Advances in clinical application of optical coherence tomography in vitreomacular interface disease

Vitreous macular interface disease mainly includes vitreomacular traction syndrome, idiopathic macular epiretinal membrane and idiopathic macular hole. Optical coherence tomography(OCT)as a new tool that provides high resolution biopsy cross section image non traumatic imaging inspection, has a unique high resolution, no damage characteristics, and hence clinical widely used, vitreous macular interface for clinical disease diagnosis, differential diagnosis and condition monitoring and quantitative evaluation, treatment options, <i>etc</i> provides important information and reference value. Vitreous macular interface disease in OCT image of anatomical morphology characteristics, improve the clinical on disease occurrence and development of knowledge. We reviewed the advances in the application of OCT in vitreomacular interface disease

A minimal two-band model for the superconducting Fe-pnictides

Following the discovery of the Fe-pnictide superconductors, LDA band structure calculations showed that the dominant contributions to the spectral weight near the Fermi energy came from the Fe 3d orbitals. The Fermi surface is characterized by two hole surfaces around the $\Gamma$ point and two electron surfaces around the M point of the 2 Fe/cell Brillouin zone. Here, we describe a 2-band model that reproduces the topology of the LDA Fermi surface and exhibits both ferromagnetic and $q=(\pi,0)$ spin density wave (SDW) fluctuations. We argue that this minimal model contains the essential low energy physics of these materials.Comment: 5 figures, 5 page

A Kohn-Sham Scheme Based Neural Network for Nuclear Systems

A Kohn-Sham scheme based multi-task neural network is elaborated for the supervised learning of nuclear shell evolution. The training set is composed of the single-particle wave functions and occupation probabilities of 320 nuclei, calculated by the Skyrme density functional theory. It is found that the deduced density distributions, momentum distributions, and charge radii are in good agreements with the benchmarking results for the untrained nuclei. In particular, accomplishing shell evolution leads to a remarkable improvement in the extrapolation of nuclear density. After a further charge-radius-based calibration, the network evolves a stronger predictive capability. This opens the possibility to infer correlations among observables by combining experimental data for nuclear complex systems