ALBERT

Description: A deformed exponential family is a generalization of exponential families. Since the useful classes of power law tailed distributions are described by the deformed exponential families, they are important objects in the theory of complex systems. Though the deformed exponential families are defined by deformed exponential functions, these functions do not satisfy the law of exponents in general. The deformed algebras have been introduced based on the deformed exponential functions. In this paper, after summarizing such deformed algebraic structures, it is clarified how deformed algebras work on deformed exponential families. In fact, deformed algebras cause generalization of expectations. The three kinds of expectations for random variables are introduced in this paper, and it is discussed why these generalized expectations are natural from the viewpoint of information geometry. In addition, deformed algebras cause generalization of independences. Whereas it is difficult to check the well-definedness of deformed independence in general, the κ-independence is always well-defined on κ-exponential families. This is one of advantages of κ-exponential families in complex systems. Consequently, we can well generalize the maximum likelihood method for the κ-exponential family from the viewpoint of information geometry.

Description: We consider the problem of learning a Bayesian network structure given n examples and the prior probability based on maximizing the posterior probability. We propose an algorithm that runs in O(n log n) time and that addresses continuous variables and discrete variables without assuming any class of distribution. We prove that the decision is strongly consistent, i.e., correct with probability one as n ! 1. To date, consistency has only been obtained for discrete variables for this class of problem, and many authors have attempted to prove consistency when continuous variables are present. Furthermore, we prove that the “log n” term that appears in the penalty term of the description length can be replaced by 2(1+ε) log log n to obtain strong consistency, where ε > 0 is arbitrary, which implies that the Hannan–Quinn proposition holds.

Description: Aiming at the combined power quality +disturbance recognition, an automated recognition method based on wavelet packet entropy (WPE) and modified incomplete S-transform (MIST) is proposed in this paper. By combining wavelet packet Tsallis singular entropy, energy entropy and MIST, a 13-dimension vector of different power quality (PQ) disturbances including single disturbances and combined disturbances is extracted. Then, a ruled decision tree is designed to recognize the combined disturbances. The proposed method is tested and evaluated using a large number of simulated PQ disturbances and some real-life signals, which include voltage sag, swell, interruption, oscillation transient, impulsive transient, harmonics, voltage fluctuation and their combinations. In addition, the comparison of the proposed recognition approach with some existing techniques is made. The experimental results show that the proposed method can effectively recognize the single and combined PQ disturbances.

Description: For general metric theories of gravity, we compare the approach that describes/derives the field equations of gravity as a thermodynamic identity with the one which looks at them from entropy bounds. The comparison is made through the consideration of the matter entropy flux across (Rindler) horizons, studied by making use of the notion of a limiting thermodynamic scale l* of matter, previously introduced in the context of entropy bounds. In doing this: (i) a bound for the entropy of any lump of matter with a given energy-momentum tensor Tab is considered, in terms of a quantity, which is independent of the theory of gravity that we use; this quantity is the variation of the Clausius entropy of a suitable horizon when the element of matter crosses it; (ii) by making use of the equations of motion of the theory, the same quantity is then expressed as the variation of Wald’s entropy of that horizon (and this leads to a generalized form of the generalized covariant entropy bound, applicable to general diffeomorphism-invariant theories of gravity); and (iii) a notion of l* for horizons, as well as an expression for it, is given.

Description: This paper introduces a new simple system with a butterfly chaotic attractor. This system has rich and complex dynamics. With some typical parameters, its Lyapunov dimension is greater than other known three dimensional chaotic systems. It exhibits chaotic behavior over a large range of parameters, and the divergence of flow of this system is not a constant. The dynamics of this new system are analyzed via Lyapunov exponent spectrum, bifurcation diagrams, phase portraits and the Poincaré map. The compound structures of this new system are also analyzed. By means of topological horseshoe theory and numerical computation, the Poincaré map defined for the system is proved to be semi-conjugate to 3-shift map, and thus the system has positive topological entropy.

Description: In this paper, the problem of robust control of nonlinear fractional-order systems in the presence of uncertainties and external disturbance is investigated. Fuzzy logic systems are used for estimating the unknown nonlinear functions. Based on the fractional Lyapunov direct method and some proposed Lemmas, an adaptive fuzzy controller is designed. The proposed method can guarantee all the signals in the closed-loop systems remain bounded and the tracking errors converge to an arbitrary small region of the origin. Lastly, an illustrative example is given to demonstrate the effectiveness of the proposed results.

Description: In this paper, we investigate the basic properties of binary classification with a pseudo model based on the Itakura–Saito distance and reveal that the Itakura–Saito distance is a unique appropriate measure for estimation with the pseudo model in the framework of general Bregman divergence. Furthermore, we propose a novelmulti-task learning algorithm based on the pseudo model in the framework of the ensemble learning method. We focus on a specific setting of the multi-task learning for binary classification problems. The set of features is assumed to be common among all tasks, which are our targets of performance improvement. We consider a situation where the shared structures among the dataset are represented by divergence between underlying distributions associated with multiple tasks. We discuss statistical properties of the proposed method and investigate the validity of the proposed method with numerical experiments.

Description: Fruit classification is quite difficult because of the various categories and similar shapes and features of fruit. In this work, we proposed two novel machine-learning based classification methods. The developed system consists of wavelet entropy (WE), principal component analysis (PCA), feedforward neural network (FNN) trained by fitness-scaled chaotic artificial bee colony (FSCABC) and biogeography-based optimization (BBO), respectively. The K-fold stratified cross validation (SCV) was utilized for statistical analysis. The classification performance for 1653 fruit images from 18 categories showed that the proposed “WE + PCA + FSCABC-FNN” and “WE + PCA + BBO-FNN” methods achieve the same accuracy of 89.5%, higher than state-of-the-art approaches: “(CH + MP + US) + PCA + GA-FNN ” of 84.8%, “(CH + MP + US) + PCA + PSO-FNN” of 87.9%, “(CH + MP + US) + PCA + ABC-FNN” of 85.4%, “(CH + MP + US) + PCA + kSVM” of 88.2%, and “(CH + MP + US) + PCA + FSCABC-FNN” of 89.1%. Besides, our methods used only 12 features, less than the number of features used by other methods. Therefore, the proposed methods are effective for fruit classification.

Description: We present a brief overview of some key concepts in the theory of generalized complex manifolds. This new geometry interpolates, so to speak, between symplectic geometry and complex geometry. As such it provides an ideal framework to analyze thermodynamical fluctuation theory in the presence of gravitational fields. To illustrate the usefulness of generalized complex geometry, we examine a simplified version of the Unruh effect: the thermalising effect of gravitational fields on the Schroedinger wavefunction.

Description: In modern industrial processes, it is easier and less expensive to configure alarms by software settings rather than by wiring, which causes the rapid growth of the number of alarms. Moreover, because there exist complex interactions, in particular the causal relationship among different parts in the process, a fault may propagate along propagation pathways once an abnormal situation occurs, which brings great difficulty to operators to identify its root cause immediately and to take proper actions correctly. Therefore, causality detection becomes a very important problem in the context of multivariate alarm analysis and design. Transfer entropy has become an effective and widely-used method to detect causality between different continuous process variables in both linear and nonlinear situations in recent years. However, such conventional methods to detect causality based on transfer entropy are computationally costly. Alternatively, using binary alarm series can be more computational-friendly and more direct because alarm data analysis is straightforward for alarm management in practice. The methodology and implementation issues are discussed in this paper. Illustrated by several case studies, including both numerical cases and simulated industrial cases, the proposed method is demonstrated to be suitable for industrial situations contaminated by noise.

Description: We provide an entropy analysis for light storage and light retrieval. In this analysis, entropy extraction and reduction in a typical light storage experiment are identified. The spatiotemporal behavior of entropy is presented for D1 transition in cold sodium atoms. The governing equations are the reduced Maxwell field equations and the Liouville–von Neumann equation for the density matrix of the dressed atom.

Description: The aeroderivate gas turbines are widely used for power generation in the oil and gas industry. In offshore marine platforms, the aeroderivative gas turbines provide the energy required to drive mechanically compressors, pumps and electric generators. Therefore, the study of the performance of aeroderivate gas turbines based on a parametric analysis is relevant to carry out a diagnostic of the engine, which can lead to operational as well as predictive and/or corrective maintenance actions. This work presents a methodology based on the exergetic analysis to estimate the irrevesibilities and exergetic efficiencies of the main components of a two-shaft aeroderivate gas turbine. The studied engine is the Solar Turbine Mars 100, which is rated to provide 11.86 MW. In this engine, the air is compressed in an axial compressor achieving a pressure ratio of 17.7 relative to ambient conditions and a high pressure turbine inlet temperature of 1220 °C. Even if the thermal efficiency associated to the pressure ratio of 17.7 is 1% lower than the maximum thermal efficiency, the irreversibilities related to this pressure ratio decrease approximately 1 GW with respect to irreversibilities of the optimal pressure ratio for the thermal efficiency. In addition, this paper contributes to develop a mathematical model to estimate the high turbine inlet temperature as well as the pressure ratio of the low and high pressure turbines.

Description: The minimum error entropy (MEE) criterion is an important learning criterion in information theoretical learning (ITL). However, the MEE solution cannot be obtained in closed form even for a simple linear regression problem, and one has to search it, usually, in an iterative manner. The fixed-point iteration is an efficient way to solve the MEE solution. In this work, we study a fixed-point MEE algorithm for linear regression, and our focus is mainly on the convergence issue. We provide a sufficient condition (although a little loose) that guarantees the convergence of the fixed-point MEE algorithm. An illustrative example is also presented.

Description: In the paper, we address Bayesian sensitivity issues when integrating experts’ judgments with available historical data in a case study about strategies for the preventive maintenance of low-pressure cast iron pipelines in an urban gas distribution network. We are interested in replacement priorities, as determined by the failure rates of pipelines deployed under different conditions. We relax the assumptions, made in previous papers, about the prior distributions on the failure rates and study changes in replacement priorities under different choices of generalized moment-constrained classes of priors. We focus on the set of non-dominated actions, and among them, we propose the least sensitive action as the optimal choice to rank different classes of pipelines, providing a sound approach to the sensitivity problem. Moreover, we are also interested in determining which classes have a failure rate exceeding a given acceptable value, considered as the threshold determining no need for replacement. Graphical tools are introduced to help decisionmakers to determine if pipelines are to be replaced and the corresponding priorities.

Description: This paper develops a class of density regression models based on proportional hazards family, namely, Gamma transformation proportional hazard (Gt-PH) model . Exact inference for the regression parameters and hazard ratio is derived. These estimators enjoy some good properties such as unbiased estimation, which may not be shared by other inference methods such as maximum likelihood estimate (MLE). Generalised confidence interval and hypothesis testing for regression parameters are also provided. The method itself is easy to implement in practice. The regression method is also extended to Lasso-based variable selection.

Description: Since Advanced Encryption Standard (AES) in stream modes, such as counter (CTR), output feedback (OFB) and cipher feedback (CFB), can meet most industrial requirements, the range of applications for dedicated stream ciphers is decreasing. There are many attack results using algebraic properties and side channel information against stream ciphers for hardware applications. Al-Hinai et al. presented an algebraic attack approach to a family of irregularly clock-controlled linear feedback shift register systems: the stop and go generator, self-decimated generator and alternating step generator. Other clock-controlled systems, such as shrinking and cascade generators, are indeed vulnerable against side channel attacks. To overcome these threats, new clock-controlled systems were presented, e.g., the generalized alternating step generator, cascade jump-controlled generator and mutual clock-controlled generator. However, the algebraic attack could be applied directly on these new systems. In this paper, we propose a new clock-controlled generator: the switching generator, which has resistance to algebraic and side channel attacks. This generator also preserves both security properties and the efficiency of existing clock-controlled generators.

Description: The Leptothrix species, Fe-oxidizing bacteria, produce an extracellular, microtubular sheath with a complicated organic–inorganic hybrid nature. We have discovered diverse industrial functions for this material, e.g., electrode material for Li-ion batteries, catalyst enhancers, pigments, plant growth promoters, and plant protectants. To consistently obtain material with the qualitative and quantitative stability needed for industrial applications, we focused on developing an optimum culture system for sheath synthesis by the Leptothrix sp. strain OUMS1. Although we have used Fe plates as an Fe source in the liquid silicon-glucose-peptone medium (SGP), the plates do not yield a consistent quality or precise mass, and formation of Fe-encrusted sheath is restricted to a surface of the plates, which limits harvest yield. In this study, to obtain a high yield of sheaths, we cultured OUMS1 in SGP supplemented with Fe powders. The addition of Fe powders to the medium (up to 14.0 g/L) did not adversely influence growth of OUMS1. The final yield of sheaths was about 10-fold greater than in the Fe plate culture. The sheaths also maintained a microtubular form and crystalline texture similar to those produced on Fe plates in SGP. The results proved the usefulness of Fe powder for consistently high yields of Fe-encrusted sheaths of stable quality.

Description: Portfolio selection in the financial literature has essentially been analyzed under two central assumptions: full knowledge of the joint probability distribution of the returns of the securities that will comprise the target portfolio; and investors’ preferences are expressed through a utility function. In the real world, operators build portfolios under risk constraints which are expressed both by their clients and regulators and which bear on the maximal loss that may be generated over a given time period at a given confidence level (the so-called Value at Risk of the position). Interestingly, in the finance literature, a serious discussion of how much or little is known from a probabilistic standpoint about the multi-dimensional density of the assets’ returns seems to be of limited relevance. Our approach in contrast is to highlight these issues and then adopt throughout a framework of entropy maximization to represent the real world ignorance of the “true” probability distributions, both univariate and multivariate, of traded securities’ returns. In this setting, we identify the optimal portfolio under a number of downside risk constraints. Two interesting results are exhibited: (i) the left- tail constraints are sufficiently powerful to override all other considerations in the conventional theory; (ii) the “barbell portfolio” (maximal certainty/ low risk in one set of holdings, maximal uncertainty in another), which is quite familiar to traders, naturally emerges in our construction.

Description: In this paper, the leader-following consensus algorithm, which is accompanied with compensations related to neighboring agents’ delayed states, is constructed for second-order multi-agent systems with communication delay. Using frequency-domain analysis, delay-independent and delay-dependent consensus conditions are obtained for second-order agents respectively to converge to the dynamical leader’s states asymptotically. Simulation illustrates the correctness of the results.

Description: Fluid machinery operating in the supersonic regime unveil avenues towards more compact technology. However, internal supersonic flows are associated with high aerodynamic and thermal penalties, which usually prevent their practical implementation. Indeed, both shock losses and the limited operational range represent particular challenges to aerodynamic designers that should be taken into account at the initial phase of the design process. This paper presents a design methodology for supersonic passages based on direct evaluations of the velocity field using the method of characteristics and computation of entropy generation across shock waves. This meshless function evaluation tool is then coupled to an optimization scheme, based on evolutionary algorithms that minimize the entropy generation across the supersonic passage. Finally, we assessed the results with 3D Reynolds Averaged Navier Stokes calculations.

Description: We propose a novel approach framed in terms of information theory and entropy to tackle the issue of the propagation of conspiracy theories. We represent the initial report of an event (such as the 9/11 terroristic attack) as a series of strings of information, each string classified by a two-state variable Ei = ±1, i = 1, …, N. If the values of the Ei are set to −1 for all strings, a state of minimum entropy is achieved. Comments on the report, focusing repeatedly on several strings Ek, might alternate their meaning (from −1 to +1). The representation of the event is turned fuzzy with an increased entropy value. Beyond some threshold value of entropy, chosen by simplicity to its maximum value, meaning N/2 variables with Ei = 1, the chance is created that a conspiracy theory might be initiated/propagated. Therefore, the evolution of the associated entropy is a way to measure the degree of penetration of a conspiracy theory. Our general framework relies on online content made voluntarily available by crowds of people, in response to some news or blog articles published by official news agencies. We apply different aggregation levels (comment, person, discussion thread) and discuss the associated patterns of entropy change.

Description: Signature schemes, proposed in 1976 by Diffie and Hellman, have become ubiquitous across modern communications. They allow for the exchange of messages from one sender to multiple recipients, with the guarantees that messages cannot be forged or tampered with and that messages also can be forwarded from one recipient to another without compromising their validity. Signatures are different from, but no less important than encryption, which ensures the privacy of a message. Commonly used signature protocols—signatures based on the Rivest–Adleman–Shamir (RSA) algorithm, the digital signature algorithm (DSA), and the elliptic curve digital signature algorithm (ECDSA)—are only computationally secure, similar to public key encryption methods. In fact, since these rely on the difficulty of finding discrete logarithms or factoring large primes, it is known that they will become completely insecure with the emergence of quantum computers. We may therefore see a shift towards signature protocols that will remain secure even in a post-quantum world. Ideally, such schemes would provide unconditional or information-theoretic security. In this paper, we aim to provide an accessible and comprehensive review of existing unconditionally securesecure signature schemes for signing classical messages, with a focus on unconditionally secure quantum signature schemes.

Description: Daily wind patterns and their relational associations with other metocean (oceanographic and meteorological) variables were algorithmically computed and extracted from a year-long wind and weather dataset, which was collected hourly from an ocean buoy located in the Penghu archipelago of Taiwan. The computational algorithm is called data cloud geometry (DCG). This DCG algorithm is a clustering-based nonparametric learning approach that was constructed and developed implicitly based on various entropy concepts. Regarding the bivariate aspect of wind speed and wind direction, the resulting multiscale clustering hierarchy revealed well-known wind characteristics of year-round pattern cycles pertaining to the particular geographic location of the buoy. A wind pattern due to a set of extreme weather days was also identified. Moreover, in terms of the relational aspect of wind and other weather variables, causal patterns were revealed through applying the DCG algorithm alternatively on the row and column axes of a data matrix by iteratively adapting distance measures to computed DCG tree structures. This adaptation technically constructed and integrated a multiscale, two-sample testing into the distance measure. These computed wind patterns and pattern-based causal relationships are useful for both general sailing and competition planning.

Description: In this paper, a fractional order economic system is studied. An active control technique is applied to control chaos in this system. The stabilization of equilibria is obtained by both theoretical analysis and the simulation result. The numerical simulations, via the improved Adams–Bashforth algorithm, show the effectiveness of the proposed controller.

Description: The structural changes along the c axis, of the Ba-exchanged montmorillonite (Swy-2-Ba), under variable relative humidity (% RH), is investigated. In this regard, the arrangement, amount and position of both exchangeable cation and the water molecules in the interlamellar space (IS), are evaluated. This aim is achieved using the X-ray diffraction (XRD) profile modeling approach that consists of comparing experimental and theoretical patterns calculated from structural models. The contributions of the hydration states and the interlayer water amounts, as a function of the % RH, are registered by quantitative XRD investigation. The validated structural models are heterogeneous, suggesting various proportions of layer types at different RH ranges, which means the coexistence of different mixed layer structure MLS packages, exhibiting different proportions of layers with contrasting hydration states. This result is attributed to the orientation of the applied hydration sequence. Indeed, the interlayer water molecule amounts, which led to the appearance of a logic hydration hysteresis, are strongly affected by hydrous perturbation.

Description: We describe how several metrics are possible in thermodynamic state space but that only one, Weinhold’s, has achieved widespread use. Lengths calculated based on this metric have been used to bound dissipation in finite-time (irreversible) processes be they continuous or discrete, and described in the energy picture or the entropy picture. Examples are provided from thermodynamics of heat conversion processes as well as chemical reactions. Even losses in economics can be bounded using a thermodynamic type metric. An essential foundation for the metric is a complete equation of state including all extensive variables of the system; examples are given. Finally, the second law of thermodynamics imposes convexity on any equation of state, be it analytical or empirical.

Description: Entropy provides a valuable tool for quantifying the regularity of physiological time series and provides important insights for understanding the underlying mechanisms of the cardiovascular system. Before any entropy calculation, certain common parameters need to be initialized: embedding dimension m, tolerance threshold r and time series length N. However, no specific guideline exists on how to determine the appropriate parameter values for distinguishing congestive heart failure (CHF) from normal sinus rhythm (NSR) subjects in clinical application. In the present study, a thorough analysis on the selection of appropriate values of m, r and N for sample entropy (SampEn) and recently proposed fuzzy measure entropy (FuzzyMEn) is presented for distinguishing two group subjects. 44 long-term NRS and 29 long-term CHF RR interval recordings from http://www.physionet.org were used as the non-pathological and pathological data respectively. Extreme (>2 s) and abnormal heartbeat RR intervals were firstly removed from each RR recording and then the recording was segmented with a non-overlapping segment length N of 300 and 1000, respectively. SampEn and FuzzyMEn were performed for each RR segment under different parameter combinations: m of 1, 2, 3 and 4, and r of 0.10, 0.15, 0.20 and 0.25 respectively. The statistical significance between NSR and CHF groups under each combination of m, r and N was observed. The results demonstrated that the selection of m, r and N plays a critical role in determining the SampEn and FuzzyMEn outputs. Compared with SampEn, FuzzyMEn shows a better regularity when selecting the parameters m and r. In addition, FuzzyMEn shows a better relative consistency for distinguishing the two groups, that is, the results of FuzzyMEn in the NSR group were consistently lower than those in the CHF group while SampEn were not. The selections of m of 2 and 3 and r of 0.10 and 0.15 for SampEn and the selections of m of 1 and 2 whenever r (herein, rL = rG = r) are for FuzzyMEn (in addition to setting nL = 3 and nG = 2) were recommended to yield the fine classification results for the NSR and CHF groups.

Description: In this paper, the fractional equations of the mass-spring-damper system with Caputo and Caputo–Fabrizio derivatives are presented. The physical units of the system are preserved by introducing an auxiliary parameter σ. The input of the resulting equations is a constant and periodic source; for the Caputo case, we obtain the analytical solution, and the resulting equations are given in terms of the Mittag–Leffler function; for the Caputo–Fabrizio approach, the numerical solutions are obtained by the numerical Laplace transform algorithm. Our results show that the mechanical components exhibit viscoelastic behaviors producing temporal fractality at different scales and demonstrate the existence of Entropy 2015, 17 6290 material heterogeneities in the mechanical components. The Markovian nature of the model is recovered when the order of the fractional derivatives is equal to one.

Description: We show explicitly, by using astrophysical data plus reasonable assumptions for the bulk viscosity in the cosmic fluid, how the magnitude of this viscosity may be high enough to drive the fluid from its position in the quintessence region at present time t = 0 across the barrier w =

Description: Several methods exist to construct complex networks from time series. In general, these methods claim to construct complex networks that preserve certain properties of the underlying dynamical system, and hence, they mark new ways of accessing quantitative indicators based on that dynamics. In this paper, we test this assertion by developing an algorithm to realize dynamical systems from these complex networks in such a way that trajectories of these dynamical systems produce time series that preserve certain statistical properties of the original time series (and hence, also the underlying true dynamical system). Trajectories from these networks are constructed from only the information in the network and are shown to be statistically equivalent to the original time series. In the context of this algorithm, we are able to demonstrate that the so-called adaptive k-nearest neighbour algorithm for generating networks out-performs methods based on ε-ball recurrence plots. For such networks, and with a suitable choice of parameter values, which we provide, the time series generated by this method function as a new kind of nonlinear surrogate generation algorithm. With this approach, we are able to test whether the simulation dynamics built from a complex network capture the underlying structure of the original system; whether the complex network is an adequate model of the dynamics.

Description: In this work, energy and exergy analyses are carried out for a combined cycle consisting of an organic Rankine cycle (ORC) and a liquefied natural gas (LNG) Rankine cycle for the recovery of low-grade heat sources and LNG cold energy. The effects of the turbine inlet pressure and the working fluid on the system performance are theoretically investigated. A modified temperature-enthalpy diagram is proposed, which can be useful to see the characteristics of the combined cycle, as well as the temperature distributions in the heat exchangers. Results show that the thermal efficiency increases with an increasing turbine inlet pressure and critical temperature of the working fluid. However, the exergy efficiency has a peak value with respect to the turbine inlet pressure, and the maximum exergy efficiency and the corresponding optimum turbine inlet pressure are significantly influenced by the selection of the working fluid. The exergy destruction at the condenser is generally the greatest among the exergy destruction components of the system.

Description: We give a brief survey of thermodynamic metrics, in particular the Hessian of the entropy function, and how they apply to black hole thermodynamics. We then provide a detailed discussion of the Gibbs surface of Kerr black holes. In particular, we analyze its global properties and extend it to take the entropy of the inner horizon into account. A brief discussion of Kerr–Newman black holes is included.

Description: In this paper, a new analytic iterative technique, called the residual power series method (RPSM), is applied to time fractional Whitham–Broer–Kaup equations. The explicit approximate traveling solutions are obtained by using this method. The efficiency and accuracy of the present method is demonstrated by two aspects. One is analyzing the approximate solutions graphically. The other is comparing the results with those of the Adomian decomposition method (ADM), the variational iteration method (VIM) and the optimal homotopy asymptotic method (OHAM). Illustrative examples reveal that the present technique outperforms the aforementioned methods and can be used as an alternative for solving fractional equations.

Description: To develop an automatic tea-category identification system with a high recall rate, we proposed a computer-vision and machine-learning based system, which did not require expensive signal acquiring devices and time-consuming procedures. We captured 300 tea images using a 3-CCD digital camera, and then extracted 64 color histogram features and 16 wavelet packet entropy (WPE) features to obtain color information and texture information, respectively. Principal component analysis was used to reduce features, which were fed into a fuzzy support vector machine (FSVM). Winner-take-all (WTA) was introduced to help the classifier deal with this 3-class problem. The 10 × 10-fold stratified cross-validation results show that the proposed FSVM + WTA method yields an overall recall rate of 97.77%, higher than 5 existing methods. In addition, the number of reduced features is only five, less than or equal to existing methods. The proposed method is effective for tea identification.

Description: We study the correlation properties of word lengths in large texts from 30 ebooks in the English language from the Gutenberg Project (www.gutenberg.org) using the natural visibility graph method (NVG). NVG converts a time series into a graph and then analyzes its graph properties. First, the original sequence of words is transformed into a sequence of values containing the length of each word, and then, it is integrated. Next, we apply the NVG to the integrated word-length series and construct the network. We show that the degree distribution of that network follows a power law, P ( k ) ∼ k - γ , with two regimes, which are characterized by the exponents γ s ≈ 1 . 7 (at short degree scales) and γ l ≈ 1 . 3 (at large degree scales). This suggests that word lengths are much more strongly correlated at large distances between words than at short distances between words. That finding is also supported by the detrended fluctuation analysis (DFA) and recurrence time distribution. These results provide new information about the universal characteristics of the structure of written texts beyond that given by word frequencies.

Description: There are a great number of thermodynamic schools, independent of each other, and without a powerful general approach, but with a split on non-equilibrium thermodynamics. In 1912, in relation to the stationary non-equilibrium states, Ehrenfest introduced the fundamental question on the existence of a functional that achieves its extreme value for stable states, as entropy does for the stationary states in equilibrium thermodynamics. Today, the new branch frontiers of science and engineering, from power engineering to environmental sciences, from chaos to complex systems, from life sciences to nanosciences, etc. require a unified approach in order to optimize results and obtain a powerful approach to non-equilibrium thermodynamics and open systems. In this paper, a generalization of the Gouy–Stodola approach is suggested as a possible answer to the Ehrenfest question.

Description: In this paper, we employed both first and second laws of thermodynamics to analyze the flow and thermal decomposition in a variable viscosity Couette flow of a conducting fluid in a rotating system under the combined influence of magnetic field and Hall current. The non-linear governing differential equations are obtained and solved numerically using shooting method coupled with fourth order Runge–Kutta–Fehlberg integration technique. Numerical results obtained for velocities and temperature profiles are utilized to determine the entropy generation rate, skin fictions, Nusselt number and the Bejan number. By plotting the graphs of various values of thermophysical parameters, the features of the flow characteristics are analyzed in detail. It is found that fluid rotation increases the dominant effect of heat transfer irreversibility at the upper moving plate region while the entropy production is more at the lower fixed plate region.

Description: The Canadian Nuclear Laboratories (CNL) is developing a long-term management strategy for its existing inventory of solid radioactive cemented wastes, which contain uranium, mercury, fission products, and a number of minor elements. The composition of the cemented radioactive waste poses significant impediments to the extraction and recovery of uranium using conventional technology. The goal of this research was to develop an innovative method for uranium, mercury and cesium recovery from surrogate radioactive cemented waste (SRCW). Leaching using sulfuric acid and saline media significantly improves the solubilization of the key elements from the SRCW. Increasing the NaCl concentration from 0.5 to 4 M increases the mercury solubilization from 82% to 96%. The sodium chloride forms a soluble mercury complex when mercury is present as HgO or metallic mercury but not with HgS that is found in 60 °C cured SRCW. Several leaching experiments were done using a sulfuric acid solution with KI to leach SRCW cured at 60 °C and/or aged for 30 months. Solubilization yields are above 97% for Cs and 98% for U and Hg. Leaching using sulfuric acid and KI improves the solubilization of Hg by oxidation of Hg0, as well as HgS, and form a mercury tetraiodide complex. Hg and Cs were selectively removed from the leachate prior to uranium recovery. It was found that U recovery from sulfuric leachate in iodide media using the resin Lewatit TP260 is very efficient. Considering these results, a process including effluent recirculation was applied. Improvements of solubilization due to the recycling of chemical reagents were observed during effluent recirculation.

Description: Sudden falls of large-area hard roofs in a mined area release a large amount of elastic energy, generate dynamic loads, and cause disasters such as impact ground pressure and gas outbursts. To address these problems, in this study, the sleeve fracturing method (SFM) was applied to weaken a hard roof. The numerical simulation software FLAC3D was used to develop three models based on an analysis of the SFM working mechanism. These models were applied to an analysis of the fracturing effects of various factors such as the borehole diameter, hole spacing, and sleeve pressure. Finally, the results of a simulation were validated using experiments with similar models. Our research indicated the following: (1) The crack propagation directions in the models were affected by the maximum principal stress and hole spacing. When the borehole diameter was fixed, the fracturing pressure increased with increasing hole spacing. In contrast, when the fracturing pressure was fixed, the fracturing range increased with increasing borehole diameter; (2) The most ideal fracturing effect was found at a fracturing pressure of 17.6 MPa in the model with a borehole diameter of 40 mm and hole spacing of 400 mm. The results showed that it is possible to regulate the falls of hard roofs using the SFM. This research may provide a theoretical basis for controlling hard roofs in mining.

Description: The functions of RNA molecules are defined by their spatial structure, whose folding is regulated by numerous factors making RNA very similar to proteins. Prediction of RNA folding nuclei gives the possibility to take a fresh look at the problems of the multiple folding pathways of RNA molecules and RNA stability. The algorithm previously developed for prediction of protein folding nuclei has been successfully applied to ~150 various RNA structures: hairpins, tRNAs, structures with pseudoknots, and the large structured P4-P6 domain of the Tetrahymena group I intron RNA. The calculated Φ-values for tRNA structures agree with the experimental data obtained earlier. According to the experiment the nucleotides of the D and T hairpin loops are the last to be involved in the tRNA tertiary structure. Such agreement allowed us to do a prediction for an example of large structured RNA, the P4-P6 RNA domain. One of the advantages of our method is that it allows us to make predictions about the folding nucleus for nontrivial RNA motifs: pseudoknots and tRNA.

Description: Iron(III) hydrolysis in the presence of chloride ions yields akaganéite, an iron oxyhydroxide mineral with a tunnel structure stabilized by the inclusion of chloride. Yet, the interactions of this anion with the iron oxyhydroxide precursors occurring during the hydrolysis process, as well as its mechanistic role during the formation of a solid phase are debated. Using a potentiometric titration assay in combination with a chloride ion-selective electrode, we have monitored the binding of chloride ions to nascent iron oxyhydroxides. Our results are consistent with earlier studies reporting that chloride ions bind to early occurring iron complexes. In addition, the data suggests that they are displaced with the onset of oxolation. Chloride ions in the akaganéite structure must be considered as remnants from the early stages of precipitation, as they do not influence the basic mechanism, or the kinetics of the hydrolysis reactions. The structure-directing role of chloride is based upon the early stages of the reaction. The presence of chloride in the tunnel-structure of akagenéite is due to a relatively strong binding to the earliest iron oxyhydroxide precursors, whereas it plays a rather passive role during the later stages of precipitation.

Description: During the measurement of friction force, the measured signal generally contains noise. To remove the noise and preserve the important features of the signal, a hybrid filtering method is introduced that uses the mutual information and a new waveform. This new waveform is the difference between the original signal and the sum of intrinsic mode functions (IMFs), which are obtained by empirical mode decomposition (EMD) or its improved versions. To evaluate the filter performance for the friction signal, ensemble EMD (EEMD), complementary ensemble EMD (CEEMD), and complete ensemble EMD with adaptive noise (CEEMDAN) are employed in combination with the proposed filtering method. The combination is used to filter the synthesizing signals at first. For the filtering of the simulation signal, the filtering effect is compared under conditions of different ensemble number, sampling frequency, and the input signal-noise ratio, respectively. Results show that CEEMDAN outperforms other signal filtering methods. In particular, this method is successful in filtering the friction signal as evaluated by the de-trended fluctuation analysis (DFA) algorithm.

Description: The time evolution of macroscopic systems can be experimentally observed and mathematically described on many different levels of description. It has been conjectured that the governing equations on all levels are particular realizations of a single abstract equation. We support this conjecture by interpreting the abstract equation as a geometrical formulation of general nonequilibrium thermodynamics.

Description: In this paper, exact solutions of the new Hamiltonian amplitude equation and Fokas-Lenells equation are successfully obtained. The extended trial equation method (ETEM) and generalized Kudryashov method (GKM) are applied to find several exact solutions of the new Hamiltonian amplitude equation and Fokas-Lenells equation. Primarily, we seek some exact solutions of the new Hamiltonian amplitude equation and Fokas-Lenells equation by using ETEM. Then, we research dark soliton solutions of the new Hamiltonian amplitude equation and Fokas-Lenells equation by using GKM. Lastly, according to the values of some parameters, we draw two and three dimensional graphics of imaginary and real values of certain solutions found by utilizing both methods.

Description: We analyze the mesoscopic dynamics of small-scale systems from the perspective of mesoscopic non-equilibrium thermodynamics. The theory obtains the Fokker–Planck equation as a diffusion equation for the probability density of the mesoscopic variables and the nonlinear relationships between activation rates and affinities proper of activated processes. The situations that can be studied with this formalism include, among others, barrier crossing dynamics and non-linear transport in a great variety of systems. We, in particular, consider the cases of single-molecule stretching and activated processes in small systems.

Description: Quantifying behaviors of robots which were generated autonomously from task-independent objective functions is an important prerequisite for objective comparisons of algorithms and movements of animals. The temporal sequence of such a behavior can be considered as a time series and hence complexity measures developed for time series are natural candidates for its quantification. The predictive information and the excess entropy are such complexity measures. They measure the amount of information the past contains about the future and thus quantify the nonrandom structure in the temporal sequence. However, when using these measures for systems with continuous states one has to deal with the fact that their values will depend on the resolution with which the systems states are observed. For deterministic systems both measures will diverge with increasing resolution. We therefore propose a new decomposition of the excess entropy in resolution dependent and resolution independent parts and discuss how they depend on the dimensionality of the dynamics, correlations and the noise level. For the practical estimation we propose to use estimates based on the correlation integral instead of the direct estimation of the mutual information based on next neighbor statistics because the latter allows less control of the scale dependencies. Using our algorithm we are able to show how autonomous learning generates behavior of increasing complexity with increasing learning duration.

Description: For the modeling of complex and nonlinear crude oil price dynamics and movement, wavelet analysis can decompose the time series and produce multiple economically meaningful decomposition structures based on different assumptions of wavelet families and decomposition scale. However, the determination of the optimal model specification will critically affect the forecasting accuracy. In this paper, we propose a new wavelet entropy based approach to identify the optimal model specification and construct the effective wavelet entropy based forecasting models. The wavelet entropy algorithm is introduced to determine the optimal wavelet families and decomposition scale, that will produce the improved forecasting performance. Empirical studies conducted in the crude oil markets show that the proposed algorithm outperforms the benchmark model, in terms of conventional performance evaluation criteria for the model forecasting accuracy.

Description: In this paper, synchronization for a class of uncertain fractional-order neural networks subject to external disturbances and disturbed system parameters is studied. Based on the fractional-order extension of the Lyapunov stability criterion, an adaptive synchronization controller is designed, and fractional-order adaptation law is proposed to update the controller parameter online. The proposed controller can guarantee that the synchronization errors between two uncertain fractional-order neural networks converge to zero asymptotically. By using some proposed lemmas, the quadratic Lyapunov functions are employed in the stability analysis. Finally, numerical simulations are presented to confirm the effectiveness of the proposed method.

Description: The maximum correntropy criterion (MCC) has recently been successfully applied to adaptive filtering. Adaptive algorithms under MCC show strong robustness against large outliers. In this work, we apply the MCC criterion to develop a robust Hammerstein adaptive filter. Compared with the traditional Hammerstein adaptive filters, which are usually derived based on the well-known mean square error (MSE) criterion, the proposed algorithm can achieve better convergence performance especially in the presence of impulsive non-Gaussian (e.g., α-stable) noises. Additionally, some theoretical results concerning the convergence behavior are also obtained. Simulation examples are presented to confirm the superior performance of the new algorithm.

Description: One of the major requirements of content based image retrieval (CBIR) systems is to ensure meaningful image retrieval against query images. The performance of these systems is severely degraded by the inclusion of image content which does not contain the objects of interest in an image during the image representation phase. Segmentation of the images is considered as a solution but there is no technique that can guarantee the object extraction in a robust way. Another limitation of the segmentation is that most of the image segmentation techniques are slow and their results are not reliable. To overcome these problems, a bandelet transform based image representation technique is presented in this paper, which reliably returns the information about the major objects found in an image. For image retrieval purposes, artificial neural networks (ANN) are applied and the performance of the system and achievement is evaluated on three standard data sets used in the domain of CBIR.

Description: Although risk management tools are put to good use in many industrial sectors, some large projects have been met with numerous problems due to failure to take occupational health and safety (OHS) into consideration. In spite of the high level of risk and uncertainty associated with many industrial projects, the number of studies of methods for managing all known risks systematically remains small. Under effervescent economic conditions, industries must meet several challenges associated with frequent project start-ups. In highly complex and uncertain environments, rigorous management of risk remains indispensable for avoiding threats to the success of projects. Many businesses seek continually to create and improve integrated approaches to risk management. This article puts into perspective the complexity of the challenge of integrating OHS into industrial project risk management. A conceptual and methodological approach is proposed to guide future research focused on meeting this challenge. The approach is based on applying multi-disciplinary research modes to a complex industrial context in order to identify all scenarios likely to contain threats to humans or the environment. A case study is used to illustrate the potential of the proposed approach for application and its contribution to meeting the challenge of taking OHS into consideration. On-site researchers were able to develop a new approach that helped two mining companies in Quebec (Canada) to achieve successful integration of OHS into expansion projects.

Description: We construct a model of Brownian motion in Minkowski space. There are two aspects of the problem. The first is to define a sequence of stopping times associated with the Brownian “kicks” or impulses. The second is to define the dynamics of the particle along geodesics in between the Brownian kicks. When these two aspects are taken together, the Central Limit Theorem (CLT) leads to temperature dependent four dimensional distributions defined on Minkowski space, for distances and 4-velocities. In particular, our processes are characterized by two independent time variables defined with respect to the laboratory frame: a discrete one corresponding to the stopping times when the impulses take place and a continuous one corresponding to the geodesic motion in-between impulses. The subsequent distributions are solutions of a (covariant) pseudo-diffusion equation which involves derivatives with respect to both time variables, rather than solutions of the telegraph equation which has a single time variable. This approach simplifies some of the known problems in this context.

Description: This editorial explains the scope of the special issue and provides a thematic introduction to the contributed papers.

Description: Virtually all modern imaging devices collect electromagnetic or acoustic waves and use the energy carried by these waves to determine pixel values to create what is basically an “energy” picture. However, waves also carry “information”, as quantified by some form of entropy, and this may also be used to produce an “information” image. Numerous published studies have demonstrated the advantages of entropy, or “information imaging”, over conventional methods. The most sensitive information measure appears to be the joint entropy of the collected wave and a reference signal. The sensitivity of repeated experimental observations of a slowly-changing quantity may be defined as the mean variation (i.e., observed change) divided by mean variance (i.e., noise). Wiener integration permits computation of the required mean values and variances as solutions to the heat equation, permitting estimation of their relative magnitudes. There always exists a reference, such that joint entropy has larger variation and smaller variance than the corresponding quantities for signal energy, matching observations of several studies. Moreover, a general prescription for finding an “optimal” reference for the joint entropy emerges, which also has been validated in several studies.

Description: Signal state preparation in quantum key distribution schemes can be realized using either an active or a passive source. Passive sources might be valuable in some scenarios; for instance, in those experimental setups operating at high transmission rates, since no externally driven element is required. Typical passive transmitters involve parametric down-conversion. More recently, it has been shown that phase-randomized coherent pulses also allow passive generation of decoy states and Bennett–Brassard 1984 (BB84) polarization signals, though the combination of both setups in a single passive source is cumbersome. In this paper, we present a complete passive transmitter that prepares decoy-state BB84 signals using coherent light. Our method employs sum-frequency generation together with linear optical components and classical photodetectors. In the asymptotic limit of an infinite long experiment, the resulting secret key rate (per pulse) is comparable to the one delivered by an active decoy-state BB84 setup with an infinite number of decoy settings.

Description: The different kinds of boundary conditions for standard and fractional diffusion and advection diffusion equations are analyzed. Near the interface between two phases there arises a transition region which state differs from the state of contacting media owing to the different material particle interaction conditions. Particular emphasis has been placed on the conditions of nonperfect diffusive contact for the time-fractional advection diffusion equation. When the reduced characteristics of the interfacial region are equal to zero, the conditions of perfect contact are obtained as a particular case.

Description: Bioleaching is the mobilization of metal cations from insoluble ores by microorganisms. Biofilms can enhance this process. Since Sulfobacillus often appears in leaching heaps or reactors, this genus has aroused attention. In this study, biofilm formation and subsequent pyrite dissolution by the Gram-positive, moderately thermophilic acidophile Sulfobacillus thermosulfidooxidans were investigated. Five strategies, including adjusting initial pH, supplementing an extra energy source or ferric ions, as well as exchanging exhausted medium with fresh medium, were tested for enhancement of its biofilm formation. The results show that regularly exchanging exhausted medium leads to a continuous biofilm development on pyrite. By this way, multiply layered biofilms were observed on pyrite slices, while only monolayer biofilms were visible on pyrite grains. In addition, biofilms were proven to be responsible for pyrite leaching in the early stages.

Description: High-entropy alloys (HEAs) have recently become a vibrant field of study in the metallic materials area. In the early years, the design of HEAs was more of an exploratory nature. The selection of compositions was somewhat arbitrary, and there was typically no specific goal to be achieved in the design. Very recently, however, the development of HEAs has gradually entered a different stage. Unlike the early alloys, HEAs developed nowadays are usually designed to meet clear goals, and have carefully chosen components, deliberately introduced multiple phases, and tailored microstructures. These alloys are referred to as advanced HEAs. In this paper, the progress in advanced HEAs is briefly reviewed. The design strategies for these materials are examined and are classified into three categories. Representative works in each category are presented. Finally, important issues and future directions in the development of advanced HEAs are pointed out and discussed.

Description: A maximum entropy copula is the copula associated with the joint distribution, with prescribed marginal distributions on [ 0 , 1 ] , which maximizes the Tsallis–Havrda–Chavát entropy with q = 2 . We find necessary and sufficient conditions for each maximum entropy copula to be a copula in the class introduced in Rodríguez-Lallena and Úbeda-Flores (2004), and we also show that each copula in that class is a maximum entropy copula.

Description: Volcanic layers in coal seams in southwestern China coalfields have received much attention given their significance in coal geology studies and their potential economic value. In this study, the mineralogical and geochemical compositions of C19 and C25 coal seams were examined, and the following findings were obtained. (1) Clay minerals in sample C19-r are argillized, and sedimentary layering is not observed. The acicular idiomorphic crystals of apatite and the phenocrysts of Ti-augite coexisting with magnetite in roof sample C19-r are common minerals in basaltic rock. The rare earth elements (REE) distribution pattern of C19-r, which is characterized by positive Eu anomalies and M-REE enrichment, is the same as that of high-Ti basalt. The concentrations of Ti, V, Co, Cr, Ni, Cu, Zn, Nb, Ta, Zr, and Hf in C19-r are closer to those of high-Ti basalt. In conclusion, roof sample C19-r consists of tuffaceous clay, probably with a high-Ti mafic magma source. (2) The geochemical characteristics of the C25 coals are same as those reported for coal affected by alkali volcanic ash, enrichment in Nb, Ta, Zr, Hf, and REE, causing the C25 minable coal seams to have higher potential value. Such a vertical study of coals and host rocks could provide more information for coal-forming depositional environment analysis, for identification of volcanic eruption time and magma intrusion, and for facilitating stratigraphic subdivision and correlation.

Description: This paper studies a continuous Bertrand duopoly game model with two-stage delay. Our aim is to investigate the influence of delay and weight on the complex dynamic characteristics of the system. We obtain the bifurcation point of the system respect to delay parameter by calculating. In addition, the dynamic properties of the system are simulated by power spectrum, attractor, bifurcation diagram, the largest Lyapunov exponent, 3D surface chart, 4D Cubic Chart, 2D parameter bifurcation diagram, and 3D parameter bifurcation diagram. The results show that the stability of the system depends on the delay and weight, in order to maintain stability of price and ensure the firm profit, the firms must control the parameters in the reasonable region. Otherwise, the system will lose stability, and even into chaos, which will cause fluctuations in prices, the firms cannot be profitable. Finally, the chaos control of the system is carried out by a control strategy of the state variables’ feedback and parameter variation, which effectively avoid the damage of chaos to the economic system. Therefore, the results of this study have an important practical significance to make decisions with multi-stage delay for oligopoly firms.

Description: At the industrial scale, bioleaching of metal sulfides includes two main technologies, tank leaching and heap leaching. Fluctuations in temperature caused by the exothermic reactions in a heap have a pronounced effect on the growth of microbes and composition of mixed microbial populations. Currently, little is known on the influence of pre-colonized mesophiles or moderate thermophiles on the attachment and bioleaching efficiency by thermophiles. The objective of this study was to investigate the interspecies interactions of the moderate thermophile Sulfobacillus thermosulfidooxidans DSM 9293T and the thermophile Acidianus sp. DSM 29099 during initial attachment to and dissolution of pyrite. Our results showed that: (1) Acidianus sp. DSM 29099 interacted with S. thermosulfidooxidansT during initial attachment in mixed cultures. In particular, cell attachment was improved in mixed cultures compared to pure cultures alone; however, no improvement of pyrite leaching in mixed cultures compared with pure cultures was observed; (2) active or inactivated cells of S. thermosulfidooxidansT on pyrite inhibited or showed no influence on the initial attachment of Acidianus sp. DSM 29099, respectively, but both promoted its leaching efficiency; (3) S. thermosulfidooxidansT exudates did not enhance the initial attachment of Acidianus sp. DSM 29099 to pyrite, but greatly facilitated its pyrite dissolution efficiency. Our study provides insights into cell-cell interactions between moderate thermophiles and thermophiles and is helpful for understanding of the microbial interactions in a heap leaching environment.

Description: Estimators derived from a divergence criterion such as φ - divergences are generally more robust than the maximum likelihood ones. We are interested in particular in the so-called minimum dual φ–divergence estimator (MDφDE), an estimator built using a dual representation of φ–divergences. We present in this paper an iterative proximal point algorithm that permits the calculation of such an estimator. The algorithm contains by construction the well-known Expectation Maximization (EM) algorithm. Our work is based on the paper of Tseng on the likelihood function. We provide some convergence properties by adapting the ideas of Tseng. We improve Tseng’s results by relaxing the identifiability condition on the proximal term, a condition which is not verified for most mixture models and is hard to be verified for “non mixture” ones. Convergence of the EM algorithm in a two-component Gaussian mixture is discussed in the spirit of our approach. Several experimental results on mixture models are provided to confirm the validity of the approach.

Description: More than 370,000 Americans die every year from coronary artery disease (CAD). Early detection and treatment are crucial to reducing this number. Current diagnostic and disease-monitoring methods are invasive, costly, and time-consuming. Using an electronic stethoscope and spectral and nonlinear dynamics analysis of the recorded heart sound, we investigated the acoustic signature of CAD in subjects with only a single coronary occlusion before and after stent placement, as well as subjects with clinically normal coronary arteries. The CAD signature was evaluated by estimating power ratios of the total power above 150 Hz over the total power below 150 Hz of the FFT of the acoustic signal. Additionally, approximate entropy values were estimated to assess the differences induced by the stent placement procedure to the acoustic signature of the signals in the time domain. The groups were identified with this method with 82% sensitivity and 64% specificity (using the power ratio method) and 82% sensitivity and 55% specificity (using the approximate entropy). Power ratios and approximate entropy values after stent placement are not statistically different from those estimated from subjects with no coronary occlusions. Our approach demonstrates that the effect of stent placement on coronary occlusions can be monitored using an electronic stethoscope.

Description: We propose using five data-driven community detection approaches from social networks to partition the label space in the task of multi-label classification as an alternative to random partitioning into equal subsets as performed by RAkELd. We evaluate modularity-maximizing using fast greedy and leading eigenvector approximations, infomap, walktrap and label propagation algorithms. For this purpose, we propose to construct a label co-occurrence graph (both weighted and unweighted versions) based on training data and perform community detection to partition the label set. Then, each partition constitutes a label space for separate multi-label classification sub-problems. As a result, we obtain an ensemble of multi-label classifiers that jointly covers the whole label space. Based on the binary relevance and label powerset classification methods, we compare community detection methods to label space divisions against random baselines on 12 benchmark datasets over five evaluation measures. We discover that data-driven approaches are more efficient and more likely to outperform RAkELd than binary relevance or label powerset is, in every evaluated measure. For all measures, apart from Hamming loss, data-driven approaches are significantly better than RAkELd ( α = 0 . 05 ), and at least one data-driven approach is more likely to outperform RAkELd than a priori methods in the case of RAkELd’s best performance. This is the largest RAkELd evaluation published to date with 250 samplings per value for 10 values of RAkELd parameter k on 12 datasets published to date.

Description: The composite discrete chaotic system (CDCS) is a complex chaotic system that combines two or more discrete chaotic systems. This system holds the chaotic characteristics of different chaotic systems in a random way and has more complex chaotic behaviors. In this paper, we aim to provide a novel image encryption algorithm based on a new two-dimensional (2D) CDCS. The proposed scheme consists of two parts: firstly, we propose a new 2D CDCS and analysis the chaotic behaviors, then, we introduce the bit-level permutation and pixel-level diffusion encryption architecture with the new CDCS to form the full proposed algorithm. Random values and the total information of the plain image are added into the diffusion procedure to enhance the security of the proposed algorithm. Both the theoretical analysis and simulations confirm the security of the proposed algorithm.

Description: Representative perlite bulk rock samples from two areas of Milos Island, Greece were collected and the expansion properties of their industrial product were investigated. Coarse crude perlite from Tsigrado exhibits better expansibility, which is assigned to the presence of coarser crystallites in its bulk parent rock. During thermal treatment, the finer crystallites of the coarse crude perlite from Trachilas are entrapped in the groundmass and lead to overheating, which inhibits expansion and eventually results in shrinkage. Geochemical modification of the expanded perlites relative to their crude precursors were investigated, using the isocon method. Volatilisation of crystalline water is the main factor controlling mass reduction of the expanded perlites. Other elements, during the adequate expansion of the Tsigrado perlite, can be classified into three categories. The elements that participate preferentially in crystals decrease in the expanded material at amounts higher than the total mass loss of the rock, due to their escape controlled mainly by the removal of the crystalline phases. The elements equally participating in crystals and the groundmass show losses equivalent to the total mass loss of the rocks, as they escaped in the crystalline phases and airborne particles from the groundmass during thermal treatment. Decrease of highly incompatible elements, which mostly participate in the groundmass, in the expanded products is less than the total mass loss, as they escaped mainly in the airborne particles. The inadequate expansion and burst of the Trachilas perlite did not allow for a similar categorisation, due to random and unpredictable escape of the elements. We propose the application of this method to an artificial system to predict unexpandable mineral phases in bulk perlite, as well as elements that are most likely to participate in the amorphous perlite phase, which cannot be determined from a regular industrial production line. This graphical method may also predict environmental pollution of the atmosphere from the release of volatile compounds and airborne particles during thermal treatment of perlite or other processes of mineral treatment.

Description: In a Software Product Line (SPL), the central notion of implementability provides the requisite connection between specifications and their implementations, leading to the definition of products. While it appears to be a simple extension of the traceability relation between components and features, it involves several subtle issues that were overlooked in the existing literature. In this paper, we have introduced a precise and formal definition of implementability over a fairly expressive traceability relation. The consequent definition of products in the given SPL naturally entails a set of useful analysis problems that are either refinements of known problems or are completely novel. We also propose a new approach to solve these analysis problems by encoding them as Quantified Boolean Formulae (QBF) and solving them through Quantified Satisfiability (QSAT) solvers. QBF can represent more complex analysis operations, which cannot be represented by using propositional formulae. The methodology scales much better than the SAT-based solutions hinted in the literature and were demonstrated through a tool called SPLAnE (SPL Analysis Engine) on a large set of SPL models.

Description: The electrocardiogram (ECG) is one of the most important techniques for heart disease diagnosis. Many traditional methodologies of feature extraction and classification have been widely applied to ECG analysis. However, the effectiveness and efficiency of such methodologies remain to be improved, and much existing research did not consider the separation of training and testing samples from the same set of patients (so called inter-patient scheme). To cope with these issues, in this paper, we propose a method to classify ECG signals using wavelet packet entropy (WPE) and random forests (RF) following the Association for the Advancement of Medical Instrumentation (AAMI) recommendations and the inter-patient scheme. Specifically, we firstly decompose the ECG signals by wavelet packet decomposition (WPD), and then calculate entropy from the decomposed coefficients as representative features, and finally use RF to build an ECG classification model. To the best of our knowledge, it is the first time that WPE and RF are used to classify ECG following the AAMI recommendations and the inter-patient scheme. Extensive experiments are conducted on the publicly available MIT–BIH Arrhythmia database and influence of mother wavelets and level of decomposition for WPD, type of entropy and the number of base learners in RF on the performance are also discussed. The experimental results are superior to those by several state-of-the-art competing methods, showing that WPE and RF is promising for ECG classification.

Description: The Hess–Murray law is a correlation between the radii of successive branchings in bi/trifurcated vessels in biological tissues. First proposed by the Swiss physiologist and Nobel laureate Walter Rudolf Hess in his 1914 doctoral thesis and published in 1917, the law was “rediscovered” by the American physiologist Cecil Dunmore Murray in 1926. The law is based on the assumption that blood or lymph circulation in living organisms is governed by a “work minimization” principle that—under a certain set of specified conditions—leads to an “optimal branching ratio” of r i + 1 r i = 1 2 3 = 0.7937 . This “cubic root of 2” correlation underwent extensive theoretical and experimental reassessment in the second half of the 20th century, and the results indicate that—under a well-defined series of conditions—the law is sufficiently accurate for the smallest vessels (r of the order of fractions of millimeter) but fails for the larger ones; moreover, it cannot be successfully extended to turbulent flows. Recent comparisons with numerical investigations of branched flows led to similar conclusions. More recently, the Hess–Murray law came back into the limelight when it was taken as a founding paradigm of the Constructal Law, a theory that employs physical intuition and mathematical reasoning to derive “optimal paths” for the transport of matter and energy between a source and a sink, regardless of the mode of transportation (continuous, like in convection and conduction, or discrete, like in the transportation of goods and people). This paper examines the foundation of the law and argues that both for natural flows and for engineering designs, a minimization of the irreversibility under physically sound boundary conditions leads to somewhat different results. It is also shown that, in the light of an exergy-based resource analysis, an amended version of the Hess–Murray law may still hold an important position in engineering and biological sciences.

Description: Percutaneous coronary intervention (PCI) is a common treatment method for patients with coronary artery disease (CAD), but its effect on synchronously measured heart rate variability (HRV) and pulse transit time variability (PTTV) have not been well established. This study aimed to verify whether PCI for CAD patients affects both HRV and PTTV parameters. Sixteen CAD patients were enrolled. Two five-minute ECG and finger photoplethysmography (PPG) signals were recorded, one within 24 h before PCI and another within 24 h after PCI. The changes of RR and pulse transit time (PTT) intervals due to the PCI procedure were first compared. Then, HRV and PTTV were evaluated by a standard short-term time-domain variability index of standard deviation of time series (SDTS) and our previously developed entropy-based index of fuzzy measure entropy (FuzzyMEn). To test the effect of different time series length on HRV and PTTV results, we segmented the RR and PTT time series using four time windows of 200, 100, 50 and 25 beats respectively. The PCI-induced changes in HRV and PTTV, as well as in RR and PTT intervals, are different. PCI procedure significantly decreased RR intervals (before PCI 973 ± 85 vs. after PCI 907 ± 100 ms, p 〈 0.05) while significantly increasing PTT intervals (207 ± 18 vs. 214 ± 19 ms, p 〈 0.01). For HRV, SDTS-only output significant lower values after PCI when time windows are 100 and 25 beats while presenting no significant decreases for other two time windows. By contrast, FuzzyMEn gave significant lower values after PCI for all four time windows (all p 〈 0.05). For PTTV, SDTS hardly changed after PCI at any time window (all p > 0.90) whereas FuzzyMEn still reported significant lower values (p 〈 0.05 for 25 beats time window and p 〈 0.01 for other three time windows). For both HRV and PTTV, with the increase of time window values, SDTS decreased while FuzzyMEn increased. This pilot study demonstrated that the RR interval decreased whereas the PTT interval increased after the PCI procedure and that there were significant reductions in both HRV and PTTV immediately after PCI using the FuzzyMEn method, indicating the changes in underlying mechanisms in cardiovascular system.

Description: The paper presents a method for processing acoustic signals which allows the extraction, from a very noisy signal, of components which contain diagnostically useful information on the increased valve clearance of a combustion engine. This method used two-stage denoising of the acoustic signal performed by means of a discrete wavelet transform. Afterwards, based on the signal cleaned-up in this manner, its entropy was calculated as a quantitative measure of qualitative changes caused by the excessive clearance. The testing and processing of the actual acoustic signal of a combustion engine enabled clear extraction of components which contain information on the valve clearance being diagnosed.

Description: In this work, we consider the value of the momentum map of the symplectic mechanics as an affine tensor called momentum tensor. From this point of view, we analyze the underlying geometric structure of the theories of Lie group statistical mechanics and relativistic thermodynamics of continua, formulated by Souriau independently of each other. We bridge the gap between them in the classical Galilean context. These geometric structures of the thermodynamics are rich and we think they might be a source of inspiration for the geometric theory of information based on the concept of entropy.

Description: Statistics of distinguishable particles has become relevant in systems of colloidal particles and in the context of applications of statistical mechanics to complex networks. In this paper, we present evidence that a commonly used expression for the partition function of a system of distinguishable particles leads to huge fluctuations of the number of particles in the grand canonical ensemble and, consequently, to nonequivalence of statistical ensembles. We will show that the alternative definition of the partition function including, naturally, Boltzmann’s correct counting factor for distinguishable particles solves the problem and restores ensemble equivalence. Finally, we also show that this choice for the partition function does not produce any inconsistency for a system of distinguishable localized particles, where the monoparticular partition function is not extensive.

Description: In this paper, we address theoretically and experimentally the optimization problem of the heat transfer occurring in two coupled thermoelectric devices. A simple experimental set up is used. The optimization parameters are the applied electric currents. When one thermoelectric is analysed, the temperature difference Δ T between the thermoelectric boundaries shows a parabolic profile with respect to the applied electric current. This behaviour agrees qualitatively with the corresponding experimental measurement. The global entropy generation shows a monotonous increase with the electric current. In the case of two coupled thermoelectric devices, elliptic isocontours for Δ T are obtained in applying an electric current through each of the thermoelectrics. The isocontours also fit well with measurements. Optimal figure of merit is found for a specific set of values of the applied electric currents. The entropy generation-thermal figure of merit relationship is studied. It is shown that, given a value of the thermal figure of merit, the device can be operated in a state of minimum entropy production.

Description: Charge transport in nanosized electronic systems is described by semiclassical or quantum kinetic equations that are often costly to solve numerically and difficult to reduce systematically to macroscopic balance equations for densities, currents, temperatures and other moments of macroscopic variables. The maximum entropy principle can be used to close the system of equations for the moments but its accuracy or range of validity are not always clear. In this paper, we compare numerical solutions of balance equations for nonlinear electron transport in semiconductor superlattices. The equations have been obtained from Boltzmann–Poisson kinetic equations very far from equilibrium for strong fields, either by the maximum entropy principle or by a systematic Chapman–Enskog perturbation procedure. Both approaches produce the same current-voltage characteristic curve for uniform fields. When the superlattices are DC voltage biased in a region where there are stable time periodic solutions corresponding to recycling and motion of electric field pulses, the differences between the numerical solutions produced by numerically solving both types of balance equations are smaller than the expansion parameter used in the perturbation procedure. These results and possible new research venues are discussed.

Description: Carbon dioxide (CO2) is considered one of the most important greenhouse gases in the study of climate change. CO2 adsorption was studied using the gas chromatography technique, while the Freundlich and Langmuir adsorption models were employed for processing isotherm data in the temperature range of 473–573 K. The isosteric heat of adsorption was calculated from the Clausius–Clapeyron equation. Moreover, the thermodynamic properties ΔG, ΔU, and ΔS were evaluated from the adsorption isotherms of Langmuir using the Van’t Hoff Equation. The four soil samples were recollected from San Juan Amecac, Puebla, Mexico, and their morphologies were investigated through X-ray diffraction (XRD) and N2 adsorption at 77 K. The SJA4 soil has a crystalline Kaolinite phase, which is one of its non-metallic raw materials, and N2 isotherms allowed for the determination of pore size distributions and specific surface areas of soil samples. The Barrett–Joyner–Halenda (BJH) distribution of pore diameters was bimodal with peaks at 1.04 and 3.7 nm, respectively. CO2 adsorption showed that the SJA1 soil afforded a higher amount of adsorbed CO2 in the temperature range from 453 to 573 K followed by SJA4 and finally SJA2, classifying this process as exothermic physisorption.

Description: We prove that, for a measure preserving action of a sofic group with positive sofic entropy, the stabilizer is finite on a set of positive measures. This extends the results of Weiss and Seward for amenable groups and free groups, respectively. It follows that the action of a sofic group on its subgroups by inner automorphisms has zero topological sofic entropy, and that a faithful action that has completely positive sofic entropy must be free.

Description: A millimeter wave (MMW) radar sensor is employed in our laboratory to detect human speech because it provides a new non-contact speech acquisition method that is suitable for various applications. However, the speech detected by the radar sensor is often degraded by combined noise. This paper proposes a new perceptual wavelet packet method that is able to enhance the speech acquired using a 94 GHz MMW radar system by suppressing the noise. The process is as follows. First, the radar speech signal is decomposed using a perceptual wavelet packet. Then, an adaptive wavelet threshold and new modified thresholding function are employed to remove the noise from the detected speech. The results obtained from the speech spectrograms, listening tests and objective evaluation show that the new method significantly improves the performance of the detected speech.

Description: Mechanics from its side and thermodynamics from its side consider evolution of complex systems, including the Universe. Created classical thermodynamic theory of evolution has one important drawback since it predicts an inevitable heat death of the Universe which is unlikely to take place according to the modern perceptions. The attempts to create a generalized theory of evolution in mechanics were unsuccessful since mechanical equations do not discriminate between future and past. It is natural that the union of mechanics and thermodynamics was difficult to realize since they are based on different methodology. We make an attempt to propose a generalized theory of evolution which is based on the concept of tribo-fatigue entropy. Essence of the proposed approach is that tribo-fatigue entropy is determined by the processes of damageability conditioned by thermodynamic and mechanical effects causing to the change of states of any systems. Law of entropy increase is formulated analytically in the general form. Mechanothermodynamical function is constructed for specific case of fatigue damage of materials due to variation of temperature from 3 K to 0.8 of melting temperature basing on the analysis of 136 experimental results.

Description: In this paper, our concern is to design some criteria for deterministic remote state preparation for preparing an arbitrary three-particle state via a genuinely entangled six-qubit state. First, we put forward two schemes in both the real and complex Hilbert space, respectively. Using an appropriate set of eight-qubit measurement basis, the remote three-qubit preparation is completed with unit success probability. Departing from previous research, our protocol has a salient feature in that the serviceable measurement basis only contains the initial coefficients and their conjugate values. By utilizing the permutation group, it is convenient to provide the permutation relationship between coefficients. Second, our ideas and methods can also be generalized to the situation of preparing an arbitrary N-particle state in complex case by taking advantage of Bell states as quantum resources. More importantly, criteria satisfied conditions for preparation with 100% success probability in complex Hilbert space is summarized. Third, the classical communication costs of our scheme are calculated to determine the classical recourses required. It is also worth mentioning that our protocol has higher efficiency and lower resource costs compared with the other papers.

Description: The discovery of the entropy production paradox (Hoffmann et al., 1998) raised basic questions about the nature of irreversibility in the regime between diffusion and waves. First studied in the form of spatial movements of moments of H functions, pseudo propagation is the pre-limit propagation-like movements of skewed probability density function (PDFs) in the domain between the wave and diffusion equations that goes over to classical partial differential equation propagation of characteristics in the wave limit. Many of the strange properties that occur in this extraordinary regime were thought to be connected in some manner to this form of proto-movement. This paper eliminates pseudo propagation by employing a similar evolution equation that imposes spatial unimodal symmetry on evolving PDFs. Contrary to initial expectations, familiar peculiarities emerge despite the imposed symmetry, but they have a distinct character.

Description: Many statistical models over a discrete sample space often face the computational difficulty of the normalization constant. Because of that, the maximum likelihood estimator does not work. In order to circumvent the computation difficulty, alternative estimators such as pseudo-likelihood and composite likelihood that require only a local computation over the sample space have been proposed. In this paper, we present a theoretical analysis of such localized estimators. The asymptotic variance of localized estimators depends on the neighborhood system on the sample space. We investigate the relation between the neighborhood system and estimation accuracy of localized estimators. Moreover, we derive the efficiency bound. The theoretical results are applied to investigate the statistical properties of existing estimators and some extended ones.

Description: Agate nodules from Kerrouchen (Khénifra Province, Meknés-Tafilalet Region) in Morocco occur in Triassic basalts and reach up to 30 cm in diameter. Monocentric, banded agates—mainly in pastel pink, grey, white and yellow—with infiltration canals (osculum) are observed. Raman microspectroscopy revealed that the agates mainly consist of low quartz and subordinately moganite with distinctive 460 and 501 cm−1 marker bands, respectively. Linear mapping indicated that moganite mainly concentrates in grey zones of the monocentric agate nodules. The other types, polycentric and pseudostalactitic agates, are usually brown and red and contain minerals such as hematite and goethite. They form both regular and irregular mosaics rich in ornamentation. Occasionally, aggregates of copper sulphides or titanium oxides (rutile) can also be observed. These minerals are sometimes accompanied by carbonaceous material marked by 1320 and 1585 cm−1 Raman bands. It seems that formation of agates from Kerrouchen was induced by Si-rich and Fe-moderate fluids. Copper sulphides, rutile, and carbonates (possibly calcite) were most likely incorporated during post-magmatic processes. The origin of solid bitumen can be the result of hydrothermal or hypergenic processes.

Description: A relevant research effort is devoted to the synthesis and characterization of phases belonging to the ternary system Cu–Sn–S, mainly for their possible applications in semiconductor technology. Among all ternary phases, kuramite, Cu3SnS4, mohite, Cu2SnS3, and Cu4Sn7S16 have attracted the highest interest. Numerous studies were carried out claiming for the description of new phases in the ternary compositional field. In this study, we revise the existing literature on this ternary system, with a special focus on the phases stable in a temperature range at 25 °C. The only two ternary phases observed in nature are mohite and kuramite. Their occurrence is described as very rare. A numerical modelling of the stable solid phases in contact with a water solution was underwent to define stability relationships of the relevant phases of the system. The numerical modelling of the Eh-pH diagrams was carried out through the phreeqc software with the lnll.dat thermodynamic database. Owing to the complexity of this task, the subsystems Cu–O–H, Sn–O–H, Cu–S–O–H and Sn–S–O–H were firstly considered. The first Pourbaix diagram for the two naturally relevant ternary phases is then proposed.

Description: The impact of methane explosions on mining operations can never be over-emphasized. The safety of miners could be threatened and local ventilation facilities are likely to be damaged by the flame and overpressure induced by a methane explosion event, making it essential to understand the destructiveness and influence range of a specific explosion. In this paper, the attenuation effect of geometric changes, most commonly bends, obstacles, and branches, present in the way of blast-wave propagation and the capability of the selected numerical model were studied. Although some relevant experimental research has been provided, quantitative analysis is insufficient. This paper investigates the attenuation factors of seven bends, three obstacles, and two T-branch scenarios to ascertain a better insight of this potentially devastating event quantitatively. The results suggest that (1) the numerical model used is capable of predicting four of the seven validated scenarios with a relative error less than 12%; (2) the maximum peak overpressure is obtained when the angle equals 50° for bend cases; and (3) the selected numerical scheme would overestimate the obstacle cases by around 15%.

Description: Due to the low grade of V2O5 in stone coal, the existing vanadium extraction technologies face challenges in terms of large handling capacity, high acid consumption and production cost. The pre-concentration of vanadium from stone coal before the extraction process is an effective method to reduce cost. In this study, detailed mineral characterization of stone coal was investigated. It has been confirmed that the vanadium mainly occurs in muscovite and illite. A significant demand for an effective pre-concentration process with simple manipulation for discarding quartz and other gangue minerals is expected. Based on the mineralogical study, a new vanadium pre-concentration process using a fine mineral spiral was investigated. The experimental results showed that the separation process, which was comprised of a rougher and scavenger, could efficiently discard quartz, pyrite and apatite. A final concentrate with V2O5 grade of 1.02% and recovery of 89.6% could be obtained, with 26.9% of the raw ore being discarded as final tailings.

Description: We present a new conceptual approach for modeling of fluid flows in random porous media based on explicit exploration of the treelike geometry of complex capillary networks. Such patterns can be represented mathematically as ultrametric spaces and the dynamics of fluids by ultrametric diffusion. The images of p-adic fields, extracted from the real multiscale rock samples and from some reference images, are depicted. In this model the porous background is treated as the environment contributing to the coefficients of evolutionary equations. For the simplest trees, these equations are essentially less complicated than those with fractional differential operators which are commonly applied in geological studies looking for some fractional analogs to conventional Euclidean space but with anomalous scaling and diffusion properties. It is possible to solve the former equation analytically and, in particular, to find stationary solutions. The main aim of this paper is to attract the attention of researchers working on modeling of geological processes to the novel utrametric approach and to show some examples from the petroleum reservoir static and dynamic characterization, able to integrate the p-adic approach with multifractals, thermodynamics and scaling. We also present a non-mathematician friendly review of trees and ultrametric spaces and pseudo-differential operators on such spaces.

Description: The recovery of gold by ore leaching is influenced by the size of the particles and the chemical environment. The effect of particle size on the dissolution of gold is usually studied using mono-size particles as the gold in solution comes from the ore of a unique leached particle size. This paper proposes a method to estimate the gold dissolution as a function of particle size using a bulk ore sample, i.e., with the dissolved gold coming from the various sizes of particles carried by the ore. The results are consistent with the fact that gold dissolution increases with the decreasing particle size but results also indicate that gold dissolution of the ore within a size interval is not significantly affected by the grinding time used for the ore size reduction. Results also show a good dissolution of the gold contained in the fine-size fractions without oxidation and lead nitrate pre-treatment for an ore that is known to require such pre-treatment.

Description: Aging alters muscular coordination patterns. This study aimed to investigate aging-related changes in the coordination of agonist and antagonist muscles from two aspects, the activities of individual muscles and the inter-muscular coupling. Eighteen young subjects and 10 elderly subjects were recruited to modulate the agonist muscle activity to track a target during voluntary isometric elbow flexion and extension. Normalized muscle activation and fuzzy entropy (FuzzyEn) were applied to depict the activities of biceps and triceps. Mutual information (MI) was utilized to measure the inter-muscular coupling between biceps and triceps. The agonist activation decreased and the antagonist activation increased significantly during elbow flexion and extension with aging. FuzzyEn values of agonist electromyogram (EMG) were similar between the two age groups. FuzzyEn values of antagonist EMG increased significantly with aging during elbow extension. MI decreased significantly with aging during elbow extension. These results indicated increased antagonist co-activation and decreased inter-muscular coupling with aging during elbow extension, which might result from the reduced reciprocal inhibition and the recruitment of additional cortical-spinal pathways connected to biceps. Based on FuzzyEn and MI, this study provided a comprehensive understanding of the mechanisms underlying the aging-related changes in the coordination of agonist and antagonist muscles.

Description: A three dimensional computational solution has been obtained to investigate the natural convection and entropy generation of nanofluid-filled open cavities with an adiabatic diamond shaped obstacle. In the model, the finite volume technique was used to solve the governing equations. Based on the configuration, the cavity is heated from the left vertical wall and the diamond shape was chosen as adiabatic. Effects of nanoparticle volume fraction, Rayleigh number (103 ≤ Ra ≤ 106) and width of diamond shape were studied as governing parameters. It was found that the geometry of the partition is a control parameter for heat and fluid flow inside the open enclosure.

Description: There exist problems of small samples and heteroscedastic noise in design time forecasts. To solve them, a kernel-based regression with Gaussian distribution weights (GDW-KR) is proposed here. GDW-KR maintains a Gaussian distribution over weight vectors for the regression. It is applied to seek the least informative distribution from those that keep the target value within the confidence interval of the forecast value. GDW-KR inherits the benefits of Gaussian margin machines. By assuming a Gaussian distribution over weight vectors, it could simultaneously offer a point forecast and its confidence interval, thus providing more information about product design time. Our experiments with real examples verify the effectiveness and flexibility of GDW-KR.

Description: The study considers advantages of the introduced measure of time based on the entropy change under irreversible processes (entropy production). Using the example of non-equilibrium expansion of an ideal gas in vacuum, such a measure is introduced. It is shown that, in the general case, this measure of time proves to be nonlinearly related to the reference measure assumed uniform by convention. The connection between this result and the results of other authors investigating the measure of time in some biological and cosmological problems is noted.

Description: Automatically extracting quantities and generating final answers for numerical attributes is very useful in many occasions, including question answering, image processing, human-computer interaction, etc. A common approach is to learn linguistics templates or wrappers and employ some algorithm or model to generate a final answer. However, building linguistics templates or wrappers is a tough task for builders. In addition, linguistics templates or wrappers are domain-dependent. To make the builder escape from building linguistics templates or wrappers, we propose a new approach to final answer generation based on Predicates-Units Table (PUT), a mini domain-independent knowledge base. It is deserved to point out that, in the following cases, quantities are not represented well. Quantities are absent of units. Quantities are perhaps wrong for a given question. Even if all of them are represented well, their units are perhaps inconsistent. These cases have a strong impact on final answer solving. One thousand nine hundred twenty-six real queries are employed to test the proposed method, and the experimental results show that the average correctness ratio of our approach is 87.1%.

Description: In analyzing a temporal data set from a continuous variable, diffusion processes can be suitable under certain conditions, depending on the distribution of increments. We are interested in processes where a semi-permeable barrier splits the state space, producing a skewed diffusion that can have different rates on each side. In this work, the asymptotic behavior of some Bayesian inferences for this class of processes is discussed and validated through simulations. As an application, we model the location of South American sea lions (Otaria flavescens) on the coast of Calbuco, southern Chile, which can be used to understand how the foraging behavior of apex predators varies temporally and spatially.

Description: In this paper, we address the question: To what extent is the quantum state preparation of multiatom clusters (before they are injected into the microwave cavity) instrumental for determining not only the kind of machine we may operate, but also the quantitative bounds of its performance? Figuratively speaking, if the multiatom cluster is the “crude oil”, the question is: Which preparation of the cluster is the refining process that can deliver a “gasoline” with a “specific octane”? We classify coherences or quantum correlations among the atoms according to their ability to serve as: (i) fuel for nonthermal machines corresponding to atomic states whose coherences displace or squeeze the cavity field, as well as cause its heating; and (ii) fuel that is purely “combustible”, i.e., corresponds to atomic states that only allow for heat and entropy exchange with the field and can energize a proper heat engine. We identify highly promising multiatom states for each kind of fuel and propose viable experimental schemes for their implementation.

Description: Fisher matrices play an important role in experimental design and in data analysis. Their primary role is to make predictions for the inference of model parameters—both their errors and covariances. In this short review, I outline a number of extensions to the simple Fisher matrix formalism, covering a number of recent developments in the field. These are: (a) situations where the data (in the form of ( x , y ) pairs) have errors in both x and y; (b) modifications to parameter inference in the presence of systematic errors, or through fixing the values of some model parameters; (c) Derivative Approximation for LIkelihoods (DALI) - higher-order expansions of the likelihood surface, going beyond the Gaussian shape approximation; (d) extensions of the Fisher-like formalism, to treat model selection problems with Bayesian evidence.

Description: We study continuous countably-piecewise monotone interval maps and formulate conditions under which these are conjugate to maps of constant slope, particularly when this slope is given by the topological entropy of the map. We confine our investigation to the Markov case and phrase our conditions in the terminology of the Vere-Jones classification of infinite matrices.

Description: In this paper, a surfactant, atlox4862 (formaldehyde condensate of methyl naphthalene sulfonic sodium salt) (MF), was introduced as a depressant for reverse flotation separation of sericite from graphite. Natural flake graphite has a strong hydrophobic property. After interacting with MF, the graphite became moderately hydrophilic. The flotation results showed that MF had a depressing ability for both sericite and graphite and that the flotation separation of sericite from graphite was attributed to the different declining levels of recovery between graphite and sericite with increased MF concentration. For a pulp pH of 8 and a MF concentration of 250 mg/L, the recovery rates of sericite and graphite were 89.7% and 11.3%, respectively. The results of the FTIR spectra and zeta potential measurements demonstrated that the interaction of MF with graphite and sericite is mainly through electrostatic attraction. MF was preferred to adsorb on the surface of graphite, decreasing its zeta potential and improving its hydrophilicity more than that of sericite.

Description: The Upper No. 3 coal of the Early Permian age is a major workable seam in the southwestern Shandong coalfield, which is located in the eastern part of North China. From Early Jurassic to Neogene, the coalfield was subjected to intensive tectonic processes, leading to a significant rearrangement in depth of coal seams. In this paper, three Upper No. 3 coals occurring at −228, −670 and −938 m in the Luxi, Liangbaosi, and Tangkou mines, respectively, were collected to investigate their mineralogical and geochemical characteristics, with emphasis on modes of occurrence and origin of epigenetic minerals. The three coal seams are similar in vitrinite reflectance, volatile matter yield, and maceral components, suggesting insignificant influence from the tectonic activities on coal rank. Terrigenous minerals (e.g., kaolinite and quartz) are comparable in both types and distribution patterns in the three coals. The presence of siderite and pyrite of syngenetic or penecontemporaneous origin indicate they were emplaced during peat accumulation. The distribution of epigenetic minerals (e.g., calcite, ankerite, and dolomite) are associated with the underground water activities, which were Ca (Mg, Fe)-bearing.