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Institution

Nanjing University

EducationNanjing, China
About: Nanjing University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 85961 authors who have published 105504 publications receiving 2289036 citations. The organization is also known as: NJU & Nanking University.


Papers
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Journal ArticleDOI
Nicholas J Kassebaum1, Megha Arora1, Ryan M Barber1, Zulfiqar A Bhutta2  +679 moreInstitutions (268)
TL;DR: In this paper, the authors used the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) for all-cause mortality, cause-specific mortality, and non-fatal disease burden to derive HALE and DALYs by sex for 195 countries and territories from 1990 to 2015.

1,533 citations

Journal ArticleDOI
23 Feb 2010-Langmuir
TL;DR: The photodegradation mechanisms for two typical dyes, rhodamine B (Rh B) and methyl orange (MO), are proposed based on comparison experiments and the electron paramagnetic resonance was used to detect the active species for the photodegrading reaction over g-C(3)N(4).
Abstract: Graphitic carbon nitride (g-C3N4) and boron-doped g-C3N4 were prepared by heating melamine and the mixture of melamine and boron oxide, respectively. X-ray diffraction, X-ray photoelectron spectroscopy, and UV−vis spectra were used to describe the properties of as-prepared samples. The electron paramagnetic resonance was used to detect the active species for the photodegradation reaction over g-C3N4. The photodegradation mechanisms for two typical dyes, rhodamine B (Rh B) and methyl orange (MO), are proposed based on our comparison experiments. In the g-C3N4 photocatalysis system, the photodegradation of Rh B and MO is attributed to the direct hole oxidation and overall reaction, respectively; however, for the MO photodegradation the reduction process initiated by photogenerated electrons is a major photocatalytic process compared with the oxidation process induced by photogenerated holes. Boron doping for g-C3N4 can promote photodegradation of Rh B because the boron doping improves the dye adsorption and...

1,495 citations

Journal ArticleDOI
TL;DR: This review focuses on the etiology, epidemiology, and clinical symptoms of COVID-19, while highlighting the role of chest CT in prevention and disease control.
Abstract: In December 2019, an outbreak of severe acute respiratory syndrome coronavirus 2 infection occurred in Wuhan, Hubei Province, China, and spread across China and beyond. On February 12, 2020, the World Health Organization officially named the disease caused by the novel coronavirus as coronavirus disease 2019 (COVID-19). Because most patients infected with COVID-19 had pneumonia and characteristic CT imaging patterns, radiologic examinations have become vital in early diagnosis and the assessment of disease course. To date, CT findings have been recommended as major evidence for clinical diagnosis of COVID-19 in Hubei, China. This review focuses on the etiology, epidemiology, and clinical symptoms of COVID-19 while highlighting the role of chest CT in prevention and disease control.

1,485 citations

Journal ArticleDOI
22 Oct 2018-Nature
TL;DR: It is found that the itinerant ferromagnetism persists in Fe3GeTe2 down to the monolayer with an out-of-plane magnetocrystalline anisotropy, which opens up opportunities for potential voltage-controlled magnetoelectronics based on atomically thin van der Waals crystals.
Abstract: Materials research has driven the development of modern nano-electronic devices. In particular, research in magnetic thin films has revolutionized the development of spintronic devices1,2 because identifying new magnetic materials is key to better device performance and design. Van der Waals crystals retain their chemical stability and structural integrity down to the monolayer and, being atomically thin, are readily tuned by various kinds of gate modulation3,4. Recent experiments have demonstrated that it is possible to obtain two-dimensional ferromagnetic order in insulating Cr2Ge2Te6 (ref. 5) and CrI3 (ref. 6) at low temperatures. Here we develop a device fabrication technique and isolate monolayers from the layered metallic magnet Fe3GeTe2 to study magnetotransport. We find that the itinerant ferromagnetism persists in Fe3GeTe2 down to the monolayer with an out-of-plane magnetocrystalline anisotropy. The ferromagnetic transition temperature, Tc, is suppressed relative to the bulk Tc of 205 kelvin in pristine Fe3GeTe2 thin flakes. An ionic gate, however, raises Tc to room temperature, much higher than the bulk Tc. The gate-tunable room-temperature ferromagnetism in two-dimensional Fe3GeTe2 opens up opportunities for potential voltage-controlled magnetoelectronics7-11 based on atomically thin van der Waals crystals.

1,416 citations

Proceedings ArticleDOI
01 Jun 2019
TL;DR: SKNet as discussed by the authors proposes a dynamic selection mechanism in CNNs that allows each neuron to adaptively adjust its receptive field size based on multiple scales of input information, which can capture target objects with different scales.
Abstract: In standard Convolutional Neural Networks (CNNs), the receptive fields of artificial neurons in each layer are designed to share the same size. It is well-known in the neuroscience community that the receptive field size of visual cortical neurons are modulated by the stimulus, which has been rarely considered in constructing CNNs. We propose a dynamic selection mechanism in CNNs that allows each neuron to adaptively adjust its receptive field size based on multiple scales of input information. A building block called Selective Kernel (SK) unit is designed, in which multiple branches with different kernel sizes are fused using softmax attention that is guided by the information in these branches. Different attentions on these branches yield different sizes of the effective receptive fields of neurons in the fusion layer. Multiple SK units are stacked to a deep network termed Selective Kernel Networks (SKNets). On the ImageNet and CIFAR benchmarks, we empirically show that SKNet outperforms the existing state-of-the-art architectures with lower model complexity. Detailed analyses show that the neurons in SKNet can capture target objects with different scales, which verifies the capability of neurons for adaptively adjusting their receptive field sizes according to the input. The code and models are available at https://github.com/implus/SKNet.

1,401 citations


Authors

Showing all 86514 results

NameH-indexPapersCitations
Yi Chen2174342293080
H. S. Chen1792401178529
Zhenan Bao169865106571
Gang Chen1673372149819
Peter G. Schultz15689389716
Xiang Zhang1541733117576
Rui Zhang1512625107917
Yi Yang143245692268
Markku Kulmala142148785179
Jian Yang1421818111166
Wei Huang139241793522
Bin Liu138218187085
Jun Lu135152699767
Hui Li1352982105903
Lei Zhang135224099365
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20242
2023276
20221,087
20219,130
20208,684
20198,203