Wuhan University

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

Bond Formations between Two Nucleophiles: Transition Metal Catalyzed Oxidative Cross-Coupling Reactions

Abstract: 3.1. C-M and X-H as Nucleophiles 1806 3.2. C-H and X-M as Nucleophiles 1809 3.2.1. C-Halogen Bond Formations 1809 3.2.2. C-O Bond Formations 1812 3.3. C-H and X-H as Nucleophiles 1812 3.3.1. C-O Bond Formations 1812 3.3.2. C-N Bond Formations 1815 4. Oxidative X-X Bond Formations between Two Nucleophiles 1819 5. Conclusions 1819 Author Information 1819 Biographies 1819 Acknowledgment 1820 References 1820

Aerodynamic analysis of SARS-CoV-2 in two Wuhan hospitals.

Abstract: The ongoing outbreak of coronavirus disease 2019 (COVID-19) has spread rapidly on a global scale. Although it is clear that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is transmitted through human respiratory droplets and direct contact, the potential for aerosol transmission is poorly understood1-3. Here we investigated the aerodynamic nature of SARS-CoV-2 by measuring viral RNA in aerosols in different areas of two Wuhan hospitals during the outbreak of COVID-19 in February and March 2020. The concentration of SARS-CoV-2 RNA in aerosols that was detected in isolation wards and ventilated patient rooms was very low, but it was higher in the toilet areas used by the patients. Levels of airborne SARS-CoV-2 RNA in the most public areas was undetectable, except in two areas that were prone to crowding; this increase was possibly due to individuals infected with SARS-CoV-2 in the crowd. We found that some medical staff areas initially had high concentrations of viral RNA with aerosol size distributions that showed peaks in the submicrometre and/or supermicrometre regions; however, these levels were reduced to undetectable levels after implementation of rigorous sanitization procedures. Although we have not established the infectivity of the virus detected in these hospital areas, we propose that SARS-CoV-2 may have the potential to be transmitted through aerosols. Our results indicate that room ventilation, open space, sanitization of protective apparel, and proper use and disinfection of toilet areas can effectively limit the concentration of SARS-CoV-2 RNA in aerosols. Future work should explore the infectivity of aerosolized virus.

Anion-exchange membranes in electrochemical energy systems

Abstract: This article provides an up-to-date perspective on the use of anion-exchange membranes in fuel cells, electrolysers, redox flow batteries, reverse electrodialysis cells, and bioelectrochemical systems (e.g. microbial fuel cells). The aim is to highlight key concepts, misconceptions, the current state-of-the-art, technological and scientific limitations, and the future challenges (research priorities) related to the use of anion-exchange membranes in these energy technologies. All the references that the authors deemed relevant, and were available on the web by the manuscript submission date (30th April 2014), are included.

DOTA: A Large-Scale Dataset for Object Detection in Aerial Images

Abstract: Object detection is an important and challenging problem in computer vision. Although the past decade has witnessed major advances in object detection in natural scenes, such successes have been slow to aerial imagery, not only because of the huge variation in the scale, orientation and shape of the object instances on the earth's surface, but also due to the scarcity of well-annotated datasets of objects in aerial scenes. To advance object detection research in Earth Vision, also known as Earth Observation and Remote Sensing, we introduce a large-scale Dataset for Object deTection in Aerial images (DOTA). To this end, we collect 2806 aerial images from different sensors and platforms. Each image is of the size about 4000 A— 4000 pixels and contains objects exhibiting a wide variety of scales, orientations, and shapes. These DOTA images are then annotated by experts in aerial image interpretation using 15 common object categories. The fully annotated DOTA images contains 188, 282 instances, each of which is labeled by an arbitrary (8 d.o.f.) quadrilateral. To build a baseline for object detection in Earth Vision, we evaluate state-of-the-art object detection algorithms on DOTA. Experiments demonstrate that DOTA well represents real Earth Vision applications and are quite challenging.