Interaction Rule between Rare Earths and LowMelting Point Elements in Fe-,Cu-,AI-,Ni-Base Liquid Solutions

Interaction rule between representative RE and Sn, Sb, Pb, Cu, S, P low melting point elements respectively in Fe , Cu , Al , Ni base liquid solutions including totally 34 ternary and quarternary systems was investigated. For each system some thermodynamic properties were obtained, such as the standard free energies of equilibrium reactions, activity interaction coefficients etc ..

A Theoretical Analysis of Interactive Coercing Effects Between Urbanization and Eco-environment

Objectively, a complex interactive coercing relationship exists between urbanization and eco-environment, and the research of this relationship is primarily divided into three schools, i.e., interactive coercion theory, interactive promotion theory and coupling symbiosis theory. Harmonizing the relationship between urbanization and eco-environment is not only an important proposition for the national development plan but also the only way to promote healthy urbanization. Based on an analysis of urbanization process and its relationship with the eco-environment, this article analyzes interactive coercing effects between urbanization and eco-environment from three perspectives of population urbanization, economic urbanization and spatial urbanization, respectively, and analyzes risk effects of the interactive coercion. Further, it shows six basic laws followed by interactive coercion between urbanization and eco-environment, namely, coupling fission law, dynamic hierarchy law, stochastic fluctuation law, non-linear synergetic law, threshold value law and forewarning law, and divides the interactive coercing process into five stages, namely, low-level coordinate, antagonistic, break-in, ameliorative and high-grade coordinate. Based on the geometric derivation, the interactive coercing relationship between urbanization and eco-environment is judged to be non-linear and it can be explained by a double-exponential function formed by the combination of power and exponential functions. Then, the evolutionary types of the interactive coercing relationship are divided into nine ones: rudimentary coordinating, ecology-dominated, synchronal coordinating, urbanization lagging, stepwise break-in, exorbitant urbanization, fragile ecology, rudimentary break-in and unsustainable types. Finally, based on an interactive coercion model, the degree of interactive coercion can be examined, and then, an evolutionary cycle can be divided into four phases, namely rudimentary symbiosis, harmonious development, utmost increasing and spiral type rising. The study results offer a scientific decision-making of healthy urbanization for achieving the goal of eco-environment protection and promoting urbanization.

CONVERGENCE OF A CLASS OF MULTI-AGENT SYSTEMS IN PROBABILISTIC FRAMEWORK

Multi-agent systems arise from diverse fields in natural and artificial systems, and a basic problem is to understand how locally interacting agents lead to collective behaviors （e.g., synchronization） of the overall system. In this paper, we will consider a basic class of multi-agent systems that are described by a simplification of the well-known Vicsek model. This model looks simple, but the rigorous theoretical analysis is quite complicated, because there are strong nonlinear interactions among the agents in the model. In fact, most of the existing results on synchronization need to impose a certain connectivity condition on the global behaviors of the agents＇ trajectories （or on the closed-loop dynamic neighborhood graphs）, which are quite hard to verify in general. In this paper, by introducing a probabilistic framework to this problem, we will provide a complete and rigorous proof for the fact that the overall multi-agent system will synchronize with large probability as long as the number of agents is large enough. The proof is based on a detailed analysis of both the dynamical properties of the nonlinear system evolution and the asymptotic properties of the spectrum of random geometric graphs.