Institution
Zhejiang University
Education•Hangzhou, Zhejiang, China•
About: Zhejiang University is a education organization based out in Hangzhou, Zhejiang, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 161257 authors who have published 183264 publications receiving 3417592 citations. The organization is also known as: Chekiang University & Zheda.
Topics: Catalysis, Population, Computer science, Medicine, Cancer
Papers published on a yearly basis
Papers
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15 Jun 2019TL;DR: A Pixel-wise Voting Network (PVNet) is introduced to regress pixel-wise vectors pointing to the keypoints and use these vectors to vote for keypoint locations, which creates a flexible representation for localizing occluded or truncated keypoints.
Abstract: This paper addresses the challenge of 6DoF pose estimation from a single RGB image under severe occlusion or truncation. Many recent works have shown that a two-stage approach, which first detects keypoints and then solves a Perspective-n-Point (PnP) problem for pose estimation, achieves remarkable performance. However, most of these methods only localize a set of sparse keypoints by regressing their image coordinates or heatmaps, which are sensitive to occlusion and truncation. Instead, we introduce a Pixel-wise Voting Network (PVNet) to regress pixel-wise vectors pointing to the keypoints and use these vectors to vote for keypoint locations. This creates a flexible representation for localizing occluded or truncated keypoints. Another important feature of this representation is that it provides uncertainties of keypoint locations that can be further leveraged by the PnP solver. Experiments show that the proposed approach outperforms the state of the art on the LINEMOD, Occlusion LINEMOD and YCB-Video datasets by a large margin, while being efficient for real-time pose estimation. We further create a Truncation LINEMOD dataset to validate the robustness of our approach against truncation. The code is available at https://zju3dv.github.io/pvnet/.
517 citations
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TL;DR: ADMETlab 2.0 as discussed by the authors is a completely redesigned version of the widely used AMDETlab web server for the predictions of pharmacokinetics and toxicity properties of chemicals, of which the supported ADMET-related endpoints are approximately twice the number of the endpoints in the previous version, including 17 physicochemical properties, 13 medicinal chemistry properties, 23 ADME properties, 27 toxicity endpoints and 8 toxicophore rules.
Abstract: Because undesirable pharmacokinetics and toxicity of candidate compounds are the main reasons for the failure of drug development, it has been widely recognized that absorption, distribution, metabolism, excretion and toxicity (ADMET) should be evaluated as early as possible. In silico ADMET evaluation models have been developed as an additional tool to assist medicinal chemists in the design and optimization of leads. Here, we announced the release of ADMETlab 2.0, a completely redesigned version of the widely used AMDETlab web server for the predictions of pharmacokinetics and toxicity properties of chemicals, of which the supported ADMET-related endpoints are approximately twice the number of the endpoints in the previous version, including 17 physicochemical properties, 13 medicinal chemistry properties, 23 ADME properties, 27 toxicity endpoints and 8 toxicophore rules (751 substructures). A multi-task graph attention framework was employed to develop the robust and accurate models in ADMETlab 2.0. The batch computation module was provided in response to numerous requests from users, and the representation of the results was further optimized. The ADMETlab 2.0 server is freely available, without registration, at https://admetmesh.scbdd.com/.
515 citations
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TL;DR: In contrast with the predicted commensurate spin-density-wave order at the nesting wave vector (pi, 0), a completely different magnetic order with a composition tunable propagation vector (deltapi, deltapi) was determined for the parent compound Fe 1+y}Te in this powder and single-crystal neutron diffraction study as discussed by the authors.
Abstract: The new alpha-Fe(Te,Se) superconductors share the common iron building block and ferminology with the LaFeAsO and BaFe(2)As(2) families of superconductors. In contrast with the predicted commensurate spin-density-wave order at the nesting wave vector (pi, 0), a completely different magnetic order with a composition tunable propagation vector (deltapi, deltapi) was determined for the parent compound Fe_{1+y}Te in this powder and single-crystal neutron diffraction study. The new antiferromagnetic order survives as a short-range one even in the highest T_{C} sample. An alternative to the prevailing nesting Fermi surface mechanism is required to understand the latest family of ferrous superconductors.
515 citations
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TL;DR: An overview of the recent advances on these luminescent nanomaterials with emphases on their optical characteristics that are crucial in fluorescence microscopy are given, both advantages and limitations in their usage as well as challenges they face, and puts forward the future direction of fluorescent labels in the area of biolabelling.
Abstract: The use of labelling or staining agents has greatly assisted the study of complex biological interactions in the field of biology. In particular, fluorescent labelling of biomolecules has been demonstrated as an indispensable tool in many biological studies. Types of fluorescent labelling agents that are commonly used include conventional classes of organic fluorophores such as fluorescein and cyanine dyes, as well as newer types of inorganic nanoparticles such as QDs, and novel fluorescent latex/silica nanobeads. The newer classes of fluorescent labels are gaining increasing popularity in place of their predecessors due to their better optical properties such as possessing an enhanced photostability and a larger Stokes shift over conventional organic fluorophores, for example. This paper gives an overview of the recent advances on these luminescent nanomaterials with emphases on their optical characteristics that are crucial in fluorescence microscopy, both advantages and limitations in their usage as well as challenges they face, and puts forward the future direction of fluorescent labels in the area of biolabelling.
514 citations
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TL;DR: The extension of the QAHE into the three-dimensional thickness region addresses the universality of this quantum transport phenomenon and motivates the exploration of new QA HE phases with tunable Chern numbers.
Abstract: We investigate the quantum anomalous Hall effect (QAHE) and related chiral transport in the millimeter-size ${({\mathrm{Cr}}_{0.12}{\mathrm{Bi}}_{0.26}{\mathrm{Sb}}_{0.62})}_{2}{\mathrm{Te}}_{3}$ films. With high sample quality and robust magnetism at low temperatures, the quantized Hall conductance of ${e}^{2}/h$ is found to persist even when the film thickness is beyond the two-dimensional (2D) hybridization limit. Meanwhile, the Chern insulator-featured chiral edge conduction is manifested by the nonlocal transport measurements. In contrast to the 2D hybridized thin film, an additional weakly field-dependent longitudinal resistance is observed in the ten-quintuple-layer film, suggesting the influence of the film thickness on the dissipative edge channel in the QAHE regime. The extension of the QAHE into the three-dimensional thickness region addresses the universality of this quantum transport phenomenon and motivates the exploration of new QAHE phases with tunable Chern numbers. In addition, the observation of scale-invariant dissipationless chiral propagation on a macroscopic scale makes a major stride towards ideal low-power interconnect applications.
514 citations
Authors
Showing all 162389 results
Name | H-index | Papers | Citations |
---|---|---|---|
Stuart H. Orkin | 186 | 715 | 112182 |
H. S. Chen | 179 | 2401 | 178529 |
Markus Antonietti | 176 | 1068 | 127235 |
Yang Yang | 171 | 2644 | 153049 |
Gang Chen | 167 | 3372 | 149819 |
Jun Wang | 166 | 1093 | 141621 |
Hua Zhang | 163 | 1503 | 116769 |
Rui Zhang | 151 | 2625 | 107917 |
Ben Zhong Tang | 149 | 2007 | 116294 |
J. Fraser Stoddart | 147 | 1239 | 96083 |
Yi Yang | 143 | 2456 | 92268 |
Jian Yang | 142 | 1818 | 111166 |
Liming Dai | 141 | 781 | 82937 |
Joseph Lau | 140 | 1048 | 99305 |
Wei Huang | 139 | 2417 | 93522 |