About: Southeast University is a(n) education organization based out in Nanjing, China. It is known for research contribution in the topic(s): MIMO & Control theory. The organization has 66363 authors who have published 79434 publication(s) receiving 1170576 citation(s). The organization is also known as: SEU.
Papers published on a yearly basis
01 Sep 2007-Nature Nanotechnology
TL;DR: It is reported that magnetite nanoparticles in fact possess an intrinsic enzyme mimetic activity similar to that found in natural peroxidases, which are widely used to oxidize organic substrates in the treatment of wastewater or as detection tools.
Abstract: Nanoparticles containing magnetic materials, such as magnetite (Fe3O4), are particularly useful for imaging and separation techniques. As these nanoparticles are generally considered to be biologically and chemically inert, they are typically coated with metal catalysts, antibodies or enzymes to increase their functionality as separation agents. Here, we report that magnetite nanoparticles in fact possess an intrinsic enzyme mimetic activity similar to that found in natural peroxidases, which are widely used to oxidize organic substrates in the treatment of wastewater or as detection tools. Based on this finding, we have developed a novel immunoassay in which antibody-modified magnetite nanoparticles provide three functions: capture, separation and detection. The stability, ease of production and versatility of these nanoparticles makes them a powerful tool for a wide range of potential applications in medicine, biotechnology and environmental chemistry.
Rutgers University1, New York University2, University of Oxford3, Harvard University4, Bangor University5, University of Copenhagen6, National Institutes of Health7, Oregon Health & Science University8, Yale University9, Nathan Kline Institute for Psychiatric Research10, Medical College of Wisconsin11, University of Oulu12, Radboud University Nijmegen13, National Yang-Ming University14, Cleveland Clinic15, Duke University16, Max Planck Society17, Emory University18, University of Queensland19, University of Michigan20, Kennedy Krieger Institute21, Washington University in St. Louis22, Technische Universität München23, Leiden University24, University of Texas at Dallas25, Charité26, University of Pittsburgh27, Southeast University28, Otto-von-Guericke University Magdeburg29, Massachusetts Institute of Technology30, University of Western Ontario31, Medical University of Vienna32, Beijing Normal University33
TL;DR: The 1000 Functional Connectomes Project (Fcon_1000) as discussed by the authors is a large-scale collection of functional connectome data from 1,414 volunteers collected independently at 35 international centers.
Abstract: Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/.
TL;DR: This paper aims to provide a timely review on this area with emphasis on state-of-the-art multi-label learning algorithms with relevant analyses and discussions.
Abstract: Multi-label learning studies the problem where each example is represented by a single instance while associated with a set of labels simultaneously. During the past decade, significant amount of progresses have been made toward this emerging machine learning paradigm. This paper aims to provide a timely review on this area with emphasis on state-of-the-art multi-label learning algorithms. Firstly, fundamentals on multi-label learning including formal definition and evaluation metrics are given. Secondly and primarily, eight representative multi-label learning algorithms are scrutinized under common notations with relevant analyses and discussions. Thirdly, several related learning settings are briefly summarized. As a conclusion, online resources and open research problems on multi-label learning are outlined for reference purposes.
19 Feb 2014-IEEE Communications Magazine
TL;DR: A potential cellular architecture that separates indoor and outdoor scenarios is proposed, and various promising technologies for 5G wireless communication systems, such as massive MIMO, energy-efficient communications, cognitive radio networks, and visible light communications are discussed.
Abstract: The fourth generation wireless communication systems have been deployed or are soon to be deployed in many countries. However, with an explosion of wireless mobile devices and services, there are still some challenges that cannot be accommodated even by 4G, such as the spectrum crisis and high energy consumption. Wireless system designers have been facing the continuously increasing demand for high data rates and mobility required by new wireless applications and therefore have started research on fifth generation wireless systems that are expected to be deployed beyond 2020. In this article, we propose a potential cellular architecture that separates indoor and outdoor scenarios, and discuss various promising technologies for 5G wireless communication systems, such as massive MIMO, energy-efficient communications, cognitive radio networks, and visible light communications. Future challenges facing these potential technologies are also discussed.
TL;DR: In this article, the authors reviewed some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006 and proposed several promising research directions along with some open problems that are deemed important for further investigations.
Abstract: This paper reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles, and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations.
Showing all 66363 results
|H. S. Chen||179||2401||178529|
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