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Institution

Wuhan University

EducationWuhan, China
About: Wuhan University is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Population & Feature extraction. The organization has 92849 authors who have published 92882 publications receiving 1691049 citations. The organization is also known as: WHU & Wuhan College.


Papers
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Journal ArticleDOI
TL;DR: Synthesis of atomically dispersed Rh on N-doped carbon is successfully synthesized and it is discovered that SA-Rh/CN exhibits promising electrocatalytic properties for formic acid oxidation and exhibits greatly enhanced tolerance to CO poisoning.
Abstract: To meet the requirements of potential applications, it is of great importance to explore new catalysts for formic acid oxidation that have both ultra-high mass activity and CO resistance. Here, we successfully synthesize atomically dispersed Rh on N-doped carbon (SA-Rh/CN) and discover that SA-Rh/CN exhibits promising electrocatalytic properties for formic acid oxidation. The mass activity shows 28- and 67-fold enhancements compared with state-of-the-art Pd/C and Pt/C, respectively, despite the low activity of Rh/C. Interestingly, SA-Rh/CN exhibits greatly enhanced tolerance to CO poisoning, and Rh atoms in SA-Rh/CN resist sintering after long-term testing, resulting in excellent catalytic stability. Density functional theory calculations suggest that the formate route is more favourable on SA-Rh/CN. According to calculations, the high barrier to produce CO, together with the relatively unfavourable binding with CO, contribute to its CO tolerance. Atomically dispersed Rh on N-doped carbon exhibits 28- and 67-fold enhancements compared with state-of-the-art Pd/C and Pt/C, despite the low activity of Rh/C. The Rh single atoms exhibit high tolerance to CO poisoning compared to Rh nanoparticles.

335 citations

Journal ArticleDOI
TL;DR: In this paper, a multiscale and multidepth CNN was proposed for pan-sharpening of remote sensing images, and the proposed network yields high-resolution MS images that are superior to the compared state-of-the-art methods.
Abstract: Pan-sharpening is a fundamental and significant task in the field of remote sensing imagery processing, in which high-resolution spatial details from panchromatic images are employed to enhance the spatial resolution of multispectral (MS) images. As the transformation from low spatial resolution MS image to high-resolution MS image is complex and highly nonlinear, inspired by the powerful representation for nonlinear relationships of deep neural networks, we introduce multiscale feature extraction and residual learning into the basic convolutional neural network (CNN) architecture and propose the multiscale and multidepth CNN for the pan-sharpening of remote sensing imagery. Both the quantitative assessment results and the visual assessment confirm that the proposed network yields high-resolution MS images that are superior to the images produced by the compared state-of-the-art methods.

335 citations

Journal ArticleDOI
TL;DR: The successful design of lead-free direct band gap perovskite NCs with superior optical properties opens the door for high-performance lead-based optoelectronic devices.
Abstract: Lead-free double-perovskite nanocrystals (NCs), that is, Cs2AgInxBi1–xCl6 (x = 0, 0.25, 0.5, 0.75, and 0.9), that can be tuned from indirect band gap (x = 0, 0.25, and 0.5) to direct band gap (x = 0.75 and 0.9) are designed. Direct band gap NCs exhibit 3 times greater absorption cross section, lower sub-band gap trap states, and >5 times photoluminescence quantum efficiency (PLQE) compared to those observed for indirect band gap NCs (Cs2AgBiCl6). A PLQE of 36.6% for direct band gap NCs is comparable to those observed for lead perovskite NCs in the violet region. Besides the band edge violet emission, the direct band gap NCs exhibit bright orange (570 nm) emission. Density functional theory calculations suggesting forbidden transition is responsible for the orange emission, which is supported by time-resolved PL and PL excitation spectra. The successful design of lead-free direct band gap perovskite NCs with superior optical properties opens the door for high-performance lead-free perovskite optoelectronic...

335 citations

Posted ContentDOI
03 Mar 2020-medRxiv
TL;DR: Serum SARS-CoV-2 viral load (RNAaemia) is strongly associated with cytokine storm and can be used to predict the poor prognosis of COVID-19 patients and strongly suggest that cytokine IL-6 should be considered as a therapeutic target in critically ill patients with excessive inflammatory response.
Abstract: Background Although the SARS-CoV-2 viral load detection of respiratory specimen has been widely used for novel coronavirus disease (COVID-19) diagnosis, it is undeniable that serum SARS-CoV-2 nucleic acid (RNAaemia) could be detected in a fraction of the COVID-19 patients. However, it is not clear that if the incidence of RNAaemia could be correlated with the occurrence of cytokine storm or with the specific class of patients. Methods This study enrolled 48 patients with COVID-19 admitted to the General Hospital of Central Theater Command, PLA, a designated hospital in Wuhan, China. The patients were divided into three groups according to the Diagnosis and Treatment of New Coronavirus Pneumonia (version 6) published by the National Health Commission of China. The clinical and laboratory data were collected. The serum viral load detection and serum IL-6 levels were determined. Except for routine statistical analysis, Generalized Linear Models (GLMs) analysis was used to establish a patient status prediction model based on real-time RT-PCR Ct value. Findings The Result showed that cases with RNAaemia were exclusively confirmed in critically ill patients group and appeared to reflect the illness severity. Further more, the inflammatory cytokine IL-6 levels were significantly elevated in critically ill patients, which is almost 10-folds higher than those in other patients. More importantly, the extremely high IL-6 level was closely correlated with the incidence of RNAaemia (R=0.902) and the vital signs of COVID-19 patients (R= −0.682). Interpretation Serum SARS-CoV-2 viral load (RNAaemia) is strongly associated with cytokine storm and can be used to predict the poor prognosis of COVID-19 patients. Moreover, our results strongly suggest that cytokine IL-6 should be considered as a therapeutic target in critically ill patients with excessive inflammatory response.

335 citations

Journal ArticleDOI
TL;DR: The synchronous fluorescence, CD and three-dimensional fluorescence spectral results showed that the hydrophobicity of amino acid residues increased and the losing of α-helix content in the presence of PAAB revealed that the microenvironment and conformation of BSA were changed in the binding reaction.
Abstract: In this paper, the interaction between p-aminoazobenzene (PAAB) and BSA was investigated mainly by fluorescence quenching spectra, circular dichroism (CD) and three-dimensional fluorescence spectra under simulative physiological conditions. It was proved that the fluorescence quenching of BSA by PAAB was mainly a result of the formation of a PAAB-BSA complex. The modified Stern-Volmer quenching constant Ka and the corresponding thermodynamic parameters ΔH, ΔG and ΔS at different temperatures were calculated. The results indicated that van der Waals interactions and hydrogen bonds were the predominant intermolecular forces in stabilizing the complex. The distance r = 4.33 nm between the donor (BSA) and acceptor (PAAB) was obtained according to Forster’s non-radioactive energy transfer theory. The synchronous fluorescence, CD and three-dimensional fluorescence spectral results showed that the hydrophobicity of amino acid residues increased and the losing of α-helix content (from 63.57 to 51.83%) in the presence of PAAB. These revealed that the microenvironment and conformation of BSA were changed in the binding reaction.

334 citations


Authors

Showing all 93441 results

NameH-indexPapersCitations
Jing Wang1844046202769
Jiaguo Yu178730113300
Lei Jiang1702244135205
Gang Chen1673372149819
Omar M. Yaghi165459163918
Xiang Zhang1541733117576
Yi Yang143245692268
Thomas P. Russell141101280055
Jun Chen136185677368
Lei Zhang135224099365
Chuan He13058466438
Han Zhang13097058863
Lei Zhang130231286950
Zhen Li127171271351
Chao Zhang127311984711
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023286
20221,139
20219,716
20209,672
20197,977
20186,629