P; Waxman, D; Feng, J F

2013-10-09

We use entropy to characterize intrinsic ageing properties of the human brain. Analysis of fMRI data from a large dataset of individuals, using resting state BOLD signals, demonstrated that a functional entropy associated with brain activity increases with age. During an average lifespan, the entropy, which was calculated from a population of individuals, increased by approximately 0.1 bits, due to correlations in BOLD activity becoming more widely distributed. We attribute this to the number of excitatory neurons and the excitatory conductance decreasing with age. Incorporating these properties into a computational model leads to quantitatively similar results to the fMRI data. Our dataset involved males and females and we found significant differences between them. The entropy of males at birth was lower than that of females. However, the entropies of the two sexes increase at different rates, and intersect at approximately 50 years; after this age, males have a larger entropy.

Increased resting-state brain entropy in Alzheimer's disease.

PubMed

Xue, Shao-Wei; Guo, Yonghu

2018-03-07

Entropy analysis of resting-state functional MRI (R-fMRI) is a novel approach to characterize brain temporal dynamics and facilitates the identification of abnormal brain activity caused by several disease conditions. However, Alzheimer's disease (AD)-related brain entropy mapping based on R-fMRI has not been assessed. Here, we measured the sample entropy and voxel-wise connectivity of the network degree centrality (DC) of the intrinsic brain activity acquired by R-fMRI in 26 patients with AD and 26 healthy controls. Compared with the controls, AD patients showed increased entropy in the middle temporal gyrus and the precentral gyrus and also showed decreased DC in the precuneus. Moreover, the magnitude of the negative correlation between local brain activity (entropy) and network connectivity (DC) was increased in AD patients in comparison with healthy controls. These findings provide new evidence on AD-related brain entropy alterations.

The Increase of the Functional Entropy of the Human Brain with Age

PubMed Central

Yao, Y.; Lu, W. L.; Xu, B.; Li, C. B.; Lin, C. P.; Waxman, D.; Feng, J. F.

2013-01-01

We use entropy to characterize intrinsic ageing properties of the human brain. Analysis of fMRI data from a large dataset of individuals, using resting state BOLD signals, demonstrated that a functional entropy associated with brain activity increases with age. During an average lifespan, the entropy, which was calculated from a population of individuals, increased by approximately 0.1 bits, due to correlations in BOLD activity becoming more widely distributed. We attribute this to the number of excitatory neurons and the excitatory conductance decreasing with age. Incorporating these properties into a computational model leads to quantitatively similar results to the fMRI data. Our dataset involved males and females and we found significant differences between them. The entropy of males at birth was lower than that of females. However, the entropies of the two sexes increase at different rates, and intersect at approximately 50 years; after this age, males have a larger entropy. PMID:24103922

Microscopic insights into the NMR relaxation based protein conformational entropy meter

PubMed Central

Kasinath, Vignesh; Sharp, Kim A.; Wand, A. Joshua

2013-01-01

Conformational entropy is a potentially important thermodynamic parameter contributing to protein function. Quantitative measures of conformational entropy are necessary for an understanding of its role but have been difficult to obtain. An empirical method that utilizes changes in conformational dynamics as a proxy for changes in conformational entropy has recently been introduced. Here we probe the microscopic origins of the link between conformational dynamics and conformational entropy using molecular dynamics simulations. Simulation of seven pro! teins gave an excellent correlation with measures of side-chain motion derived from NMR relaxation. The simulations show that the motion of methyl-bearing side-chains are sufficiently coupled to that of other side chains to serve as excellent reporters of the overall side-chain conformational entropy. These results tend to validate the use of experimentally accessible measures of methyl motion - the NMR-derived generalized order parameters - as a proxy from which to derive changes in protein conformational entropy. PMID:24007504

Preserved entropy and fragile magnetism

DOE PAGES

Canfield, Paul C.; Bud’ko, Sergey L.

2016-07-05

Here, a large swath of quantum critical and strongly correlated electron systems can be associated with the phenomena of preserved entropy and fragile magnetism. In this overview we present our thoughts and plans for the discovery and development of lanthanide and transition metal based, strongly correlated systems that are revealed by suppressed, fragile magnetism, quantum criticality, or grow out of preserved entropy. We will present and discuss current examples such as YbBiPt, YbAgGe, YbFe 2Zn 20, PrAg 2In, BaFe 2As 2, CaFe 2As 2, LaCrSb 3 and LaCrGe 3 as part of our motivation and to provide illustrative examples.

Measurement of Entropy of a Multiparticle System: a ``Do-List''

NASA Astrophysics Data System (ADS)

Bialas, A.; Czyz, W.

2000-03-01

An algorithm for measurement of entropy in multiparticle systems, based on the recently published proposal of the present authors is given. Dependence on discretization of the system and effects of multiparticle correlations are discussed in some detail.

Excess entropy and crystallization in Stillinger-Weber and Lennard-Jones fluids

NASA Astrophysics Data System (ADS)

Dhabal, Debdas; Nguyen, Andrew Huy; Singh, Murari; Khatua, Prabir; Molinero, Valeria; Bandyopadhyay, Sanjoy; Chakravarty, Charusita

2015-10-01

Molecular dynamics simulations are used to contrast the supercooling and crystallization behaviour of monatomic liquids that exemplify the transition from simple to anomalous, tetrahedral liquids. As examples of simple fluids, we use the Lennard-Jones (LJ) liquid and a pair-dominated Stillinger-Weber liquid (SW16). As examples of tetrahedral, water-like fluids, we use the Stillinger-Weber model with variable tetrahedrality parameterized for germanium (SW20), silicon (SW21), and water (SW23.15 or mW model). The thermodynamic response functions show clear qualitative differences between simple and water-like liquids. For simple liquids, the compressibility and the heat capacity remain small on isobaric cooling. The tetrahedral liquids in contrast show a very sharp rise in these two response functions as the lower limit of liquid-phase stability is reached. While the thermal expansivity decreases with temperature but never crosses zero in simple liquids, in all three tetrahedral liquids at the studied pressure, there is a temperature of maximum density below which thermal expansivity is negative. In contrast to the thermodynamic response functions, the excess entropy on isobaric cooling does not show qualitatively different features for simple and water-like liquids; however, the slope and curvature of the entropy-temperature plots reflect the heat capacity trends. Two trajectory-based computational estimation methods for the entropy and the heat capacity are compared for possible structural insights into supercooling, with the entropy obtained from thermodynamic integration. The two-phase thermodynamic estimator for the excess entropy proves to be fairly accurate in comparison to the excess entropy values obtained by thermodynamic integration, for all five Lennard-Jones and Stillinger-Weber liquids. The entropy estimator based on the multiparticle correlation expansion that accounts for both pair and triplet correlations, denoted by Strip, is also studied. Strip is a good entropy estimator for liquids where pair and triplet correlations are important such as Ge and Si, but loses accuracy for purely pair-dominated liquids, like LJ fluid, or near the crystallization temperature (Tthr). Since local tetrahedral order is compatible with both liquid and crystalline states, the reorganisation of tetrahedral liquids is accompanied by a clear rise in the pair, triplet, and thermodynamic contributions to the heat capacity, resulting in the heat capacity anomaly. In contrast, the pair-dominated liquids show increasing dominance of triplet correlations on approaching crystallization but no sharp rise in either the pair or thermodynamic heat capacities.

Supersymmetric Renyi entropy in CFT 2 and AdS 3

DOE PAGES

Giveon, Amit; Kutasov, David

2016-01-01

We show that in any two dimensional conformal field theory with (2, 2) super-symmetry one can define a supersymmetric analog of the usual Renyi entropy of a spatial region A. It differs from the Renyi entropy by a universal function (which we compute) of the central charge, Renyi parameter n and the geometric parameters of A. In the limit n → 1 it coincides with the entanglement entropy. Thus, it contains the same information as the Renyi entropy but its computation only involves correlation functions of chiral and anti-chiral operators. We also show that this quantity appears naturally in stringmore » theory on AdS3.« less

The Correlation of Standard Entropy with Enthalpy Supplied from 0 to 298.15 K

ERIC Educational Resources Information Center

Lambert, Frank L.; Leff, Harvey S.

2009-01-01

As a substance is heated at constant pressure from near 0 K to 298 K, each incremental enthalpy increase, dH, alters entropy by dH/T, bringing it from approximately zero to its standard molar entropy S degrees. Using heat capacity data for 32 solids and CODATA results for another 45, we found a roughly linear relationship between S degrees and…

[A research in speech endpoint detection based on boxes-coupling generalization dimension].

PubMed

Wang, Zimei; Yang, Cuirong; Wu, Wei; Fan, Yingle

2008-06-01

In this paper, a new calculating method of generalized dimension, based on boxes-coupling principle, is proposed to overcome the edge effects and to improve the capability of the speech endpoint detection which is based on the original calculating method of generalized dimension. This new method has been applied to speech endpoint detection. Firstly, the length of overlapping border was determined, and through calculating the generalized dimension by covering the speech signal with overlapped boxes, three-dimension feature vectors including the box dimension, the information dimension and the correlation dimension were obtained. Secondly, in the light of the relation between feature distance and similarity degree, feature extraction was conducted by use of common distance. Lastly, bi-threshold method was used to classify the speech signals. The results of experiment indicated that, by comparison with the original generalized dimension (OGD) and the spectral entropy (SE) algorithm, the proposed method is more robust and effective for detecting the speech signals which contain different kinds of noise in different signal noise ratio (SNR), especially in low SNR.

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop.

PubMed

Li, Lian-Hui; Mo, Rong

2015-01-01

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility.

Production Task Queue Optimization Based on Multi-Attribute Evaluation for Complex Product Assembly Workshop

PubMed Central

Li, Lian-hui; Mo, Rong

2015-01-01

The production task queue has a great significance for manufacturing resource allocation and scheduling decision. Man-made qualitative queue optimization method has a poor effect and makes the application difficult. A production task queue optimization method is proposed based on multi-attribute evaluation. According to the task attributes, the hierarchical multi-attribute model is established and the indicator quantization methods are given. To calculate the objective indicator weight, criteria importance through intercriteria correlation (CRITIC) is selected from three usual methods. To calculate the subjective indicator weight, BP neural network is used to determine the judge importance degree, and then the trapezoid fuzzy scale-rough AHP considering the judge importance degree is put forward. The balanced weight, which integrates the objective weight and the subjective weight, is calculated base on multi-weight contribution balance model. The technique for order preference by similarity to an ideal solution (TOPSIS) improved by replacing Euclidean distance with relative entropy distance is used to sequence the tasks and optimize the queue by the weighted indicator value. A case study is given to illustrate its correctness and feasibility. PMID:26414758

Informational basis of sensory adaptation: entropy and single-spike efficiency in rat barrel cortex.

PubMed

Adibi, Mehdi; Clifford, Colin W G; Arabzadeh, Ehsan

2013-09-11

We showed recently that exposure to whisker vibrations enhances coding efficiency in rat barrel cortex despite increasing correlations in variability (Adibi et al., 2013). Here, to understand how adaptation achieves this improvement in sensory representation, we decomposed the stimulus information carried in neuronal population activity into its fundamental components in the framework of information theory. In the context of sensory coding, these components are the entropy of the responses across the entire stimulus set (response entropy) and the entropy of the responses conditional on the stimulus (conditional response entropy). We found that adaptation decreased response entropy and conditional response entropy at both the level of single neurons and the pooled activity of neuronal populations. However, the net effect of adaptation was to increase the mutual information because the drop in the conditional entropy outweighed the drop in the response entropy. The information transmitted by a single spike also increased under adaptation. As population size increased, the information content of individual spikes declined but the relative improvement attributable to adaptation was maintained.

Nonlinear dynamic analysis of voices before and after surgical excision of vocal polyps

NASA Astrophysics Data System (ADS)

Zhang, Yu; McGilligan, Clancy; Zhou, Liang; Vig, Mark; Jiang, Jack J.

2004-05-01

Phase space reconstruction, correlation dimension, and second-order entropy, methods from nonlinear dynamics, are used to analyze sustained vowels generated by patients before and after surgical excision of vocal polyps. Two conventional acoustic perturbation parameters, jitter and shimmer, are also employed to analyze voices before and after surgery. Presurgical and postsurgical analyses of jitter, shimmer, correlation dimension, and second-order entropy are statistically compared. Correlation dimension and second-order entropy show a statistically significant decrease after surgery, indicating reduced complexity and higher predictability of postsurgical voice dynamics. There is not a significant postsurgical difference in shimmer, although jitter shows a significant postsurgical decrease. The results suggest that jitter and shimmer should be applied to analyze disordered voices with caution; however, nonlinear dynamic methods may be useful for analyzing abnormal vocal function and quantitatively evaluating the effects of surgical excision of vocal polyps.

Local Response of Topological Order to an External Perturbation

NASA Astrophysics Data System (ADS)

Hamma, Alioscia; Cincio, Lukasz; Santra, Siddhartha; Zanardi, Paolo; Amico, Luigi

2013-05-01

We study the behavior of the Rényi entropies for the toric code subject to a variety of different perturbations, by means of 2D density matrix renormalization group and analytical methods. We find that Rényi entropies of different index α display derivatives with opposite sign, as opposed to typical symmetry breaking states, and can be detected on a very small subsystem regardless of the correlation length. This phenomenon is due to the presence in the phase of a point with flat entanglement spectrum, zero correlation length, and area law for the entanglement entropy. We argue that this kind of splitting is common to all the phases with a certain group theoretic structure, including quantum double models, cluster states, and other quantum spin liquids. The fact that the size of the subsystem does not need to scale with the correlation length makes it possible for this effect to be accessed experimentally.

[Changes in the entropy of heart mass in dogs during inhalation of transuranic radionuclides].

PubMed

Kalmykova, Z I; Buldakov, L A; Tokarskaia, Z V

1991-01-01

Altogether 140 random-bred dogs of both sexes, aged 2 to 4 (body mass 14.5 +/- 0.1 kg) were examined. Age-related changes of heart mass entropy, resulting from disorder in the correlation of cardiac parts during aging, progress with age. During inhalation of acute, subacute and chronic effective amounts of nitrates of polymeric 239Pu and monomeric 241Am aerosol particles, measured in micron, dog heart mass entropy increases as compared to the age control, and during inhalation of transuranic radionuclides at small amounts, causing the animals' life prolongation, heart mass entropy decreases.

Effect of Entropy Generation on Wear Mechanics and System Reliability

NASA Astrophysics Data System (ADS)

Gidwani, Akshay; James, Siddanth; Jagtap, Sagar; Karthikeyan, Ram; Vincent, S.

2018-04-01

Wear is an irreversible phenomenon. Processes such as mutual sliding and rolling between materials involve entropy generation. These processes are monotonic with respect to time. The concept of entropy generation is further quantified using Degradation Entropy Generation theorem formulated by Michael D. Bryant. The sliding-wear model can be extrapolated to different instances in order to further provide a potential analysis of machine prognostics as well as system and process reliability for various processes besides even mere mechanical processes. In other words, using the concept of ‘entropy generation’ and wear, one can quantify the reliability of a system with respect to time using a thermodynamic variable, which is the basis of this paper. Thus in the present investigation, a unique attempt has been made to establish correlation between entropy-wear-reliability which can be useful technique in preventive maintenance.

Correlations and Functional Connections in a Population of Grid Cells

PubMed Central

Roudi, Yasser

2015-01-01

We study the statistics of spike trains of simultaneously recorded grid cells in freely behaving rats. We evaluate pairwise correlations between these cells and, using a maximum entropy kinetic pairwise model (kinetic Ising model), study their functional connectivity. Even when we account for the covariations in firing rates due to overlapping fields, both the pairwise correlations and functional connections decay as a function of the shortest distance between the vertices of the spatial firing pattern of pairs of grid cells, i.e. their phase difference. They take positive values between cells with nearby phases and approach zero or negative values for larger phase differences. We find similar results also when, in addition to correlations due to overlapping fields, we account for correlations due to theta oscillations and head directional inputs. The inferred connections between neurons in the same module and those from different modules can be both negative and positive, with a mean close to zero, but with the strongest inferred connections found between cells of the same module. Taken together, our results suggest that grid cells in the same module do indeed form a local network of interconnected neurons with a functional connectivity that supports a role for attractor dynamics in the generation of grid pattern. PMID:25714908

An Improved Evidential-IOWA Sensor Data Fusion Approach in Fault Diagnosis

PubMed Central

Zhou, Deyun; Zhuang, Miaoyan; Fang, Xueyi; Xie, Chunhe

2017-01-01

As an important tool of information fusion, Dempster–Shafer evidence theory is widely applied in handling the uncertain information in fault diagnosis. However, an incorrect result may be obtained if the combined evidence is highly conflicting, which may leads to failure in locating the fault. To deal with the problem, an improved evidential-Induced Ordered Weighted Averaging (IOWA) sensor data fusion approach is proposed in the frame of Dempster–Shafer evidence theory. In the new method, the IOWA operator is used to determine the weight of different sensor data source, while determining the parameter of the IOWA, both the distance of evidence and the belief entropy are taken into consideration. First, based on the global distance of evidence and the global belief entropy, the α value of IOWA is obtained. Simultaneously, a weight vector is given based on the maximum entropy method model. Then, according to IOWA operator, the evidence are modified before applying the Dempster’s combination rule. The proposed method has a better performance in conflict management and fault diagnosis due to the fact that the information volume of each evidence is taken into consideration. A numerical example and a case study in fault diagnosis are presented to show the rationality and efficiency of the proposed method. PMID:28927017

The Role of Hellinger Processes in Mathematical Finance

NASA Astrophysics Data System (ADS)

Choulli, T.; Hurd, T. R.

2001-09-01

This paper illustrates the natural role that Hellinger processes can play in solving problems from ¯nance. We propose an extension of the concept of Hellinger process applicable to entropy distance and f-divergence distances, where f is a convex logarithmic function or a convex power function with general order q, 0 6= q < 1. These concepts lead to a new approach to Merton's optimal portfolio problem and its dual in general L¶evy markets.

Measuring the potential utility of seasonal climate predictions

NASA Astrophysics Data System (ADS)

Tippett, Michael K.; Kleeman, Richard; Tang, Youmin

2004-11-01

Variation of sea surface temperature (SST) on seasonal-to-interannual time-scales leads to changes in seasonal weather statistics and seasonal climate anomalies. Relative entropy, an information theory measure of utility, is used to quantify the impact of SST variations on seasonal precipitation compared to natural variability. An ensemble of general circulation model (GCM) simulations is used to estimate this quantity in three regions where tropical SST has a large impact on precipitation: South Florida, the Nordeste of Brazil and Kenya. We find the yearly variation of relative entropy is strongly correlated with shifts in ensemble mean precipitation and weakly correlated with ensemble variance. Relative entropy is also found to be related to measures of the ability of the GCM to reproduce observations.

Entanglement Entropy of the ν=1/2 Composite Fermion Non-Fermi Liquid State.

PubMed

Shao, Junping; Kim, Eun-Ah; Haldane, F D M; Rezayi, Edward H

2015-05-22

The so-called "non-Fermi liquid" behavior is very common in strongly correlated systems. However, its operational definition in terms of "what it is not" is a major obstacle for the theoretical understanding of this fascinating correlated state. Recently there has been much interest in entanglement entropy as a theoretical tool to study non-Fermi liquids. So far explicit calculations have been limited to models without direct experimental realizations. Here we focus on a two-dimensional electron fluid under magnetic field and filling fraction ν=1/2, which is believed to be a non-Fermi liquid state. Using a composite fermion wave function which captures the ν=1/2 state very accurately, we compute the second Rényi entropy using the variational Monte Carlo technique. We find the entanglement entropy scales as LlogL with the length of the boundary L as it does for free fermions, but has a prefactor twice that of free fermions.

Analysis of the anomalous mean-field like properties of Gaussian core model in terms of entropy

NASA Astrophysics Data System (ADS)

Nandi, Manoj Kumar; Maitra Bhattacharyya, Sarika

2018-01-01

Studies of the Gaussian core model (GCM) have shown that it behaves like a mean-field model and the properties are quite different from standard glass former. In this work, we investigate the entropies, namely, the excess entropy (Sex) and the configurational entropy (Sc) and their different components to address these anomalies. Our study corroborates most of the earlier observations and also sheds new light on the high and low temperature dynamics. We find that unlike in standard glass former where high temperature dynamics is dominated by two-body correlation and low temperature by many-body correlations, in the GCM both high and low temperature dynamics are dominated by many-body correlations. We also find that the many-body entropy which is usually positive at low temperatures and is associated with activated dynamics is negative in the GCM suggesting suppression of activation. Interestingly despite the suppression of activation, the Adam-Gibbs (AG) relation that describes activated dynamics holds in the GCM, thus suggesting a non-activated contribution in AG relation. We also find an overlap between the AG relation and mode coupling power law regime leading to a power law behavior of Sc. From our analysis of this power law behavior, we predict that in the GCM the high temperature dynamics will disappear at dynamical transition temperature and below that there will be a transition to the activated regime. Our study further reveals that the activated regime in the GCM is quite narrow.

Binding stability of peptides on major histocompatibility complex class I proteins: role of entropy and dynamics.

PubMed

Gul, Ahmet; Erman, Burak

2018-01-16

Prediction of peptide binding on specific human leukocyte antigens (HLA) has long been studied with successful results. We herein describe the effects of entropy and dynamics by investigating the binding stabilities of 10 nanopeptides on various HLA Class I alleles using a theoretical model based on molecular dynamics simulations. The fluctuational entropies of the peptides are estimated over a temperature range of 310-460 K. The estimated entropies correlate well with experimental binding affinities of the peptides: peptides that have higher binding affinities have lower entropies compared to non-binders, which have significantly larger entropies. The computation of the entropies is based on a simple model that requires short molecular dynamics trajectories and allows for approximate but rapid determination. The paper draws attention to the long neglected dynamic aspects of peptide binding, and provides a fast computation scheme that allows for rapid scanning of large numbers of peptides on selected HLA antigens, which may be useful in defining the right peptides for personal immunotherapy.

Binding stability of peptides on major histocompatibility complex class I proteins: role of entropy and dynamics

NASA Astrophysics Data System (ADS)

Gul, Ahmet; Erman, Burak

2018-03-01

Prediction of peptide binding on specific human leukocyte antigens (HLA) has long been studied with successful results. We herein describe the effects of entropy and dynamics by investigating the binding stabilities of 10 nanopeptides on various HLA Class I alleles using a theoretical model based on molecular dynamics simulations. The fluctuational entropies of the peptides are estimated over a temperature range of 310-460 K. The estimated entropies correlate well with experimental binding affinities of the peptides: peptides that have higher binding affinities have lower entropies compared to non-binders, which have significantly larger entropies. The computation of the entropies is based on a simple model that requires short molecular dynamics trajectories and allows for approximate but rapid determination. The paper draws attention to the long neglected dynamic aspects of peptide binding, and provides a fast computation scheme that allows for rapid scanning of large numbers of peptides on selected HLA antigens, which may be useful in defining the right peptides for personal immunotherapy.

Entropy of hydrological systems under small samples: Uncertainty and variability

NASA Astrophysics Data System (ADS)

Liu, Dengfeng; Wang, Dong; Wang, Yuankun; Wu, Jichun; Singh, Vijay P.; Zeng, Xiankui; Wang, Lachun; Chen, Yuanfang; Chen, Xi; Zhang, Liyuan; Gu, Shenghua

2016-01-01

Entropy theory has been increasingly applied in hydrology in both descriptive and inferential ways. However, little attention has been given to the small-sample condition widespread in hydrological practice, where either hydrological measurements are limited or are even nonexistent. Accordingly, entropy estimated under this condition may incur considerable bias. In this study, small-sample condition is considered and two innovative entropy estimators, the Chao-Shen (CS) estimator and the James-Stein-type shrinkage (JSS) estimator, are introduced. Simulation tests are conducted with common distributions in hydrology, that lead to the best-performing JSS estimator. Then, multi-scale moving entropy-based hydrological analyses (MM-EHA) are applied to indicate the changing patterns of uncertainty of streamflow data collected from the Yangtze River and the Yellow River, China. For further investigation into the intrinsic property of entropy applied in hydrological uncertainty analyses, correlations of entropy and other statistics at different time-scales are also calculated, which show connections between the concept of uncertainty and variability.

EEG entropy measures indicate decrease of cortical information processing in Disorders of Consciousness.

PubMed

Thul, Alexander; Lechinger, Julia; Donis, Johann; Michitsch, Gabriele; Pichler, Gerald; Kochs, Eberhard F; Jordan, Denis; Ilg, Rüdiger; Schabus, Manuel

2016-02-01

Clinical assessments that rely on behavioral responses to differentiate Disorders of Consciousness are at times inapt because of some patients' motor disabilities. To objectify patients' conditions of reduced consciousness the present study evaluated the use of electroencephalography to measure residual brain activity. We analyzed entropy values of 18 scalp EEG channels of 15 severely brain-damaged patients with clinically diagnosed Minimally-Conscious-State (MCS) or Unresponsive-Wakefulness-Syndrome (UWS) and compared the results to a sample of 24 control subjects. Permutation entropy (PeEn) and symbolic transfer entropy (STEn), reflecting information processes in the EEG, were calculated for all subjects. Participants were tested on a modified active own-name paradigm to identify correlates of active instruction following. PeEn showed reduced local information content in the EEG in patients, that was most pronounced in UWS. STEn analysis revealed altered directed information flow in the EEG of patients, indicating impaired feed-backward connectivity. Responses to auditory stimulation yielded differences in entropy measures, indicating reduced information processing in MCS and UWS. Local EEG information content and information flow are affected in Disorders of Consciousness. This suggests local cortical information capacity and feedback information transfer as neural correlates of consciousness. The utilized EEG entropy analyses were able to relate to patient groups with different Disorders of Consciousness. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Accuracy of topological entanglement entropy on finite cylinders.

PubMed

Jiang, Hong-Chen; Singh, Rajiv R P; Balents, Leon

2013-09-06

Topological phases are unique states of matter which support nonlocal excitations which behave as particles with fractional statistics. A universal characterization of gapped topological phases is provided by the topological entanglement entropy (TEE). We study the finite size corrections to the TEE by focusing on systems with a Z2 topological ordered state using density-matrix renormalization group and perturbative series expansions. We find that extrapolations of the TEE based on the Renyi entropies with a Renyi index of n≥2 suffer from much larger finite size corrections than do extrapolations based on the von Neumann entropy. In particular, when the circumference of the cylinder is about ten times the correlation length, the TEE obtained using von Neumann entropy has an error of order 10(-3), while for Renyi entropies it can even exceed 40%. We discuss the relevance of these findings to previous and future searches for topological ordered phases, including quantum spin liquids.

Entropy of black holes with multiple horizons

NASA Astrophysics Data System (ADS)

He, Yun; Ma, Meng-Sen; Zhao, Ren

2018-05-01

We examine the entropy of black holes in de Sitter space and black holes surrounded by quintessence. These black holes have multiple horizons, including at least the black hole event horizon and a horizon outside it (cosmological horizon for de Sitter black holes and "quintessence horizon" for the black holes surrounded by quintessence). Based on the consideration that the two horizons are not independent each other, we conjecture that the total entropy of these black holes should not be simply the sum of entropies of the two horizons, but should have an extra term coming from the correlations between the two horizons. Different from our previous works, in this paper we consider the cosmological constant as the variable and employ an effective method to derive the explicit form of the entropy. We also try to discuss the thermodynamic stabilities of these black holes according to the entropy and the effective temperature.

Entropy perspective on the thermal crossover in a fermionic Hubbard chain

NASA Astrophysics Data System (ADS)

Bonnes, Lars; Pichler, Hannes; Läuchli, Andreas M.

2013-10-01

We study the Renyi entropy in the finite-temperature crossover regime of a Hubbard chain using quantum Monte Carlo. The ground-state entropy has characteristic features such as a logarithmic divergence with block size and 2kF oscillations that are a hallmark of its Luttinger liquid nature. The interplay between the (extensive) thermal entropy and the ground-state features is studied and we analyze the temperature-induced decay of the amplitude of the oscillations as well as the scaling of the purity. Furthermore, we show how the spin and charge velocities can be extracted from the temperature dependence of the Renyi entropy, bridging our findings to recent experimental proposals on how to implement the measurement of Renyi entropies in the cold atom system. Studying the Renyi mutual information, we also demonstrate how constraints such as particle number conservation can induce persistent correlations visible in the mutual information even at high temperature.

[The nonlinear parameters of interference EMG of two day old human newborns].

PubMed

Voroshilov, A S; Meĭgal, A Iu

2011-01-01

Temporal structure of interference electromyogram (iEMG) was studied in healthy two days old human newborns (n = 76) using the non-linear parameters (correlation dimension, fractal dimension, correlation entropy). It has been found that the non-linear parameters of iEMG were time-dependent because they were decreasing within the first two days of life. Also, these parameters were sensitive to muscle function, because correlation dimension, fractal dimension, and correlation entropy of iEMG in gastrocnemius muscle differed from the other muscles. The non-linear parameters were proven to be independent of the iEMG amplitude. That model of early ontogenesis may be of potential use for investigation of anti-gravitation activity.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dhabal, Debdas; Chakravarty, Charusita, E-mail: charus@chemistry.iitd.ac.in; Nguyen, Andrew Huy

Molecular dynamics simulations are used to contrast the supercooling and crystallization behaviour of monatomic liquids that exemplify the transition from simple to anomalous, tetrahedral liquids. As examples of simple fluids, we use the Lennard-Jones (LJ) liquid and a pair-dominated Stillinger-Weber liquid (SW{sub 16}). As examples of tetrahedral, water-like fluids, we use the Stillinger-Weber model with variable tetrahedrality parameterized for germanium (SW{sub 20}), silicon (SW{sub 21}), and water (SW{sub 23.15} or mW model). The thermodynamic response functions show clear qualitative differences between simple and water-like liquids. For simple liquids, the compressibility and the heat capacity remain small on isobaric cooling. Themore » tetrahedral liquids in contrast show a very sharp rise in these two response functions as the lower limit of liquid-phase stability is reached. While the thermal expansivity decreases with temperature but never crosses zero in simple liquids, in all three tetrahedral liquids at the studied pressure, there is a temperature of maximum density below which thermal expansivity is negative. In contrast to the thermodynamic response functions, the excess entropy on isobaric cooling does not show qualitatively different features for simple and water-like liquids; however, the slope and curvature of the entropy-temperature plots reflect the heat capacity trends. Two trajectory-based computational estimation methods for the entropy and the heat capacity are compared for possible structural insights into supercooling, with the entropy obtained from thermodynamic integration. The two-phase thermodynamic estimator for the excess entropy proves to be fairly accurate in comparison to the excess entropy values obtained by thermodynamic integration, for all five Lennard-Jones and Stillinger-Weber liquids. The entropy estimator based on the multiparticle correlation expansion that accounts for both pair and triplet correlations, denoted by S{sub trip}, is also studied. S{sub trip} is a good entropy estimator for liquids where pair and triplet correlations are important such as Ge and Si, but loses accuracy for purely pair-dominated liquids, like LJ fluid, or near the crystallization temperature (T{sub thr}). Since local tetrahedral order is compatible with both liquid and crystalline states, the reorganisation of tetrahedral liquids is accompanied by a clear rise in the pair, triplet, and thermodynamic contributions to the heat capacity, resulting in the heat capacity anomaly. In contrast, the pair-dominated liquids show increasing dominance of triplet correlations on approaching crystallization but no sharp rise in either the pair or thermodynamic heat capacities.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giveon, Amit; Kutasov, David

We show that in any two dimensional conformal field theory with (2, 2) super-symmetry one can define a supersymmetric analog of the usual Renyi entropy of a spatial region A. It differs from the Renyi entropy by a universal function (which we compute) of the central charge, Renyi parameter n and the geometric parameters of A. In the limit n → 1 it coincides with the entanglement entropy. Thus, it contains the same information as the Renyi entropy but its computation only involves correlation functions of chiral and anti-chiral operators. We also show that this quantity appears naturally in stringmore » theory on AdS3.« less

Temporal Correlations and Neural Spike Train Entropy

NASA Astrophysics Data System (ADS)

Schultz, Simon R.; Panzeri, Stefano

2001-06-01

Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight to the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower rms error information estimates in comparison to a ``brute force'' approach.

Applications of quantum entropy to statistics

NASA Astrophysics Data System (ADS)

Silver, R. N.; Martz, H. F.

This paper develops two generalizations of the maximum entropy (ME) principle. First, Shannon classical entropy is replaced by von Neumann quantum entropy to yield a broader class of information divergences (or penalty functions) for statistics applications. Negative relative quantum entropy enforces convexity, positivity, non-local extensivity and prior correlations such as smoothness. This enables the extension of ME methods from their traditional domain of ill-posed in-verse problems to new applications such as non-parametric density estimation. Second, given a choice of information divergence, a combination of ME and Bayes rule is used to assign both prior and posterior probabilities. Hyperparameters are interpreted as Lagrange multipliers enforcing constraints. Conservation principles are proposed to act statistical regularization and other hyperparameters, such as conservation of information and smoothness. ME provides an alternative to hierarchical Bayes methods.

Bayesian Approach to Spectral Function Reconstruction for Euclidean Quantum Field Theories

NASA Astrophysics Data System (ADS)

Burnier, Yannis; Rothkopf, Alexander

2013-11-01

We present a novel approach to the inference of spectral functions from Euclidean time correlator data that makes close contact with modern Bayesian concepts. Our method differs significantly from the maximum entropy method (MEM). A new set of axioms is postulated for the prior probability, leading to an improved expression, which is devoid of the asymptotically flat directions present in the Shanon-Jaynes entropy. Hyperparameters are integrated out explicitly, liberating us from the Gaussian approximations underlying the evidence approach of the maximum entropy method. We present a realistic test of our method in the context of the nonperturbative extraction of the heavy quark potential. Based on hard-thermal-loop correlator mock data, we establish firm requirements in the number of data points and their accuracy for a successful extraction of the potential from lattice QCD. Finally we reinvestigate quenched lattice QCD correlators from a previous study and provide an improved potential estimation at T=2.33TC.

Bayesian approach to spectral function reconstruction for Euclidean quantum field theories.

PubMed

Burnier, Yannis; Rothkopf, Alexander

2013-11-01

We present a novel approach to the inference of spectral functions from Euclidean time correlator data that makes close contact with modern Bayesian concepts. Our method differs significantly from the maximum entropy method (MEM). A new set of axioms is postulated for the prior probability, leading to an improved expression, which is devoid of the asymptotically flat directions present in the Shanon-Jaynes entropy. Hyperparameters are integrated out explicitly, liberating us from the Gaussian approximations underlying the evidence approach of the maximum entropy method. We present a realistic test of our method in the context of the nonperturbative extraction of the heavy quark potential. Based on hard-thermal-loop correlator mock data, we establish firm requirements in the number of data points and their accuracy for a successful extraction of the potential from lattice QCD. Finally we reinvestigate quenched lattice QCD correlators from a previous study and provide an improved potential estimation at T=2.33T(C).

A secure image encryption method based on dynamic harmony search (DHS) combined with chaotic map

NASA Astrophysics Data System (ADS)

Mirzaei Talarposhti, Khadijeh; Khaki Jamei, Mehrzad

2016-06-01

In recent years, there has been increasing interest in the security of digital images. This study focuses on the gray scale image encryption using dynamic harmony search (DHS). In this research, first, a chaotic map is used to create cipher images, and then the maximum entropy and minimum correlation coefficient is obtained by applying a harmony search algorithm on them. This process is divided into two steps. In the first step, the diffusion of a plain image using DHS to maximize the entropy as a fitness function will be performed. However, in the second step, a horizontal and vertical permutation will be applied on the best cipher image, which is obtained in the previous step. Additionally, DHS has been used to minimize the correlation coefficient as a fitness function in the second step. The simulation results have shown that by using the proposed method, the maximum entropy and the minimum correlation coefficient, which are approximately 7.9998 and 0.0001, respectively, have been obtained.

Spectral Entropies as Information-Theoretic Tools for Complex Network Comparison

NASA Astrophysics Data System (ADS)

De Domenico, Manlio; Biamonte, Jacob

2016-10-01

Any physical system can be viewed from the perspective that information is implicitly represented in its state. However, the quantification of this information when it comes to complex networks has remained largely elusive. In this work, we use techniques inspired by quantum statistical mechanics to define an entropy measure for complex networks and to develop a set of information-theoretic tools, based on network spectral properties, such as Rényi q entropy, generalized Kullback-Leibler and Jensen-Shannon divergences, the latter allowing us to define a natural distance measure between complex networks. First, we show that by minimizing the Kullback-Leibler divergence between an observed network and a parametric network model, inference of model parameter(s) by means of maximum-likelihood estimation can be achieved and model selection can be performed with appropriate information criteria. Second, we show that the information-theoretic metric quantifies the distance between pairs of networks and we can use it, for instance, to cluster the layers of a multilayer system. By applying this framework to networks corresponding to sites of the human microbiome, we perform hierarchical cluster analysis and recover with high accuracy existing community-based associations. Our results imply that spectral-based statistical inference in complex networks results in demonstrably superior performance as well as a conceptual backbone, filling a gap towards a network information theory.

Computational Methods for Configurational Entropy Using Internal and Cartesian Coordinates.

PubMed

Hikiri, Simon; Yoshidome, Takashi; Ikeguchi, Mitsunori

2016-12-13

The configurational entropy of solute molecules is a crucially important quantity to study various biophysical processes. Consequently, it is necessary to establish an efficient quantitative computational method to calculate configurational entropy as accurately as possible. In the present paper, we investigate the quantitative performance of the quasi-harmonic and related computational methods, including widely used methods implemented in popular molecular dynamics (MD) software packages, compared with the Clausius method, which is capable of accurately computing the change of the configurational entropy upon temperature change. Notably, we focused on the choice of the coordinate systems (i.e., internal or Cartesian coordinates). The Boltzmann-quasi-harmonic (BQH) method using internal coordinates outperformed all the six methods examined here. The introduction of improper torsions in the BQH method improves its performance, and anharmonicity of proper torsions in proteins is identified to be the origin of the superior performance of the BQH method. In contrast, widely used methods implemented in MD packages show rather poor performance. In addition, the enhanced sampling of replica-exchange MD simulations was found to be efficient for the convergent behavior of entropy calculations. Also in folding/unfolding transitions of a small protein, Chignolin, the BQH method was reasonably accurate. However, the independent term without the correlation term in the BQH method was most accurate for the folding entropy among the methods considered in this study, because the QH approximation of the correlation term in the BQH method was no longer valid for the divergent unfolded structures.

Identification of hydrometeor mixtures in polarimetric radar measurements and their linear de-mixing

NASA Astrophysics Data System (ADS)

Besic, Nikola; Ventura, Jordi Figueras i.; Grazioli, Jacopo; Gabella, Marco; Germann, Urs; Berne, Alexis

2017-04-01

The issue of hydrometeor mixtures affects radar sampling volumes without a clear dominant hydrometeor type. Containing a number of different hydrometeor types which significantly contribute to the polarimetric variables, these volumes are likely to occur in the vicinity of the melting layer and mainly, at large distance from a given radar. Motivated by potential benefits for both quantitative and qualitative applications of dual-pol radar, we propose a method for the identification of hydrometeor mixtures and their subsequent linear de-mixing. This method is intrinsically related to our recently proposed semi-supervised approach for hydrometeor classification. The mentioned classification approach [1] performs labeling of radar sampling volumes by using as a criterion the Euclidean distance with respect to five-dimensional centroids, depicting nine hydrometeor classes. The positions of the centroids in the space formed by four radar moments and one external parameter (phase indicator), are derived through a technique of k-medoids clustering, applied on a selected representative set of radar observations, and coupled with statistical testing which introduces the assumed microphysical properties of the different hydrometeor types. Aside from a hydrometeor type label, each radar sampling volume is characterized by an entropy estimate, indicating the uncertainty of the classification. Here, we revisit the concept of entropy presented in [1], in order to emphasize its presumed potential for the identification of hydrometeor mixtures. The calculation of entropy is based on the estimate of the probability (pi ) that the observation corresponds to the hydrometeor type i (i = 1,ṡṡṡ9) . The probability is derived from the Euclidean distance (di ) of the observation to the centroid characterizing the hydrometeor type i . The parametrization of the d → p transform is conducted in a controlled environment, using synthetic polarimetric radar datasets. It ensures balanced entropy values: low for pure volumes, and high for different possible combinations of mixed hydrometeors. The parametrized entropy is further on applied to real polarimetric C and X band radar datasets, where we demonstrate the potential of linear de-mixing using a simplex formed by a set of pre-defined centroids in the five-dimensional space. As main outcome, the proposed approach allows to provide plausible proportions of the different hydrometeors contained in a given radar sampling volume. [1] Besic, N., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach, Atmos. Meas. Tech., 9, 4425-4445, doi:10.5194/amt-9-4425-2016, 2016.

Financial time series analysis based on effective phase transfer entropy

NASA Astrophysics Data System (ADS)

Yang, Pengbo; Shang, Pengjian; Lin, Aijing

2017-02-01

Transfer entropy is a powerful technique which is able to quantify the impact of one dynamic system on another system. In this paper, we propose the effective phase transfer entropy method based on the transfer entropy method. We use simulated data to test the performance of this method, and the experimental results confirm that the proposed approach is capable of detecting the information transfer between the systems. We also explore the relationship between effective phase transfer entropy and some variables, such as data size, coupling strength and noise. The effective phase transfer entropy is positively correlated with the data size and the coupling strength. Even in the presence of a large amount of noise, it can detect the information transfer between systems, and it is very robust to noise. Moreover, this measure is indeed able to accurately estimate the information flow between systems compared with phase transfer entropy. In order to reflect the application of this method in practice, we apply this method to financial time series and gain new insight into the interactions between systems. It is demonstrated that the effective phase transfer entropy can be used to detect some economic fluctuations in the financial market. To summarize, the effective phase transfer entropy method is a very efficient tool to estimate the information flow between systems.

Time-series analysis of multiple foreign exchange rates using time-dependent pattern entropy

NASA Astrophysics Data System (ADS)

Ishizaki, Ryuji; Inoue, Masayoshi

2018-01-01

Time-dependent pattern entropy is a method that reduces variations to binary symbolic dynamics and considers the pattern of symbols in a sliding temporal window. We use this method to analyze the instability of daily variations in multiple foreign exchange rates. The time-dependent pattern entropy of 7 foreign exchange rates (AUD/USD, CAD/USD, CHF/USD, EUR/USD, GBP/USD, JPY/USD, and NZD/USD) was found to be high in the long period after the Lehman shock, and be low in the long period after Mar 2012. We compared the correlation matrix between exchange rates in periods of high and low of the time-dependent pattern entropy.

The third order correction on Hawking radiation and entropy conservation during black hole evaporation process

NASA Astrophysics Data System (ADS)

Yan, Hao-Peng; Liu, Wen-Biao

2016-08-01

Using Parikh-Wilczek tunneling framework, we calculate the tunneling rate from a Schwarzschild black hole under the third order WKB approximation, and then obtain the expressions for emission spectrum and black hole entropy to the third order correction. The entropy contains four terms including the Bekenstein-Hawking entropy, the logarithmic term, the inverse area term, and the square of inverse area term. In addition, we analyse the correlation between sequential emissions under this approximation. It is shown that the entropy is conserved during the process of black hole evaporation, which consists with the request of quantum mechanics and implies the information is conserved during this process. We also compare the above result with that of pure thermal spectrum case, and find that the non-thermal correction played an important role.

Two faces of entropy and information in biological systems.

PubMed

Mitrokhin, Yuriy

2014-10-21

The article attempts to overcome the well-known paradox of contradictions between the emerging biological organization and entropy production in biological systems. It is assumed that quality, speculative correlation between entropy and antientropy processes taking place both in the past and today in the metabolic and genetic cellular systems may be perfectly authorized for adequate description of the evolution of biological organization. So far as thermodynamic entropy itself cannot compensate for the high degree of organization which exists in the cell, we discuss the mode of conjunction of positive entropy events (mutations) in the genetic systems of the past generations and the formation of organized structures of current cells. We argue that only the information which is generated in the conditions of the information entropy production (mutations and other genome reorganization) in genetic systems of the past generations provides the physical conjunction of entropy and antientropy processes separated from each other in time generations. It is readily apparent from the requirements of the Second law of thermodynamics. Copyright © 2014 Elsevier Ltd. All rights reserved.

Clarifying the link between von Neumann and thermodynamic entropies

NASA Astrophysics Data System (ADS)

Deville, Alain; Deville, Yannick

2013-01-01

The state of a quantum system being described by a density operator ρ, quantum statistical mechanics calls the quantity - kTr( ρln ρ), introduced by von Neumann, its von Neumann or statistical entropy. A 1999 Shenker's paper initiated a debate about its link with the entropy of phenomenological thermodynamics. Referring to Gibbs's and von Neumann's founding texts, we replace von Neumann's 1932 contribution in its historical context, after Gibbs's 1902 treatise and before the creation of the information entropy concept, which places boundaries into the debate. Reexamining von Neumann's reasoning, we stress that the part of his reasoning implied in the debate mainly uses thermodynamics, not quantum mechanics, and identify two implicit postulates. We thoroughly examine Shenker's and ensuing papers, insisting upon the presence of open thermodynamical subsystems, imposing us the use of the chemical potential concept. We briefly mention Landau's approach to the quantum entropy. On the whole, it is shown that von Neumann's viewpoint is right, and why Shenker's claim that von Neumann entropy "is not the quantum-mechanical correlate of thermodynamic entropy" can't be retained.

Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome

NASA Astrophysics Data System (ADS)

Teschendorff, Andrew E.; Enver, Tariq

2017-06-01

The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes.

Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptome

PubMed Central

Teschendorff, Andrew E.; Enver, Tariq

2017-01-01

The ability to quantify differentiation potential of single cells is a task of critical importance. Here we demonstrate, using over 7,000 single-cell RNA-Seq profiles, that differentiation potency of a single cell can be approximated by computing the signalling promiscuity, or entropy, of a cell's transcriptome in the context of an interaction network, without the need for feature selection. We show that signalling entropy provides a more accurate and robust potency estimate than other entropy-based measures, driven in part by a subtle positive correlation between the transcriptome and connectome. Signalling entropy identifies known cell subpopulations of varying potency and drug resistant cancer stem-cell phenotypes, including those derived from circulating tumour cells. It further reveals that expression heterogeneity within single-cell populations is regulated. In summary, signalling entropy allows in silico estimation of the differentiation potency and plasticity of single cells and bulk samples, providing a means to identify normal and cancer stem-cell phenotypes. PMID:28569836

Evaluation of cluster expansions and correlated one-body properties of nuclei

NASA Astrophysics Data System (ADS)

Moustakidis, Ch. C.; Massen, S. E.; Panos, C. P.; Grypeos, M. E.; Antonov, A. N.

2001-07-01

Three different cluster expansions for the evaluation of correlated one-body properties of s-p and s-d shell nuclei are compared. Harmonic oscillator wave functions and Jastrow-type correlations are used, while analytical expressions are obtained for the charge form factor, density distribution, and momentum distribution by truncating the expansions and using a standard Jastrow correlation function f. The harmonic oscillator parameter b and the correlation parameter β have been determined by a least-squares fit to the experimental charge form factors in each case. The information entropy of nuclei in position space (Sr) and momentum space (Sk) according to the three methods are also calculated. It is found that the larger the entropy sum, S=Sr+Sk (the net information content of the system), the smaller the values of χ2. This indicates that maximal S is a criterion of the quality of a given nuclear model, according to the maximum entropy principle. Only two exceptions to this rule, out of many cases examined, were found. Finally an analytic expression for the so-called ``healing'' or ``wound'' integrals is derived with the function f considered, for any state of the relative two-nucleon motion, and their values in certain cases are computed and compared.

Complex Networks/Foundations of Information Systems

DTIC Science & Technology

2013-03-06

the benefit of feedback or dynamic correlations in coding and protocol. Using Renyi correlation analysis and entropy to model this wider class of...dynamic heterogeneous conditions. Lizhong Zheng, MIT Renyi Channel Correlation Analysis (connected to geometric curvature) Network Channel

Measurement of entanglement entropy in the two-dimensional Potts model using wavelet analysis.

PubMed

Tomita, Yusuke

2018-05-01

A method is introduced to measure the entanglement entropy using a wavelet analysis. Using this method, the two-dimensional Haar wavelet transform of a configuration of Fortuin-Kasteleyn (FK) clusters is performed. The configuration represents a direct snapshot of spin-spin correlations since spin degrees of freedom are traced out in FK representation. A snapshot of FK clusters loses image information at each coarse-graining process by the wavelet transform. It is shown that the loss of image information measures the entanglement entropy in the Potts model.

Pedagogical introduction to the entropy of entanglement for Gaussian states

NASA Astrophysics Data System (ADS)

Demarie, Tommaso F.

2018-05-01

In quantum information theory, the entropy of entanglement is a standard measure of bipartite entanglement between two partitions of a composite system. For a particular class of continuous variable quantum states, the Gaussian states, the entropy of entanglement can be expressed elegantly in terms of symplectic eigenvalues, elements that characterise a Gaussian state and depend on the correlations of the canonical variables. We give a rigorous step-by-step derivation of this result and provide physical insights, together with an example that can be useful in practice for calculations.

Breakdown of the equal area law for holographic entanglement entropy

NASA Astrophysics Data System (ADS)

McCarthy, Fiona; Kubizňák, David; Mann, Robert B.

2017-11-01

We investigate a holographic version of Maxwell's equal area law analogous to that for the phase transition in the black hole temperature/black hole entropy plane of a charged AdS black hole. We consider proposed area laws for both the black hole temperature/holographic entanglement entropy plane and the black hole temperature/2- point correlation function plane. Despite recent claims to the contrary, we demonstrate numerically that neither proposal is valid. We argue that there is no physical reason to expect such a construction in these planes.

Mutual Information Item Selection in Adaptive Classification Testing

ERIC Educational Resources Information Center

Weissman, Alexander

2007-01-01

A general approach for item selection in adaptive multiple-category classification tests is provided. The approach uses mutual information (MI), a special case of the Kullback-Leibler distance, or relative entropy. MI works efficiently with the sequential probability ratio test and alleviates the difficulties encountered with using other local-…

Performance Analysis of Entropy Methods on K Means in Clustering Process

NASA Astrophysics Data System (ADS)

Dicky Syahputra Lubis, Mhd.; Mawengkang, Herman; Suwilo, Saib

2017-12-01

K Means is a non-hierarchical data clustering method that attempts to partition existing data into one or more clusters / groups. This method partitions the data into clusters / groups so that data that have the same characteristics are grouped into the same cluster and data that have different characteristics are grouped into other groups.The purpose of this data clustering is to minimize the objective function set in the clustering process, which generally attempts to minimize variation within a cluster and maximize the variation between clusters. However, the main disadvantage of this method is that the number k is often not known before. Furthermore, a randomly chosen starting point may cause two points to approach the distance to be determined as two centroids. Therefore, for the determination of the starting point in K Means used entropy method where this method is a method that can be used to determine a weight and take a decision from a set of alternatives. Entropy is able to investigate the harmony in discrimination among a multitude of data sets. Using Entropy criteria with the highest value variations will get the highest weight. Given this entropy method can help K Means work process in determining the starting point which is usually determined at random. Thus the process of clustering on K Means can be more quickly known by helping the entropy method where the iteration process is faster than the K Means Standard process. Where the postoperative patient dataset of the UCI Repository Machine Learning used and using only 12 data as an example of its calculations is obtained by entropy method only with 2 times iteration can get the desired end result.

Hydration entropy change from the hard sphere model.

PubMed

Graziano, Giuseppe; Lee, Byungkook

2002-12-10

The gas to liquid transfer entropy change for a pure non-polar liquid can be calculated quite accurately using a hard sphere model that obeys the Carnahan-Starling equation of state. The same procedure fails to produce a reasonable value for hydrogen bonding liquids such as water, methanol and ethanol. However, the size of the molecules increases when the hydrogen bonds are turned off to produce the hard sphere system and the volume packing density rises. We show here that the hard sphere system that has this increased packing density reproduces the experimental transfer entropy values rather well. The gas to water transfer entropy values for small non-polar hydrocarbons is also not reproduced by a hard sphere model, whether one uses the normal (2.8 A diameter) or the increased (3.2 A) size for water. At least part of the reason that the hard sphere model with 2.8 A size water produces too small entropy change is that the size of water is too small for a system without hydrogen bonds. The reason that the 3.2 A model also produces too small entropy values is that this is an overly crowded system and that the free volume introduced in the system by the addition of a solute molecule produces too much of a relief to this crowding. A hard sphere model, in which the free volume increase is limited by requiring that the average surface-to-surface distance between the solute and water molecules is the same as that between the increased-size water molecules, does approximately reproduce the experimental hydration entropy values. Copyright 2002 Elsevier Science B.V.

Entropy of international trades

NASA Astrophysics Data System (ADS)

Oh, Chang-Young; Lee, D.-S.

2017-05-01

The organization of international trades is highly complex under the collective efforts towards economic profits of participating countries given inhomogeneous resources for production. Considering the trade flux as the probability of exporting a product from a country to another, we evaluate the entropy of the world trades in the period 1950-2000. The trade entropy has increased with time, and we show that it is mainly due to the extension of trade partnership. For a given number of trade partners, the mean trade entropy is about 60% of the maximum possible entropy, independent of time, which can be regarded as a characteristic of the trade fluxes' heterogeneity and is shown to be derived from the scaling and functional behaviors of the universal trade-flux distribution. The correlation and time evolution of the individual countries' gross-domestic products and the number of trade partners show that most countries achieved their economic growth partly by extending their trade relationship.

Dynamical manifestations of quantum chaos

NASA Astrophysics Data System (ADS)

Torres Herrera, Eduardo Jonathan; Santos, Lea

2017-04-01

A main feature of a chaotic quantum system is a rigid spectrum, where the levels do not cross. Dynamical quantities, such as the von Neumann entanglement entropy, Shannon information entropy, and out-of-time correlators can differentiate the ergodic from the nonergodic phase in disordered interacting systems, but not level repulsion from level crossing in the delocalized phase of disordered and clean models. This is in contrast with the long-time evolution of the survival probability of the initial state. The onset of correlated energy levels is manifested by a drop, referred to as correlation hole, below the asymptotic value of the survival probability. The correlation hole is an unambiguous indicator of the presence of level repulsion. EJTH is grateful to VIEP, BUAP for financial support through the VIEP projects program.

Inferring Weighted Directed Association Network from Multivariate Time Series with a Synthetic Method of Partial Symbolic Transfer Entropy Spectrum and Granger Causality

PubMed Central

Hu, Yanzhu; Ai, Xinbo

2016-01-01

Complex network methodology is very useful for complex system explorer. However, the relationships among variables in complex system are usually not clear. Therefore, inferring association networks among variables from their observed data has been a popular research topic. We propose a synthetic method, named small-shuffle partial symbolic transfer entropy spectrum (SSPSTES), for inferring association network from multivariate time series. The method synthesizes surrogate data, partial symbolic transfer entropy (PSTE) and Granger causality. A proper threshold selection is crucial for common correlation identification methods and it is not easy for users. The proposed method can not only identify the strong correlation without selecting a threshold but also has the ability of correlation quantification, direction identification and temporal relation identification. The method can be divided into three layers, i.e. data layer, model layer and network layer. In the model layer, the method identifies all the possible pair-wise correlation. In the network layer, we introduce a filter algorithm to remove the indirect weak correlation and retain strong correlation. Finally, we build a weighted adjacency matrix, the value of each entry representing the correlation level between pair-wise variables, and then get the weighted directed association network. Two numerical simulated data from linear system and nonlinear system are illustrated to show the steps and performance of the proposed approach. The ability of the proposed method is approved by an application finally. PMID:27832153

Quantifying ‘Causality’ in Complex Systems: Understanding Transfer Entropy

PubMed Central

Abdul Razak, Fatimah; Jensen, Henrik Jeldtoft

2014-01-01

‘Causal’ direction is of great importance when dealing with complex systems. Often big volumes of data in the form of time series are available and it is important to develop methods that can inform about possible causal connections between the different observables. Here we investigate the ability of the Transfer Entropy measure to identify causal relations embedded in emergent coherent correlations. We do this by firstly applying Transfer Entropy to an amended Ising model. In addition we use a simple Random Transition model to test the reliability of Transfer Entropy as a measure of ‘causal’ direction in the presence of stochastic fluctuations. In particular we systematically study the effect of the finite size of data sets. PMID:24955766

How long the singular value decomposed entropy predicts the stock market? - Evidence from the Dow Jones Industrial Average Index

NASA Astrophysics Data System (ADS)

Gu, Rongbao; Shao, Yanmin

2016-07-01

In this paper, a new concept of multi-scales singular value decomposition entropy based on DCCA cross correlation analysis is proposed and its predictive power for the Dow Jones Industrial Average Index is studied. Using Granger causality analysis with different time scales, it is found that, the singular value decomposition entropy has predictive power for the Dow Jones Industrial Average Index for period less than one month, but not for more than one month. This shows how long the singular value decomposition entropy predicts the stock market that extends Caraiani's result obtained in Caraiani (2014). On the other hand, the result also shows an essential characteristic of stock market as a chaotic dynamic system.

Predicting protein β-sheet contacts using a maximum entropy-based correlated mutation measure.

PubMed

Burkoff, Nikolas S; Várnai, Csilla; Wild, David L

2013-03-01

The problem of ab initio protein folding is one of the most difficult in modern computational biology. The prediction of residue contacts within a protein provides a more tractable immediate step. Recently introduced maximum entropy-based correlated mutation measures (CMMs), such as direct information, have been successful in predicting residue contacts. However, most correlated mutation studies focus on proteins that have large good-quality multiple sequence alignments (MSA) because the power of correlated mutation analysis falls as the size of the MSA decreases. However, even with small autogenerated MSAs, maximum entropy-based CMMs contain information. To make use of this information, in this article, we focus not on general residue contacts but contacts between residues in β-sheets. The strong constraints and prior knowledge associated with β-contacts are ideally suited for prediction using a method that incorporates an often noisy CMM. Using contrastive divergence, a statistical machine learning technique, we have calculated a maximum entropy-based CMM. We have integrated this measure with a new probabilistic model for β-contact prediction, which is used to predict both residue- and strand-level contacts. Using our model on a standard non-redundant dataset, we significantly outperform a 2D recurrent neural network architecture, achieving a 5% improvement in true positives at the 5% false-positive rate at the residue level. At the strand level, our approach is competitive with the state-of-the-art single methods achieving precision of 61.0% and recall of 55.4%, while not requiring residue solvent accessibility as an input. http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software/

Connecting complexity with spectral entropy using the Laplace transformed solution to the fractional diffusion equation

NASA Astrophysics Data System (ADS)

Liang, Yingjie; Chen, Wen; Magin, Richard L.

2016-07-01

Analytical solutions to the fractional diffusion equation are often obtained by using Laplace and Fourier transforms, which conveniently encode the order of the time and the space derivatives (α and β) as non-integer powers of the conjugate transform variables (s, and k) for the spectral and the spatial frequencies, respectively. This study presents a new solution to the fractional diffusion equation obtained using the Laplace transform and expressed as a Fox's H-function. This result clearly illustrates the kinetics of the underlying stochastic process in terms of the Laplace spectral frequency and entropy. The spectral entropy is numerically calculated by using the direct integration method and the adaptive Gauss-Kronrod quadrature algorithm. Here, the properties of spectral entropy are investigated for the cases of sub-diffusion and super-diffusion. We find that the overall spectral entropy decreases with the increasing α and β, and that the normal or Gaussian case with α = 1 and β = 2, has the lowest spectral entropy (i.e., less information is needed to describe the state of a Gaussian process). In addition, as the neighborhood over which the entropy is calculated increases, the spectral entropy decreases, which implies a spatial averaging or coarse graining of the material properties. Consequently, the spectral entropy is shown to provide a new way to characterize the temporal correlation of anomalous diffusion. Future studies should be designed to examine changes of spectral entropy in physical, chemical and biological systems undergoing phase changes, chemical reactions and tissue regeneration.

Cellular network entropy as the energy potential in Waddington's differentiation landscape

PubMed Central

Banerji, Christopher R. S.; Miranda-Saavedra, Diego; Severini, Simone; Widschwendter, Martin; Enver, Tariq; Zhou, Joseph X.; Teschendorff, Andrew E.

2013-01-01

Differentiation is a key cellular process in normal tissue development that is significantly altered in cancer. Although molecular signatures characterising pluripotency and multipotency exist, there is, as yet, no single quantitative mark of a cellular sample's position in the global differentiation hierarchy. Here we adopt a systems view and consider the sample's network entropy, a measure of signaling pathway promiscuity, computable from a sample's genome-wide expression profile. We demonstrate that network entropy provides a quantitative, in-silico, readout of the average undifferentiated state of the profiled cells, recapitulating the known hierarchy of pluripotent, multipotent and differentiated cell types. Network entropy further exhibits dynamic changes in time course differentiation data, and in line with a sample's differentiation stage. In disease, network entropy predicts a higher level of cellular plasticity in cancer stem cell populations compared to ordinary cancer cells. Importantly, network entropy also allows identification of key differentiation pathways. Our results are consistent with the view that pluripotency is a statistical property defined at the cellular population level, correlating with intra-sample heterogeneity, and driven by the degree of signaling promiscuity in cells. In summary, network entropy provides a quantitative measure of a cell's undifferentiated state, defining its elevation in Waddington's landscape. PMID:24154593

Modern Quantum Field Theory II - Proceeeings of the International Colloquium

NASA Astrophysics Data System (ADS)

Das, S. R.; Mandal, G.; Mukhi, S.; Wadia, S. R.

1995-08-01

The Table of Contents for the book is as follows: * Foreword * 1. Black Holes and Quantum Gravity * Quantum Black Holes and the Problem of Time * Black Hole Entropy and the Semiclassical Approximation * Entropy and Information Loss in Two Dimensions * Strings on a Cone and Black Hole Entropy (Abstract) * Boundary Dynamics, Black Holes and Spacetime Fluctuations in Dilation Gravity (Abstract) * Pair Creation of Black Holes (Abstract) * A Brief View of 2-Dim. String Theory and Black Holes (Abstract) * 2. String Theory * Non-Abelian Duality in WZW Models * Operators and Correlation Functions in c ≤ 1 String Theory * New Symmetries in String Theory * A Look at the Discretized Superstring Using Random Matrices * The Nested BRST Structure of Wn-Symmetries * Landau-Ginzburg Model for a Critical Topological String (Abstract) * On the Geometry of Wn Gravity (Abstract) * O(d, d) Tranformations, Marginal Deformations and the Coset Construction in WZNW Models (Abstract) * Nonperturbative Effects and Multicritical Behaviour of c = 1 Matrix Model (Abstract) * Singular Limits and String Solutions (Abstract) * BV Algebra on the Moduli Spaces of Riemann Surfaces and String Field Theory (Abstract) * 3. Condensed Matter and Statistical Mechanics * Stochastic Dynamics in a Deposition-Evaporation Model on a Line * Models with Inverse-Square Interactions: Conjectured Dynamical Correlation Functions of the Calogero-Sutherland Model at Rational Couplings * Turbulence and Generic Scale Invariance * Singular Perturbation Approach to Phase Ordering Dynamics * Kinetics of Diffusion-Controlled and Ballistically-Controlled Reactions * Field Theory of a Frustrated Heisenberg Spin Chain * FQHE Physics in Relativistic Field Theories * Importance of Initial Conditions in Determining the Dynamical Class of Cellular Automata (Abstract) * Do Hard-Core Bosons Exhibit Quantum Hall Effect? (Abstract) * Hysteresis in Ferromagnets * 4. Fundamental Aspects of Quantum Mechanics and Quantum Field Theory * Finite Quantum Physics and Noncommutative Geometry * Higgs as Gauge Field and the Standard Model * Canonical Quantisation of an Off-Conformal Theory * Deterministic Quantum Mechanics in One Dimension * Spin-Statistics Relations for Topological Geons in 2+1 Quantum Gravity * Generalized Fock Spaces * Geometrical Expression for Short Distance Singularities in Field Theory * 5. Mathematics and Quantum Field Theory * Knot Invariants from Quantum Field Theories * Infinite Grassmannians and Moduli Spaces of G-Bundles * A Review of an Algebraic Geometry Approach to a Model Quantum Field Theory on a Curve (Abstract) * 6. Integrable Models * Spectral Representation of Correlation Functions in Two-Dimensional Quantum Field Theories * On Various Avatars of the Pasquier Algebra * Supersymmetric Integrable Field Theories and Eight Vertex Free Fermion Models (Abstract) * 7. Lattice Field Theory * From Kondo Model and Strong Coupling Lattice QCD to the Isgur-Wise Function * Effective Confinement from a Logarithmically Running Coupling (Abstract)

Molecular recognition in a diverse set of protein-ligand interactions studied with molecular dynamics simulations and end-point free energy calculations.

PubMed

Wang, Bo; Li, Liwei; Hurley, Thomas D; Meroueh, Samy O

2013-10-28

End-point free energy calculations using MM-GBSA and MM-PBSA provide a detailed understanding of molecular recognition in protein-ligand interactions. The binding free energy can be used to rank-order protein-ligand structures in virtual screening for compound or target identification. Here, we carry out free energy calculations for a diverse set of 11 proteins bound to 14 small molecules using extensive explicit-solvent MD simulations. The structure of these complexes was previously solved by crystallography and their binding studied with isothermal titration calorimetry (ITC) data enabling direct comparison to the MM-GBSA and MM-PBSA calculations. Four MM-GBSA and three MM-PBSA calculations reproduced the ITC free energy within 1 kcal·mol(-1) highlighting the challenges in reproducing the absolute free energy from end-point free energy calculations. MM-GBSA exhibited better rank-ordering with a Spearman ρ of 0.68 compared to 0.40 for MM-PBSA with dielectric constant (ε = 1). An increase in ε resulted in significantly better rank-ordering for MM-PBSA (ρ = 0.91 for ε = 10), but larger ε significantly reduced the contributions of electrostatics, suggesting that the improvement is due to the nonpolar and entropy components, rather than a better representation of the electrostatics. The SVRKB scoring function applied to MD snapshots resulted in excellent rank-ordering (ρ = 0.81). Calculations of the configurational entropy using normal-mode analysis led to free energies that correlated significantly better to the ITC free energy than the MD-based quasi-harmonic approach, but the computed entropies showed no correlation with the ITC entropy. When the adaptation energy is taken into consideration by running separate simulations for complex, apo, and ligand (MM-PBSAADAPT), there is less agreement with the ITC data for the individual free energies, but remarkably good rank-ordering is observed (ρ = 0.89). Interestingly, filtering MD snapshots by prescoring protein-ligand complexes with a machine learning-based approach (SVMSP) resulted in a significant improvement in the MM-PBSA results (ε = 1) from ρ = 0.40 to ρ = 0.81. Finally, the nonpolar components of MM-GBSA and MM-PBSA, but not the electrostatic components, showed strong correlation to the ITC free energy; the computed entropies did not correlate with the ITC entropy.

Molecular Recognition in a Diverse Set of Protein-Ligand Interactions Studied with Molecular Dynamics Simulations and End-Point Free Energy Calculations

PubMed Central

Wang, Bo; Li, Liwei; Hurley, Thomas D.; Meroueh, Samy O.

2014-01-01

End-point free energy calculations using MM-GBSA and MM-PBSA provide a detailed understanding of molecular recognition in protein-ligand interactions. The binding free energy can be used to rank-order protein-ligand structures in virtual screening for compound or target identification. Here, we carry out free energy calculations for a diverse set of 11 proteins bound to 14 small molecules using extensive explicit-solvent MD simulations. The structure of these complexes was previously solved by crystallography and their binding studied with isothermal titration calorimetry (ITC) data enabling direct comparison to the MM-GBSA and MM-PBSA calculations. Four MM-GBSA and three MM-PBSA calculations reproduced the ITC free energy within 1 kcal•mol−1 highlighting the challenges in reproducing the absolute free energy from end-point free energy calculations. MM-GBSA exhibited better rank-ordering with a Spearman ρ of 0.68 compared to 0.40 for MM-PBSA with dielectric constant (ε = 1). An increase in ε resulted in significantly better rank-ordering for MM-PBSA (ρ = 0.91 for ε = 10). But larger ε significantly reduced the contributions of electrostatics, suggesting that the improvement is due to the non-polar and entropy components, rather than a better representation of the electrostatics. SVRKB scoring function applied to MD snapshots resulted in excellent rank-ordering (ρ = 0.81). Calculations of the configurational entropy using normal mode analysis led to free energies that correlated significantly better to the ITC free energy than the MD-based quasi-harmonic approach, but the computed entropies showed no correlation with the ITC entropy. When the adaptation energy is taken into consideration by running separate simulations for complex, apo and ligand (MM-PBSAADAPT), there is less agreement with the ITC data for the individual free energies, but remarkably good rank-ordering is observed (ρ = 0.89). Interestingly, filtering MD snapshots by pre-scoring protein-ligand complexes with a machine learning-based approach (SVMSP) resulted in a significant improvement in the MM-PBSA results (ε = 1) from ρ = 0.40 to ρ = 0.81. Finally, the non-polar components of MM-GBSA and MM-PBSA, but not the electrostatic components, showed strong correlation to the ITC free energy; the computed entropies did not correlate with the ITC entropy. PMID:24032517

Differences between state entropy and bispectral index during analysis of identical electroencephalogram signals: a comparison with two randomised anaesthetic techniques.

PubMed

Pilge, Stefanie; Kreuzer, Matthias; Karatchiviev, Veliko; Kochs, Eberhard F; Malcharek, Michael; Schneider, Gerhard

2015-05-01

It is claimed that bispectral index (BIS) and state entropy reflect an identical clinical spectrum, the hypnotic component of anaesthesia. So far, it is not known to what extent different devices display similar index values while processing identical electroencephalogram (EEG) signals. To compare BIS and state entropy during analysis of identical EEG data. Inspection of raw EEG input to detect potential causes of erroneous index calculation. Offline re-analysis of EEG data from a randomised, single-centre controlled trial using the Entropy Module and an Aspect A-2000 monitor. Klinikum rechts der Isar, Technische Universität München, Munich. Forty adult patients undergoing elective surgery under general anaesthesia. Blocked randomisation of 20 patients per anaesthetic group (sevoflurane/remifentanil or propofol/remifentanil). Isolated forearm technique for differentiation between consciousness and unconsciousness. Prediction probability (PK) of state entropy to discriminate consciousness from unconsciousness. Correlation and agreement between state entropy and BIS from deep to light hypnosis. Analysis of raw EEG compared with index values that are in conflict with clinical examination, with frequency measures (frequency bands/Spectral Edge Frequency 95) and visual inspection for physiological EEG patterns (e.g. beta or delta arousal), pathophysiological features such as high-frequency signals (electromyogram/high-frequency EEG or eye fluttering/saccades), different types of electro-oculogram or epileptiform EEG and technical artefacts. PK of state entropy was 0.80 and of BIS 0.84; correlation coefficient of state entropy with BIS 0.78. Nine percent BIS and 14% state entropy values disagreed with clinical examination. Highest incidence of disagreement occurred after state transitions, in particular for state entropy after loss of consciousness during sevoflurane anaesthesia. EEG sequences which led to false 'conscious' index values often showed high-frequency signals and eye blinks. High-frequency EEG/electromyogram signals were pooled because a separation into EEG and fast electro-oculogram, for example eye fluttering or saccades, on the basis of a single EEG channel may not be very reliable. These signals led to higher Spectral Edge Frequency 95 and ratio of relative beta and gamma band power than EEG signals, indicating adequate unconscious classification. The frequency of other artefacts that were assignable, for example technical artefacts, movement artefacts, was negligible and they were excluded from analysis. High-frequency signals and eye blinks may account for index values that falsely indicate consciousness. Compared with BIS, state entropy showed more false classifications of the clinical state at transition between consciousness and unconsciousness.

Correlation between magnetocaloric and electrical properties based on phenomenological models in La0.47Pr0.2Pb0.33MnO3 perovskite

NASA Astrophysics Data System (ADS)

Mechi, Nesrine; Alzahrani, Bandar; Hcini, Sobhi; Bouazizi, Mohamed Lamjed; Dhahri, Abdessalem

2018-06-01

We have investigated the correlation between magnetocaloric and electrical properties of La0.47Pr0.2Pb0.33MnO3 perovskite prepared using the sol-gel method. Rietveld analysis of X-ray diffraction (XRD) pattern shows pure crystalline phase with rhombohedral ? structure. Magnetic entropy change, relative cooling power (RCP) and specific heat were predicted from M(T, μ0H) data at different magnetic fields with the help of the phenomenological model. The magnetic entropy change reaches a maximum value ? of about 3.96 J kg-1 K-1 for μ0H = 5 T corresponding to RCP of 183 J kg-1. These values are relatively higher, making our sample a promising candidate for the magnetic refrigeration. Electrical-resistivity measurements were well fitted with the phenomenological percolation model, which is based on the phase segregation of ferromagnetic-metallic clusters and paramagnetic-semiconductor regions. The temperature and magnetic field dependences of resistivity data, ρ(T, μ0H), allowed us to determine the magnetic entropy change ?. Results show that the as-obtained magnetic entropy change values are similar to those determined from the phenomenological model.

Large entropy derived from low-frequency vibrations and its implications for hydrogen storage

NASA Astrophysics Data System (ADS)

Wang, Xiaoxia; Chen, Hongshan

2018-02-01

Adsorption and desorption are driven by the energy and entropy competition, but the entropy effect is often ignored in hydrogen storage and the optimal adsorption strength for the ambient storage is controversial in the literature. This letter investigated the adsorption states of the H2 molecule on M-B12C6N6 (M = Li, Na, Mg, Ca, and Sc) and analyzed the correlation among the zero point energy (ZPE), the entropy change, and the adsorption energy and their effects on the delivery capacities. The ZPE has large correction to the adsorption energy due to the light mass of hydrogen. The computations show that the potential energies along the spherical surface centered at the alkali metals are very flat and it leads to large entropy (˜70 J/mol.K) of the adsorbed H2 molecules. The entropy change can compensate the enthalpy change effectively, and the ambient storage can be realized with relatively weak adsorption of ΔH = -12 kJ/mol. The results are encouraging and instructive for the design of hydrogen storage materials.

Irreversible entropy model for damage diagnosis in resistors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cuadras, Angel, E-mail: angel.cuadras@upc.edu; Crisóstomo, Javier; Ovejas, Victoria J.

2015-10-28

We propose a method to characterize electrical resistor damage based on entropy measurements. Irreversible entropy and the rate at which it is generated are more convenient parameters than resistance for describing damage because they are essentially positive in virtue of the second law of thermodynamics, whereas resistance may increase or decrease depending on the degradation mechanism. Commercial resistors were tested in order to characterize the damage induced by power surges. Resistors were biased with constant and pulsed voltage signals, leading to power dissipation in the range of 4–8 W, which is well above the 0.25 W nominal power to initiate failure. Entropymore » was inferred from the added power and temperature evolution. A model is proposed to understand the relationship among resistance, entropy, and damage. The power surge dissipates into heat (Joule effect) and damages the resistor. The results show a correlation between entropy generation rate and resistor failure. We conclude that damage can be conveniently assessed from irreversible entropy generation. Our results for resistors can be easily extrapolated to other systems or machines that can be modeled based on their resistance.« less

Universality of quantum information in chaotic CFTs

NASA Astrophysics Data System (ADS)

Lashkari, Nima; Dymarsky, Anatoly; Liu, Hong

2018-03-01

We study the Eigenstate Thermalization Hypothesis (ETH) in chaotic conformal field theories (CFTs) of arbitrary dimensions. Assuming local ETH, we compute the reduced density matrix of a ball-shaped subsystem of finite size in the infinite volume limit when the full system is an energy eigenstate. This reduced density matrix is close in trace distance to a density matrix, to which we refer as the ETH density matrix, that is independent of all the details of an eigenstate except its energy and charges under global symmetries. In two dimensions, the ETH density matrix is universal for all theories with the same value of central charge. We argue that the ETH density matrix is close in trace distance to the reduced density matrix of the (micro)canonical ensemble. We support the argument in higher dimensions by comparing the Von Neumann entropy of the ETH density matrix with the entropy of a black hole in holographic systems in the low temperature limit. Finally, we generalize our analysis to the coherent states with energy density that varies slowly in space, and show that locally such states are well described by the ETH density matrix.

Enhancement of heat transfer and entropy generation analysis of nanofluids turbulent convection flow in square section tubes

NASA Astrophysics Data System (ADS)

Bianco, Vincenzo; Nardini, Sergio; Manca, Oronzio

2011-12-01

In this article, developing turbulent forced convection flow of a water-Al2O3 nanofluid in a square tube, subjected to constant and uniform wall heat flux, is numerically investigated. The mixture model is employed to simulate the nanofluid flow and the investigation is accomplished for particles size equal to 38 nm. An entropy generation analysis is also proposed in order to find the optimal working condition for the given geometry under given boundary conditions. A simple analytical procedure is proposed to evaluate the entropy generation and its results are compared with the numerical calculations, showing a very good agreement. A comparison of the resulting Nusselt numbers with experimental correlations available in literature is accomplished. To minimize entropy generation, the optimal Reynolds number is determined.

A Maximum Entropy Test for Evaluating Higher-Order Correlations in Spike Counts

PubMed Central

Onken, Arno; Dragoi, Valentin; Obermayer, Klaus

2012-01-01

Evaluating the importance of higher-order correlations of neural spike counts has been notoriously hard. A large number of samples are typically required in order to estimate higher-order correlations and resulting information theoretic quantities. In typical electrophysiology data sets with many experimental conditions, however, the number of samples in each condition is rather small. Here we describe a method that allows to quantify evidence for higher-order correlations in exactly these cases. We construct a family of reference distributions: maximum entropy distributions, which are constrained only by marginals and by linear correlations as quantified by the Pearson correlation coefficient. We devise a Monte Carlo goodness-of-fit test, which tests - for a given divergence measure of interest - whether the experimental data lead to the rejection of the null hypothesis that it was generated by one of the reference distributions. Applying our test to artificial data shows that the effects of higher-order correlations on these divergence measures can be detected even when the number of samples is small. Subsequently, we apply our method to spike count data which were recorded with multielectrode arrays from the primary visual cortex of anesthetized cat during an adaptation experiment. Using mutual information as a divergence measure we find that there are spike count bin sizes at which the maximum entropy hypothesis can be rejected for a substantial number of neuronal pairs. These results demonstrate that higher-order correlations can matter when estimating information theoretic quantities in V1. They also show that our test is able to detect their presence in typical in-vivo data sets, where the number of samples is too small to estimate higher-order correlations directly. PMID:22685392

Entanglement between random and clean quantum spin chains

NASA Astrophysics Data System (ADS)

Juhász, Róbert; Kovács, István A.; Roósz, Gergő; Iglói, Ferenc

2017-08-01

The entanglement entropy in clean, as well as in random quantum spin chains has a logarithmic size-dependence at the critical point. Here, we study the entanglement of composite systems that consist of a clean subsystem and a random subsystem, both being critical. In the composite, antiferromagnetic XX-chain with a sharp interface, the entropy is found to grow in a double-logarithmic fashion {{ S}}∼ \\ln\\ln(L) , where L is the length of the chain. We have also considered an extended defect at the interface, where the disorder penetrates into the homogeneous region in such a way that the strength of disorder decays with the distance l from the contact point as  ∼l-κ . For κ<1/2 , the entropy scales as {{ S}}(κ) ≃ \\frac{\\ln 2 (1-2κ)}{6}{\\ln L} , while for κ ≥slant 1/2 , when the extended interface defect is an irrelevant perturbation, we recover the double-logarithmic scaling. These results are explained through strong-disorder RG arguments.

Dynamic approximate entropy electroanatomic maps detect rotors in a simulated atrial fibrillation model.

PubMed

Ugarte, Juan P; Orozco-Duque, Andrés; Tobón, Catalina; Kremen, Vaclav; Novak, Daniel; Saiz, Javier; Oesterlein, Tobias; Schmitt, Clauss; Luik, Armin; Bustamante, John

2014-01-01

There is evidence that rotors could be drivers that maintain atrial fibrillation. Complex fractionated atrial electrograms have been located in rotor tip areas. However, the concept of electrogram fractionation, defined using time intervals, is still controversial as a tool for locating target sites for ablation. We hypothesize that the fractionation phenomenon is better described using non-linear dynamic measures, such as approximate entropy, and that this tool could be used for locating the rotor tip. The aim of this work has been to determine the relationship between approximate entropy and fractionated electrograms, and to develop a new tool for rotor mapping based on fractionation levels. Two episodes of chronic atrial fibrillation were simulated in a 3D human atrial model, in which rotors were observed. Dynamic approximate entropy maps were calculated using unipolar electrogram signals generated over the whole surface of the 3D atrial model. In addition, we optimized the approximate entropy calculation using two real multi-center databases of fractionated electrogram signals, labeled in 4 levels of fractionation. We found that the values of approximate entropy and the levels of fractionation are positively correlated. This allows the dynamic approximate entropy maps to localize the tips from stable and meandering rotors. Furthermore, we assessed the optimized approximate entropy using bipolar electrograms generated over a vicinity enclosing a rotor, achieving rotor detection. Our results suggest that high approximate entropy values are able to detect a high level of fractionation and to locate rotor tips in simulated atrial fibrillation episodes. We suggest that dynamic approximate entropy maps could become a tool for atrial fibrillation rotor mapping.

Enthalpy-entropy compensation: the role of solvation.

PubMed

Dragan, Anatoliy I; Read, Christopher M; Crane-Robinson, Colyn

2017-05-01

Structural modifications to interacting systems frequently lead to changes in both the enthalpy (heat) and entropy of the process that compensate each other, so that the Gibbs free energy is little changed: a major barrier to the development of lead compounds in drug discovery. The conventional explanation for such enthalpy-entropy compensation (EEC) is that tighter contacts lead to a more negative enthalpy but increased molecular constraints, i.e., a compensating conformational entropy reduction. Changes in solvation can also contribute to EEC but this contribution is infrequently discussed. We review long-established and recent cases of EEC and conclude that the large fluctuations in enthalpy and entropy observed are too great to be a result of only conformational changes and must result, to a considerable degree, from variations in the amounts of water immobilized or released on forming complexes. Two systems exhibiting EEC show a correlation between calorimetric entropies and local mobilities, interpreted to mean conformational control of the binding entropy/free energy. However, a substantial contribution from solvation gives the same effect, as a consequence of a structural link between the amount of bound water and the protein flexibility. Only by assuming substantial changes in solvation-an intrinsically compensatory process-can a more complete understanding of EEC be obtained. Faced with such large, and compensating, changes in the enthalpies and entropies of binding, the best approach to engineering elevated affinities must be through the addition of ionic links, as they generate increased entropy without affecting the enthalpy.

Three-dimensional positron emission tomography image texture analysis of esophageal squamous cell carcinoma: relationship between tumor 18F-fluorodeoxyglucose uptake heterogeneity, maximum standardized uptake value, and tumor stage.

PubMed

Dong, Xinzhe; Xing, Ligang; Wu, Peipei; Fu, Zheng; Wan, Honglin; Li, Dengwang; Yin, Yong; Sun, Xiaorong; Yu, Jinming

2013-01-01

To explore the relationship of a new PET image parameter, (18)F-fluorodeoxyglucose ((18)F-FDG) uptake heterogeneity assessed by texture analysis, with maximum standardized uptake value (SUV(max)) and tumor TNM staging. Forty consecutive patients with esophageal squamous cell carcinoma were enrolled. All patients underwent whole-body preoperative (18)F-FDG PET/CT. Heterogeneity of intratumoral (18)F-FDG uptake was assessed on the basis of the textural features (entropy and energy) of the three-dimensional images using MATLAB software. The correlations between the textural parameters and SUV(max), histological grade, tumor location, and TNM stage were analyzed. Tumors with higher SUV(max) were seen to be more heterogenous on (18)F-FDG uptake. Significant correlations were observed between T stage and SUV(max) (r(s)=0.390, P=0.013), entropy (rs=0.693, P<0.001), and energy (r(s)=-0.469, P=0.002). Correlations were also found between SUV(max), entropy, energy, and N stage (r(s)=0.326, P=0.04; r(s)=0.501, P=0.001; r(s)=-0.413, P=0.008). The American Joint Committee on Cancer stage correlated significantly with all metabolic parameters. The receiver-operating characteristic curve demonstrated an entropy of 4.699 as the optimal cutoff point for detecting tumors above stage II(b) with an areas under the ROC curve of 0.789 (P<0.001). This study provides initial evidence for the relationship between the new parameter of tumor uptake heterogeneity and the commonly used simplistic parameter of SUV and tumor stage. Our findings suggest a complementary role of these parameters in the staging and prognosis of esophageal squamous cell carcinoma.

Effect of age on the performance of bispectral and entropy indices during sevoflurane pediatric anesthesia: a pharmacometric study.

PubMed

Sciusco, Alberto; Standing, Joseph F; Sheng, Yucheng; Raimondo, Pasquale; Cinnella, Gilda; Dambrosio, Michele

2017-04-01

Bispectral index (BIS) and entropy monitors have been proposed for use in children, but research has not supported their validity for infants. However, effective monitoring of young children may be even more important than for adults, to aid appropriate anesthetic dosing and reduce the chance of adverse consequences. This prospective study aimed to investigate the relationships between age and the predictive performance of BIS and entropy monitors in measuring the anesthetic drug effects within a pediatric surgery setting. We concurrently recorded BIS and entropy (SE/RE) in 48 children aged 1 month-12 years, undergoing general anesthesia with sevoflurane and fentanyl. Nonlinear mixed effects modeling was used to characterize the concentration-response relationship independently between the three monitor indicators with sevoflurane. The model's goodness-of-fit was assessed by prediction-corrected visual predictive checks. Model fit with age was evaluated using absolute conditional individual weighted residuals (|CIWRES|). The ability of BIS and entropy monitors to describe the effect of anesthesia was compared with prediction probabilities (P K ) in different age groups. Intraoperative and awakening values were compared in the age groups. The correlation between BIS and entropy was also calculated. |CIWRES| vs age showed an increasing trend in the model's accuracy for all three indicators. P K probabilities were similar for all three indicators within each age group, though lower in infants. The linear correlations between BIS and entropy in different age groups were lower for infants. Infants also tended to have lower values during surgery and at awakening than older children, while toddlers had higher values. Performance of both monitors improves as age increases. Our results suggest a need for the development of new monitor algorithms or calibration to better account for the age-specific EEG dynamics of younger patients. © 2017 John Wiley & Sons Ltd.

SU-E-I-91: Quantitative Assessment of Early Hepatocellular Carcinoma and Cavernous Hemangioma of Live Using In-Line Phase-Contrast X-Ray Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duan, J

Purpose: To investigate the potential utility of in-line phase-contrast imaging (ILPCI) technique with synchrotron radiation in detecting early hepatocellular carcinoma and cavernous hemangioma of live using in vitro model system. Methods: Without contrast agents, three typical early hepatocellular carcinoma specimens and three typical cavernous hemangioma of live specimens were imaged using ILPCI. To quantitatively discriminate early hepatocellular carcinoma tissues and cavernous hemangioma tissues, the projection images texture feature based on gray level co-occurrence matrix (GLCM) were extracted. The texture parameters of energy, inertia, entropy, correlation, sum average, sum entropy, difference average, difference entropy and inverse difference moment, were obtained respectively.more » Results: In the ILPCI planar images of early hepatocellular carcinoma specimens, vessel trees were clearly visualized on the micrometer scale. Obvious distortion deformation was presented, and the vessel mostly appeared as a ‘dry stick’. Liver textures appeared not regularly. In the ILPCI planar images of cavernous hemangioma of live specimens, typical vessels had not been found compared with the early hepatocellular carcinoma planar images. The planar images of cavernous hemangioma of live specimens clearly displayed the dilated hepatic sinusoids with the diameter of less than 100 microns, but all of them were overlapped with each other. The texture parameters of energy, inertia, entropy, correlation, sum average, sum entropy, and difference average, showed a statistically significant between the two types specimens image (P<0.01), except the texture parameters of difference entropy and inverse difference moment(P>0.01). Conclusion: The results indicate that there are obvious changes in morphological levels including vessel structures and liver textures. The study proves that this imaging technique has a potential value in evaluating early hepatocellular carcinoma and cavernous hemangioma of live.« less

Entanglement entropy production in gravitational collapse: covariant regularization and solvable models

NASA Astrophysics Data System (ADS)

Bianchi, Eugenio; De Lorenzo, Tommaso; Smerlak, Matteo

2015-06-01

We study the dynamics of vacuum entanglement in the process of gravitational collapse and subsequent black hole evaporation. In the first part of the paper, we introduce a covariant regularization of entanglement entropy tailored to curved spacetimes; this regularization allows us to propose precise definitions for the concepts of black hole "exterior entropy" and "radiation entropy." For a Vaidya model of collapse we find results consistent with the standard thermodynamic properties of Hawking radiation. In the second part of the paper, we compute the vacuum entanglement entropy of various spherically-symmetric spacetimes of interest, including the nonsingular black hole model of Bardeen, Hayward, Frolov and Rovelli-Vidotto and the "black hole fireworks" model of Haggard-Rovelli. We discuss specifically the role of event and trapping horizons in connection with the behavior of the radiation entropy at future null infinity. We observe in particular that ( i) in the presence of an event horizon the radiation entropy diverges at the end of the evaporation process, ( ii) in models of nonsingular evaporation (with a trapped region but no event horizon) the generalized second law holds only at early times and is violated in the "purifying" phase, ( iii) at late times the radiation entropy can become negative (i.e. the radiation can be less correlated than the vacuum) before going back to zero leading to an up-down-up behavior for the Page curve of a unitarily evaporating black hole.

Modeling of groundwater productivity in northeastern Wasit Governorate, Iraq using frequency ratio and Shannon's entropy models

NASA Astrophysics Data System (ADS)

Al-Abadi, Alaa M.

2017-05-01

In recent years, delineation of groundwater productivity zones plays an increasingly important role in sustainable management of groundwater resource throughout the world. In this study, groundwater productivity index of northeastern Wasit Governorate was delineated using probabilistic frequency ratio (FR) and Shannon's entropy models in framework of GIS. Eight factors believed to influence the groundwater occurrence in the study area were selected and used as the input data. These factors were elevation (m), slope angle (degree), geology, soil, aquifer transmissivity (m2/d), storativity (dimensionless), distance to river (m), and distance to faults (m). In the first step, borehole location inventory map consisting of 68 boreholes with relatively high yield (>8 l/sec) was prepared. 47 boreholes (70 %) were used as training data and the remaining 21 (30 %) were used for validation. The predictive capability of each model was determined using relative operating characteristic technique. The results of the analysis indicate that the FR model with a success rate of 87.4 % and prediction rate 86.9 % performed slightly better than Shannon's entropy model with success rate of 84.4 % and prediction rate of 82.4 %. The resultant groundwater productivity index was classified into five classes using natural break classification scheme: very low, low, moderate, high, and very high. The high-very high classes for FR and Shannon's entropy models occurred within 30 % (217 km2) and 31 % (220 km2), respectively indicating low productivity conditions of the aquifer system. From final results, both of the models were capable to prospect GWPI with very good results, but FR was better in terms of success and prediction rates. Results of this study could be helpful for better management of groundwater resources in the study area and give planners and decision makers an opportunity to prepare appropriate groundwater investment plans.

Minimum and Maximum Entropy Distributions for Binary Systems with Known Means and Pairwise Correlations

DTIC Science & Technology

2017-08-21

distributions, and we discuss some applications for engineered and biological information transmission systems. Keywords: information theory; minimum...of its interpretation as a measure of the amount of information communicable by a neural system to groups of downstream neurons. Previous authors...of the maximum entropy approach. Our results also have relevance for engineered information transmission systems. We show that empirically measured

Evaluation of spectral entropy to measure anaesthetic depth and antinociception in sevoflurane-anaesthetised Beagle dogs.

PubMed

Morgaz, Juan; Granados, María del Mar; Domínguez, Juan Manuel; Navarrete, Rocío; Fernández, Andrés; Galán, Alba; Muñoz, Pilar; Gómez-Villamandos, Rafael J

2011-06-01

The use of spectral entropy to determine anaesthetic depth and antinociception was evaluated in sevoflurane-anaesthetised Beagle dogs. Dogs were anaesthetised at each of five multiples of their individual minimum alveolar concentrations (MAC; 0.75, 1, 1.25, 1.5 and 1.75 MAC), and response entropy (RE), state entropy (SE), RE-SE difference, burst suppression rate (BSR) and cardiorespiratory parameters were recorded before and after a painful stimulus. RE, SE and RE-SE difference did not change significantly after the stimuli. The correlation between MAC-entropy parameters was weak, but these values increased when 1.75 MAC results were excluded from the analysis. BSR was different to zero at 1.5 and 1.75 MAC. It was concluded that RE and RE-SE differences were not adequate indicators of antinociception and SE and RE were unable to detect deep planes of anaesthesia in dogs, although they both distinguished the awake and unconscious states. Copyright © 2010 Elsevier Ltd. All rights reserved.

Computing the Entropy of Kerr-Newman Black Hole Without Brick Walls Method

NASA Astrophysics Data System (ADS)

Zhang, Li-Chun; Wu, Yue-Qin; Li, Huai-Fan; Ren, Zhao

By using the entanglement entropy method, the statistical entropy of the Bose and Fermi fields in a thin film is calculated and the Bekenstein-Hawking entropy of Kerr-Newman black hole is obtained. Here, the Bose and Fermi fields are entangled with the quantum states in Kerr-Newman black hole and are outside of the horizon. The divergence of brick-wall model is avoided without any cutoff by the new equation of state density obtained with the generalized uncertainty principle. The calculation implies that the high density quantum states near the event horizon are strongly correlated with the quantum states in black hole. The black hole entropy is a quantum effect. It is an intrinsic characteristic of space-time. The ultraviolet cutoff in the brick-wall model is unreasonable. The generalized uncertainty principle should be considered in the high energy quantum field near the event horizon. From the calculation, the constant λ introduced in the generalized uncertainty principle is related to polar angle θ in an axisymmetric space-time.

Free energy and entropy of a dipolar liquid by computer simulations

NASA Astrophysics Data System (ADS)

Palomar, Ricardo; Sesé, Gemma

2018-02-01

Thermodynamic properties for a system composed of dipolar molecules are computed. Free energy is evaluated by means of the thermodynamic integration technique, and it is also estimated by using a perturbation theory approach, in which every molecule is modeled as a hard sphere within a square well, with an electric dipole at its center. The hard sphere diameter, the range and depth of the well, and the dipole moment have been calculated from properties easily obtained in molecular dynamics simulations. Connection between entropy and dynamical properties is explored in the liquid and supercooled states by using instantaneous normal mode calculations. A model is proposed in order to analyze translation and rotation contributions to entropy separately. Both contributions decrease upon cooling, and a logarithmic correlation between excess entropy associated with translation and the corresponding proportion of imaginary frequency modes is encountered. Rosenfeld scaling law between reduced diffusion and excess entropy is tested, and the origin of its failure at low temperatures is investigated.

Multiscale permutation entropy analysis of EEG recordings during sevoflurane anesthesia

NASA Astrophysics Data System (ADS)

Li, Duan; Li, Xiaoli; Liang, Zhenhu; Voss, Logan J.; Sleigh, Jamie W.

2010-08-01

Electroencephalogram (EEG) monitoring of the effect of anesthetic drugs on the central nervous system has long been used in anesthesia research. Several methods based on nonlinear dynamics, such as permutation entropy (PE), have been proposed to analyze EEG series during anesthesia. However, these measures are still single-scale based and may not completely describe the dynamical characteristics of complex EEG series. In this paper, a novel measure combining multiscale PE information, called CMSPE (composite multi-scale permutation entropy), was proposed for quantifying the anesthetic drug effect on EEG recordings during sevoflurane anesthesia. Three sets of simulated EEG series during awake, light and deep anesthesia were used to select the parameters for the multiscale PE analysis: embedding dimension m, lag τ and scales to be integrated into the CMSPE index. Then, the CMSPE index and raw single-scale PE index were applied to EEG recordings from 18 patients who received sevoflurane anesthesia. Pharmacokinetic/pharmacodynamic (PKPD) modeling was used to relate the measured EEG indices and the anesthetic drug concentration. Prediction probability (Pk) statistics and correlation analysis with the response entropy (RE) index, derived from the spectral entropy (M-entropy module; GE Healthcare, Helsinki, Finland), were investigated to evaluate the effectiveness of the new proposed measure. It was found that raw single-scale PE was blind to subtle transitions between light and deep anesthesia, while the CMSPE index tracked these changes accurately. Around the time of loss of consciousness, CMSPE responded significantly more rapidly than the raw PE, with the absolute slopes of linearly fitted response versus time plots of 0.12 (0.09-0.15) and 0.10 (0.06-0.13), respectively. The prediction probability Pk of 0.86 (0.85-0.88) and 0.85 (0.80-0.86) for CMSPE and raw PE indicated that the CMSPE index correlated well with the underlying anesthetic effect. The correlation coefficient for the comparison between the CMSPE index and RE index of 0.84 (0.80-0.88) was significantly higher than the raw PE index of 0.75 (0.66-0.84). The results show that the CMSPE outperforms the raw single-scale PE in reflecting the sevoflurane drug effect on the central nervous system.

Reconstructing quantum entropy production to probe irreversibility and correlations

NASA Astrophysics Data System (ADS)

Gherardini, Stefano; Müller, Matthias M.; Trombettoni, Andrea; Ruffo, Stefano; Caruso, Filippo

2018-07-01

One of the major goals of quantum thermodynamics is the characterization of irreversibility and its consequences in quantum processes. Here, we discuss how entropy production provides a quantification of the irreversibility in open quantum systems through the quantum fluctuation theorem. We start by introducing a two-time quantum measurement scheme, in which the dynamical evolution between the measurements is described by a completely positive, trace-preserving (CPTP) quantum map (forward process). By inverting the measurement scheme and applying the time-reversed version of the quantum map, we can study how this backward process differs from the forward one. When the CPTP map is unital, we show that the stochastic quantum entropy production is a function only of the probabilities to get the initial measurement outcomes in correspondence of the forward and backward processes. For bipartite open quantum systems we also prove that the mean value of the stochastic quantum entropy production is sub-additive with respect to the bipartition (except for product states). Hence, we find a method to detect correlations between the subsystems. Our main result is the proposal of an efficient protocol to determine and reconstruct the characteristic functions of the stochastic entropy production for each subsystem. This procedure enables to reconstruct even others thermodynamical quantities, such as the work distribution of the composite system and the corresponding internal energy. Efficiency and possible extensions of the protocol are also discussed. Finally, we show how our findings might be experimentally tested by exploiting the state of-the-art trapped-ion platforms.

[Quantitative assessment of urban ecosystem services flow based on entropy theory: A case study of Beijing, China].

PubMed

Li, Jing Xin; Yang, Li; Yang, Lei; Zhang, Chao; Huo, Zhao Min; Chen, Min Hao; Luan, Xiao Feng

2018-03-01

Quantitative evaluation of ecosystem service is a primary premise for rational resources exploitation and sustainable development. Examining ecosystem services flow provides a scientific method to quantity ecosystem services. We built an assessment indicator system based on land cover/land use under the framework of four types of ecosystem services. The types of ecosystem services flow were reclassified. Using entropy theory, disorder degree and developing trend of indicators and urban ecosystem were quantitatively assessed. Beijing was chosen as the study area, and twenty-four indicators were selected for evaluation. The results showed that the entropy value of Beijing urban ecosystem during 2004 to 2015 was 0.794 and the entropy flow was -0.024, suggesting a large disordered degree and near verge of non-health. The system got maximum values for three times, while the mean annual variation of the system entropy value increased gradually in three periods, indicating that human activities had negative effects on urban ecosystem. Entropy flow reached minimum value in 2007, implying the environmental quality was the best in 2007. The determination coefficient for the fitting function of total permanent population in Beijing and urban ecosystem entropy flow was 0.921, indicating that urban ecosystem health was highly correlated with total permanent population.

A proposed methodology for studying the historical trajectory of words' meaning through Tsallis entropy

NASA Astrophysics Data System (ADS)

Neuman, Yair; Cohen, Yochai; Israeli, Navot; Tamir, Boaz

2018-02-01

The availability of historical textual corpora has led to the study of words' frequency along the historical time line, as representing the public's focus of attention over time. However, studying of the dynamics of words' meaning is still in its infancy. In this paper, we propose a methodology for studying the historical trajectory of words' meaning through Tsallis entropy. First, we present the idea that the meaning of a word may be studied through the entropy of its embedding. Using two historical case studies, we show that this entropy measure is correlated with the intensity in which a word is used. More importantly, we show that using Tsallis entropy with a superadditive entropy index may provide a better estimation of a word's frequency of use than using Shannon entropy. We explain this finding as resulting from an increasing redundancy between the words that comprise the semantic field of the target word and develop a new measure of redundancy between words. Using this measure, which relies on the Tsallis version of the Kullback-Leibler divergence, we show that the evolving meaning of a word involves the dynamics of increasing redundancy between components of its semantic field. The proposed methodology may enrich the toolkit of researchers who study the dynamics of word senses.

Bayesian framework inspired no-reference region-of-interest quality measure for brain MRI images

PubMed Central

Osadebey, Michael; Pedersen, Marius; Arnold, Douglas; Wendel-Mitoraj, Katrina

2017-01-01

Abstract. We describe a postacquisition, attribute-based quality assessment method for brain magnetic resonance imaging (MRI) images. It is based on the application of Bayes theory to the relationship between entropy and image quality attributes. The entropy feature image of a slice is segmented into low- and high-entropy regions. For each entropy region, there are three separate observations of contrast, standard deviation, and sharpness quality attributes. A quality index for a quality attribute is the posterior probability of an entropy region given any corresponding region in a feature image where quality attribute is observed. Prior belief in each entropy region is determined from normalized total clique potential (TCP) energy of the slice. For TCP below the predefined threshold, the prior probability for a region is determined by deviation of its percentage composition in the slice from a standard normal distribution built from 250 MRI volume data provided by Alzheimer’s Disease Neuroimaging Initiative. For TCP above the threshold, the prior is computed using a mathematical model that describes the TCP–noise level relationship in brain MRI images. Our proposed method assesses the image quality of each entropy region and the global image. Experimental results demonstrate good correlation with subjective opinions of radiologists for different types and levels of quality distortions. PMID:28630885

Optimization of a Circular Microchannel With Entropy Generation Minimization Method

NASA Astrophysics Data System (ADS)

Jafari, Arash; Ghazali, Normah Mohd

2010-06-01

New advances in micro and nano scales are being realized and the contributions of micro and nano heat dissipation devices are of high importance in this novel technology development. Past studies showed that microchannel design depends on its thermal resistance and pressure drop. However, entropy generation minimization (EGM) as a new optimization theory stated that the rate of entropy generation should be also optimized. Application of EGM in microchannel heat sink design is reviewed and discussed in this paper. Latest principles for deriving the entropy generation relations are discussed to present how this approach can be achieved. An optimization procedure using EGM method with the entropy generation rate is derived for a circular microchannel heat sink based upon thermal resistance and pressure drop. The equations are solved using MATLAB and the obtained results are compared to similar past studies. The effects of channel diameter, number of channels, heat flux, and pumping power on the entropy generation rate and Reynolds number are investigated. Analytical correlations are utilized for heat transfer and friction coefficients. A minimum entropy generation has been observed for N = 40 and channel diameter of 90μm. It is concluded that for N = 40 and channel hydraulic diameter of 90μm, the circular microchannel heat sink is on its optimum operating point based on second law of thermodynamics.

The Correlation Entropy as a Measure of the Complexity of High-Lying Single-Particle Modes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stoyanov, Chavdar; Zelevinsky, Vladimir; Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824-1321

Highly-excited single-particle states in nuclei are coupled with the excitations of a more complex character, first of all with collective phonon-like modes of the core. In the framework of the quasiparticle-phonon model we consider the structure of resulting complex configurations using the 1k17/2 orbital in 209Pb as an example. The eigenstates of the model carry significant degree of complexity that can be quantified with the aid of correlational invariant entropy. With artificially enhanced particle-core coupling, the system undergoes the doubling phase transition with the quasiparticle strength concentrated in two repelling peaks.

Spatial correlation in matter-wave interference as a measure of decoherence, dephasing, and entropy

NASA Astrophysics Data System (ADS)

Chen, Zilin; Beierle, Peter; Batelaan, Herman

2018-04-01

The loss of contrast in double-slit electron diffraction due to dephasing and decoherence processes is studied. It is shown that the spatial intensity correlation function of diffraction patterns can be used to distinguish between dephasing and decoherence. This establishes a measure of time reversibility that does not require the determination of coherence terms of the density matrix, while von Neumann entropy, another measure of time reversibility, does require coherence terms. This technique is exciting in view of the need to understand and control the detrimental experimental effect of contrast loss and for fundamental studies on the transition from the classical to the quantum regime.

Thermodynamics of Ising spins on the triangular kagome lattice: Exact analytical method and Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Loh, Y. L.; Yao, D. X.; Carlson, E. W.

2008-04-01

A new class of two-dimensional magnetic materials Cu9X2(cpa)6ṡxH2O ( cpa=2 -carboxypentonic acid; X=F,Cl,Br ) was recently fabricated in which Cu sites form a triangular kagome lattice (TKL). As the simplest model of geometric frustration in such a system, we study the thermodynamics of Ising spins on the TKL using exact analytic method as well as Monte Carlo simulations. We present the free energy, internal energy, specific heat, entropy, sublattice magnetizations, and susceptibility. We describe the rich phase diagram of the model as a function of coupling constants, temperature, and applied magnetic field. For frustrated interactions in the absence of applied field, the ground state is a spin liquid phase with residual entropy per spin s0/kB=(1)/(9)ln72≈0.4752… . In weak applied field, the system maps to the dimer model on a honeycomb lattice, with residual entropy 0.0359 per spin and quasi-long-range order with power-law spin-spin correlations that should be detectable by neutron scattering. The power-law correlations become exponential at finite temperatures, but the correlation length may still be long.

Entropic benefit of a cross-link in protein association.

PubMed

Zaman, Muhammad H; Berry, R Stephen; Sosnick, Tobin R

2002-08-01

We introduce a method to estimate the loss of configurational entropy upon insertion of a cross-link to a dimeric system. First, a clear distinction is established between the loss of entropy upon tethering and binding, two quantities that are often considered to be equivalent. By comparing the probability distribution of the center-to-center distances for untethered and cross-linked versions, we are able to calculate the loss of translational entropy upon cross-linking. The distribution function for the untethered helices is calculated from the probability that a given helix is closer to its partner than to all other helices, the "Nearest Neighbor" method. This method requires no assumptions about the nature of the solvent, and hence resolves difficulties normally associated with calculations for systems in liquids. Analysis of the restriction of angular freedom upon tethering indicates that the loss of rotational entropy is negligible. The method is applied in the context of the folding of a ten turn helical coiled coil with the tether modeled as a Gaussian chain or a flexible amino acid chain. After correcting for loop closure entropy in the docked state, we estimate the introduction of a six-residue tether in the coiled coil results in an effective concentration of the chain to be about 4 or 100 mM, depending upon whether the helices are denatured or pre-folded prior to their association. Thus, tethering results in significant stabilization for systems with millimolar or stronger dissociation constants. Copyright 2002 Wiley-Liss, Inc.

Differential network entropy reveals cancer system hallmarks

PubMed Central

West, James; Bianconi, Ginestra; Severini, Simone; Teschendorff, Andrew E.

2012-01-01

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network we here demonstrate that cancer cells are characterised by an increase in network entropy. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local network entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local correlation patterns. In particular, we find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in network entropy. These findings may have potential implications for identifying novel drug targets. PMID:23150773

On the composition dependence of faceting behaviour of primary phases during solidification

NASA Astrophysics Data System (ADS)

Saroch, Mamta; Dubey, K. S.; Ramachandrarao, P.

1993-02-01

The entropy of solution of the primary aluminium-rich phase in the aluminium-tin melts has been evaluated as a function of temperature using available thermodynamic and phase equilibria data with a view to understand the faceting behaviour of this phase. It was noticed that the range of compositions in which alloys of aluminium and tin yield a faceted primary phase is correlated with the domain of compositions over which the entropy of solution shows a strong temperature dependence. It is demonstrated that both a high value of the entropy of solution and a strong temperature dependence of it are essential for providing faceting. A strong temperature dependence of the entropy of solution is in turn a consequence of negligible liquidus slope and existence of retrograde solubility. The AgBi and AgPb systems have similar features.

Quantitative morphometric analysis of hepatocellular carcinoma: development of a programmed algorithm and preliminary application.

PubMed

Yap, Felix Y; Bui, James T; Knuttinen, M Grace; Walzer, Natasha M; Cotler, Scott J; Owens, Charles A; Berkes, Jamie L; Gaba, Ron C

2013-01-01

The quantitative relationship between tumor morphology and malignant potential has not been explored in liver tumors. We designed a computer algorithm to analyze shape features of hepatocellular carcinoma (HCC) and tested feasibility of morphologic analysis. Cross-sectional images from 118 patients diagnosed with HCC between 2007 and 2010 were extracted at the widest index tumor diameter. The tumor margins were outlined, and point coordinates were input into a MATLAB (MathWorks Inc., Natick, Massachusetts, USA) algorithm. Twelve shape descriptors were calculated per tumor: the compactness, the mean radial distance (MRD), the RD standard deviation (RDSD), the RD area ratio (RDAR), the zero crossings, entropy, the mean Feret diameter (MFD), the Feret ratio, the convex hull area (CHA) and perimeter (CHP) ratios, the elliptic compactness (EC), and the elliptic irregularity (EI). The parameters were correlated with the levels of alpha-fetoprotein (AFP) as an indicator of tumor aggressiveness. The quantitative morphometric analysis was technically successful in all cases. The mean parameters were as follows: compactness 0.88±0.086, MRD 0.83±0.056, RDSD 0.087±0.037, RDAR 0.045±0.023, zero crossings 6±2.2, entropy 1.43±0.16, MFD 4.40±3.14 cm, Feret ratio 0.78±0.089, CHA 0.98±0.027, CHP 0.98±0.030, EC 0.95±0.043, and EI 0.95±0.023. MFD and RDAR provided the widest value range for the best shape discrimination. The larger tumors were less compact, more concave, and less ellipsoid than the smaller tumors (P < 0.0001). AFP-producing tumors displayed greater morphologic irregularity based on several parameters, including compactness, MRD, RDSD, RDAR, entropy, and EI (P < 0.05 for all). Computerized HCC image analysis using shape descriptors is technically feasible. Aggressively growing tumors have wider diameters and more irregular margins. Future studies will determine further clinical applications for this morphologic analysis.

Constraints on rapidity-dependent initial conditions from charged-particle pseudorapidity densities and two-particle correlations

NASA Astrophysics Data System (ADS)

Ke, Weiyao; Moreland, J. Scott; Bernhard, Jonah E.; Bass, Steffen A.

2017-10-01

We study the initial three-dimensional spatial configuration of the quark-gluon plasma (QGP) produced in relativistic heavy-ion collisions using centrality and pseudorapidity-dependent measurements of the medium's charged particle density and two-particle correlations. A cumulant-generating function is first used to parametrize the rapidity dependence of local entropy deposition and extend arbitrary boost-invariant initial conditions to nonzero beam rapidities. The model is then compared to p +Pb and Pb + Pb charged-particle pseudorapidity densities and two-particle pseudorapidity correlations and systematically optimized using Bayesian parameter estimation to extract high-probability initial condition parameters. The optimized initial conditions are then compared to a number of experimental observables including the pseudorapidity-dependent anisotropic flows, event-plane decorrelations, and flow correlations. We find that the form of the initial local longitudinal entropy profile is well constrained by these experimental measurements.

High-entropy fireballs and jets in gamma-ray burst sources

NASA Technical Reports Server (NTRS)

Meszaros, P.; Rees, M. J.

1992-01-01

Two mechanisms whereby compact coalescing binaries can produce relatively 'clean' fireballs via neutrino-antineutrino annihilation are proposed. Preejected mass due to tidal heating will collimate the fireball into jets. The resulting anisotropic gamma-ray emission can be efficient and intense enough to provide an acceptable model for gamma-ray bursts, if these originate at cosmological distances.

Adaptive Statistical Language Modeling; A Maximum Entropy Approach

DTIC Science & Technology

1994-04-19

models exploit the immediate past only. To extract information from further back in the document’s history , I use trigger pairs as the basic information...9 2.2 Context-Free Estimation (Unigram) ...... .................... 12 2.3 Short-Term History (Conventional N-gram...12 2.4 Short-term Class History (Class-Based N-gram) ................... 14 2.5 Intermediate Distance ........ ........................... 16

Quantitative study of fluctuation effects by fast lattice Monte Carlo simulations: Compression of grafted homopolymers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Pengfei; Wang, Qiang, E-mail: q.wang@colostate.edu

2014-01-28

Using fast lattice Monte Carlo (FLMC) simulations [Q. Wang, Soft Matter 5, 4564 (2009)] and the corresponding lattice self-consistent field (LSCF) calculations, we studied a model system of grafted homopolymers, in both the brush and mushroom regimes, in an explicit solvent compressed by an impenetrable surface. Direct comparisons between FLMC and LSCF results, both of which are based on the same Hamiltonian (thus without any parameter-fitting between them), unambiguously and quantitatively reveal the fluctuations/correlations neglected by the latter. We studied both the structure (including the canonical-ensemble averages of the height and the mean-square end-to-end distances of grafted polymers) and thermodynamicsmore » (including the ensemble-averaged reduced energy density and the related internal energy per chain, the differences in the Helmholtz free energy and entropy per chain from the uncompressed state, and the pressure due to compression) of the system. In particular, we generalized the method for calculating pressure in lattice Monte Carlo simulations proposed by Dickman [J. Chem. Phys. 87, 2246 (1987)], and combined it with the Wang-Landau–Optimized Ensemble sampling [S. Trebst, D. A. Huse, and M. Troyer, Phys. Rev. E 70, 046701 (2004)] to efficiently and accurately calculate the free energy difference and the pressure due to compression. While we mainly examined the effects of the degree of compression, the distance between the nearest-neighbor grafting points, the reduced number of chains grafted at each grafting point, and the system fluctuations/correlations in an athermal solvent, the θ-solvent is also considered in some cases.« less

Dynamic Approximate Entropy Electroanatomic Maps Detect Rotors in a Simulated Atrial Fibrillation Model

PubMed Central

Ugarte, Juan P.; Orozco-Duque, Andrés; Tobón, Catalina; Kremen, Vaclav; Novak, Daniel; Saiz, Javier; Oesterlein, Tobias; Schmitt, Clauss; Luik, Armin; Bustamante, John

2014-01-01

There is evidence that rotors could be drivers that maintain atrial fibrillation. Complex fractionated atrial electrograms have been located in rotor tip areas. However, the concept of electrogram fractionation, defined using time intervals, is still controversial as a tool for locating target sites for ablation. We hypothesize that the fractionation phenomenon is better described using non-linear dynamic measures, such as approximate entropy, and that this tool could be used for locating the rotor tip. The aim of this work has been to determine the relationship between approximate entropy and fractionated electrograms, and to develop a new tool for rotor mapping based on fractionation levels. Two episodes of chronic atrial fibrillation were simulated in a 3D human atrial model, in which rotors were observed. Dynamic approximate entropy maps were calculated using unipolar electrogram signals generated over the whole surface of the 3D atrial model. In addition, we optimized the approximate entropy calculation using two real multi-center databases of fractionated electrogram signals, labeled in 4 levels of fractionation. We found that the values of approximate entropy and the levels of fractionation are positively correlated. This allows the dynamic approximate entropy maps to localize the tips from stable and meandering rotors. Furthermore, we assessed the optimized approximate entropy using bipolar electrograms generated over a vicinity enclosing a rotor, achieving rotor detection. Our results suggest that high approximate entropy values are able to detect a high level of fractionation and to locate rotor tips in simulated atrial fibrillation episodes. We suggest that dynamic approximate entropy maps could become a tool for atrial fibrillation rotor mapping. PMID:25489858

Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task

PubMed Central

Tian, Yin; Zhang, Huiling; Xu, Wei; Zhang, Haiyong; Yang, Li; Zheng, Shuxing; Shi, Yupan

2017-01-01

Spectral entropy, which was generated by applying the Shannon entropy concept to the power distribution of the Fourier-transformed electroencephalograph (EEG), was utilized to measure the uniformity of power spectral density underlying EEG when subjects performed the working memory tasks twice, i.e., before and after training. According to Signed Residual Time (SRT) scores based on response speed and accuracy trade-off, 20 subjects were divided into two groups, namely high-performance and low-performance groups, to undertake working memory (WM) tasks. We found that spectral entropy derived from the retention period of WM on channel FC4 exhibited a high correlation with SRT scores. To this end, spectral entropy was used in support vector machine classifier with linear kernel to differentiate these two groups. Receiver operating characteristics analysis and leave-one out cross-validation (LOOCV) demonstrated that the averaged classification accuracy (CA) was 90.0 and 92.5% for intra-session and inter-session, respectively, indicating that spectral entropy could be used to distinguish these two different WM performance groups successfully. Furthermore, the support vector regression prediction model with radial basis function kernel and the root-mean-square error of prediction revealed that spectral entropy could be utilized to predict SRT scores on individual WM performance. After testing the changes in SRT scores and spectral entropy for each subject by short-time training, we found that 16 in 20 subjects’ SRT scores were clearly promoted after training and 15 in 20 subjects’ SRT scores showed consistent changes with spectral entropy before and after training. The findings revealed that spectral entropy could be a promising indicator to predict individual’s WM changes by training and further provide a novel application about WM for brain–computer interfaces. PMID:28912701

Spectral simplicity of apparent complexity. II. Exact complexities and complexity spectra

NASA Astrophysics Data System (ADS)

Riechers, Paul M.; Crutchfield, James P.

2018-03-01

The meromorphic functional calculus developed in Part I overcomes the nondiagonalizability of linear operators that arises often in the temporal evolution of complex systems and is generic to the metadynamics of predicting their behavior. Using the resulting spectral decomposition, we derive closed-form expressions for correlation functions, finite-length Shannon entropy-rate approximates, asymptotic entropy rate, excess entropy, transient information, transient and asymptotic state uncertainties, and synchronization information of stochastic processes generated by finite-state hidden Markov models. This introduces analytical tractability to investigating information processing in discrete-event stochastic processes, symbolic dynamics, and chaotic dynamical systems. Comparisons reveal mathematical similarities between complexity measures originally thought to capture distinct informational and computational properties. We also introduce a new kind of spectral analysis via coronal spectrograms and the frequency-dependent spectra of past-future mutual information. We analyze a number of examples to illustrate the methods, emphasizing processes with multivariate dependencies beyond pairwise correlation. This includes spectral decomposition calculations for one representative example in full detail.

Fractal-Based Analysis of the Influence of Music on Human Respiration

NASA Astrophysics Data System (ADS)

Reza Namazi, H.

An important challenge in respiration related studies is to investigate the influence of external stimuli on human respiration. Auditory stimulus is an important type of stimuli that influences human respiration. However, no one discovered any trend, which relates the characteristics of the auditory stimuli to the characteristics of the respiratory signal. In this paper, we investigate the correlation between auditory stimuli and respiratory signal from fractal point of view. We found out that the fractal structure of respiratory signal is correlated with the fractal structure of the applied music. Based on the obtained results, the music with greater fractal dimension will result in respiratory signal with smaller fractal dimension. In order to verify this result, we benefit from approximate entropy. The results show the respiratory signal will have smaller approximate entropy by choosing the music with smaller approximate entropy. The method of analysis could be further investigated to analyze the variations of different physiological time series due to the various types of stimuli when the complexity is the main concern.

A Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression

PubMed Central

Nguyen, Nha; Vo, An; Choi, Inchan

2015-01-01

Abstract Studying epigenetic landscapes is important to understand the condition for gene regulation. Clustering is a useful approach to study epigenetic landscapes by grouping genes based on their epigenetic conditions. However, classical clustering approaches that often use a representative value of the signals in a fixed-sized window do not fully use the information written in the epigenetic landscapes. Clustering approaches to maximize the information of the epigenetic signals are necessary for better understanding gene regulatory environments. For effective clustering of multidimensional epigenetic signals, we developed a method called Dewer, which uses the entropy of stationary wavelet of epigenetic signals inside enriched regions for gene clustering. Interestingly, the gene expression levels were highly correlated with the entropy levels of epigenetic signals. Dewer separates genes better than a window-based approach in the assessment using gene expression and achieved a correlation coefficient above 0.9 without using any training procedure. Our results show that the changes of the epigenetic signals are useful to study gene regulation. PMID:25383910

Entanglement versus Stosszahlansatz: disappearance of the thermodynamic arrow in a high-correlation environment.

PubMed

Partovi, M Hossein

2008-02-01

The crucial role of ambient correlations in determining thermodynamic behavior is established. A class of entangled states of two macroscopic systems is constructed such that each component is in a state of thermal equilibrium at a given temperature, and when the two are allowed to interact heat can flow from the colder to the hotter system. A dilute gas model exhibiting this behavior is presented. This reversal of the thermodynamic arrow is a consequence of the entanglement between the two systems, a condition that is opposite to molecular chaos and shown to be unlikely in a low-entropy environment. By contrast, the second law is established by proving Clausius' inequality in a low-entropy environment. These general results strongly support the expectation, first expressed by Boltzmann and subsequently elaborated by others, that the second law is an emergent phenomenon which requires a low-entropy cosmological environment, one that can effectively function as an ideal information sink.

Entropy studies on beam distortion by atmospheric turbulence

NASA Astrophysics Data System (ADS)

Wu, Chensheng; Ko, Jonathan; Davis, Christopher C.

2015-09-01

When a beam propagates through atmospheric turbulence over a known distance, the target beam profile deviates from the projected profile of the beam on the receiver. Intuitively, the unwanted distortion provides information about the atmospheric turbulence. This information is crucial for guiding adaptive optic systems and improving beam propagation results. In this paper, we propose an entropy study based on the image from a plenoptic sensor to provide a measure of information content of atmospheric turbulence. In general, lower levels of atmospheric turbulence will have a smaller information size while higher levels of atmospheric turbulence will cause significant expansion of the information size, which may exceed the maximum capacity of a sensing system and jeopardize the reliability of an AO system. Therefore, the entropy function can be used to analyze the turbulence distortion and evaluate performance of AO systems. In fact, it serves as a metric that can tell the improvement of beam correction in each iteration step. In addition, it points out the limitation of an AO system at optimized correction as well as the minimum information needed for wavefront sensing to achieve certain levels of correction. In this paper, we will demonstrate the definition of the entropy function and how it is related to evaluating information (randomness) carried by atmospheric turbulence.

Cause-and-effect relationships in tandem swimmer models using transfer entropy

NASA Astrophysics Data System (ADS)

Peterson, Sean; Rosen, Maxwell; Gementzopoulos, Antonios; Zhang, Peng; Porfiri, Maurizio

2017-11-01

Swimming in a group affords a number of advantages to fish, including an enhanced ability to escape from predators, search for food, and mate. To study coordinated movements of fish, principled approaches are needed to unravel cause-and-effect relationships from raw-time series of multiple bodies moving in an encompassing fluid. In this work, we aim at demonstrating the validity of transfer entropy to elucidate cause-and-effect relationships in a fluid-structure interaction problem. Specifically, we consider two tandem airfoils in a uniform flow, wherein the pitching angle of one airfoil is actively controlled while the other is allowed to passively rotate. The active control alternates the pitch angle based upon an underlying two-state ergodic Markov process. We monitor the pitch angle of both the active and passive airfoils in time and demonstrate that transfer entropy can detect causality independent of which airfoil is actuated. The influence estimated by transfer entropy is found to be modulated by the distance between the two airfoils. The proposed data-driven technique offers a model-free perspective on fluid-structure interactions that can help illuminate the mechanisms of swimming in coordination. This work was supported by the National Science Foundation under Grant Numbers CBET-1332204 and CMMI-1433670.

Bayesian cross-entropy methodology for optimal design of validation experiments

NASA Astrophysics Data System (ADS)

Jiang, X.; Mahadevan, S.

2006-07-01

An important concern in the design of validation experiments is how to incorporate the mathematical model in the design in order to allow conclusive comparisons of model prediction with experimental output in model assessment. The classical experimental design methods are more suitable for phenomena discovery and may result in a subjective, expensive, time-consuming and ineffective design that may adversely impact these comparisons. In this paper, an integrated Bayesian cross-entropy methodology is proposed to perform the optimal design of validation experiments incorporating the computational model. The expected cross entropy, an information-theoretic distance between the distributions of model prediction and experimental observation, is defined as a utility function to measure the similarity of two distributions. A simulated annealing algorithm is used to find optimal values of input variables through minimizing or maximizing the expected cross entropy. The measured data after testing with the optimum input values are used to update the distribution of the experimental output using Bayes theorem. The procedure is repeated to adaptively design the required number of experiments for model assessment, each time ensuring that the experiment provides effective comparison for validation. The methodology is illustrated for the optimal design of validation experiments for a three-leg bolted joint structure and a composite helicopter rotor hub component.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Horodecki, Michal; Sen, Aditi; Sen, Ujjwal

The impossibility of cloning and deleting of unknown states constitute important restrictions on processing of information in the quantum world. On the other hand, a known quantum state can always be cloned or deleted. However, if we restrict the class of allowed operations, there will arise restrictions on the ability of cloning and deleting machines. We have shown that cloning and deleting of known states is in general not possible by local operations. This impossibility hints at quantum correlation in the state. We propose dual measures of quantum correlation based on the dual restrictions of no local cloning and nomore » local deleting. The measures are relative entropy distances of the desired states in a (generally impossible) perfect local cloning or local deleting process from the best approximate state that is actually obtained by imperfect local cloning or deleting machines. Just like the dual measures of entanglement cost and distillable entanglement, the proposed measures are based on important processes in quantum information. We discuss their properties. For the case of pure states, estimations of these two measures are also provided. Interestingly, the entanglement of cloning for a maximally entangled state of two two-level systems is not unity.« less

Multipartite entangled states in particle mixing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blasone, M.; INFN Sezione di Napoli, Gruppo collegato di Salerno, Baronissi; Dell'Anno, F.

2008-05-01

In the physics of flavor mixing, the flavor states are given by superpositions of mass eigenstates. By using the occupation number to define a multiqubit space, the flavor states can be interpreted as multipartite mode-entangled states. By exploiting a suitable global measure of entanglement, based on the entropies related to all possible bipartitions of the system, we analyze the correlation properties of such states in the instances of three- and four-flavor mixing. Depending on the mixing parameters, and, in particular, on the values taken by the free phases, responsible for the CP-violation, entanglement concentrates in certain bipartitions. We quantify inmore » detail the amount and the distribution of entanglement in the physically relevant cases of flavor mixing in quark and neutrino systems. By using the wave packet description for localized particles, we use the global measure of entanglement, suitably adapted for the instance of multipartite mixed states, to analyze the decoherence, induced by the free evolution dynamics, on the quantum correlations of stationary neutrino beams. We define a decoherence length as the distance associated with the vanishing of the coherent interference effects among massive neutrino states. We investigate the role of the CP-violating phase in the decoherence process.« less

Information-Theoretical Quantifier of Brain Rhythm Based on Data-Driven Multiscale Representation

PubMed Central

2015-01-01

This paper presents a data-driven multiscale entropy measure to reveal the scale dependent information quantity of electroencephalogram (EEG) recordings. This work is motivated by the previous observations on the nonlinear and nonstationary nature of EEG over multiple time scales. Here, a new framework of entropy measures considering changing dynamics over multiple oscillatory scales is presented. First, to deal with nonstationarity over multiple scales, EEG recording is decomposed by applying the empirical mode decomposition (EMD) which is known to be effective for extracting the constituent narrowband components without a predetermined basis. Following calculation of Renyi entropy of the probability distributions of the intrinsic mode functions extracted by EMD leads to a data-driven multiscale Renyi entropy. To validate the performance of the proposed entropy measure, actual EEG recordings from rats (n = 9) experiencing 7 min cardiac arrest followed by resuscitation were analyzed. Simulation and experimental results demonstrate that the use of the multiscale Renyi entropy leads to better discriminative capability of the injury levels and improved correlations with the neurological deficit evaluation after 72 hours after cardiac arrest, thus suggesting an effective diagnostic and prognostic tool. PMID:26380297

Loss of conformational entropy in protein folding calculated using realistic ensembles and its implications for NMR-based calculations

PubMed Central

Baxa, Michael C.; Haddadian, Esmael J.; Jumper, John M.; Freed, Karl F.; Sosnick, Tobin R.

2014-01-01

The loss of conformational entropy is a major contribution in the thermodynamics of protein folding. However, accurate determination of the quantity has proven challenging. We calculate this loss using molecular dynamic simulations of both the native protein and a realistic denatured state ensemble. For ubiquitin, the total change in entropy is TΔSTotal = 1.4 kcal⋅mol−1 per residue at 300 K with only 20% from the loss of side-chain entropy. Our analysis exhibits mixed agreement with prior studies because of the use of more accurate ensembles and contributions from correlated motions. Buried side chains lose only a factor of 1.4 in the number of conformations available per rotamer upon folding (ΩU/ΩN). The entropy loss for helical and sheet residues differs due to the smaller motions of helical residues (TΔShelix−sheet = 0.5 kcal⋅mol−1), a property not fully reflected in the amide N-H and carbonyl C=O bond NMR order parameters. The results have implications for the thermodynamics of folding and binding, including estimates of solvent ordering and microscopic entropies obtained from NMR. PMID:25313044

The progression of the entropy of a five dimensional psychotherapeutic system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Badalamenti, A.F.; Langs, R.J.

This paper presents a study of the deterministic and stochastic behavior of the entropy of a 5-dimensional, 2400 state, system across each of six psychotherapeutic sessions. The growth of entropy was found to be logarithmic in each session. The stochastic behavior of a moving 600 second estimator of entropy revealed a Box-Jenkins model of type (1,1,0) - that is, the first difference of the entropy series was first order autoregressive or prior state sensitive. In addition, the patient and therapist entropy series exhibited no significant cross correlation across lags of -300 to +300 seconds. Yet all such pairs of seriesmore » exhibited high coherency past the frequency of .06 (on a full range of 0 to .5). Furthermore, all the patients and therapists were attracted to a geometric center of mass in 5-dimensional space which was different from the geometric center of the region where the system lived. The process significance of the findings and the relationship between the deterministic and stochastic results are discussed. The paper is then placed in the broader context of our efforts to provide new and meaningful quantitative dimensions and mathematical models to psychotherapy research. 59 refs.« less

Neural Correlates of Wakefulness, Sleep, and General Anesthesia: An Experimental Study in Rat.

PubMed

Pal, Dinesh; Silverstein, Brian H; Lee, Heonsoo; Mashour, George A

2016-11-01

Significant advances have been made in our understanding of subcortical processes related to anesthetic- and sleep-induced unconsciousness, but the associated changes in cortical connectivity and cortical neurochemistry have yet to be fully clarified. Male Sprague-Dawley rats were instrumented for simultaneous measurement of cortical acetylcholine and electroencephalographic indices of corticocortical connectivity-coherence and symbolic transfer entropy-before, during, and after general anesthesia (propofol, n = 11; sevoflurane, n = 13). In another group of rats (n = 7), these electroencephalographic indices were analyzed during wakefulness, slow wave sleep (SWS), and rapid eye movement (REM) sleep. Compared to wakefulness, anesthetic-induced unconsciousness was characterized by a significant decrease in cortical acetylcholine that recovered to preanesthesia levels during recovery wakefulness. Corticocortical coherence and frontal-parietal symbolic transfer entropy in high γ band (85 to 155 Hz) were decreased during anesthetic-induced unconsciousness and returned to preanesthesia levels during recovery wakefulness. Sleep-wake states showed a state-dependent change in coherence and transfer entropy in high γ bandwidth, which correlated with behavioral arousal: high during wakefulness, low during SWS, and lowest during REM sleep. By contrast, frontal-parietal θ connectivity during sleep-wake states was not correlated with behavioral arousal but showed an association with well-established changes in cortical acetylcholine: high during wakefulness and REM sleep and low during SWS. Corticocortical coherence and frontal-parietal connectivity in high γ bandwidth correlates with behavioral arousal and is not mediated by cholinergic mechanisms, while θ connectivity correlates with cortical acetylcholine levels.

Influence of temperature variations on the entropy and correlation of the Grey-Level Co-occurrence Matrix from B-Mode images.

PubMed

Alvarenga, André V; Teixeira, César A; Ruano, Maria Graça; Pereira, Wagner C A

2010-02-01

In this work, the feasibility of texture parameters extracted from B-Mode images were explored in quantifying medium temperature variation. The goal is to understand how parameters obtained from the gray-level content can be used to improve the actual state-of-the-art methods for non-invasive temperature estimation (NITE). B-Mode images were collected from a tissue mimic phantom heated in a water bath. The phantom is a mixture of water, glycerin, agar-agar and graphite powder. This mixture aims to have similar acoustical properties to in vivo muscle. Images from the phantom were collected using an ultrasound system that has a mechanical sector transducer working at 3.5 MHz. Three temperature curves were collected, and variations between 27 and 44 degrees C during 60 min were allowed. Two parameters (correlation and entropy) were determined from Grey-Level Co-occurrence Matrix (GLCM) extracted from image, and then assessed for non-invasive temperature estimation. Entropy values were capable of identifying variations of 2.0 degrees C. Besides, it was possible to quantify variations from normal human body temperature (37 degrees C) to critical values, as 41 degrees C. In contrast, despite correlation parameter values (obtained from GLCM) presented a correlation coefficient of 0.84 with temperature variation, the high dispersion of values limited the temperature assessment.

The effect of orthostatic stress on multiscale entropy of heart rate and blood pressure.

PubMed

Turianikova, Zuzana; Javorka, Kamil; Baumert, Mathias; Calkovska, Andrea; Javorka, Michal

2011-09-01

Cardiovascular control acts over multiple time scales, which introduces a significant amount of complexity to heart rate and blood pressure time series. Multiscale entropy (MSE) analysis has been developed to quantify the complexity of a time series over multiple time scales. In previous studies, MSE analyses identified impaired cardiovascular control and increased cardiovascular risk in various pathological conditions. Despite the increasing acceptance of the MSE technique in clinical research, information underpinning the involvement of the autonomic nervous system in the MSE of heart rate and blood pressure is lacking. The objective of this study is to investigate the effect of orthostatic challenge on the MSE of heart rate and blood pressure variability (HRV, BPV) and the correlation between MSE (complexity measures) and traditional linear (time and frequency domain) measures. MSE analysis of HRV and BPV was performed in 28 healthy young subjects on 1000 consecutive heart beats in the supine and standing positions. Sample entropy values were assessed on scales of 1-10. We found that MSE of heart rate and blood pressure signals is sensitive to changes in autonomic balance caused by postural change from the supine to the standing position. The effect of orthostatic challenge on heart rate and blood pressure complexity depended on the time scale under investigation. Entropy values did not correlate with the mean values of heart rate and blood pressure and showed only weak correlations with linear HRV and BPV measures. In conclusion, the MSE analysis of heart rate and blood pressure provides a sensitive tool to detect changes in autonomic balance as induced by postural change.

Serotonergic Psychedelics Temporarily Modify Information Transfer in Humans

PubMed Central

Alonso, Joan Francesc; Romero, Sergio; Mañanas, Miquel Àngel

2015-01-01

Background: Psychedelics induce intense modifications in the sensorium, the sense of “self,” and the experience of reality. Despite advances in our understanding of the molecular and cellular level mechanisms of these drugs, knowledge of their actions on global brain dynamics is still incomplete. Recent imaging studies have found changes in functional coupling between frontal and parietal brain structures, suggesting a modification in information flow between brain regions during acute effects. Methods: Here we assessed the psychedelic-induced changes in directionality of information flow during the acute effects of a psychedelic in humans. We measured modifications in connectivity of brain oscillations using transfer entropy, a nonlinear measure of directed functional connectivity based on information theory. Ten healthy male volunteers with prior experience with psychedelics participated in 2 experimental sessions. They received a placebo or a dose of ayahuasca, a psychedelic preparation containing the serotonergic 5-HT2A agonist N,N-dimethyltryptamine. Results: The analysis showed significant changes in the coupling of brain oscillations between anterior and posterior recording sites. Transfer entropy analysis showed that frontal sources decreased their influence over central, parietal, and occipital sites. Conversely, sources in posterior locations increased their influence over signals measured at anterior locations. Exploratory correlations found that anterior-to-posterior transfer entropy decreases were correlated with the intensity of subjective effects, while the imbalance between anterior-to-posterior and posterior-to-anterior transfer entropy correlated with the degree of incapacitation experienced. Conclusions: These results suggest that psychedelics induce a temporary disruption of neural hierarchies by reducing top-down control and increasing bottom-up information transfer in the human brain. PMID:25820842

Universality in volume-law entanglement of scrambled pure quantum states.

PubMed

Nakagawa, Yuya O; Watanabe, Masataka; Fujita, Hiroyuki; Sugiura, Sho

2018-04-24

A pure quantum state can fully describe thermal equilibrium as long as one focuses on local observables. The thermodynamic entropy can also be recovered as the entanglement entropy of small subsystems. When the size of the subsystem increases, however, quantum correlations break the correspondence and mandate a correction to this simple volume law. The elucidation of the size dependence of the entanglement entropy is thus essentially important in linking quantum physics with thermodynamics. Here we derive an analytic formula of the entanglement entropy for a class of pure states called cTPQ states representing equilibrium. We numerically find that our formula applies universally to any sufficiently scrambled pure state representing thermal equilibrium, i.e., energy eigenstates of non-integrable models and states after quantum quenches. Our formula is exploited as diagnostics for chaotic systems; it can distinguish integrable models from non-integrable models and many-body localization phases from chaotic phases.

Enhanced magnetocaloric effect tuning efficiency in Ni-Mn-Sn alloy ribbons

NASA Astrophysics Data System (ADS)

Quintana-Nedelcos, A.; Sánchez Llamazares, J. L.; Daniel-Perez, G.

2017-11-01

The present work was undertaken to investigate the effect of microstructure on the magnetic entropy change of Ni50Mn37Sn13 ribbon alloys. Unchanged sample composition and cell parameter of austenite allowed us to study strictly the correlation between the average grain size and the total magnetic field induced entropy change (ΔST). We found that a size-dependent martensitic transformation tuning results in a wide temperature range tailoring (>40 K) of the magnetic entropy change with a reasonably small variation on the peak value of the total field induced entropy change. The peak values varied from 6.0 J kg-1 K-1 to 7.7 J kg-1 K-1 for applied fields up to 2 T. Different tuning efficiencies obtained by diverse MCE tailoring approaches are compared to highlight the advantages of the herein proposed mechanism.

Entropy Production in Field Theories without Time-Reversal Symmetry: Quantifying the Non-Equilibrium Character of Active Matter

NASA Astrophysics Data System (ADS)

Nardini, Cesare; Fodor, Étienne; Tjhung, Elsen; van Wijland, Frédéric; Tailleur, Julien; Cates, Michael E.

2017-04-01

Active-matter systems operate far from equilibrium because of the continuous energy injection at the scale of constituent particles. At larger scales, described by coarse-grained models, the global entropy production rate S quantifies the probability ratio of forward and reversed dynamics and hence the importance of irreversibility at such scales: It vanishes whenever the coarse-grained dynamics of the active system reduces to that of an effective equilibrium model. We evaluate S for a class of scalar stochastic field theories describing the coarse-grained density of self-propelled particles without alignment interactions, capturing such key phenomena as motility-induced phase separation. We show how the entropy production can be decomposed locally (in real space) or spectrally (in Fourier space), allowing detailed examination of the spatial structure and correlations that underly departures from equilibrium. For phase-separated systems, the local entropy production is concentrated mainly on interfaces, with a bulk contribution that tends to zero in the weak-noise limit. In homogeneous states, we find a generalized Harada-Sasa relation that directly expresses the entropy production in terms of the wave-vector-dependent deviation from the fluctuation-dissipation relation between response functions and correlators. We discuss extensions to the case where the particle density is coupled to a momentum-conserving solvent and to situations where the particle current, rather than the density, should be chosen as the dynamical field. We expect the new conceptual tools developed here to be broadly useful in the context of active matter, allowing one to distinguish when and where activity plays an essential role in the dynamics.

Entropy and generalized least square methods in assessment of the regional value of streamgages

USGS Publications Warehouse

Markus, M.; Vernon, Knapp H.; Tasker, Gary D.

2003-01-01

The Illinois State Water Survey performed a study to assess the streamgaging network in the State of Illinois. One of the important aspects of the study was to assess the regional value of each station through an assessment of the information transfer among gaging records for low, average, and high flow conditions. This analysis was performed for the main hydrologic regions in the State, and the stations were initially evaluated using a new approach based on entropy analysis. To determine the regional value of each station within a region, several information parameters, including total net information, were defined based on entropy. Stations were ranked based on the total net information. For comparison, the regional value of the same stations was assessed using the generalized least square regression (GLS) method, developed by the US Geological Survey. Finally, a hybrid combination of GLS and entropy was created by including a function of the negative net information as a penalty function in the GLS. The weights of the combined model were determined to maximize the average correlation with the results of GLS and entropy. The entropy and GLS methods were evaluated using the high-flow data from southern Illinois stations. The combined method was compared with the entropy and GLS approaches using the high-flow data from eastern Illinois stations. ?? 2003 Elsevier B.V. All rights reserved.

Entropic cohering power in quantum operations

NASA Astrophysics Data System (ADS)

Xi, Zhengjun; Hu, Ming-Liang; Li, Yongming; Fan, Heng

2018-02-01

Coherence is a basic feature of quantum systems and a common necessary condition for quantum correlations. It is also an important physical resource in quantum information processing. In this paper, using relative entropy, we consider a more general definition of the cohering power of quantum operations. First, we calculate the cohering power of unitary quantum operations and show that the amount of distributed coherence caused by non-unitary quantum operations cannot exceed the quantum-incoherent relative entropy between system of interest and its environment. We then find that the difference between the distributed coherence and the cohering power is larger than the quantum-incoherent relative entropy. As an application, we consider the distributed coherence caused by purification.

Causal Entropies – a measure for determining changes in the temporal organization of neural systems

PubMed Central

Waddell, Jack; Dzakpasu, Rhonda; Booth, Victoria; Riley, Brett; Reasor, Jonathan; Poe, Gina; Zochowski, Michal

2009-01-01

We propose a novel measure to detect temporal ordering in the activity of individual neurons in a local network, which is thought to be a hallmark of activity-dependent synaptic modifications during learning. The measure, called Causal Entropy, is based on the time-adaptive detection of asymmetries in the relative temporal patterning between neuronal pairs. We characterize properties of the measure on both simulated data and experimental multiunit recordings of hippocampal neurons from the awake, behaving rat, and show that the metric can more readily detect those asymmetries than standard cross correlation-based techniques, especially since the temporal sensitivity of causal entropy can detect such changes rapidly and dynamically. PMID:17275095

Exact computation of the maximum-entropy potential of spiking neural-network models.

PubMed

Cofré, R; Cessac, B

2014-05-01

Understanding how stimuli and synaptic connectivity influence the statistics of spike patterns in neural networks is a central question in computational neuroscience. The maximum-entropy approach has been successfully used to characterize the statistical response of simultaneously recorded spiking neurons responding to stimuli. However, in spite of good performance in terms of prediction, the fitting parameters do not explain the underlying mechanistic causes of the observed correlations. On the other hand, mathematical models of spiking neurons (neuromimetic models) provide a probabilistic mapping between the stimulus, network architecture, and spike patterns in terms of conditional probabilities. In this paper we build an exact analytical mapping between neuromimetic and maximum-entropy models.

Correlations and Fluctuations in Strong Interactions:. a Selection of Topics

NASA Astrophysics Data System (ADS)

Bialas, A.

2003-09-01

Invited talk at the 10th Workshop on Multiparticle Production: Correlations and Fluctuations in QCD. It contains a short account of (i) Event-by-event fluctuations and their relations to "inclusive distributions; (ii) Fluctuations of the conserved charges" (iii) Coincidence probabilities and Renyi entropies, and (iv) HBT correlations in the presence of flow.

Application of an Entropic Approach to Assessing Systems Integration

DTIC Science & Technology

2012-03-01

two econometrical measures of information efficiency – Shannon entropy and Hurst exponent . Shannon entropy (which is explained in Chapter III) can be...applied to evaluate long-term correlation of time series, while Hurst exponent can be applied to classify the time series in accordance to existence...of trend. Hurst exponent is the statistical measure of time series long-range dependence, and its value falls in the interval [0, 1] – a value in

Characterization of separability and entanglement in (2xD)- and (3xD)-dimensional systems by single-qubit and single-qutrit unitary transformations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giampaolo, Salvatore M.; CNR-INFM Coherentia, Naples; CNISM Unita di Salerno and INFN Sezione di Napoli, Gruppo collegato di Salerno, Baronissi

2007-10-15

We investigate the geometric characterization of pure state bipartite entanglement of (2xD)- and (3xD)-dimensional composite quantum systems. To this aim, we analyze the relationship between states and their images under the action of particular classes of local unitary operations. We find that invariance of states under the action of single-qubit and single-qutrit transformations is a necessary and sufficient condition for separability. We demonstrate that in the (2xD)-dimensional case the von Neumann entropy of entanglement is a monotonic function of the minimum squared Euclidean distance between states and their images over the set of single qubit unitary transformations. Moreover, both inmore » the (2xD)- and in the (3xD)-dimensional cases the minimum squared Euclidean distance exactly coincides with the linear entropy [and thus as well with the tangle measure of entanglement in the (2xD)-dimensional case]. These results provide a geometric characterization of entanglement measures originally established in informational frameworks. Consequences and applications of the formalism to quantum critical phenomena in spin systems are discussed.« less

Estimation of conformational entropy in protein-ligand interactions: a computational perspective.

PubMed

Polyansky, Anton A; Zubac, Ruben; Zagrovic, Bojan

2012-01-01

Conformational entropy is an important component of the change in free energy upon binding of a ligand to its target protein. As a consequence, development of computational techniques for reliable estimation of conformational entropies is currently receiving an increased level of attention in the context of computational drug design. Here, we review the most commonly used techniques for conformational entropy estimation from classical molecular dynamics simulations. Although by-and-large still not directly used in practical drug design, these techniques provide a golden standard for developing other, computationally less-demanding methods for such applications, in addition to furthering our understanding of protein-ligand interactions in general. In particular, we focus on the quasi-harmonic approximation and discuss different approaches that can be used to go beyond it, most notably, when it comes to treating anharmonic and/or correlated motions. In addition to reviewing basic theoretical formalisms, we provide a concrete set of steps required to successfully calculate conformational entropy from molecular dynamics simulations, as well as discuss a number of practical issues that may arise in such calculations.

Epoch-based Entropy for Early Screening of Alzheimer's Disease.

PubMed

Houmani, N; Dreyfus, G; Vialatte, F B

2015-12-01

In this paper, we introduce a novel entropy measure, termed epoch-based entropy. This measure quantifies disorder of EEG signals both at the time level and spatial level, using local density estimation by a Hidden Markov Model on inter-channel stationary epochs. The investigation is led on a multi-centric EEG database recorded from patients at an early stage of Alzheimer's disease (AD) and age-matched healthy subjects. We investigate the classification performances of this method, its robustness to noise, and its sensitivity to sampling frequency and to variations of hyperparameters. The measure is compared to two alternative complexity measures, Shannon's entropy and correlation dimension. The classification accuracies for the discrimination of AD patients from healthy subjects were estimated using a linear classifier designed on a development dataset, and subsequently tested on an independent test set. Epoch-based entropy reached a classification accuracy of 83% on the test dataset (specificity = 83.3%, sensitivity = 82.3%), outperforming the two other complexity measures. Furthermore, it was shown to be more stable to hyperparameter variations, and less sensitive to noise and sampling frequency disturbances than the other two complexity measures.

Detection of cracks in shafts with the Approximated Entropy algorithm

NASA Astrophysics Data System (ADS)

Sampaio, Diego Luchesi; Nicoletti, Rodrigo

2016-05-01

The Approximate Entropy is a statistical calculus used primarily in the fields of Medicine, Biology, and Telecommunication for classifying and identifying complex signal data. In this work, an Approximate Entropy algorithm is used to detect cracks in a rotating shaft. The signals of the cracked shaft are obtained from numerical simulations of a de Laval rotor with breathing cracks modelled by the Fracture Mechanics. In this case, one analysed the vertical displacements of the rotor during run-up transients. The results show the feasibility of detecting cracks from 5% depth, irrespective of the unbalance of the rotating system and crack orientation in the shaft. The results also show that the algorithm can differentiate the occurrence of crack only, misalignment only, and crack + misalignment in the system. However, the algorithm is sensitive to intrinsic parameters p (number of data points in a sample vector) and f (fraction of the standard deviation that defines the minimum distance between two sample vectors), and good results are only obtained by appropriately choosing their values according to the sampling rate of the signal.

Quasi-exact solvability and entropies of the one-dimensional regularised Calogero model

NASA Astrophysics Data System (ADS)

Pont, Federico M.; Osenda, Omar; Serra, Pablo

2018-05-01

The Calogero model can be regularised through the introduction of a cutoff parameter which removes the divergence in the interaction term. In this work we show that the one-dimensional two-particle regularised Calogero model is quasi-exactly solvable and that for certain values of the Hamiltonian parameters the eigenfunctions can be written in terms of Heun’s confluent polynomials. These eigenfunctions are such that the reduced density matrix of the two-particle density operator can be obtained exactly as well as its entanglement spectrum. We found that the number of non-zero eigenvalues of the reduced density matrix is finite in these cases. The limits for the cutoff distance going to zero (Calogero) and infinity are analysed and all the previously obtained results for the Calogero model are reproduced. Once the exact eigenfunctions are obtained, the exact von Neumann and Rényi entanglement entropies are studied to characterise the physical traits of the model. The quasi-exactly solvable character of the model is assessed studying the numerically calculated Rényi entropy and entanglement spectrum for the whole parameter space.

Entanglement entropy in causal set theory

NASA Astrophysics Data System (ADS)

Sorkin, Rafael D.; Yazdi, Yasaman K.

2018-04-01

Entanglement entropy is now widely accepted as having deep connections with quantum gravity. It is therefore desirable to understand it in the context of causal sets, especially since they provide in a natural manner the UV cutoff needed to render entanglement entropy finite. Formulating a notion of entanglement entropy in a causal set is not straightforward because the type of canonical hypersurface-data on which its definition typically relies is not available. Instead, we appeal to the more global expression given in Sorkin (2012 (arXiv:1205.2953)) which, for a Gaussian scalar field, expresses the entropy of a spacetime region in terms of the field’s correlation function within that region (its ‘Wightman function’ W(x, x') ). Carrying this formula over to the causal set, one obtains an entropy which is both finite and of a Lorentz invariant nature. We evaluate this global entropy-expression numerically for certain regions (primarily order-intervals or ‘causal diamonds’) within causal sets of 1  +  1 dimensions. For the causal-set counterpart of the entanglement entropy, we obtain, in the first instance, a result that follows a (spacetime) volume law instead of the expected (spatial) area law. We find, however, that one obtains an area law if one truncates the commutator function (‘Pauli–Jordan operator’) and the Wightman function by projecting out the eigenmodes of the Pauli–Jordan operator whose eigenvalues are too close to zero according to a geometrical criterion which we describe more fully below. In connection with these results and the questions they raise, we also study the ‘entropy of coarse-graining’ generated by thinning out the causal set, and we compare it with what one obtains by similarly thinning out a chain of harmonic oscillators, finding the same, ‘universal’ behaviour in both cases.

[Evaluation of a simplified index (spectral entropy) about sleep state of electrocardiogram recorded by a simplified polygraph, MemCalc-Makin2].

PubMed

Ohisa, Noriko; Ogawa, Hiromasa; Murayama, Nobuki; Yoshida, Katsumi

2010-02-01

Polysomnography (PSG) is the gold standard for the diagnosis of sleep apnea hypopnea syndrome (SAHS), but it takes time to analyze the PSG and PSG cannot be performed repeatedly because of efforts and costs. Therefore, simplified sleep respiratory disorder indices in which are reflected the PSG results are needed. The Memcalc method, which is a combination of the maximum entropy method for spectral analysis and the non-linear least squares method for fitting analysis (Makin2, Suwa Trust, Tokyo, Japan) has recently been developed. Spectral entropy which is derived by the Memcalc method might be useful to expressing the trend of time-series behavior. Spectral entropy of ECG which is calculated with the Memcalc method was evaluated by comparing to the PSG results. Obstructive SAS patients (n = 79) and control volanteer (n = 7) ECG was recorded using MemCalc-Makin2 (GMS) with PSG recording using Alice IV (Respironics) from 20:00 to 6:00. Spectral entropy of ECG, which was calculated every 2 seconds using the Memcalc method, was compared to sleep stages which were analyzed manually from PSG recordings. Spectral entropy value (-0.473 vs. -0.418, p < 0.05) were significantly increased in the OSAHS compared to the control. For the entropy cutoff level of -0.423, sensitivity and specificity for OSAHS were 86.1% and 71.4%, respectively, resulting in a receiver operating characteristic with an area under the curve of 0.837. The absolute value of entropy had inverse correlation with stage 3. Spectral entropy, which was calculated with Memcalc method, might be a possible index evaluating the quality of sleep.

Analysis of the phase transition in the two-dimensional Ising ferromagnet using a Lempel-Ziv string-parsing scheme and black-box data-compression utilities

NASA Astrophysics Data System (ADS)

Melchert, O.; Hartmann, A. K.

2015-02-01

In this work we consider information-theoretic observables to analyze short symbolic sequences, comprising time series that represent the orientation of a single spin in a two-dimensional (2D) Ising ferromagnet on a square lattice of size L2=1282 for different system temperatures T . The latter were chosen from an interval enclosing the critical point Tc of the model. At small temperatures the sequences are thus very regular; at high temperatures they are maximally random. In the vicinity of the critical point, nontrivial, long-range correlations appear. Here we implement estimators for the entropy rate, excess entropy (i.e., "complexity"), and multi-information. First, we implement a Lempel-Ziv string-parsing scheme, providing seemingly elaborate entropy rate and multi-information estimates and an approximate estimator for the excess entropy. Furthermore, we apply easy-to-use black-box data-compression utilities, providing approximate estimators only. For comparison and to yield results for benchmarking purposes, we implement the information-theoretic observables also based on the well-established M -block Shannon entropy, which is more tedious to apply compared to the first two "algorithmic" entropy estimation procedures. To test how well one can exploit the potential of such data-compression techniques, we aim at detecting the critical point of the 2D Ising ferromagnet. Among the above observables, the multi-information, which is known to exhibit an isolated peak at the critical point, is very easy to replicate by means of both efficient algorithmic entropy estimation procedures. Finally, we assess how good the various algorithmic entropy estimates compare to the more conventional block entropy estimates and illustrate a simple modification that yields enhanced results.

Automated EEG entropy measurements in coma, vegetative state/unresponsive wakefulness syndrome and minimally conscious state

PubMed Central

Gosseries, Olivia; Schnakers, Caroline; Ledoux, Didier; Vanhaudenhuyse, Audrey; Bruno, Marie-Aurélie; Demertzi, Athéna; Noirhomme, Quentin; Lehembre, Rémy; Damas, Pierre; Goldman, Serge; Peeters, Erika; Moonen, Gustave; Laureys, Steven

Summary Monitoring the level of consciousness in brain-injured patients with disorders of consciousness is crucial as it provides diagnostic and prognostic information. Behavioral assessment remains the gold standard for assessing consciousness but previous studies have shown a high rate of misdiagnosis. This study aimed to investigate the usefulness of electroencephalography (EEG) entropy measurements in differentiating unconscious (coma or vegetative) from minimally conscious patients. Left fronto-temporal EEG recordings (10-minute resting state epochs) were prospectively obtained in 56 patients and 16 age-matched healthy volunteers. Patients were assessed in the acute (≤1 month post-injury; n=29) or chronic (>1 month post-injury; n=27) stage. The etiology was traumatic in 23 patients. Automated online EEG entropy calculations (providing an arbitrary value ranging from 0 to 91) were compared with behavioral assessments (Coma Recovery Scale-Revised) and outcome. EEG entropy correlated with Coma Recovery Scale total scores (r=0.49). Mean EEG entropy values were higher in minimally conscious (73±19; mean and standard deviation) than in vegetative/unresponsive wakefulness syndrome patients (45±28). Receiver operating characteristic analysis revealed an entropy cut-off value of 52 differentiating acute unconscious from minimally conscious patients (sensitivity 89% and specificity 90%). In chronic patients, entropy measurements offered no reliable diagnostic information. EEG entropy measurements did not allow prediction of outcome. User-independent time-frequency balanced spectral EEG entropy measurements seem to constitute an interesting diagnostic – albeit not prognostic – tool for assessing neural network complexity in disorders of consciousness in the acute setting. Future studies are needed before using this tool in routine clinical practice, and these should seek to improve automated EEG quantification paradigms in order to reduce the remaining false negative and false positive findings. PMID:21693085

Feature extraction using gray-level co-occurrence matrix of wavelet coefficients and texture matching for batik motif recognition

NASA Astrophysics Data System (ADS)

Suciati, Nanik; Herumurti, Darlis; Wijaya, Arya Yudhi

2017-02-01

Batik is one of Indonesian's traditional cloth. Motif or pattern drawn on a piece of batik fabric has a specific name and philosopy. Although batik cloths are widely used in everyday life, but only few people understand its motif and philosophy. This research is intended to develop a batik motif recognition system which can be used to identify motif of Batik image automatically. First, a batik image is decomposed into sub-images using wavelet transform. Six texture descriptors, i.e. max probability, correlation, contrast, uniformity, homogenity and entropy, are extracted from gray-level co-occurrence matrix of each sub-image. The texture features are then matched to the template features using canberra distance. The experiment is performed on Batik Dataset consisting of 1088 batik images grouped into seven motifs. The best recognition rate, that is 92,1%, is achieved using feature extraction process with 5 level wavelet decomposition and 4 directional gray-level co-occurrence matrix.

Gray-level co-occurrence matrix analysis of several cell types in mouse brain using resolution-enhanced photothermal microscopy

NASA Astrophysics Data System (ADS)

Kobayashi, Takayoshi; Sundaram, Durga; Nakata, Kazuaki; Tsurui, Hiromichi

2017-03-01

Qualifications of intracellular structure were performed for the first time using the gray-level co-occurrence matrix (GLCM) method for images of cells obtained by resolution-enhanced photothermal imaging. The GLCM method has been used to extract five parameters of texture features for five different types of cells in mouse brain; pyramidal neurons and glial cells in the basal nucleus (BGl), dentate gyrus granule cells, cerebellar Purkinje cells, and cerebellar granule cells. The parameters are correlation, contrast, angular second moment (ASM), inverse difference moment (IDM), and entropy for the images of cells of interest in a mouse brain. The parameters vary depending on the pixel distance taken in the analysis method. Based on the obtained results, we identified that the most suitable GLCM parameter is IDM for pyramidal neurons and BGI, granule cells in the dentate gyrus, Purkinje cells and granule cells in the cerebellum. It was also found that the ASM is the most appropriate for neurons in the basal nucleus.

Radiation Entropy and Near-Field Thermophotovoltaics

NASA Astrophysics Data System (ADS)

Zhang, Zhuomin M.

2008-08-01

Radiation entropy was key to the original derivation of Planck's law of blackbody radiation, in 1900. This discovery opened the door to quantum mechanical theory and Planck was awarded the Nobel Prize in Physics in 1918. Thermal radiation plays an important role in incandescent lamps, solar energy utilization, temperature measurements, materials processing, remote sensing for astronomy and space exploration, combustion and furnace design, food processing, cryogenic engineering, as well as numerous agricultural, health, and military applications. While Planck's law has been fruitfully applied to a large number of engineering problems for over 100 years, questions have been raised about its limitation in micro/nano systems, especially at subwavelength distances or in the near field. When two objects are located closer than the characteristic wavelength, wave interference and photon tunneling occurs that can result in significant enhancement of the radiative transfer. Recent studies have shown that the near-field effects can realize emerging technologies, such as superlens, sub-wavelength light source, polariton-assisted nanolithography, thermophotovoltaic (TPV) systems, scanning tunneling thermal microscopy, etc. The concept of entropy has also been applied to explain laser cooling of solids as well as the second law efficiency of devices that utilize thermal radiation to produce electricity. However, little is known as regards the nature of entropy in near-field radiation. Some history and recent advances are reviewed in this presentation with a call for research of radiation entropy in the near field, due to the important applications in the optimization of thermophotovoltaic converters and in the design of practical systems that can harvest photon energies efficiently.

Fast Diffusion to Self-Similarity: Complete Spectrum, Long-Time Asymptotics, and Numerology

NASA Astrophysics Data System (ADS)

Denzler, Jochen; McCann, Robert J.

2005-03-01

The complete spectrum is determined for the operator on the Sobolev space W1,2ρ(Rn) formed by closing the smooth functions of compact support with respect to the norm Here the Barenblatt profile ρ is the stationary attractor of the rescaled diffusion equation in the fast, supercritical regime m the same diffusion dynamics represent the steepest descent down an entropy E(u) on probability measures with respect to the Wasserstein distance d2. Formally, the operator H=HessρE is the Hessian of this entropy at its minimum ρ, so the spectral gap H≧α:=2-n(1-m) found below suggests the sharp rate of asymptotic convergence: from any centered initial data 0≦u(0,x) ∈ L1(Rn) with second moments. This bound improves various results in the literature, and suggests the conjecture that the self-similar solution u(t,x)=R(t)-nρ(x/R(t)) is always slowest to converge. The higher eigenfunctions which are polynomials with hypergeometric radial parts and the presence of continuous spectrum yield additional insight into the relations between symmetries of Rn and the flow. Thus the rate of convergence can be improved if we are willing to replace the distance to ρ with the distance to its nearest mass-preserving dilation (or still better, affine image). The strange numerology of the spectrum is explained in terms of the number of moments of ρ.

Effect of frying temperature and time on image characterizations of pellet snacks.

PubMed

Mohammadi Moghaddam, Toktam; BahramParvar, Maryam; Razavi, Seyed M A

2015-05-01

The development of non-destructive methods for the evaluation of food properties has important advantages for the food processing industries. So, the aim of this study was to evaluate the effects of frying temperature (150, 170, and 190 °C) and time (0.5, 1.5, 2.5, 3.5 and 4.5 min) on image properties (L*, a* and b*, fractal dimension, correlation, entropy, contrast and homogeneity) of pellet snacks. Textures were computed separately for eight channels (RGB, R, G, B, U, V, H and S). Enhancing the frying time from 0.5 min to 2.5 min increased the fractal dimension; but its increase from 2.5 min to 4.5 min could not expand the samples. Then, the highest volume of pellet snacks was observed at 2.5 min. Features derived from the image texture contained better information than color features. The best result was for U channel which showed that increasing the frying time increased the contrast, entropy and correlation. Developing the frying temperature up to 170 °C decreased contrast, entropy and correlation of images; however these factors were increased when frying temperature was 190 °C. These results were invert for homogeneity.

Exploring Localization in Nuclear Spin Chains

NASA Astrophysics Data System (ADS)

Wei, Ken Xuan; Ramanathan, Chandrasekhar; Cappellaro, Paola

2018-02-01

Characterizing out-of-equilibrium many-body dynamics is a complex but crucial task for quantum applications and understanding fundamental phenomena. A central question is the role of localization in quenching thermalization in many-body systems and whether such localization survives in the presence of interactions. Probing this question in real systems necessitates the development of an experimentally measurable metric that can distinguish between different types of localization. While it is known that the localized phase of interacting systems [many-body localization (MBL)] exhibits a long-time logarithmic growth in entanglement entropy that distinguishes it from the noninteracting case of Anderson localization (AL), entanglement entropy is difficult to measure experimentally. Here, we present a novel correlation metric, capable of distinguishing MBL from AL in high-temperature spin systems. We demonstrate the use of this metric to detect localization in a natural solid-state spin system using nuclear magnetic resonance (NMR). We engineer the natural Hamiltonian to controllably introduce disorder and interactions, and observe the emergence of localization. In particular, while our correlation metric saturates for AL, it slowly keeps increasing for MBL, demonstrating analogous features to entanglement entropy, as we show in simulations. Our results show that our NMR techniques, akin to measuring out-of-time correlations, are well suited for studying localization in spin systems.

State Anxiety and Nonlinear Dynamics of Heart Rate Variability in Students.

PubMed

Dimitriev, Dimitriy A; Saperova, Elena V; Dimitriev, Aleksey D

2016-01-01

Clinical and experimental research studies have demonstrated that the emotional experience of anxiety impairs heart rate variability (HRV) in humans. The present study investigated whether changes in state anxiety (SA) can also modulate nonlinear dynamics of heart rate. A group of 96 students volunteered to participate in the study. For each student, two 5-minute recordings of beat intervals (RR) were performed: one during a rest period and one just before a university examination, which was assumed to be a real-life stressor. Nonlinear analysis of HRV was performed. The Spielberger's State-Trait Anxiety Inventory was used to assess the level of SA. Before adjusting for heart rate, a Wilcoxon matched pairs test showed significant decreases in Poincaré plot measures, entropy, largest Lyapunov exponent (LLE), and pointwise correlation dimension (PD2), and an increase in the short-term fractal-like scaling exponent of detrended fluctuation analysis (α1) during the exam session, compared with the rest period. A Pearson analysis indicated significant negative correlations between the dynamics of SA and Poincaré plot axes ratio (SD1/SD2), and between changes in SA and changes in entropy measures. A strong negative correlation was found between the dynamics of SA and LLE. A significant positive correlation was found between the dynamics of SA and α1. The decreases in Poincaré plot measures (SD1, complex correlation measure), entropy measures, and LLE were still significant after adjusting for heart rate. Corrected α1 was increased during the exam session. As before, the dynamics of adjusted LLE was significantly correlated with the dynamics of SA. The qualitative increase in SA during academic examination was related to the decrease in the complexity and size of the Poincaré plot through a reduction of both the interbeat interval and its variation.

Extremes of fractional noises: A model for the timings of arrhythmic heart beats in post-infarction patients

NASA Astrophysics Data System (ADS)

Witt, Annette; Ehlers, Frithjof; Luther, Stefan

2017-09-01

We have analyzed symbol sequences of heart beat annotations obtained from 24-h electrocardiogram recordings of 184 post-infarction patients (from the Cardiac Arrhythmia Suppression Trial database, CAST). In the symbol sequences, each heart beat was coded as an arrhythmic or as a normal beat. The symbol sequences were analyzed with a model-based approach which relies on two-parametric peaks over the threshold (POT) model, interpreting each premature ventricular contraction (PVC) as an extreme event. For the POT model, we explored (i) the Shannon entropy which was estimated in terms of the Lempel-Ziv complexity, (ii) the shape parameter of the Weibull distribution that best fits the PVC return times, and (iii) the strength of long-range correlations quantified by detrended fluctuation analysis (DFA) for the two-dimensional parameter space. We have found that in the frame of our model the Lempel-Ziv complexity is functionally related to the shape parameter of the Weibull distribution. Thus, two complementary measures (entropy and strength of long-range correlations) are sufficient to characterize realizations of the two-parametric model. For the CAST data, we have found evidence for an intermediate strength of long-range correlations in the PVC timings, which are correlated to the age of the patient: younger post-infarction patients have higher strength of long-range correlations than older patients. The normalized Shannon entropy has values in the range 0.5

Power spectrum entropy of acceleration time-series during movement as an indicator of smoothness of movement.

PubMed

Kojima, Motonaga; Obuchi, Shuichi; Mizuno, Kousuke; Henmi, Osamu; Ikeda, Noriaki

2008-06-01

We propose a novel indicator for smoothness of movement, i.e., the power spectrum entropy of the acceleration time-series, and compare it with conventional indices of smoothness. For this purpose, nineteen healthy adults (21.3+/-2.5 years old) performed the task of raising and lowering a beaker between the level of the umbilicus and eye level under the two following conditions: one with the beaker containing water and the other with the beaker containing a weight of the same mass as the water. Moving the beaker up and down when it contained water required extra control to prevent the water from being spilled. This means that movement was not as smooth as when the beaker contained a weight. Under these two conditions, entropy was measured along with a traditional indicator of smoothness of movement, the jerk index. The entropy could distinguish just as well as the jerk index (p<0.01) between when water was used and when the weight was used. The entropy correlated highly with the jerk index, with Spearman's rho at 0.88 (p<0.01). These results showed that the entropy derived from the spectrum of the acceleration time-series during movement is useful as an indicator of the smoothness of that movement.

Information loss in effective field theory: Entanglement and thermal entropies

NASA Astrophysics Data System (ADS)

Boyanovsky, Daniel

2018-03-01

Integrating out high energy degrees of freedom to yield a low energy effective field theory leads to a loss of information with a concomitant increase in entropy. We obtain the effective field theory of a light scalar field interacting with heavy fields after tracing out the heavy degrees of freedom from the time evolved density matrix. The initial density matrix describes the light field in its ground state and the heavy fields in equilibrium at a common temperature T . For T =0 , we obtain the reduced density matrix in a perturbative expansion; it reveals an emergent mixed state as a consequence of the entanglement between light and heavy fields. We obtain the effective action that determines the time evolution of the reduced density matrix for the light field in a nonperturbative Dyson resummation of one-loop correlations of the heavy fields. The Von-Neumann entanglement entropy associated with the reduced density matrix is obtained for the nonresonant and resonant cases in the asymptotic long time limit. In the nonresonant case the reduced density matrix displays an incipient thermalization albeit with a wave-vector, time and coupling dependent effective temperature as a consequence of memory of initial conditions. The entanglement entropy is time independent and is the thermal entropy for this effective, nonequilibrium temperature. In the resonant case the light field fully thermalizes with the heavy fields, the reduced density matrix loses memory of the initial conditions and the entanglement entropy becomes the thermal entropy of the light field. We discuss the relation between the entanglement entropy ultraviolet divergences and renormalization.

Comparison of spectral entropy and BIS VISTA™ monitor during general anesthesia for cardiac surgery.

PubMed

Musialowicz, Tadeusz; Lahtinen, Pasi; Pitkänen, Otto; Kurola, Jouni; Parviainen, Ilkka

2011-04-01

We compared the primary metrics of the Spectral entropy M-ENTROPY™ module and BIS VISTA™ monitor-i.e., bispectral index (BIS), state entropy (SE), and response entropy (RE) in terms of agreement and correlation during general anesthesia for cardiac surgery. We also evaluated responsiveness of electroencephalogram (EEG)-based and hemodynamic parameters to surgical noxious stimulation, skin incision, and sternotomy, hypothesizing that RE would be a better responsiveness predictor. BIS and entropy sensors were applied before anesthesia induction in 32 patients having elective cardiac surgery. Total intravenous anesthesia was standardized and guided by the BIS index with neuromuscular blockade tested with train-of-four monitoring. Parameters included SE, RE, BIS, forehead electromyography (EMG), and hemodynamic variables. Time points for analyzing BIS, entropy, and hemodynamic values were 1 min before and after: anesthesia induction, intubation, skin incision, sternotomy, cannulation of the aorta, cardiopulmonary bypass (CPB), cross-clamping the aorta, de-clamping the aorta, and end of CPB; also after starting the re-warming phase and at 10, 20, 30, and 40 min following. The mean difference between BIS and SE (Bland-Altman) was 2.14 (+16/- 11; 95% CI 1.59-2.67), and between BIS and RE it was 0.02 (+14/- 14; 95% CI 0.01-0.06). BIS and SE (r(2) = 0.66; P = 0.001) and BIS and RE (r(2) = 0.7; P = 0.001) were closely correlated (Pearson's). EEG parameters, EMG values, and systolic blood pressure significantly increased after skin incision, and sternotomy. The effect of surgical stimulation (Cohen's d) was highest for RE after skin incision (-0.71; P = 0.0001) and sternotomy (-0.94; P = 0.0001). Agreement was poor between the BIS index measured by BIS VISTA™ and SE values at critical anesthesia time points in patients undergoing cardiac surgery. RE was a good predictor of arousal after surgical stimulation regardless of the surgical level of muscle relaxation. Index differences most likely resulted from different algorithms for calculating consciousness level.

T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results.

PubMed

Nketiah, Gabriel; Elschot, Mattijs; Kim, Eugene; Teruel, Jose R; Scheenen, Tom W; Bathen, Tone F; Selnæs, Kirsten M

2017-07-01

To evaluate the diagnostic relevance of T2-weighted (T2W) MRI-derived textural features relative to quantitative physiological parameters derived from diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI in Gleason score (GS) 3+4 and 4+3 prostate cancers. 3T multiparametric-MRI was performed on 23 prostate cancer patients prior to prostatectomy. Textural features [angular second moment (ASM), contrast, correlation, entropy], apparent diffusion coefficient (ADC), and DCE pharmacokinetic parameters (K trans and V e ) were calculated from index tumours delineated on the T2W, DW, and DCE images, respectively. The association between the textural features and prostatectomy GS and the MRI-derived parameters, and the utility of the parameters in differentiating between GS 3+4 and 4+3 prostate cancers were assessed statistically. ASM and entropy correlated significantly (p < 0.05) with both GS and median ADC. Contrast correlated moderately with median ADC. The textural features correlated insignificantly with K trans and V e . GS 4+3 cancers had significantly lower ASM and higher entropy than 3+4 cancers, but insignificant differences in median ADC, K trans , and V e . The combined texture-MRI parameters yielded higher classification accuracy (91%) than the individual parameter sets. T2W MRI-derived textural features could serve as potential diagnostic markers, sensitive to the pathological differences in prostate cancers. • T2W MRI-derived textural features correlate significantly with Gleason score and ADC. • T2W MRI-derived textural features differentiate Gleason score 3+4 from 4+3 cancers. • T2W image textural features could augment tumour characterization.

New hesitation-based distance and similarity measures on intuitionistic fuzzy sets and their applications

NASA Astrophysics Data System (ADS)

Kang, Yun; Wu, Shunxiang; Cao, Da; Weng, Wei

2018-03-01

In this paper, we present new definitions on distance and similarity measures between intuitionistic fuzzy sets (IFSs) by combining with hesitation degree. First, we discuss the limitations in traditional distance and similarity measures, which are caused by the neglect of hesitation degree's influence. Even though a vector-valued similarity measure was proposed, which has two components indicating similarity and hesitation aspects, it still cannot perform well in practical applications because hesitation works only when the values of similarity measures are equal. In order to overcome the limitations, we propose new definitions on hesitation, distance and similarity measures, and research some theorems which satisfy the requirements of the proposed definitions. Meanwhile, we investigate the relationships among hesitation, distance, similarity and entropy of IFSs to verify the consistency of our work and previous research. Finally, we analyse and discuss the advantages and disadvantages of the proposed similarity measure in detail, and then we apply the proposed measures (dH and SH) to deal with pattern recognition problems, and demonstrate that they outperform state-of-the-art distance and similarity measures.

Non-linear HRV indices under autonomic nervous system blockade.

PubMed

Bolea, Juan; Pueyo, Esther; Laguna, Pablo; Bailón, Raquel

2014-01-01

Heart rate variability (HRV) has been studied as a non-invasive technique to characterize the autonomic nervous system (ANS) regulation of the heart. Non-linear methods based on chaos theory have been used during the last decades as markers for risk stratification. However, interpretation of these nonlinear methods in terms of sympathetic and parasympathetic activity is not fully established. In this work we study linear and non-linear HRV indices during ANS blockades in order to assess their relation with sympathetic and parasympathetic activities. Power spectral content in low frequency (0.04-0.15 Hz) and high frequency (0.15-0.4 Hz) bands of HRV, as well as correlation dimension, sample and approximate entropies were computed in a database of subjects during single and dual ANS blockade with atropine and/or propranolol. Parasympathetic blockade caused a significant decrease in the low and high frequency power of HRV, as well as in correlation dimension and sample and approximate entropies. Sympathetic blockade caused a significant increase in approximate entropy. Sympathetic activation due to postural change from supine to standing caused a significant decrease in all the investigated non-linear indices and a significant increase in the normalized power in the low frequency band. The other investigated linear indices did not show significant changes. Results suggest that parasympathetic activity has a direct relation with sample and approximate entropies.

Maximum entropy analysis of polarized fluorescence decay of (E)GFP in aqueous solution

NASA Astrophysics Data System (ADS)

Novikov, Eugene G.; Skakun, Victor V.; Borst, Jan Willem; Visser, Antonie J. W. G.

2018-01-01

The maximum entropy method (MEM) was used for the analysis of polarized fluorescence decays of enhanced green fluorescent protein (EGFP) in buffered water/glycerol mixtures, obtained with time-correlated single-photon counting (Visser et al 2016 Methods Appl. Fluoresc. 4 035002). To this end, we used a general-purpose software module of MEM that was earlier developed to analyze (complex) laser photolysis kinetics of ligand rebinding reactions in oxygen binding proteins. We demonstrate that the MEM software provides reliable results and is easy to use for the analysis of both total fluorescence decay and fluorescence anisotropy decay of aqueous solutions of EGFP. The rotational correlation times of EGFP in water/glycerol mixtures, obtained by MEM as maxima of the correlation-time distributions, are identical to the single correlation times determined by global analysis of parallel and perpendicular polarized decay components. The MEM software is also able to determine homo-FRET in another dimeric GFP, for which the transfer correlation time is an order of magnitude shorter than the rotational correlation time. One important advantage utilizing MEM analysis is that no initial guesses of parameters are required, since MEM is able to select the least correlated solution from the feasible set of solutions.

Discriminative components of data.

PubMed

Peltonen, Jaakko; Kaski, Samuel

2005-01-01

A simple probabilistic model is introduced to generalize classical linear discriminant analysis (LDA) in finding components that are informative of or relevant for data classes. The components maximize the predictability of the class distribution which is asymptotically equivalent to 1) maximizing mutual information with the classes, and 2) finding principal components in the so-called learning or Fisher metrics. The Fisher metric measures only distances that are relevant to the classes, that is, distances that cause changes in the class distribution. The components have applications in data exploration, visualization, and dimensionality reduction. In empirical experiments, the method outperformed, in addition to more classical methods, a Renyi entropy-based alternative while having essentially equivalent computational cost.

Toward a Classical Thermodynamic Model for Retro-cognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

May, Edwin C.

2011-11-29

Retro-cognition--a human response before a randomly determined future stimulus--has always been part of our experience. Experiments over the last 80 years show a small but statistically significant effect. If this turns out to be true, then it suggests a form of macroscopic retro-causation. The 2nd Law of Thermodynamics provides an explanation for the apparent single direction of time at the macroscopic level although time is reversible at the microscopic level. In a preliminary study, I examined seven anomalous cognition (a.k.a., ESP) studies in which the entropic gradients and the entropy of their associated target systems were calculated, and the qualitymore » of the response was estimated by a rating system called the figure of merit. The combined Spearman's correlation coefficient for these variables for the seven studies was 0.211 (p = 6.4x10{sup -4}) with a 95% confidence interval for the correlation of [0.084, 0.332]; whereas, the same data for a correlation with the entropy itself was 0.028 (p = 0.36; 95% confidence interval of [-0.120-0.175]). This suggests that anomalous cognition is mediated via some kind of a sensory system in that all the normal sensory systems are more sensitive to changes than they are to inputs that are not changing. A standard relationship for the change of entropy of a binary sequence appears to provide an upper limit to anomalous cognition functioning for free response and for forced-choice Zener card guessing. This entropic relation and an apparent limit set by the entropy may provide a clue for understanding macroscopic retro-causation.« less

Serotonergic psychedelics temporarily modify information transfer in humans.

PubMed

Alonso, Joan Francesc; Romero, Sergio; Mañanas, Miquel Àngel; Riba, Jordi

2015-03-28

Psychedelics induce intense modifications in the sensorium, the sense of "self," and the experience of reality. Despite advances in our understanding of the molecular and cellular level mechanisms of these drugs, knowledge of their actions on global brain dynamics is still incomplete. Recent imaging studies have found changes in functional coupling between frontal and parietal brain structures, suggesting a modification in information flow between brain regions during acute effects. Here we assessed the psychedelic-induced changes in directionality of information flow during the acute effects of a psychedelic in humans. We measured modifications in connectivity of brain oscillations using transfer entropy, a nonlinear measure of directed functional connectivity based on information theory. Ten healthy male volunteers with prior experience with psychedelics participated in 2 experimental sessions. They received a placebo or a dose of ayahuasca, a psychedelic preparation containing the serotonergic 5-HT2A agonist N,N-dimethyltryptamine. The analysis showed significant changes in the coupling of brain oscillations between anterior and posterior recording sites. Transfer entropy analysis showed that frontal sources decreased their influence over central, parietal, and occipital sites. Conversely, sources in posterior locations increased their influence over signals measured at anterior locations. Exploratory correlations found that anterior-to-posterior transfer entropy decreases were correlated with the intensity of subjective effects, while the imbalance between anterior-to-posterior and posterior-to-anterior transfer entropy correlated with the degree of incapacitation experienced. These results suggest that psychedelics induce a temporary disruption of neural hierarchies by reducing top-down control and increasing bottom-up information transfer in the human brain. © The Author 2015. Published by Oxford University Press on behalf of CINP.

Effect of curvature squared corrections to gravitational action on viscosity-to-entropy ratio of the dual gauge theory

NASA Astrophysics Data System (ADS)

Petrov, Pavel

In this thesis we study the properties of strongly-coupled large-N conformal field theories (CFT's) using AdS/CFT correspondence. Chapter 1 serves as an introduction. In Chapter 2 we study the shear viscosity of strongly-coupled large-N conformal field theories. We find that it is affected by R2 corrections to the AdS action and present an example of 4D theory in which the the conjectured universal lower bound on viscosity-to-entropy ratio η/s > 1/4π is violated by 1/N corrections. This fact proves that there is no universal lower bound of 1/4π on viscosity-to-entropy ratio and may be relevant for the studies of QCD quark-gluon plasma for which this ratio is experimentally found to be close to 1/4π. In Chapter 3 we study the formation of the electron star in 4D AdS space. We show that in a gravity theory with charged fermions a layer of charged fermion fluid may form at a finite distance from the charged black hole. We show that these “electron stars” are candidate gravity duals for strongly interacting fermion systems at finite density and finite temperature. Entropy density for such systems scales as s ˜ T2/z at low temperatures as expected from IR criticality of electron stars solutions.

HMM for hyperspectral spectrum representation and classification with endmember entropy vectors

NASA Astrophysics Data System (ADS)

Arabi, Samir Y. W.; Fernandes, David; Pizarro, Marco A.

2015-10-01

The Hyperspectral images due to its good spectral resolution are extensively used for classification, but its high number of bands requires a higher bandwidth in the transmission data, a higher data storage capability and a higher computational capability in processing systems. This work presents a new methodology for hyperspectral data classification that can work with a reduced number of spectral bands and achieve good results, comparable with processing methods that require all hyperspectral bands. The proposed method for hyperspectral spectra classification is based on the Hidden Markov Model (HMM) associated to each Endmember (EM) of a scene and the conditional probabilities of each EM belongs to each other EM. The EM conditional probability is transformed in EM vector entropy and those vectors are used as reference vectors for the classes in the scene. The conditional probability of a spectrum that will be classified is also transformed in a spectrum entropy vector, which is classified in a given class by the minimum ED (Euclidian Distance) among it and the EM entropy vectors. The methodology was tested with good results using AVIRIS spectra of a scene with 13 EM considering the full 209 bands and the reduced spectral bands of 128, 64 and 32. For the test area its show that can be used only 32 spectral bands instead of the original 209 bands, without significant loss in the classification process.

Taxi trips distribution modeling based on Entropy-Maximizing theory: A case study in Harbin city-China

NASA Astrophysics Data System (ADS)

Tang, Jinjun; Zhang, Shen; Chen, Xinqiang; Liu, Fang; Zou, Yajie

2018-03-01

Understanding Origin-Destination distribution of taxi trips is very important for improving effects of transportation planning and enhancing quality of taxi services. This study proposes a new method based on Entropy-Maximizing theory to model OD distribution in Harbin city using large-scale taxi GPS trajectories. Firstly, a K-means clustering method is utilized to partition raw pick-up and drop-off location into different zones, and trips are assumed to start from and end at zone centers. A generalized cost function is further defined by considering travel distance, time and fee between each OD pair. GPS data collected from more than 1000 taxis at an interval of 30 s during one month are divided into two parts: data from first twenty days is treated as training dataset and last ten days is taken as testing dataset. The training dataset is used to calibrate model while testing dataset is used to validate model. Furthermore, three indicators, mean absolute error (MAE), root mean square error (RMSE) and mean percentage absolute error (MPAE), are applied to evaluate training and testing performance of Entropy-Maximizing model versus Gravity model. The results demonstrate Entropy-Maximizing model is superior to Gravity model. Findings of the study are used to validate the feasibility of OD distribution from taxi GPS data in urban system.

Complexity of intracranial pressure correlates with outcome after traumatic brain injury

PubMed Central

Lu, Cheng-Wei; Czosnyka, Marek; Shieh, Jiann-Shing; Smielewska, Anna; Pickard, John D.

2012-01-01

This study applied multiscale entropy analysis to investigate the correlation between the complexity of intracranial pressure waveform and outcome after traumatic brain injury. Intracranial pressure and arterial blood pressure waveforms were low-pass filtered to remove the respiratory and pulse components and then processed using a multiscale entropy algorithm to produce a complexity index. We identified significant differences across groups classified by the Glasgow Outcome Scale in intracranial pressure, pressure-reactivity index and complexity index of intracranial pressure (P < 0.0001; P = 0.001; P < 0.0001, respectively). Outcome was dichotomized as survival/death and also as favourable/unfavourable. The complexity index of intracranial pressure achieved the strongest statistical significance (F = 28.7; P < 0.0001 and F = 17.21; P < 0.0001, respectively) and was identified as a significant independent predictor of mortality and favourable outcome in a multivariable logistic regression model (P < 0.0001). The results of this study suggest that complexity of intracranial pressure assessed by multiscale entropy was significantly associated with outcome in patients with brain injury. PMID:22734128

Respiration-Averaged CT for Attenuation Correction of PET Images – Impact on PET Texture Features in Non-Small Cell Lung Cancer Patients

PubMed Central

Cheng, Nai-Ming; Fang, Yu-Hua Dean; Tsan, Din-Li

2016-01-01

Purpose We compared attenuation correction of PET images with helical CT (PET/HCT) and respiration-averaged CT (PET/ACT) in patients with non-small-cell lung cancer (NSCLC) with the goal of investigating the impact of respiration-averaged CT on 18F FDG PET texture parameters. Materials and Methods A total of 56 patients were enrolled. Tumors were segmented on pretreatment PET images using the adaptive threshold. Twelve different texture parameters were computed: standard uptake value (SUV) entropy, uniformity, entropy, dissimilarity, homogeneity, coarseness, busyness, contrast, complexity, grey-level nonuniformity, zone-size nonuniformity, and high grey-level large zone emphasis. Comparisons of PET/HCT and PET/ACT were performed using Wilcoxon signed-rank tests, intraclass correlation coefficients, and Bland-Altman analysis. Receiver operating characteristic (ROC) curves as well as univariate and multivariate Cox regression analyses were used to identify the parameters significantly associated with disease-specific survival (DSS). A fixed threshold at 45% of the maximum SUV (T45) was used for validation. Results SUV maximum and total lesion glycolysis (TLG) were significantly higher in PET/ACT. However, texture parameters obtained with PET/ACT and PET/HCT showed a high degree of agreement. The lowest levels of variation between the two modalities were observed for SUV entropy (9.7%) and entropy (9.8%). SUV entropy, entropy, and coarseness from both PET/ACT and PET/HCT were significantly associated with DSS. Validation analyses using T45 confirmed the usefulness of SUV entropy and entropy in both PET/HCT and PET/ACT for the prediction of DSS, but only coarseness from PET/ACT achieved the statistical significance threshold. Conclusions Our results indicate that 1) texture parameters from PET/ACT are clinically useful in the prediction of survival in NSCLC patients and 2) SUV entropy and entropy are robust to attenuation correction methods. PMID:26930211

Information content exploitation of imaging spectrometer's images for lossless compression

NASA Astrophysics Data System (ADS)

Wang, Jianyu; Zhu, Zhenyu; Lin, Kan

1996-11-01

Imaging spectrometer, such as MAIS produces a tremendous volume of image data with up to 5.12 Mbps raw data rate, which needs urgently a real-time, efficient and reversible compression implementation. Between the lossy scheme with high compression ratio and the lossless scheme with high fidelity, we must make our choice based on the particular information content analysis of each imaging spectrometer's image data. In this paper, we present a careful analysis of information-preserving compression of imaging spectrometer MAIS with an entropy and autocorrelation study on the hyperspectral images. First, the statistical information in an actual MAIS image, captured in Marble Bar Australia, is measured with its entropy, conditional entropy, mutual information and autocorrelation coefficients on both spatial dimensions and spectral dimension. With these careful analyses, it is shown that there is high redundancy existing in the spatial dimensions, but the correlation in spectral dimension of the raw images is smaller than expected. The main reason of the nonstationarity on spectral dimension is attributed to the instruments's discrepancy on detector's response and channel's amplification in different spectral bands. To restore its natural correlation, we preprocess the signal in advance. There are two methods to accomplish this requirement: onboard radiation calibration and normalization. A better result can be achieved by the former one. After preprocessing, the spectral correlation increases so high that it contributes much redundancy in addition to spatial correlation. At last, an on-board hardware implementation for the lossless compression is presented with an ideal result.

Sway Area and Velocity Correlated With MobileMat Balance Error Scoring System (BESS) Scores.

PubMed

Caccese, Jaclyn B; Buckley, Thomas A; Kaminski, Thomas W

2016-08-01

The Balance Error Scoring System (BESS) is often used for sport-related concussion balance assessment. However, moderate intratester and intertester reliability may cause low initial sensitivity, suggesting that a more objective balance assessment method is needed. The MobileMat BESS was designed for objective BESS scoring, but the outcome measures must be validated with reliable balance measures. Thus, the purpose of this investigation was to compare MobileMat BESS scores to linear and nonlinear measures of balance. Eighty-eight healthy collegiate student-athletes (age: 20.0 ± 1.4 y, height: 177.7 ± 10.7 cm, mass: 74.8 ± 13.7 kg) completed the MobileMat BESS. MobileMat BESS scores were compared with 95% area, sway velocity, approximate entropy, and sample entropy. MobileMat BESS scores were significantly correlated with 95% area for single-leg (r = .332) and tandem firm (r = .474), and double-leg foam (r = .660); and with sway velocity for single-leg (r = .406) and tandem firm (r = .601), and double-leg (r = .575) and single-leg foam (r = .434). MobileMat BESS scores were not correlated with approximate or sample entropy. MobileMat BESS scores were low to moderately correlated with linear measures, suggesting the ability to identify changes in the center of mass-center of pressure relationship, but not higher-order processing associated with nonlinear measures. These results suggest that the MobileMat BESS may be a clinically-useful tool that provides objective linear balance measures.

Textural features of dynamic contrast-enhanced MRI derived model-free and model-based parameter maps in glioma grading.

PubMed

Xie, Tian; Chen, Xiao; Fang, Jingqin; Kang, Houyi; Xue, Wei; Tong, Haipeng; Cao, Peng; Wang, Sumei; Yang, Yizeng; Zhang, Weiguo

2018-04-01

Presurgical glioma grading by dynamic contrast-enhanced MRI (DCE-MRI) has unresolved issues. The aim of this study was to investigate the ability of textural features derived from pharmacokinetic model-based or model-free parameter maps of DCE-MRI in discriminating between different grades of gliomas, and their correlation with pathological index. Retrospective. Forty-two adults with brain gliomas. 3.0T, including conventional anatomic sequences and DCE-MRI sequences (variable flip angle T1-weighted imaging and three-dimensional gradient echo volumetric imaging). Regions of interest on the cross-sectional images with maximal tumor lesion. Five commonly used textural features, including Energy, Entropy, Inertia, Correlation, and Inverse Difference Moment (IDM), were generated. All textural features of model-free parameters (initial area under curve [IAUC], maximal signal intensity [Max SI], maximal up-slope [Max Slope]) could effectively differentiate between grade II (n = 15), grade III (n = 13), and grade IV (n = 14) gliomas (P < 0.05). Two textural features, Entropy and IDM, of four DCE-MRI parameters, including Max SI, Max Slope (model-free parameters), vp (Extended Tofts), and vp (Patlak) could differentiate grade III and IV gliomas (P < 0.01) in four measurements. Both Entropy and IDM of Patlak-based K trans and vp could differentiate grade II (n = 15) from III (n = 13) gliomas (P < 0.01) in four measurements. No textural features of any DCE-MRI parameter maps could discriminate between subtypes of grade II and III gliomas (P < 0.05). Both Entropy and IDM of Extended Tofts- and Patlak-based vp showed highest area under curve in discriminating between grade III and IV gliomas. However, intraclass correlation coefficient (ICC) of these features revealed relatively lower inter-observer agreement. No significant correlation was found between microvascular density and textural features, compared with a moderate correlation found between cellular proliferation index and those features. Textural features of DCE-MRI parameter maps displayed a good ability in glioma grading. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1099-1111. © 2017 International Society for Magnetic Resonance in Medicine.

Entanglement entropy and the Fermi surface.

PubMed

Swingle, Brian

2010-07-30

Free fermions with a finite Fermi surface are known to exhibit an anomalously large entanglement entropy. The leading contribution to the entanglement entropy of a region of linear size L in d spatial dimensions is S∼L(d-1)logL, a result that should be contrasted with the usual boundary law S∼L(d-1). This term depends only on the geometry of the Fermi surface and on the boundary of the region in question. I give an intuitive account of this anomalous scaling based on a low energy description of the Fermi surface as a collection of one-dimensional gapless modes. Using this picture, I predict a violation of the boundary law in a number of other strongly correlated systems.

Some calculable contributions to entanglement entropy.

PubMed

Hertzberg, Mark P; Wilczek, Frank

2011-02-04

Entanglement entropy appears as a central property of quantum systems in broad areas of physics. However, its precise value is often sensitive to unknown microphysics, rendering it incalculable. By considering parametric dependence on correlation length, we extract finite, calculable contributions to the entanglement entropy for a scalar field between the interior and exterior of a spatial domain of arbitrary shape. The leading term is proportional to the area of the dividing boundary; we also extract finite subleading contributions for a field defined in the bulk interior of a waveguide in 3+1 dimensions, including terms proportional to the waveguide's cross-sectional geometry: its area, perimeter length, and integrated curvature. We also consider related quantities at criticality and suggest a class of systems for which these contributions might be measurable.

Computer program for calculation of real gas turbulent boundary layers with variable edge entropy

NASA Technical Reports Server (NTRS)

Boney, L. R.

1974-01-01

A user's manual for a computer program which calculates real gas turbulent boundary layers with variable edge entropy on a blunt cone or flat plate at zero angle of attack is presented. An integral method is used. The method includes the effect of real gas in thermodynamic equilibrium and variable edge entropy. A modified Crocco enthalpy velocity relationship is used for the enthalpy profiles and an empirical correlation of the N-power law profile is used for the velocity profile. The skin-friction-coefficient expressions of Spalding and Chi and Van Driest are used in the solution of the momentum equation and in the heat-transfer predictions that use several modified forms of Reynolds analogy.

Quantum Liouville theory and BTZ black hole entropy

NASA Astrophysics Data System (ADS)

Chen, Yujun

In this thesis I give an explicit conformal field theory description of (2+1)-dimensional BTZ black hole entropy. In the boundary Liouville field theory I investigate the reducible Verma modules in the elliptic sector, which correspond to certain irreducible representations of the quantum algebra Uq(sl2) ⊙ Uq̂(sl2). I show that there are states that decouple from these reducible Verma modules in a similar fashion to the decoupling of null states in minimal models. Because of the nonstandard form of the Ward identity for the two-point correlation functions in quantum Liouville field theory, these decoupling states have positive-definite norms. The unitary representations built on these decoupling states give the Bekenstein-Hawking entropy of the BTZ black hole.

Diverse nucleotide compositions and sequence fluctuation in Rubisco protein genes

NASA Astrophysics Data System (ADS)

Holden, Todd; Dehipawala, S.; Cheung, E.; Bienaime, R.; Ye, J.; Tremberger, G., Jr.; Schneider, P.; Lieberman, D.; Cheung, T.

2011-10-01

The Rubisco protein-enzyme is arguably the most abundance protein on Earth. The biology dogma of transcription and translation necessitates the study of the Rubisco genes and Rubisco-like genes in various species. Stronger correlation of fractal dimension of the atomic number fluctuation along a DNA sequence with Shannon entropy has been observed in the studied Rubisco-like gene sequences, suggesting a more diverse evolutionary pressure and constraints in the Rubisco sequences. The strategy of using metal for structural stabilization appears to be an ancient mechanism, with data from the porphobilinogen deaminase gene in Capsaspora owczarzaki and Monosiga brevicollis. Using the chi-square distance probability, our analysis supports the conjecture that the more ancient Rubisco-like sequence in Microcystis aeruginosa would have experienced very different evolutionary pressure and bio-chemical constraint as compared to Bordetella bronchiseptica, the two microbes occupying either end of the correlation graph. Our exploratory study would indicate that high fractal dimension Rubisco sequence would support high carbon dioxide rate via the Michaelis- Menten coefficient; with implication for the control of the whooping cough pathogen Bordetella bronchiseptica, a microbe containing a high fractal dimension Rubisco-like sequence (2.07). Using the internal comparison of chi-square distance probability for 16S rRNA (~ E-22) versus radiation repair Rec-A gene (~ E-05) in high GC content Deinococcus radiodurans, our analysis supports the conjecture that high GC content microbes containing Rubisco-like sequence are likely to include an extra-terrestrial origin, relative to Deinococcus radiodurans. Similar photosynthesis process that could utilize host star radiation would not compete with radiation resistant process from the biology dogma perspective in environments such as Mars and exoplanets.

Nonequilibrium Thermodynamics in Biological Systems

NASA Astrophysics Data System (ADS)

Aoki, I.

2005-12-01

1. Respiration Oxygen-uptake by respiration in organisms decomposes macromolecules such as carbohydrate, protein and lipid and liberates chemical energy of high quality, which is then used to chemical reactions and motions of matter in organisms to support lively order in structure and function in organisms. Finally, this chemical energy becomes heat energy of low quality and is discarded to the outside (dissipation function). Accompanying this heat energy, entropy production which inevitably occurs by irreversibility also is discarded to the outside. Dissipation function and entropy production are estimated from data of respiration. 2. Human body From the observed data of respiration (oxygen absorption), the entropy production in human body can be estimated. Entropy production from 0 to 75 years old human has been obtained, and extrapolated to fertilized egg (beginning of human life) and to 120 years old (maximum period of human life). Entropy production show characteristic behavior in human life span : early rapid increase in short growing phase and later slow decrease in long aging phase. It is proposed that this tendency is ubiquitous and constitutes a Principle of Organization in complex biotic systems. 3. Ecological communities From the data of respiration of eighteen aquatic communities, specific (i.e. per biomass) entropy productions are obtained. They show two phase character with respect to trophic diversity : early increase and later decrease with the increase of trophic diversity. The trophic diversity in these aquatic ecosystems is shown to be positively correlated with the degree of eutrophication, and the degree of eutrophication is an "arrow of time" in the hierarchy of aquatic ecosystems. Hence specific entropy production has the two phase: early increase and later decrease with time. 4. Entropy principle for living systems The Second Law of Thermodynamics has been expressed as follows. 1) In isolated systems, entropy increases with time and approaches to a maximum value. This is well-known classical Clausius principle. 2) In open systems near equilibrium entropy production always decreases with time approaching a minimum stationary level. This is the minimum entropy production principle by Prigogine. These two principle are established ones. However, living systems are not isolated and not near to equilibrium. Hence, these two principles can not be applied to living systems. What is entropy principle for living systems? Answer: Entropy production in living systems consists of multi-stages with time: early increasing, later decreasing and/or intermediate stages. This tendency is supported by various living systems.

Quantum Entanglement Growth under Random Unitary Dynamics

NASA Astrophysics Data System (ADS)

Nahum, Adam; Ruhman, Jonathan; Vijay, Sagar; Haah, Jeongwan

2017-07-01

Characterizing how entanglement grows with time in a many-body system, for example, after a quantum quench, is a key problem in nonequilibrium quantum physics. We study this problem for the case of random unitary dynamics, representing either Hamiltonian evolution with time-dependent noise or evolution by a random quantum circuit. Our results reveal a universal structure behind noisy entanglement growth, and also provide simple new heuristics for the "entanglement tsunami" in Hamiltonian systems without noise. In 1D, we show that noise causes the entanglement entropy across a cut to grow according to the celebrated Kardar-Parisi-Zhang (KPZ) equation. The mean entanglement grows linearly in time, while fluctuations grow like (time )1/3 and are spatially correlated over a distance ∝(time )2/3. We derive KPZ universal behavior in three complementary ways, by mapping random entanglement growth to (i) a stochastic model of a growing surface, (ii) a "minimal cut" picture, reminiscent of the Ryu-Takayanagi formula in holography, and (iii) a hydrodynamic problem involving the dynamical spreading of operators. We demonstrate KPZ universality in 1D numerically using simulations of random unitary circuits. Importantly, the leading-order time dependence of the entropy is deterministic even in the presence of noise, allowing us to propose a simple coarse grained minimal cut picture for the entanglement growth of generic Hamiltonians, even without noise, in arbitrary dimensionality. We clarify the meaning of the "velocity" of entanglement growth in the 1D entanglement tsunami. We show that in higher dimensions, noisy entanglement evolution maps to the well-studied problem of pinning of a membrane or domain wall by disorder.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burke, K.; Smith, J. C.; Grabowski, P. E.

Universal exact conditions guided the construction of most ground-state density functional approximations in use today. Here, we derive the relation between the entropy and Mermin free energy density functionals for thermal density functional theory. Both the entropy and sum of kinetic and electron-electron repulsion functionals are shown to be monotonically increasing with temperature, while the Mermin functional is concave downwards. Analogous relations are found for both exchange and correlation. The importance of these conditions is illustrated in two extremes: the Hubbard dimer and the uniform gas.

Solubility and dissolution thermodynamics of tetranitroglycoluril in organic solvents at 295-318 K

NASA Astrophysics Data System (ADS)

Zheng, Zhihua; Wang, Jianlong; Hu, Zhiyan; Du, Hongbin

2017-08-01

The solubility data of tetranitroglycoluril in acetone, methanol, ethanol, ethyl acetate, nitromethane and chloroform at temperatures ranging from 295-318 K were measured by gravimetric method. The solubility data of tetranitroglycoluril were fitted with Apelblat semiempirical equation. The dissolution enthalpy, entropy and Gibbs energy of tetranitroglycoluril were calculated using the Van't Hoff and Gibbs equations. The results showed that the Apelblat semiempirical equation was significantly correlated with solubility data. The dissolving process was endothermic, entropy-driven, and nonspontaneous.

Cell-model prediction of the melting of a Lennard-Jones solid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holian, B.L.

The classical free energy of the Lennard-Jones 6-12 solid is computed from a single-particle anharmonic cell model with a correction to the entropy given by the classical correlational entropy of quasiharmonic lattice dynamics. The free energy of the fluid is obtained from the Hansen-Ree analytic fit to Monte Carlo equation-of-state calculations. The resulting predictions of the solid-fluid coexistence curves by this corrected cell model of the solid are in excellent agreement with the computer experiments.

REMARKS ON THE MAXIMUM ENTROPY METHOD APPLIED TO FINITE TEMPERATURE LATTICE QCD.

DOE Office of Scientific and Technical Information (OSTI.GOV)

UMEDA, T.; MATSUFURU, H.

2005-07-25

We make remarks on the Maximum Entropy Method (MEM) for studies of the spectral function of hadronic correlators in finite temperature lattice QCD. We discuss the virtues and subtlety of MEM in the cases that one does not have enough number of data points such as at finite temperature. Taking these points into account, we suggest several tests which one should examine to keep the reliability for the results, and also apply them using mock and lattice QCD data.

Detection of the Vibration Signal from Human Vocal Folds Using a 94-GHz Millimeter-Wave Radar

PubMed Central

Chen, Fuming; Li, Sheng; Zhang, Yang; Wang, Jianqi

2017-01-01

The detection of the vibration signal from human vocal folds provides essential information for studying human phonation and diagnosing voice disorders. Doppler radar technology has enabled the noncontact measurement of the human-vocal-fold vibration. However, existing systems must be placed in close proximity to the human throat and detailed information may be lost because of the low operating frequency. In this paper, a long-distance detection method, involving the use of a 94-GHz millimeter-wave radar sensor, is proposed for detecting the vibration signals from human vocal folds. An algorithm that combines empirical mode decomposition (EMD) and the auto-correlation function (ACF) method is proposed for detecting the signal. First, the EMD method is employed to suppress the noise of the radar-detected signal. Further, the ratio of the energy and entropy is used to detect voice activity in the radar-detected signal, following which, a short-time ACF is employed to extract the vibration signal of the human vocal folds from the processed signal. For validating the method and assessing the performance of the radar system, a vibration measurement sensor and microphone system are additionally employed for comparison. The experimental results obtained from the spectrograms, the vibration frequency of the vocal folds, and coherence analysis demonstrate that the proposed method can effectively detect the vibration of human vocal folds from a long detection distance. PMID:28282892

Demonstration and resolution of the Gibbs paradox of the first kind

NASA Astrophysics Data System (ADS)

Peters, Hjalmar

2014-01-01

The Gibbs paradox of the first kind (GP1) refers to the false increase in entropy which, in statistical mechanics, is calculated from the process of combining two gas systems S1 and S2 consisting of distinguishable particles. Presented in a somewhat modified form, the GP1 manifests as a contradiction to the second law of thermodynamics. Contrary to popular belief, this contradiction affects not only classical but also quantum statistical mechanics. This paper resolves the GP1 by considering two effects. (i) The uncertainty about which particles are located in S1 and which in S2 contributes to the entropies of S1 and S2. (ii) S1 and S2 are correlated by the fact that if a certain particle is located in one system, it cannot be located in the other. As a consequence, the entropy of the total system consisting of S1 and S2 is not the sum of the entropies of S1 and S2.

Entanglement Entropy of the Six-Dimensional Horowitz-Strominger Black Hole

NASA Astrophysics Data System (ADS)

Li, Huai-Fan; Zhang, Sheng-Li; Wu, Yue-Qin; Ren, Zhao

By using the entanglement entropy method, the statistical entropy of the Bose and Fermi fields in a thin film is calculated and the Bekenstein-Hawking entropy of six-dimensional Horowitz-Strominger black hole is obtained. Here, the Bose and Fermi fields are entangled with the quantum states in six-dimensional Horowitz-Strominger black hole and the fields are outside of the horizon. The divergence of brick-wall model is avoided without any cutoff by the new equation of state density obtained with the generalized uncertainty principle. The calculation implies that the high density quantum states near the event horizon are strongly correlated with the quantum states in black hole. The black hole entropy is a quantum effect. It is an intrinsic characteristic of space-time. The ultraviolet cutoff in the brick-wall model is unreasonable. The generalized uncertainty principle should be considered in the high energy quantum field near the event horizon. Using the quantum statistical method, we directly calculate the partition function of the Bose and Fermi fields under the background of the six-dimensional black hole. The difficulty in solving the wave equations of various particles is overcome.

The coupling analysis between stock market indices based on permutation measures

NASA Astrophysics Data System (ADS)

Shi, Wenbin; Shang, Pengjian; Xia, Jianan; Yeh, Chien-Hung

2016-04-01

Many information-theoretic methods have been proposed for analyzing the coupling dependence between time series. And it is significant to quantify the correlation relationship between financial sequences since the financial market is a complex evolved dynamic system. Recently, we developed a new permutation-based entropy, called cross-permutation entropy (CPE), to detect the coupling structures between two synchronous time series. In this paper, we extend the CPE method to weighted cross-permutation entropy (WCPE), to address some of CPE's limitations, mainly its inability to differentiate between distinct patterns of a certain motif and the sensitivity of patterns close to the noise floor. It shows more stable and reliable results than CPE does when applied it to spiky data and AR(1) processes. Besides, we adapt the CPE method to infer the complexity of short-length time series by freely changing the time delay, and test it with Gaussian random series and random walks. The modified method shows the advantages in reducing deviations of entropy estimation compared with the conventional one. Finally, the weighted cross-permutation entropy of eight important stock indices from the world financial markets is investigated, and some useful and interesting empirical results are obtained.

Entangled de Sitter from stringy axionic Bell pair I: an analysis using Bunch-Davies vacuum

NASA Astrophysics Data System (ADS)

Choudhury, Sayantan; Panda, Sudhakar

2018-01-01

In this work, we study the quantum entanglement and compute entanglement entropy in de Sitter space for a bipartite quantum field theory driven by an axion originating from Type IIB string compactification on a Calabi-Yau three fold (CY^3) and in the presence of an NS5 brane. For this computation, we consider a spherical surface S^2, which divides the spatial slice of de Sitter (dS_4) into exterior and interior sub-regions. We also consider the initial choice of vacuum to be Bunch-Davies state. First we derive the solution of the wave function of the axion in a hyperbolic open chart by constructing a suitable basis for Bunch-Davies vacuum state using Bogoliubov transformation. We then derive the expression for density matrix by tracing over the exterior region. This allows us to compute the entanglement entropy and Rényi entropy in 3+1 dimension. Furthermore, we quantify the UV-finite contribution of the entanglement entropy which contain the physics of long range quantum correlations of our expanding universe. Finally, our analysis complements the necessary condition for generating non-vanishing entanglement entropy in primordial cosmology due to the axion.

Entropy of balance - some recent results

PubMed Central

2010-01-01

Background Entropy when applied to biological signals is expected to reflect the state of the biological system. However the physiological interpretation of the entropy is not always straightforward. When should high entropy be interpreted as a healthy sign, and when as marker of deteriorating health? We address this question for the particular case of human standing balance and the Center of Pressure data. Methods We have measured and analyzed balance data of 136 participants (young, n = 45; elderly, n = 91) comprising in all 1085 trials, and calculated the Sample Entropy (SampEn) for medio-lateral (M/L) and anterior-posterior (A/P) Center of Pressure (COP) together with the Hurst self-similariy (ss) exponent α using Detrended Fluctuation Analysis (DFA). The COP was measured with a force plate in eight 30 seconds trials with eyes closed, eyes open, foam, self-perturbation and nudge conditions. Results 1) There is a significant difference in SampEn for the A/P-direction between the elderly and the younger groups Old > young. 2) For the elderly we have in general A/P > M/L. 3) For the younger group there was no significant A/P-M/L difference with the exception for the nudge trials where we had the reverse situation, A/P < M/L. 4) For the elderly we have, Eyes Closed > Eyes Open. 5) In case of the Hurst ss-exponent we have for the elderly, M/L > A/P. Conclusions These results seem to be require some modifications of the more or less established attention-constraint interpretation of entropy. This holds that higher entropy correlates with a more automatic and a less constrained mode of balance control, and that a higher entropy reflects, in this sense, a more efficient balancing. PMID:20670457

Entropic Imaging of Cataract Lens: An In Vitro Study

PubMed Central

Shung, K. Kirk; Tsui, Po-Hsiang; Fang, Jui; Ma, Hsiang-Yang; Wu, Shuicai; Lin, Chung-Chih

2014-01-01

Phacoemulsification is a common surgical method for treating advanced cataracts. Determining the optimal phacoemulsification energy depends on the hardness of the lens involved. Previous studies have shown that it is possible to evaluate lens hardness via ultrasound parametric imaging based on statistical models that require data to follow a specific distribution. To make the method more system-adaptive, nonmodel-based imaging approach may be necessary in the visualization of lens hardness. This study investigated the feasibility of applying an information theory derived parameter – Shannon entropy from ultrasound backscatter to quantify lens hardness. To determine the physical significance of entropy, we performed computer simulations to investigate the relationship between the signal-to-noise ratio (SNR) based on the Rayleigh distribution and Shannon entropy. Young's modulus was measured in porcine lenses, in which cataracts had been artificially induced by the immersion in formalin solution in vitro. A 35-MHz ultrasound transducer was used to scan the cataract lenses for entropy imaging. The results showed that the entropy is 4.8 when the backscatter data form a Rayleigh distribution corresponding to an SNR of 1.91. The Young's modulus of the lens increased from approximately 8 to 100 kPa when we increased the immersion time from 40 to 160 min (correlation coefficient r = 0.99). Furthermore, the results indicated that entropy imaging seemed to facilitate visualizing different degrees of lens hardening. The mean entropy value increased from 2.7 to 4.0 as the Young's modulus increased from 8 to 100 kPa (r = 0.85), suggesting that entropy imaging may have greater potential than that of conventional statistical parametric imaging in determining the optimal energy to apply during phacoemulsification. PMID:24760103

Quantification of correlations in quantum many-particle systems.

PubMed

Byczuk, Krzysztof; Kuneš, Jan; Hofstetter, Walter; Vollhardt, Dieter

2012-02-24

We introduce a well-defined and unbiased measure of the strength of correlations in quantum many-particle systems which is based on the relative von Neumann entropy computed from the density operator of correlated and uncorrelated states. The usefulness of this general concept is demonstrated by quantifying correlations of interacting electrons in the Hubbard model and in a series of transition-metal oxides using dynamical mean-field theory.

Entanglement entropy for the long-range Ising chain in a transverse field.

PubMed

Koffel, Thomas; Lewenstein, M; Tagliacozzo, Luca

2012-12-28

We consider the Ising model in a transverse field with long-range antiferromagnetic interactions that decay as a power law with their distance. We study both the phase diagram and the entanglement properties as a function of the exponent of the interaction. The phase diagram can be used as a guide for future experiments with trapped ions. We find two gapped phases, one dominated by the transverse field, exhibiting quasi-long-range order, and one dominated by the long-range interaction, with long-range Néel ordered ground states. We determine the location of the quantum critical points separating those two phases. We determine their critical exponents and central charges. In the phase with quasi-long-range order the ground states exhibit exotic corrections to the area law for the entanglement entropy coexisting with gapped entanglement spectra.

Digital focusing of OCT images based on scalar diffraction theory and information entropy.

PubMed

Liu, Guozhong; Zhi, Zhongwei; Wang, Ruikang K

2012-11-01

This paper describes a digital method that is capable of automatically focusing optical coherence tomography (OCT) en face images without prior knowledge of the point spread function of the imaging system. The method utilizes a scalar diffraction model to simulate wave propagation from out-of-focus scatter to the focal plane, from which the propagation distance between the out-of-focus plane and the focal plane is determined automatically via an image-definition-evaluation criterion based on information entropy theory. By use of the proposed approach, we demonstrate that the lateral resolution close to that at the focal plane can be recovered from the imaging planes outside the depth of field region with minimal loss of resolution. Fresh onion tissues and mouse fat tissues are used in the experiments to show the performance of the proposed method.

Colorectal Cancer and Colitis Diagnosis Using Fourier Transform Infrared Spectroscopy and an Improved K-Nearest-Neighbour Classifier.

PubMed

Li, Qingbo; Hao, Can; Kang, Xue; Zhang, Jialin; Sun, Xuejun; Wang, Wenbo; Zeng, Haishan

2017-11-27

Combining Fourier transform infrared spectroscopy (FTIR) with endoscopy, it is expected that noninvasive, rapid detection of colorectal cancer can be performed in vivo in the future. In this study, Fourier transform infrared spectra were collected from 88 endoscopic biopsy colorectal tissue samples (41 colitis and 47 cancers). A new method, viz., entropy weight local-hyperplane k-nearest-neighbor (EWHK), which is an improved version of K-local hyperplane distance nearest-neighbor (HKNN), is proposed for tissue classification. In order to avoid limiting high dimensions and small values of the nearest neighbor, the new EWHK method calculates feature weights based on information entropy. The average results of the random classification showed that the EWHK classifier for differentiating cancer from colitis samples produced a sensitivity of 81.38% and a specificity of 92.69%.

On the Origin of Time and the Universe

NASA Astrophysics Data System (ADS)

Jejjala, Vishnu; Kavic, Michael; Minic, Djordje; Tze, Chia-Hsiung

We present a novel solution to the low entropy and arrow of time puzzles of the initial state of the universe. Our approach derives from the physics of a specific generalization of Matrix theory put forth in earlier work as the basis for a quantum theory of gravity. The particular dynamical state space of this theory, the infinite-dimensional analogue of the Fubini-Study metric over a complex nonlinear Grassmannian, has recently been studied by Michor and Mumford. The geodesic distance between any two points on this space is zero. Here we show that this mathematical result translates to a description of a hot, zero entropy state and an arrow of time after the Big Bang. This is modeled as a far from equilibrium, large fluctuation driven, "freezing by heating" metastable ordered phase transition of a nonlinear dissipative dynamical system.

Entropy-scaling laws for diffusion coefficients in liquid metals under high pressures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao, Qi-Long, E-mail: qlcao@mail.ustc.edu.cn; Shao, Ju-Xiang; Wang, Fan-Hou, E-mail: eatonch@gmail.com

2015-04-07

Molecular dynamic simulations on the liquid copper and tungsten are used to investigate the empirical entropy-scaling laws D{sup *}=A exp(BS{sub ex}), proposed independently by Rosenfeld and Dzugutov for diffusion coefficient, under high pressure conditions. We show that the scaling laws hold rather well for them under high pressure conditions. Furthermore, both the original diffusion coefficients and the reduced diffusion coefficients exhibit an Arrhenius relationship D{sub M}=D{sub M}{sup 0} exp(−E{sub M}/K{sub B}T), (M=un,R,D) and the activation energy E{sub M} increases with increasing pressure, the diffusion pre-exponential factors (D{sub R}{sup 0} and D{sub D}{sup 0}) are nearly independent of the pressure and element. Themore » pair correlation entropy, S{sub 2}, depends linearly on the reciprocal temperature S{sub 2}=−E{sub S}/T, and the activation energy, E{sub S}, increases with increasing pressure. In particular, the ratios of the activation energies (E{sub un}, E{sub R}, and E{sub D}) obtained from diffusion coefficients to the activation energy, E{sub S}, obtained from the entropy keep constants in the whole pressure range. Therefore, the entropy-scaling laws for the diffusion coefficients and the Arrhenius law are linked via the temperature dependence of entropy.« less

Quantitative image variables reflect the intratumoral pathologic heterogeneity of lung adenocarcinoma.

PubMed

Choi, E-Ryung; Lee, Ho Yun; Jeong, Ji Yun; Choi, Yoon-La; Kim, Jhingook; Bae, Jungmin; Lee, Kyung Soo; Shim, Young Mog

2016-10-11

We aimed to compare quantitative radiomic parameters from dual-energy computed tomography (DECT) of lung adenocarcinoma and pathologic complexity.A total 89 tumors with clinical stage I/II lung adenocarcinoma were prospectively included. Fifty one radiomic features were assessed both from iodine images and non-contrast images of DECT datasets. Comprehensive histologic subtyping was evaluated with all surgically resected tumors. The degree of pathologic heterogeneity was assessed using pathologic index and the number of mixture histologic subtypes in a tumor. Radiomic parameters were correlated with pathologic index. Tumors were classified as three groups according to the number of mixture histologic subtypes and radiomic parameters were compared between the three groups.Tumor density and 50th through 97.5th percentile Hounsfield units (HU) of histogram on non-contrast images showed strong correlation with the pathologic heterogeneity. Radiomic parameters including 75th and 97.5th percentile HU of histogram, entropy, and inertia on 1-, 2- and 3 voxel distance on non-contrast images showed incremental changes while homogeneity showed detrimental change according to the number of mixture histologic subtypes (all Ps < 0.05).Radiomic variables from DECT of lung adenocarcinoma reflect pathologic intratumoral heterogeneity, which may help in the prediction of intratumoral heterogeneity of the whole tumor.

Entropy: A new measure of stock market volatility?

NASA Astrophysics Data System (ADS)

Bentes, Sonia R.; Menezes, Rui

2012-11-01

When uncertainty dominates understanding stock market volatility is vital. There are a number of reasons for that. On one hand, substantial changes in volatility of financial market returns are capable of having significant negative effects on risk averse investors. In addition, such changes can also impact on consumption patterns, corporate capital investment decisions and macroeconomic variables. Arguably, volatility is one of the most important concepts in the whole finance theory. In the traditional approach this phenomenon has been addressed based on the concept of standard-deviation (or variance) from which all the famous ARCH type models - Autoregressive Conditional Heteroskedasticity Models- depart. In this context, volatility is often used to describe dispersion from an expected value, price or model. The variability of traded prices from their sample mean is only an example. Although as a measure of uncertainty and risk standard-deviation is very popular since it is simple and easy to calculate it has long been recognized that it is not fully satisfactory. The main reason for that lies in the fact that it is severely affected by extreme values. This may suggest that this is not a closed issue. Bearing on the above we might conclude that many other questions might arise while addressing this subject. One of outstanding importance, from which more sophisticated analysis can be carried out, is how to evaluate volatility, after all? If the standard-deviation has some drawbacks shall we still rely on it? Shall we look for an alternative measure? In searching for this shall we consider the insight of other domains of knowledge? In this paper we specifically address if the concept of entropy, originally developed in physics by Clausius in the XIX century, which can constitute an effective alternative. Basically, what we try to understand is, which are the potentialities of entropy compared to the standard deviation. But why entropy? The answer lies on the fact that there is already some research on the domain of Econophysics, which points out that as a measure of disorder, distance from equilibrium or even ignorance, entropy might present some advantages. However another question arises: since there is several measures of entropy which one since there are several measures of entropy, which one shall be used? As a starting point we discuss the potentialities of Shannon entropy and Tsallis entropy. The main difference between them is that both Renyi and Tsallis are adequate for anomalous systems while Shannon has revealed optimal for equilibrium systems.

Concepts in receptor optimization: targeting the RGD peptide.

PubMed

Chen, Wei; Chang, Chia-en; Gilson, Michael K

2006-04-12

Synthetic receptors have a wide range of potential applications, but it has been difficult to design low molecular weight receptors that bind ligands with high, "proteinlike" affinities. This study uses novel computational methods to understand why it is hard to design a high-affinity receptor and to explore the limits of affinity, with the bioactive peptide RGD as a model ligand. The M2 modeling method is found to yield excellent agreement with experiment for a known RGD receptor and then is used to analyze a series of receptors generated in silico with a de novo design algorithm. Forces driving binding are found to be systematically opposed by proportionate repulsions due to desolvation and entropy. In particular, strong correlations are found between Coulombic attractions and the electrostatic desolvation penalty and between the mean energy change on binding and the cost in configurational entropy. These correlations help explain why it is hard to achieve high affinity. The change in surface area upon binding is found to correlate poorly with affinity within this series. Measures of receptor efficiency are formulated that summarize how effectively a receptor uses surface area, total energy, and Coulombic energy to achieve affinity. Analysis of the computed efficiencies suggests that a low molecular weight receptor can achieve proteinlike affinity. It is also found that macrocyclization of a receptor can, unexpectedly, increase the entropy cost of binding because the macrocyclic structure further restricts ligand motion.

Clustering of neural code words revealed by a first-order phase transition

NASA Astrophysics Data System (ADS)

Huang, Haiping; Toyoizumi, Taro

2016-06-01

A network of neurons in the central nervous system collectively represents information by its spiking activity states. Typically observed states, i.e., code words, occupy only a limited portion of the state space due to constraints imposed by network interactions. Geometrical organization of code words in the state space, critical for neural information processing, is poorly understood due to its high dimensionality. Here, we explore the organization of neural code words using retinal data by computing the entropy of code words as a function of Hamming distance from a particular reference codeword. Specifically, we report that the retinal code words in the state space are divided into multiple distinct clusters separated by entropy-gaps, and that this structure is shared with well-known associative memory networks in a recallable phase. Our analysis also elucidates a special nature of the all-silent state. The all-silent state is surrounded by the densest cluster of code words and located within a reachable distance from most code words. This code-word space structure quantitatively predicts typical deviation of a state-trajectory from its initial state. Altogether, our findings reveal a non-trivial heterogeneous structure of the code-word space that shapes information representation in a biological network.

Bayesian Maximum Entropy space/time estimation of surface water chloride in Maryland using river distances.

PubMed

Jat, Prahlad; Serre, Marc L

2016-12-01

Widespread contamination of surface water chloride is an emerging environmental concern. Consequently accurate and cost-effective methods are needed to estimate chloride along all river miles of potentially contaminated watersheds. Here we introduce a Bayesian Maximum Entropy (BME) space/time geostatistical estimation framework that uses river distances, and we compare it with Euclidean BME to estimate surface water chloride from 2005 to 2014 in the Gunpowder-Patapsco, Severn, and Patuxent subbasins in Maryland. River BME improves the cross-validation R 2 by 23.67% over Euclidean BME, and river BME maps are significantly different than Euclidean BME maps, indicating that it is important to use river BME maps to assess water quality impairment. The river BME maps of chloride concentration show wide contamination throughout Baltimore and Columbia-Ellicott cities, the disappearance of a clean buffer separating these two large urban areas, and the emergence of multiple localized pockets of contamination in surrounding areas. The number of impaired river miles increased by 0.55% per year in 2005-2009 and by 1.23% per year in 2011-2014, corresponding to a marked acceleration of the rate of impairment. Our results support the need for control measures and increased monitoring of unassessed river miles. Copyright © 2016. Published by Elsevier Ltd.

Texture descriptions of lunar surface derived from LOLA data: Kilometer-scale roughness and entropy maps

NASA Astrophysics Data System (ADS)

Li, Bo; Ling, Zongcheng; Zhang, Jiang; Chen, Jian; Wu, Zhongchen; Ni, Yuheng; Zhao, Haowei

2015-11-01

The lunar global texture maps of roughness and entropy are derived at kilometer scales from Digital Elevation Models (DEMs) data obtained by Lunar Orbiter Laser Altimeter (LOLA) aboard on Lunar Reconnaissance Orbiter (LRO) spacecraft. We use statistical moments of a gray-level histogram of elevations in a neighborhood to compute the roughness and entropy value. Our texture descriptors measurements are shown in global maps at multi-sized square neighborhoods, whose length of side is 3, 5, 10, 20, 40 and 80 pixels, respectively. We found that large-scale topographical changes can only be displayed in maps with longer side of neighborhood, but the small scale global texture maps are more disorderly and unsystematic because of more complicated textures' details. Then, the frequency curves of texture maps are made out, whose shapes and distributions are changing as the spatial scales increases. Entropy frequency curve with minimum 3-pixel scale has large fluctuations and six peaks. According to this entropy curve we can classify lunar surface into maria, highlands, different parts of craters preliminarily. The most obvious textures in the middle-scale roughness and entropy maps are the two typical morphological units, smooth maria and rough highlands. For the impact crater, its roughness and entropy value are characterized by a multiple-ring structure obviously, and its different parts have different texture results. In the last, we made a 2D scatter plot between the two texture results of typical lunar maria and highlands. There are two clusters with largest dot density which are corresponded to the lunar highlands and maria separately. In the lunar mare regions (cluster A), there is a high correlation between roughness and entropy, but in the highlands (Cluster B), the entropy shows little change. This could be subjected to different geological processes of maria and highlands forming different landforms.

Nonextensivity in a Dark Maximum Entropy Landscape

NASA Astrophysics Data System (ADS)

Leubner, M. P.

2011-03-01

Nonextensive statistics along with network science, an emerging branch of graph theory, are increasingly recognized as potential interdisciplinary frameworks whenever systems are subject to long-range interactions and memory. Such settings are characterized by non-local interactions evolving in a non-Euclidean fractal/multi-fractal space-time making their behavior nonextensive. After summarizing the theoretical foundations from first principles, along with a discussion of entropy bifurcation and duality in nonextensive systems, we focus on selected significant astrophysical consequences. Those include the gravitational equilibria of dark matter (DM) and hot gas in clustered structures, the dark energy(DE) negative pressure landscape governed by the highest degree of mutual correlations and the hierarchy of discrete cosmic structure scales, available upon extremizing the generalized nonextensive link entropy in a homogeneous growing network.

An investigation of combustion and entropy noise

NASA Technical Reports Server (NTRS)

Strahle, W. C.

1977-01-01

The relative importance of entropy and direct combustion noise in turbopropulsion systems and the parameters upon which these noise sources depend were studied. Theory and experiment were employed to determine that at least with the apparatus used here, entropy noise can dominate combustion noise if there is a sufficient pressure gradient terminating the combustor. Measurements included combustor interior fluctuating pressure, near and far field fluctuating pressure, and combustor exit plane fluctuating temperatures, as well as mean pressures and temperatures. Analysis techniques included spectral, cross-correlation, cross power spectra, and ordinary and partial coherence analysis. Also conducted were combustor liner modification experiments to investigate the origin of the frequency content of combustion noise. Techniques were developed to extract nonpropagational pseudo-sound and the heat release fluctuation spectra from the data.

Study of the cross-market effects of Brexit based on the improved symbolic transfer entropy GARCH model—An empirical analysis of stock–bond correlations

PubMed Central

Chen, Xiurong; Zhao, Rubo

2017-01-01

In this paper, we study the cross-market effects of Brexit on the stock and bond markets of nine major countries in the world. By incorporating information theory, we introduce the time-varying impact weights based on symbolic transfer entropy to improve the traditional GARCH model. The empirical results show that under the influence of Brexit, flight-to-quality not only commonly occurs between the stocks and bonds of each country but also simultaneously occurs among different countries. We also find that the accuracy of the time-varying symbolic transfer entropy GARCH model proposed in this paper has been improved compared to the traditional GARCH model, which indicates that it has a certain practical application value. PMID:28817712

Application of Tsallis Entropy to EEG: Quantifying the Presence of Burst Suppression After Asphyxial Cardiac Arrest in Rats

PubMed Central

Zhang, Dandan; Jia, Xiaofeng; Ding, Haiyan; Ye, Datian; Thakor, Nitish V.

2011-01-01

Burst suppression (BS) activity in EEG is clinically accepted as a marker of brain dysfunction or injury. Experimental studies in a rodent model of brain injury following asphyxial cardiac arrest (CA) show evidence of BS soon after resuscitation, appearing as a transitional recovery pattern between isoelectricity and continuous EEG. The EEG trends in such experiments suggest varying levels of uncertainty or randomness in the signals. To quantify the EEG data, Shannon entropy and Tsallis entropy (TsEn) are examined. More specifically, an entropy-based measure named TsEn area (TsEnA) is proposed to reveal the presence and the extent of development of BS following brain injury. The methodology of TsEnA and the selection of its parameter are elucidated in detail. To test the validity of this measure, 15 rats were subjected to 7 or 9 min of asphyxial CA. EEG recordings immediately after resuscitation from CA were investigated and characterized by TsEnA. The results show that TsEnA correlates well with the outcome assessed by evaluating the rodents after the experiments using a well-established neurological deficit score (Pearson correlation = 0.86, p ⪡ 0.01). This research shows that TsEnA reliably quantifies the complex dynamics in BS EEG, and may be useful as an experimental or clinical tool for objective estimation of the gravity of brain damage after CA. PMID:19695982

Novel sonar signal processing tool using Shannon entropy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quazi, A.H.

1996-06-01

Traditionally, conventional signal processing extracts information from sonar signals using amplitude, signal energy or frequency domain quantities obtained using spectral analysis techniques. The object is to investigate an alternate approach which is entirely different than that of traditional signal processing. This alternate approach is to utilize the Shannon entropy as a tool for the processing of sonar signals with emphasis on detection, classification, and localization leading to superior sonar system performance. Traditionally, sonar signals are processed coherently, semi-coherently, and incoherently, depending upon the a priori knowledge of the signals and noise. Here, the detection, classification, and localization technique will bemore » based on the concept of the entropy of the random process. Under a constant energy constraint, the entropy of a received process bearing finite number of sample points is maximum when hypothesis H{sub 0} (that the received process consists of noise alone) is true and decreases when correlated signal is present (H{sub 1}). Therefore, the strategy used for detection is: (I) Calculate the entropy of the received data; then, (II) compare the entropy with the maximum value; and, finally, (III) make decision: H{sub 1} is assumed if the difference is large compared to pre-assigned threshold and H{sub 0} is otherwise assumed. The test statistics will be different between entropies under H{sub 0} and H{sub 1}. Here, we shall show the simulated results for detecting stationary and non-stationary signals in noise, and results on detection of defects in a Plexiglas bar using an ultrasonic experiment conducted by Hughes. {copyright} {ital 1996 American Institute of Physics.}« less

Entropy–enthalpy transduction caused by conformational shifts can obscure the forces driving protein–ligand binding

PubMed Central

Fenley, Andrew T.; Muddana, Hari S.; Gilson, Michael K.

2012-01-01

Molecular dynamics simulations of unprecedented duration now can provide new insights into biomolecular mechanisms. Analysis of a 1-ms molecular dynamics simulation of the small protein bovine pancreatic trypsin inhibitor reveals that its main conformations have different thermodynamic profiles and that perturbation of a single geometric variable, such as a torsion angle or interresidue distance, can select for occupancy of one or another conformational state. These results establish the basis for a mechanism that we term entropy–enthalpy transduction (EET), in which the thermodynamic character of a local perturbation, such as enthalpic binding of a small molecule, is camouflaged by the thermodynamics of a global conformational change induced by the perturbation, such as a switch into a high-entropy conformational state. It is noted that EET could occur in many systems, making measured entropies and enthalpies of folding and binding unreliable indicators of actual thermodynamic driving forces. The same mechanism might also account for the high experimental variance of measured enthalpies and entropies relative to free energies in some calorimetric studies. Finally, EET may be the physical mechanism underlying many cases of entropy–enthalpy compensation. PMID:23150595

Statistical thermodynamics of amphiphile chains in micelles

PubMed Central

Ben-Shaul, A.; Szleifer, I.; Gelbart, W. M.

1984-01-01

The probability distribution of amphiphile chain conformations in micelles of different geometries is derived through maximization of their packing entropy. A lattice model, first suggested by Dill and Flory, is used to represent the possible chain conformations in the micellar core. The polar heads of the chains are assumed to be anchored to the micellar surface, with the other chain segments occupying all lattice sites in the interior of the micelle. This “volume-filling” requirement, the connectivity of the chains, and the geometry of the micelle define constraints on the possible probability distributions of chain conformations. The actual distribution is derived by maximizing the chain's entropy subject to these constraints; “reversals” of the chains back towards the micellar surface are explicitly included. Results are presented for amphiphiles organized in planar bilayers and in cylindrical and spherical micelles of different sizes. It is found that, for all three geometries, the bond order parameters decrease as a function of the bond distance from the polar head, in accordance with recent experimental data. The entropy differences associated with geometrical changes are shown to be significant, suggesting thereby the need to include curvature (environmental)-dependent “tail” contributions in statistical thermodynamic treatments of micellization. PMID:16593492

Propensity approach to nonequilibrium thermodynamics of a chemical reaction network: Controlling single E-coli β-galactosidase enzyme catalysis through the elementary reaction stepsa)

NASA Astrophysics Data System (ADS)

Das, Biswajit; Banerjee, Kinshuk; Gangopadhyay, Gautam

2013-12-01

In this work, we develop an approach to nonequilibrium thermodynamics of an open chemical reaction network in terms of the elementary reaction propensities. The method is akin to the microscopic formulation of the dissipation function in terms of the Kullback-Leibler distance of phase space trajectories in Hamiltonian system. The formalism is applied to a single oligomeric enzyme kinetics at chemiostatic condition that leads the reaction system to a nonequilibrium steady state, characterized by a positive total entropy production rate. Analytical expressions are derived, relating the individual reaction contributions towards the total entropy production rate with experimentally measurable reaction velocity. Taking a real case of Escherichia coli β-galactosidase enzyme obeying Michaelis-Menten kinetics, we thoroughly analyze the temporal as well as the steady state behavior of various thermodynamic quantities for each elementary reaction. This gives a useful insight in the relative magnitudes of various energy terms and the dissipated heat to sustain a steady state of the reaction system operating far-from-equilibrium. It is also observed that, the reaction is entropy-driven at low substrate concentration and becomes energy-driven as the substrate concentration rises.

Determinism, chaos, self-organization and entropy.

PubMed

Pontes, José

2016-01-01

We discuss two changes of paradigms that occurred in science along the XXth century: the end of the mechanist determinism, and the end of the apparent incompatibility between biology, where emergence of order is law, and physics, postulating a progressive loss of order in natural systems. We recognize today that three mechanisms play a major role in the building of order: the nonlinear nature of most evolution laws, along with distance to equilibrium, and with the new paradigm, that emerged in the last forty years, as we recognize that networks present collective order properties not found in the individual nodes. We also address the result presented by Blumenfeld (L.A. Blumenfeld, Problems of Biological Physics, Springer, Berlin, 1981) showing that entropy decreases resulting from building one of the most complex biological structures, the human being, are small and may be trivially compensated for compliance with thermodynamics. Life is made at the expense of very low thermodynamic cost, so thermodynamics does not pose major restrictions to the emergence of life. Besides, entropy does not capture our idea of order in biological systems. The above questions show that science is not free of confl icts and backlashes, often resulting from excessive extrapolations.

Calculation of the Intensity of Physical Time Fluctuations Using the Standard Solar Model and its Comparison with the Results of Experimental Measurements

NASA Astrophysics Data System (ADS)

Morozov, A. N.

2017-11-01

The article reviews the possibility of describing physical time as a random Poisson process. An equation allowing the intensity of physical time fluctuations to be calculated depending on the entropy production density within irreversible natural processes has been proposed. Based on the standard solar model the work calculates the entropy production density inside the Sun and the dependence of the intensity of physical time fluctuations on the distance to the centre of the Sun. A free model parameter has been established, and the method of its evaluation has been suggested. The calculations of the entropy production density inside the Sun showed that it differs by 2-3 orders of magnitude in different parts of the Sun. The intensity of physical time fluctuations on the Earth's surface depending on the entropy production density during the sunlight-to-Earth's thermal radiation conversion has been theoretically predicted. A method of evaluation of the Kullback's measure of voltage fluctuations in small amounts of electrolyte has been proposed. Using a simple model of the Earth's surface heat transfer to the upper atmosphere, the effective Earth's thermal radiation temperature has been determined. A comparison between the theoretical values of the Kullback's measure derived from the fluctuating physical time model and the experimentally measured values of this measure for two independent electrolytic cells showed a good qualitative and quantitative concurrence of predictions of both theoretical model and experimental data.

Entropy is conserved in Hawking radiation as tunneling: A revisit of the black hole information loss paradox

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang Baocheng; Graduate University of Chinese Academy of Sciences, Beijing 100049; Cai Qingyu, E-mail: qycai@wipm.ac.cn

2011-02-15

Research Highlights: > Information is found to be encoded and carried away by Hawking radiations. > Entropy is conserved in Hawking radiation. > We thus conclude no information is lost. > The dynamics of black hole may be unitary. - Abstract: We revisit in detail the paradox of black hole information loss due to Hawking radiation as tunneling. We compute the amount of information encoded in correlations among Hawking radiations for a variety of black holes, including the Schwarzchild black hole, the Reissner-Nordstroem black hole, the Kerr black hole, and the Kerr-Newman black hole. The special case of tunneling throughmore » a quantum horizon is also considered. Within a phenomenological treatment based on the accepted emission probability spectrum from a black hole, we find that information is leaked out hidden in the correlations of Hawking radiation. The recovery of this previously unaccounted for information helps to conserve the total entropy of a system composed of a black hole plus its radiations. We thus conclude, irrespective of the microscopic picture for black hole collapsing, the associated radiation process: Hawking radiation as tunneling, is consistent with unitarity as required by quantum mechanics.« less

Predicting the distribution pattern of small carnivores in response to environmental factors in the Western Ghats.

PubMed

Kalle, Riddhika; Ramesh, Tharmalingam; Qureshi, Qamar; Sankar, Kalyanasundaram

2013-01-01

Due to their secretive habits, predicting the pattern of spatial distribution of small carnivores has been typically challenging, yet for conservation management it is essential to understand the association between this group of animals and environmental factors. We applied maximum entropy modeling (MaxEnt) to build distribution models and identify environmental predictors including bioclimatic variables, forest and land cover type, topography, vegetation index and anthropogenic variables for six small carnivore species in Mudumalai Tiger Reserve. Species occurrence records were collated from camera-traps and vehicle transects during the years 2010 and 2011. We used the average training gain from forty model runs for each species to select the best set of predictors. The area under the curve (AUC) of the receiver operating characteristic plot (ROC) ranged from 0.81 to 0.93 for the training data and 0.72 to 0.87 for the test data. In habitat models for F. chaus, P. hermaphroditus, and H. smithii "distance to village" and precipitation of the warmest quarter emerged as some of the most important variables. "Distance to village" and aspect were important for V. indica while "distance to village" and precipitation of the coldest quarter were significant for H. vitticollis. "Distance to village", precipitation of the warmest quarter and land cover were influential variables in the distribution of H. edwardsii. The map of predicted probabilities of occurrence showed potentially suitable habitats accounting for 46 km(2) of the reserve for F. chaus, 62 km(2) for V. indica, 30 km(2) for P. hermaphroditus, 63 km(2) for H. vitticollis, 45 km(2) for H. smithii and 28 km(2) for H. edwardsii. Habitat heterogeneity driven by the east-west climatic gradient was correlated with the spatial distribution of small carnivores. This study exemplifies the usefulness of modeling small carnivore distribution to prioritize and direct conservation planning for habitat specialists in southern India.

Predicting the Distribution Pattern of Small Carnivores in Response to Environmental Factors in the Western Ghats

PubMed Central

Kalle, Riddhika; Ramesh, Tharmalingam; Qureshi, Qamar; Sankar, Kalyanasundaram

2013-01-01

Due to their secretive habits, predicting the pattern of spatial distribution of small carnivores has been typically challenging, yet for conservation management it is essential to understand the association between this group of animals and environmental factors. We applied maximum entropy modeling (MaxEnt) to build distribution models and identify environmental predictors including bioclimatic variables, forest and land cover type, topography, vegetation index and anthropogenic variables for six small carnivore species in Mudumalai Tiger Reserve. Species occurrence records were collated from camera-traps and vehicle transects during the years 2010 and 2011. We used the average training gain from forty model runs for each species to select the best set of predictors. The area under the curve (AUC) of the receiver operating characteristic plot (ROC) ranged from 0.81 to 0.93 for the training data and 0.72 to 0.87 for the test data. In habitat models for F. chaus, P. hermaphroditus, and H. smithii “distance to village” and precipitation of the warmest quarter emerged as some of the most important variables. “Distance to village” and aspect were important for V. indica while “distance to village” and precipitation of the coldest quarter were significant for H. vitticollis. “Distance to village”, precipitation of the warmest quarter and land cover were influential variables in the distribution of H. edwardsii. The map of predicted probabilities of occurrence showed potentially suitable habitats accounting for 46 km2 of the reserve for F. chaus, 62 km2 for V. indica, 30 km2 for P. hermaphroditus, 63 km2 for H. vitticollis, 45 km2 for H. smithii and 28 km2 for H. edwardsii. Habitat heterogeneity driven by the east-west climatic gradient was correlated with the spatial distribution of small carnivores. This study exemplifies the usefulness of modeling small carnivore distribution to prioritize and direct conservation planning for habitat specialists in southern India. PMID:24244470

Textural feature calculated from segmental fluences as a modulation index for VMAT.

PubMed

Park, So-Yeon; Park, Jong Min; Kim, Jung-In; Kim, Hyoungnyoun; Kim, Il Han; Ye, Sung-Joon

2015-12-01

Textural features calculated from various segmental fluences of volumetric modulated arc therapy (VMAT) plans were optimized to enhance its performance to predict plan delivery accuracy. Twenty prostate and twenty head and neck VMAT plans were selected retrospectively. Fluences were generated for each VMAT plan by summations of segments at sequential groups of control points. The numbers of summed segments were 5, 10, 20, 45, 90, 178 and 356. For each fluence, we investigated 6 textural features: angular second moment, inverse difference moment, contrast, variance, correlation and entropy (particular displacement distances, d = 1, 5 and 10). Spearman's rank correlation coefficients (rs) were calculated between each textural feature and several different measures of VMAT delivery accuracy. The values of rs of contrast (d = 10) with 10 segments to both global and local gamma passing rates with 2%/2 mm were 0.666 (p <0.001) and 0.573 (p <0.001), respectively. It showed rs values of -0.895 (p <0.001) and 0.727 (p <0.001) to multi-leaf collimator positional errors and gantry angle errors during delivery, respectively. The number of statistically significant rs values (p <0.05) to the changes in dose-volumetric parameters during delivery was 14 among a total of 35 tested parameters. Contrast (d = 10) with 10 segments showed higher correlations to the VMAT delivery accuracy than did the conventional modulation indices. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Quantum coherence and correlations in quantum system

PubMed Central

Xi, Zhengjun; Li, Yongming; Fan, Heng

2015-01-01

Criteria of measure quantifying quantum coherence, a unique property of quantum system, are proposed recently. In this paper, we first give an uncertainty-like expression relating the coherence and the entropy of quantum system. This finding allows us to discuss the relations between the entanglement and the coherence. Further, we discuss in detail the relations among the coherence, the discord and the deficit in the bipartite quantum system. We show that, the one-way quantum deficit is equal to the sum between quantum discord and the relative entropy of coherence of measured subsystem. PMID:26094795

On the deduction of chemical reaction pathways from measurements of time series of concentrations.

PubMed

Samoilov, Michael; Arkin, Adam; Ross, John

2001-03-01

We discuss the deduction of reaction pathways in complex chemical systems from measurements of time series of chemical concentrations of reacting species. First we review a technique called correlation metric construction (CMC) and show the construction of a reaction pathway from measurements on a part of glycolysis. Then we present two new improved methods for the analysis of time series of concentrations, entropy metric construction (EMC), and entropy reduction method (ERM), and illustrate (EMC) with calculations on a model reaction system. (c) 2001 American Institute of Physics.

Exact conditions on the temperature dependence of density functionals

DOE PAGES

Burke, K.; Smith, J. C.; Grabowski, P. E.; ...

2016-05-15

Universal exact conditions guided the construction of most ground-state density functional approximations in use today. Here, we derive the relation between the entropy and Mermin free energy density functionals for thermal density functional theory. Both the entropy and sum of kinetic and electron-electron repulsion functionals are shown to be monotonically increasing with temperature, while the Mermin functional is concave downwards. Analogous relations are found for both exchange and correlation. The importance of these conditions is illustrated in two extremes: the Hubbard dimer and the uniform gas.

Retrieving pace in vegetation growth using precipitation and soil moisture

NASA Astrophysics Data System (ADS)

Sohoulande Djebou, D. C.; Singh, V. P.

2013-12-01

The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and NDVI. The analysis is performed by combining both scenes 7 and 8 data. Schematic illustration of the two dimension transinformation entropy approach. T(P,SM;VI) stand for the transinformation contained in the couple soil moisture (SM)/precipitation (P) and explaining vegetation growth (VI).

State Anxiety and Nonlinear Dynamics of Heart Rate Variability in Students

PubMed Central

Dimitriev, Aleksey D.

2016-01-01

Objectives Clinical and experimental research studies have demonstrated that the emotional experience of anxiety impairs heart rate variability (HRV) in humans. The present study investigated whether changes in state anxiety (SA) can also modulate nonlinear dynamics of heart rate. Methods A group of 96 students volunteered to participate in the study. For each student, two 5-minute recordings of beat intervals (RR) were performed: one during a rest period and one just before a university examination, which was assumed to be a real-life stressor. Nonlinear analysis of HRV was performed. The Spielberger’s State-Trait Anxiety Inventory was used to assess the level of SA. Results Before adjusting for heart rate, a Wilcoxon matched pairs test showed significant decreases in Poincaré plot measures, entropy, largest Lyapunov exponent (LLE), and pointwise correlation dimension (PD2), and an increase in the short-term fractal-like scaling exponent of detrended fluctuation analysis (α1) during the exam session, compared with the rest period. A Pearson analysis indicated significant negative correlations between the dynamics of SA and Poincaré plot axes ratio (SD1/SD2), and between changes in SA and changes in entropy measures. A strong negative correlation was found between the dynamics of SA and LLE. A significant positive correlation was found between the dynamics of SA and α1. The decreases in Poincaré plot measures (SD1, complex correlation measure), entropy measures, and LLE were still significant after adjusting for heart rate. Corrected α1 was increased during the exam session. As before, the dynamics of adjusted LLE was significantly correlated with the dynamics of SA. Conclusions The qualitative increase in SA during academic examination was related to the decrease in the complexity and size of the Poincaré plot through a reduction of both the interbeat interval and its variation. PMID:26807793

Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach.

PubMed

Ramakrishnan, Raghunathan; Dral, Pavlo O; Rupp, Matthias; von Lilienfeld, O Anatole

2015-05-12

Chemically accurate and comprehensive studies of the virtual space of all possible molecules are severely limited by the computational cost of quantum chemistry. We introduce a composite strategy that adds machine learning corrections to computationally inexpensive approximate legacy quantum methods. After training, highly accurate predictions of enthalpies, free energies, entropies, and electron correlation energies are possible, for significantly larger molecular sets than used for training. For thermochemical properties of up to 16k isomers of C7H10O2 we present numerical evidence that chemical accuracy can be reached. We also predict electron correlation energy in post Hartree-Fock methods, at the computational cost of Hartree-Fock, and we establish a qualitative relationship between molecular entropy and electron correlation. The transferability of our approach is demonstrated, using semiempirical quantum chemistry and machine learning models trained on 1 and 10% of 134k organic molecules, to reproduce enthalpies of all remaining molecules at density functional theory level of accuracy.

Uncertainties in Forecasting Streamflow using Entropy Theory

NASA Astrophysics Data System (ADS)

Cui, H.; Singh, V. P.

2017-12-01

Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.

From Maximum Entropy Models to Non-Stationarity and Irreversibility

NASA Astrophysics Data System (ADS)

Cofre, Rodrigo; Cessac, Bruno; Maldonado, Cesar

The maximum entropy distribution can be obtained from a variational principle. This is important as a matter of principle and for the purpose of finding approximate solutions. One can exploit this fact to obtain relevant information about the underlying stochastic process. We report here in recent progress in three aspects to this approach.1- Biological systems are expected to show some degree of irreversibility in time. Based on the transfer matrix technique to find the spatio-temporal maximum entropy distribution, we build a framework to quantify the degree of irreversibility of any maximum entropy distribution.2- The maximum entropy solution is characterized by a functional called Gibbs free energy (solution of the variational principle). The Legendre transformation of this functional is the rate function, which controls the speed of convergence of empirical averages to their ergodic mean. We show how the correct description of this functional is determinant for a more rigorous characterization of first and higher order phase transitions.3- We assess the impact of a weak time-dependent external stimulus on the collective statistics of spiking neuronal networks. We show how to evaluate this impact on any higher order spatio-temporal correlation. RC supported by ERC advanced Grant ``Bridges'', BC: KEOPS ANR-CONICYT, Renvision and CM: CONICYT-FONDECYT No. 3140572.

High Grazing Angle and High Resolution Sea Clutter: Correlation and Polarisation Analyses

DTIC Science & Technology

2007-03-01

the azimuthal correlation. The correlation between the HH and VV sea clutter data is low. A CA-CFAR ( cell average constant false-alarm rate...to calculate the power spectra of correlation profiles. The frequency interval of the traditional Discrete Fourier Transform is NT1 Hz, where N and...sea spikes, the Entropy-Alpha decomposition of sea spikes is shown in Figure 30. The process first locates spikes using a cell -average constant false

Intra-Tumour Signalling Entropy Determines Clinical Outcome in Breast and Lung Cancer

PubMed Central

Banerji, Christopher R. S.; Severini, Simone; Caldas, Carlos; Teschendorff, Andrew E.

2015-01-01

The cancer stem cell hypothesis, that a small population of tumour cells are responsible for tumorigenesis and cancer progression, is becoming widely accepted and recent evidence has suggested a prognostic and predictive role for such cells. Intra-tumour heterogeneity, the diversity of the cancer cell population within the tumour of an individual patient, is related to cancer stem cells and is also considered a potential prognostic indicator in oncology. The measurement of cancer stem cell abundance and intra-tumour heterogeneity in a clinically relevant manner however, currently presents a challenge. Here we propose signalling entropy, a measure of signalling pathway promiscuity derived from a sample’s genome-wide gene expression profile, as an estimate of the stemness of a tumour sample. By considering over 500 mixtures of diverse cellular expression profiles, we reveal that signalling entropy also associates with intra-tumour heterogeneity. By analysing 3668 breast cancer and 1692 lung adenocarcinoma samples, we further demonstrate that signalling entropy correlates negatively with survival, outperforming leading clinical gene expression based prognostic tools. Signalling entropy is found to be a general prognostic measure, valid in different breast cancer clinical subgroups, as well as within stage I lung adenocarcinoma. We find that its prognostic power is driven by genes involved in cancer stem cells and treatment resistance. In summary, by approximating both stemness and intra-tumour heterogeneity, signalling entropy provides a powerful prognostic measure across different epithelial cancers. PMID:25793737

Digital focusing of OCT images based on scalar diffraction theory and information entropy

PubMed Central

Liu, Guozhong; Zhi, Zhongwei; Wang, Ruikang K.

2012-01-01

This paper describes a digital method that is capable of automatically focusing optical coherence tomography (OCT) en face images without prior knowledge of the point spread function of the imaging system. The method utilizes a scalar diffraction model to simulate wave propagation from out-of-focus scatter to the focal plane, from which the propagation distance between the out-of-focus plane and the focal plane is determined automatically via an image-definition-evaluation criterion based on information entropy theory. By use of the proposed approach, we demonstrate that the lateral resolution close to that at the focal plane can be recovered from the imaging planes outside the depth of field region with minimal loss of resolution. Fresh onion tissues and mouse fat tissues are used in the experiments to show the performance of the proposed method. PMID:23162717

Ordering states with various coherence measures

NASA Astrophysics Data System (ADS)

Yang, Long-Mei; Chen, Bin; Fei, Shao-Ming; Wang, Zhi-Xi

2018-04-01

Quantum coherence is one of the most significant theories in quantum physics. Ordering states with various coherence measures is an intriguing task in quantification theory of coherence. In this paper, we study this problem by use of four important coherence measures—the l_1 norm of coherence, the relative entropy of coherence, the geometric measure of coherence and the modified trace distance measure of coherence. We show that each pair of these measures give a different ordering of qudit states when d≥3. However, for single-qubit states, the l_1 norm of coherence and the geometric coherence provide the same ordering. We also show that the relative entropy of coherence and the geometric coherence give a different ordering for single-qubit states. Then we partially answer the open question proposed in Liu et al. (Quantum Inf Process 15:4189, 2016) whether all the coherence measures give a different ordering of states.

A two-stage approach to removing noise from recorded music

NASA Astrophysics Data System (ADS)

Berger, Jonathan; Goldberg, Maxim J.; Coifman, Ronald C.; Goldberg, Maxim J.; Coifman, Ronald C.

2004-05-01

A two-stage algorithm for removing noise from recorded music signals (first proposed in Berger et al., ICMC, 1995) is described and updated. The first stage selects the ``best'' local trigonometric basis for the signal and models noise as the part having high entropy [see Berger et al., J. Audio Eng. Soc. 42(10), 808-818 (1994)]. In the second stage, the original source and the model of the noise obtained from the first stage are expanded into dyadic trees of smooth local sine bases. The best basis for the source signal is extracted using a relative entropy function (the Kullback-Leibler distance) to compare the sum of the costs of the children nodes to the cost of their parent node; energies of the noise in corresponding nodes of the model noise tree are used as weights. The talk will include audio examples of various stages of the method and proposals for further research.

Nonequilibrium thermodynamics and a fluctuation theorem for individual reaction steps in a chemical reaction network

NASA Astrophysics Data System (ADS)

Pal, Krishnendu; Das, Biswajit; Banerjee, Kinshuk; Gangopadhyay, Gautam

2015-09-01

We have introduced an approach to nonequilibrium thermodynamics of an open chemical reaction network in terms of the propensities of the individual elementary reactions and the corresponding reverse reactions. The method is a microscopic formulation of the dissipation function in terms of the relative entropy or Kullback-Leibler distance which is based on the analogy of phase space trajectory with the path of elementary reactions in a network of chemical process. We have introduced here a fluctuation theorem valid for each opposite pair of elementary reactions which is useful in determining the contribution of each sub-reaction on the nonequilibrium thermodynamics of overall reaction. The methodology is applied to an oligomeric enzyme kinetics at a chemiostatic condition that leads the reaction to a nonequilibrium steady state for which we have estimated how each step of the reaction is energy driven or entropy driven to contribute to the overall reaction.

Revisiting the phase transition of AdS-Maxwell-power-Yang-Mills black holes via AdS/CFT tools

NASA Astrophysics Data System (ADS)

El Moumni, H.

2018-01-01

In the present work we investigate the Van der Waals-like phase transition of AdS black hole solution in the Einstein-Maxwell-power-Yang-Mills gravity (EMPYM) via different approaches. After reconsidering this phase structure in the entropy-thermal plane, we recall the nonlocal observables such as holographic entanglement entropy and two point correlation function to show that the both observables exhibit a Van der Waals-like behavior as the case of the thermal entropy. By checking the Maxwell's equal area law and calculating the critical exponent for different values of charge C and nonlinearity parameter q we confirm that the first and the second order phases persist in the holographic framework. Also the validity of the Maxwell law is governed by the proximity to the critical point.

Fading Hawking radiation

NASA Astrophysics Data System (ADS)

Sakalli, Izzet; Halilsoy, Mustafa; Pasaoglu, Hale

2012-07-01

In this study, we explore a particular type Hawking radiation which ends with zero temperature and entropy. The appropriate black holes for this purpose are the linear dilaton black holes. In addition to the black hole choice, a recent formalism in which the Parikh-Wilczek's tunneling formalism amalgamated with quantum corrections to all orders in ħ is considered. The adjustment of the coefficients of the quantum corrections plays a crucial role on this particular Hawking radiation. The obtained tunneling rate indicates that the radiation is not pure thermal anymore, and hence correlations of outgoing quanta are capable of carrying away information encoded within them. Finally, we show in detail that when the linear dilaton black hole completely evaporates through such a particular radiation, entropy of the radiation becomes identical with the entropy of the black hole, which corresponds to "no information loss".

Permutation Entropy Applied to Movement Behaviors of Drosophila Melanogaster

NASA Astrophysics Data System (ADS)

Liu, Yuedan; Chon, Tae-Soo; Baek, Hunki; Do, Younghae; Choi, Jin Hee; Chung, Yun Doo

Movement of different strains in Drosophila melanogaster was continuously observed by using computer interfacing techniques and was analyzed by permutation entropy (PE) after exposure to toxic chemicals, toluene (0.1 mg/m3) and formaldehyde (0.01 mg/m3). The PE values based on one-dimensional time series position (vertical) data were variable according to internal constraint (i.e. strains) and accordingly increased in response to external constraint (i.e. chemicals) by reflecting diversity in movement patterns from both normal and intoxicated states. Cross-correlation function revealed temporal associations between the PE values and between the component movement patterns in different chemicals and strains through the period of intoxication. The entropy based on the order of position data could be a useful means for complexity measure in behavioral changes and for monitoring the impact of stressors in environment.

Detection of Unilateral Hearing Loss by Stationary Wavelet Entropy.

PubMed

Zhang, Yudong; Nayak, Deepak Ranjan; Yang, Ming; Yuan, Ti-Fei; Liu, Bin; Lu, Huimin; Wang, Shuihua

2017-01-01

Sensorineural hearing loss is correlated to massive neurological or psychiatric disease. T1-weighted volumetric images were acquired from fourteen subjects with right-sided hearing loss (RHL), fifteen subjects with left-sided hearing loss (LHL), and twenty healthy controls (HC). We treated a three-class classification problem: HC, LHL, and RHL. Stationary wavelet entropy was employed to extract global features from magnetic resonance images of each subject. Those stationary wavelet entropy features were used as input to a single-hidden layer feedforward neuralnetwork classifier. The 10 repetition results of 10-fold cross validation show that the accuracies of HC, LHL, and RHL are 96.94%, 97.14%, and 97.35%, respectively. Our developed system is promising and effective in detecting hearing loss. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Prediction of microsleeps using pairwise joint entropy and mutual information between EEG channels.

PubMed

Baseer, Abdul; Weddell, Stephen J; Jones, Richard D

2017-07-01

Microsleeps are involuntary and brief instances of complete loss of responsiveness, typically of 0.5-15 s duration. They adversely affect performance in extended attention-driven jobs and can be fatal. Our aim was to predict microsleeps from 16 channel EEG signals. Two information theoretic concepts - pairwise joint entropy and mutual information - were independently used to continuously extract features from EEG signals. k-nearest neighbor (kNN) with k = 3 was used to calculate both joint entropy and mutual information. Highly correlated features were discarded and the rest were ranked using Fisher score followed by an average of 3-fold cross-validation area under the curve of the receiver operating characteristic (AUC ROC ). Leave-one-out method (LOOM) was performed to test the performance of microsleep prediction system on independent data. The best prediction for 0.25 s ahead was AUCROC, sensitivity, precision, geometric mean (GM), and φ of 0.93, 0.68, 0.33, 0.75, and 0.38 respectively with joint entropy using single linear discriminant analysis (LDA) classifier.

Self-Similar Random Process and Chaotic Behavior In Serrated Flow of High Entropy Alloys

PubMed Central

Chen, Shuying; Yu, Liping; Ren, Jingli; Xie, Xie; Li, Xueping; Xu, Ying; Zhao, Guangfeng; Li, Peizhen; Yang, Fuqian; Ren, Yang; Liaw, Peter K.

2016-01-01

The statistical and dynamic analyses of the serrated-flow behavior in the nanoindentation of a high-entropy alloy, Al0.5CoCrCuFeNi, at various holding times and temperatures, are performed to reveal the hidden order associated with the seemingly-irregular intermittent flow. Two distinct types of dynamics are identified in the high-entropy alloy, which are based on the chaotic time-series, approximate entropy, fractal dimension, and Hurst exponent. The dynamic plastic behavior at both room temperature and 200 °C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. The fractal dimension of the indentation depth increases with the increase of temperature, and there is an inflection at the holding time of 10 s at the same temperature. A large fractal dimension suggests the concurrent nucleation of a large number of slip bands. In particular, for the indentation with the holding time of 10 s at room temperature, the slip process evolves as a self-similar random process with a weak negative correlation similar to a random walk. PMID:27435922

Self-similar random process and chaotic behavior in serrated flow of high entropy alloys

DOE PAGES

Chen, Shuying; Yu, Liping; Ren, Jingli; ...

2016-07-20

Here, the statistical and dynamic analyses of the serrated-flow behavior in the nanoindentation of a high-entropy alloy, Al 0.5CoCrCuFeNi, at various holding times and temperatures, are performed to reveal the hidden order associated with the seemingly-irregular intermittent flow. Two distinct types of dynamics are identified in the high-entropy alloy, which are based on the chaotic time-series, approximate entropy, fractal dimension, and Hurst exponent. The dynamic plastic behavior at both room temperature and 200 °C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. The fractal dimension of the indentation depth increases with the increase of temperature, andmore » there is an inflection at the holding time of 10 s at the same temperature. A large fractal dimension suggests the concurrent nucleation of a large number of slip bands. In particular, for the indentation with the holding time of 10 s at room temperature, the slip process evolves as a self-similar random process with a weak negative correlation similar to a random walk.« less

Multibody local approximation: Application to conformational entropy calculations on biomolecules

NASA Astrophysics Data System (ADS)

Suárez, Ernesto; Suárez, Dimas

2012-08-01

Multibody type expansions like mutual information expansions are widely used for computing or analyzing properties of large composite systems. The power of such expansions stems from their generality. Their weaknesses, however, are the large computational cost of including high order terms due to the combinatorial explosion and the fact that truncation errors do not decrease strictly with the expansion order. Herein, we take advantage of the redundancy of multibody expansions in order to derive an efficient reformulation that captures implicitly all-order correlation effects within a given cutoff, avoiding the combinatory explosion. This approach, which is cutoff dependent rather than order dependent, keeps the generality of the original expansions and simultaneously mitigates their limitations provided that a reasonable cutoff can be used. An application of particular interest can be the computation of the conformational entropy of flexible peptide molecules from molecular dynamics trajectories. By combining the multibody local estimations of conformational entropy with average values of the rigid-rotor and harmonic-oscillator entropic contributions, we obtain by far a tighter upper bound of the absolute entropy than the one obtained by the broadly used quasi-harmonic method.

Multibody local approximation: application to conformational entropy calculations on biomolecules.

PubMed

Suárez, Ernesto; Suárez, Dimas

2012-08-28

Multibody type expansions like mutual information expansions are widely used for computing or analyzing properties of large composite systems. The power of such expansions stems from their generality. Their weaknesses, however, are the large computational cost of including high order terms due to the combinatorial explosion and the fact that truncation errors do not decrease strictly with the expansion order. Herein, we take advantage of the redundancy of multibody expansions in order to derive an efficient reformulation that captures implicitly all-order correlation effects within a given cutoff, avoiding the combinatory explosion. This approach, which is cutoff dependent rather than order dependent, keeps the generality of the original expansions and simultaneously mitigates their limitations provided that a reasonable cutoff can be used. An application of particular interest can be the computation of the conformational entropy of flexible peptide molecules from molecular dynamics trajectories. By combining the multibody local estimations of conformational entropy with average values of the rigid-rotor and harmonic-oscillator entropic contributions, we obtain by far a tighter upper bound of the absolute entropy than the one obtained by the broadly used quasi-harmonic method.

Self-Similar Random Process and Chaotic Behavior In Serrated Flow of High Entropy Alloys.

PubMed

Chen, Shuying; Yu, Liping; Ren, Jingli; Xie, Xie; Li, Xueping; Xu, Ying; Zhao, Guangfeng; Li, Peizhen; Yang, Fuqian; Ren, Yang; Liaw, Peter K

2016-07-20

The statistical and dynamic analyses of the serrated-flow behavior in the nanoindentation of a high-entropy alloy, Al0.5CoCrCuFeNi, at various holding times and temperatures, are performed to reveal the hidden order associated with the seemingly-irregular intermittent flow. Two distinct types of dynamics are identified in the high-entropy alloy, which are based on the chaotic time-series, approximate entropy, fractal dimension, and Hurst exponent. The dynamic plastic behavior at both room temperature and 200 °C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. The fractal dimension of the indentation depth increases with the increase of temperature, and there is an inflection at the holding time of 10 s at the same temperature. A large fractal dimension suggests the concurrent nucleation of a large number of slip bands. In particular, for the indentation with the holding time of 10 s at room temperature, the slip process evolves as a self-similar random process with a weak negative correlation similar to a random walk.

Efficient Computation of Small-Molecule Configurational Binding Entropy and Free Energy Changes by Ensemble Enumeration

PubMed Central

2013-01-01

Here we present a novel, end-point method using the dead-end-elimination and A* algorithms to efficiently and accurately calculate the change in free energy, enthalpy, and configurational entropy of binding for ligand–receptor association reactions. We apply the new approach to the binding of a series of human immunodeficiency virus (HIV-1) protease inhibitors to examine the effect ensemble reranking has on relative accuracy as well as to evaluate the role of the absolute and relative ligand configurational entropy losses upon binding in affinity differences for structurally related inhibitors. Our results suggest that most thermodynamic parameters can be estimated using only a small fraction of the full configurational space, and we see significant improvement in relative accuracy when using an ensemble versus single-conformer approach to ligand ranking. We also find that using approximate metrics based on the single-conformation enthalpy differences between the global minimum energy configuration in the bound as well as unbound states also correlates well with experiment. Using a novel, additive entropy expansion based on conditional mutual information, we also analyze the source of ligand configurational entropy loss upon binding in terms of both uncoupled per degree of freedom losses as well as changes in coupling between inhibitor degrees of freedom. We estimate entropic free energy losses of approximately +24 kcal/mol, 12 kcal/mol of which stems from loss of translational and rotational entropy. Coupling effects contribute only a small fraction to the overall entropy change (1–2 kcal/mol) but suggest differences in how inhibitor dihedral angles couple to each other in the bound versus unbound states. The importance of accounting for flexibility in drug optimization and design is also discussed. PMID:24250277

Diffusion Profiling via a Histogram Approach Distinguishes Low-grade from High-grade Meningiomas, Can Reflect the Respective Proliferative Potential and Progesterone Receptor Status.

PubMed

Gihr, Georg Alexander; Horvath-Rizea, Diana; Garnov, Nikita; Kohlhof-Meinecke, Patricia; Ganslandt, Oliver; Henkes, Hans; Meyer, Hans Jonas; Hoffmann, Karl-Titus; Surov, Alexey; Schob, Stefan

2018-02-01

Presurgical grading, estimation of growth kinetics, and other prognostic factors are becoming increasingly important for selecting the best therapeutic approach for meningioma patients. Diffusion-weighted imaging (DWI) provides microstructural information and reflects tumor biology. A novel DWI approach, histogram profiling of apparent diffusion coefficient (ADC) volumes, provides more distinct information than conventional DWI. Therefore, our study investigated whether ADC histogram profiling distinguishes low-grade from high-grade lesions and reflects Ki-67 expression and progesterone receptor status. Pretreatment ADC volumes of 37 meningioma patients (28 low-grade, 9 high-grade) were used for histogram profiling. WHO grade, Ki-67 expression, and progesterone receptor status were evaluated. Comparative and correlative statistics investigating the association between histogram profiling and neuropathology were performed. The entire ADC profile (p10, p25, p75, p90, mean, median) was significantly lower in high-grade versus low-grade meningiomas. The lower percentiles, mean, and modus showed significant correlations with Ki-67 expression. Skewness and entropy of the ADC volumes were significantly associated with progesterone receptor status and Ki-67 expression. ROC analysis revealed entropy to be the most accurate parameter distinguishing low-grade from high-grade meningiomas. ADC histogram profiling provides a distinct set of parameters, which help differentiate low-grade versus high-grade meningiomas. Also, histogram metrics correlate significantly with histological surrogates of the respective proliferative potential. More specifically, entropy revealed to be the most promising imaging biomarker for presurgical grading. Both, entropy and skewness were significantly associated with progesterone receptor status and Ki-67 expression and therefore should be investigated further as predictors for prognostically relevant tumor biological features. Since absolute ADC values vary between MRI scanners of different vendors and field strengths, their use is more limited in the presurgical setting.

Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping.

PubMed

Wang, Bin; Niu, Yan; Miao, Liwen; Cao, Rui; Yan, Pengfei; Guo, Hao; Li, Dandan; Guo, Yuxiang; Yan, Tianyi; Wu, Jinglong; Xiang, Jie; Zhang, Hui

2017-01-01

Alzheimer's disease (AD) is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI) and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE) to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA) on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE) scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ) scores and global Clinical Dementia Rating (CDR) scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo) in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE in rs-fMRI signals can provide important information about the fMRI characteristics of cognitive impairments in MCI and AD.

Decreased Complexity in Alzheimer's Disease: Resting-State fMRI Evidence of Brain Entropy Mapping

PubMed Central

Wang, Bin; Niu, Yan; Miao, Liwen; Cao, Rui; Yan, Pengfei; Guo, Hao; Li, Dandan; Guo, Yuxiang; Yan, Tianyi; Wu, Jinglong; Xiang, Jie; Zhang, Hui

2017-01-01

Alzheimer's disease (AD) is a frequently observed, irreversible brain function disorder among elderly individuals. Resting-state functional magnetic resonance imaging (rs-fMRI) has been introduced as an alternative approach to assessing brain functional abnormalities in AD patients. However, alterations in the brain rs-fMRI signal complexities in mild cognitive impairment (MCI) and AD patients remain unclear. Here, we described the novel application of permutation entropy (PE) to investigate the abnormal complexity of rs-fMRI signals in MCI and AD patients. The rs-fMRI signals of 30 normal controls (NCs), 33 early MCI (EMCI), 32 late MCI (LMCI), and 29 AD patients were obtained from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. After preprocessing, whole-brain entropy maps of the four groups were extracted and subjected to Gaussian smoothing. We performed a one-way analysis of variance (ANOVA) on the brain entropy maps of the four groups. The results after adjusting for age and sex differences together revealed that the patients with AD exhibited lower complexity than did the MCI and NC controls. We found five clusters that exhibited significant differences and were distributed primarily in the occipital, frontal, and temporal lobes. The average PE of the five clusters exhibited a decreasing trend from MCI to AD. The AD group exhibited the least complexity. Additionally, the average PE of the five clusters was significantly positively correlated with the Mini-Mental State Examination (MMSE) scores and significantly negatively correlated with Functional Assessment Questionnaire (FAQ) scores and global Clinical Dementia Rating (CDR) scores in the patient groups. Significant correlations were also found between the PE and regional homogeneity (ReHo) in the patient groups. These results indicated that declines in PE might be related to changes in regional functional homogeneity in AD. These findings suggested that complexity analyses using PE in rs-fMRI signals can provide important information about the fMRI characteristics of cognitive impairments in MCI and AD. PMID:29209199

A hybrid correlation analysis with application to imaging genetics

NASA Astrophysics Data System (ADS)

Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

2018-03-01

Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding the correlation between brain imaging and genomic data.

[Perinatal model of human transition from hypogravity to the earth's gravity based on the electromyogram nonlinear characteristics].

PubMed

Meĭgal, A Iu; Voroshilov, A S

2009-01-01

Interferential electromyogram (iEMG) was analyzed in healthy newborn infants (n=29) during the first 24 hours of life as a model of transition from hypogravity (intrauterine immersion) to the Earth's gravity (postnatal period). Nonlinear instruments of iEMG analysis (correlation dimension, entropy and fractal dimension) reflected the complexity, chaotic character and predictability of signals from the leg and arm antagonistic muscles. Except for m. gastrocnemius, in all other musles iEMG fractal dimension was shown to grow as the postnatal period extended. Low fractal and correlation dimensions and entropy marked flexor muscles, particularly against low iEMG amplitude suggesting a better congenital programming for the flexors as compared to the extensors. It is concluded that the early ontogenesis model can be practicable in studying the evolution and states of antigravity functions.

Differences in evolutionary pressure acting within highly conserved ortholog groups.

PubMed

Przytycka, Teresa M; Jothi, Raja; Aravind, L; Lipman, David J

2008-07-17

In highly conserved widely distributed ortholog groups, the main evolutionary force is assumed to be purifying selection that enforces sequence conservation, with most divergence occurring by accumulation of neutral substitutions. Using a set of ortholog groups from prokaryotes, with a single representative in each studied organism, we asked the question if this evolutionary pressure is acting similarly on different subgroups of orthologs defined as major lineages (e.g. Proteobacteria or Firmicutes). Using correlations in entropy measures as a proxy for evolutionary pressure, we observed two distinct behaviors within our ortholog collection. The first subset of ortholog groups, called here informational, consisted mostly of proteins associated with information processing (i.e. translation, transcription, DNA replication) and the second, the non-informational ortholog groups, mostly comprised of proteins involved in metabolic pathways. The evolutionary pressure acting on non-informational proteins is more uniform relative to their informational counterparts. The non-informational proteins show higher level of correlation between entropy profiles and more uniformity across subgroups. The low correlation of entropy profiles in the informational ortholog groups suggest that the evolutionary pressure acting on the informational ortholog groups is not uniform across different clades considered this study. This might suggest "fine-tuning" of informational proteins in each lineage leading to lineage-specific differences in selection. This, in turn, could make these proteins less exchangeable between lineages. In contrast, the uniformity of the selective pressure acting on the non-informational groups might allow the exchange of the genetic material via lateral gene transfer.

Measuring Out-of-Time-Order Correlators on a Nuclear Magnetic Resonance Quantum Simulator

NASA Astrophysics Data System (ADS)

Li, Jun; Fan, Ruihua; Wang, Hengyan; Ye, Bingtian; Zeng, Bei; Zhai, Hui; Peng, Xinhua; Du, Jiangfeng

2017-07-01

The idea of the out-of-time-order correlator (OTOC) has recently emerged in the study of both condensed matter systems and gravitational systems. It not only plays a key role in investigating the holographic duality between a strongly interacting quantum system and a gravitational system, it also diagnoses the chaotic behavior of many-body quantum systems and characterizes information scrambling. Based on OTOCs, three different concepts—quantum chaos, holographic duality, and information scrambling—are found to be intimately related to each other. Despite its theoretical importance, the experimental measurement of the OTOC is quite challenging, and thus far there is no experimental measurement of the OTOC for local operators. Here, we report the measurement of OTOCs of local operators for an Ising spin chain on a nuclear magnetic resonance quantum simulator. We observe that the OTOC behaves differently in the integrable and nonintegrable cases. Based on the recent discovered relationship between OTOCs and the growth of entanglement entropy in the many-body system, we extract the entanglement entropy from the measured OTOCs, which clearly shows that the information entropy oscillates in time for integrable models and scrambles for nonintgrable models. With the measured OTOCs, we also obtain the experimental result of the butterfly velocity, which measures the speed of correlation propagation. Our experiment paves a way for experimentally studying quantum chaos, holographic duality, and information scrambling in many-body quantum systems with quantum simulators.

Rigid Residue Scan Simulations Systematically Reveal Residue Entropic Roles in Protein Allostery

PubMed Central

Liu, Jin

2016-01-01

Intra-protein information is transmitted over distances via allosteric processes. This ubiquitous protein process allows for protein function changes due to ligand binding events. Understanding protein allostery is essential to understanding protein functions. In this study, allostery in the second PDZ domain (PDZ2) in the human PTP1E protein is examined as model system to advance a recently developed rigid residue scan method combining with configurational entropy calculation and principal component analysis. The contributions from individual residues to whole-protein dynamics and allostery were systematically assessed via rigid body simulations of both unbound and ligand-bound states of the protein. The entropic contributions of individual residues to whole-protein dynamics were evaluated based on covariance-based correlation analysis of all simulations. The changes of overall protein entropy when individual residues being held rigid support that the rigidity/flexibility equilibrium in protein structure is governed by the La Châtelier’s principle of chemical equilibrium. Key residues of PDZ2 allostery were identified with good agreement with NMR studies of the same protein bound to the same peptide. On the other hand, the change of entropic contribution from each residue upon perturbation revealed intrinsic differences among all the residues. The quasi-harmonic and principal component analyses of simulations without rigid residue perturbation showed a coherent allosteric mode from unbound and bound states, respectively. The projection of simulations with rigid residue perturbation onto coherent allosteric modes demonstrated the intrinsic shifting of ensemble distributions supporting the population-shift theory of protein allostery. Overall, the study presented here provides a robust and systematic approach to estimate the contribution of individual residue internal motion to overall protein dynamics and allostery. PMID:27115535

Quantum Entanglement Growth under Random Unitary Dynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nahum, Adam; Ruhman, Jonathan; Vijay, Sagar

Characterizing how entanglement grows with time in a many-body system, for example, after a quantum quench, is a key problem in nonequilibrium quantum physics. We study this problem for the case of random unitary dynamics, representing either Hamiltonian evolution with time-dependent noise or evolution by a random quantum circuit. Our results reveal a universal structure behind noisy entanglement growth, and also provide simple new heuristics for the “entanglement tsunami” in Hamiltonian systems without noise. In 1D, we show that noise causes the entanglement entropy across a cut to grow according to the celebrated Kardar-Parisi-Zhang (KPZ) equation. The mean entanglement growsmore » linearly in time, while fluctuations grow like (time) 1/3 and are spatially correlated over a distance ∝(time) 2/3. We derive KPZ universal behavior in three complementary ways, by mapping random entanglement growth to (i) a stochastic model of a growing surface, (ii) a “minimal cut” picture, reminiscent of the Ryu-Takayanagi formula in holography, and (iii) a hydrodynamic problem involving the dynamical spreading of operators. We demonstrate KPZ universality in 1D numerically using simulations of random unitary circuits. Importantly, the leading-order time dependence of the entropy is deterministic even in the presence of noise, allowing us to propose a simple coarse grained minimal cut picture for the entanglement growth of generic Hamiltonians, even without noise, in arbitrary dimensionality. We clarify the meaning of the “velocity” of entanglement growth in the 1D entanglement tsunami. We show that in higher dimensions, noisy entanglement evolution maps to the well-studied problem of pinning of a membrane or domain wall by disorder.« less

Quantum Entanglement Growth under Random Unitary Dynamics

DOE PAGES

Nahum, Adam; Ruhman, Jonathan; Vijay, Sagar; ...

2017-07-24

Characterizing how entanglement grows with time in a many-body system, for example, after a quantum quench, is a key problem in nonequilibrium quantum physics. We study this problem for the case of random unitary dynamics, representing either Hamiltonian evolution with time-dependent noise or evolution by a random quantum circuit. Our results reveal a universal structure behind noisy entanglement growth, and also provide simple new heuristics for the “entanglement tsunami” in Hamiltonian systems without noise. In 1D, we show that noise causes the entanglement entropy across a cut to grow according to the celebrated Kardar-Parisi-Zhang (KPZ) equation. The mean entanglement growsmore » linearly in time, while fluctuations grow like (time) 1/3 and are spatially correlated over a distance ∝(time) 2/3. We derive KPZ universal behavior in three complementary ways, by mapping random entanglement growth to (i) a stochastic model of a growing surface, (ii) a “minimal cut” picture, reminiscent of the Ryu-Takayanagi formula in holography, and (iii) a hydrodynamic problem involving the dynamical spreading of operators. We demonstrate KPZ universality in 1D numerically using simulations of random unitary circuits. Importantly, the leading-order time dependence of the entropy is deterministic even in the presence of noise, allowing us to propose a simple coarse grained minimal cut picture for the entanglement growth of generic Hamiltonians, even without noise, in arbitrary dimensionality. We clarify the meaning of the “velocity” of entanglement growth in the 1D entanglement tsunami. We show that in higher dimensions, noisy entanglement evolution maps to the well-studied problem of pinning of a membrane or domain wall by disorder.« less

The ground states of iron(III) porphines: role of entropy-enthalpy compensation, Fermi correlation, dispersion, and zero-point energies.

PubMed

Kepp, Kasper P

2011-10-01

Porphyrins are much studied due to their biochemical relevance and many applications. The density functional TPSSh has previously accurately described the energy of close-lying electronic states of transition metal systems such as porphyrins. However, a recent study questioned this conclusion based on calculations of five iron(III) porphines. Here, we compute the geometries of 80 different electronic configurations and the free energies of the most stable configurations with the functionals TPSSh, TPSS, and B3LYP. Zero-point energies and entropy favor high-spin by ~4kJ/mol and 0-10kJ/mol, respectively. When these effects are included, and all electronic configurations are evaluated, TPSSh correctly predicts the spin of all the four difficult phenylporphine cases and is within the lower bound of uncertainty of any known theoretical method for the fifth, iron(III) chloroporphine. Dispersion computed with DFT-D3 favors low-spin by 3-53kJ/mol (TPSSh) or 4-15kJ/mol (B3LYP) due to the attractive r(-6) term and the shorter distances in low-spin. The very large and diverse corrections from TPSS and TPSSh seem less consistent with the similarity of the systems than when calculated from B3LYP. If the functional-specific corrections are used, B3LYP and TPSSh are of equal accuracy, and TPSS is much worse, whereas if the physically reasonable B3LYP-computed dispersion effect is used for all functionals, TPSSh is accurate for all systems. B3LYP is significantly more accurate when dispersion is added, confirming previous results. Copyright © 2011 Elsevier Inc. All rights reserved.

Classification of pre-sliced pork and Turkey ham qualities based on image colour and textural features and their relationships with consumer responses.

PubMed

Iqbal, Abdullah; Valous, Nektarios A; Mendoza, Fernando; Sun, Da-Wen; Allen, Paul

2010-03-01

Images of three qualities of pre-sliced pork and Turkey hams were evaluated for colour and textural features to characterize and classify them, and to model the ham appearance grading and preference responses of a group of consumers. A total of 26 colour features and 40 textural features were extracted for analysis. Using Mahalanobis distance and feature inter-correlation analyses, two best colour [mean of S (saturation in HSV colour space), std. deviation of b*, which indicates blue to yellow in L*a*b* colour space] and three textural features [entropy of b*, contrast of H (hue of HSV colour space), entropy of R (red of RGB colour space)] for pork, and three colour (mean of R, mean of H, std. deviation of a*, which indicates green to red in L*a*b* colour space) and two textural features [contrast of B, contrast of L* (luminance or lightness in L*a*b* colour space)] for Turkey hams were selected as features with the highest discriminant power. High classification performances were reached for both types of hams (>99.5% for pork and >90.5% for Turkey) using the best selected features or combinations of them. In spite of the poor/fair agreement among ham consumers as determined by Kappa analysis (Kappa-value<0.4) for sensory grading (surface colour, colour uniformity, bitonality, texture appearance and acceptability), a dichotomous logistic regression model using the best image features was able to explain the variability of consumers' responses for all sensorial attributes with accuracies higher than 74.1% for pork hams and 83.3% for Turkey hams. Copyright 2009 Elsevier Ltd. All rights reserved.

Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters.

PubMed

Galavis, Paulina E; Hollensen, Christian; Jallow, Ngoneh; Paliwal, Bhudatt; Jeraj, Robert

2010-10-01

Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes and reconstruction parameters. Twenty patients with solid tumors underwent PET/CT scans on a GE Discovery VCT scanner, 45-60 minutes post-injection of 10 mCi of [(18)F]FDG. Scans were acquired in both 2D and 3D modes. For each acquisition the raw PET data was reconstructed using five different reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. Fifty textural features were classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range ≤ 5%) were entropy-first order, energy, maximal correlation coefficient (second order feature) and low-gray level run emphasis (high-order feature). The features with intermediate variability (10% ≤ range ≤ 25%) were entropy-GLCM, sum entropy, high gray level run emphsis, gray level non-uniformity, small number emphasis, and entropy-NGL. Forty remaining features presented large variations (range > 30%). Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small variations due to different acquisition modes and reconstruction parameters. Features with low level of variations are better candidates for reproducible tumor segmentation. Even though features such as contrast-NGTD, coarseness, homogeneity, and busyness have been previously used, our data indicated that these features presented large variations, therefore they could not be considered as a good candidates for tumor segmentation.

Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters

PubMed Central

GALAVIS, PAULINA E.; HOLLENSEN, CHRISTIAN; JALLOW, NGONEH; PALIWAL, BHUDATT; JERAJ, ROBERT

2014-01-01

Background Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes and reconstruction parameters. Material and methods Twenty patients with solid tumors underwent PET/CT scans on a GE Discovery VCT scanner, 45–60 minutes post-injection of 10 mCi of [18F]FDG. Scans were acquired in both 2D and 3D modes. For each acquisition the raw PET data was reconstructed using five different reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. Results Fifty textural features were classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range ≤ 5%) were entropy-first order, energy, maximal correlation coefficient (second order feature) and low-gray level run emphasis (high-order feature). The features with intermediate variability (10% ≤ range ≤ 25%) were entropy-GLCM, sum entropy, high gray level run emphsis, gray level non-uniformity, small number emphasis, and entropy-NGL. Forty remaining features presented large variations (range > 30%). Conclusion Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small variations due to different acquisition modes and reconstruction parameters. Features with low level of variations are better candidates for reproducible tumor segmentation. Even though features such as contrast-NGTD, coarseness, homogeneity, and busyness have been previously used, our data indicated that these features presented large variations, therefore they could not be considered as a good candidates for tumor segmentation. PMID:20831489

Entanglement quantification by local unitary operations

NASA Astrophysics Data System (ADS)

Monras, A.; Adesso, G.; Giampaolo, S. M.; Gualdi, G.; Davies, G. B.; Illuminati, F.

2011-07-01

Invariance under local unitary operations is a fundamental property that must be obeyed by every proper measure of quantum entanglement. However, this is not the only aspect of entanglement theory where local unitary operations play a relevant role. In the present work we show that the application of suitable local unitary operations defines a family of bipartite entanglement monotones, collectively referred to as “mirror entanglement.” They are constructed by first considering the (squared) Hilbert-Schmidt distance of the state from the set of states obtained by applying to it a given local unitary operator. To the action of each different local unitary operator there corresponds a different distance. We then minimize these distances over the sets of local unitary operations with different spectra, obtaining an entire family of different entanglement monotones. We show that these mirror-entanglement monotones are organized in a hierarchical structure, and we establish the conditions that need to be imposed on the spectrum of a local unitary operator for the associated mirror entanglement to be faithful, i.e., to vanish in and only in separable pure states. We analyze in detail the properties of one particularly relevant member of the family, the “stellar mirror entanglement” associated with the traceless local unitary operations with nondegenerate spectra and equispaced eigenvalues in the complex plane. This particular measure generalizes the original analysis of S. M. Giampaolo and F. Illuminati [Phys. Rev. APLRAAN1050-294710.1103/PhysRevA.76.042301 76, 042301 (2007)], valid for qubits and qutrits. We prove that the stellar entanglement is a faithful bipartite entanglement monotone in any dimension and that it is bounded from below by a function proportional to the linear entropy and from above by the linear entropy itself, coinciding with it in two- and three-dimensional spaces.

Entanglement quantification by local unitary operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Monras, A.; Giampaolo, S. M.; Gualdi, G.

2011-07-15

Invariance under local unitary operations is a fundamental property that must be obeyed by every proper measure of quantum entanglement. However, this is not the only aspect of entanglement theory where local unitary operations play a relevant role. In the present work we show that the application of suitable local unitary operations defines a family of bipartite entanglement monotones, collectively referred to as ''mirror entanglement.'' They are constructed by first considering the (squared) Hilbert-Schmidt distance of the state from the set of states obtained by applying to it a given local unitary operator. To the action of each different localmore » unitary operator there corresponds a different distance. We then minimize these distances over the sets of local unitary operations with different spectra, obtaining an entire family of different entanglement monotones. We show that these mirror-entanglement monotones are organized in a hierarchical structure, and we establish the conditions that need to be imposed on the spectrum of a local unitary operator for the associated mirror entanglement to be faithful, i.e., to vanish in and only in separable pure states. We analyze in detail the properties of one particularly relevant member of the family, the ''stellar mirror entanglement'' associated with the traceless local unitary operations with nondegenerate spectra and equispaced eigenvalues in the complex plane. This particular measure generalizes the original analysis of S. M. Giampaolo and F. Illuminati [Phys. Rev. A 76, 042301 (2007)], valid for qubits and qutrits. We prove that the stellar entanglement is a faithful bipartite entanglement monotone in any dimension and that it is bounded from below by a function proportional to the linear entropy and from above by the linear entropy itself, coinciding with it in two- and three-dimensional spaces.« less

Holographic calculation for large interval Rényi entropy at high temperature

NASA Astrophysics Data System (ADS)

Chen, Bin; Wu, Jie-qiang

2015-11-01

In this paper, we study the holographic Rényi entropy of a large interval on a circle at high temperature for the two-dimensional conformal field theory (CFT) dual to pure AdS3 gravity. In the field theory, the Rényi entropy is encoded in the CFT partition function on n -sheeted torus connected with each other by a large branch cut. As proposed by Chen and Wu [Large interval limit of Rényi entropy at high temperature, arXiv:1412.0763], the effective way to read the entropy in the large interval limit is to insert a complete set of state bases of the twist sector at the branch cut. Then the calculation transforms into an expansion of four-point functions in the twist sector with respect to e-2/π T R n . By using the operator product expansion of the twist operators at the branch points, we read the first few terms of the Rényi entropy, including the leading and next-to-leading contributions in the large central charge limit. Moreover, we show that the leading contribution is actually captured by the twist vacuum module. In this case by the Ward identity the four-point functions can be derived from the correlation function of four twist operators, which is related to double interval entanglement entropy. Holographically, we apply the recipe in [T. Faulkner, The entanglement Rényi entropies of disjoint intervals in AdS/CFT, arXiv:1303.7221] and [T. Barrella et al., Holographic entanglement beyond classical gravity, J. High Energy Phys. 09 (2013) 109] to compute the classical Rényi entropy and its one-loop quantum correction, after imposing a new set of monodromy conditions. The holographic classical result matches exactly with the leading contribution in the field theory up to e-4 π T R and l6, while the holographical one-loop contribution is in exact agreement with next-to-leading results in field theory up to e-6/π T R n and l4 as well.

Inferring the effects of potential dispersal routes on the metacommunity structure of stream insects: as the crow flies, as the fish swims or as the fox runs?

PubMed

Kärnä, Olli-Matti; Grönroos, Mira; Antikainen, Harri; Hjort, Jan; Ilmonen, Jari; Paasivirta, Lauri; Heino, Jani

2015-09-01

1. Metacommunity research relies largely on proxies for inferring the effect of dispersal on local community structure. Overland and watercourse distances have been typically used as such proxies. A good proxy for dispersal should, however, take into account more complex landscape features that can affect an organism's movement and dispersal. The cost distance approach does just that, allowing determining the path of least resistance across a landscape. 2. Here, we examined the distance decay of assemblage similarity within a subarctic stream insect metacommunity. We tested whether overland, watercourse and cumulative cost distances performed differently as correlates of dissimilarity in assemblage composition between sites. We also investigated the effect of body size and dispersal mode on metacommunity organization. 3. We found that dissimilarities in assemblage composition correlated more strongly with environmental than physical distances between sites. Overland and watercourse distances showed similar correlations to assemblage dissimilarity between sites, being sometimes significantly correlated with biological variation of entire insect communities. In metacommunities deconstructed by body size or dispersal mode, contrary to our expectation, passive dispersers showed a slightly stronger correlation than active dispersers to environmental differences between sites, although passive dispersers also showed a stronger correlation than active dispersers to physical distances between sites. The strength of correlation between environmental distance and biological dissimilarity also varied slightly among the body size classes. 4. After controlling for environmental differences between sites, cumulative cost distances were slightly better correlates of biological dissimilarities than overland or watercourse distances between sites. However, quantitative differences in correlation coefficients were small between different physical distances. 5. Although environmental differences typically override physical distances as determinants of the composition of stream insect assemblages, correlations between environmental distances and biological dissimilarities are typically rather weak. This undetermined variation may be attributable to dispersal processes, which may be captured using better proxies for the process. We suggest that further modifying the measurement of cost distances may be a fruitful avenue, especially if complemented by more direct natural history information on insect dispersal behaviour and distances travelled by them. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levay, Peter; Nagy, Szilvia; Pipek, Janos

An elementary formula for the von Neumann and Renyi entropies describing quantum correlations in two-fermionic systems having four single-particle states is presented. An interesting geometric structure of fermionic entanglement is revealed. A connection with the generalized Pauli principle is established.

Inferring the Presence of Reverse Proxies Through Timing Analysis

DTIC Science & Technology

2015-06-01

16 Figure 3.2 The three different instances of timing measurement configurations 17 Figure 3.3 Permutation of a web request iteration...Their data showed that they could detect at least 6 bits of entropy between unlike devices and that it was enough to determine that they are in fact...depending on the permutation being executed so that every iteration was conducted under the same distance 15 City   Lat   Long   City   Lat   Long

Deconfinement as an entropic self-destruction: A solution for the quarkonium suppression puzzle?

DOE PAGES

Kharzeev, Dmitri E.

2014-10-02

The entropic approach to dissociation of bound states immersed in strongly coupled systems is developed. In such systems, the excitations of the bound state are often delocalized and characterized by a large entropy, so that the bound state is strongly entangled with the rest of the statistical system. If this entropy S increases with the separation r between the constituents of the bound state, S=S(r), then the resulting entropic force F=T ∂S/∂r (T is temperature) can drive the dissociation process. As a specific example, we consider the case of heavy quarkonium in strongly coupled quark-gluon plasma, where lattice QCD indicatesmore » a large amount of entropy associated with the heavy quark pair at temperatures 0.9T c ≤ T ≤ 1.5T c (T c is the deconfinement temperature); this entropy S(r) grows with the interquark distance r. We argue that the entropic mechanism results in an anomalously strong quarkonium suppression in the temperature range near T c. This entropic self-destruction may thus explain why the experimentally measured quarkonium nuclear modification factor at RHIC (lower energy density) is smaller than at LHC (higher energy density), possibly resolving the “quarkonium suppression puzzle”—all of the previously known mechanisms of quarkonium dissociation operate more effectively at higher energy densities, and this contradicts the data. As a result, we find that near T c the entropic force leads to delocalization of the bound hadron states; we argue that this delocalization may be the mechanism underlying deconfinement.« less

Detection of periodicity based on independence tests - III. Phase distance correlation periodogram

NASA Astrophysics Data System (ADS)

Zucker, Shay

2018-02-01

I present the Phase Distance Correlation (PDC) periodogram - a new periodicity metric, based on the Distance Correlation concept of Gábor Székely. For each trial period, PDC calculates the distance correlation between the data samples and their phases. PDC requires adaptation of the Székely's distance correlation to circular variables (phases). The resulting periodicity metric is best suited to sparse data sets, and it performs better than other methods for sawtooth-like periodicities. These include Cepheid and RR-Lyrae light curves, as well as radial velocity curves of eccentric spectroscopic binaries. The performance of the PDC periodogram in other contexts is almost as good as that of the Generalized Lomb-Scargle periodogram. The concept of phase distance correlation can be adapted also to astrometric data, and it has the potential to be suitable also for large evenly spaced data sets, after some algorithmic perfection.

Path-integral Monte Carlo method for Rényi entanglement entropies.

PubMed

Herdman, C M; Inglis, Stephen; Roy, P-N; Melko, R G; Del Maestro, A

2014-07-01

We introduce a quantum Monte Carlo algorithm to measure the Rényi entanglement entropies in systems of interacting bosons in the continuum. This approach is based on a path-integral ground state method that can be applied to interacting itinerant bosons in any spatial dimension with direct relevance to experimental systems of quantum fluids. We demonstrate how it may be used to compute spatial mode entanglement, particle partitioned entanglement, and the entanglement of particles, providing insights into quantum correlations generated by fluctuations, indistinguishability, and interactions. We present proof-of-principle calculations and benchmark against an exactly soluble model of interacting bosons in one spatial dimension. As this algorithm retains the fundamental polynomial scaling of quantum Monte Carlo when applied to sign-problem-free models, future applications should allow for the study of entanglement entropy in large-scale many-body systems of interacting bosons.

Novel quantum phase transition from bounded to extensive entanglement

PubMed Central

Zhang, Zhao; Ahmadain, Amr

2017-01-01

The nature of entanglement in many-body systems is a focus of intense research with the observation that entanglement holds interesting information about quantum correlations in large systems and their relation to phase transitions. In particular, it is well known that although generic, many-body states have large, extensive entropy, ground states of reasonable local Hamiltonians carry much smaller entropy, often associated with the boundary length through the so-called area law. Here we introduce a continuous family of frustration-free Hamiltonians with exactly solvable ground states and uncover a remarkable quantum phase transition whereby the entanglement scaling changes from area law into extensively large entropy. This transition shows that entanglement in many-body systems may be enhanced under special circumstances with a potential for generating “useful” entanglement for the purpose of quantum computing and that the full implications of locality and its restrictions on possible ground states may hold further surprises. PMID:28461464

Novel quantum phase transition from bounded to extensive entanglement.

PubMed

Zhang, Zhao; Ahmadain, Amr; Klich, Israel

2017-05-16

The nature of entanglement in many-body systems is a focus of intense research with the observation that entanglement holds interesting information about quantum correlations in large systems and their relation to phase transitions. In particular, it is well known that although generic, many-body states have large, extensive entropy, ground states of reasonable local Hamiltonians carry much smaller entropy, often associated with the boundary length through the so-called area law. Here we introduce a continuous family of frustration-free Hamiltonians with exactly solvable ground states and uncover a remarkable quantum phase transition whereby the entanglement scaling changes from area law into extensively large entropy. This transition shows that entanglement in many-body systems may be enhanced under special circumstances with a potential for generating "useful" entanglement for the purpose of quantum computing and that the full implications of locality and its restrictions on possible ground states may hold further surprises.

Analysis of natural convection in nanofluid-filled H-shaped cavity by entropy generation and heatline visualization using lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Rahimi, Alireza; Sepehr, Mohammad; Lariche, Milad Janghorban; Mesbah, Mohammad; Kasaeipoor, Abbas; Malekshah, Emad Hasani

2018-03-01

The lattice Boltzmann simulation of natural convection in H-shaped cavity filled with nanofluid is performed. The entropy generation analysis and heatline visualization are employed to analyze the considered problem comprehensively. The produced nanofluid is SiO2-TiO2/Water-EG (60:40) hybrid nanofluid, and the thermal conductivity and dynamic viscosity of used nanofluid are measured experimentally. To use the experimental data of thermal conductivity and dynamic viscosity, two sets of correlations based on temperature for six different solid volume fractions of 0.5, 1, 1.5, 2, 2.5 and 3 vol% are derived. The influences of different governing parameters such different aspect ratio, solid volume fractions of nanofluid and Rayleigh numbers on the fluid flow, temperature filed, average/local Nusselt number, total/local entropy generation and heatlines are presented.

Entropy Conservation of Linear Dilaton Black Holes in Quantum Corrected Hawking Radiation

NASA Astrophysics Data System (ADS)

Sakalli, I.; Halilsoy, M.; Pasaoglu, H.

2011-10-01

It has been shown recently that information is lost in the Hawking radiation of the linear dilaton black holes in various theories when applying the tunneling formalism of Parikh and Wilczek without considering quantum gravity effects. In this paper, we recalculate the emission probability by taking into account the log-area correction to the Bekenstein-Hawking entropy and the statistical correlation between quanta emitted. The crucial role of the quantum gravity effects on the information leakage and black hole remnant is highlighted. The entropy conservation of the linear dilaton black holes is discussed in detail. We also model the remnant as an extreme linear dilaton black hole with a pointlike horizon in order to show that such a remnant cannot radiate and its temperature becomes zero. In summary, we show that the information can also leak out of the linear dilaton black holes together with preserving unitarity in quantum mechanics.

Fuzzy geometry, entropy, and image information

NASA Technical Reports Server (NTRS)

Pal, Sankar K.

1991-01-01

Presented here are various uncertainty measures arising from grayness ambiguity and spatial ambiguity in an image, and their possible applications as image information measures. Definitions are given of an image in the light of fuzzy set theory, and of information measures and tools relevant for processing/analysis e.g., fuzzy geometrical properties, correlation, bound functions and entropy measures. Also given is a formulation of algorithms along with management of uncertainties for segmentation and object extraction, and edge detection. The output obtained here is both fuzzy and nonfuzzy. Ambiguity in evaluation and assessment of membership function are also described.

LiDAR-Derived Surface Roughness Signatures of Basaltic Lava Types at the Muliwai a Pele Lava Channel, Mauna Ulu, Hawai'i

NASA Technical Reports Server (NTRS)

Whelley, Patrick L.; Garry, W. Brent; Hamilton, Christopher W.; Bleacher, Jacob E.

2017-01-01

We used light detection and ranging (LiDAR) data to calculate roughness patterns (homogeneity, mean-roughness, and entropy) for five lava types at two different resolutions (1.5 and 0.1 m/pixel). We found that end-member types (a a and pahoehoe) are separable (with 95% confidence) at both scales, indicating that roughness patterns are well suited for analyzing types of lava. Intermediate lavas were also explored, and we found that slabby-pahoehoe is separable from the other end-members using 1.5 m/pixel data, but not in the 0.1 m/pixel analysis. This suggests that the conversion from pahoehoe to slabby-pahoehoe is a meter-scale process, and the finer roughness characteristics of pahoehoe, such as ropes and toes, are not significantly affected. Furthermore, we introduce the ratio ENT/HOM (derived from lava roughness) as a proxy for assessing local lava flow rate from topographic data. High entropy and low homogeneity regions correlate with high flow rate while low entropy and high homogeneity regions correlate with low flow rate.We suggest that this relationship is not directional, rather it is apparent through roughness differences of the associated lava type emplaced at the high and low rates, respectively.

Characterizing groundwater quality ranks for drinking purposes in Sylhet district, Bangladesh, using entropy method, spatial autocorrelation index, and geostatistics.

PubMed

Islam, Abu Reza Md Towfiqul; Ahmed, Nasir; Bodrud-Doza, Md; Chu, Ronghao

2017-12-01

Drinking water is susceptible to the poor quality of contaminated water affecting the health of humans. Thus, it is an essential study to investigate factors affecting groundwater quality and its suitability for drinking uses. In this paper, the entropy theory, multivariate statistics, spatial autocorrelation index, and geostatistics are applied to characterize groundwater quality and its spatial variability in the Sylhet district of Bangladesh. A total of 91samples have been collected from wells (e.g., shallow, intermediate, and deep tube wells at 15-300-m depth) from the study area. The results show that NO 3 - , then SO 4 2- , and As are the most contributed parameters influencing the groundwater quality according to the entropy theory. The principal component analysis (PCA) and correlation coefficient also confirm the results of the entropy theory. However, Na + has the highest spatial autocorrelation and the most entropy, thus affecting the groundwater quality. Based on the entropy-weighted water quality index (EWQI) and groundwater quality index (GWQI) classifications, it is observed that 60.45 and 53.86% of water samples are classified as having an excellent to good qualities, while the remaining samples vary from medium to extremely poor quality domains for drinking purposes. Furthermore, the EWQI classification provides the more reasonable results than GWQIs due to its simplicity, accuracy, and ignoring of artificial weight. A Gaussian semivariogram model has been chosen to the best fit model, and groundwater quality indices have a weak spatial dependence, suggesting that both geogenic and anthropogenic factors play a pivotal role in spatial heterogeneity of groundwater quality oscillations.

SU-F-R-13: Decoding 18F-FDG Uptake Heterogeneity for Primary and Lymphoma Tumors by Using Texture Analysis in PET Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, C; Yin, Y

Purpose: To explore 18F-FDG uptake heterogeneity of primary tumor and lymphoma tumor by texture features of PET image and quantify the heterogeneity difference between primary tumor and lymphoma tumor. Methods: 18 patients with primary tumor and lymphoma tumor in lung cancer were enrolled. All patients underwent whole-body 18F-FDG PET/CT scans before treatment. Texture features, based on Gray-level Co-occurrence Matrix, second and high order matrices are extracted from code using MATLAB software to quantify 18F-FDG uptake heterogeneity. The relationships of volume between energy, entropy, correlation, homogeneity and contrast were analyzed. Results: For different cases, tumor heterogeneity was not the same. Texturemore » parameters (contrast, entropy, and correlation) of lymphoma were lower than primary tumor. On the contrast, the texture parameters (energy, homogeneity and inverse different moment) of lymphoma were higher than primary tumor. Significantly, correlations were observed between volume and energy (primary, r=−0.194, p=0.441; lymphoma, r=−0.339, p=0.582), homogeneity (primary, r=−0.146, p=0.382; lymphoma, r=−0.193, p=0.44), inverse difference moment (primary, r=−0.14, p=0.374; lymphoma, r=−0.172, p=0.414) and a positive correlation between volume and entropy (primary, r=0.233, p=0.483; lymphoma, r=0.462, p=0.680), contrast (primary, r=0.159, p=0.399; lymphoma, r=0.341, p=0.584), correlation (primary, r=0.027, p=0.165; lymphoma, r=0.046, p=0.215). For the same patient, energy for primary and lymphoma tumor is equal. The volume of lymphoma is smaller than primary tumor, but the homogeneity were higher than primary tumor. Conclusion: This study showed that there were effective heterogeneity differences between primary and lymphoma tumor by FDG-PET image texture analysis.« less

The Generalization of Mutual Information as the Information between a Set of Variables: The Information Correlation Function Hierarchy and the Information Structure of Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Wolf, David R.

2004-01-01

The topic of this paper is a hierarchy of information-like functions, here named the information correlation functions, where each function of the hierarchy may be thought of as the information between the variables it depends upon. The information correlation functions are particularly suited to the description of the emergence of complex behaviors due to many- body or many-agent processes. They are particularly well suited to the quantification of the decomposition of the information carried among a set of variables or agents, and its subsets. In more graphical language, they provide the information theoretic basis for understanding the synergistic and non-synergistic components of a system, and as such should serve as a forceful toolkit for the analysis of the complexity structure of complex many agent systems. The information correlation functions are the natural generalization to an arbitrary number of sets of variables of the sequence starting with the entropy function (one set of variables) and the mutual information function (two sets). We start by describing the traditional measures of information (entropy) and mutual information.

Measuring entanglement entropy in a quantum many-body system.

PubMed

Islam, Rajibul; Ma, Ruichao; Preiss, Philipp M; Tai, M Eric; Lukin, Alexander; Rispoli, Matthew; Greiner, Markus

2015-12-03

Entanglement is one of the most intriguing features of quantum mechanics. It describes non-local correlations between quantum objects, and is at the heart of quantum information sciences. Entanglement is now being studied in diverse fields ranging from condensed matter to quantum gravity. However, measuring entanglement remains a challenge. This is especially so in systems of interacting delocalized particles, for which a direct experimental measurement of spatial entanglement has been elusive. Here, we measure entanglement in such a system of itinerant particles using quantum interference of many-body twins. Making use of our single-site-resolved control of ultracold bosonic atoms in optical lattices, we prepare two identical copies of a many-body state and interfere them. This enables us to directly measure quantum purity, Rényi entanglement entropy, and mutual information. These experiments pave the way for using entanglement to characterize quantum phases and dynamics of strongly correlated many-body systems.

Autofocusing in digital holography using deep learning

NASA Astrophysics Data System (ADS)

Ren, Zhenbo; Xu, Zhimin; Lam, Edmund Y.

2018-02-01

In digital holography, it is critical to know the distance in order to reconstruct the multi-sectional object. This autofocusing is traditionally solved by reconstructing a stack of in-focus and out-of-focus images and using some focus metric, such as entropy or variance, to calculate the sharpness of each reconstructed image. Then the distance corresponding to the sharpest image is determined as the focal position. This method is effective but computationally demanding and time-consuming. To get an accurate estimation, one has to reconstruct many images. Sometimes after a coarse search, a refinement is needed. To overcome this problem in autofocusing, we propose to use deep learning, i.e., a convolutional neural network (CNN), to solve this problem. Autofocusing is viewed as a classification problem, in which the true distance is transferred as a label. To estimate the distance is equated to labeling a hologram correctly. To train such an algorithm, totally 1000 holograms are captured under the same environment, i.e., exposure time, incident angle, object, except the distance. There are 5 labels corresponding to 5 distances. These data are randomly split into three datasets to train, validate and test a CNN network. Experimental results show that the trained network is capable of predicting the distance without reconstructing or knowing any physical parameters about the setup. The prediction time using this method is far less than traditional autofocusing methods.

A new complexity measure for time series analysis and classification

NASA Astrophysics Data System (ADS)

Nagaraj, Nithin; Balasubramanian, Karthi; Dey, Sutirth

2013-07-01

Complexity measures are used in a number of applications including extraction of information from data such as ecological time series, detection of non-random structure in biomedical signals, testing of random number generators, language recognition and authorship attribution etc. Different complexity measures proposed in the literature like Shannon entropy, Relative entropy, Lempel-Ziv, Kolmogrov and Algorithmic complexity are mostly ineffective in analyzing short sequences that are further corrupted with noise. To address this problem, we propose a new complexity measure ETC and define it as the "Effort To Compress" the input sequence by a lossless compression algorithm. Here, we employ the lossless compression algorithm known as Non-Sequential Recursive Pair Substitution (NSRPS) and define ETC as the number of iterations needed for NSRPS to transform the input sequence to a constant sequence. We demonstrate the utility of ETC in two applications. ETC is shown to have better correlation with Lyapunov exponent than Shannon entropy even with relatively short and noisy time series. The measure also has a greater rate of success in automatic identification and classification of short noisy sequences, compared to entropy and a popular measure based on Lempel-Ziv compression (implemented by Gzip).

Causality, transfer entropy, and allosteric communication landscapes in proteins with harmonic interactions.

PubMed

Hacisuleyman, Aysima; Erman, Burak

2017-06-01

A fast and approximate method of generating allosteric communication landscapes in proteins is presented by using Schreiber's entropy transfer concept in combination with the Gaussian Network Model of proteins. Predictions of the model and the allosteric communication landscapes generated show that information transfer in proteins does not necessarily take place along a single path, but an ensemble of pathways is possible. The model emphasizes that knowledge of entropy only is not sufficient for determining allosteric communication and additional information based on time delayed correlations should be introduced, which leads to the presence of causality in proteins. The model provides a simple tool for mapping entropy sink-source relations into pairs of residues. By this approach, residues that should be manipulated to control protein activity may be determined. This should be of great importance for allosteric drug design and for understanding the effects of mutations on function. The model is applied to determine allosteric communication in three proteins, Ubiquitin, Pyruvate Kinase, and the PDZ domain. Predictions are in agreement with molecular dynamics simulations and experimental evidence. Proteins 2017; 85:1056-1064. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Thermal coefficients of the methyl groups within ubiquitin

PubMed Central

Sabo, T Michael; Bakhtiari, Davood; Walter, Korvin F A; McFeeters, Robert L; Giller, Karin; Becker, Stefan; Griesinger, Christian; Lee, Donghan

2012-01-01

Physiological processes such as protein folding and molecular recognition are intricately linked to their dynamic signature, which is reflected in their thermal coefficient. In addition, the local conformational entropy is directly related to the degrees of freedom, which each residue possesses within its conformational space. Therefore, the temperature dependence of the local conformational entropy may provide insight into understanding how local dynamics may affect the stability of proteins. Here, we analyze the temperature dependence of internal methyl group dynamics derived from the cross-correlated relaxation between dipolar couplings of two CH bonds within ubiquitin. Spanning a temperature range from 275 to 308 K, internal methyl group dynamics tend to increase with increasing temperature, which translates to a general increase in local conformational entropy. With this data measured over multiple temperatures, the thermal coefficient of the methyl group order parameter, the characteristic thermal coefficient, and the local heat capacity were obtained. By analyzing the distribution of methyl group thermal coefficients within ubiquitin, we found that the N-terminal region has relatively high thermostability. These results indicate that methyl groups contribute quite appreciably to the total heat capacity of ubiquitin through the regulation of local conformational entropy. PMID:22334336

Configurational entropy as a lifetime predictor and pattern discriminator for oscillons

NASA Astrophysics Data System (ADS)

Gleiser, Marcelo; Stephens, Michelle; Sowinski, Damian

2018-05-01

Oscillons are long-lived, spherically symmetric, attractor scalar field configurations that emerge as certain field configurations evolve in time. It has been known for many years that there is a direct correlation between the initial configuration's shape and the resulting oscillon lifetime: a shape memory. In this paper, we use an information-entropic measure of spatial complexity known as differential configurational entropy (DCE) to obtain estimates of oscillon lifetimes in scalar field theories with symmetric and asymmetric double-well potentials. The time-dependent DCE is built from the Fourier transform of the two-point correlation function of the energy density of the scalar field configuration. We obtain a scaling law correlating oscillon lifetimes and measures obtained from its evolving DCE. For the symmetric double well, for example, we show that we can apply DCE to predict an oscillon's lifetime with an average accuracy of 6% or better. We also show that the DCE acts as a pattern discriminator, able to distinguish initial configurations that evolve into long-lived oscillons from other nonperturbative short-lived fluctuations.

Phase space gradient of dissipated work and information: A role of relative Fisher information

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamano, Takuya, E-mail: yamano@amy.hi-ho.ne.jp

2013-11-15

We show that an information theoretic distance measured by the relative Fisher information between canonical equilibrium phase densities corresponding to forward and backward processes is intimately related to the gradient of the dissipated work in phase space. We present a universal constraint on it via the logarithmic Sobolev inequality. Furthermore, we point out that a possible expression of the lower bound indicates a deep connection in terms of the relative entropy and the Fisher information of the canonical distributions.

Computer simulation of the carbon activity in austenite

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murch, G.E.; Thorn, R.J.

1979-02-01

Carbon activity in austenite is described in terms of an Ising-like f.c.c. lattice gas model in which carbon interstitials repel only at the distance of nearest neighbors. A Monte Carlo simulation method in the petit canonical ensemble is employed to calculate directly the carbon activity as a function of composition and temperature. The computed activities are in satisfactory agreement with the experimental data, similarly for the decompostion of the activity to the partial molar enthalpy and entropy.

Analog Correlator Based on One Bit Digital Correlator

NASA Technical Reports Server (NTRS)

Prokop, Norman (Inventor); Krasowski, Michael (Inventor)

2017-01-01

A two input time domain correlator may perform analog correlation. In order to achieve high throughput rates with reduced or minimal computational overhead, the input data streams may be hard limited through adaptive thresholding to yield two binary bit streams. Correlation may be achieved through the use of a Hamming distance calculation, where the distance between the two bit streams approximates the time delay that separates them. The resulting Hamming distance approximates the correlation time delay with high accuracy.

Correlation of the Y-Balance Test with Lower-limb Strength of Adult Women

PubMed Central

Lee, Dong-Kyu; Kim, Gyoung-Mo; Ha, Sung-Min; Oh, Jae-Seop

2014-01-01

[Purpose] The purpose of this study was to elucidate the relationship between Y-balance test (YBT) distance and the lower-limb strength of adult women. [Subjects] Forty women aged 45 to 80 years volunteered for this study. [Methods] The participants were tested for maximal muscle strength of the lower limbs (hip extensors, hip flexors, hip abductors, knee extensors, knee flexors, and ankle dorsiflexors) and YBT distances in the anterior, posteromedial, and posterolateral directions. Pearson’s correlation coefficient was used to quantify the linear relationships between YBT distances and lower-limb strength. [Results] Hip extensor and knee flexor strength were positively correlated with YBT anterior distance. Hip extensor, hip abductor, and knee flexor strength were positively correlated with the YBT posteromedial distance. Hip extensor and knee flexor strength were positively correlated with YBT posterolateral distance. [Conclusion] There was a weak correlation between lower-limb strength (hip extensors, hip abductors, and knee flexors) and dynamic postural control as measured by the YBT. PMID:24926122

Frustration in protein elastic network models

NASA Astrophysics Data System (ADS)

Lezon, Timothy; Bahar, Ivet

2010-03-01

Elastic network models (ENMs) are widely used for studying the equilibrium dynamics of proteins. The most common approach in ENM analysis is to adopt a uniform force constant or a non-specific distance dependent function to represent the force constant strength. Here we discuss the influence of sequence and structure in determining the effective force constants between residues in ENMs. Using a novel method based on entropy maximization, we optimize the force constants such that they exactly reporduce a subset of experimentally determined pair covariances for a set of proteins. We analyze the optimized force constants in terms of amino acid types, distances, contact order and secondary structure, and we demonstrate that including frustrated interactions in the ENM is essential for accurately reproducing the global modes in the middle of the frequency spectrum.

Quantum Discord in Photon-Added Glauber Coherent States of GHZ-Type

NASA Astrophysics Data System (ADS)

Daoud, M.; Kaydi, W.; El Hadfi, H.

2015-11-01

We investigate the influence of photon excitations on quantum correlations in tripartite Glauber coherent states of Greenberger-Horne-Zeilinger type (GHZ-type). The pairwise correlations are measured by means of the entropy-based quantum discord. We also analyze the monogamy property of quantum discord in this class of tripartite states in terms of the strength of Glauber coherent states and the photon excitation order.

A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring

PubMed Central

Li, Xiaoli; Li, Duan; Li, Yongwang; Ursino, Mauro

2016-01-01

Objective Multiscale permutation entropy (MSPE) is becoming an interesting tool to explore neurophysiological mechanisms in recent years. In this study, six MSPE measures were proposed for on-line depth of anesthesia (DoA) monitoring to quantify the anesthetic effect on the real-time EEG recordings. The performance of these measures in describing the transient characters of simulated neural populations and clinical anesthesia EEG were evaluated and compared. Methods Six MSPE algorithms—derived from Shannon permutation entropy (SPE), Renyi permutation entropy (RPE) and Tsallis permutation entropy (TPE) combined with the decomposition procedures of coarse-graining (CG) method and moving average (MA) analysis—were studied. A thalamo-cortical neural mass model (TCNMM) was used to generate noise-free EEG under anesthesia to quantitatively assess the robustness of each MSPE measure against noise. Then, the clinical anesthesia EEG recordings from 20 patients were analyzed with these measures. To validate their effectiveness, the ability of six measures were compared in terms of tracking the dynamical changes in EEG data and the performance in state discrimination. The Pearson correlation coefficient (R) was used to assess the relationship among MSPE measures. Results CG-based MSPEs failed in on-line DoA monitoring at multiscale analysis. In on-line EEG analysis, the MA-based MSPE measures at 5 decomposed scales could track the transient changes of EEG recordings and statistically distinguish the awake state, unconsciousness and recovery of consciousness (RoC) state significantly. Compared to single-scale SPE and RPE, MSPEs had better anti-noise ability and MA-RPE at scale 5 performed best in this aspect. MA-TPE outperformed other measures with faster tracking speed of the loss of unconsciousness. Conclusions MA-based multiscale permutation entropies have the potential for on-line anesthesia EEG analysis with its simple computation and sensitivity to drug effect changes. CG-based multiscale permutation entropies may fail to describe the characteristics of EEG at high decomposition scales. PMID:27723803

A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring.

PubMed

Su, Cui; Liang, Zhenhu; Li, Xiaoli; Li, Duan; Li, Yongwang; Ursino, Mauro

2016-01-01

Multiscale permutation entropy (MSPE) is becoming an interesting tool to explore neurophysiological mechanisms in recent years. In this study, six MSPE measures were proposed for on-line depth of anesthesia (DoA) monitoring to quantify the anesthetic effect on the real-time EEG recordings. The performance of these measures in describing the transient characters of simulated neural populations and clinical anesthesia EEG were evaluated and compared. Six MSPE algorithms-derived from Shannon permutation entropy (SPE), Renyi permutation entropy (RPE) and Tsallis permutation entropy (TPE) combined with the decomposition procedures of coarse-graining (CG) method and moving average (MA) analysis-were studied. A thalamo-cortical neural mass model (TCNMM) was used to generate noise-free EEG under anesthesia to quantitatively assess the robustness of each MSPE measure against noise. Then, the clinical anesthesia EEG recordings from 20 patients were analyzed with these measures. To validate their effectiveness, the ability of six measures were compared in terms of tracking the dynamical changes in EEG data and the performance in state discrimination. The Pearson correlation coefficient (R) was used to assess the relationship among MSPE measures. CG-based MSPEs failed in on-line DoA monitoring at multiscale analysis. In on-line EEG analysis, the MA-based MSPE measures at 5 decomposed scales could track the transient changes of EEG recordings and statistically distinguish the awake state, unconsciousness and recovery of consciousness (RoC) state significantly. Compared to single-scale SPE and RPE, MSPEs had better anti-noise ability and MA-RPE at scale 5 performed best in this aspect. MA-TPE outperformed other measures with faster tracking speed of the loss of unconsciousness. MA-based multiscale permutation entropies have the potential for on-line anesthesia EEG analysis with its simple computation and sensitivity to drug effect changes. CG-based multiscale permutation entropies may fail to describe the characteristics of EEG at high decomposition scales.

Holographic entanglement entropy in Suzuki-Trotter decomposition of spin systems.

PubMed

Matsueda, Hiroaki

2012-03-01

In quantum spin chains at criticality, two types of scaling for the entanglement entropy exist: one comes from conformal field theory (CFT), and the other is for entanglement support of matrix product state (MPS) approximation. On the other hand, the quantum spin-chain models can be mapped onto two-dimensional (2D) classical ones by the Suzuki-Trotter decomposition. Motivated by the scaling and the mapping, we introduce information entropy for 2D classical spin configurations as well as a spectrum, and examine their basic properties in the Ising and the three-state Potts models on the square lattice. They are defined by the singular values of the reduced density matrix for a Monte Carlo snapshot. We find scaling relations of the entropy compatible with the CFT and the MPS results. Thus, we propose that the entropy is a kind of "holographic" entanglement entropy. At T(c), the spin configuration is fractal, and various sizes of ordered clusters coexist. Then, the singular values automatically decompose the original snapshot into a set of images with different length scales, respectively. This is the origin of the scaling. In contrast to the MPS scaling, long-range spin correlation can be described by only few singular values. Furthermore, the spectrum, which is a set of logarithms of the singular values, also seems to be a holographic entanglement spectrum. We find multiple gaps in the spectrum, and in contrast to the topological phases, the low-lying levels below the gap represent spontaneous symmetry breaking. These contrasts are strong evidence of the dual nature of the holography. Based on these observations, we discuss the amount of information contained in one snapshot.

Effect of rotation preference on spontaneous alternation behavior on Y maze and introduction of a new analytical method, entropy of spontaneous alternation.

PubMed

Bak, Jia; Pyeon, Hae-In; Seok, Jin-I; Choi, Yun-Sik

2017-03-01

Y maze has been used to test spatial working memory in rodents. To this end, the percentage of spontaneous alternation has been employed. Alternation indicates sequential entries into all three arms; e.g., when an animal visits all three arms clockwise or counterclockwise sequentially, alternation is achieved. Interestingly, animals have a tendency to rotate or turn to a preferred side. Thus, when an animal has a high rotation preference, this may influence their alternation behavior. Here, we have generated a new analytical method, termed entropy of spontaneous alternation, to offset the effect of rotation preference on Y maze. To validate the entropy of spontaneous alternation, we employed a free rotation test using a cylinder and a spatial working memory test on Y maze. We identified that mice showed 65.1% rotation preference on average. Importantly, the percentage of spontaneous alternation in the high preference group (more than 70% rotation to a preferred side) was significantly higher than that in the no preference group (<55%). In addition, there was a clear correlation between rotation preference on cylinder and turning preference on Y maze. On the other hand, this potential leverage effect that arose from rotation preference disappeared when the animal behavior on Y maze was analyzed with the entropy of spontaneous alternation. Further, entropy of spontaneous alternation significantly determined the loss of spatial working memory by scopolamine administration. Combined, these data indicate that the entropy of spontaneous alternation provides higher credibility when spatial working memory is evaluated using Y maze. Copyright © 2016 Elsevier B.V. All rights reserved.

Thermodynamic Basis of Selectivity in the Interactions of Tissue Inhibitors of Metalloproteinases N-domains with Matrix Metalloproteinases-1, -3, and -14*

PubMed Central

Zou, Haiyin; Wu, Ying

2016-01-01

The four tissue inhibitors of metalloproteinases (TIMPs) are potent inhibitors of the many matrixins (MMPs), except that TIMP1 weakly inhibits some MMPs, including MMP14. The broad-spectrum inhibition of MMPs by TIMPs and their N-domains (NTIMPs) is consistent with the previous isothermal titration calorimetric finding that their interactions are entropy-driven but differ in contributions from solvent and conformational entropy (ΔSsolv, ΔSconf), estimated using heat capacity changes (ΔCp). Selective engineered NTIMPs have potential applications for treating MMP-related diseases, including cancer and cardiomyopathy. Here we report isothermal titration calorimetric studies of the effects of selectivity-modifying mutations in NTIMP1 and NTIMP2 on the thermodynamics of their interactions with MMP1, MMP3, and MMP14. The weak inhibition of MMP14 by NTIMP1 reflects a large conformational entropy penalty for binding. The T98L mutation, peripheral to the NTIMP1 reactive site, enhances binding by increasing ΔSsolv but also reduces ΔSconf. However, the same mutation increases NTIMP1 binding to MMP3 in an interaction that has an unusual positive ΔCp. This indicates a decrease in solvent entropy compensated by increased conformational entropy, possibly reflecting interactions involving alternative conformers. The NTIMP2 mutant, S2D/S4A is a selective MMP1 inhibitor through electrostatic effects of a unique MMP-1 arginine. Asp-2 increases reactive site polarity, reducing ΔCp, but increases conformational entropy to maintain strong binding to MMP1. There is a strong negative correlation between ΔSsolv and ΔSconf for all characterized interactions, but the data for each MMP have characteristic ranges, reflecting intrinsic differences in the structures and dynamics of their free and inhibitor-bound forms. PMID:27033700

Using multi-scale entropy and principal component analysis to monitor gears degradation via the motor current signature analysis

NASA Astrophysics Data System (ADS)

Aouabdi, Salim; Taibi, Mahmoud; Bouras, Slimane; Boutasseta, Nadir

2017-06-01

This paper describes an approach for identifying localized gear tooth defects, such as pitting, using phase currents measured from an induction machine driving the gearbox. A new tool of anomaly detection based on multi-scale entropy (MSE) algorithm SampEn which allows correlations in signals to be identified over multiple time scales. The motor current signature analysis (MCSA) in conjunction with principal component analysis (PCA) and the comparison of observed values with those predicted from a model built using nominally healthy data. The Simulation results show that the proposed method is able to detect gear tooth pitting in current signals.

Holographic research on phase transitions for a five dimensional AdS black hole with conformally coupled scalar hair

NASA Astrophysics Data System (ADS)

Li, Hui-Ling; Yang, Shu-Zheng; Zu, Xiao-Tao

2017-01-01

In the framework of holography, we survey the phase structure for a higher dimensional hairy black hole including the effects of the scalar field hair. It is worth emphasizing that, not only black hole entropy, but also entanglement entropy and two point correlation function exhibit the Van der Waals-like phase transition in a fixed scalar charge ensemble. Furthermore, by making use of numerical computation, we show that the Maxwell's equal area law is valid for the first order phase transition. In addition, we also discuss how the hair parameter affects the black hole's phase transition.

Monte Carlo simulation of a noisy quantum channel with memory.

PubMed

Akhalwaya, Ismail; Moodley, Mervlyn; Petruccione, Francesco

2015-10-01

The classical capacity of quantum channels is well understood for channels with uncorrelated noise. For the case of correlated noise, however, there are still open questions. We calculate the classical capacity of a forgetful channel constructed by Markov switching between two depolarizing channels. Techniques have previously been applied to approximate the output entropy of this channel and thus its capacity. In this paper, we use a Metropolis-Hastings Monte Carlo approach to numerically calculate the entropy. The algorithm is implemented in parallel and its performance is studied and optimized. The effects of memory on the capacity are explored and previous results are confirmed to higher precision.

Single molecule thermodynamics in biological motors.

PubMed

Taniguchi, Yuichi; Karagiannis, Peter; Nishiyama, Masayoshi; Ishii, Yoshiharu; Yanagida, Toshio

2007-04-01

Biological molecular machines use thermal activation energy to carry out various functions. The process of thermal activation has the stochastic nature of output events that can be described according to the laws of thermodynamics. Recently developed single molecule detection techniques have allowed each distinct enzymatic event of single biological machines to be characterized providing clues to the underlying thermodynamics. In this study, the thermodynamic properties in the stepping movement of a biological molecular motor have been examined. A single molecule detection technique was used to measure the stepping movements at various loads and temperatures and a range of thermodynamic parameters associated with the production of each forward and backward step including free energy, enthalpy, entropy and characteristic distance were obtained. The results show that an asymmetry in entropy is a primary factor that controls the direction in which the motor will step. The investigation on single molecule thermodynamics has the potential to reveal dynamic properties underlying the mechanisms of how biological molecular machines work.

Entanglement across extended random defects in the XX spin chain

NASA Astrophysics Data System (ADS)

Juhász, Róbert

2017-08-01

We study the half-chain entanglement entropy in the ground state of the spin-1/2 XX chain across an extended random defect, where the strength of disorder decays with the distance from the interface algebraically as Δ_l∼ l-κ . In the whole regime κ≥slant 0 , the average entanglement entropy is found to increase logarithmically with the system size L as S_L≃\\frac{c_eff(κ)}{6}\\ln L+const , where the effective central charge c_eff(κ) depends on κ. In the regime κ<1/2 , where the extended defect is a relevant perturbation, the strong-disorder renormalization group method gives c_eff(κ)=(1-2κ)\\ln2 , while, in the regime κ≥slant 1/2 , where the extended defect is irrelevant in the bulk, numerical results indicate a non-zero effective central charge, which increases with κ. The variation of c_eff(κ) is thus found to be non-monotonic and discontinuous at κ=1/2 .

Distinguishability of generic quantum states

NASA Astrophysics Data System (ADS)

Puchała, Zbigniew; Pawela, Łukasz; Życzkowski, Karol

2016-06-01

Properties of random mixed states of dimension N distributed uniformly with respect to the Hilbert-Schmidt measure are investigated. We show that for large N , due to the concentration of measure, the trace distance between two random states tends to a fixed number D ˜=1 /4 +1 /π , which yields the Helstrom bound on their distinguishability. To arrive at this result, we apply free random calculus and derive the symmetrized Marchenko-Pastur distribution, which is shown to describe numerical data for the model of coupled quantum kicked tops. Asymptotic value for the root fidelity between two random states, √{F }=3/4 , can serve as a universal reference value for further theoretical and experimental studies. Analogous results for quantum relative entropy and Chernoff quantity provide other bounds on the distinguishablity of both states in a multiple measurement setup due to the quantum Sanov theorem. We study also mean entropy of coherence of random pure and mixed states and entanglement of a generic mixed state of a bipartite system.

Cave spiders choose optimal environmental factors with respect to the generated entropy when laying their cocoon

PubMed Central

Chiavazzo, Eliodoro; Isaia, Marco; Mammola, Stefano; Lepore, Emiliano; Ventola, Luigi; Asinari, Pietro; Pugno, Nicola Maria

2015-01-01

The choice of a suitable area to spiders where to lay eggs is promoted in terms of Darwinian fitness. Despite its importance, the underlying factors behind this key decision are generally poorly understood. Here, we designed a multidisciplinary study based both on in-field data and laboratory experiments focusing on the European cave spider Meta menardi (Araneae, Tetragnathidae) and aiming at understanding the selective forces driving the female in the choice of the depositional area. Our in-field data analysis demonstrated a major role of air velocity and distance from the cave entrance within a particular cave in driving the female choice. This has been interpreted using a model based on the Entropy Generation Minimization - EGM - method, without invoking best fit parameters and thanks to independent lab experiments, thus demonstrating that the female chooses the depositional area according to minimal level of thermo-fluid-dynamic irreversibility. This methodology may pave the way to a novel approach in understanding evolutionary strategies for other living organisms. PMID:25556697

Potential energy landscapes identify the information-theoretic nature of the epigenome

PubMed Central

Jenkinson, Garrett; Pujadas, Elisabet; Goutsias, John; Feinberg, Andrew P.

2017-01-01

Epigenetics studies genomic modifications carrying information independent of DNA sequence heritable through cell division. In 1940, Waddington coined the term “epigenetic landscape” as a metaphor for pluripotency and differentiation, but methylation landscapes have not yet been rigorously computed. By using principles of statistical physics and information theory, we derive epigenetic energy landscapes from whole-genome bisulfite sequencing data that allow us to quantify methylation stochasticity genome-wide using Shannon’s entropy and associate entropy with chromatin structure. Moreover, we consider the Jensen-Shannon distance between sample-specific energy landscapes as a measure of epigenetic dissimilarity and demonstrate its effectiveness for discerning epigenetic differences. By viewing methylation maintenance as a communications system, we introduce methylation channels and show that higher-order chromatin organization can be predicted from their informational properties. Our results provide a fundamental understanding of the information-theoretic nature of the epigenome that leads to a powerful approach for studying its role in disease and aging. PMID:28346445

The Dominant Folding Route Minimizes Backbone Distortion in SH3

PubMed Central

Lammert, Heiko; Noel, Jeffrey K.; Onuchic, José N.

2012-01-01

Energetic frustration in protein folding is minimized by evolution to create a smooth and robust energy landscape. As a result the geometry of the native structure provides key constraints that shape protein folding mechanisms. Chain connectivity in particular has been identified as an essential component for realistic behavior of protein folding models. We study the quantitative balance of energetic and geometrical influences on the folding of SH3 in a structure-based model with minimal energetic frustration. A decomposition of the two-dimensional free energy landscape for the folding reaction into relevant energy and entropy contributions reveals that the entropy of the chain is not responsible for the folding mechanism. Instead the preferred folding route through the transition state arises from a cooperative energetic effect. Off-pathway structures are penalized by excess distortion in local backbone configurations and contact pair distances. This energy cost is a new ingredient in the malleable balance of interactions that controls the choice of routes during protein folding. PMID:23166485

Calculation of Five Thermodynamic Molecular Descriptors by Means of a General Computer Algorithm Based on the Group-Additivity Method: Standard Enthalpies of Vaporization, Sublimation and Solvation, and Entropy of Fusion of Ordinary Organic Molecules and Total Phase-Change Entropy of Liquid Crystals.

PubMed

Naef, Rudolf; Acree, William E

2017-06-25

The calculation of the standard enthalpies of vaporization, sublimation and solvation of organic molecules is presented using a common computer algorithm on the basis of a group-additivity method. The same algorithm is also shown to enable the calculation of their entropy of fusion as well as the total phase-change entropy of liquid crystals. The present method is based on the complete breakdown of the molecules into their constituting atoms and their immediate neighbourhood; the respective calculations of the contribution of the atomic groups by means of the Gauss-Seidel fitting method is based on experimental data collected from literature. The feasibility of the calculations for each of the mentioned descriptors was verified by means of a 10-fold cross-validation procedure proving the good to high quality of the predicted values for the three mentioned enthalpies and for the entropy of fusion, whereas the predictive quality for the total phase-change entropy of liquid crystals was poor. The goodness of fit ( Q ²) and the standard deviation (σ) of the cross-validation calculations for the five descriptors was as follows: 0.9641 and 4.56 kJ/mol ( N = 3386 test molecules) for the enthalpy of vaporization, 0.8657 and 11.39 kJ/mol ( N = 1791) for the enthalpy of sublimation, 0.9546 and 4.34 kJ/mol ( N = 373) for the enthalpy of solvation, 0.8727 and 17.93 J/mol/K ( N = 2637) for the entropy of fusion and 0.5804 and 32.79 J/mol/K ( N = 2643) for the total phase-change entropy of liquid crystals. The large discrepancy between the results of the two closely related entropies is discussed in detail. Molecules for which both the standard enthalpies of vaporization and sublimation were calculable, enabled the estimation of their standard enthalpy of fusion by simple subtraction of the former from the latter enthalpy. For 990 of them the experimental enthalpy-of-fusion values are also known, allowing their comparison with predictions, yielding a correlation coefficient R ² of 0.6066.

Functional connectivity and structural covariance between regions of interest can be measured more accurately using multivariate distance correlation.

PubMed

Geerligs, Linda; Cam-Can; Henson, Richard N

2016-07-15

Studies of brain-wide functional connectivity or structural covariance typically use measures like the Pearson correlation coefficient, applied to data that have been averaged across voxels within regions of interest (ROIs). However, averaging across voxels may result in biased connectivity estimates when there is inhomogeneity within those ROIs, e.g., sub-regions that exhibit different patterns of functional connectivity or structural covariance. Here, we propose a new measure based on "distance correlation"; a test of multivariate dependence of high dimensional vectors, which allows for both linear and non-linear dependencies. We used simulations to show how distance correlation out-performs Pearson correlation in the face of inhomogeneous ROIs. To evaluate this new measure on real data, we use resting-state fMRI scans and T1 structural scans from 2 sessions on each of 214 participants from the Cambridge Centre for Ageing & Neuroscience (Cam-CAN) project. Pearson correlation and distance correlation showed similar average connectivity patterns, for both functional connectivity and structural covariance. Nevertheless, distance correlation was shown to be 1) more reliable across sessions, 2) more similar across participants, and 3) more robust to different sets of ROIs. Moreover, we found that the similarity between functional connectivity and structural covariance estimates was higher for distance correlation compared to Pearson correlation. We also explored the relative effects of different preprocessing options and motion artefacts on functional connectivity. Because distance correlation is easy to implement and fast to compute, it is a promising alternative to Pearson correlations for investigating ROI-based brain-wide connectivity patterns, for functional as well as structural data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Biometric ratio in estimating widths of maxillary anterior teeth derived after correlating anthropometric measurements with dental measurements.

PubMed

Kini, Ashwini Y; Angadi, Gangadhar S

2013-06-01

To correlate dental measurements i.e. combined mesiodistal width of six maxillary anterior teeth with facial measurements i.e. inner canthal distance, interpupillary distance and intercommissural width and acquire a biometric ratio to serve as a preliminary guide in selection of the maxillary anterior teeth. In the absence of pre-extraction records, the resultant denture can lead to patient dissatisfaction towards the aesthetic appeal of their dentures. The maxillary anterior teeth play a pivotal role in denture aesthetics. Various techniques and biometric ratios have been described in literature for selection of the maxillary anteriors. This study derives a biometric ratio for the same, obtained after correlating anthropometric measurements with dental measurements. Two standardized digital photographs of the face were generated; one, when the facial muscles were relaxed and the other, when the subject was smiling; thereby, revealing the maxillary anterior teeth upto the canine tip. Inner canthal distance, interpupillary distance, intercommissural distance, distance between the tips of the maxillary canines and distance between the distal surfaces of the canines were measured. On the cast, the distance between tips of maxillary canines and distance between distal surfaces of maxillary canines were noted. The data was analysed using Spearman's rank correlation coefficient. A high correlation was found between the intercommissural measurement with distance between the tips of the canines on the photograph and between the tips of the canines on the cast with the interpupillary distance, giving a biometric ratio of 1:1.35 and 1:1.41 respectively. The least correlation was between the inner canthal distance and the tips of the canines measured on the photograph. Extra oral anthropometric measurements of the interpupillary distances and the intercommissural distances with the help of standardised photographs can help us determine the combined widths of the anterior teeth accurately, thus aiding their selection in the absence of pre-extraction records. © 2012 John Wiley & Sons A/S and The Gerodontology Society. Published by John Wiley & Sons Ltd.

Characterization of time dynamical evolution of electroencephalographic epileptic records

NASA Astrophysics Data System (ADS)

Rosso, Osvaldo A.; Mairal, María. Liliana

2002-09-01

Since traditional electrical brain signal analysis is mostly qualitative, the development of new quantitative methods is crucial for restricting the subjectivity in the study of brain signals. These methods are particularly fruitful when they are strongly correlated with intuitive physical concepts that allow a better understanding of the brain dynamics. The processing of information by the brain is reflected in dynamical changes of the electrical activity in time, frequency, and space. Therefore, the concomitant studies require methods capable of describing the qualitative variation of the signal in both time and frequency. The entropy defined from the wavelet functions is a measure of the order/disorder degree present in a time series. In consequence, this entropy evaluates over EEG time series gives information about the underlying dynamical process in the brain, more specifically of the synchrony of the group cells involved in the different neural responses. The total wavelet entropy results independent of the signal energy and becomes a good tool for detecting dynamical changes in the system behavior. In addition the total wavelet entropy has advantages over the Lyapunov exponents, because it is parameter free and independent of the stationarity of the time series. In this work we compared the results of the time evolution of the chaoticity (Lyapunov exponent as a function of time) with the corresponding time evolution of the total wavelet entropy in two different EEG records, one provide by depth electrodes and other by scalp ones.

The cluster-cluster correlation function. [of galaxies

NASA Technical Reports Server (NTRS)

Postman, M.; Geller, M. J.; Huchra, J. P.

1986-01-01

The clustering properties of the Abell and Zwicky cluster catalogs are studied using the two-point angular and spatial correlation functions. The catalogs are divided into eight subsamples to determine the dependence of the correlation function on distance, richness, and the method of cluster identification. It is found that the Corona Borealis supercluster contributes significant power to the spatial correlation function to the Abell cluster sample with distance class of four or less. The distance-limited catalog of 152 Abell clusters, which is not greatly affected by a single system, has a spatial correlation function consistent with the power law Xi(r) = 300r exp -1.8. In both the distance class four or less and distance-limited samples the signal in the spatial correlation function is a power law detectable out to 60/h Mpc. The amplitude of Xi(r) for clusters of richness class two is about three times that for richness class one clusters. The two-point spatial correlation function is sensitive to the use of estimated redshifts.

Distance correlation methods for discovering associations in large astrophysical databases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martínez-Gómez, Elizabeth; Richards, Mercedes T.; Richards, Donald St. P., E-mail: elizabeth.martinez@itam.mx, E-mail: mrichards@astro.psu.edu, E-mail: richards@stat.psu.edu

2014-01-20

High-dimensional, large-sample astrophysical databases of galaxy clusters, such as the Chandra Deep Field South COMBO-17 database, provide measurements on many variables for thousands of galaxies and a range of redshifts. Current understanding of galaxy formation and evolution rests sensitively on relationships between different astrophysical variables; hence an ability to detect and verify associations or correlations between variables is important in astrophysical research. In this paper, we apply a recently defined statistical measure called the distance correlation coefficient, which can be used to identify new associations and correlations between astrophysical variables. The distance correlation coefficient applies to variables of any dimension,more » can be used to determine smaller sets of variables that provide equivalent astrophysical information, is zero only when variables are independent, and is capable of detecting nonlinear associations that are undetectable by the classical Pearson correlation coefficient. Hence, the distance correlation coefficient provides more information than the Pearson coefficient. We analyze numerous pairs of variables in the COMBO-17 database with the distance correlation method and with the maximal information coefficient. We show that the Pearson coefficient can be estimated with higher accuracy from the corresponding distance correlation coefficient than from the maximal information coefficient. For given values of the Pearson coefficient, the distance correlation method has a greater ability than the maximal information coefficient to resolve astrophysical data into highly concentrated horseshoe- or V-shapes, which enhances classification and pattern identification. These results are observed over a range of redshifts beyond the local universe and for galaxies from elliptical to spiral.« less

Crystal structure correlations with the intrinsic thermodynamics of human carbonic anhydrase inhibitor binding

PubMed Central

Smirnov, Alexey; Zubrienė, Asta; Manakova, Elena; Gražulis, Saulius

2018-01-01

The structure-thermodynamics correlation analysis was performed for a series of fluorine- and chlorine-substituted benzenesulfonamide inhibitors binding to several human carbonic anhydrase (CA) isoforms. The total of 24 crystal structures of 16 inhibitors bound to isoforms CA I, CA II, CA XII, and CA XIII provided the structural information of selective recognition between a compound and CA isoform. The binding thermodynamics of all structures was determined by the analysis of binding-linked protonation events, yielding the intrinsic parameters, i.e., the enthalpy, entropy, and Gibbs energy of binding. Inhibitor binding was compared within structurally similar pairs that differ by para- or meta-substituents enabling to obtain the contributing energies of ligand fragments. The pairs were divided into two groups. First, similar binders—the pairs that keep the same orientation of the benzene ring exhibited classical hydrophobic effect, a less exothermic enthalpy and a more favorable entropy upon addition of the hydrophobic fragments. Second, dissimilar binders—the pairs of binders that demonstrated altered positions of the benzene rings exhibited the non-classical hydrophobic effect, a more favorable enthalpy and variable entropy contribution. A deeper understanding of the energies contributing to the protein-ligand recognition should lead toward the eventual goal of rational drug design where chemical structures of ligands could be designed based on the target protein structure. PMID:29503769

Multiple Diffusion Mechanisms Due to Nanostructuring in Crowded Environments

PubMed Central

Sanabria, Hugo; Kubota, Yoshihisa; Waxham, M. Neal

2007-01-01

One of the key questions regarding intracellular diffusion is how the environment affects molecular mobility. Mostly, intracellular diffusion has been described as hindered, and the physical reasons for this behavior are: immobile barriers, molecular crowding, and binding interactions with immobile or mobile molecules. Using results from multi-photon fluorescence correlation spectroscopy, we describe how immobile barriers and crowding agents affect translational mobility. To study the hindrance produced by immobile barriers, we used sol-gels (silica nanostructures) that consist of a continuous solid phase and aqueous phase in which fluorescently tagged molecules diffuse. In the case of molecular crowding, translational mobility was assessed in increasing concentrations of 500 kDa dextran solutions. Diffusion of fluorescent tracers in both sol-gels and dextran solutions shows clear evidence of anomalous subdiffusion. In addition, data from the autocorrelation function were analyzed using the maximum entropy method as adapted to fluorescence correlation spectroscopy data and compared with the standard model that incorporates anomalous diffusion. The maximum entropy method revealed evidence of different diffusion mechanisms that had not been revealed using the anomalous diffusion model. These mechanisms likely correspond to nanostructuring in crowded environments and to the relative dimensions of the crowding agent with respect to the tracer molecule. Analysis with the maximum entropy method also revealed information about the degree of heterogeneity in the environment as reported by the behavior of diffusive molecules. PMID:17040979

Proposed mechanism for learning and memory erasure in a white-noise-driven sleeping cortex.

PubMed

Steyn-Ross, Moira L; Steyn-Ross, D A; Sleigh, J W; Wilson, M T; Wilcocks, Lara C

2005-12-01

Understanding the structure and purpose of sleep remains one of the grand challenges of neurobiology. Here we use a mean-field linearized theory of the sleeping cortex to derive statistics for synaptic learning and memory erasure. The growth in correlated low-frequency high-amplitude voltage fluctuations during slow-wave sleep (SWS) is characterized by a probability density function that becomes broader and shallower as the transition into rapid-eye-movement (REM) sleep is approached. At transition, the Shannon information entropy of the fluctuations is maximized. If we assume Hebbian-learning rules apply to the cortex, then its correlated response to white-noise stimulation during SWS provides a natural mechanism for a synaptic weight change that will tend to shut down reverberant neural activity. In contrast, during REM sleep the weights will evolve in a direction that encourages excitatory activity. These entropy and weight-change predictions lead us to identify the final portion of deep SWS that occurs immediately prior to transition into REM sleep as a time of enhanced erasure of labile memory. We draw a link between the sleeping cortex and Landauer's dissipation theorem for irreversible computing [R. Landauer, IBM J. Res. Devel. 5, 183 (1961)], arguing that because information erasure is an irreversible computation, there is an inherent entropy cost as the cortex transits from SWS into REM sleep.

Proposed mechanism for learning and memory erasure in a white-noise-driven sleeping cortex

NASA Astrophysics Data System (ADS)

Steyn-Ross, Moira L.; Steyn-Ross, D. A.; Sleigh, J. W.; Wilson, M. T.; Wilcocks, Lara C.

2005-12-01

Understanding the structure and purpose of sleep remains one of the grand challenges of neurobiology. Here we use a mean-field linearized theory of the sleeping cortex to derive statistics for synaptic learning and memory erasure. The growth in correlated low-frequency high-amplitude voltage fluctuations during slow-wave sleep (SWS) is characterized by a probability density function that becomes broader and shallower as the transition into rapid-eye-movement (REM) sleep is approached. At transition, the Shannon information entropy of the fluctuations is maximized. If we assume Hebbian-learning rules apply to the cortex, then its correlated response to white-noise stimulation during SWS provides a natural mechanism for a synaptic weight change that will tend to shut down reverberant neural activity. In contrast, during REM sleep the weights will evolve in a direction that encourages excitatory activity. These entropy and weight-change predictions lead us to identify the final portion of deep SWS that occurs immediately prior to transition into REM sleep as a time of enhanced erasure of labile memory. We draw a link between the sleeping cortex and Landauer’s dissipation theorem for irreversible computing [R. Landauer, IBM J. Res. Devel. 5, 183 (1961)], arguing that because information erasure is an irreversible computation, there is an inherent entropy cost as the cortex transits from SWS into REM sleep.

Ab initio study of the temperature-dependent structural properties of Al(110)

NASA Astrophysics Data System (ADS)

Scharoch, Pawel

2009-09-01

Temperature-dependent structural properties of Al(110) surface have been studied ab initio employing the concepts of the potential-energy surface (PES) and the free-energy surface (FES), with the latter based on the harmonic approximation for lattice dynamics. Three effects have been identified as contributing to the temperature-dependent multilayer relaxation: the bulk-substrate thermal expansion, the effect of asymmetry of PESs, and the entropy-driven shift of the minima of FESs. Thanks to the proper choice of constraints for PESs and FESs, it was possible to find relative contribution of the three effects to variation with temperature of the first three interlayer distances. A very satisfactory agreement of the calculation results with experimental data has been obtained. Also, a reference of the theoretical data to the experimentally observed anisotropic surface melting has been noticed. A softening phonon mode has been identified which is responsible for both: the entropy-driven spectacular expansion of the second interlayer distance and the loss of the surface stability. The latter can be associated with the anisotropic surface melting. The methodology applied has been found to be complementary to previous theoretical works [N. Marzari, D. Vanderbilt, A. De Vita, and M. C. Payne, Phys. Rev. Lett. 82, 3296 (1999); S. Narasimhan, Phys. Rev. B 64, 125409 (2001)], by offering another point of view and additional insight into the relative contribution of different physical effects to the temperature-dependent structural phenomena in Al(110) surface.

Expectation values of twist fields and universal entanglement saturation of the free massive boson

NASA Astrophysics Data System (ADS)

Blondeau-Fournier, Olivier; Doyon, Benjamin

2017-07-01

The evaluation of vacuum expectation values (VEVs) in massive integrable quantum field theory (QFT) is a nontrivial renormalization-group ‘connection problem’—relating large and short distance asymptotics—and is in general unsolved. This is particularly relevant in the context of entanglement entropy, where VEVs of branch-point twist fields give universal saturation predictions. We propose a new method to compute VEVs of twist fields associated to continuous symmetries in QFT. The method is based on a differential equation in the continuous symmetry parameter, and gives VEVs as infinite form-factor series which truncate at two-particle level in free QFT. We verify the method by studying U(1) twist fields in free models, which are simply related to the branch-point twist fields. We provide the first exact formulae for the VEVs of such fields in the massive uncompactified free boson model, checking against an independent calculation based on angular quantization. We show that logarithmic terms, overlooked in the original work of Callan and Wilczek (1994 Phys. Lett. B 333 55-61), appear both in the massless and in the massive situations. This implies that, in agreement with numerical form-factor observations by Bianchini and Castro-Alvaredo (2016 Nucl. Phys. B 913 879-911), the standard power-law short-distance behavior is corrected by a logarithmic factor. We discuss how this gives universal formulae for the saturation of entanglement entropy of a single interval in near-critical harmonic chains, including loglog corrections.

Binding free energy analysis of protein-protein docking model structures by evERdock.

PubMed

Takemura, Kazuhiro; Matubayasi, Nobuyuki; Kitao, Akio

2018-03-14

To aid the evaluation of protein-protein complex model structures generated by protein docking prediction (decoys), we previously developed a method to calculate the binding free energies for complexes. The method combines a short (2 ns) all-atom molecular dynamics simulation with explicit solvent and solution theory in the energy representation (ER). We showed that this method successfully selected structures similar to the native complex structure (near-native decoys) as the lowest binding free energy structures. In our current work, we applied this method (evERdock) to 100 or 300 model structures of four protein-protein complexes. The crystal structures and the near-native decoys showed the lowest binding free energy of all the examined structures, indicating that evERdock can successfully evaluate decoys. Several decoys that show low interface root-mean-square distance but relatively high binding free energy were also identified. Analysis of the fraction of native contacts, hydrogen bonds, and salt bridges at the protein-protein interface indicated that these decoys were insufficiently optimized at the interface. After optimizing the interactions around the interface by including interfacial water molecules, the binding free energies of these decoys were improved. We also investigated the effect of solute entropy on binding free energy and found that consideration of the entropy term does not necessarily improve the evaluations of decoys using the normal model analysis for entropy calculation.

Binding free energy analysis of protein-protein docking model structures by evERdock

NASA Astrophysics Data System (ADS)

Takemura, Kazuhiro; Matubayasi, Nobuyuki; Kitao, Akio

2018-03-01

To aid the evaluation of protein-protein complex model structures generated by protein docking prediction (decoys), we previously developed a method to calculate the binding free energies for complexes. The method combines a short (2 ns) all-atom molecular dynamics simulation with explicit solvent and solution theory in the energy representation (ER). We showed that this method successfully selected structures similar to the native complex structure (near-native decoys) as the lowest binding free energy structures. In our current work, we applied this method (evERdock) to 100 or 300 model structures of four protein-protein complexes. The crystal structures and the near-native decoys showed the lowest binding free energy of all the examined structures, indicating that evERdock can successfully evaluate decoys. Several decoys that show low interface root-mean-square distance but relatively high binding free energy were also identified. Analysis of the fraction of native contacts, hydrogen bonds, and salt bridges at the protein-protein interface indicated that these decoys were insufficiently optimized at the interface. After optimizing the interactions around the interface by including interfacial water molecules, the binding free energies of these decoys were improved. We also investigated the effect of solute entropy on binding free energy and found that consideration of the entropy term does not necessarily improve the evaluations of decoys using the normal model analysis for entropy calculation.

[Study on infrared spectrum change of Ganoderma lucidum and its extracts].

PubMed

Chen, Zao-Xin; Xu, Yong-Qun; Chen, Xiao-Kang; Huang, Dong-Lan; Lu, Wen-Guan

2013-05-01

From the determination of the infrared spectra of four substances (original ganoderma lucidum and ganoderma lucidum water extract, 95% ethanol extract and petroleum ether extract), it was found that the infrared spectrum can carry systematic chemical information and basically reflects the distribution of each component of the analyte. Ganoderma lucidum and its extracts can be distinguished according to the absorption peak area ratio of 3 416-3 279, 1 541 and 723 cm(-1) to 2 935-2 852 cm(-1). A method of calculating the information entropy of the sample set with Euclidean distance was proposed, the relationship between the information entropy and the amount of chemical information carried by the sample set was discussed, and the authors come to a conclusion that sample set of original ganoderma lucidum carry the most abundant chemical information. The infrared spectrum set of original ganoderma lucidum has better clustering effect on ganoderma atrum, Cyan ganoderma, ganoderma multiplicatum and ganoderma lucidum when making hierarchical cluster analysis of 4 sample set. The results show that infrared spectrum carries the chemical information of the material structure and closely relates to the chemical composition of the system. The higher the value of information entropy, the much richer the chemical information and the more the benefit for pattern recognition. This study has a guidance function to the construction of the sample set in pattern recognition.

Statistical and linguistic features of DNA sequences

NASA Technical Reports Server (NTRS)

Havlin, S.; Buldyrev, S. V.; Goldberger, A. L.; Mantegna, R. N.; Peng, C. K.; Simons, M.; Stanley, H. E.

1995-01-01

We present evidence supporting the idea that the DNA sequence in genes containing noncoding regions is correlated, and that the correlation is remarkably long range--indeed, base pairs thousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene. We resolve the problem of the "non-stationary" feature of the sequence of base pairs by applying a new algorithm called Detrended Fluctuation Analysis (DFA). We address the claim of Voss that there is no difference in the statistical properties of coding and noncoding regions of DNA by systematically applying the DFA algorithm, as well as standard FFT analysis, to all eukaryotic DNA sequences (33 301 coding and 29 453 noncoding) in the entire GenBank database. We describe a simple model to account for the presence of long-range power-law correlations which is based upon a generalization of the classic Levy walk. Finally, we describe briefly some recent work showing that the noncoding sequences have certain statistical features in common with natural languages. Specifically, we adapt to DNA the Zipf approach to analyzing linguistic texts, and the Shannon approach to quantifying the "redundancy" of a linguistic text in terms of a measurable entropy function. We suggest that noncoding regions in plants and invertebrates may display a smaller entropy and larger redundancy than coding regions, further supporting the possibility that noncoding regions of DNA may carry biological information.

Linearized semiclassical initial value time correlation functions with maximum entropy analytic continuation.

PubMed

Liu, Jian; Miller, William H

2008-09-28

The maximum entropy analytic continuation (MEAC) method is used to extend the range of accuracy of the linearized semiclassical initial value representation (LSC-IVR)/classical Wigner approximation for real time correlation functions. LSC-IVR provides a very effective "prior" for the MEAC procedure since it is very good for short times, exact for all time and temperature for harmonic potentials (even for correlation functions of nonlinear operators), and becomes exact in the classical high temperature limit. This combined MEAC+LSC/IVR approach is applied here to two highly nonlinear dynamical systems, a pure quartic potential in one dimensional and liquid para-hydrogen at two thermal state points (25 and 14 K under nearly zero external pressure). The former example shows the MEAC procedure to be a very significant enhancement of the LSC-IVR for correlation functions of both linear and nonlinear operators, and especially at low temperature where semiclassical approximations are least accurate. For liquid para-hydrogen, the LSC-IVR is seen already to be excellent at T=25 K, but the MEAC procedure produces a significant correction at the lower temperature (T=14 K). Comparisons are also made as to how the MEAC procedure is able to provide corrections for other trajectory-based dynamical approximations when used as priors.

Diagnosing entropy production and dissipation in fully kinetic plasmas

NASA Astrophysics Data System (ADS)

Juno, James; Tenbarge, Jason; Hakim, Ammar; Dorland, William; Cagas, Petr

2017-10-01

Many plasma systems, from the core of a tokamak to the outer heliosphere, are weakly collisional and thus most accurately described by kinetic theory. The typical approach to solving the kinetic equation has been the particle-in-cell algorithm, which, while a powerful tool, introduces counting noise into the particle distribution function. The counting noise is particularly problematic when attempting to study grand challenge problems such as entropy production from phenomena like shocks and turbulence. In this poster, we present studies of entropy production and dissipation processes present in simple turbulence and shock calculations using the continuum Vlasov-Maxwell solver in the Gkeyll framework. Particular emphasis is placed on a novel diagnostic, the field-particle correlation, which is especially efficient at separating the secular energy transfer into its constituent components, for example, cyclotron damping, Landau damping, or transit-time damping, when applied to a noise-free distribution function. National Science Foundation SHINE award No. AGS-1622306 and the UMD DOE Grant DE-FG02-93ER54197.

Diagnosing entropy production and dissipation in fully kinetic plasmas

NASA Astrophysics Data System (ADS)

Juno, J.; TenBarge, J. M.; Hakim, A.; Dorland, W.

2017-12-01

Many plasma systems, from the core of a tokamak to the outer heliosphere, are weakly collisional and thus most accurately described by kinetic theory. The typical approach to solving the kinetic equation has been the particle-in-cell algorithm, which, while a powerful tool, introduces counting noise into the particle distribution function. The counting noise is particularly problematic when attempting to study grand challenge problems such as entropy production from phenomena like shocks and turbulence. In this poster, we present studies of entropy production and dissipation processes present in simple turbulence and shock calculations using the continuum Vlasov-Maxwell solver in the Gkeyll framework. Particular emphasis is placed on a novel diagnostic, the field-particle correlation, which is especially efficient at separating the secular energy transfer into its constituent components, for example, cyclotron damping, Landau damping, or transit-time damping, when applied to a noise-free distribution function. Using reduced systems such as completely transverse electromagnetic shocks, we also explore the signatures of perpendicular, non-resonant, energization mechanisms.

Larson-Miller Constant of Heat-Resistant Steel

NASA Astrophysics Data System (ADS)

Tamura, Manabu; Abe, Fujio; Shiba, Kiyoyuki; Sakasegawa, Hideo; Tanigawa, Hiroyasu

2013-06-01

Long-term rupture data for 79 types of heat-resistant steels including carbon steel, low-alloy steel, high-alloy steel, austenitic stainless steel, and superalloy were analyzed, and a constant for the Larson-Miller (LM) parameter was obtained in the current study for each material. The calculated LM constant, C, is approximately 20 for heat-resistant steels and alloys except for high-alloy martensitic steels with high creep resistance, for which C ≈ 30 . The apparent activation energy was also calculated, and the LM constant was found to be proportional to the apparent activation energy with a high correlation coefficient, which suggests that the LM constant is a material constant possessing intrinsic physical meaning. The contribution of the entropy change to the LM constant is not small, especially for several martensitic steels with large values of C. Deformation of such martensitic steels should accompany a large entropy change of 10 times the gas constant at least, besides the entropy change due to self-diffusion.

Estimation of Lithological Classification in Taipei Basin: A Bayesian Maximum Entropy Method

NASA Astrophysics Data System (ADS)

Wu, Meng-Ting; Lin, Yuan-Chien; Yu, Hwa-Lung

2015-04-01

In environmental or other scientific applications, we must have a certain understanding of geological lithological composition. Because of restrictions of real conditions, only limited amount of data can be acquired. To find out the lithological distribution in the study area, many spatial statistical methods used to estimate the lithological composition on unsampled points or grids. This study applied the Bayesian Maximum Entropy (BME method), which is an emerging method of the geological spatiotemporal statistics field. The BME method can identify the spatiotemporal correlation of the data, and combine not only the hard data but the soft data to improve estimation. The data of lithological classification is discrete categorical data. Therefore, this research applied Categorical BME to establish a complete three-dimensional Lithological estimation model. Apply the limited hard data from the cores and the soft data generated from the geological dating data and the virtual wells to estimate the three-dimensional lithological classification in Taipei Basin. Keywords: Categorical Bayesian Maximum Entropy method, Lithological Classification, Hydrogeological Setting

Reduced Data Dualscale Entropy Analysis of HRV Signals for Improved Congestive Heart Failure Detection

NASA Astrophysics Data System (ADS)

Kuntamalla, Srinivas; Lekkala, Ram Gopal Reddy

2014-10-01

Heart rate variability (HRV) is an important dynamic variable of the cardiovascular system, which operates on multiple time scales. In this study, Multiscale entropy (MSE) analysis is applied to HRV signals taken from Physiobank to discriminate Congestive Heart Failure (CHF) patients from healthy young and elderly subjects. The discrimination power of the MSE method is decreased as the amount of the data reduces and the lowest amount of the data at which there is a clear discrimination between CHF and normal subjects is found to be 4000 samples. Further, this method failed to discriminate CHF from healthy elderly subjects. In view of this, the Reduced Data Dualscale Entropy Analysis method is proposed to reduce the data size required (as low as 500 samples) for clearly discriminating the CHF patients from young and elderly subjects with only two scales. Further, an easy to interpret index is derived using this new approach for the diagnosis of CHF. This index shows 100 % accuracy and correlates well with the pathophysiology of heart failure.

Side-chain mobility in the folded state of Myoglobin

NASA Astrophysics Data System (ADS)

Lammert, Heiko; Onuchic, Jose

We study the accessibility of alternative side-chain rotamer configurations in the native state of Myoglobin, using an all-atom structure-based model. From long, unbiased simulation trajectories we determine occupancies of rotameric states and also estimate configurational and vibrational entropies. Direct sampling of the full native-state dynamics, enabled by the simple model, reveals facilitation of side-chain motions by backbone dynamics. Correlations between different dihedral angles are quantified and prove to be weak. We confirm global trends in the mobilities of side-chains, following burial and also the chemical character of residues. Surface residues loose little configurational entropy upon folding; side-chains contribute significantly to the entropy of the folded state. Mobilities of buried side-chains vary strongly with temperature. At ambient temperature, individual side-chains in the core of the protein gain substantial access to alternative rotamers, with occupancies that are likely observable experimentally. Finally, the dynamics of buried side-chains may be linked to the internal pockets, available to ligand gas molecules in Myoglobin.

Edge theory approach to topological entanglement entropy, mutual information, and entanglement negativity in Chern-Simons theories

NASA Astrophysics Data System (ADS)

Wen, Xueda; Matsuura, Shunji; Ryu, Shinsei

2016-06-01

We develop an approach based on edge theories to calculate the entanglement entropy and related quantities in (2+1)-dimensional topologically ordered phases. Our approach is complementary to, e.g., the existing methods using replica trick and Witten's method of surgery, and applies to a generic spatial manifold of genus g , which can be bipartitioned in an arbitrary way. The effects of fusion and braiding of Wilson lines can be also straightforwardly studied within our framework. By considering a generic superposition of states with different Wilson line configurations, through an interference effect, we can detect, by the entanglement entropy, the topological data of Chern-Simons theories, e.g., the R symbols, monodromy, and topological spins of quasiparticles. Furthermore, by using our method, we calculate other entanglement/correlation measures such as the mutual information and the entanglement negativity. In particular, it is found that the entanglement negativity of two adjacent noncontractible regions on a torus provides a simple way to distinguish Abelian and non-Abelian topological orders.

Statistical mechanics of letters in words

PubMed Central

Stephens, Greg J.; Bialek, William

2013-01-01

We consider words as a network of interacting letters, and approximate the probability distribution of states taken on by this network. Despite the intuition that the rules of English spelling are highly combinatorial and arbitrary, we find that maximum entropy models consistent with pairwise correlations among letters provide a surprisingly good approximation to the full statistics of words, capturing ~92% of the multi-information in four-letter words and even “discovering” words that were not represented in the data. These maximum entropy models incorporate letter interactions through a set of pairwise potentials and thus define an energy landscape on the space of possible words. Guided by the large letter redundancy we seek a lower-dimensional encoding of the letter distribution and show that distinctions between local minima in the landscape account for ~68% of the four-letter entropy. We suggest that these states provide an effective vocabulary which is matched to the frequency of word use and much smaller than the full lexicon. PMID:20866490

Measuring the performance of visual to auditory information conversion.

PubMed

Tan, Shern Shiou; Maul, Tomás Henrique Bode; Mennie, Neil Russell

2013-01-01

Visual to auditory conversion systems have been in existence for several decades. Besides being among the front runners in providing visual capabilities to blind users, the auditory cues generated from image sonification systems are still easier to learn and adapt to compared to other similar techniques. Other advantages include low cost, easy customizability, and universality. However, every system developed so far has its own set of strengths and weaknesses. In order to improve these systems further, we propose an automated and quantitative method to measure the performance of such systems. With these quantitative measurements, it is possible to gauge the relative strengths and weaknesses of different systems and rank the systems accordingly. Performance is measured by both the interpretability and also the information preservation of visual to auditory conversions. Interpretability is measured by computing the correlation of inter image distance (IID) and inter sound distance (ISD) whereas the information preservation is computed by applying Information Theory to measure the entropy of both visual and corresponding auditory signals. These measurements provide a basis and some insights on how the systems work. With an automated interpretability measure as a standard, more image sonification systems can be developed, compared, and then improved. Even though the measure does not test systems as thoroughly as carefully designed psychological experiments, a quantitative measurement like the one proposed here can compare systems to a certain degree without incurring much cost. Underlying this research is the hope that a major breakthrough in image sonification systems will allow blind users to cost effectively regain enough visual functions to allow them to lead secure and productive lives.

The change in spatial distribution of upper trapezius muscle activity is correlated to contraction duration.

PubMed

Farina, Dario; Leclerc, Frédéric; Arendt-Nielsen, Lars; Buttelli, Olivier; Madeleine, Pascal

2008-02-01

The aim of the study was to confirm the hypothesis that the longer a contraction is sustained, the larger are the changes in the spatial distribution of muscle activity. For this purpose, surface electromyographic (EMG) signals were recorded with a 13 x 5 grid of electrodes from the upper trapezius muscle of 11 healthy male subjects during static contractions with shoulders 90 degrees abducted until endurance. The entropy (degree of uniformity) and center of gravity of the EMG root mean square map were computed to assess spatial inhomogeneity in muscle activation and changes over time in EMG amplitude spatial distribution. At the endurance time, entropy decreased (mean+/-SD, percent change 2.0+/-1.6%; P<0.0001) and the center of gravity moved in the cranial direction (shift 11.2+/-6.1mm; P<0.0001) with respect to the beginning of the contraction. The shift in the center of gravity was positively correlated with endurance time (R(2)=0.46, P<0.05), thus subjects with larger shift in the activity map showed longer endurance time. The percent variation in average (over the grid) root mean square was positively correlated with the shift in the center of gravity (R(2)=0.51, P<0.05). Moreover, the shift in the center of gravity was negatively correlated to both initial and final (at the endurance) entropy (R(2)=0.54 and R(2)=0.56, respectively; P<0.01 in both cases), indicating that subjects with less uniform root mean square maps had larger shift of the center of gravity over time. The spatial changes in root mean square EMG were likely due to spatially-dependent changes in motor unit activation during the sustained contraction. It was concluded that the changes in spatial muscle activity distribution play a role in the ability to maintain a static contraction.

A Study of Feature Extraction Using Divergence Analysis of Texture Features

NASA Technical Reports Server (NTRS)

Hallada, W. A.; Bly, B. G.; Boyd, R. K.; Cox, S.

1982-01-01

An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.

[Glossary of terms used by radiologists in image processing].

PubMed

Rolland, Y; Collorec, R; Bruno, A; Ramée, A; Morcet, N; Haigron, P

1995-01-01

We give the definition of 166 words used in image processing. Adaptivity, aliazing, analog-digital converter, analysis, approximation, arc, artifact, artificial intelligence, attribute, autocorrelation, bandwidth, boundary, brightness, calibration, class, classification, classify, centre, cluster, coding, color, compression, contrast, connectivity, convolution, correlation, data base, decision, decomposition, deconvolution, deduction, descriptor, detection, digitization, dilation, discontinuity, discretization, discrimination, disparity, display, distance, distorsion, distribution dynamic, edge, energy, enhancement, entropy, erosion, estimation, event, extrapolation, feature, file, filter, filter floaters, fitting, Fourier transform, frequency, fusion, fuzzy, Gaussian, gradient, graph, gray level, group, growing, histogram, Hough transform, Houndsfield, image, impulse response, inertia, intensity, interpolation, interpretation, invariance, isotropy, iterative, JPEG, knowledge base, label, laplacian, learning, least squares, likelihood, matching, Markov field, mask, matching, mathematical morphology, merge (to), MIP, median, minimization, model, moiré, moment, MPEG, neural network, neuron, node, noise, norm, normal, operator, optical system, optimization, orthogonal, parametric, pattern recognition, periodicity, photometry, pixel, polygon, polynomial, prediction, pulsation, pyramidal, quantization, raster, reconstruction, recursive, region, rendering, representation space, resolution, restoration, robustness, ROC, thinning, transform, sampling, saturation, scene analysis, segmentation, separable function, sequential, smoothing, spline, split (to), shape, threshold, tree, signal, speckle, spectrum, spline, stationarity, statistical, stochastic, structuring element, support, syntaxic, synthesis, texture, truncation, variance, vision, voxel, windowing.

The relationship of walking distances estimated by the patient, on the corridor and on a treadmill, and the Walking Impairment Questionnaire in intermittent claudication.

PubMed

Frans, Franceline Alkine; Zagers, Marjolein B; Jens, Sjoerd; Bipat, Shandra; Reekers, Jim A; Koelemay, Mark J W

2013-03-01

Physicians and patients consider the limited walking distance and perceived disability when they make decisions regarding (invasive) treatment of intermittent claudication (IC). We investigated the relationship between walking distances estimated by the patient, on the corridor and on a treadmill, and the Walking Impairment Questionnaire (WIQ) in patients with IC due to peripheral arterial disease. This was a single-center, prospective observational cohort study at a vascular laboratory in a university hospital in the Netherlands. The study consisted of 60 patients (41 male) with a median age of 64 years (range, 44-86 years) with IC and a walking distance ≤ 250 m on a standardized treadmill test. Main outcome measures were differences and Spearman rank correlations between pain-free walking distance, maximum walking distance (MWD) estimated by the patient, on the corridor and on a standardized treadmill test, and their correlation with the WIQ. The median patients' estimated, corridor, and treadmill MWD were 200, 200, and 123, respectively (P < .05). Although the median patients' estimated and corridor MWD were not significantly different, there was a difference on an individual basis. The correlation between the patients' estimated and corridor MWD was moderate (r = 0.61; 95% confidence interval [CI], 0.42-0.75). The correlation between patients' estimated and treadmill MWD was weak (r = 0.39; 95%, CI 0.15-0.58). Respective correlations for the pain-free walking distance were comparable. The patients' estimated MWD was moderately correlated with WIQ total score (r = 0.63; 95%, CI 0.45-0.76) and strongly correlated with WIQ distance score (r = 0.81; 95% CI, 0.69-0.88). The correlation between the corridor MWD and WIQ distance score was moderate (r = 0.59; 95% CI, 0.40-0.74). Patients' estimated walking distances and on a treadmill do not reflect walking distances in daily life. Instruments that take into account the perceived walking impairment, such as the WIQ, may help to better guide and evaluate treatment decisions. Copyright © 2013 Society for Vascular Surgery. Published by Mosby, Inc. All rights reserved.

Prediction of pKa Values for Neutral and Basic Drugs based on Hybrid Artificial Intelligence Methods.

PubMed

Li, Mengshan; Zhang, Huaijing; Chen, Bingsheng; Wu, Yan; Guan, Lixin

2018-03-05

The pKa value of drugs is an important parameter in drug design and pharmacology. In this paper, an improved particle swarm optimization (PSO) algorithm was proposed based on the population entropy diversity. In the improved algorithm, when the population entropy was higher than the set maximum threshold, the convergence strategy was adopted; when the population entropy was lower than the set minimum threshold the divergence strategy was adopted; when the population entropy was between the maximum and minimum threshold, the self-adaptive adjustment strategy was maintained. The improved PSO algorithm was applied in the training of radial basis function artificial neural network (RBF ANN) model and the selection of molecular descriptors. A quantitative structure-activity relationship model based on RBF ANN trained by the improved PSO algorithm was proposed to predict the pKa values of 74 kinds of neutral and basic drugs and then validated by another database containing 20 molecules. The validation results showed that the model had a good prediction performance. The absolute average relative error, root mean square error, and squared correlation coefficient were 0.3105, 0.0411, and 0.9685, respectively. The model can be used as a reference for exploring other quantitative structure-activity relationships.

The Anterior Insula Tracks Behavioral Entropy during an Interpersonal Competitive Game

PubMed Central

Matsumoto, Madoka; Matsumoto, Kenji; Omori, Takashi

2015-01-01

In competitive situations, individuals need to adjust their behavioral strategy dynamically in response to their opponent’s behavior. In the present study, we investigated the neural basis of how individuals adjust their strategy during a simple, competitive game of matching pennies. We used entropy as a behavioral index of randomness in decision-making, because maximizing randomness is thought to be an optimal strategy in the game, according to game theory. While undergoing functional magnetic resonance imaging (fMRI), subjects played matching pennies with either a human or computer opponent in each block, although in reality they played the game with the same computer algorithm under both conditions. The winning rate of each block was also manipulated. Both the opponent (human or computer), and the winning rate, independently affected subjects’ block-wise entropy during the game. The fMRI results revealed that activity in the bilateral anterior insula was positively correlated with subjects’ (not opponent’s) behavioral entropy during the game, which indicates that during an interpersonal competitive game, the anterior insula tracked how uncertain subjects’ behavior was, rather than how uncertain subjects felt their opponent's behavior was. Our results suggest that intuitive or automatic processes based on somatic markers may be a key to optimally adjusting behavioral strategies in competitive situations. PMID:26039634

Relations between work and entropy production for general information-driven, finite-state engines

NASA Astrophysics Data System (ADS)

Merhav, Neri

2017-02-01

We consider a system model of a general finite-state machine (ratchet) that simultaneously interacts with three kinds of reservoirs: a heat reservoir, a work reservoir, and an information reservoir, the latter being taken to be a running digital tape whose symbols interact sequentially with the machine. As has been shown in earlier work, this finite-state machine can act as a demon (with memory), which creates a net flow of energy from the heat reservoir into the work reservoir (thus extracting useful work) at the price of increasing the entropy of the information reservoir. Under very few assumptions, we propose a simple derivation of a family of inequalities that relate the work extraction with the entropy production. These inequalities can be seen as either upper bounds on the extractable work or as lower bounds on the entropy production, depending on the point of view. Many of these bounds are relatively easy to calculate and they are tight in the sense that equality can be approached arbitrarily closely. In their basic forms, these inequalities are applicable to any finite number of cycles (and not only asymptotically), and for a general input information sequence (possibly correlated), which is not necessarily assumed even stationary. Several known results are obtained as special cases.

Information theory-based decision support system for integrated design of multivariable hydrometric networks

NASA Astrophysics Data System (ADS)

Keum, Jongho; Coulibaly, Paulin

2017-07-01

Adequate and accurate hydrologic information from optimal hydrometric networks is an essential part of effective water resources management. Although the key hydrologic processes in the water cycle are interconnected, hydrometric networks (e.g., streamflow, precipitation, groundwater level) have been routinely designed individually. A decision support framework is proposed for integrated design of multivariable hydrometric networks. The proposed method is applied to design optimal precipitation and streamflow networks simultaneously. The epsilon-dominance hierarchical Bayesian optimization algorithm was combined with Shannon entropy of information theory to design and evaluate hydrometric networks. Specifically, the joint entropy from the combined networks was maximized to provide the most information, and the total correlation was minimized to reduce redundant information. To further optimize the efficiency between the networks, they were designed by maximizing the conditional entropy of the streamflow network given the information of the precipitation network. Compared to the traditional individual variable design approach, the integrated multivariable design method was able to determine more efficient optimal networks by avoiding the redundant stations. Additionally, four quantization cases were compared to evaluate their effects on the entropy calculations and the determination of the optimal networks. The evaluation results indicate that the quantization methods should be selected after careful consideration for each design problem since the station rankings and the optimal networks can change accordingly.

Metallization of vanadium dioxide driven by large phonon entropy

DOE PAGES

Budai, John D.; Hong, Jiawang; Manley, Michael E.; ...

2014-11-10

Phase competition underlies many remarkable and technologically important phenomena in transition-metal oxides. Vanadium dioxide exhibits a first-order metal-insulator transition (MIT) near room temperature, where conductivity is suppressed and the lattice changes from tetragonal to monoclinic on cooling. Ongoing attempts to explain this coupled structural and electronic transition begin with two classic starting points: a Peierls MIT driven by instabilities in electron-lattice dynamics versus a Mott MIT where strong electron-electron correlations drive charge localization1-10. A key-missing piece of the VO2 puzzle is the role of lattice vibrations. Moreover, a comprehensive thermodynamic treatment must integrate both entropic and energetic aspects of themore » transition. Our measurements establish that the entropy driving the MIT is dominated by strongly anharmonic phonons rather than electronic contributions, and provide a direct determination of phonon dispersions. Our calculations identify softer bonding as the origin of the large vibrational entropy stabilizing the metallic rutile phase. They further reveal how a balance between higher entropy in the metal and orbital-driven lower energy in the insulator fully describes the thermodynamic forces controlling the MIT. This study illustrates the critical role of anharmonic lattice dynamics in metal-oxide phase competition, and provides guidance for the predictive design of new materials.« less

Correlations in quantum thermodynamics: Heat, work, and entropy production

PubMed Central

Alipour, S.; Benatti, F.; Bakhshinezhad, F.; Afsary, M.; Marcantoni, S.; Rezakhani, A. T.

2016-01-01

We provide a characterization of energy in the form of exchanged heat and work between two interacting constituents of a closed, bipartite, correlated quantum system. By defining a binding energy we derive a consistent quantum formulation of the first law of thermodynamics, in which the role of correlations becomes evident, and this formulation reduces to the standard classical picture in relevant systems. We next discuss the emergence of the second law of thermodynamics under certain—but fairly general—conditions such as the Markovian assumption. We illustrate the role of correlations and interactions in thermodynamics through two examples. PMID:27767124

Entropy is conserved in Hawking radiation as tunneling: A revisit of the black hole information loss paradox

NASA Astrophysics Data System (ADS)

Zhang, Baocheng; Cai, Qing-yu; Zhan, Ming-sheng; You, Li

2011-02-01

We revisit in detail the paradox of black hole information loss due to Hawking radiation as tunneling. We compute the amount of information encoded in correlations among Hawking radiations for a variety of black holes, including the Schwarzchild black hole, the Reissner-Nordström black hole, the Kerr black hole, and the Kerr-Newman black hole. The special case of tunneling through a quantum horizon is also considered. Within a phenomenological treatment based on the accepted emission probability spectrum from a black hole, we find that information is leaked out hidden in the correlations of Hawking radiation. The recovery of this previously unaccounted for information helps to conserve the total entropy of a system composed of a black hole plus its radiations. We thus conclude, irrespective of the microscopic picture for black hole collapsing, the associated radiation process: Hawking radiation as tunneling, is consistent with unitarity as required by quantum mechanics.

Metal-organic complexes in geochemical processes: temperature dependence of the standard thermodynamic properties of aqueous complexes between metal cations and dicarboxylate ligands

NASA Astrophysics Data System (ADS)

Prapaipong, Panjai; Shock, Everett L.; Koretsky, Carla M.

1999-10-01

By combining results from regression and correlation methods, standard state thermodynamic properties for aqueous complexes between metal cations and divalent organic acid ligands (oxalate, malonate, succinate, glutarate, and adipate) are evaluated and applied to geochemical processes. Regression of experimental standard-state equilibrium constants with the revised Helgeson-Kirkham-Flowers (HKF) equation of state yields standard partial molal entropies (S¯°) of aqueous metal-organic complexes, which allow determination of thermodynamic properties of the complexes at elevated temperatures. In cases where S¯° is not available from either regression or calorimetric measurement, the values of S¯° can be estimated from a linear correlation between standard partial molal entropies of association (ΔS¯°r) and standard partial molal entropies of aqueous cations (S¯°M). The correlation is independent of cation charge, which makes it possible to predict S¯° for complexes between divalent organic acids and numerous metal cations. Similarly, correlations between standard Gibbs free energies of association of metal-organic complexes (ΔḠ°r) and Gibbs free energies of formation (ΔḠ°f) for divalent metal cations allow estimates of standard-state equilibrium constants where experimental data are not available. These correlations are found to be a function of ligand structure and cation charge. Predicted equilibrium constants for dicarboxylate complexes of numerous cations were included with those for inorganic and other organic complexes to study the effects of dicarboxylate complexes on the speciation of metals and organic acids in oil-field brines. Relatively low concentrations of oxalic and malonic acids affect the speciation of cations more than similar concentrations of succinic, glutaric, and adipic acids. However, the extent to which metal-dicarboxylate complexes contribute to the speciation of dissolved metals depends on the type of dicarboxylic acid ligand; relative concentration of inorganic, mono-, and dicarboxylate ligands; and the type of metal cation. As an example, in the same solution, dicarboxylic acids have a greater influence on the speciation of Fe+2 and Mg+2 than on the speciation of Zn+2 and Mn+2.

Diffusion profiling of tumor volumes using a histogram approach can predict proliferation and further microarchitectural features in medulloblastoma.

PubMed

Schob, Stefan; Beeskow, Anne; Dieckow, Julia; Meyer, Hans-Jonas; Krause, Matthias; Frydrychowicz, Clara; Hirsch, Franz-Wolfgang; Surov, Alexey

2018-05-31

Medulloblastomas are the most common central nervous system tumors in childhood. Treatment and prognosis strongly depend on histology and transcriptomic profiling. However, the proliferative potential also has prognostical value. Our study aimed to investigate correlations between histogram profiling of diffusion-weighted images and further microarchitectural features. Seven patients (age median 14.6 years, minimum 2 years, maximum 20 years; 5 male, 2 female) were included in this retrospective study. Using a Matlab-based analysis tool, histogram analysis of whole apparent diffusion coefficient (ADC) volumes was performed. ADC entropy revealed a strong inverse correlation with the expression of the proliferation marker Ki67 (r = - 0.962, p = 0.009) and with total nuclear area (r = - 0.888, p = 0.044). Furthermore, ADC percentiles, most of all ADCp90, showed significant correlations with Ki67 expression (r = 0.902, p = 0.036). Diffusion histogram profiling of medulloblastomas provides valuable in vivo information which potentially can be used for risk stratification and prognostication. First of all, entropy revealed to be the most promising imaging biomarker. However, further studies are warranted.

Cross-sample entropy of foreign exchange time series

NASA Astrophysics Data System (ADS)

Liu, Li-Zhi; Qian, Xi-Yuan; Lu, Heng-Yao

2010-11-01

The correlation of foreign exchange rates in currency markets is investigated based on the empirical data of DKK/USD, NOK/USD, CAD/USD, JPY/USD, KRW/USD, SGD/USD, THB/USD and TWD/USD for a period from 1995 to 2002. Cross-SampEn (cross-sample entropy) method is used to compare the returns of every two exchange rate time series to assess their degree of asynchrony. The calculation method of confidence interval of SampEn is extended and applied to cross-SampEn. The cross-SampEn and its confidence interval for every two of the exchange rate time series in periods 1995-1998 (before the Asian currency crisis) and 1999-2002 (after the Asian currency crisis) are calculated. The results show that the cross-SampEn of every two of these exchange rates becomes higher after the Asian currency crisis, indicating a higher asynchrony between the exchange rates. Especially for Singapore, Thailand and Taiwan, the cross-SampEn values after the Asian currency crisis are significantly higher than those before the Asian currency crisis. Comparison with the correlation coefficient shows that cross-SampEn is superior to describe the correlation between time series.

Dynamical manifestations of quantum chaos: correlation hole and bulge

NASA Astrophysics Data System (ADS)

Torres-Herrera, E. J.; Santos, Lea F.

2017-10-01

A main feature of a chaotic quantum system is a rigid spectrum where the levels do not cross. We discuss how the presence of level repulsion in lattice many-body quantum systems can be detected from the analysis of their time evolution instead of their energy spectra. This approach is advantageous to experiments that deal with dynamics, but have limited or no direct access to spectroscopy. Dynamical manifestations of avoided crossings occur at long times. They correspond to a drop, referred to as correlation hole, below the asymptotic value of the survival probability and to a bulge above the saturation point of the von Neumann entanglement entropy and the Shannon information entropy. By contrast, the evolution of these quantities at shorter times reflects the level of delocalization of the initial state, but not necessarily a rigid spectrum. The correlation hole is a general indicator of the integrable-chaos transition in disordered and clean models and as such can be used to detect the transition to the many-body localized phase in disordered interacting systems. This article is part of the themed issue 'Breakdown of ergodicity in quantum systems: from solids to synthetic matter'.

Genomic validation of the differential preservation of population history in modern human cranial anatomy.

PubMed

Reyes-Centeno, Hugo; Ghirotto, Silvia; Harvati, Katerina

2017-01-01

In modern humans, the significant correlation between neutral genetic loci and cranial anatomy suggests that the cranium preserves a population history signature. However, there is disagreement on whether certain parts of the cranium preserve this signature to a greater degree than other parts. It is also unclear how different quantitative measures of phenotype affect the association of genetic variation and anatomy. Here, we revisit these matters by testing the correlation of genetic distances and various phenotypic distances for ten modern human populations. Geometric morphometric shape data from the crania of adult individuals (n = 224) are used to calculate phenotypic P ST , Procrustes, and Mahalanobis distances. We calculate their correlation to neutral genetic distances, F ST , derived from single nucleotide polymorphisms (SNPs). We subset the cranial data into landmark configurations that include the neurocranium, the face, and the temporal bone in order to evaluate whether these cranial regions are differentially correlated to neutral genetic variation. Our results show that P ST , Mahalanobis, and Procrustes distances are correlated with F ST distances to varying degrees. They indicate that overall cranial shape is significantly correlated with neutral genetic variation. Of the component parts examined, P ST distances for both the temporal bone and the face have a stronger association with F ST distances than the neurocranium. When controlling for population divergence time, only the whole cranium and the temporal bone have a statistically significant association with F ST distances. Our results confirm that the cranium, as a whole, and the temporal bone can be used to reconstruct modern human population history. © 2016 Wiley Periodicals, Inc.

A Numerical Investigation of the Burnett Equations Based on the Second Law

NASA Technical Reports Server (NTRS)

Comeaux, Keith A.; Chapman, Dean R.; MacCormack, Robert W.; Edwards, Thomas A. (Technical Monitor)

1995-01-01

The Burnett equations have been shown to potentially violate the second law of thermodynamics. The objective of this investigation is to correlate the numerical problems experienced by the Burnett equations to the negative production of entropy. The equations have had a long history of numerical instability to small wavelength disturbances. Recently, Zhong corrected the instability problem and made solutions attainable for one dimensional shock waves and hypersonic blunt bodies. Difficulties still exist when attempting to solve hypersonic flat plate boundary layers and blunt body wake flows, however. Numerical experiments will include one-dimensional shock waves, quasi-one dimensional nozzles, and expanding Prandlt-Meyer flows and specifically examine the entropy production for these cases.

Quantifying networks complexity from information geometry viewpoint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Felice, Domenico, E-mail: domenico.felice@unicam.it; Mancini, Stefano; INFN-Sezione di Perugia, Via A. Pascoli, I-06123 Perugia

We consider a Gaussian statistical model whose parameter space is given by the variances of random variables. Underlying this model we identify networks by interpreting random variables as sitting on vertices and their correlations as weighted edges among vertices. We then associate to the parameter space a statistical manifold endowed with a Riemannian metric structure (that of Fisher-Rao). Going on, in analogy with the microcanonical definition of entropy in Statistical Mechanics, we introduce an entropic measure of networks complexity. We prove that it is invariant under networks isomorphism. Above all, considering networks as simplicial complexes, we evaluate this entropy onmore » simplexes and find that it monotonically increases with their dimension.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alcaraz, Francisco Castilho; Ibanez Berganza, Miguel; Sierra, German

In a quantum critical chain, the scaling regime of the energy and momentum of the ground state and low-lying excitations are described by conformal field theory (CFT). The same holds true for the von Neumann and Renyi entropies of the ground state, which display a universal logarithmic behavior depending on the central charge. In this Letter we generalize this result to those excited states of the chain that correspond to primary fields in CFT. It is shown that the nth Renyi entropy is related to a 2n-point correlator of primary fields. We verify this statement for the critical XX andmore » XXZ chains. This result uncovers a new link between quantum information theory and CFT.« less

Better late than never: information retrieval from black holes.

PubMed

Braunstein, Samuel L; Pirandola, Stefano; Życzkowski, Karol

2013-03-08

We show that, in order to preserve the equivalence principle until late times in unitarily evaporating black holes, the thermodynamic entropy of a black hole must be primarily entropy of entanglement across the event horizon. For such black holes, we show that the information entering a black hole becomes encoded in correlations within a tripartite quantum state, the quantum analogue of a one-time pad, and is only decoded into the outgoing radiation very late in the evaporation. This behavior generically describes the unitary evaporation of highly entangled black holes and requires no specially designed evolution. Our work suggests the existence of a matter-field sum rule for any fundamental theory.

Detection of Dendritic Spines Using Wavelet Packet Entropy and Fuzzy Support Vector Machine.

PubMed

Wang, Shuihua; Li, Yang; Shao, Ying; Cattani, Carlo; Zhang, Yudong; Du, Sidan

2017-01-01

The morphology of dendritic spines is highly correlated with the neuron function. Therefore, it is of positive influence for the research of the dendritic spines. However, it is tried to manually label the spine types for statistical analysis. In this work, we proposed an approach based on the combination of wavelet contour analysis for the backbone detection, wavelet packet entropy, and fuzzy support vector machine for the spine classification. The experiments show that this approach is promising. The average detection accuracy of "MushRoom" achieves 97.3%, "Stubby" achieves 94.6%, and "Thin" achieves 97.2%. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Faithful nonclassicality indicators and extremal quantum correlations in two-qubit states

NASA Astrophysics Data System (ADS)

Girolami, Davide; Paternostro, Mauro; Adesso, Gerardo

2011-09-01

The state disturbance induced by locally measuring a quantum system yields a signature of nonclassical correlations beyond entanglement. Here, we present a detailed study of such correlations for two-qubit mixed states. To overcome the asymmetry of quantum discord and the unfaithfulness of measurement-induced disturbance (severely overestimating quantum correlations), we propose an ameliorated measurement-induced disturbance as nonclassicality indicator, optimized over joint local measurements, and we derive its closed expression for relevant two-qubit states. We study its analytical relation with discord, and characterize the maximally quantum-correlated mixed states, that simultaneously extremize both quantifiers at given von Neumann entropy: among all two-qubit states, these states possess the most robust quantum correlations against noise.

Long-range dismount activity classification: LODAC

NASA Astrophysics Data System (ADS)

Garagic, Denis; Peskoe, Jacob; Liu, Fang; Cuevas, Manuel; Freeman, Andrew M.; Rhodes, Bradley J.

2014-06-01

Continuous classification of dismount types (including gender, age, ethnicity) and their activities (such as walking, running) evolving over space and time is challenging. Limited sensor resolution (often exacerbated as a function of platform standoff distance) and clutter from shadows in dense target environments, unfavorable environmental conditions, and the normal properties of real data all contribute to the challenge. The unique and innovative aspect of our approach is a synthesis of multimodal signal processing with incremental non-parametric, hierarchical Bayesian machine learning methods to create a new kind of target classification architecture. This architecture is designed from the ground up to optimally exploit correlations among the multiple sensing modalities (multimodal data fusion) and rapidly and continuously learns (online self-tuning) patterns of distinct classes of dismounts given little a priori information. This increases classification performance in the presence of challenges posed by anti-access/area denial (A2/AD) sensing. To fuse multimodal features, Long-range Dismount Activity Classification (LODAC) develops a novel statistical information theoretic approach for multimodal data fusion that jointly models multimodal data (i.e., a probabilistic model for cross-modal signal generation) and discovers the critical cross-modal correlations by identifying components (features) with maximal mutual information (MI) which is efficiently estimated using non-parametric entropy models. LODAC develops a generic probabilistic pattern learning and classification framework based on a new class of hierarchical Bayesian learning algorithms for efficiently discovering recurring patterns (classes of dismounts) in multiple simultaneous time series (sensor modalities) at multiple levels of feature granularity.

A full-Bayesian approach to parameter inference from tracer travel time moments and investigation of scale effects at the Cape Cod experimental site

USGS Publications Warehouse

Woodbury, Allan D.; Rubin, Yoram

2000-01-01

A method for inverting the travel time moments of solutes in heterogeneous aquifers is presented and is based on peak concentration arrival times as measured at various samplers in an aquifer. The approach combines a Lagrangian [Rubin and Dagan, 1992] solute transport framework with full‐Bayesian hydrogeological parameter inference. In the full‐Bayesian approach the noise values in the observed data are treated as hyperparameters, and their effects are removed by marginalization. The prior probability density functions (pdfs) for the model parameters (horizontal integral scale, velocity, and log K variance) and noise values are represented by prior pdfs developed from minimum relative entropy considerations. Analysis of the Cape Cod (Massachusetts) field experiment is presented. Inverse results for the hydraulic parameters indicate an expected value for the velocity, variance of log hydraulic conductivity, and horizontal integral scale of 0.42 m/d, 0.26, and 3.0 m, respectively. While these results are consistent with various direct‐field determinations, the importance of the findings is in the reduction of confidence range about the various expected values. On selected control planes we compare observed travel time frequency histograms with the theoretical pdf, conditioned on the observed travel time moments. We observe a positive skew in the travel time pdf which tends to decrease as the travel time distance grows. We also test the hypothesis that there is no scale dependence of the integral scale λ with the scale of the experiment at Cape Cod. We adopt two strategies. The first strategy is to use subsets of the full data set and then to see if the resulting parameter fits are different as we use different data from control planes at expanding distances from the source. The second approach is from the viewpoint of entropy concentration. No increase in integral scale with distance is inferred from either approach over the range of the Cape Cod tracer experiment.

Develop and Test a Solvent Accessible Surface Area-Based Model in Conformational Entropy Calculations

PubMed Central

Wang, Junmei; Hou, Tingjun

2012-01-01

It is of great interest in modern drug design to accurately calculate the free energies of protein-ligand or nucleic acid-ligand binding. MM-PBSA (Molecular Mechanics-Poisson Boltzmann Surface Area) and MM-GBSA (Molecular Mechanics-Generalized Born Surface Area) have gained popularity in this field. For both methods, the conformational entropy, which is usually calculated through normal mode analysis (NMA), is needed to calculate the absolute binding free energies. Unfortunately, NMA is computationally demanding and becomes a bottleneck of the MM-PB/GBSA-NMA methods. In this work, we have developed a fast approach to estimate the conformational entropy based upon solvent accessible surface area calculations. In our approach, the conformational entropy of a molecule, S, can be obtained by summing up the contributions of all atoms, no matter they are buried or exposed. Each atom has two types of surface areas, solvent accessible surface area (SAS) and buried SAS (BSAS). The two types of surface areas are weighted to estimate the contribution of an atom to S. Atoms having the same atom type share the same weight and a general parameter k is applied to balance the contributions of the two types of surface areas. This entropy model was parameterized using a large set of small molecules for which their conformational entropies were calculated at the B3LYP/6-31G* level taking the solvent effect into account. The weighted solvent accessible surface area (WSAS) model was extensively evaluated in three tests. For the convenience, TS, the product of temperature T and conformational entropy S, were calculated in those tests. T was always set to 298.15 K through the text. First of all, good correlations were achieved between WSAS TS and NMA TS for 44 protein or nucleic acid systems sampled with molecular dynamics simulations (10 snapshots were collected for post-entropy calculations): the mean correlation coefficient squares (R2) was 0.56. As to the 20 complexes, the TS changes upon binding, TΔS, were also calculated and the mean R2 was 0.67 between NMA and WSAS. In the second test, TS were calculated for 12 proteins decoy sets (each set has 31 conformations) generated by the Rosetta software package. Again, good correlations were achieved for all decoy sets: the mean, maximum, minimum of R2 were 0.73, 0.89 and 0.55, respectively. Finally, binding free energies were calculated for 6 protein systems (the numbers of inhibitors range from 4 to 18) using four scoring functions. Compared to the measured binding free energies, the mean R2 of the six protein systems were 0.51, 0.47, 0.40 and 0.43 for MM-GBSA-WSAS, MM-GBSA-NMA, MM-PBSA-WSAS and MM-PBSA-NMA, respectively. The mean RMS errors of prediction were 1.19, 1.24, 1.41, 1.29 kcal/mol for the four scoring functions, correspondingly. Therefore, the two scoring functions employing WSAS achieved a comparable prediction performance to that of the scoring functions using NMA. It should be emphasized that no minimization was performed prior to the WSAS calculation in the last test. Although WSAS is not as rigorous as physical models such as quasi-harmonic analysis and thermodynamic integration (TI), it is computationally very efficient as only surface area calculation is involved and no structural minimization is required. Moreover, WSAS has achieved a comparable performance to normal mode analysis. We expect that this model could find its applications in the fields like high throughput screening (HTS), molecular docking and rational protein design. In those fields, efficiency is crucial since there are a large number of compounds, docking poses or protein models to be evaluated. A list of acronyms and abbreviations used in this work is provided for quick reference. PMID:22497310

Optimization of rainfall networks using information entropy and temporal variability analysis

NASA Astrophysics Data System (ADS)

Wang, Wenqi; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

2018-04-01

Rainfall networks are the most direct sources of precipitation data and their optimization and evaluation are essential and important. Information entropy can not only represent the uncertainty of rainfall distribution but can also reflect the correlation and information transmission between rainfall stations. Using entropy this study performs optimization of rainfall networks that are of similar size located in two big cities in China, Shanghai (in Yangtze River basin) and Xi'an (in Yellow River basin), with respect to temporal variability analysis. Through an easy-to-implement greedy ranking algorithm based on the criterion called, Maximum Information Minimum Redundancy (MIMR), stations of the networks in the two areas (each area is further divided into two subareas) are ranked during sliding inter-annual series and under different meteorological conditions. It is found that observation series with different starting days affect the ranking, alluding to the temporal variability during network evaluation. We propose a dynamic network evaluation framework for considering temporal variability, which ranks stations under different starting days with a fixed time window (1-year, 2-year, and 5-year). Therefore, we can identify rainfall stations which are temporarily of importance or redundancy and provide some useful suggestions for decision makers. The proposed framework can serve as a supplement for the primary MIMR optimization approach. In addition, during different periods (wet season or dry season) the optimal network from MIMR exhibits differences in entropy values and the optimal network from wet season tended to produce higher entropy values. Differences in spatial distribution of the optimal networks suggest that optimizing the rainfall network for changing meteorological conditions may be more recommended.

Integrated design of multivariable hydrometric networks using entropy theory with a multiobjective optimization approach

NASA Astrophysics Data System (ADS)

Kim, Y.; Hwang, T.; Vose, J. M.; Martin, K. L.; Band, L. E.

2016-12-01

Obtaining quality hydrologic observations is the first step towards a successful water resources management. While remote sensing techniques have enabled to convert satellite images of the Earth's surface to hydrologic data, the importance of ground-based observations has never been diminished because in-situ data are often highly accurate and can be used to validate remote measurements. The existence of efficient hydrometric networks is becoming more important to obtain as much as information with minimum redundancy. The World Meteorological Organization (WMO) has recommended a guideline for the minimum hydrometric network density based on physiography; however, this guideline is not for the optimum network design but for avoiding serious deficiency from a network. Moreover, all hydrologic variables are interconnected within the hydrologic cycle, while monitoring networks have been designed individually. This study proposes an integrated network design method using entropy theory with a multiobjective optimization approach. In specific, a precipitation and a streamflow networks in a semi-urban watershed in Ontario, Canada were designed simultaneously by maximizing joint entropy, minimizing total correlation, and maximizing conditional entropy of streamflow network given precipitation network. After comparing with the typical individual network designs, the proposed design method would be able to determine more efficient optimal networks by avoiding the redundant stations, in which hydrologic information is transferable. Additionally, four quantization cases were applied in entropy calculations to assess their implications on the station rankings and the optimal networks. The results showed that the selection of quantization method should be considered carefully because the rankings and optimal networks are subject to change accordingly.

Integrated design of multivariable hydrometric networks using entropy theory with a multiobjective optimization approach

NASA Astrophysics Data System (ADS)

Keum, J.; Coulibaly, P. D.

2017-12-01

Obtaining quality hydrologic observations is the first step towards a successful water resources management. While remote sensing techniques have enabled to convert satellite images of the Earth's surface to hydrologic data, the importance of ground-based observations has never been diminished because in-situ data are often highly accurate and can be used to validate remote measurements. The existence of efficient hydrometric networks is becoming more important to obtain as much as information with minimum redundancy. The World Meteorological Organization (WMO) has recommended a guideline for the minimum hydrometric network density based on physiography; however, this guideline is not for the optimum network design but for avoiding serious deficiency from a network. Moreover, all hydrologic variables are interconnected within the hydrologic cycle, while monitoring networks have been designed individually. This study proposes an integrated network design method using entropy theory with a multiobjective optimization approach. In specific, a precipitation and a streamflow networks in a semi-urban watershed in Ontario, Canada were designed simultaneously by maximizing joint entropy, minimizing total correlation, and maximizing conditional entropy of streamflow network given precipitation network. After comparing with the typical individual network designs, the proposed design method would be able to determine more efficient optimal networks by avoiding the redundant stations, in which hydrologic information is transferable. Additionally, four quantization cases were applied in entropy calculations to assess their implications on the station rankings and the optimal networks. The results showed that the selection of quantization method should be considered carefully because the rankings and optimal networks are subject to change accordingly.

Sleeping distance in wild wolf packs

USGS Publications Warehouse

Knick, S.T.; Mech, L.D.

1980-01-01

Sleeping distances were observed among members of 13 wild wolf (Canis lupus) packs and 11 pairs in northeastern Minnesota to determine if the distances correlated with pack size and composition. The study utilized aerial radio-tracking and observation during winter. Pack size and number of adults per pack were inversely related to pack average sleeping distance and variability. No correlation between sleeping distance and microclimate was observed. Possible relationships between social bonding and our results are discussed.

Entropy Production in Convective Hydrothermal Systems

NASA Astrophysics Data System (ADS)

Boersing, Nele; Wellmann, Florian; Niederau, Jan

2016-04-01

Exploring hydrothermal reservoirs requires reliable estimates of subsurface temperatures to delineate favorable locations of boreholes. It is therefore of fundamental and practical importance to understand the thermodynamic behavior of the system in order to predict its performance with numerical studies. To this end, the thermodynamic measure of entropy production is considered as a useful abstraction tool to characterize the convective state of a system since it accounts for dissipative heat processes and gives insight into the system's average behavior in a statistical sense. Solving the underlying conservation principles of a convective hydrothermal system is sensitive to initial conditions and boundary conditions which in turn are prone to uncertain knowledge in subsurface parameters. There exist multiple numerical solutions to the mathematical description of a convective system and the prediction becomes even more challenging as the vigor of convection increases. Thus, the variety of possible modes contained in such highly non-linear problems needs to be quantified. A synthetic study is carried out to simulate fluid flow and heat transfer in a finite porous layer heated from below. Various two-dimensional models are created such that their corresponding Rayleigh numbers lie in a range from the sub-critical linear to the supercritical non-linear regime, that is purely conductive to convection-dominated systems. Entropy production is found to describe the transient evolution of convective processes fairly well and can be used to identify thermodynamic equilibrium. Additionally, varying the aspect ratio for each Rayleigh number shows that the variety of realized convection modes increases with both larger aspect ratio and higher Rayleigh number. This phenomenon is also reflected by an enlarged spread of entropy production for the realized modes. Consequently, the Rayleigh number can be correlated to the magnitude of entropy production. In cases of moderate Rayleigh number and moderate aspect ratio, entropy production even enables to predict a preferred convection mode for a model with homogeneous parameter distribution. As a general rule, the thermodynamic measure of entropy production can be used to analyze uncertainties accompanied by modelling convective hydrothermal systems. Without considering any probability distributions of input data, this synthetic study shows that a higher entropy production implies a lower ability to uniquely predict the convection pattern. This in turn means that the uncertainty in estimating subsurface temperatures is higher.

Entropy generation method to quantify thermal comfort.

PubMed

Boregowda, S C; Tiwari, S N; Chaturvedi, S K

2001-12-01

The present paper presents a thermodynamic approach to assess the quality of human-thermal environment interaction and quantify thermal comfort. The approach involves development of entropy generation term by applying second law of thermodynamics to the combined human-environment system. The entropy generation term combines both human thermal physiological responses and thermal environmental variables to provide an objective measure of thermal comfort. The original concepts and definitions form the basis for establishing the mathematical relationship between thermal comfort and entropy generation term. As a result of logic and deterministic approach, an Objective Thermal Comfort Index (OTCI) is defined and established as a function of entropy generation. In order to verify the entropy-based thermal comfort model, human thermal physiological responses due to changes in ambient conditions are simulated using a well established and validated human thermal model developed at the Institute of Environmental Research of Kansas State University (KSU). The finite element based KSU human thermal computer model is being utilized as a "Computational Environmental Chamber" to conduct series of simulations to examine the human thermal responses to different environmental conditions. The output from the simulation, which include human thermal responses and input data consisting of environmental conditions are fed into the thermal comfort model. Continuous monitoring of thermal comfort in comfortable and extreme environmental conditions is demonstrated. The Objective Thermal Comfort values obtained from the entropy-based model are validated against regression based Predicted Mean Vote (PMV) values. Using the corresponding air temperatures and vapor pressures that were used in the computer simulation in the regression equation generates the PMV values. The preliminary results indicate that the OTCI and PMV values correlate well under ideal conditions. However, an experimental study is needed in the future to fully establish the validity of the OTCI formula and the model. One of the practical applications of this index is that could it be integrated in thermal control systems to develop human-centered environmental control systems for potential use in aircraft, mass transit vehicles, intelligent building systems, and space vehicles.

Entropy generation method to quantify thermal comfort

NASA Technical Reports Server (NTRS)

Boregowda, S. C.; Tiwari, S. N.; Chaturvedi, S. K.

2001-01-01

The present paper presents a thermodynamic approach to assess the quality of human-thermal environment interaction and quantify thermal comfort. The approach involves development of entropy generation term by applying second law of thermodynamics to the combined human-environment system. The entropy generation term combines both human thermal physiological responses and thermal environmental variables to provide an objective measure of thermal comfort. The original concepts and definitions form the basis for establishing the mathematical relationship between thermal comfort and entropy generation term. As a result of logic and deterministic approach, an Objective Thermal Comfort Index (OTCI) is defined and established as a function of entropy generation. In order to verify the entropy-based thermal comfort model, human thermal physiological responses due to changes in ambient conditions are simulated using a well established and validated human thermal model developed at the Institute of Environmental Research of Kansas State University (KSU). The finite element based KSU human thermal computer model is being utilized as a "Computational Environmental Chamber" to conduct series of simulations to examine the human thermal responses to different environmental conditions. The output from the simulation, which include human thermal responses and input data consisting of environmental conditions are fed into the thermal comfort model. Continuous monitoring of thermal comfort in comfortable and extreme environmental conditions is demonstrated. The Objective Thermal Comfort values obtained from the entropy-based model are validated against regression based Predicted Mean Vote (PMV) values. Using the corresponding air temperatures and vapor pressures that were used in the computer simulation in the regression equation generates the PMV values. The preliminary results indicate that the OTCI and PMV values correlate well under ideal conditions. However, an experimental study is needed in the future to fully establish the validity of the OTCI formula and the model. One of the practical applications of this index is that could it be integrated in thermal control systems to develop human-centered environmental control systems for potential use in aircraft, mass transit vehicles, intelligent building systems, and space vehicles.

Correlation of the tibial tuberosity-trochlear groove distance with the Q-angle.

PubMed

Dickschas, Jörg; Harrer, Jörg; Bayer, Thomas; Schwitulla, Judith; Strecker, Wolf

2016-03-01

The Q-angle has been used for years to quantify lateralization of the patella. The tibial tuberosity-trochlea groove distance (TT-TG distance) was introduced to analyse patellar tracking. Does a significant correlation exist between these two parameters? Do other significant interrelations exist between the Q-angle/TT-TG distance, torsion of the femur and tibia, the frontal axis, overall leg length, gender, former patellar dislocation, BMI? One hundred knees in 55 patients with patellofemoral symptoms were included in a prospective study. All patients underwent clinical examination, including measurement of the Q-angle. A torsional CT was obtained from all patients. The correlation coefficient was 0.33/0.34 (left/right leg), showing that the TT-TG distance tends to rise in direct ratio to a rising Q-angle. Thus, a significant correlation was found (p = 0.017). Femoral and tibial torsion had a positive effect on the TT-TG distance, but showed no significant correlation. Leg length had a significant effect on the TT-TG distance (p = 0.04). The frontal axis had a nonsignificant influence on the Q-angle or TT-TG distance. On average, the Q-angle in women was 2.38° greater than it was in men, but the difference was not significant. A significant correlation was noted between the Q-angle and the TT-TG distance. Both depend on various parameters and must be assessed for the analysis of patellofemoral maltracking. The Q-angle did not differ significantly between men and women; thus, the conclusion is that no different ranges need not be used. Diagnostic study, Level III.

Comparison of efficiency of distance measurement methodologies in mango (Mangifera indica) progenies based on physicochemical descriptors.

PubMed

Alves, E O S; Cerqueira-Silva, C B M; Souza, A M; Santos, C A F; Lima Neto, F P; Corrêa, R X

2012-03-14

We investigated seven distance measures in a set of observations of physicochemical variables of mango (Mangifera indica) submitted to multivariate analyses (distance, projection and grouping). To estimate the distance measurements, five mango progeny (total of 25 genotypes) were analyzed, using six fruit physicochemical descriptors (fruit weight, equatorial diameter, longitudinal diameter, total soluble solids in °Brix, total titratable acidity, and pH). The distance measurements were compared by the Spearman correlation test, projection in two-dimensional space and grouping efficiency. The Spearman correlation coefficients between the seven distance measurements were, except for the Mahalanobis' generalized distance (0.41 ≤ rs ≤ 0.63), high and significant (rs ≥ 0.91; P < 0.001). Regardless of the origin of the distance matrix, the unweighted pair group method with arithmetic mean grouping method proved to be the most adequate. The various distance measurements and grouping methods gave different values for distortion (-116.5 ≤ D ≤ 74.5), cophenetic correlation (0.26 ≤ rc ≤ 0.76) and stress (-1.9 ≤ S ≤ 58.9). Choice of distance measurement and analysis methods influence the.

Metal-organic complexes in geochemical processes: Estimation of standard partial molal thermodynamic properties of aqueous complexes between metal cations and monovalent organic acid ligands at high pressures and temperatures

NASA Astrophysics Data System (ADS)

Shock, Everetr L.; Koretsky, Carla M.

1995-04-01

Regression of standard state equilibrium constants with the revised Helgeson-Kirkham-Flowers (HKF) equation of state allows evaluation of standard partial molal entropies ( overlineSo) of aqueous metal-organic complexes involving monovalent organic acid ligands. These values of overlineSo provide the basis for correlations that can be used, together with correlation algorithms among standard partial molal properties of aqueous complexes and equation-of-state parameters, to estimate thermodynamic properties including equilibrium constants for complexes between aqueous metals and several monovalent organic acid ligands at the elevated pressures and temperatures of many geochemical processes which involve aqueous solutions. Data, parameters, and estimates are given for 270 formate, propanoate, n-butanoate, n-pentanoate, glycolate, lactate, glycinate, and alanate complexes, and a consistent algorithm is provided for making other estimates. Standard partial molal entropies of association ( Δ -Sro) for metal-monovalent organic acid ligand complexes fall into at least two groups dependent upon the type of functional groups present in the ligand. It is shown that isothermal correlations among equilibrium constants for complex formation are consistent with one another and with similar correlations for inorganic metal-ligand complexes. Additional correlations allow estimates of standard partial molal Gibbs free energies of association at 25°C and 1 bar which can be used in cases where no experimentally derived values are available.