Institution
University of Electronic Science and Technology of China
Education•Chengdu, 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: Antenna (radio) & Dielectric. The organization has 50594 authors who have published 58502 publications receiving 711188 citations. The organization is also known as: UESTC.
Topics: Antenna (radio), Dielectric, Thin film, Radar, Artificial neural network
Papers published on a yearly basis
Papers
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TL;DR: The focus here is on the progress of graphene synthesis on Cu foils by CVD, including various CVD techniques, graphene growth mechanisms and kinetics, strategies for synthesizing large-area graphene single crystals, graphene transfer techniques, and, finally, challenges and prospects are discussed.
Abstract: Over the past decade, graphene has advanced rapidly as one of the most promising materials changing human life. Development of production-worthy synthetic methodologies for the preparation of various types of graphene forms the basis for its investigation and applications. Graphene can be used in the forms of either microflake powders or large-area thin films. Graphene powders are prepared by the exfoliation of graphite or the reduction of graphene oxide, while graphene films are prepared predominantly by chemical vapor deposition (CVD) on a variety of substrates. Both metal and dielectric substrates have been explored; while dielectric substrates are preferred over any other substrate, much higher quality graphene large-area films have been grown on metal substrates such as Cu. The focus here is on the progress of graphene synthesis on Cu foils by CVD, including various CVD techniques, graphene growth mechanisms and kinetics, strategies for synthesizing large-area graphene single crystals, graphene transfer techniques, and, finally, challenges and prospects are discussed.
263 citations
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TL;DR: The main focus of this review will be to summarize human preclinical work and particularly the rapidly growing number of clinical studies which have identified important links between oxytocin and a wide range of psychiatric disorders, and have now started to directly assess its therapeutic potential.
263 citations
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TL;DR: Evidence is provided for a mechanism by which OXT may contribute to romantic bonds in men by enhancing their partner's attractiveness and reward value compared with other women and for a finding that this finding is partner-bond specific rather than due to familiarity.
Abstract: The biological mechanisms underlying long-term partner bonds in humans are unclear. The evolutionarily conserved neuropeptide oxytocin (OXT) is associated with the formation of partner bonds in some species via interactions with brain dopamine reward systems. However, whether it plays a similar role in humans has as yet not been established. Here, we report the results of a discovery and a replication study, each involving a double-blind, placebo-controlled, within-subject, pharmaco-functional MRI experiment with 20 heterosexual pair-bonded male volunteers. In both experiments, intranasal OXT treatment (24 IU) made subjects perceive their female partner's face as more attractive compared with unfamiliar women but had no effect on the attractiveness of other familiar women. This enhanced positive partner bias was paralleled by an increased response to partner stimuli compared with unfamiliar women in brain reward regions including the ventral tegmental area and the nucleus accumbens (NAcc). In the left NAcc, OXT even augmented the neural response to the partner compared with a familiar woman, indicating that this finding is partner-bond specific rather than due to familiarity. Taken together, our results suggest that OXT could contribute to romantic bonds in men by enhancing their partner's attractiveness and reward value compared with other women.
262 citations
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TL;DR: This work draws attention to the identification of diametrically opposing patterns of variability changes between schizophrenia and attention deficit hyperactivity disorder/autism and provides insights into the dynamic organization of the resting brain and how it changes in brain disorders.
Abstract: SEE MATTAR ET AL DOI101093/AWW151 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Functional brain networks demonstrate significant temporal variability and dynamic reconfiguration even in the resting state. Currently, most studies investigate temporal variability of brain networks at the scale of single (micro) or whole-brain (macro) connectivity. However, the mechanism underlying time-varying properties remains unclear, as the coupling between brain network variability and neural activity is not readily apparent when analysed at either micro or macroscales. We propose an intermediate (meso) scale analysis and characterize temporal variability of the functional architecture associated with a particular region. This yields a topography of variability that reflects the whole-brain and, most importantly, creates an analytical framework to establish the fundamental relationship between variability of regional functional architecture and its neural activity or structural connectivity. We find that temporal variability reflects the dynamical reconfiguration of a brain region into distinct functional modules at different times and may be indicative of brain flexibility and adaptability. Primary and unimodal sensory-motor cortices demonstrate low temporal variability, while transmodal areas, including heteromodal association areas and limbic system, demonstrate the high variability. In particular, regions with highest variability such as hippocampus/parahippocampus, inferior and middle temporal gyrus, olfactory gyrus and caudate are all related to learning, suggesting that the temporal variability may indicate the level of brain adaptability. With simultaneously recorded electroencephalography/functional magnetic resonance imaging and functional magnetic resonance imaging/diffusion tensor imaging data, we also find that variability of regional functional architecture is modulated by local blood oxygen level-dependent activity and α-band oscillation, and is governed by the ratio of intra- to inter-community structural connectivity. Application of the mesoscale variability measure to multicentre datasets of three mental disorders and matched controls involving 1180 subjects reveals that those regions demonstrating extreme, i.e. highest/lowest variability in controls are most liable to change in mental disorders. Specifically, we draw attention to the identification of diametrically opposing patterns of variability changes between schizophrenia and attention deficit hyperactivity disorder/autism. Regions of the default-mode network demonstrate lower variability in patients with schizophrenia, but high variability in patients with autism/attention deficit hyperactivity disorder, compared with respective controls. In contrast, subcortical regions, especially the thalamus, show higher variability in schizophrenia patients, but lower variability in patients with attention deficit hyperactivity disorder. The changes in variability of these regions are also closely related to symptom scores. Our work provides insights into the dynamic organization of the resting brain and how it changes in brain disorders. The nodal variability measure may also be potentially useful as a predictor for learning and neural rehabilitation.
262 citations
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TL;DR: A novel predictor called iDNA6mA-PseKNC is proposed that is established by incorporating nucleotide physicochemical properties into Pseudo K-tuple Nucleotide Composition (PSEKNC), and it has been observed via rigorous cross-validations that the predictor's sensitivity, specificity, accuracy, and stability are excellent.
261 citations
Authors
Showing all 51090 results
Name | H-index | Papers | Citations |
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Gang Chen | 167 | 3372 | 149819 |
Frede Blaabjerg | 147 | 2161 | 112017 |
Kuo-Chen Chou | 143 | 487 | 57711 |
Yi Yang | 143 | 2456 | 92268 |
Guanrong Chen | 141 | 1652 | 92218 |
Shuit-Tong Lee | 138 | 1121 | 77112 |
Lei Zhang | 135 | 2240 | 99365 |
Rajkumar Buyya | 133 | 1066 | 95164 |
Lei Zhang | 130 | 2312 | 86950 |
Bin Wang | 126 | 2226 | 74364 |
Haiyan Wang | 119 | 1674 | 86091 |
Bo Wang | 119 | 2905 | 84863 |
Yi Zhang | 116 | 436 | 73227 |
Qiang Yang | 112 | 1117 | 71540 |
Chun-Sing Lee | 109 | 977 | 47957 |