Impurity resonance states in electron-doped high T_c superconductors

Two scenarios, i.e., the anisotropic s-wave pairing (the s-wave scenario) and the d-wave pairing coexisting with antiferromagnetism (the coexisting scenario) have been introduced to understand some of seemingly s-wave like behaviors in electron doped cuprates. We considered the electronic structure in the presence of a nonmagnetic impurity in the coexistence scenario. We found that even if the AF order opens a full gap in quasi-particle excitation spectra, the mid-gap resonant peaks in local density of states (LDoS) around an impurity can still be observed in the presence of a d-wave pairing gap. The features of the impurity states in the coexisting phase are markedly different from the pure AF or pure d-wave pairing phases, showing the unique role of the coexisting AF and d-wave pairing orders. On the other hand, it is known that in the pure s-wave case no mid-gap states can be induced by a nonmagnetic impurity. Therefore we proposed that the response to a nonmagnetic impurity can be used to differentiate the two scenarios.Comment: 5 pages, two-column revtex4, 5 figures, author list correcte

TCF1 and LEF1 Control Treg Competitive Survival and Tfr Development to Prevent Autoimmune Diseases.

CD4+ Foxp3+ T regulatory (Treg) cells are key players in preventing lethal autoimmunity. Tregs undertake differentiation processes and acquire diverse functional properties. However, how Treg's differentiation and functional specification are regulated remains incompletely understood. Here, we report that gradient expression of TCF1 and LEF1 distinguishes Tregs into three distinct subpopulations, particularly highlighting a subset of activated Treg (aTreg) cells. Treg-specific ablation of TCF1 and LEF1 renders the mice susceptible to systemic autoimmunity. TCF1 and LEF1 are dispensable for Treg's suppressive capacity but essential for maintaining a normal aTreg pool and promoting Treg's competitive survival. As a consequence, the development of T follicular regulatory (Tfr) cells, which are a subset of aTreg, is abolished in TCF1/LEF1-conditional knockout mice, leading to unrestrained T follicular helper (Tfh) and germinal center B cell responses. Thus, TCF1 and LEF1 act redundantly to control the maintenance and functional specification of Treg subsets to prevent autoimmunity

Research on the Hydraulic Pump Test System Based on AMESim

A set of hydraulic test system was designed and built to complete the performance test for pumps. Next, the simulation model of the system was built in the hydraulic simulation software AMESim, and the models of tested pump, relief valves and check valves were built by HCD library. According to National Standard JB/T 9714-1999, the necessary test items were simulated and the dynamic responses of the test system were analyzed. Simulation results show that the test system can exactly reflect the performance parameters of tested pump and meet the demand of hydraulic pump performance test. Finally, corresponding test bed was built according to the test system and verified the above simulation results. Experimental results were consistent with simulation results, which proves the feasibility of the test system

Second generation Dirac cones and inversion symmetry breaking induced gaps in graphene/hexagonal boron nitride

Graphene/h-BN has emerged as a model van der Waals heterostructure, and the band structure engineering by the superlattice potential has led to various novel quantum phenomena including the self-similar Hofstadter butterfly states. Although newly generated second generation Dirac cones (SDCs) are believed to be crucial for understanding such intriguing phenomena, so far fundamental knowledge of SDCs in such heterostructure, e.g. locations and dispersion of SDCs, the effect of inversion symmetry breaking on the gap opening, still remains highly debated due to the lack of direct experimental results. Here we report first direct experimental results on the dispersion of SDCs in 0$^\circ$ aligned graphene/h-BN heterostructure using angle-resolved photoemission spectroscopy. Our data reveal unambiguously SDCs at the corners of the superlattice Brillouin zone, and at only one of the two superlattice valleys. Moreover, gaps of $\approx$ 100 meV and $\approx$ 160 meV are observed at the SDCs and the original graphene Dirac cone respectively. Our work highlights the important role of a strong inversion symmetry breaking perturbation potential in the physics of graphene/h-BN, and fills critical knowledge gaps in the band structure engineering of Dirac fermions by a superlattice potential.Comment: Nature Physics 2016, In press, Supplementary Information include

Sensitivity Analysis of Incentive Situations and Personal Attributes to Driving Anger Based on MNL Model: A Naturalistic Experimental Study

Driving anger, called "road rage", has gradually become universal phenomenon nowadays, which has been a concern to traffic management authorities. It is necessary to figure out impacting degree of the influencing factors on driving anger for taking the corresponding intervening measures. Forty drivers were enrolled to conduct naturalistic experiments on a busy route in Wuhan, China, where drivers\u27 anger can be induced by various incentive situations including jaywalking, weaving/cutting in line, traffic congestion and red light with extra paid if completing the experiment ahead of reference time. According to behavioral theory and disaggregation theory, the influencing factors including the incentive situations and personal attributes (i.e. gender, age, temperament) were determined for proposing driving anger prediction model based on MNL (multinomial logit). Then, the sensitivity of each influencing factor on driving anger was analyzed by elasticity theory on the basis of the proposed model. The result indicates that age, temperament and illegal behaviors from surrounding people are decisive influencing factors to driving anger sates with different intensity because their average elasticity values for none anger (neutral), low anger, medium anger, high anger are 1.254, 2.713, 2.914, respectively, which are all bigger than 1. Moreover, the accuracy of the proposed model is 78.30%. The results can provide theoretical support for developing key monitoring or targeted intervention to deal with the decisive influencing factors for traffic management authorities