Emergent phases in iron pnictides: Double-Q antiferromagnetism, charge order and enhanced nematic correlations

Electron correlations produce a rich phase diagram in the iron pnictides. Earlier theoretical studies on the correlation effect demonstrated how quantum fluctuations weaken and concurrently suppress a $C_2$-symmetric single-Q antiferromagnetic order and a nematic order. Here we examine the emergent phases near the quantum phase transition. For a $C_4$-symmetric collinear double-Q antiferromagnetic order, we show that it is accompanied by both a charge order and an enhanced nematic susceptibility. Our results provide understanding for several intriguing recent experiments in hole-doped iron arsenides, and bring out common physics that underlies the different magnetic phases of various iron-based superconductors.Comment: 5+6 pages, 2 figures; (v2) issues with cross-referencing between the main text and supplementary material are fixe

Optical transitions between Landau levels: AA-stacked bilayer graphene

The low-frequency optical excitations of AA-stacked bilayer graphene are investigated by the tight-binding model. Two groups of asymmetric LLs lead to two kinds of absorption peaks resulting from only intragroup excitations. Each absorption peak obeys a single selection rule similar to that of monolayer graphene. The excitation channel of each peak is changed as the field strength approaches a critical strength. This alteration of the excitation channel is strongly related to the setting of the Fermi level. The peculiar optical properties can be attributed to the characteristics of the LL wave functions of the two LL groups. A detailed comparison of optical properties between AA-stacked and AB-stacked bilayer graphenes is also offered. The compared results demonstrate that the optical properties are strongly dominated by the stacking symmetry. Furthermore, the presented results may be used to discriminate AABG from MG, which can be hardly done by STM

Global dynamics of an impulsive vector-borne disease model with time delays

In this paper, we investigate a time-delayed vector-borne disease model with impulsive culling of the vector. The basic reproduction number $\mathcal{R}_0$ of our model is first introduced by the theory recently established in [1]. Then the threshold dynamics in terms of $\mathcal{R}_0$ are further developed. In particular, we show that if \mathcal{R}_0 < 1 , then the disease will go extinct; if \mathcal{R}_0 > 1 , then the disease will persist. The main mathematical approach is based on the uniform persistent theory for discrete-time semiflows on some appropriate Banach space. Finally, we carry out simulations to illustrate the analytic results and test the parametric sensitivity on $\mathcal{R}_0$

Diagnostic Proteomics: Serum Proteomic Patterns for the Detection of Early Stage Cancers

The ability to interrogate thousands of proteins found in complex biological samples using proteomic technologies has brought the hope of discovering novel disease-specific biomarkers. While most proteomic technologies used to discover diagnostic biomarkers are quite sophisticated, proteomic pattern analysis has emerged as a simple, yet potentially revolutionary, method for the early diagnosis of diseases. Utilizing this technology, hundreds of clinical samples can be analyzed per day and several preliminary studies suggest proteomic pattern analysis has the potential to be a novel, highly sensitive diagnostic tool for the early detection of cancer