International Journal of Modern Physics C

Grain is the most basic material condition for human survival and development, and the structure of grain import and export trade has seriously affected national grain security. In this paper, we quantitatively analyze the evolution of international grain (maize, wheat, rice) trade patterns from 1987 to 2019 based on a complex network and entropy methods, and provide some suggestions and references for relevant countries. We measure the ranking of countries by applying various indicators from complex networks to quantify the importance of nodes in international trade networks. Then, we analyze the evolution of trade scale and community structure in different regions. Finally, we analyze the weight structure of the whole network through entropy, revealing the evolution characteristics and mechanism of the system more comprehensively. The results first show that the international grains trade network (IGTN) satisfies the scale-free properties and that global trade volumes are increasing year by year. The distribution of trade volumes in the IGTN follows the 80/20 rule, with less than 20$\%$ of countries accounting for more than 80$\%$ of global trade volumes. Second, countries in the Asian region have gradually increased their position in the grain trade network, while the position of countries in North and South America has declined. Third, the heterogeneity of the topology and weight structure of the international grain trade network is weakened, and the status of hub countries in the IGTN is reduced. The importance gap of nodal connections is narrowing, showing the trend of multilateralization of global trade. Fourth, the world grain export market is highly concentrated. The USA, Canada, Brazil, Argentina and Russia are the major exporters of grain.

Chimera states have drawn great attention during the last several years. Multi-clustered chimera states with several coherent domains are one important type of chimera dynamics due to their relations with pattern formation. In this work, we study a ring of nonlocally coupled Brusselators. We find that the multi-stability of multi-clustered chimera states prevails in the model and that the phenomenon is insensitive to the coupling radius. The mechanisms behind the multi-stability of multi-clustered chimera states are explored. We find that there are two types of multi-clustered chimera states, one occurring at the coupling radius close to 0.5 and the other occurring at the coupling radius away from 0.5. The multi-stability of the former one originates from the periodic two-cluster dynamics in globally coupled Brusselators. The multi-stability of the latter one may be explained by linear growth rates of the perturbation, which are related but insensitive to different wave numbers to homogeneous states.

We investigate the electronic structure and the optical characterizations of iron incorporating titanium dioxide by ab initio method by employing the density functional theory. We show that Fe atoms can be incorporated into TiO₂ by replacing Ti atoms in the crystal structure of ${\mathrm{\text{Fe}}}_x{\mathrm{\text{Ti}}}_{1-x}{\mathrm{\text{O}}}_2$ according to the ratio $X=0.00$, 0.25, 0.50, 0.75 and 1.00. The partial density of state and the energy band structure of the optimized structure have been calculated. Adding Fe atoms to the TiO₂ causes shrinkage of the bands in the band structure that leads to a decrease in the energy gap of the pure titanium dioxide crystal structure. The results of the optical properties showed that the titanium dioxide has no absorption in the range of the visible light and detect only in the ultraviolet light (UV). The optical constant absorption coefficient, reflectivity and real and imaginary parts of the dielectric constant have been calculated. It exhibits that the properties of pure TiO₂ will change by adding the Fe atoms to the structure, which leads to a significant enhancement in the optical characteristics.

From the years 2001 to 2017, per capita nominal and real (adjusted to inflation) GDP at purchasing power parity (PCGDP-PPP) distributions for cities and regions are fitted to various functions. For most years and regions, real PCGDP-PPP data are very well adjusted to the one-parameter Boltzmann–Gibbs distribution (BGD), in accordance with the exponential behavior predicted by the simple econophysics analogy between conserved money in economic trade and energy in elastic collisions in gases. Overall, fittings are better for large regions in recent years, which may reflect an increasing economic globalization in time. Cities, small regions and large regions values are well fitted by stretched exponential distributions.

In this research, the rotation of a solid particle in a vortex flow is investigated computationally. The bvp4c MATLAB scheme is employed for mathematical modeling and physical analysis. After solving the governing equations, the influences of some physical parameters like initial values of radius, radial velocity and angular velocity as well as the ratio of drag force to inertia force on the velocity and displacement characteristics of the particle will be analyzed. The findings indicate that increasing $r_0$ and ${\omega }_0$ causes an increase in radial velocity, but increasing $u_0$ and ${\alpha }^2$ have conversed treatments. Also, the angular velocity enhances by increasing the ratio of drag-to-inertia forces.

In the recent decades, the main reason for the high death rate is related to cardiovascular disease and stroke. In this paper, numerical studies have been done to investigate the hemodynamic effects on the rupture of middle cerebral artery (MCA) in different working conditions. In this work, the effects of the blood viscosity and velocity on the pressure distribution and average wall shear stress (AWSS) are fully investigated. Also, the flow pattern inside the aneurysm is investigated to obtain the high-risk regions for the rupture of the aneurysm. Our findings show that the wall shear stress increases with increasing the blood flow velocity. Meanwhile, the risk of aneurysm rupture is considerably increased when the AWSS increases more than 0.6. In fact, the blood flow with high viscosity expands the high-risk region on the wall of the aneurysm. Blood flow indicates that the angle of the incoming bloodstream is substantially effective in the high-risk region on the aneurysm wall. The augmentation of the blood velocity and vortices considerably increases the risk of hemorrhage of the aneurysm.

We use the logistic equation to model the dynamics of the GDP and the trade of the six countries with the highest GDP in the world, namely, USA, China, Japan, Germany, UK and India. From the modeling of the economic data, which are made available by the World Bank, we predict the maximum values of the growth of GDP and trade, as well as the duration over which exponential growth can be sustained. We set up the correlated growth of GDP and trade as the phase solutions of an autonomous second-order dynamical system. GDP and trade are related to each other by a power law, whose exponent seems to differentiate the six national economies into two types. Under conducive conditions for economic growth, our conclusions have general validity.

The solutions to many problems on complex networks depend on the calculation of the similarity between nodes. The existing methods face the problems of the lack of hierarchical information richness or large computational requirements. In order to flexibly analyze the similarity of nodes on an optional multi-order scale as needed, we propose a novel method for calculating the similarity based on the relative entropy of $k$-order edge capacity in this paper. The distribution of edges affects the network heterogeneity, information propagation, node centrality and so on. Entropy of $k$-order edge capacity can represent the edge distribution feature in the range of $k$-order of node. It increases as $k$ increases and converges at the eccentricity of the node. Relative entropy of $k$-order edge capacity can be used to compare the similarity of edge distribution between nodes within $k$-order. As order $k$ increases, upper bound of the relative entropy possibly increases. Relative entropy gets the maximum when nodes compared with isolated nodes. By quantifying the effect difference of the most similar nodes on the network structure and information propagation, we compared relative entropy of $k$-order edge capacity with some major similarity methods in the experiments, combined with visual analysis. The results show the rationality and effectiveness of the proposed method.

Urban road traffic network is becoming increasingly complex. The increasing travel demand has exceeded facility supply of transportation system. Thus, a scientific way of transportation can solve the problem of traffic congestion. If some central intersections are congested, the road network could easily lose its travel efficiency and further lead to cascading failure. In this regard, from the viewpoint of complex networks, this paper provides a cascading failure mitigation strategy for the urban road traffic network. A load redistribution strategy is represented which can redistribute congestion load reasonably. Random and intentional failures are simulated with MATLAB on Barabási and Albert (BA) scale-free network. The indices related to complex network of different methods are compared on BA network and part of the real road network in Baoding City. The load redistribution strategy in this paper is implemented combined with user equilibrium assignment, then the travel time related to urban road network is compared with another method on the Sioux Falls network. The simulation results suggest that when the capacity parameter reaches the threshold, further increase has little effect on the mitigation time. Comparisons of other mitigation approaches verify the effectiveness of our approach in lessening cascading failure caused by traffic congestion. The increase in total network travel time and additional delay by reason of load redistribution is acceptable.

The polymer-bonded explosives (PBXs) contain randomly distributed particles with irregular shapes, high volume fraction (greater than 90%) and gradation feature of size. The precise mesostructure modeling is essential to predict the mechanical properties of PBXs. This study proposes a Voronoi-based mesostructure modeling method of PBXs by considering the real characteristics of PBXs, which can meet both the requirements of high volume fraction and specified size gradation of explosive particles. The key point of the method is to place the particles generated by Monte Carlo method into the representative volume element of PBXs by proposing an improved random walking algorithm (RWA). In the improved RWA, a subregion-independent particle delivery criterion is introduced to enhance the placement efficiency, and an overlapping judgment criterion by tolerating slight overlaps between particles is applied to make the size of placed particles match the grading relationship better. Numerical examples have been provided to verify the correctness and efficiency of the proposed mesostructure modeling method.

The growth of technology and social media websites has increased the potential to online explore different products and places around the globe. While online websites are primarily responsible for the generation of large amounts of data, this big data may be beneficial to other users provided the proper decision pattern can be analyzed. This work is focusing on the big data from social media to determine the travel destination preferences for Indian tourists. The analysis of online tourism reviews is beneficial to both tourists and businesses in tourist countries. Tourists can analyze all the required aspects prior to traveling and businesses in the destination country can enhance their products. The study aims to analyze the online tourist reviews using supervised machine learning methods (decision tree, k-nearest neighbor, back propagation neural networks and support vector machine) and ensemble learning in order to ascertain the travel preferences of Indian tourists visiting other countries. For the research experiments, significant travel data histories of tourists for the five destination places (Dubai, Indonesia, Malaysia, Thailand and Singapore) are extracted from TripAdvisor. TripAdvisor is a worldwide popular tourism website that provides access to consumers to share their travel experiences. From the selected five destination places, the preferences of Indian tourists are analyzed for the factors of travel & destination comfort, hotel facilities, food quality and attractions of the place. The analysis results of the proposed recommendation system indicate the determination of precise suggestions for Indian tourists traveling to other countries.

The traffic in the weaving region is subject to lane-changing turbulence, which results in a significant impact on traffic safety, reduces traffic efficiency, and creates traffic bottlenecks. To mitigate the negative effect of the weaving, vehicles are distributed in each segment located inside and upstream of the weaving region by a lane-changing advisory using Connected Autonomous Vehicle (CAV) technology, called segment-base lane-changing control (SLDC), and a heuristic optimization algorithm is applied to obtain the proportion of CAVs to be assigned to each segment. Further, to decrease volume variation on the mainline, the ramp metering (RM) control strategy is coordinated and applied to ensure the lane-changing process in the weaving region. Conditions of different traffic demands are analyzed using the cellular automata traffic simulation based on a typical one-sided ramp motorway weaving region. Results indicated that the proposed CAV distribution algorithm and SLDC-RM coordination control strategy could improve traffic efficiency and reduce traffic conflicts. The coordination control is better than SLDC when the occupancy of the weaving region reaches 25 veh/km/ln, also the effects with different proportions of connected vehicles are discussed.

The electronic, mechanical and thermodynamic properties of layered ThB₂C are investigated using the first-principles calculations with generalized gradient and local density approximations. The equilibrium geometry and elastic stiffness constants of ThB₂C are studied, and various elastic moduli, Poisson’s ratios and velocities are estimated from the elastic stiffness constants. ThB₂C exhibits brittle characteristics. The phonon dispersion relationship verifies the thermodynamic stability of ThB₂C. Considering the effect of phonon vibration on the thermodynamic properties of ThB₂C, the variation of Gibbs free energy, bulk modulus and heat capacity at constant pressure with temperature are calculated using quasi-harmonic approximation in the temperature range of $0-1000$K.

Nodes usually cooperate to form groups and survive or fail in real-world systems. Researchers typically consider the interdependence between node groups in studying the interdependent network. This paper studies the robustness of interdependent hypergraph networks under different attack strategies. According to the characteristics of the network model, we propose a series of target attack strategies and compare the destructive effect of these strategies on the network. Second, we analyze the impact of the random edge removal strategy on the robustness of hypergraph networks under different edge removal ratios. Finally, we propose four target-node edge removal strategies and compare their destructive effects on the network at the same edge removal ratios. Simulation results show that target attack and edge removal strategies can appreciably reduce the robustness of interdependent hypergraph networks and accelerate the networks’ collapse.