Learning a Mixture of Deep Networks for Single Image Super-Resolution

Single image super-resolution (SR) is an ill-posed problem which aims to recover high-resolution (HR) images from their low-resolution (LR) observations. The crux of this problem lies in learning the complex mapping between low-resolution patches and the corresponding high-resolution patches. Prior arts have used either a mixture of simple regression models or a single non-linear neural network for this propose. This paper proposes the method of learning a mixture of SR inference modules in a unified framework to tackle this problem. Specifically, a number of SR inference modules specialized in different image local patterns are first independently applied on the LR image to obtain various HR estimates, and the resultant HR estimates are adaptively aggregated to form the final HR image. By selecting neural networks as the SR inference module, the whole procedure can be incorporated into a unified network and be optimized jointly. Extensive experiments are conducted to investigate the relation between restoration performance and different network architectures. Compared with other current image SR approaches, our proposed method achieves state-of-the-arts restoration results on a wide range of images consistently while allowing more flexible design choices. The source codes are available in http://www.ifp.illinois.edu/~dingliu2/accv2016

Spin filtering implemented through Rashba and weak magnetic modulations

We present two theoretical schemes for spin filters in one-dimensional semiconductor quantum wires with spatially modulated Rashba spin-orbit coupling (SOC) as well as weak magnetic potential. For case I, the SOC is periodic and the weak magnetic potential is applied uniformly along the wire. Full spin polarizations with opposite signs are obtained within two separated energy intervals. For case II, the weak magnetic potential is periodic while the SOC is uniform. An ideal negative/positive switching effect for spin polarization is realized by tuning the strength of SOC. The roles of SOC, magnetic potential, and their coupling on the spin filtering are analyzed.Comment: 4 pages, 4 figure

LLAGN and jet-scaling probed with the EVN

Accreting black holes on all mass scales (from stellar to supermassive) appear to follow a nonlinear relation between X-ray luminosity, radio luminosity and BH mass, indicating that similar physical processes drive the central engines in X-ray binaries and active galactic nuclei (AGN). However, in recent years an increasing number of BH systems have been identified that do not fit into this scheme. These outliers may be the key to understand how BH systems are powered by accretion. Here we present results from EVN observations of a sample of low-luminosity AGN (LLAGN) with known mass that have unusually high radio powers when compared with their X-ray luminosity.Comment: Presented at the 11th EVN Symposium, Bordeaux, France, 2012 October 9-12. Six pages, including a figure and a table. Final, accepted versio

Methylation of CpG island is not a ubiquitous mechanism for the loss of oestrogen receptor in breast cancer cells.

Methylation has been shown to play an important role in the down-regulation of oestrogen receptors (ER) in breast cancer cells. One critical question that remains unclear is whether methylation can account for the loss of ER expression in cells derived from an ER-positive cell line. This laboratory has established an in vitro cell system using long-term growth of human ER-positive breast cancer cell line T47D in oestrogen-free medium. A clonal cell line, T47D:C4:2 (C4:2), has been characterized. Unlike T47D:A18 (A18), which is a T47D line maintained in oestrogen medium, C4:2 has lost the expression of ER and hormone responsiveness. DNA fingerprinting and restriction fragment length polymorphism (RFLP) analysis results confirmed that C4:2 was of the same lineage as A18. These cell lines provide an invaluable system to study the mechanism of ER expression and regulatory pathways leading to hormone-independent growth. The results here clearly demonstrate that the ER CpG island in C4:2 cells remains unmethylated. The loss of ER in the cell line must be due to mechanisms other than methylation. We also evaluated the ER CpG island in the MDA-MB-231:10A (10A) cell line, which is a clone from the MDA-MB-231 line obtained from ATCC and the DNA from the MDA-MB-231 cell line used in the original report. Unlike the cell line from the report, which showed a full methylation pattern in the island, the 10A line only showed a partial methylation pattern in the CpG island. Possible mechanisms pertaining to the heterogeneous methylation pattern of the ER CpG island in the breast cancer cells are discussed