Southeast University

About: Southeast University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Computer science & MIMO. The organization has 66363 authors who have published 79434 publications receiving 1170576 citations. The organization is also known as: SEU.

H3K27 acetylation activated-long non-coding RNA CCAT1 affects cell proliferation and migration by regulating SPRY4 and HOXB13 expression in esophageal squamous cell carcinoma.

Abstract: Recently, long non-coding RNAs (lncRNAs) have been shown to have important regulatory roles in human cancer biology. In our study, we found that lncRNA CCAT1, whose expression is significantly increased and is correlated with outcomes in Esophageal Squamous Cell Carcinoma (ESCC). Consecutive experiments confirmed that H3K27-acetylation could activate expression of colon cancer associated transcript-1 (CCAT1). Further experiments revealed that CCAT1 knockdown significantly repressed the proliferation and migration both in vitro and in vivo. RNA-seq analysis revealed that CCAT1 knockdown preferentially affected genes that are linked to cell proliferation, cell migration and cell adhesion. Mechanistic investigations found that CCAT1 could serve as a scaffold for two distinct epigenetic modification complexes (5΄ domain of CCAT1 binding Polycomb Repressive Complex 2 (PRC2) while 3΄ domain of CCAT1 binding SUV39H1) and modulate the histone methylation of promoter of SPRY4 (sprouty RTK signaling antagonist 4) in nucleus. In cytoplasm, CCAT1 regulates HOXB13 as a molecular decoy for miR-7, a microRNA that targets both CCAT1 and HOXB13, thus facilitating cell growth and migration. Together, our data demonstrated the important roles of CCAT1 in ESCC oncogenesis and might serve as targets for ESCC diagnosis and therapy.

Decentralized Multi-Agent System-Based Cooperative Frequency Control for Autonomous Microgrids With Communication Constraints

Abstract: Based on power line carrier communication technology, a decentralized multi-agent system (DMAS)-based frequency control strategy is proposed and investigated in this study on an autonomous microgrid with communication constraints, where each agent can only communicate with its neighboring agents. Using the optimized average consensus algorithm, the global information (i.e., total active power deficiency of the microgrid) can be accurately shared in a decentralized way. Depending on the discovered global information, the cooperative frequency control strategy, which involves primary and secondary frequency control and multi-stage load shedding, is executed to achieve a cooperative frequency recovery. Simulation results indicate that the proposed frequency control approach can guarantee the consensus and coordination of the distributed agents and maintain the frequency stability of islanded microgrids even in emergency conditions.

Spatial- and Frequency-Wideband Effects in Millimeter-Wave Massive MIMO Systems

Abstract: When there are a large number of antennas in massive MIMO systems, the transmitted wideband signal will be sensitive to the physical propagation delay of electromagnetic waves across the large array aperture, which is called the spatial-wideband effect. In this scenario, the transceiver design is different from most of the existing works, which presume that the bandwidth of the transmitted signals is not that wide, ignore the spatial-wideband effect, and only address the frequency selectivity. In this paper, we investigate spatial- and frequency-wideband effects, called dual-wideband effects in massive MIMO systems from the array signal processing point of view. Taking millimeter-wave-band communications as an example, we describe the transmission process to address the dual-wideband effects. By exploiting the channel sparsity in the angle domain and the delay domain, we develop the efficient uplink and downlink channel estimation strategies that require much less amount of training overhead and cause no pilot contamination. Thanks to the array signal processing techniques, the proposed channel estimation is suitable for both TDD and FDD massive MIMO systems. Numerical examples demonstrate that the proposed transmission design for massive MIMO systems can effectively deal with the dual-wideband effects.

Matching large ontologies: A divide-and-conquer approach

Abstract: Ontologies proliferate with the progress of the Semantic Web. Ontology matching is an important way of establishing interoperability between (Semantic) Web applications that use different but related ontologies. Due to their sizes and monolithic nature, large ontologies regarding real world domains bring a new challenge to the state of the art ontology matching technology. In this paper, we propose a divide-and-conquer approach to matching large ontologies. We develop a structure-based partitioning algorithm, which partitions entities of each ontology into a set of small clusters and constructs blocks by assigning RDF Sentences to those clusters. Then, the blocks from different ontologies are matched based on precalculated anchors, and the block mappings holding high similarities are selected. Finally, two powerful matchers, V-Doc and Gmo, are employed to discover alignments in the block mappings. Comprehensive evaluation on both synthetic and real world data sets demonstrates that our approach both solves the scalability problem and achieves good precision and recall with significant reduction of execution time.