A Multifractal Detrended Fluctuation Analysis of the Ising Financial Markets Model with Small World Topology

We present a multifractal detrended fluctuation analysis （MFDFA） of the time series of return generated by our recently-proposed Ising financial market model with underlying small world topology. The result of the MFDFA shows that there exists obvious multifractal scaling behavior in produced time series. We compare the MFDFA results for original time series with those for shuffled series, and find that its multifractal nature is due to two factors： broadness of probability density function of the series and different correlations in small- and large-scale fluctuations. This may provide new insight to the problem of the origin of multifractality in financial time series.

Numerical modelling of the depth variation and the fluctuation of the thermocline under the effects of wind in the Bohai Sea

-In this paper, numerical modelling of the fluctuation of the thermocline in the Bohai Sea has been made using a two-dimensional nonlinear model in stratified ocean and the model for the depth of the thermocline under the effects of wind stirring. The computed results depict the variations of the fluctuation of the thermocline driven by different kinds of wind fields. The fluctuation of the thermocline in the Bohai Sea varies somewhat with different directions, paths and locations of typhoon (cyclone). Under the effects of strong wind, the thermoclines both sink due to mixing and fluctuate. Furthermore, the fluctuation of the thermocline speeds up mixing. At last, the thermoclines disappear after 12-15 h when the strong wind increases from Force 6 to Force 9.

Bayesian-MCMC-based parameter estimation of stealth aircraft RCS models

When modeling a stealth aircraft with low RCS（Radar Cross Section）, conventional parameter estimation methods may cause a deviation from the actual distribution, owing to the fact that the characteristic parameters are estimated via directly calculating the statistics of RCS. The Bayesian–Markov Chain Monte Carlo（Bayesian-MCMC） method is introduced herein to estimate the parameters so as to improve the fitting accuracies of fluctuation models. The parameter estimations of the lognormal and the Legendre polynomial models are reformulated in the Bayesian framework. The MCMC algorithm is then adopted to calculate the parameter estimates. Numerical results show that the distribution curves obtained by the proposed method exhibit improved consistence with the actual ones, compared with those fitted by the conventional method. The fitting accuracy could be improved by no less than 25% for both fluctuation models, which implies that the Bayesian-MCMC method might be a good candidate among the optimal parameter estimation methods for stealth aircraft RCS models.

Heterogeneous performance analysis of the new model of CFAR detectors for partially-correlated χ~2-targets

To mitigate the deleterious effects of clutter and jammer, modern radars have adopted adaptive processing techniques such as constant false alarm rate(CFAR) detectors which are widely used to prevent clutter and noise interference from saturating the radar’s display and preventing targets from being obscured.This paper concerns with the detection analysis of the novel version of CFAR schemes(cell-averaging generalized trimmed-mean,CATM) in the presence of additional outlying targets other than the target under research. The spurious targets as well as the tested one are assumed to be fluctuating in accordance with the χ~2-model with two-degrees of freedom. In this situation, the processor performance is enclosed by the swerling models(SWI and SWII). Between these bounds, there is an important class of target fluctuation which is known as moderately fluctuating targets. The detection of this class has many practical applications. Structure of the CATM detector is described briefly. Detection performances for optimal, CAM, CA, trimmed-mean(TM) and ordered-statistic(OS) CFAR strategies have been analyzed and compared for desired probability of false alarm and determined size of the reference window. False alarm rate performance of these processors has been evaluated for different strengths of interfering signal and the effect of correlation among the target returns on the detection and false alarm performances has also been studied. Our numerical results show that, with a proper choice of trimming parameters,the novel model CAM presents an ideal detection performance outweighing that of the Neyman-Pearson detector on condition that the tested target obeys the SWII model in its fluctuation. Although the new models CAS and CAM can be treated as special cases of the CATM algorithm, their multi-target performance is modest even it has an enhancement relative to that of the classical CAcheme. Additionally, they fail to maintain the false alarm rate constant when the operating environment is of type target multiplicity. Moreover, the non-coherent integration of M pulses ameliorates the processor performance either it operates in homogeneous or multi-target environment.

A two-scale second-order moment two-phase turbulence model for simulating dense gas-particle flows

A two-scale second-order moment two-phase turbulence model accounting for inter-particle collision is developed, based on the concepts of particle large-scale fluctuation due to turbulence and particle small-scale fluctuation due to collision and through a unified treatment of these two kinds of fluctuations. The proposed model is used to simulate gas-particle flows in a channel and in a downer. Simulation results are in agreement with the experimental results reported in references and are near the results obtained using the sin- gle-scale second-order moment two-phase turbulence model superposed with a particle collision model （USM-θ model） in most regions.

ELASTIC BEHAVIOR OF COMB-LIKE POLYMER CHAINS

Three-dimensional Monte Carlo simulations of comb-like polymer chains with various backbone lengths Nb, arm lengths Na and arm densities m are carried out to study the elastic behavior of comb-like polymer chains. The radius of gyration, the shape factors and bond length in different cases during elastic process are calculated, and it is found that the comb-like polymer molecules with longer backbone or shorter arm are more close to linear chains. But the arm density rn affects the chain conformation non-monotonously. Some thermodynamic properties are also studied. Average Helmholtz free energy and elastic force fall increase with elongation ratio 2 for all chains.

MONTE CARLO STUDY ON THE CRITICAL ADSORPTION POINT OF BONDFLUCTUATED POLYMER CHAINS TETHERED ON ADSORBING SURFACES

The behavior of three-dimensional bond fluctuation model chains tethered on an adsorbing fiat surface was simulated by the Monte Carlo method.The dependence of the number of surface contacts M on the interaction strengthεand the chain length N was investigated by a finite-size scaling law M = N;[a;+a;N;κ+ O((N;κ);)]forεnear the critical adsorption pointε;,i.e.,κ=（ε-ε;）/ε;closes to 0.The critical adsorption point was estimated to beε;=0.93,and the exponentsφ= 0.49 and l/v= 0.57.

A numerical method for spherical particle motion in turbulent flow with large Reynolds number

A new mathematical model, fluctuation spectrum random trajectory model (FSRTM) for the particle motion in environmental fluid was developed using Lagrangian method, in which the time mean velocity of the fluid was calculated by a time mean velocity formula for two dimensional homogeneous shear turbulent flows in open channel, the velocity fluctuation of the fluid was determined by Fourier expansion and fluctuation spectrum, and the particle motion equation was solved using Ronge Kutta method. For comparison, the spherical cation exchange resins with a density of 1 44 g/cm\+3 and diameters ranging from 0 50—0 60 mm, 0 60—0 70 mm and 0 80—0 90 mm were selected as the experimental solid particles, and their moving velocities and trajectories in shear turbulent flows with the flow Reynolds number of 4710, 10240, 11900 and 20760 were investigated. The comparing analyses of the modeled results with the measured results have shown that the model developed in this paper can describe the motions of the particles in shear turbulent flow.

Arguing on Entropic and Enthalpic First-Order Phase Transitions in Strongly Interacting Matter

The pattern of isentropes in the vicinity of a first-order phase transition is proposed as a key for a sub-classification. While the confinement-deconfinement transition, conjectured to set in beyond a critical end point in the QCD phase diagram, is often related to an entropic transition and the apparently settled gas-liquid transition in nuclear matter is an enthalphic transition, the conceivable local isentropes w.r.t. “incoming” or “outgoing” serve as another useful guide for discussing possible implications, both in the presumed hydrodynamical expansion stage of heavy-ion collisions and the core-collapse of supernova explosions. Examples, such as the quark-meson model and two-phase models, are shown to distinguish concisely the different transitions.

A TWO-SCALE SECOND-ORDER MOMENT PARTICLE TURBULENCE MODEL FOR GAS-PARTICLE FLOW

A two-scale second-order moment two-phase turbulence model was developed and used to simulate gas-particle flow in a sudden-expansion chamber and a channel. The simulation results were in agreement with the experimental results, and the results were compared with those of the single-scale second-order moment two-phase turbulence model. Several improved features show that the two-scale model is to a certain extent better than the single-scale model, which may be attributed to the fact that particle turbulence is well characterized by the two-scale turbulence model.

Microhydration of Alanine in Gas Phase Studied by Quantum Chemical Method and ABEEMσπ~/MM Fluctuating Charge Model

A fluctuating charge interaction potential function for alanine-water was constructed in the spirit of newly developed ABEEMax/MM（atom-bond electronegativity equalization method at the azc level fused into molecular mechanics）. The properties of gaseous neutral alanine-（H20）n（n=l--7） clusters were systematically investigated by quantum mechanics（QM） and the constructed ABEEMax/MM potential, such as conformations, hydrogen bonds （H-bonds）, interaction energies, charge distributions, and so on. The results of ABEEM^rrc/MM model are in fair agreement with those of QM and available experimental data. For isolated alanine, compared with those of experi- mental structure, the average absolute deviations（AAD） of bond length and bond angle are 0.002 nm and 1.4~, re- spectively. For alanine-water clusters, the AAD of interaction energies and H-bond lengths are only 3.77 kJ/mol and 0.012 nm, respectively, compared to the results of MP2/aug-cc-pVDZ//MP2/6-31 I＋G＊＊ method. The ABEEMa charges fluctuate with the changing conformation of the system, and can accurately and reasonably reflect the inter- polarization between water and alanine. The presented alanine-water potential function may provide a basis for fur- ther simulations on related aqueous solutions ofbiomolecules.

Discussion on the paper “Analyzing short time series data from periodically fluctuating rodent populations by threshold models: A nearestblock bootstrap approach”

The authors are to be congratulated for an innovative paper in terms of both modelling methodology and subject matter significance. The analysis of short time series is known to be

Discussion on the paper “Analyzing short time series data from periodically fluctuating rodent populations by threshold models: A nearestblock bootstrap approach”

This is a very attractive article. It combines fascinating new methodology with a most interesting dataset, and a highly motivating presentation. However, despite the many

Influence of stealth aircraft dynamic RCS peak on radar detection probability

For modern stealth aircraft,it is important to analyze the influence of Radar Cross Section(RCS)peak exposure on penetration for guiding stealth design and penetration trajectory planning,which needs to reflect the RCS statistical uncertainty and the RCS difference with the change of incident angle.Based on the RCS characteristics of typical stealth aircraft,this paper established a simplified RCS dynamic fluctuation statistical model with the parameters log mean and log standard deviation.According to the detection probability algorithm in radar signal processing field,this paper built the algorithm of radar detection probability based on the RCS dynamic fluctuation statistical model.The analysis of examples concluded that the key to successful penetration is to shorten the RCS peak exposure time,which can be reduced by decreasing the RCS peak width or increasing velocity.Based on the conclusion,this paper proposed the method of turning maneuvering to reduce RCS peak exposure time dramatically.

Effect of particle degradation on electrostatic sensor measurements and flow characteristics in dilute pneumatic conveying

Vigorous particle collisions and mechanical processes occurring during high-velocity pneumatic con- veying often lead to particle degradation. The resulting particle size reduction and particle number increase will impact on the flow characteristics, and subsequently affect the electrostatic type of flow measurements. This study investigates this phenomenon using both experimental and numerical meth- ods. Particle degradation was induced experimentally by recursively conveying the fillite material within a pneumatic pipeline. The associated particle size reduction was monitored. Three electrostatic sensors were embedded along the pipeline to monitor the flow. The results indicated a decreasing trend in the electrostatic sensor outputs with decreasing particle size, which suggested the attenuation of the flow velocity fluctuation. This trend was more apparent at higher conveying velocities, which suggested that more severe particle degradation occurred under these conditions. Coupled computational fluid dynamics and discrete element methods （CFD-DEM） analysis was used to qualitatively validate these experimental results. The numerical results suggested that smaller particles exhibited lower flow velocity fluctua- tions, which was consistent with the observed experimental results. These findings provide important information for the accurate aoolication of electrostatic measurement devices in oneumatic conveyors.