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.

Cobalt(II)-Catalyzed Electrooxidative C-H Amination of Arenes with Alkylamines.

Abstract: An environmentally friendly electrochemical protocol about cobalt-catalyzed C–H amination of arenes has been developed, which offers a simple way to access synthetically useful arylamines. In divided cells, a wide variety of arenes and alkylamines are examined to afford C–N formation products without using external oxidants, which avoids the formation of undesired byproducts and exhibits high atom economy. Importantly, the reaction can also be extended to gram level with moderate efficiency. KIE experiments indicate that C–H bond cleavage might not be involved during the rate-limiting step.

Overcoming the Heat Endurance of Tumor Cells by Interfering with the Anaerobic Glycolysis Metabolism for Improved Photothermal Therapy.

Abstract: In this study, we developed a general method to decorate plasmonic gold nanorods (GNRs) with a CD44-targeting functional polymer, containing a hyaluronic acid (HA)-targeting moiety and a small molecule Glut1 inhibitor of diclofenac (DC), to obtain GNR/HA-DC. This nanosystem exhibited the superiority of selectively sensitizing tumor cells for photothermal therapy (PTT) by inhibiting anaerobic glycolysis. Upon specifically targeting CD44, sequentially time-dependent DC release could be achieved by the trigger of hyaluronidase (HAase), which abundantly existed in tumor tissues. The released DC depleted the Glut1 level in tumor cells and induced a cascade effect on cellular metabolism by inhibiting glucose uptake, blocking glycolysis, decreasing ATP levels, hampering heat shock protein (HSP) expression, and ultimately leaving malignant cells out from the protection of HSPs to stress (e.g., heat), and then tumor cells were more easy to kill. Owing to the sensitization effect of GNR/HA-DC, CD44 overexpressed tu...

Remote Sensing Image Fusion With Deep Convolutional Neural Network

Abstract: Remote sensing images with different spatial and spectral resolution, such as panchromatic (PAN) images and multispectral (MS) images, can be captured by many earth-observing satellites. Normally, PAN images possess high spatial resolution but low spectral resolution, while MS images have high spectral resolution with low spatial resolution. In order to integrate spatial and spectral information contained in the PAN and MS images, image fusion techniques are commonly adopted to generate remote sensing images at both high spatial and spectral resolution. In this study, based on the deep convolutional neural network, a remote sensing image fusion method that can adequately extract spectral and spatial features from source images is proposed. The major innovation of this study is that the proposed fusion method contains a two branches network with the deeper structure which can capture salient features of the MS and PAN images separately. Besides, the residual learning is adopted in our network to thoroughly study the relationship between the high- and low-resolution MS images. The proposed method mainly consists of two procedures. First, spatial and spectral features are respectively extracted from the MS and PAN images by convolutional layers with different depth. Second, the feature fusion procedure utilizes the extracted features from the former step to yield fused images. By evaluating the performance on the QuickBird and Gaofen-1 images, our proposed method provides better results compared with other classical methods.

Crustal Deformation in the India‐Eurasia Collision Zone From 25 Years of GPS Measurements

Abstract: The India‐Eurasia collision zone is the largest deforming region on the planet; direct measurements of present‐day deformation from Global Positioning System (GPS) have the potential to discriminate between competing models of continental tectonics. But the increasing spatial resolution and accuracy of observations have only led to increasingly complex realizations of competing models. Here we present the most complete, accurate, and up‐to‐date velocity field for India‐Eurasia available, comprising 2576 velocities measured during 1991–2015. The core of our velocity field is from the Crustal Movement Observation Network of China‐I/II: 27 continuous stations observed since 1999; 56 campaign stations observed annually during 1998–2007; 1000 campaign stations observed in 1999, 2001, 2004, and 2007; 260 continuous stations operating since late 2010; and 2000 campaign stations observed in 2009, 2011, 2013, and 2015. We process these data and combine the solutions in a consistent reference frame with stations from the Global Strain Rate Model compilation, then invert for continuous velocity and strain rate fields. We update geodetic slip rates for the major faults (some vary along strike), and find that those along the major Tibetan strike‐slip faults are in good agreement with recent geological estimates. The velocity field shows several large undeforming areas, strain focused around some major faults, areas of diffuse strain, and dilation of the high plateau. We suggest that a new generation of dynamic models incorporating strength variations and strain‐weakening mechanisms is required to explain the key observations. Seismic hazard in much of the region is elevated, not just near the major faults.