Shanghai University

About: Shanghai University is a education organization based out in Shanghai, Shanghai, China. It is known for research contribution in the topics: Microstructure & Catalysis. The organization has 59583 authors who have published 56840 publications receiving 753549 citations. The organization is also known as: Shànghǎi Dàxué.

RNA-Seq profiling of circular RNAs in human colorectal Cancer liver metastasis and the potential biomarkers

Abstract: In this study, the secondary sequencing was used to profile circRNA expression in the tissue samples from three CRC patients with liver metastasis and three matched CRC patients. After verified some candidates in another 40 CRC and CRC-m samples by qRT-PCR, we further demonstrated that circRNA_0001178 and circRNA_0000826 were significantly upregulated in CRC-m tissues, and both of them had the potential for diagnosing liver metastases from colorectal cancer. Finally, the networks of circRNA-miRNA-mRNA base on these two circRNAs were constructed respectively. This study showed that differentially expressed circRNAs were existed between the tissue samples from colorectal cancer patients with and without liver metastasis. And also suggested that circRNA_0001178 and circRNA_0000826 may serve as a potential diagnostic biomarker for liver metastases from colorectal cancer.

A Game Theoretical Incentive Scheme for Relay Selection Services in Mobile Social Networks

Abstract: Rapid developments in mobile services and wireless technologies have prompted users to form mobile social networks (MSNs), where bundles can be delivered via opportunistic peer-to-peer links in a store–carry–forward mode. This mode needs all nodes to work in a cooperative way. However, mobile nodes may be selfish and might not be willing to forward data to others due to the limited resources (e.g., buffer and energy), resulting in degraded system performance. To tackle the aforementioned problem, this paper proposes a novel incentive scheme to stimulate selfish nodes to participate in bundle delivery in MSNs. At first, a virtual currency is introduced to pay for the relay service. Then, a bundle carrier selects a relay node from its friends or other strangers based on its status. Next, a bargain game is employed to model the transaction pricing for relay service. In addition, the simulation results show that the proposal can improve the performance of the existing schemes significantly.

Unsupervised Salient Object Segmentation Based on Kernel Density Estimation and Two-Phase Graph Cut

Abstract: In this paper, we propose an unsupervised salient object segmentation approach based on kernel density estimation (KDE) and two-phase graph cut. A set of KDE models are first constructed based on the pre-segmentation result of the input image, and then for each pixel, a set of likelihoods to fit all KDE models are calculated accordingly. The color saliency and spatial saliency of each KDE model are then evaluated based on its color distinctiveness and spatial distribution, and the pixel-wise saliency map is generated by integrating likelihood measures of pixels and saliency measures of KDE models. In the first phase of salient object segmentation, the saliency map based graph cut is exploited to obtain an initial segmentation result. In the second phase, the segmentation is further refined based on an iterative seed adjustment method, which efficiently utilizes the information of minimum cut generated using the KDE model based graph cut, and exploits a balancing weight update scheme for convergence of segmentation refinement. Experimental results on a dataset containing 1000 test images with ground truths demonstrate the better segmentation performance of our approach.