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HUA Tuo: The first neurosurgeon in the world

Yuqi Zhang, Yuqi Zhang
2015 Translational Neuroscience and Clinics  
Citation Zhang YQ. HUA Tuo: The first neurosurgeon in the world. Transl. Neurosci. Clin. 2015, 1(1): 71-72.  ...  ZHANG Guowei. He used his seal carving for official documents during the Beijing Olympic Games in 2008. There are also seal carvings with written sentiments (Figure 2) .  ... 
doi:10.18679/cn11-6030/r.2015.008 fatcat:rep3jj2i7bfh5nwwqnf55afgpi

Cerebral glioblastoma mimicking a cavernous malformation: A case report and literature review

Jiefei Li, Jiefei Li, Yuqi Zhang, Huancong Zuo, Yuqi Zhang, Huancong Zuo
2017 Translational Neuroscience and Clinics  
doi:10.18679/cn11-6030/r.2017.005 fatcat:z24vpsrtffejzk243c3heoa5ky

Conductive Polymer Porous Film with Tunable Wettability and Adhesion

Yuqi Teng, Yuqi Zhang, Liping Heng, Xiangfu Meng, Qiaowen Yang, Lei Jiang
2015 Materials  
Acknowledgments Author Contributions Yuqi Teng finished the experiment and data processing; Yuqi Zhang write the article; Liping Heng and Xiangfu Meng schemed the experiment; Qiaowen Yang and Lei Jiang  ... 
doi:10.3390/ma8041817 pmid:28788033 pmcid:PMC5507056 fatcat:rttlixjibjhphdv5qbswulatiy

OMG - Emotion Challenge Solution [article]

Yuqi Cui, Xiao Zhang, Yang Wang, Chenfeng Guo, Dongrui Wu
2018 arXiv   pre-print
This short paper describes our solution to the 2018 IEEE World Congress on Computational Intelligence One-Minute Gradual-Emotional Behavior Challenge, whose goal was to estimate continuous arousal and valence values from short videos. We designed four base regression models using visual and audio features, and then used a spectral approach to fuse them to obtain improved performance.
arXiv:1805.00348v1 fatcat:dfhjovkejrhw3jz7ojwoaeazg4

Photoacoustic Drug Delivery

Yuqi Zhang, Jicheng Yu, Anna Kahkoska, Zhen Gu
2017 Sensors  
Recently, Zhang et al. synthesized an electron donor-acceptor (D-A) conjugated polymer for light absorption [108] .  ... 
doi:10.3390/s17061400 pmid:28617354 pmcid:PMC5492670 fatcat:nong6sdt2jff3bti2ebyrucrju

DNA charge transport: Moving beyond 1D

Yuqi Zhang, William B. Zhang, Chaoren Liu, Peng Zhang, Alexander Balaeff, David N. Beratan
2016 Surface Science  
Charge transport across novel DNA junctions has been studied for several decades. From early attempts to move charge across DNA double crossover junctions to recent studies on DNA three-way junctions and G4 motifs, it is becoming clear that efficient cross-junction charge migration requires strong base-to-base electronic coupling at the junction, facilitated by favorable pi-stacking. We review recent progress toward the goal of manipulating and controlling charge transport through DNA junctions.
doi:10.1016/j.susc.2016.03.011 fatcat:xr3ujqjtobbcrg3g64py5l6isu

Emergence of Machine Language: Towards Symbolic Intelligence with Neural Networks [article]

Yuqi Wang, Xu-Yao Zhang, Cheng-Lin Liu, Zhaoxiang Zhang
2022 arXiv   pre-print
Representation is a core issue in artificial intelligence. Humans use discrete language to communicate and learn from each other, while machines use continuous features (like vector, matrix, or tensor in deep neural networks) to represent cognitive patterns. Discrete symbols are low-dimensional, decoupled, and have strong reasoning ability, while continuous features are high-dimensional, coupled, and have incredible abstracting capabilities. In recent years, deep learning has developed the idea
more » ... of continuous representation to the extreme, using millions of parameters to achieve high accuracies. Although this is reasonable from the statistical perspective, it has other major problems like lacking interpretability, poor generalization, and is easy to be attacked. Since both paradigms have strengths and weaknesses, a better choice is to seek reconciliation. In this paper, we make an initial attempt towards this direction. Specifically, we propose to combine symbolism and connectionism principles by using neural networks to derive a discrete representation. This process is highly similar to human language, which is a natural combination of discrete symbols and neural systems, where the brain processes continuous signals and represents intelligence via discrete language. To mimic this functionality, we denote our approach as machine language. By designing an interactive environment and task, we demonstrated that machines could generate a spontaneous, flexible, and semantic language through cooperation. Moreover, through experiments we show that discrete language representation has several advantages compared with continuous feature representation, from the aspects of interpretability, generalization, and robustness.
arXiv:2201.05489v1 fatcat:aw4rk4brqjfzjk4y676f66qkaa

2nd Place Solution to Google Landmark Retrieval 2021 [article]

Zhang Yuqi, Xu Xianzhe, Chen Weihua, Wang Yaohua, Zhang Fangyi, Wang Fan, Li Hao
2021 arXiv   pre-print
This paper presents the 2nd place solution to the Google Landmark Retrieval 2021 Competition on Kaggle. The solution is based on a baseline with training tricks from person re-identification, a continent-aware sampling strategy is presented to select training images according to their country tags and a Landmark-Country aware reranking is proposed for the retrieval task. With these contributions, we achieve 0.52995 mAP@100 on private leaderboard. Code available at
more » ... 991/Google_Landmark_Retrieval_2021_2nd_Place_Solution
arXiv:2110.04294v1 fatcat:3un4enqyqjfnbmdjke5rhdb7pu

Adaptive Feature Representation for Visual Tracking [article]

Yuqi Han, Chenwei Deng, Zengshuo Zhang, Jiatong Li, Baojun Zhao
2017 arXiv   pre-print
Robust feature representation plays significant role in visual tracking. However, it remains a challenging issue, since many factors may affect the experimental performance. The existing method which combine different features by setting them equally with the fixed weight could hardly solve the issues, due to the different statistical properties of different features across various of scenarios and attributes. In this paper, by exploiting the internal relationship among these features, we
more » ... p a robust method to construct a more stable feature representation. More specifically, we utilize a co-training paradigm to formulate the intrinsic complementary information of multi-feature template into the efficient correlation filter framework. We test our approach on challenging se- quences with illumination variation, scale variation, deformation etc. Experimental results demonstrate that the proposed method outperforms state-of-the-art methods favorably.
arXiv:1705.04442v1 fatcat:az5mdtk6mvakdd42qbu7ikocva

On the sum of simultaneously proximinal sets [article]

Longfa Sun, Yuqi Sun, Wen Zhang, Zheming Zheng
2020 arXiv   pre-print
In this paper, we show that the sum of a compact convex subset and a simultaneously τ-strongly proximinal convex subset (resp. simultaneously approximatively τ-compact convex subset) of a Banach space X is simultaneously tau-strongly proximinal (resp. simultaneously approximatively τ-compact ), and the sum of weakly compact convex subset and a simultaneously approximatively weakly compact convex subset of X is still simultaneously approximatively weakly compact, where τ is the norm or the weak
more » ... opology. Moreover, some related results on the sum of simultaneously proximinal subspaces are presented.
arXiv:2002.11961v1 fatcat:c6mdks4kf5bwvetrneikv5ponq

Correlation Tracking via Robust Region Proposals [article]

Yuqi Han, Jinghong Nan, Zengshuo Zhang, Jingjing Wang, Baojun Zhao
2018 arXiv   pre-print
Recently, correlation filter-based trackers have received extensive attention due to their simplicity and superior speed. However, such trackers perform poorly when the target undergoes occlusion, viewpoint change or other challenging attributes due to pre-defined sampling strategy. To tackle these issues, in this paper, we propose an adaptive region proposal scheme to facilitate visual tracking. To be more specific, a novel tracking monitoring indicator is advocated to forecast tracking
more » ... . Afterwards, we incorporate detection and scale proposals respectively, to recover from model drift as well as handle aspect ratio variation. We test the proposed algorithm on several challenging sequences, which have demonstrated that the proposed tracker performs favourably against state-of-the-art trackers.
arXiv:1806.05530v1 fatcat:zsc52if72jbyfo4r52wrrbti7i

Dynamic Duo: Synergy between Cancer Radiation Therapy and Immunotherapy

Yuqi Zhang, Manchao Zhang
2016 Immunotherapy Open Access  
Citation: Yuqi Zhang, Manchao Zhang (2016) Dynamic Duo: Synergy between Cancer Radiation Therapy and Immunotherapy .  ...  Immunother Open Acc 2: 107. doi:10.4172/2471-9552.1000107 Immunother Open Acc ISSN:2471-9552 IMT, an open access journal Volume 2 • Issue 1 • 1000107 Page 2 of 7 Citation: Yuqi Zhang, Manchao Zhang  ... 
doi:10.4172/2471-9552.1000107 fatcat:6rpyzu6eczc37iixhjme3gf4ei

Broadband Terahertz Wave Emission from Liquid Metal [article]

Yuqi Cao, Yiwen E, Pingjie Huang, X.-C. Zhang
2020 arXiv   pre-print
Metals have been studied as terahertz sources for decades. Recent research has shown the potential of metals in generating extremely high THz pulse energy excited by intense laser pulses. To avoid the metal surface debris caused by laser pulses, here, we report the results of the broadband terahertz wave emission from a flowing liquid metal line excited by sub-picosecond laser pulses. The THz signal emitted from the liquid gallium line shows stronger field with broader bandwidth comparing with
more » ... he signal from water under the identical optical excitation conditions. Our preliminary study suggests that the liquid metals have the potential to serve as efficient and powerful THz sources for the intense lasers with a high repetition rate.
arXiv:2006.01946v1 fatcat:njkcutwxtbh4bmup7dlwfohequ

SN-Graph: a Minimalist 3D Object Representation for Classification [article]

Siyu Zhang, Hui Cao, Yuqi Liu, Shen Cai, Yanting Zhang, Yuanzhan Li, Xiaoyu Chi
2021 arXiv   pre-print
Using deep learning techniques to process 3D objects has achieved many successes. However, few methods focus on the representation of 3D objects, which could be more effective for specific tasks than traditional representations, such as point clouds, voxels, and multi-view images. In this paper, we propose a Sphere Node Graph (SN-Graph) to represent 3D objects. Specifically, we extract a certain number of internal spheres (as nodes) from the signed distance field (SDF), and then establish
more » ... tions (as edges) among the sphere nodes to construct a graph, which is seamlessly suitable for 3D analysis using graph neural network (GNN). Experiments conducted on the ModelNet40 dataset show that when there are fewer nodes in the graph or the tested objects are rotated arbitrarily, the classification accuracy of SN-Graph is significantly higher than the state-of-the-art methods.
arXiv:2105.14784v1 fatcat:qlfc7xeynnfodi4fqjn37mqqfy

Sexism-Related Stigma Affects Pain Perception

Ming Zhang, Yuqi Zhang, Zhihui Li, Li Hu, Yazhuo Kong, Jianzhong Su
2021 Neural Plasticity  
People with stigmatized characteristics tend to be devalued by others in a given society. The negative experiences related to stigma cause individuals to struggle as they would if they were in physical pain and bring various negative outcomes in the way that physical pain does. However, it is unclear whether stigma related to one's identity would affect their perception of physical pain. To address this issue, using sexism-related paradigms, we found that females had reduced pain
more » ... ance in the Cold Pressor Test (Experiment 1) and an increased rating for nociceptive laser stimuli with fixed intensity (Experiment 2). Additionally, we observed that there was a larger laser-evoked N1, an early laser-evoked P2, and a larger magnitude of low-frequency component in laser-evoked potentials (LEPs) in the stigma condition than in the control condition (Experiment 3). Our study provides behavioral and electrophysiological evidence that sexism-related stigma affects the pain perception of females.
doi:10.1155/2021/6612456 pmid:33854543 pmcid:PMC8019650 fatcat:hc2bcp3l6fetpkbuya2hnyexl4
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