University of Electronic Science and Technology of China

About: University of Electronic Science and Technology of China is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Computer science & Antenna (radio). The organization has 50594 authors who have published 58502 publications receiving 711188 citations. The organization is also known as: UESTC.

Link prediction in complex networks: A survey

Abstract: Link prediction in complex networks has attracted increasing attention from both physical and computer science communities. The algorithms can be used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. This article summaries recent progress about link prediction algorithms, emphasizing on the contributions from physical perspectives and approaches, such as the random-walk-based methods and the maximum likelihood methods. We also introduce three typical applications: reconstruction of networks, evaluation of network evolving mechanism and classification of partially labeled networks. Finally, we introduce some applications and outline future challenges of link prediction algorithms.

Efficient design and assembly of custom TALEN and other TAL effector-based constructs for DNA targeting

Abstract: TALENs are important new tools for genome engineering. Fusions of transcription activator-like (TAL) effectors of plant pathogenic Xanthomonas spp. to the FokI nuclease, TALENs bind and cleave DNA in pairs. Binding specificity is determined by customizable arrays of polymorphic amino acid repeats in the TAL effectors. We present a method and reagents for efficiently assembling TALEN constructs with custom repeat arrays. We also describe design guidelines based on naturally occurring TAL effectors and their binding sites. Using software that applies these guidelines, in nine genes from plants, animals and protists, we found candidate cleavage sites on average every 35bp. Each of 15 sites selected from this set was cleaved in a yeast-based assay with TALEN pairs constructed with our reagents. We used two of the TALEN pairs to mutate HPRT1 in human cells and ADH1 in Arabidopsis thaliana protoplasts. Our reagents include a plasmid construct for making custom TAL effectors and one for TAL effector fusions to additional proteins of interest. Using the former, we constructed de novo a functional analog of AvrHah1 of Xanthomonas gardneri. The complete plasmid set is available through the non-profit repository AddGene

Coding metamaterials, digital metamaterials and programmable metamaterials

Abstract: Smart materials offering great freedom in manipulating electromagnetic radiation have been developed. This exciting new concept was realized by Tie Jun Cui and co-workers at the Southeast University, China, who developed digital metamaterials consisting of two kinds of unit cells whose different phase responses allow them to act as ‘0’ and ‘1’ bits. These cells can be judiciously arranged in sequences to enable controlled manipulation of electromagnetic waves. This is one-bit coding; higher-bit coding is possible by employing more kinds of unit cells. The researchers developed a metamaterial cell whose binary response can be controlled by a biased diode. By using a field-programmable gate array, they demonstrated that this digital metamaterial can be programmed. Such metamaterials are attractive for controlling radiation beams in antennas and for realizing other ‘smart’ metamaterials.

The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture

Abstract: The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states.

Simple Baselines for Human Pose Estimation and Tracking

Abstract: There has been significant progress on pose estimation and increasing interests on pose tracking in recent years. At the same time, the overall algorithm and system complexity increases as well, making the algorithm analysis and comparison more difficult. This work provides simple and effective baseline methods. They are helpful for inspiring and evaluating new ideas for the field. State-of-the-art results are achieved on challenging benchmarks. The code will be available at https://github.com/leoxiaobin/pose.pytorch.