Xiaoliang Wang

Arc plasmas have promising applications in many fields, and exploring their properties is of interest. This research paper presents detailed pressure-based finite volume simulations of an argon arc. Simulations of the free-burning argon arc show good agreement with experiment. We observe an interesting phenomenon that an argon arc concentrates intensively in a high-frequency alternating longitudinal magnetic field. This is different from existing constricting mechanisms, as here the arc is pinched through continuous dynamic transitions between shrinking and expansion. The underlying mechanism is that via working together with an arc's motion inertia, the applied high-frequency alternating magnetic field is able to effectively play a “plasma trap” role, which leads the arc plasma to be confined to a narrower space. This finding may provide a new approach to constrict arc plasmas.

A big challenge in current biology is to understand the exact self‐organization mechanism underlying complex multi‐physics coupling developmental processes. Using multiscale computations of subcellular gene expressions and cell population dynamics that are based on first principles, it is shown that cell cycles can self‐organize into periodic stripes in the development of E. coli populations from one single cell, relying on the moving graded nutrient concentration profile, which provides directing positional information for cells to keep their cycle phases in place. Resultantly, the statistical cell cycle distribution within the population is observed to collapse to a universal function and shows a scale invariance. Depending on the radial distribution mode of genetic oscillations in cell populations, a transition between gene patterns is achieved. When an inhibitor–inhibitor gene network is subsequently activated by a gene‐oscillatory network, cell populations with zebra stripes can be established, with the positioning precision of cell‐fate‐specific domains influenced by cells’ speed of free motions. Such information may provide important implications for understanding relevant dynamic processes of multicellular systems, such as, biological development.

This article considers a mechanism to explain the emergence and evolution of social cooperation. Selfish individuals tend to benefit themselves, which makes it hard for the maintenance of cooperation between unrelated individuals. We propose and validate that a smart group strategy can effectively facilitate the evolution of cooperation, provided cooperators spatially align whilst cooperating at a new level of alliance. The general evolutionary model presented here shows that a non-kin selection effect is a possible cause for cooperation between unrelated individuals and highlights that non-kin selection may be a hallmark of biological evolution.