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Your search keyword '"Zhao, Yufan"' showing total 269 results
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269 results on '"Zhao, Yufan"'

1. Rivoceranib, a VEGFR-2 inhibitor, monotherapy in previously treated patients with advanced or metastatic gastric or gastroesophageal junction cancer (ANGEL study): an international, randomized, placebo-controlled, phase 3 trial

Author

Kang, Yoon-Koo, Ryu, Min-Hee, Di Bartolomeo, Maria, Chau, Ian, Yoon, Harry, Kim, Jong Gwang, Lee, Keun-Wook, Oh, Sang Chul, Takashima, Atsuo, Kryzhanivska, Anna, Chao, Yee, Evesque, Ludovic, Schenker, Michael, McGinn, Arlo, Zhao, Yufan, Lee, Jennifer, Wyrwicz, Lucjan, and Boku, Narikazu

Published
2024
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2. Optimization of directional energy deposition forming process of high-strength aluminum alloy based on laser mode control

Author

SHI Donglai, JIA Chewang, SUN Liushuo, ZHAO Yufan, YANG Haiou, and LIN Xin

Subjects
directional energy deposition, high-strength aluminum alloy, laser mode control, forming quality, microstructure, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

Due to the low boiling points of the main constituents of 7075 aluminum alloy and the high surface tension gradient of the molten alloy， combined with the uneven energy distribution of the circular Gaussian （CG） laser beam spot commonly used in directed energy deposition （DED） processes， the forming quality of 7075 aluminum alloy DED specimens is generally poor. This significantly restricts the further application of DED in 7075 aluminum alloy. By regulating the laser mode， it is possible to effectively modify the temperature and flow fields of the melt pool， as well as the corresponding solidification conditions. Thus， the forming quality of laser additive manufacturing specimens and the active control of microstructure are improved. An off-axis parabolic integrating mirror is employed to homogenize the CG laser mode into a circular flat-top （CF） laser mode， which is further tilted to achieve a transversely elliptical flat-top （TE） laser mode. Using these three different laser modes， single-track cladding， single-wall structures， and 7075 aluminum alloy in DED block specimens are prepared. Combined with numerical simulations， the influence laws and underlying mechanisms of the laser modes on the forming quality and solidification structure are revealed. The simulation results indicate that by modulating the laser beam spot from the conventional CG laser mode to the CF and TE laser modes， the uniformity of the heat flux on the surface of the cladding layer is significantly improved， subsequently reducing the temperature gradient of the melt， and increasing the solidification rate. Compared to the CG laser mode， the surface forming quality of single-wall structures and block specimens under the CF and TE laser modes is significantly enhanced. The width variation of the single-wall structures is greatly reduced， and the dimensional accuracy in the horizontal direction of the block specimens is improved. Additionally， the density of the block specimens increases from 95.8% to 97.2% and 97.7%， respectively. In terms of solidification structure， the texture is significantly weakened， the grain size is reduced by approximately 50%， and the number of nano-precipitated η-phase within the grains is also increased.

Published
2024
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7. Are Pre-trained Language Models Knowledgeable to Ground Open Domain Dialogues?

Author

Zhao, Yufan, Wu, Wei, and Xu, Can

Subjects
Computer Science - Computation and Language
Abstract

We study knowledge-grounded dialogue generation with pre-trained language models. Instead of pursuing new state-of-the-art on benchmarks, we try to understand if the knowledge stored in parameters of the pre-trained models is already enough to ground open domain dialogues, and thus allows us to get rid of the dependency on external knowledge sources in generation. Through extensive experiments on benchmarks, we find that by fine-tuning with a few dialogues containing knowledge, the pre-trained language models can outperform the state-of-the-art model that requires external knowledge in automatic evaluation and human judgment, suggesting a positive answer to the question we raised.

Published
2020

9. Zero-Resource Knowledge-Grounded Dialogue Generation

Author

Li, Linxiao, Xu, Can, Wu, Wei, Zhao, Yufan, Zhao, Xueliang, and Tao, Chongyang

Subjects
Computer Science - Computation and Language
Abstract

While neural conversation models have shown great potentials towards generating informative and engaging responses via introducing external knowledge, learning such a model often requires knowledge-grounded dialogues that are difficult to obtain. To overcome the data challenge and reduce the cost of building a knowledge-grounded dialogue system, we explore the problem under a zero-resource setting by assuming no context-knowledge-response triples are needed for training. To this end, we propose representing the knowledge that bridges a context and a response and the way that the knowledge is expressed as latent variables, and devise a variational approach that can effectively estimate a generation model from a dialogue corpus and a knowledge corpus that are independent with each other. Evaluation results on three benchmarks of knowledge-grounded dialogue generation indicate that our model can achieve comparable performance with state-of-the-art methods that rely on knowledge-grounded dialogues for training, and exhibits a good generalization ability over different topics and different datasets., Comment: Accepted by NeurIPS 2020

Published
2020

10. Learning a Simple and Effective Model for Multi-turn Response Generation with Auxiliary Tasks

Author

Zhao, Yufan, Xu, Can, Wu, Wei, and Yu, Lei

Subjects
Computer Science - Computation and Language
Abstract

We study multi-turn response generation for open-domain dialogues. The existing state-of-the-art addresses the problem with deep neural architectures. While these models improved response quality, their complexity also hinders the application of the models in real systems. In this work, we pursue a model that has a simple structure yet can effectively leverage conversation contexts for response generation. To this end, we propose four auxiliary tasks including word order recovery, utterance order recovery, masked word recovery, and masked utterance recovery, and optimize the objectives of these tasks together with maximizing the likelihood of generation. By this means, the auxiliary tasks that relate to context understanding can guide the learning of the generation model to achieve a better local optimum. Empirical studies with three benchmarks indicate that our model can significantly outperform state-of-the-art generation models in terms of response quality on both automatic evaluation and human judgment, and at the same time enjoys a much faster decoding process.

Published
2020

26. Achieving superior strength-plasticity performance in laser powder bed fusion of AlSi10Mg via high-speed scanning remelting.

Author

Shi, Shuoqing, Zhao, Yufan, Yang, Haiou, Jia, Chewang, Deng, Haoyuan, Zhang, Tianchi, Lin, Xin, and Huang, Weidong

Subjects
POWDERS, MICROSTRUCTURE, LASERS, ALLOYS, ALUMINUM alloys
Abstract

The limited mechanical properties of Al–Si alloys hinder their application in demanding and extreme conditions. The cracking tendency of high-strength aluminum alloys and high-cost of rare-earth elements pose challenges for the large-scale application of aluminum alloys in additive manufacturing. The novel and practical high-speed scanning remelting proposed in this study enables Al–Si alloys to exhibit significant proportion of fine microstructures and nano-precipitates, surpassing the mechanical properties of aluminum alloys fabricated by normal methods with exceptional strength (496.1 ± 5.8 MPa) and plasticity (21.4 ± 0.9%). This in-situ microstructure control method opens new pathways for the application in demanding engineering contexts. [ABSTRACT FROM AUTHOR]

Published
2024
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27. The Effect of Restorative Environment and Presence Based on Virtual Reality for Anxiety and Depression

Author

Wang, Zhimeng, An, Jingchen, Zhao, Yufan, Wang, Ziyi, Yu, Yue, Jiang, Ting, Wu, Jianping, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Ahram, Tareq Z., editor, and Falcão, Christianne S., editor

Published
2021
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28. Cannabidiol Inhibits Epithelial Ovarian Cancer: Role of Gut Microbiome

Author

Cao, Danli, primary, Lin, Yiru, additional, Lin, Caiji, additional, Xu, Mengzhi, additional, Wang, Jiaxing, additional, Zeng, Zheng, additional, Wang, Pengfei, additional, Li, Qinghai, additional, Wang, Xiaoyu, additional, Wang, Wenxue, additional, Luo, Lingjie, additional, Zhao, Yufan, additional, Shi, Yongwei, additional, Gao, Zixiang, additional, Kang, Xin, additional, Wang, Shuang, additional, Zhang, Yuanyuan, additional, Xu, Xiaohui, additional, Liu, Shu-Lin, additional, and Liu, Huidi, additional

Published
2024
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34. On Trading American Put Options with Interactive Volatility

Author

Assing, Sigurd and Zhao, Yufan

Subjects
Quantitative Finance - Pricing of Securities, Mathematics - Probability, 60G40 (Primary) 60J28 (Secondary)
Abstract

We introduce a simple stochastic volatility model, whose novelty consists in taking into account hitting times of the asset price, and study the optimal stopping problem corresponding to a put option whose time horizon (after the asset price hits a certain level) is exponentially distributed. We obtain explicit optimal stopping rules in various cases one of which is interestingly complex because of an unexpected disconnected continuation region. Finally, we discuss in detail how these stopping rules could be used for trading an American put when the trader expects a market drop in the near future., Comment: improved version (minor corrections), 28 pages, 6 figures

Published
2014

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