Influence Robustness of Nodes in Multiplex Networks against Attacks

Recent advances have focused mainly on the resilience of the monoplex network in attacks targeting random nodes or links, as well as the robustness of the network against cascading attacks. However, very little research has been done to investigate the robustness of nodes in multiplex networks against targeted attacks. In this paper, we first propose a new measure, MultiCoreRank, to calculate the global influence of nodes in a multiplex network. The measure models the influence propagation on the core lattice of a multiplex network after the core decomposition. Then, to study how the structural features can affect the influence robustness of nodes, we compare the dynamics of node influence on three types of multiplex networks: assortative, neutral, and disassortative, where the assortativity is measured by the correlation coefficient of the degrees of nodes across different layers. We found that assortative networks have higher resilience against attack than neutral and disassortative networks. The structure of disassortative networks tends to break down quicker under attack

Aerodynamic simulation of wind turbine blade airfoil with different turbulence models

The different turbulence models have significant impacts on the aerodynamic performance of wind turbine blade airfoil. A kind of wind turbine blade airfoil was applied as the research object, in order to analyze the impacts of three different turbulence models which are S-A, k-εRNG, k-ωSST on the aerodynamic performance of wind turbine airfoil under different attack angles. By comparing the aerodynamic simulation results with the theoretical values of the lift coefficients, drag coefficients and the ratio of lift coefficient to drag coefficient for the forecast of best angle of attack, the effects of these three turbulence models on the blade airfoil aerodynamic performance were estimated in detail. The simulation of lift coefficient of wind turbine blade airfoil was verified with the flow field simulation of blade airfoil. A combined turbulence model, using different turbulence model for different angle of attack, was put forward. The simulation results demonstrate that, for the selected blade airfoil, using S-A turbulence model before the best attack angle and k-εRNG turbulence model after the best attack angle respectively, can make the simulation of blade airfoil aerodynamic performance much more accurate than the aerodynamic performance simulation using one single turbulence model, with the acceptable iterative time and the acceptable ratio of lift coefficient to drag coefficient. Therefore, the combined turbulence model can overcome the shortcomings when using only a traditional single turbulence model to simulate the aerodynamic performance of wind turbine blade airfoil, which will have a development and application value in the future

The aeroelastic analysis of two different wind turbine blades

The aeroelasticity of the wind turbine blade has been emphasized by the related fields as the size of blade increased dramatically. The eigenvalue approach and the time domain method are applied to analyze the aeroelastic responses of wind turbine blade to determine the flutter region respectively. In order to clarify the difference of the flutter analysis for different blade, two different airfoils are used. The flutter region will be obtained directly by judging the sign of the real part of the eigenvalue of the blade system using the eigenvalue approach. Then the time domain analysis of flutter of wind turbine blade will be carried out through the use of the four-order Runge-Kutta numerical method, so the flutter region will be acquired in another way. The time domain analysis can give the changing tread of the aeroelastic responses in great detail than that of the eigenvalue method. For the two different airfoils, the flutter region given by the eigenvalue approach coincides with that of the time domain analysis method accurately. There are two critical tip speed ratios for the two airfoils, the lower tip speed ratio and the higher tip speed ratio. The flap displacement of these two different airfoils will change from convergence to divergence, and change from divergence to convergence. But the extent of flutter differs with the different blade airfoil. The flutter of airfoil NACA63-418 diverges much more dramatically than that of the airfoil FX77-W-153. So the latter is better for the wind turbine blade. The eigenvalue approach combined with the time domain method can be applied to choose the blade airfoil and to determine the flutter region in order to avoid the flutter of wind turbine blade

The aeroelastic analysis of two different wind turbine blades

The aeroelasticity of the wind turbine blade has been emphasized by the related fields as the size of blade increased dramatically. The eigenvalue approach and the time domain method are applied to analyze the aeroelastic responses of wind turbine blade to determine the flutter region respectively. In order to clarify the difference of the flutter analysis for different blade, two different airfoils are used. The flutter region will be obtained directly by judging the sign of the real part of the eigenvalue of the blade system using the eigenvalue approach. Then the time domain analysis of flutter of wind turbine blade will be carried out through the use of the four-order Runge-Kutta numerical method, so the flutter region will be acquired in another way. The time domain analysis can give the changing tread of the aeroelastic responses in great detail than that of the eigenvalue method. For the two different airfoils, the flutter region given by the eigenvalue approach coincides with that of the time domain analysis method accurately. There are two critical tip speed ratios for the two airfoils, the lower tip speed ratio and the higher tip speed ratio. The flap displacement of these two different airfoils will change from convergence to divergence, and change from divergence to convergence. But the extent of flutter differs with the different blade airfoil. The flutter of airfoil NACA63-418 diverges much more dramatically than that of the airfoil FX77-W-153. So the latter is better for the wind turbine blade. The eigenvalue approach combined with the time domain method can be applied to choose the blade airfoil and to determine the flutter region in order to avoid the flutter of wind turbine blade

Chiral Phonons in Chiral Materials

The concept of chirality makes ubiquitous appearance in nature. Particularly, both a structure and its collective excitations may acquire well defined chiralities. In this work, we reveal an intrinsic connection between the chiralities of a crystal structure and its phonon excitations. We show that the phonon chirality and its propagation direction are strongly coupled with the lattice chirality, which will be reversed when a chiral lattice is switched to its enantiomorph. In addition, distinct from achiral lattices, propagating chiral phonons exist for chiral crystals also on the principal axis through the $\Gamma$ point, which strengthens its relevance to various physical processes. We demonstrate our theory with a 1D helix-chain model and with a concrete and important 3D material, the $\alpha$-quartz. We predict a chirality diode effect in these systems, namely, at certain frequency window, a chiral signal can only pass the system in one way but not the other, specified by the system chirality. Experimental setups to test our theory are proposed. Our work discovers fundamental physics of chirality coupling between different levels of a system, and the predicted effects will provide a new way to control thermal transport and design information devices.Comment: 5 pages, 5 figure

NMI inhibits cancer stem cell traits by downregulating hTERT in breast cancer.

N-myc and STAT interactor (NMI) has been proved to bind to different transcription factors to regulate a variety of signaling mechanisms including DNA damage, cell cycle and epithelial-mesenchymal transition. However, the role of NMI in the regulation of cancer stem cells (CSCs) remains poorly understood. In this study, we investigated the regulation of NMI on CSCs traits in breast cancer and uncovered the underlying molecular mechanisms. We found that NMI was lowly expressed in breast cancer stem cells (BCSCs)-enriched populations. Knockdown of NMI promoted CSCs traits while its overexpression inhibited CSCs traits, including the expression of CSC-related markers, the number of CD44+CD24- cell populations and the ability of mammospheres formation. We also found that NMI-mediated regulation of BCSCs traits was at least partially realized through the modulation of hTERT signaling. NMI knockdown upregulated hTERT expression while its overexpression downregulated hTERT in breast cancer cells, and the changes in CSCs traits and cell invasion ability mediated by NMI were rescued by hTERT. The in vivo study also validated that NMI knockdown promoted breast cancer growth by upregulating hTERT signaling in a mouse model. Moreover, further analyses for the clinical samples demonstrated that NMI expression was negatively correlated with hTERT expression and the low NMI/high hTERT expression was associated with the worse status of clinical TNM stages in breast cancer patients. Furthermore, we demonstrated that the interaction of YY1 protein with NMI and its involvement in NMI-mediated transcriptional regulation of hTERT in breast cancer cells. Collectively, our results provide new insights into understanding the regulatory mechanism of CSCs and suggest that the NMI-YY1-hTERT signaling axis may be a potential therapeutic target for breast cancers