Effect of non-vacuum thermal annealing on high indium content InGaN films deposited by pulsed laser deposition

InGaN films with 33% and 60% indium contents were deposited by pulsed laser deposition (PLD) at a low growth temperature of 300 °C. The films were then annealed at 500-800 °C in the non-vacuum furnace for 15 min with an addition of N(2) atmosphere. X-ray diffraction results indicate that the indium contents in these two films were raised to 41% and 63%, respectively, after annealing in furnace. In(2)O(3) phase was formed on InGaN surface during the annealing process, which can be clearly observed by the measurements of auger electron spectroscopy, transmission electron microscopy and x-ray photoelectron spectroscopy. Due to the obstruction of indium out-diffusion by forming In(2)O(3) on surface, it leads to the efficient increment in indium content of InGaN layer. In addition, the surface roughness was greatly improved by removing In(2)O(3) with the etching treatment in HCl solution. Micro-photoluminescence measurement was performed to analyze the emission property of InGaN layer. For the as-grown InGaN with 33% indium content, the emission wavelength was gradually shifted from 552 to 618 nm with increasing the annealing temperature to 800 °C. It reveals the InGaN films have high potential in optoelectronic applications

Fast Deep Matting for Portrait Animation on Mobile Phone

Image matting plays an important role in image and video editing. However, the formulation of image matting is inherently ill-posed. Traditional methods usually employ interaction to deal with the image matting problem with trimaps and strokes, and cannot run on the mobile phone in real-time. In this paper, we propose a real-time automatic deep matting approach for mobile devices. By leveraging the densely connected blocks and the dilated convolution, a light full convolutional network is designed to predict a coarse binary mask for portrait images. And a feathering block, which is edge-preserving and matting adaptive, is further developed to learn the guided filter and transform the binary mask into alpha matte. Finally, an automatic portrait animation system based on fast deep matting is built on mobile devices, which does not need any interaction and can realize real-time matting with 15 fps. The experiments show that the proposed approach achieves comparable results with the state-of-the-art matting solvers.Comment: ACM Multimedia Conference (MM) 2017 camera-read

PTA and stenting in supra-aortic arch arteries

published_or_final_versio

Access to recreational physical activities by car and bus : an assessment of socio-spatial inequalities in mainland Scotland

Obesity and other chronic conditions linked with low levels of physical activity (PA) are associated with deprivation. One reason for this could be that it is more difficult for low-income groups to access recreational PA facilities such as swimming pools and sports centres than high-income groups. In this paper, we explore the distribution of access to PA facilities by car and bus across mainland Scotland by income deprivation at datazone level. GIS car and bus networks were created to determine the number of PA facilities accessible within travel times of 10, 20 and 30 minutes. Multilevel negative binomial regression models were then used to investigate the distribution of the number of accessible facilities, adjusting for datazone population size and local authority. Access to PA facilities by car was significantly (p<0.01) higher for the most affluent quintile of area-based income deprivation than for most other quintiles in small towns and all other quintiles in rural areas. Accessibility by bus was significantly lower for the most affluent quintile than for other quintiles in urban areas and small towns, but not in rural areas. Overall, we found that the most disadvantaged groups were those without access to a car and living in the most affluent areas or in rural areas

Ellagic acid, a phenolic compound, exerts anti-angiogenesis effects via VEGFR-2 signaling pathway in breast cancer

Anti-angiogenesis targeting VEGFR-2 has been considered as an important strategy for cancer therapy. Ellagic acid is a naturally existing polyphenol widely found in fruits and vegetables. It was reported that ellagic acid interfered with some angiogenesis-dependent pathologies. Yet the mechanisms involved were not fully understood. Thus, we analyzed its anti-angiogenesis effects and mechanisms on human breast cancer utilizing in-vitro and in-vivo methodologies. The in-silico analysis was also carried out to further analyze the structure-based interaction between ellagic acid and VEGFR-2. We found that ellagic acid significantly inhibited a series of VEGF-induced angiogenesis processes including proliferation, migration, and tube formation of endothelial cells. Besides, it directly inhibited VEGFR-2 tyrosine kinase activity and its downstream signaling pathways including MAPK and PI3K/Akt in endothelial cells. Ellagic acid also obviously inhibited neo-vessel formation in chick chorioallantoic membrane and sprouts formation of chicken aorta. Breast cancer xenografts study also revealed that ellagic acid significantly inhibited MDA-MB-231 cancer growth and P-VEGFR2 expression. Molecular docking simulation indicated that ellagic acid could form hydrogen bonds and aromatic interactions within the ATP-binding region of the VEGFR-2 kinase unit. Taken together, ellagic acid could exert anti-angiogenesis effects via VEGFR-2 signaling pathway in breast cancer. © 2012 The Author(s).published_or_final_versio

Adaptive Evolution of the Myo6 Gene in Old World Fruit Bats (Family: Pteropodidae)

PMCID: PMC3631194This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Continuous variable quantum key distribution with two-mode squeezed states

Quantum key distribution (QKD) enables two remote parties to grow a shared key which they can use for unconditionally secure communication [1]. The applicable distance of a QKD protocol depends on the loss and the excess noise of the connecting quantum channel [2-10]. Several QKD schemes based on coherent states and continuous variable (CV) measurements are resilient to high loss in the channel, but strongly affected by small amounts of channel excess noise [2-6]. Here we propose and experimentally address a CV QKD protocol which uses fragile squeezed states combined with a large coherent modulation to greatly enhance the robustness to channel noise. As a proof of principle we experimentally demonstrate that the resulting QKD protocol can tolerate more noise than the benchmark set by the ideal CV coherent state protocol. Our scheme represents a very promising avenue for extending the distance for which secure communication is possible.Comment: 8 pages, 5 figure

GN-SCCA: GraphNet based Sparse Canonical Correlation Analysis for Brain Imaging Genetics

Identifying associations between genetic variants and neuroimaging quantitative traits (QTs) is a popular research topic in brain imaging genetics. Sparse canonical correlation analysis (SCCA) has been widely used to reveal complex multi-SNP-multi-QT associations. Several SCCA methods explicitly incorporate prior knowledge into the model and intend to uncover the hidden structure informed by the prior knowledge. We propose a novel structured SCCA method using Graph constrained Elastic-Net (GraphNet) regularizer to not only discover important associations, but also induce smoothness between coefficients that are adjacent in the graph. In addition, the proposed method incorporates the covariance structure information usually ignored by most SCCA methods. Experiments on simulated and real imaging genetic data show that, the proposed method not only outperforms a widely used SCCA method but also yields an easy-to-interpret biological findings

Transgenic plants of Petunia hybrida harboring the CYP2E1 gene efficiently remove benzene and toluene pollutants and improve resistance to formaldehyde

The CYP2E1 protein belongs to the P450 enzymes family and plays an important role in the metabolism of small molecular and organic pollutants. In this study we generated CYP2E1 transgenic plants of Petunia using Agrobacterium rhizogenes K599. PCR analysis confirmed that the regenerated plants contained the CYP2E1 transgene and the rolB gene of the Ri plasmid. Southern blotting revealed the presence of multiple copies of CYP2E1 in the genome of transgenic plants. Fluorescent quantitative PCR revealed exogenous CYP2E1 gene expression in CYP2E1 transgenic plants at various levels, whereas no like expression was detected in either GUS transgenic plants or wild-types. The absorption of benzene and toluene by transgenic plants was analyzed through quantitative gas chromatography. Transgenic plants with high CYP2E1 expression showed a significant increase in absorption capacity of environmental benzene and toluene, compared to control GUS transgenic and wild type plants. Furthermore, these plants also presented obvious improved resistance to formaldehyde. This study, besides being the first to reveal that the CYP2E1 gene enhances plant resistance to formaldehyde, also furnishes a new method for reducing pollutants, such as benzene, toluene and formaldehyde, by using transgenic flowering horticultural plants