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541 results on '"Cai, Yuanyuan"'

103. Soluble ST2 Is a Sensitive and Specific Biomarker for Fulminant Myocarditis

Author

Wang, Jin, primary, He, Mengying, additional, Li, Huihui, additional, Chen, Yanghui, additional, Nie, Xiang, additional, Cai, Yuanyuan, additional, Xie, Rong, additional, Li, Lijuan, additional, Chen, Peng, additional, Sun, Yang, additional, Li, Chenze, additional, Yu, Ting, additional, Zuo, Houjuan, additional, Cui, Guanglin, additional, Miao, Kun, additional, Zhao, Chunxia, additional, Jiang, Jiangang, additional, Heidecker, Bettina, additional, Barnett, Olga, additional, Maisel, Alan, additional, Chen, Chen, additional, and Wang, Dao Wen, additional

Published
2022
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114. Development of a rapid measurement system for coarse aggregate morphological parameters

Author

Ning Lv, Cai Yuanyuan, Hejun Zhu, and Huaiying Fang

Subjects
Measure (data warehouse), Scanner, Accuracy and precision, Aggregate (composite), business.industry, General Chemical Engineering, System of measurement, Flatness (systems theory), 02 engineering and technology, 021001 nanoscience & nanotechnology, Sphericity, Asphalt concrete, 020401 chemical engineering, General Materials Science, 0204 chemical engineering, 0210 nano-technology, Biological system, business, Mathematics
Abstract

Morphological parameters of coarse aggregates, including the angularity index (AI), flat and elongated ratio, flatness ratio, and sphericity, strongly affect the performance of asphalt concrete. A device must be developed to efficiently and accurately measure these parameters. Herein, a charge-coupled device camera and a linear profile scanner are combined to evaluate the parameters. The AI is calculated using three methods. The results show that the fitted-ellipse method provides superior results among the three AI measurement methods. Moreover, the use of a linear profile scanner improves the AI measurement accuracy. Therefore, the proposed combination has high measurement efficiency and is suitable for batch inspections.

Published
2020

117. The independent characterization and experimental study of coarse aggregate angularity

Author

Fang Huaiying, Su Xu, Hejun Zhu, Cai Yuanyuan, Ning Lv, and Yang Jianhong

Subjects
Materials science, Aggregate (composite), business.industry, General Chemical Engineering, 02 engineering and technology, 021001 nanoscience & nanotechnology, Compression method, Characterization (materials science), Asphalt concrete, 020401 chemical engineering, Particle size, 0204 chemical engineering, Composite material, 0210 nano-technology, business
Abstract

The morphological parameters of coarse aggregates, including the angularity, flat and elongated (FE) and particle size, strongly influence the performance of asphalt concrete. At present, the measu...

Published
2019

122. Atomic-interface strategy and N,O co-doping enable WS2 electrodes with ultrafast ion transport rate in sodium-ion batteries.

Author

Han, Meisheng, Mu, Yongbiao, Cai, Yuanyuan, Wei, Lei, Zeng, Lin, and Zhao, Tianshou

Abstract

The high theoretical capacity and graphene-like structure enable WS2 to be a promising anode material for fast-charging sodium-ion batteries. However, poor intrinsic electrical conductivity and large Na+-diffusion energy barrier limit its practical applications. Here, an atomic-interface strategy and N,O co-doping were first introduced for WS2 electrodes to obtain a unique WS2/C nanocomposite. The atomic-interface strategy that allowed the construction of a unilamellar interoverlapped superstructure maximized the contact area of WS2 and C, thus significantly improving the electrical conductivity and decreasing the Na+-diffusion energy barrier of WS2 electrodes during cycling. More importantly, the atomic-interface strategy suppressed the growth of superparamagnetic W metallic nanoparticles during conversion reactions, resulting in a strong surface-capacitance effect to boost the Na+ transport. Besides, N,O co-doping changed the electronic structure of WS2 to decrease the bandgap from 1.6 to 0 eV and enlarged the interlayer spacing between WS2 and C, thus boosting the electron and ion transport. Consequently, WS2/C exhibited an ultrafast Na+-storage capability (450.8 mA h g−1 at 13 A g−1), with an ultrahigh capacity of 669.2 mA h g−1 at 0.065 A g−1 and an ultralong lifetime of over 3000 cycles at 6.5 A g−1 in half-cells. Further, the full-cells showed superior fast-charging capability with an 80.6% capacity retention at 1.95 A g−1. [ABSTRACT FROM AUTHOR]

Published
2022
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127. Properties of defect modes in two-dimensional organic octagonal quasicrystals at low dielectric contrast

Author

Xiao Chen, Cai Yuanyuan, Changwei Li, Yiquan Wang, Zhi Wang, Xiaoqing Wang, and Shuai Feng

Subjects
Materials science, Rotational symmetry, Physics::Optics, 02 engineering and technology, 01 natural sciences, law.invention, Vertical-cavity surface-emitting laser, 010309 optics, Optics, law, 0103 physical sciences, OLED, Electrical and Electronic Engineering, Physical and Theoretical Chemistry, Photonic crystal, Coupling, business.industry, Quasicrystal, 021001 nanoscience & nanotechnology, Laser, Atomic and Molecular Physics, and Optics, Electronic, Optical and Magnetic Materials, Organic semiconductor, Optoelectronics, 0210 nano-technology, business
Abstract

We study theoretically the localization and coupling properties of defect modes in octagonal quasi-crystals made of conjugated polymers for the light modulation of organic light-emitting devices (OLED) and organic lasers. Due to the rotational symmetry of quasicrystals and the low refractive-index of organic semiconductors, it is observed that localized modes only occur in the complex defect-cavity structures. Unlike conventional photonic crystals with high-index, some unusual characteristics of defect modes coupling in quasicrystals under the low-index contrast are revealed and analyzed, such as the loss of defect modes, composite resonant cavity, and phase-opposition of modal tails. These results will allow us to better utilize the light control in organic photonic crystal microcavity lasers, especially in the localization region, and further to apply in OLED and VCSEL (Vertical Cavity Surface Emitting Laser) fields.

Published
2018

130. 立式三反离轴相机光机结构设计

Author

李庆林 Li Qinglin, 蔡媛媛 Cai Yuanyuan, 张志飞 Zhang Zhifei, 常君磊 Chang Junlei, and 张楠 Zhang Nan

Subjects
Space and Planetary Science, Aerospace Engineering, Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics
Published
2022

133. Octagonal Quasicrystal Defect Mode Laser-Based PVK: Ir(ppy) 3 Polymer Driven by Optical Pumping.

Author

Cai, Yuanyuan, Zhang, Shuai, Wu, Chenyu, Wang, Zhiwei, Xu, Weiran, Chen, Xiao, and Wang, Yiquan

Abstract

Based on the conjugated complex PVK: Ir(ppy)3, a green-emitting organic quasicrystal microcavity laser is demonstrated driven by optical pumping. The organic laser adopts a sandwich structure of DBR/organic gain membrane/output Ag-layer for the vertical oscillation and an octagonal quasi-crystal for in-plane light localization. The experimental results show that the single-mode lasing action is observed at 521 nm with an FWHM of 0.8 nm. The threshold of lasing is lowered to 0.181 μJ/cm2. [ABSTRACT FROM AUTHOR]

Published
2022
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141. Image Localized Style Transfer to Design Clothes Based on CNN and Interactive Segmentation

Author

Haitao Xiong, Cai Yuanyuan, and Hanying Wang

Subjects
Article Subject, General Computer Science, Computer science, General Mathematics, Computer applications to medicine. Medical informatics, R858-859.7, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Neurosciences. Biological psychiatry. Neuropsychiatry, 02 engineering and technology, Image (mathematics), Clothing, Position (vector), 0202 electrical engineering, electronic engineering, information engineering, Image Processing, Computer-Assisted, Computer vision, Segmentation, Rectangle, ComputingMethodologies_COMPUTERGRAPHICS, business.industry, General Neuroscience, Deep learning, 020207 software engineering, General Medicine, Total variation denoising, 020201 artificial intelligence & image processing, Artificial intelligence, Neural Networks, Computer, business, Distance transform, Algorithms, RC321-571, Research Article
Abstract

In recent years, image style transfer has been greatly improved by using deep learning technology. However, when directly applied to clothing style transfer, the current methods cannot allow the users to self-control the local transfer position of an image, such as separating specific T-shirt or trousers from a figure, and cannot achieve the perfect preservation of clothing shape. Therefore, this paper proposes an interactive image localized style transfer method especially for clothes. We introduce additional image called outline image, which is extracted from content image by interactive algorithm. The interaction consists simply of dragging a rectangle around the desired clothing. Then, we introduce an outline loss function based on distance transform of the outline image, which can achieve the perfect preservation of clothing shape. In order to smooth and denoise the boundary region, total variation regularization is employed. The proposed method constrains that the new style is generated only in the desired clothing part rather than the whole image including background. Therefore, in our new generated images, the original clothing shape can be reserved perfectly. Experiment results show impressive generated clothing images and demonstrate that this is a good approach to design clothes.

Published
2020

142. A Bichannel Transformer with Context Encoding for Document-Driven Conversation Generation in Social Media

Author

Qingchuan Zhang, Cai Yuanyuan, Ke Li, Haitao Xiong, and Min Zuo

Subjects
Multidisciplinary, General Computer Science, Article Subject, Computer science, media_common.quotation_subject, QA75.5-76.95, Neglect, Recurrent neural network, Human–computer interaction, Electronic computers. Computer science, Social media, Conversation, Utterance, Transformer (machine learning model), media_common
Abstract

Along with the development of social media on the internet, dialogue systems are becoming more and more intelligent to meet users’ needs for communication, emotion, and social intercourse. Previous studies usually use sequence-to-sequence learning with recurrent neural networks for response generation. However, recurrent-based learning models heavily suffer from the problem of long-distance dependencies in sequences. Moreover, some models neglect crucial information in the dialogue contexts, which leads to uninformative and inflexible responses. To address these issues, we present a bichannel transformer with context encoding (BCTCE) for document-driven conversation. This conversational generator consists of a context encoder, an utterance encoder, and a decoder with attention mechanism. The encoders aim to learn the distributed representation of input texts. The multihop attention mechanism is used in BCTCE to capture the interaction between documents and dialogues. We evaluate the proposed BCTCE by both automatic evaluation and human judgment. The experimental results on the dataset CMU_DoG indicate that the proposed model yields significant improvements over the state-of-the-art baselines on most of the evaluation metrics, and the generated responses of BCTCE are more informative and more relevant to dialogues than baselines.

Published
2020

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