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Chao Zhang

Researcher at Beihang University

Publications -  4347
Citations -  118320

Chao Zhang is an academic researcher from Beihang University. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 127, co-authored 3119 publications receiving 84711 citations. Previous affiliations of Chao Zhang include West Virginia University & University of Oklahoma.

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Oxygen-vacancy-related high-temperature dielectric relaxation in SrTiO3 ceramics

TL;DR: In this article, a dielectric loss peak is observed at around 450 K and 100 Hz and it shifts to higher temperature with increasing frequency, and a Cole-Cole fitting to loss peaks reveals a weaker correlation among oxygen vacancies for such materials compared with that of ferroelectrics.
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Rehabilitation regimen after surgical treatment of acute Achilles tendon ruptures: a systematic review with meta-analysis.

TL;DR: Postoperative early weightbearing combined with early ankle motion exercises is associated with a lower minor complication rate and achieves superior and more rapid functional recovery than conventional immobilization after surgical AT repair.
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Multifunctional Superelastic Foam-Like Boron Nitride Nanotubular Cellular-Network Architectures

TL;DR: This paper presents cellular-network multifunctional foams made of interconnective nanotubular hexagonal BN (h-BN) architectures developed using carbothermal reduction-assisted in situ chemical vapor deposition conversion from N-doped tubular graphitic cellular foams, which exhibit a 98.5% porosity, remarkable shape recovery, excellent resistance to water intrusion, thermal diffusion stability, and high strength and stiffness.
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Poly(ethylene glycol) cryogels as potential cell scaffolds: effect of polymerization conditions on cryogel microstructure and properties

TL;DR: In this article, the synthesis and characterization of interconnected macroporous network structures of poly(ethylene glycol) (PEG) using cryogelation techniques was reported. But, the results were limited to a single precursor.
Proceedings ArticleDOI

Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks

TL;DR: HEER as discussed by the authors proposes a comprehensive transcription of heterogeneous information networks (HINs), which embeds HINs via edge representations that are further coupled with properly-learned heterogeneous metrics.