International Journal of Modern Physics C

The traditional public opinion dissemination model studies the dissemination of single opinion public opinion, while manual processing limits the division of multiple opinions, reducing the efficiency of public opinion dissemination. Therefore, combined with the topic recognition model, the SnCIR multi-opinion public opinion competition propagation model is constructed. The comparative experiment on the ca-GrQc dataset shows that the SnCIR model has a lower propagation density than the SCIR, SEIR and SIR models before the public opinion spreads stably. At the inflection point, SnCIR is 0.02 smaller than the SCIR model propagation density, 0.04 smaller than SEIR, and 0.65 smaller than SIR. Through the guidance of mainstream and official media, the management of the Weibo platform, and the government’s supervision, this paper studies the impact on the dissemination of network public opinion. Combined with the analysis of the evolution characteristics of the network public opinion situation, some countermeasures and suggestions are given, which provide management ideas for the response and governance of network public opinion in emergencies.

Traffic speed is an essential indicator for measuring traffic conditions. Real-time and accurate traffic speed prediction is an essential part of building intelligent transportation systems (ITS). Currently, speed prediction methods are characterized by insufficient short-term prediction accuracy and stability, nonlinear, nonstationary, strong fluctuation and relatively small sample size. To better explore the traffic characteristics of the road networks, a hybrid prediction model based on wavelet transform (WT) of the autoregressive moving average model (ARIMA) and gate recurrent unit (GRU) was constructed. First, this model decomposes the original traffic speed data into low-frequency data, and high-frequency data by WT. Second, the ARIMA and GRU models are used to model data predictions in two frequency bands, respectively. Finally, the prediction result of the predicted value is fused. In addition, in this paper, traffic speed data of four sections in Guangzhou from 1 August to 31 September 2016 are taken as examples to test the validity, applicability, and practicability of the model. The results show that compared with ARIMA, LSTM, GRU, RNN, and other single models and hybrid models, the prediction method proposed in this paper has higher prediction accuracy and can provide a more scientific decision-making basis for urban traffic management.

Identifying influential nodes in social networks has drawn significant attention in the field of network science. However, most of the existing works request to know the complete structural information about networks, indeed, this information is usually sensitive, private and hard to obtain. Therefore, how to identify the influential nodes in networks without disclosing privacy is especially important. In this paper, we propose a privacy-preserving (named as HE-ranking) framework to identify influential nodes in networks based on homomorphic encryption (HE) protocol. The HE-ranking method collaboratively computes the nodes’ importance and protects the sensitive information of each private network by using the HE protocol. Extensive experimental results indicate that the method can effectively identify the influential nodes in the original networks than the baseline methods which only use each private network to identify influential nodes. More importantly, the HE-ranking method can protect the privacy of each private network in different parts.

Two stable barium phosphides, Ba₂P and BaP, are predicted by an evolutionary algorithm and first-principles calculations. Ba₂P is a layered structure and isostructural to rhombohedral anti-CdCl₂. The interlayer distance between Ba–P–Ba layers is larger than the intralayer distance of the Ba–P–Ba layers. BaP adopts a body-centered orthorhombic structure composed of P dumbbells. Rhombohedral Ba₂P is metallic, whereas body-centered orthorhombic BaP is a semiconductor that exhibits a band gap of 0.345 eV; the dynamical stabilities of these two compounds were confirmed by phonon calculations and analysis. These findings should encourage further experimental study of the Ba–P system.

Solid-state thermoelectric devices offer the possibility of exploiting waste heat from engines and power plants and converting it into electrical energy. One of the greatest challenges in the development of thermoelectric material systems is to find new thermoelectric materials with high thermoelectric figures of merit ZT. In this work, the structural, electronic and thermoelectric properties of PbSe${}_{1-x}$S${}_x$ ($x=0$, 0.25, 0.50, 0.75 and 1) semiconductors are investigated by applying density functional theory in a full potential linearized augmented plane wave method (FP-LAPW). Calculations of structural properties were completed using the generalized gradient approximation GGA of Perdew Burke and Ernzerhof PBE to get reliable lattice constant results with experimental values. The obtained electronic results show that the PbSe${}_{1-x}$S${}_x$ material is a narrow band gap semiconductor. In addition, the thermoelectric properties are studied on the basis of the fully iterative solution of the Boltzmann transport equation. PbSe${}_{1-x}$S${}_x$ had a high figure of merit indicating that our materials are promising candidates in thermoelectric applications.

For the parameter estimation problem in research related to the fractional-order chaotic systems (FOCSs), a modified optimization algorithm based on Salp Swarm Algorithm (SSA) was developed in this paper. The proposed algorithm introduced several improvements on SSA: adding a grouping step, introducing “betrayal” behavior, and improving the update method of the followers. We applied multiple classical optimization algorithms to conduct the parameter estimation experiments on the fractional-order Lorenz chaotic system (Lorenz-FOCS) and the fractional-order Financial chaotic system (Financial-FOCS). In addition, we explored the impact of searching space on parameters estimation through experiments. The experimental results confirmed the feasibility of the modified Salp Swarm Algorithm (MSSA). The MSSA performed better than the SSA and other classical optimization algorithms in terms of the estimation accuracy and convergence rate.

In this work, we study the transmission of the new coronavirus, SARS-CoV-2, which causes COVID-19. Our main aim is to analyze the disease prevalence when vaccination and social distancing strategies are used. Simulations are implemented using an agent-based model (ABM) adapted from a Susceptible-Exposed-Infectious-Recovered (SEIR) type compartmental model. Several scenarios are simulated using the most common vaccines available in Brazil. On each scenario, different fractions of the population are affected by vaccination and social distancing measures. Results show the importance to start public health interventions to reduce the size of the epidemic. Besides, simulations show that vaccination only is not capable to control the disease spread.

In this study, we investigate the effect of entropy generation on a Casson hybrid nanofluid over a stretching cylinder in the presence of linear thermal radiation and Cattaneo–Christov heat flux. We assumed ${\mathrm{\text{Fe}}}_2{\mathrm{\text{O}}}_3$ and ${\mathrm{\text{Fe}}}_3{\mathrm{\text{O}}}_4$ to be the nanoparticles suspended in the blood’s basic fluid for our model. Targeted drug delivery is one of the most proficient ways to diagnose and treat cancer. This is because attractive nanoparticles can be used as beneficial agents in the occurrence of both heat and an angled magnetic field. In addition, several form aspects have been taken into account. By making sure that the self-similarity transformations are accurate, the fundamental Partial Differential Equations (PDEs) are converted into Ordinary Differential Equations (ODEs). The Runge–Kutta fourth-order and firing approach are used to solve the ODEs. For the situations of cylinder and plate, homotopy perturbation method (HPM) and numerical method (NM) solutions on behalf of the nonlinear structure are obtained to compare one another. In this model, we compared the shapes of the sphere, the cylinder, the blade, the platelet and the lamina, which are all graphically represented. Additionally, the results are compared to those that have already been published and are found to be in great agreement. The performance of biological applications, particularly Radio-Frequency Identification (RFA), cancer therapy, MRI, tumor therapy and malaria disease, is improved by this kind of theoretical research.

This paper examines the heat transfer characteristics of magnetohydrodynamics (MHD), suction, and Marangoni convection under the stretching/shrinking Ag–Cu hybrid nanofluid surface flow. First, the governing partial differential equations (PDEs) were transformed into ordinary differential equations (ODEs), and the numerical result was obtained using the boundary value problem solver (bvp4c) in MATLAB. The development of the Nusselt number, the velocity profile and the temperature profile was plotted, discussed and inspected. Next, this paper undergoes stability analysis and heat transfer rate comparison between water, nanofluid and hybrid nanofluid. The dual solutions were observed, and the upper branch solution is determined to be stable. Compared to water, the heat transfer rates of Ag–Cu hybrid nanofluid and Cu nanofluid were accelerated by 2.84% and 2.75%, respectively.

This paper developed the dynamics of opinion network where a node interacts with only one node in each step and these nodes will not exchange their opinions until the difference of their opinions is below a tolerance threshold. Every node is a Gaussian fuzzy set with the center representing an opinion itself and a standard deviation characterizing an uncertainty about the opinion. The fuzzy opinion network with different uncertainties’ levels of nodes was investigated to show how opinions and their uncertainties propagate and evolve for reaching a consensus in the network. The theoretical and numerical analyses were used to assess the conditions where a consensus can be reached in the fuzzy opinion network.

Vehicle platoons were recently proposed to reduce energy consumption and emissions. However, the majority of platooning studies have focused on pure connected automated vehicle (CAV) environments with limited insights into energy consumption and emissions. This paper quantifies fuel consumption and emissions by studying the microscopic movements of CAVs and human driving vehicles (HDVs) in mixed traffic flows. With an extended cellular automaton model, a four-lane mixed traffic flow of CAVs and HDVs is investigated in detail. The results have shown that ad hoc platoon formation can lead to frequent acceleration and lane changing, resulting in more fuel consumption and emission. With a dedicated CAV lane (DCL) strategy, the interference of CAVs and HDVs is greatly reduced, thereby improving the fuel economy and emission reduction. The findings can benefit the organization of vehicle platoons in the persisting mixed traffic flow environment.

The purpose of this research is to reveal the effects of roughness on the hydrodynamics of the fluid around a grooved cylinder by studying the drag and recirculation length. The main objectives are to reach the maximum reduction of the wind load. This work is carried out to investigate the effect of the number of grooves on the drag reduction of flow around a circular cylinder with triangular grooves. This investigation reports numerically on a laminar steady flow over a cylinder with 2, 4, 8, 12 and 16 triangular grooves regularly distributed around the cylinder circumference with wavelength and wave amplitude of 1/10, immersed in two-dimensional unconfined Newtonian fluid over the symmetry regimes. The predicted results showed an excellent agreement with the available data of literature for validation. The obtained results used for our investigations for a Reynolds number up to 40 suggest that the presence of the grooves on the smooth cylinder surface leads to a slight reduction over the drag coefficient and the recirculation length at the same Reynolds number, this trend is more pronounced as the number of grooves increase.

The importance of the blood flow feature on the hemorrhage of the cerebral aneurysm is confirmed by surgeons and scientists. In this paper, the effects of blood hemodynamics on the growth and rupture of the Internal Carotid Intracranial (ICA) are fully investigated. This study tries to demonstrate the blood feature inside the ICA at different time stages. Besides, the effect of coiling on blood characteristics is extensively studied in this research. Computational Fluid dynamic (CFD) is used for the analysis of the blood hemodynamics on the wall shear stress and pressure distribution within the aneurysm. Obtained results indicate that reducing the coiling porosity from 0.89 to 0.79 declines maximum WSS by about 26% and 61% for $\mathrm{\text{HCT}}=0.35$ and 0.45, respectively, at the peak systolic stage. Our findings show that decreasing the porosity (or increasing coiling fraction) would decrease the maximum OSI by more than 55% in high blood viscosity of $\mathrm{\text{HCT}}=0.45$.

This study investigates the aeroacoustics of flow around a square cylinder using an in-house OpenFoam solver with Ffowcs Williams’ Hawking methodology and the $k-\omega$ SST turbulence model. First, the numerical results were validated against experimental data. Then, the effects of a 1mm thick splitter with different lengths, 2.5 ($L/D=0.25$), 5 ($L/D=0.5$), 7.5 ($L/D=0.75$) and 10 ($L/D=1$), were studied as a passive control method. The findings indicate that the splitter suppresses the vortex shedding, a dipole source of aeroacoustic emission, resulting in a reduction of the noise level by up to 7% for $L/D=0.25,9.7\%$ for $L/D=0.5,13.65\%$ for $L/D=0.75$ and 17.5% for $L/D=1$.