In this letter,we first put forward a new basic problem to the famous vector perturbation(VP) precoding that whether the extended constellation of VP could transmit more information bits.Then,we propose an opportunist...In this letter,we first put forward a new basic problem to the famous vector perturbation(VP) precoding that whether the extended constellation of VP could transmit more information bits.Then,we propose an opportunistic vector perturbation(OVP) precoding with superposition signalling scheme,which is aimed at getting the performance of VP closer to capacity limit.The main idea is using subsequent recoverable data symbol vector to perturb currently transmitting data symbol vector opportunistically.Analysis and simulation results show that the proposed OVP can transmit more valid information bits than conventional VP at the same transmit power,modulation order and number of antennas.展开更多
Long noncoding RNAs(lncRNAs)play important roles in human diseases including vascular disease.Given the large number of lncRNAs,however,whether the majority of them are associated with vascular disease remains unknown...Long noncoding RNAs(lncRNAs)play important roles in human diseases including vascular disease.Given the large number of lncRNAs,however,whether the majority of them are associated with vascular disease remains unknown.For this purpose,here we present a genomic location based bioinformatics method to predict the lncRNAs associated with vascular disease.We applied the presented method to globally screen the human lncRNAs potentially involved in vascular disease.As a result,we predicted 3043 putative vascular disease associated lncRNAs.To test the accuracy of the method,we selected 10 lncRNAs predicted to be implicated in proliferation and migration of vascular smooth muscle cells(VSMCs)for further experimental validation.The results confirmed that eight of the 10 lncRNAs(80%)are validated.This result suggests that the presented method has a reliable prediction performance.Finally,the presented bioinformatics method and the predicted vascular disease associated lncRNAs together may provide helps for not only better understanding of the roles of lncRNAs in vascular disease but also the identification of novel molecules for the diagnosis and therapy of vascular disease.展开更多
基金supported in part by Key Project of National Natural Science Foundation of China(61231008)National Natural Science Foundation of China (61301168,61271176)+1 种基金Natural Science Basic Research Plan in Shaanxi Province of China (2013JQ8001)Fundamental Research Funds for the Central Universities and the 111 Project(B08038)
文摘In this letter,we first put forward a new basic problem to the famous vector perturbation(VP) precoding that whether the extended constellation of VP could transmit more information bits.Then,we propose an opportunistic vector perturbation(OVP) precoding with superposition signalling scheme,which is aimed at getting the performance of VP closer to capacity limit.The main idea is using subsequent recoverable data symbol vector to perturb currently transmitting data symbol vector opportunistically.Analysis and simulation results show that the proposed OVP can transmit more valid information bits than conventional VP at the same transmit power,modulation order and number of antennas.
基金supported by the National Natural Science Foundation of China(91339106)National High Technology Research and Development Program of China(2014AA021102)
文摘Long noncoding RNAs(lncRNAs)play important roles in human diseases including vascular disease.Given the large number of lncRNAs,however,whether the majority of them are associated with vascular disease remains unknown.For this purpose,here we present a genomic location based bioinformatics method to predict the lncRNAs associated with vascular disease.We applied the presented method to globally screen the human lncRNAs potentially involved in vascular disease.As a result,we predicted 3043 putative vascular disease associated lncRNAs.To test the accuracy of the method,we selected 10 lncRNAs predicted to be implicated in proliferation and migration of vascular smooth muscle cells(VSMCs)for further experimental validation.The results confirmed that eight of the 10 lncRNAs(80%)are validated.This result suggests that the presented method has a reliable prediction performance.Finally,the presented bioinformatics method and the predicted vascular disease associated lncRNAs together may provide helps for not only better understanding of the roles of lncRNAs in vascular disease but also the identification of novel molecules for the diagnosis and therapy of vascular disease.
