Economic Market Fluctuation Model Based on Internet of Things Technology

In order to explore the impact of the Internet of Things technology on economic market fluctuations and the analysis effect of the Internet of Things technology on economic market fluctuations, this paper uses the Internet of Things algorithm to improve the economic fluctuation model. Moreover, this paper uses the Internet of Things algorithm to locate economic transactions and performs data processing to optimize the intelligent network system to improve the operating effect of the economic system. In addition, this paper improves the sensor node algorithm and proposes to use the weighted value of network node density to balance the positioning problem caused by the unbalanced distribution of network nodes in the detection area. Finally, this paper analyzes the market economy volatility model through the Internet of Things technology, combined with simulation experiments to explore the application of the Internet of Things technology in the economic market volatility model. Through experimental research, it can be known that economic market fluctuation models based on Internet of Things technology can play an important role in market economic analysis.

Surface properties for Ne, Na, Mg, Al and Si isotopes in the Coherent Density Fluctuation Model using the relativistic mean field densities

We have systematically studied the surface properties, such as symmetry energy, neutron pressure, and symmetry energy curvature coefficient for Ne, Na, Mg, Al, and Si nuclei from the proton to neutron drip-lines. The Coherent Density Fluctuation Model (CDFM) is used to estimate these quantities taking the relativistic mean-field densities as inputs. The Br ¨uckner energy density functional is taken for the nuclear matter binding energy and local density approximation is applied for its conversion to coordinate space. The symmetry energy again decomposed to the volume and surface components within the liquid drop model formalism to the volume and surface parts separately. Before calculating the surface properties of finite nuclei, the calculated bulk properties are compared with the experimental data, whenever available. The NL3* parameter set with the BCS pairing approach in an axially deformed frame-work is used to take care of the pairing correlation when needed. The deformed density is converted to its spherical equivalent with a two Gaussian fitting, which is used as an input for the calculation of weight function in the CDFM approximation. With the help of the symmetry energy for the recently isotopes ²⁹F, ²⁸Ne, ^29,30Na and ^31,35,36Mg are considered to be within the island of inversion emphasized [Phys. Lett. B 772, 529 (2017)]. Although we get large symmetric energies corresponding to a few neutron numbers for this isotopic chain as expected, an irregular trend appears for all these considered nuclei. The possible reason behind this abnormal behavior of symmetry energy for these lighter mass nuclei is also included in the discussion, which gives a direction for future analysis.

The Frequency Fluctuation Model for the van der Waals Broadening

The effect of atomic and molecular microfied dynamics on spectral line shapes is under consideration. This problem is treated in the framework of the Frequency Fluctuation Model (FFM). For the first time the FFM is tested for the broadening of a spectral line by neutral particles. The usage of the FFM allows one to derive simple analytical expressions and perform fast calculations of the intensity profile. The obtained results was compared with Chen and Takeo theory (CT), which is in a good agreement with experimental data. It was demonstrated that for moderate values of temperature and density the FFM successfully describes the effect of the microfield dynamics on a spectral line shape.

Distribution Characteristics of Multivariate Financial Assets Return based on Mathematical Model

For the non-normality and time variability of the distribution of multivariate financial assets return, a dynamic model of the distribution of multivariate financial assets return based on mathematical model is constructed in this paper. AR(1)-DCC(1,1)-GARCH(1,1) model reflects dynamic characteristics of conditional expectation and conditional variance of multivariate financial assets return. It solves the problem that restricts the in-depth research on high order dynamic portfolio optimization, which is the estimation of conditional coskewness matrix and conditional cokurtosis matrix. By constructing a multi-dimensional fluctuation model with biased t distribution, conditional asymmetric parameter and conditional free degree parameter, the distribution of multivariate financial assets return is researched. Experimental results show that the proposed model can reasonably reflect the time-varying characteristics of the multivariate stock return distribution in China’s stock market.

Thermoelectric Power in Ce Systems with Unstable Valence

In this paper, we report on a few exemplary tests of the applicability of analysis based on the interconfiguration fluctuation model (ICF) for a description of the temperature dependence of the thermoelectric power, S(T). The examples include a series of alloys: CeNi2(Si1−yGey)2, Ce(Ni1−xCux)2Si2, and the fluctuating valence (FV) compound CeNi4Ga. The two series develop from CeNi2Si2 being the FV system, where the f states occupation increases progressively with the Ge or Cu substitution. We find here that the ICF model parameters are of similar magnitude both for the analysis of the temperature dependence of the magnetic susceptibility and thermoelectric power. The ICF-type model appears to be a powerful tool for the analysis of S(T) dependences in Ce-based FV compounds and alloys.

Characterization of Monte Carlo Dynamic/Kinetic Properties of Local Structure in Bond Fluctuation Model of Polymer System

We report the results of the characterization of local Monte Carlo (MC) dynamics of an equilibrium bond fluctuation model polymer matrix (BFM), in time interval typical for MC simulations of non-linear optical phenomena in host-guest systems. The study contributes to the physical picture of the dynamical aspects of quasi-binary mosaic states characterized previously in the static regime. The polymer dynamics was studied at three temperatures (below, above and close to the glass transition), using time-dependent generalization of the static parameters which characterize local free volume and local mobility of the matrix. Those parameters play the central role in the kinetic MC model of host-guest systems. The analysis was done in terms of the probability distributions of instantaneous and time-averaged local parameters. The main result is the characterization of time scales characteristic of various local structural processes. Slowing down effects close to the glass transition are clearly marked. The approach yields an elegant geometric criterion for the glass transition temperature. A simplified quantitative physical picture of the dynamics of guest molecules dispersed in BFM matrix at low temperatures offers a starting point for stochastic modeling of host-guest systems.

Periodic Fluctuations in the Incidence of Gastrointestinal Cancer

PurposeNative stem cells can be periodically replaced during short and long epigenetic intervals. Cancer-prone new stem cells might bring about periodic (non-stochastic) carcinogenic events rather than stochastic events. We investigated the epigenetic non-stochastic carcinogenesis by analyzing regular fluctuations in lifelong cancer incidence.Materials and MethodsKorean National Cancer Screening Program data were collected between 2009 and 2016. Non-linear and log-linear regression models were applied to comparatively evaluate non-stochastic and stochastic increases in cancer incidence. Prediction performances of regression models were measured by calculating the coefficient of determination, R2.ResultsThe incidence of gastric and colorectal cancers fluctuated regularly during both short (8 years) and long (20 years) intervals in the non-linear regression model and increased stochastically in the log-linear regression model. In comparison between the 20-year interval fluctuation model and the stochastic model, R2 values were higher in the 20-year interval fluctuation model of men with gastric cancer (0.975 vs. 0.956), and in the stochastic model of men with colorectal cancer (0.862 vs. 0.877) and women with gastric cancer (0.837 vs. 0.890) and colorectal cancer (0.773 vs. 0.809). Men with gastric cancer showed a high R2 value (0.973) in the 8-year interval fluctuation model as well.ConclusionLifelong incidence of gastrointestinal cancer tended to fluctuate during short and long intervals, especially in men with gastric cancer, suggesting the influence of an epigenetic schedule.

Phenomenological analysis of ΔI = 4 bifurcation and identical superdeformed bands

For the first time, a systematic study of identical superdeformed (SD) bands in [Formula: see text] mass region is made, where [Formula: see text] bifurcation is present. Four pairs of identical SD bands viz. [Formula: see text] and [Formula: see text] of [Formula: see text] mass region and [Formula: see text] and [Formula: see text] of [Formula: see text] mass region have been systematically studied. The present systematic study provides the universal description of the identical SD bands in various mass regions. We presented the empirical evidence of a similar structure of identical SD bands in various mass regions. For this purpose, we have used various rotational energy formulae. The free parameters are extracted from four identical SD bands. The [Formula: see text] bifurcation in identical SD bands is calculated from shape fluctuation formulae. For the first time, this shape fluctuation model is employed to calculate the [Formula: see text] bifurcation, making it an alternate powerful tool to study SD bands of various mass regions.