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Perspective managerial trends in the use and development of Unconventional Technologies emphasize both the management of processes and the improvement and creation of new technologies, equipment, installations and machinery equipped with a high degree of flexibility and automation of the technological process. Due to the strong growth of competition on the market, the managerial conception of industrial organizations that are also identified by unconventional technologies will have to be directed not only towards increasing quality but also towards the design of specific competitive strategies. [ABSTRACT FROM AUTHOR]

A theoretical model of an n-dimensional toroidal interconnection network with the virtual cut-through routing is developed. The network performance is characterized as a function of the message load for various values of the network and communication parameters. An exact analytical expression for the saturation point has been obtained. The method of statistical physics known as the mean field theory approximation has been used in order to derive analytical expressions of latency as a function of message generation rate for the full range of the network load. The saturation point has been found proportional to the number of the torus dimensions and inversely proportional to the message length and to the length of the path from the source to the destination. It was found that the transition to the saturation state is a second-order (continuous) phase transition with a critical exponent equal to 1. [ABSTRACT FROM AUTHOR]

Associate credit risk is a kind of credit risk among the associated credit enterprises formed by credit-related enterprises. Based on the mean field theory of complex network and the classical model Susceptible–Infected–Recovered (SIR) of risk propagation dynamics, this paper explores the influence mechanism of the influence of corporate senior executives' alertness promoted by risk information on the contagion of associated credit risk. The results show that the corporate senior executives' alertness does not change the contagion threshold of associated credit risk. [ABSTRACT FROM AUTHOR]

Copyright of Iranian Journal of Information Processing & Management is the property of Iranian Information & Documentation Center (IRANDOC) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The present work analyses a lossless cavity through which two two-level atoms passed one after another. The first atom interacted with the cavity field via a three-photon process and left the cavity. The second atom entered the cavity and interacted with it when alterations were already present due to the first atom. The two atoms got entangled in the process even though they do not interact directly [1, 2]. The properties of the radiation field encountered by them crucially affect the nature of entanglement. The entanglement of formation of the joint two-atom state as a function of the Rabi angle Ωt is calculated for the Fock state field, coherent field, and thermal field, respectively, inside the cavity. We present a comparative analysis of atom-atom entanglement corresponding to different field statistics. [ABSTRACT FROM AUTHOR]

The endangered conifer whitebark pine (Pinus albicaulis), native to high elevation forests of western North America, is declining mainly due to the introduced pathogen Cronartium ribicola , causing the disease white pine blister rust. Low levels of genetic resistance to blister rust are present in whitebark pine populations. Traditional methods of inoculating seedlings to determine resistance to the rust are costly, labour intensive, and have limited capacity due to facilities. This presents a bottleneck in the development of resistant material for restoring stands that have been heavily infected by the rust. Here we test an alternative approach to controlled inoculations that could screen large numbers of families with lower costs and requiring fewer specialized resources. We screened 214 open-pollinated families from 44 provenances from British Columbia (BC), Washington (WA), Oregon (OR), Idaho (ID), Montana (MT), and Nevada (NV) to determine: (1) the effectiveness of natural rust inoculation from Ribes nigrum in a common garden; (2) family- and provenance-level resistance to blister rust; and (3) climate variables related to population-level rust resistance. Eighty-one of these families were previously screened by the US Forest Service in Cottage Grove, Oregon using standard artificial inoculation methods. The natural inoculation was effective, with 73 % of seedlings displaying stem symptoms of the disease, and 95 % showing rust infection. A clear relationship was found between distance from the nearest Ribes nigrum plant and severity of blister rust. Linear mixed models with spatial correlations were fitted to rust infection data using ASReml-R to estimate breeding values, heritability, and among-population differentiation (Q ST) for rust resistance. Population differentiation for rust resistance was moderate, with the highest resistance in provenances from the Cascade Mountains of Washington, and the most susceptible families from the BC Chilcotin and Okanagan regions. Heritability of rust resistance was moderate (0.23). The field testing was broadly consistent with classifications of families into resistant, moderate, and susceptible groups based on artificial inoculations. This method of screening could be used at a broader scale to determine families resistant to white pine blister rust without specialized testing facilities and increase the availability of resistant seedlings for restoration. • Whitebark pine is declining mainly due to white pine blister rust. • Whitebark pine has low levels of genetic resistance to white pine blister rust. • Traditional methods for screening for disease resistance have limited capacity. • Screening seedlings for resistance in an outdoor common garden can be effective. • Restoration implications, including planting recommendations, are discussed. [ABSTRACT FROM AUTHOR]

We find phase transitions and critical phenomena in cosmic thermodynamics. We derive the thermodynamic pressure (generalized force) P of the FRW (Friedmann–Robertson–Walker) universe in an effective higher order scalar-tensor theory with the work density W of a perfect fluid, which is a natural definition directly read out from the first law of thermodynamics. By this identification, we further construct an equation of state P = P (V , T) for the FRW universe and make a thorough discussion of its P − V phase transitions and critical phenomena. Impressively, we find that the coexistence phases of the phase transitions appear above the critical temperature, which is different from that of van der Waals system and most of black holes system. In the end, we calculate the critical exponents near the criticality of FRW universe and show that they are universal and are independent of the details of the physical system although the thermodynamic quantities depend on the coupling parameters. [ABSTRACT FROM AUTHOR]

We consider the thermodynamic Kuramoto model proposed in [27]. For each oscillator in thermodynamic Kuramoto model, there is a coupling effect between the phase and the temperature field. For such a model, we study a uniform stability and uniform-in-time mean-field limit to the corresponding kinetic equation. For this, we first derive a uniform ℓp-stability of the thermodynamic Kuramoto model with respect to initial data by directly estimating the temporal evolution of ℓp-distance between two admissible solutions to the particle thermodynamic Kuramoto model. In a large-oscillator limit, the Vlasov type mean-field equation can be rigorously derived using the BBGKY hierarchy, uniform stability estimate, and particle-in-cell method. We construct unique global-in-time measure-valued solutions to the derived kinetic equation and also derive a uniform-in-time stability estimate and emergent estimates. [ABSTRACT FROM AUTHOR]

The Paper presents the possibilities of using virtual reality techniques in interactive training of technical employees of a Distribution System Operator (DSO). It also describes the concept, assumptions and implementation method of the created Flexible Training System. Thanks to its capabilities, employees can participate in sophisticated training conducted in an innovative way eliminating the current disadvantages and limitations of classic – "real" training approaches. The System enables practice in two main categories of training used in the DSO environment: commutating operations and live-line works. Benefits and risks associated with system implementation in DSO structures are presented [ABSTRACT FROM AUTHOR]

A covert communication system is proposed in this study, in which a non-zero mean Gaussian sequence is used as a random carrier and its mean is modulated by a covert binary bit. The aperiodic transmitted signal exhibits the same statistical characteristics as the ambient noise to confuse an eavesdropper. The received signal is multiplied with the pseudo-random sequence synchronized with the transmitter to recover these positive and negative mean Gaussian sequence. The sample mean estimator and hard decision are used to determine the covert message, and accordingly, theoretical bit error rate in additive white Gaussian noise channel is also derived. Simulation results are very consistent with the theoretical derivation. The proposed system works in the physical layer with the advantages of simple structure, strong concealment, good BER performance and very suitable for low-cost, resource-limited and low-rate transmission devices. [ABSTRACT FROM AUTHOR]

The Pareto game for the model-free continuous-time stochastic system is studied through approximate/adaptive dynamic programming (ADP) in this paper. Firstly, the model-based online iterative algorithm is proposed, and it is proved that the control iterative sequence converges to the Pareto efficient solution, but the algorithm requires complete system parameters. Then, we derive the model-free iterative equation and develop the ADP algorithm to calculate the equation by collecting updated states and input information online. From the derivation of the ADP algorithm, the model-free iterative equation and the model-based iterative equation have the same solution, which means that the ADP algorithm can approximate the Pareto optimal solution. Next, the convergence analysis shows that the Pareto optimal strategy is uniquely determined by the ADP algorithm. Finally, two simulation examples confirm the feasibility of the ADP algorithm. • Solving the Pareto optimal control problem usually needs full system information. • The Pareto game problem is studied for model-free mean-field system. • Firstly, the Pareto optimal control is given by an iterative algorithm. • Next, an adaptive dynamic programming (ADP) method is used to get the Pareto game. • Lastly, the effectiveness of the ADP method is verified by two examples. [ABSTRACT FROM AUTHOR]

Sherardising is a surface protection method for obtaining an Fe-Zn coating on a steel surface by thermal diffusion. This paper proposes a model to study the sherardising diffusion process of low carbon steel. The diffusion mathematical model of the zinc coating element is established by the finite element method, which simulates the changes of zinc concentration field with temperature and time in the sherardising process. In the experimental work the sherardised samples were prepared for 2, 6 and 10 h at 375°C and 2, 6 and 8 h at 405°C and 420°C. Each phase's thickness and the zinc concentration of the sherardising layer were measured by scanning electron microscopy and energy dispersive spectrometry respectively. The results show that the accuracy of the finite element method is verified by the consistency between the simulation results and the experimental results. This model can effectively guide the sherardising process to achieve optimum results. [ABSTRACT FROM AUTHOR]

Zero-mean circular Gaussian statistics is a well-known model for coherent electromagnetic wave scattered by random media. Applying Kullback-Leibler Divergence to measure the deviation of the simulation scattering field probability distribution from this model, the formation of zero-mean circular Gaussian statistics is investigated quantitatively in two-dimensional random media based on finite element method. Increasing the scattering and randomness in the media, the transmission electric field gradually approaches zero-mean circular Gaussian statistics, however, the deviation from a perfect statistics distribution has a limit which is only determined by the number of random electric field variables used for estimates the probability distribution; besides, field amplitude forming stable statistics faster than field phase. [ABSTRACT FROM AUTHOR]

The following strong form of density of definable types is introduced for theories T admitting a fibered dimension function d : given a model M of T and a definable set X ⊆ M n , there is a definable type p in X , definable over a code for X and of the same d -dimension as X. Both o-minimal theories and the theory of closed ordered differential fields (CODF) are shown to have this property. As an application, we derive a new proof of elimination of imaginaries for CODF. [ABSTRACT FROM AUTHOR]

In this study, attempts to suppress numerical viscosity in incompressible smoothed particle hydrodynamics (SPH) computations are reported. Two-dimensional computations are performed for inviscid and viscous flows to evaluate the effects of numerical viscosity suppression. The first approach is to reduce numerical viscosity at the wall by considering only the wall-normal components of the forces between fluid particles and wall particles. The second approach is to reduce numerical viscosity within the flow field by employing elliptic kernel functions whose major axes are aligned with the local mean flow direction. It is found that special treatment of the wall radically reduces the numerical wall friction. Using an elliptic kernel function is found to work reasonably well in reducing numerical viscosity. [ABSTRACT FROM AUTHOR]

Abstract This paper is concerned with a stochastic optimal control of an infinite horizon system governed by mean-field forward–backward stochastic differential delay equations (MF-FBSDDEs) with Poisson jumps. We establish an Arrow's sufficient condition for this system with full information, and obtain a necessary condition of optimality under partial information. As an application of the necessary optimality condition, we also discuss a recursive utility optimal problem. [ABSTRACT FROM AUTHOR]

In the social network, when the virus or rumor breaks out, isolation strategy is widely adopted. However, the problem of invalid isolation is often existed in this strategy, and in the process, the nodes always keep the mobility. In order to solve these problems, the SIQR model is improved, some new parameters such as rate of new accession, rate of independent withdrawal and rate of invalid isolation are introduced, and the existence and stability of the equilibrium point are studied by using the complex network mean field theory. The relationship between the transmission rate and the isolation rate of the virus (rumors) is revealed. Reliability is verified through experiments. The experimental results show that the virus propagation is determined by a threshold, and the isolation rate is negatively related to this threshold. When the virus broke out, according to the relationship between the influencing factors and the threshold, take a variety of effective measures to control its propagation to the minimum range. [ABSTRACT FROM AUTHOR]

In complex color images, colors inside a homogeneous region might be contradistinctive and the distribution could not be described by a simple Gaussian distribution as used in traditional image segmentation algorithms. Based on the characteristics that the red, green, and blue color planes are not independent and pixels in the same neighborhood system might stand for the same object, we introduce a Gaussian model containing the interactions between different color planes to strengthen the connections both on a color plane and between color planes in a neighborhood system. Consequently, a Gaussian mixture model with the prior distribution, defined by Markov random field and acting as the weight, is employed to describe the distribution of color measures inside a homogeneous region. With the Gaussian mixture model containing the interactions between color planes, we proposed a fuzzy clustering approach for complex color image segmentation. Experiments on synthetic and real-color images, in which homogeneous regions are complex, show that the proposed algorithm compares favorably with the compared algorithms developed for the same purpose. [ABSTRACT FROM AUTHOR]

Cancer classification based on molecular level investigation has gained the interest of researches as it provides a systematic, accurate and objective diagnosis for different cancer types. Several recent researches have been studying the problem of cancer classification using data mining methods, machine learning algorithms and statistical methods to reach an efficient analysis for gene expression profiles. Studying the characteristics of thousands of genes simultaneously offered a deep insight into cancer classification problem. It introduced an abundant amount of data ready to be explored. It has also been applied in a wide range of applications such as drug discovery, cancer prediction and diagnosis which is a very important issue for cancer treatment. Besides, it helps in understanding the function of genes and the interaction between genes in normal and abnormal conditions. That is done by monitoring the behavior of genes -gene expression data- under different conditions. In this paper, an effective ensemble approach is proposed. Ensemble classifiers increase not only the performance of the classification, but also the confidence of the results. The motivations beyond using ensemble classifiers are that the results are less dependent on peculiarities of a single training set and because the ensemble system outperforms the performance of the best base classifier in the ensemble. [ABSTRACT FROM AUTHOR]

This paper investigates an optimal control of an infinite horizon system governed by mean-field backward stochastic differential equation with delay and partial information. Firstly, we establish the existence and uniqueness results for a mean-field backward stochastic differential equation (BSDE) with average delay. Then a class of mean-field time-advanced stochastic differential equations (ASDEs) is introduced as the adjoint equations via duality relation. Meanwhile, necessary and sufficient conditions for optimal control under partial information on infinite horizon are derived. Finally, we apply the theoretical results to study linear-quadratic control problem on infinite horizon to obtain the optimal control, which is explicitly expressed by the solution of a mean-field forward-backward stochastic differential filtering equation. [ABSTRACT FROM AUTHOR]

The grouping behavior is common in nature, e.g., fish school, bird flocks and insects swarms. Indeed, numerous theoretical and empirical predator-prey models have demonstrated the impact of group-living animals on ecosystems. To examine the interactions between individuals in the same group or competition between groups, we introduced different models based on Monte Carlo simulation and mean-field theory and found that the predator group sizes follow the geometric distribution and logarithmic distribution, as in previous empirical and theoretical cases. Our models also provide an intuitive explanation for these distributions. A new distribution based on the Holling-III functional response is presented; this distribution is heavy tailed in some specific cases. [ABSTRACT FROM AUTHOR]

This paper giving the associated credit risk model with the imperfect immunization scenario in the enterprises cluster based on assets-related under the framework of the small world network, we apply mean field theory and principle of epidemiology, to reveal the relation among associated credit risk contagion probability with imperfect immunization and asset-related in enterprises community network. The study has found that the threshold value of the associated credit risk contagion is reduced under the condition of the immune failure and immune invalidity, thereby, increasing the likelihood of related credit risk contagion; and the assets correlation between enterprises will influence the associated credit risk contagion and immune effect. [ABSTRACT FROM AUTHOR]

Mean radiant temperature (MRT) is a significant variable for outdoor thermal comfort studies. Two measurement-based methods can estimate MRT, one is globe thermometer – cheap, easily-applied but relatively inaccurate, another is integral radiation measurement method (also known as the six-directional method) - accurate but expensive. Due to low-cost and convenience, the globe thermometer has been widely used. Previous studies have improved its estimation accuracy by recalibrating the convection coefficients in the ISO method. Thus, it is pending to cross-compare the performance of these recalibrated methods. This study aims to investigate the transferability of the recalibrated methods for estimating MRT in outdoor environment. First, field measurement was conducted in a subtropical city, Hong Kong. MRT was obtained through two methods: globe thermometer and integral radiation method. Second, the existing recalibrated convection coefficients were summarized, and the localized convection coefficient was recalibrated. Third, all recalibrated methods were compared for their performance. The impacts of measurement locations, devices, analysis time intervals were examined. The results showed that the newly recalibrated method achieved the lowest estimation errors (RMSE = 3.84 °C). Other recalibrated methods presented higher RMSE (3.84–17.52 °C), similar as conventional ISO method (7.91 °C). Especially for open spaces, the coefficients from other cities should be cautiously applied when the accuracy requirement is less than ±2 °C. Kestrel and Grey globe are more recommended in subtropical cities. This study shed light on the application of globe thermometer for outdoor environment, and emphasized the necessity in recalibrating the convection coefficients locally. • Existing MRT estimation methods based on Tg were summarized and compared systematically. • The impacts of measurement locations with different SVF for MRT estimation were studied. • The impacts of measurement devices for MRT estimation were investigated. • The impacts of analysis time intervals for MRT estimation were explored. • The convection coefficient was recalibrated in a humid subtropical climate background. [ABSTRACT FROM AUTHOR]

• A mathematical model assuming prey refuge is a function of predator's density and hiding level of prey has been analyzed. • A time delay accounts for hiding behaviour of prey has been introduced, the delay parameter destabilizes the system. • Impact of fractional order, i.e., memory phenomenon has been explored in terms of stability analysis of the model system. • The probable biological explanations behind each obtained result of the model system have been thoroughly discussed. Most of the preys are well aware of sensing predation risk. Consequently, to escape from predators they usually adopt several defense mechanisms, specially refuge themselves to become invulnerable. In view of this, a mathematical model has been formulated incorporating prey refuge, where it is assumed that prey refuge is a function of predators availability in the system. It is shown that the model system is well-posed. It has been found that the hiding level and consumption rate of predators have a suitable interrelation between them. Both the parameters act as Hopf bifurcation parameters, but they play opposite role in case of stabilization of the system dynamics. Also, hiding level plays crucial role in maintaining the mean density of both the populations. Furthermore, as hiding behaviour of prey is not instantaneous, so a time delay, namely hiding delay has been introduced to make the model system more realistic and it is observed that the delay parameter destabilizes the system. Modelling approach through fractional calculus has been further deployed to study how the process of forgetting life history influences the dynamical intricacy of the population level dynamics. All the analytical findings have been testified by proper numerical performances. [ABSTRACT FROM AUTHOR]

Cotton is a vital component of the economies of Mid-South states. Producers and landowners are looking for ways to reduce the variability of irrigated yields, and soil apparent electrical conductivity (ECa) is a readily obtained parameter that can indicate soil variability. A study was conducted in 2011 and 2012 at the Fisher Delta Research Center in Portageville, MO, with the objective to determine the impact of soil spatial variability on yield and irrigation water use efficiency for cotton. Observed ECa values were low, consistent with average sand contents that ranged from 59 to 82% in the upper 0.76 m of the soil profile. Spatial autocorrelation was present in the data and thus spatial analyses were used. In 2011, yields for two treatments were not significantly different from the mean field effect; however, the ECa effect was significant, indicating that soil variability impacted yield more than irrigation differences for the two treatments. In 2012, yields for four of the six treatments were significantly different from the mean field effect; however, the ECa effect was not significant. A quadratic equation was fit to the combined data from irrigated and rainfed plots in 2012. The resulting equation had a maximum of 3,372 kg ha-1 at 135 mm total irrigation and the median observed ECa value (3.0 mS m-1). Future efforts will include additional fields and environments, which should increase the understanding of the impact of soil variability and allow for improved selection of optimum management zones for site specific application of water and other inputs. [ABSTRACT FROM AUTHOR]

Photo dissociation dynamics of linear triatomic molecule, cyanogen chloride (ClCN) in polar medium have been explored using Fourier grid Hamiltonian (FGH) method based two-dimensional mean field methodology. Ground electronic state potential of the molecule is calibrated with coupled cluster singles and doubles (CCSD) level ab initio theory using Gaussian 03 package taking 6-311++G(3df,2pd) as the basis set and fitted with two-dimensional coupled Morse potential and this potential is used for numerical calculation. Time-integrated probability current density is used as the measure of dissociation probability. Monochromatic and bichromatic laser fields are used as the external field and dissociation probability is calculated as the function of field frequency, dipolar position and pulse shape. [ABSTRACT FROM AUTHOR]

Teeth are the hardest part of the human body. Cracking of human teeth under compression progresses by avalanches emitting acoustic noise. Acoustic emission (AE) spectroscopy reveals that tooth avalanches are statistically fully compatible with predictions of mean field (MF) theory. Avalanche energies collapse into a power law distributed which is stable over more than five decades with an energy exponent ε = 1.4. Acoustic amplitudes (exponent ~τ), durations (~α), correlations between amplitudes and energies (~x), and correlations between amplitude and duration (~χ) follow equally power laws with MF values of all exponents. The exponents correlation: τ-1 = x(ε-1) = (α-1)/χ is confirmed. Crack propagation bifurcates and shows the hallmarks of avalanches where main cracks nucleate secondary cracks. [ABSTRACT FROM AUTHOR]

The technical success of an enhanced oil recovery (EOR) project depends on two main factors: first, the reservoir remaining oil saturation (ROS) after primary and secondary operations, and second, the recovery efficiency of the EOR process in mobilizing the ROS. These two interrelated parameters must be estimated before embarking on a time-consuming and costly process for designing and implementing an EOR process. The oil saturation can vary areally and vertically within the reservoir, and the distribution of the ROS will determine the success of the EOR injectants in mobilizing the remaining oil. There are many methods for determining the oil saturation (Chang et al. 1988; Pathak et al. 1989), and these include core analysis, well-log analysis, log/inject/log (LIL) procedures (Richardson et al. 1973; Reedy 1984), and single-well chemical tracer tests (SWCTT) (Deans and Carlisle 1986). These methods have different depths of investigation and different accuracies, and they all provide valuable information about the distribution of ROS. No single method achieves the best estimate of ROS, and a combination of all these methods is essential in developing a holistic picture of oil saturation and in assessing whether the oil in place (OIP) is large enough to justify the application of an EOR process. As Teletzke et al. (2010) have shown, EOR implementation is a complex process, and a staged, disciplined approach to identifying the key uncertainties and acquiring data for alleviating the uncertainties is essential. The largest uncertainty in some cases is the ROS in the reservoir. This paper presents the results from a fieldwide data acquisition program conducted in a west Texas carbonate reservoir to estimate ROS as part of an EOR project assessment. The Means field in west Texas has been producing for more than the past 75 years, and the producing mechanisms have included primary recovery, secondary waterflooding, and the application of a CO2 EOR process. The Means field is an excellent example of how the productive life and oil recovery can be increased by the application of new technology. The Means story is one of judicious application of appropriate EOR technology to the sustained development of a mature asset. The Means field is currently being evaluated for further expansion of the EOR process, and it was imperative to evaluate the oil saturation in the lower, previously undeveloped zones. This paper briefly outlines the production history, reservoir description, and reservoir management of the Means field, but this paper concentrates on the residual oil zone (ROZ) that underlies the main producing zone (MPZ) and describes a recent data acquisition program to evaluate the oil saturation in the ROZ. We discuss three major methods for evaluating the ROS: core analysis, LIL tests, and SWCTT tests. [ABSTRACT FROM AUTHOR]

Copyright of Revue d'Economie Politique is the property of Editions Dalloz Sirrey and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: Field Alignment is a useful and often necessary preprocessing step in contemporary geophysical state and parameter estimation of coherent structures. In an advance, we introduce a new framework for using Field Alignment to quantify uncertainty from an ensemble of coherent structures. Our method, called Coalescence, discovers the mean field under non-trivial misalignments of fields with complex shapes, which is especially diffcult to calculate in the presence of sparse observations. We solve the associated Field Alignment problem using novel constraints derived from turbulent displacement spectra. In conjunction with a continuation method called Scale Cascaded Alignment (SCA), we are able to extract simpler explanations of the error between fields before cascading to more complex deformation solutions. For coherent structures, SCA and Coalescence have the potential to change the way uncertainty is quantified and data is assimilated. We illustrate utility here in a Nowcasting application. [Copyright &y& Elsevier]

We address the problem of computing approximate marginals in Gaussian probabilistic models by using mean field and fractional Bethe approximations. We define the Gaussian fractional Bethe free energy in terms of the moment parameters of the approximate marginals, derive a lower and an upper bound on the fractional Bethe free energy and establish a necessary condition for the lower bound to be bounded from below. It turns out that the condition is identical to the pairwise normalizability condition, which is known to be a sufficient condition for the convergence of the message passing algorithm. We show that stable fixed points of the Gaussian message passing algorithm are local minima of the Gaussian Bethe free energy. By a counterexample, we disprove the conjecture stating that the unboundedness of the free energy implies the divergence of the message passing algorithm. [ABSTRACT FROM AUTHOR]

Abstract: Inhomogeneous dynamical mean-field theory has been employed to solve many interesting strongly interacting problems from transport in multilayered devices to the properties of ultracold atoms in a trap. The main computational step, especially for large systems, is the problem of calculating the inverse of a large sparse matrix to solve Dyson''s equation and determine the local Green''s function at each lattice site from the corresponding local self-energy. We present a new e_cient algorithm, the Lanczos-based low-rank algorithm, for the calculation of the inverse of a large sparse matrix which yields this local (imaginary time) Green''s function. The Lanczos-based low-rank algorithm is based on a domain decomposition viewpoint, but avoids explicit calculation of Schur complements and relies instead on low-rank matrix approximations derived from the Lanczos algorithm, for solving the Dyson equation. We report at least a 25-fold improvement of performance compared to explicit decomposition (such as sparse LU) of the matrix inverse. We also report that scaling relative to matrix sizes, of the low-rank correction method on the one hand and domain decomposition methods on the other, are comparable. [Copyright &y& Elsevier]

Abstract: We present a unified theoretical description of the quantum condensates in the electron-hole-photon (ehp) systems, which covers all condensates of exciton, polariton, and photon. To build such model, a phenomenological mean-field treatment for the exciton condensation is employed and extended to include the photon degree of freedom. We clarify changes from exciton/polariton condensations in the low-density limit to photon condensation in the high-density limit as a function of the detuning and the density. Clear change in the microscopic quantities are also found; the carrier distribution function shows broadening in the momentum space, and the minimal excitation energy for breaking an electron-hole (eh) pair increases even in the high density limit. Along this change, relative motion of electron and hole is confined within a tiny radius. In other words, the Wannier-type exciton-polariton picture is replaced by the Frenkel-type. This indicates that the smallest length scale of the system (corresponding to some ultraviolet cutoff) plays important roles due to the presence of coupling between carriers and coherent photons. These features show a remarkable contrast from the scenario of BEC-BCS crossover in the eh systems. [Copyright &y& Elsevier]

Abstract: The concept of replica symmetry breaking found in the solution of the mean-field Sherrington-Kirkpatrick spinglass model has been applied to a variety of problems in science ranging from biological to computational and even financial analysis. Thus it is of paramount importance to understand which predictions of the mean-field solution apply to non-mean-field systems, such as realistic short-range spin-glass models. The one-dimensional spin glass with random power-law interactions promises to be an ideal test-bed to answer this question: Not only can large system sizes—which are usually a shortcoming in simulations of high-dimensional short-range system—be studied, by tuning the power-law exponent of the interactions the universality class of the model can be continuously tuned from the mean-field to the short-range universality class. We present details of the model, as well as recent applications to some questions of the physics of spin glasses. First, we study the existence of a spin-glass state in an external field. In addition, we discuss the existence of ultrametricity in short-range spin glasses. Finally, because the range of interactions can be changed, the model is a formidable test-bed for optimization algorithms. [ABSTRACT FROM AUTHOR]

Abstract: The study of the spread of epidemic on different social networks has attracted many attentions from researchers in different fields. One main topical problem is the threshold of transmission rate or the basic reproductive number on different social networks. Recently, several efficient methods on solving the threshold of epidemic on heterogeneous networks were proposed. In this paper, we summarize several methods and compare their advantages or disadvantages systematically. [ABSTRACT FROM AUTHOR]

Abstract: We propose an improved SIS (Susceptible-Infected-Susceptible) model with mobile agents to explore the effect of agents’ motion on the epidemic spreading. Under the random jumping situation, the analytic formula of critical threshold is derived by the mean field theory. Then a large number of numerical simulations are performed to verify the theoretic prediction, and the simulation results at the condition of different population density and infection radius agree well with the mean field analysis. In addition, we also find that the long range jump will also remarkably influence the dissemination behavior of epidemic spreading. [ABSTRACT FROM AUTHOR]

Abstract: We determine the calcium fluxes through inositol 1,4,5-trisphosphate receptor/channels underlying calcium puffs of Xenopus laevis oocytes using a simplified version of the algorithm of Ventura et al. . An analysis of 130 puffs obtained with Fluo-4 indicates that Ca2+ release comes from a region of width ∼450nm, that the release duration is peaked around 18ms and that the underlying Ca2+ currents range between 0.12 and 0.95pA. All these parameters are independent of IP3 concentration. We explore what distributions of channels that open during a puff, N p , and what relations between current and number of open channels, I(N p ), are compatible with our findings and with the distribution of puff-to-trigger amplitude ratio reported in Rose et al. . To this end, we use simple “mean field” models in which all channels open and close simultaneously. We find that the variability among clusters plays an important role in shaping the observed puff amplitude distribution and that a model for which I(N p ) ∼ N p for small N p and (α >1) for large N p , provides the best agreement. Simulations of more detailed models in which channels open and close stochastically show that this nonlinear behavior can be attributed to the limited time resolution of the observations and to the averaging procedure that is implicit in the mean-field models. These conclusions are also compatible with observations of ∼400 puffs obtained using the dye Oregon green. [Copyright &y& Elsevier]

Abstract: Evolutionary game dynamics is one of the most fruitful frameworks for studying evolution in different disciplines, from Biology to Economics. Within this context, the approach of choice for many researchers is the so-called replicator equation, that describes mathematically the idea that those individuals performing better have more offspring and thus their frequency in the population grows. While very many interesting results have been obtained with this equation in the three decades elapsed since it was first proposed, it is important to realize the limits of its applicability. One particularly relevant issue in this respect is that of non-mean-field effects, that may arise from temporal fluctuations or from spatial correlations, both neglected in the replicator equation. This review discusses these temporal and spatial effects focusing on the non-trivial modifications they induce when compared to the outcome of replicator dynamics. Alongside this question, the hypothesis of linearity and its relation to the choice of the rule for strategy update is also analyzed. The discussion is presented in terms of the emergence of cooperation, as one of the current key problems in Biology and in other disciplines. [Copyright &y& Elsevier]

The NCTM Principles and Standards note that conceptual understanding of a given topic is promoted through exposure to multiple representations of the concept and exploration of connections of the topic to other learning. The following article explores this idea through careful study of "mean" from multiple viewpoints with multiple representations. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, we consider the problem of tracking similar objects. We show how a mean field approach can be used to deal with interacting targets and we compare it with Markov Chain Monte Carlo (MCMC). Two mean field implementations are presented. The first one is more general and uses particle filtering. We discuss some simplifications of the base algorithm that reduce the computation time. The second one is based on suitable Gaussian approximations of probability densities that lead to a set of self-consistent equations for the means and covariances. These equations give the Kalman solution if there is no interaction. Experiments have been performed on two kinds of sequences. The first kind is composed of a single long sequence of twenty roaming ants and was previously analysed using MCMC. In this case, our mean field algorithms obtain substantially better results. The second kind corresponds to selected sequences of a football match in which the interaction avoids tracker coalescence in situations where independent trackers fail. [Copyright &y& Elsevier]

Non-ideal gas flow behaviors are investigated by an Enskog-Vlasov type kinetic model considering the simultaneous effects of gas molecule size (volume exclusion) and long-range intermolecular attractions at the molecular level, which corresponds to the real gas equation of state at the macroscopic level. The Knudsen minimum is captured and a local Knudsen maximum may appear if gas molecule sizes or intermolecular attractive forces are considered. Although the Boltzmann equation is applicable to all the flow regimes in rarefied gas dynamics, it is invalid for a dense gas system, such as a tight or a shale gas reservoir. The Boltzmann-BGK model and the Enskog-BGK model overestimate and underestimate the mass flow rate of real gases, respectively, while Guo's model is more accurate to investigate real gas dynamics under tight confinements from a physical perspective. As the channel width increases or the solid fraction decreases, the impact of intermolecular interactions reduces. An anomalous slip regime occurs if both the volume exclusion and long-range intermolecular attraction are considered. Although the rarefaction effect is more prominent at larger Knudsen numbers, the flow at a smaller Knudsen number (a larger solid fraction or channel width) contributes to more practical gas production. The effect of long-range intermolecular attractions on gas dynamics decreases with temperature for real gases. This paper provides a novel insight into the real gas flow characteristics in a dense gas system, such as tight and shale gas reservoirs, from molecular natures of fluids. • Natural gas flows under tight confinements are investigated. • The volume exclusion among natural gas molecules is modelled by the Enskog theory. • The long-range intermolecular interactions are coupled by the mean-field theory. • The rarefaction effect is considered by the Boltzmann-BGK collision operator. • The Knudsen minimum and local Knudsen maximum are captured. [ABSTRACT FROM AUTHOR]

In this article we consider the issue of optimal control in collaborative multi-agent systems with stochastic dynamics. The agents have a joint task in which they have to reach a number of target states. The dynamics of the agents contains additive control and additive noise, and the autonomous part factorizes over the agents. Full observation of the global state is assumed. The goal is to minimize the accumulated joint cost, which consists of integrated instantaneous costs and a joint end cost. The joint end cost expresses the joint task of the agents. The instantaneous costs are quadratic in the control and factorize over the agents. The optimal control is given as a weighted linear combination of single-agent to single-target controls. The single-agent to single-target controls are expressed in terms of diffusion processes. These controls, when not closed form expressions, are formulated in terms of path integrals, which are calculated approximately by Metropolis-Hastings sampling. The weights in the control are interpreted as marginals of a joint distribution over agent to target assignments. The structure of the latter is represented by a graphical model, and the marginals are obtained by graphical model inference. Exact inference of the graphical model will break down in large systems, and so approximate inference methods are needed. We use naive mean field approximation and belief propagation to approximate the optimal control in systems with linear dynamics. We compare the approximate inference methods with the exact solution, and we show that they can accurately compute the optimal control. Finally, we demonstrate the control method in multi-agent systems with nonlinear dynamics consisting of up to 80 agents that have to reach an equal number of target states. [ABSTRACT FROM AUTHOR]

A nonlocal pressure equation is derived from mean-field free energy theory for calculating liquid-vapor systems. The proposed equation is validated analytically by showing that it reduces to van der Waals' square-gradient approximation under the assumption of slow density variations. The proposed nonlocal pressure is implemented in the mean-field free energy lattice Boltzmann method (LBM). The LBM is applied to simulate equilibrium liquid-vapor interface properties and interface dynamics of capillary waves and oscillating droplets in vapor. Computed results are validated with Maxwell constructions of liquid-vapor coexistence densities, theoretical relationship of variation of surface tension with temperature, theoretical planar interface density profiles, Laplace's law of capillarity, dispersion relationship between frequency and wave number of capillary waves, and the relationship between radius and the oscillating frequency of droplets in vapor. It is shown that the nonlocal pressure formulation gives excellent agreement with theory. [ABSTRACT FROM AUTHOR]

Abstract: A novel approach is proposed to analyzing and tracking the motion of structured deformable shapes, which consist of multiple correlated deformable subparts. Since this problem is high dimensional in nature, existing methods are plagued either by the inability to capture the detailed local deformation or by the enormous complexity induced by the curse of dimensionality. Taking advantage of the structured constraints of the different deformable subparts, we propose a new statistical representation, i.e., the Markov network, to structured deformable shapes. Then, the deformation of the structured deformable shapes is modelled by a dynamic Markov network which is proven to be very efficient in overcoming the challenges induced by the high dimensionality. Probabilistic variational analysis of this dynamic Markov model reveals a set of fixed point equations, i.e., the sequential mean field equations, which manifest the interactions among the motion posteriors of different deformable subparts. Therefore, we achieve an efficient solution to such a high-dimensional motion analysis problem. Combined with a Monte Carlo strategy, the new algorithm, namely sequential mean field Monte Carlo, achieves very efficient Bayesian inference of the structured deformation with close-to-linear complexity. Extensive experiments on tracking human lips and human faces demonstrate the effectiveness and efficiency of the proposed method. [Copyright &y& Elsevier]

We report on efficient calculation method for forces of interaction in N-body problem, which allows for time ∼o(N Iog(N)) produce the analysis of behavior of such ensembles of particles, for which use of direct summation method requires unbelievably big calculation time. In contrast with other methods of the similar purpose it possesses the advantages, which are important at modeling of the collective processes in semiconductor device by method of the particles. [ABSTRACT FROM AUTHOR]

This paper proposes a parallel mean-field approximation algorithm based on the mean-field theory. In the parallel mean-field algorithm, a stable configuration at each temperature is obtained by applying the mean-field approximation to each element in the state space of a system, so that an actual state is replaced with a mean state, and by sequentially updating the mean field. This makes the convergence of a learning process faster than those in the simulated annealing algorithm and the Boltzmann machine. This paper examines Peterson's idea from the viewpoint of the mean learning algorithm and constructs a parallel learning algorithm confirming the existence of its stable distribution. To improve the processing speed of the proposed method further, this paper introduces a new temperature scheduling method (maximum entropy cooling schedule) by reexamining the temperature schedule of the Monte Carlo process and analyzing changes of the maximum entropy at a transition of a mean field of the system. Computer simulations show that the proposed method produces the same results as the conventional method but with shorter computation time, and also that the proposed maximum-entropy cooling schedule agrees with a thermodynamic analogy. [ABSTRACT FROM AUTHOR]

Mean Radiant Temperature (T mrt) is a decisive parameter in determining outdoor thermal comfort in human biometeorology. The estimation of T mrt in an outdoor environment is however complex. This study attempts to determine T mrt by the six directional method and recalibrate the mean convection coefficient of the gray globe for ease of use in the humid subtropical climate. Six directional short - wave and long-wave radiant flux densities have been measured and analysed across different urban open spaces — plaza, promenade and green. The study presents the relationship between T mrt and the radiant flux densities. T mrt values obtained via the six directional method show a statistically significant difference with those obtained using mean convection coefficients discussed in literature. Consequently, the mean convection coefficient of the gray globe thermometer has been recalibrated for use in the humid subtropical climate. T mrt estimated via the recalibrated mean convection coefficient agrees well with the results of the six directional method. • This study evaluates short-wave and long - wave radiant flux densities in varied typologies of open spaces in the context of humid subtropical climate. • Computing T mrt in accordance with ISO 7726:1998 has been found to be inappropriate for use in the context of outdoor spaces in humid subtropical climate. • The mean convection coefficient of the gray globe thermometer has been re-calibrated for use in humid subtropical climate and results validated through field measurements. • An increment of 1 K in T mrt in the open spaces can be attributed to an increase of 8.33 Wm-2 in the weighted sum of long-wave or short-wave radiant flux densities. [ABSTRACT FROM AUTHOR]