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The viscosity of high-temperature metallic melt, which is an important index for evaluating dynamics of liquid melt, is one of the basic physical properties. It not only influences the mold-filling capacity of melting metal in traditional casting techniques, but also exhibits more distinct influence on the fabrication of advanced material, such as metallic glass. According to the variation tendency of viscosity with temperature in alloy melt, the fragility of superheated melt could be obtained, which has proved to correlate with the ability of alloy to form glass. Besides, the viscosity of alloy well above the liquidus temperature also plays a key role in probing into the characteristic of liquid-liquid phase transition, the fragile-to-strong transition phenomenon, how the potential energy landscape evolves during cooling, etc. It has been generally accepted that the viscosity of metallic melt at high temperatures increases with temperature decreasing and could be fitted by an Arrhenius curve in the whole temperature range. However, recently more and more studies show that the viscosity of metallic melt cannot be fitted by only one Arrhenius curve. Instead, there exists at least one specific temperature below which the viscosity data begins to deviate from the Arrhenius curve at high temperature during cooling. These data could be described by another Arrhenius curve. In order to in depth understand this phenomenon, in this paper we summarize the viscosity data of different metallic melts in the literature. On the basis of introducing the method of detecting high-temperature melt viscosity, we discuss comprehensively the changing tendency of viscosity with temperature and the characteristics of abnormal viscosity changes in pure metal, binary and multivariate alloys well above the liquidus temperature. It is found that the abnormal viscosity changes generally occur in alloys that could form the types of intermetallic compounds. The abnormal viscosity change in metallic melt is accompanied with exothermic or endothermic effect, depending on alloy system, and reflects the existence of liquid-liquid transition well above the liquidus temperature. Besides, such an abnormal change of viscosity influences the ability to form metallic glass liquids. Although the abnormal dynamic change of metallic melt hints the existence of complexity of structural change in liquid during cooling, what is the key factor underlying this phenomenon remains a mystery. By combining the advanced experimental techniques such as high-energy X-ray diffraction and neutron scattering with the computer simulation method, this problem may be understood further. Besides, the relation between viscosity abnormity and the phase diagram is another problem that deserves to be noticed in the future.

As an emerging research field, networked control systems have shown the increasing importance and attracted more and more attention in the recent years. The integration of control and communication in networked control systems has made the design and analysis of such systems a great theoretical challenge for conventional control theory. Such an integration also makes the implementation of networked control systems a necessary intermediate step towards the final convergence of control, communication, and computation. We here introduce the basics of networked control systems and then describe the state-of-the-art research in this field. We hope such a brief tutorial can be useful to inspire further development of networked control systems in both theory and potential applications.

Background mRNA translation involves simultaneous movement of multiple ribosomes on the mRNA and is also subject to regulatory mechanisms at different stages. Translation can be described by various codon-based models, including ODE, TASEP, and Petri net models. Although such models have been extensively used, the overlap and differences between these models and the implications of the assumptions of each model has not been systematically elucidated. The selection of the most appropriate modelling framework, and the most appropriate way to develop coarse-grained/fine-grained models in different contexts is not clear. Results We systematically analyze and compare how different modelling methodologies can be used to describe translation. We define various statistically equivalent codon-based simulation algorithms and analyze the importance of the update rule in determining the steady state, an aspect often neglected. Then a novel probabilistic Boolean network (PBN) model is proposed for modelling translation, which enjoys an exact numerical solution. This solution matches those of numerical simulation from other methods and acts as a complementary tool to analytical approximations and simulations. The advantages and limitations of various codon-based models are compared, and illustrated by examples with real biological complexities such as slow codons, premature termination and feedback regulation. Our studies reveal that while different models gives broadly similiar trends in many cases, important differences also arise and can be clearly seen, in the dependence of the translation rate on different parameters. Furthermore, the update rule affects the steady state solution. Conclusions The codon-based models are based on different levels of abstraction. Our analysis suggests that a multiple model approach to understanding translation allows one to ascertain which aspects of the conclusions are robust with respect to the choice of modelling methodology, and when (and why) important differences may arise. This approach also allows for an optimal use of analysis tools, which is especially important when additional complexities or regulatory mechanisms are included. This approach can provide a robust platform for dissecting translation, and results in an improved predictive framework for applications in systems and synthetic biology.