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Institution

Zhejiang University

EducationHangzhou, Zhejiang, China
About: Zhejiang University is a education organization based out in Hangzhou, Zhejiang, China. It is known for research contribution in the topics: Population & Catalysis. The organization has 161257 authors who have published 183264 publications receiving 3417592 citations. The organization is also known as: Chekiang University & Zheda.


Papers
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Journal ArticleDOI
TL;DR: Clinical manifestations such as fever, shortness of breath or dyspnea were associated with the progression of disease, and laboratory examination such as aspartate amino transferase(AST) > 40U/L, creatinine(Cr) ≥ 133mol/l, hypersensitive cardiac troponin I(hs-cTnI) > 28pg/mL, procalcitonin(PCT) > 0.5mg/L predicted the deterioration of disease.

1,743 citations

Journal ArticleDOI
19 Feb 2020-BMJ
TL;DR: As of early February 2020, compared with patients initially infected with SARS-Cov-2 in Wuhan, the symptoms of patients in Zhejiang province are relatively mild.
Abstract: Objective To study the clinical characteristics of patients in Zhejiang province, China, infected with the 2019 severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) responsible for coronavirus disease 2019 (covid-2019). Design Retrospective case series. Setting Seven hospitals in Zhejiang province, China. Participants 62 patients admitted to hospital with laboratory confirmed SARS-Cov-2 infection. Data were collected from 10 January 2020 to 26 January 2020. Main outcome measures Clinical data, collected using a standardised case report form, such as temperature, history of exposure, incubation period. If information was not clear, the working group in Hangzhou contacted the doctor responsible for treating the patient for clarification. Results Of the 62 patients studied (median age 41 years), only one was admitted to an intensive care unit, and no patients died during the study. According to research, none of the infected patients in Zhejiang province were ever exposed to the Huanan seafood market, the original source of the virus; all studied cases were infected by human to human transmission. The most common symptoms at onset of illness were fever in 48 (77%) patients, cough in 50 (81%), expectoration in 35 (56%), headache in 21 (34%), myalgia or fatigue in 32 (52%), diarrhoea in 3 (8%), and haemoptysis in 2 (3%). Only two patients (3%) developed shortness of breath on admission. The median time from exposure to onset of illness was 4 days (interquartile range 3-5 days), and from onset of symptoms to first hospital admission was 2 (1-4) days. Conclusion As of early February 2020, compared with patients initially infected with SARS-Cov-2 in Wuhan, the symptoms of patients in Zhejiang province are relatively mild.

1,730 citations

Journal ArticleDOI
TL;DR: All carbon aerogels with ultralow density and temperature-invariant super-elasticity are fabricated by facile assembling of commercial carbon nanotubes and chemically-converted giant graphene sheets, on the basis of the synergistic effect between elastic CNTs ribs and giant graphene cell walls.
Abstract: All carbon aerogels (up to 1000 cm(3)) with ultralow density (down to 0.16 mg cm(-3)) and temperature-invariant (-190-900 °C) super-elasticity are fabricated by facile assembling of commercial carbon nanotubes (CNTs) and chemically-converted giant graphene sheets, on the basis of the synergistic effect between elastic CNTs ribs and giant graphene cell walls.

1,680 citations

Posted Content
TL;DR: This work introduces two new modules to enhance the transformation modeling capability of CNNs, namely, deformable convolution and deformable RoI pooling, based on the idea of augmenting the spatial sampling locations in the modules with additional offsets and learning the offsets from the target tasks, without additional supervision.
Abstract: Convolutional neural networks (CNNs) are inherently limited to model geometric transformations due to the fixed geometric structures in its building modules. In this work, we introduce two new modules to enhance the transformation modeling capacity of CNNs, namely, deformable convolution and deformable RoI pooling. Both are based on the idea of augmenting the spatial sampling locations in the modules with additional offsets and learning the offsets from target tasks, without additional supervision. The new modules can readily replace their plain counterparts in existing CNNs and can be easily trained end-to-end by standard back-propagation, giving rise to deformable convolutional networks. Extensive experiments validate the effectiveness of our approach on sophisticated vision tasks of object detection and semantic segmentation. The code would be released.

1,661 citations

Journal ArticleDOI
TL;DR: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) as mentioned in this paper provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.

1,656 citations


Authors

Showing all 162389 results

NameH-indexPapersCitations
Stuart H. Orkin186715112182
H. S. Chen1792401178529
Markus Antonietti1761068127235
Yang Yang1712644153049
Gang Chen1673372149819
Jun Wang1661093141621
Hua Zhang1631503116769
Rui Zhang1512625107917
Ben Zhong Tang1492007116294
J. Fraser Stoddart147123996083
Yi Yang143245692268
Jian Yang1421818111166
Liming Dai14178182937
Joseph Lau140104899305
Wei Huang139241793522
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023468
20222,568
202119,856
202017,749
201914,872
201812,285