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Your search keyword '"Yan, Ziyue"' showing total 14 results
Start Over Author "Yan, Ziyue" Publication Type Academic Journals
14 results on '"Yan, Ziyue"'

1. Beam test of a monolithic active pixel sensor for the CEPC vertex detector

Author

Li, Shuqi, Wu, Tianya, Huang, Xinhui, Yan, Ziyue, Zhou, Jia, Zhang, Xiaoxu, Hu, Yiming, Wang, Wei, Zeng, Hao, Jia, Xuewei, Liang, Zhijun, Wei, Wei, Zhang, Ying, Wei, Xiaomin, Qi, Ming, Zhang, Lei, Hu, Jun, Fu, Jinyu, Zhang, Hongyu, Li, Gang, Wu, Linghui, Dong, Mingyi, Li, Xiaoting, Casanova, Raimon, Zhang, Liang, Dong, Jianing, Wang, Jia, Zheng, Ran, Lu, Weiguo, Grinstein, Sebastian, and da Costa, João Guimarães

Published
2024
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3. Beam test of a 180 nm CMOS Pixel Sensor for the CEPC vertex detector

Author

Wu, Tianya, Li, Shuqi, Wang, Wei, Zhou, Jia, Yan, Ziyue, Hu, Yiming, Zhang, Xiaoxu, Liang, Zhijun, Wei, Wei, Zhang, Ying, Wei, Xiaomin, Huang, Xinhui, Zhang, Lei, Qi, Ming, Zeng, Hao, Jia, Xuewei, Hu, Jun, Fu, Jinyu, Zhang, Hongyu, Li, Gang, Wu, Linghui, Dong, Mingyi, Li, Xiaoting, Casanova, Raimon, Zhang, Liang, Dong, Jianing, Wang, Jia, Zheng, Ran, Lu, Weiguo, Grinstein, Sebastian, and da Costa, João Guimarães

Published
2024
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5. Implementation and performances of the IPbus protocol for the JUNO Large-PMT readout electronics

Author

Triozzi, Riccardo, Serafini, Andrea, Bellato, Marco, Bergnoli, Antonio, Bolognesi, Matteo, Brugnera, Riccardo, Cerrone, Vanessa, Chen, Chao, Clerbaux, Barbara, Coppi, Alberto, Corti, Daniele, dal Corso, Flavio, Dong, Jianmeng, Dou, Wei, Fan, Lei, Garfagnini, Alberto, Gavrikov, Arsenii, Gong, Guanghua, Grassi, Marco, Guizzetti, Rosa Maria, Hang, Shuang, He, Cong, Hu, Jun, Isocrate, Roberto, Jelmini, Beatrice, Ji, Xiaolu, Jiang, Xiaoshan, Li, Fei, Liang, Zehong, Lippi, Ivano, Liu, Hongbang, Liu, Hongbin, Liu, Shenghui, Liu, Xuewei, Luo, Daibin, Luo, Ronghua, Marini, Filippo, Mazzaro, Daniele, Modenese, Luciano, Molla, Marta Colomer, Ning, Zhe, Peng, Yu, Petitjean, Pierre-Alexandre, Pitacco, Alberto, Qi, Mengyao, Ramina, Loris, Rampazzo, Mirco, Rebeschini, Massimo, Redchuk, Mariia, Sun, Yunhua, Triossi, Andrea, Veronese, Fabio, von Sturm, Katharina, Wang, Peiliang, Wang, Peng, Wang, Yangfu, Wang, Yusheng, Wang, Yuyi, Wang, Zheng, Wei, Ping, Weng, Jun, Xian, Shishen, Xie, Xiaochuan, Xu, Benda, Xu, Chuang, Xu, Donglian, Xu, Hai, Yan, Xiongbo, Yan, Ziyue, Yang, Fengfan, Yang, Yan, Yang, Yifan, Ye, Mei, Zeng, Tingxuan, Zhang, Shuihan, Zhang, Wei, Zhang, Aiqiang, Zhang, Bin, Zhao, Siyao, Zi, Changge, Aiello, Sebastiano, Andronico, Giuseppe, Antonelli, Vito, Barresi, Andrea, Basilico, Davide, Beretta, Marco, Brigatti, Augusto, Bruno, Riccardo, Budano, Antonio, Caccianiga, Barbara, Cammi, Antonio, Campese, Stefano, Chiesa, Davide, Clementi, Catia, Cordelli, Marco, Dusini, Stefano, Fabbri, Andrea, Felici, Giulietto, Ferraro, Federico, Giammarchi, Marco Giulio, Landini, Cecilia, Lombardi, Paolo, Lombardo, Claudio, Maino, Andrea, Mantovani, Fabio, Mari, Stefano Maria, Martini, Agnese, Meroni, Emanuela, Miramonti, Lino, Montuschi, Michele, Nastasi, Massimiliano, Orestano, Domizia, Ortica, Fausto, Paoloni, Alessandro, Parmeggiano, Sergio, Petrucci, Fabrizio, Previtali, Ezio, Ranucci, Gioacchino, Re, Alessandra Carlotta, Ricci, Barbara, Romani, Aldo, Saggese, Paolo, Sanfilippo, Simone, Sirignano, Chiara, Sisti, Monica, Stanco, Luca, Strati, Virginia, Tortorici, Francesco, Tuvé, Cristina, Venettacci, Carlo, Verde, Giuseppe, and Votano, Lucia

Published
2023
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6. Validation and integration tests of the JUNO 20-inch PMT readout electronics

Author

Cerrone, Vanessa, von Sturm, Katharina, Bellato, Marco, Bergnoli, Antonio, Bolognesi, Matteo, Brugnera, Riccardo, Chen, Chao, Clerbaux, Barbara, Coppi, Alberto, dal Corso, Flavio, Corti, Daniele, Dong, Jianmeng, Dou, Wei, Fan, Lei, Garfagnini, Alberto, Gong, Guanghua, Grassi, Marco, Hang, Shuang, Guizzetti, Rosa Maria, He, Cong, Hu, Jun, Isocrate, Roberto, Jelmini, Beatrice, Ji, Xiaolu, Jiang, Xiaoshan, Li, Fei, Liang, Zehong, Lippi, Ivano, Liu, Hongbang, Liu, Hongbin, Liu, Shenghui, Liu, Xuewei, Luo, Daibin, Luo, Ronghua, Marini, Filippo, Mazzaro, Daniele, Modenese, Luciano, Ning, Zhe, Peng, Yu, Petitjean, Pierre-Alexandre, Pitacco, Alberto, Qi, Mengyao, Ramina, Loris, Rampazzo, Mirco, Rebeschini, Massimo, Redchuk, Mariia, Serafini, Andrea, Sun, Yunhua, Triossi, Andrea, Triozzi, Riccardo, Veronese, Fabio, Wang, Peiliang, Wang, Peng, Wang, Yangfu, Wang, Yusheng, Wang, Yuyi, Wang, Zheng, Wei, Ping, Weng, Jun, Xian, Shishen, Xie, Xiaochuan, Xu, Benda, Xu, Chuang, Xu, Donglian, Xu, Hai, Yan, Xiongbo, Yan, Ziyue, Yang, Fengfan, Yang, Yan, Yang, Yifan, Ye, Mei, Zeng, Tingxuan, Zhang, Shuihan, Zhang, Wei, Zhang, Aiqiang, Zhang, Bin, Zhao, Siyao, Zi, Changge, Aiello, Sebastiano, Andronico, Giuseppe, Antonelli, Vito, Barresi, Andrea, Basilico, Davide, Beretta, Marco, Brigatti, Augusto, Bruno, Riccardo, Budano, Antonio, Caccianiga, Barbara, Cammi, Antonio, Campese, Stefano, Chiesa, Davide, Clementi, Catia, Cordelli, Marco, Dusini, Stefano, Fabbri, Andrea, Felici, Giulietto, Ferraro, Federico, Giammarchi, Marco G., Landini, Cecilia, Lombardi, Paolo, Lombardo, Claudio, Maino, Andrea, Mantovani, Fabio, Mari, Stefano Maria, Martini, Agnese, Meroni, Emanuela, Miramonti, Lino, Montuschi, Michele, Nastasi, Massimiliano, Orestano, Domizia, Ortica, Fausto, Paoloni, Alessandro, Parmeggiano, Sergio, Petrucci, Fabrizio, Previtali, Ezio, Ranucci, Gioacchino, Re, Alessandra Carlotta, Ricci, Barbara, Romani, Aldo, Saggese, Paolo, Sanfilippo, Simone, Sirignano, Chiara, Sisti, Monica, Stanco, Luca, Strati, Virginia, Tortorici, Francesco, Tuvé, Cristina, Venettacci, Carlo, Verde, Giuseppe, and Votano, Lucia

Published
2023
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7. Mass testing of the JUNO experiment 20-inch PMT readout electronics

Author

Coppi, Alberto, Jelmini, Beatrice, Bellato, Marco, Bergnoli, Antonio, Bolognesi, Matteo, Brugnera, Riccardo, Cerrone, Vanessa, Chen, Chao, Clerbaux, Barbara, Colomer Molla, Marta, Corti, Daniele, dal Corso, Flavio, Dong, Jianmeng, Dou, Wei, Fan, Lei, Garfagnini, Alberto, Gavrikov, Arsenii, Gong, Guanghua, Grassi, Marco, Guizzetti, Rosa Maria, Hang, Shuang, He, Cong, Hu, Jun, Isocrate, Roberto, Ji, Xiaolu, Jiang, Xiaoshan, Li, Fei, Liang, Zehong, Lippi, Ivano, Liu, Hongbang, Liu, Hongbin, Liu, Shenghui, Liu, Xuewei, Luo, Daibin, Luo, Ronghua, Marini, Filippo, Mazzaro, Daniele, Modenese, Luciano, Ning, Zhe, Peng, Yu, Petitjean, Pierre-Alexandre, Pitacco, Alberto, Qi, Mengyao, Ramina, Loris, Rampazzo, Mirco, Rebeschini, Massimo, Redchuk, Mariia, Serafini, Andrea, Sun, Yunhua, Triossi, Andrea, Triozzi, Riccardo, Veronese, Fabio, von Sturm, Katharina, Wang, Peiliang, Wang, Peng, Wang, Yangfu, Wang, Yusheng, Wang, Yuyi, Wang, Zheng, Wei, Ping, Weng, Jun, Xian, Shishen, Xie, Xiaochuan, Xu, Benda, Xu, Chuang, Xu, Donglian, Xu, Hai, Yan, Xiongbo, Yan, Ziyue, Yang, Fengfan, Yang, Yan, Yang, Yifan, Ye, Mei, Zeng, Tingxuan, Zhang, Shuihan, Zhang, Wei, Zhang, Aiqiang, Zhang, Bin, Zhao, Siyao, Zi, Changge, Aiello, Sebastiano, Andronico, Giuseppe, Antonelli, Vito, Barresi, Andrea, Basilico, Davide, Beretta, Marco, Brigatti, Augusto, Bruno, Riccardo, Budano, Antonio, Caccianiga, Barbara, Cammi, Antonio, Campese, Stefano, Chiesa, Davide, Clementi, Catia, Cordelli, Marco, Dusini, Stefano, Fabbri, Andrea, Felici, Giulietto, Ferraro, Federico, Giammarchi, Marco Giulio, Landini, Cecilia, Lombardi, Paolo, Lombardo, Claudio, Maino, Andrea, Mantovani, Fabio, Mari, Stefano Maria, Martini, Agnese, Meroni, Emanuela, Miramonti, Lino, Montuschi, Michele, Nastasi, Massimiliano, Orestano, Domizia, Ortica, Fausto, Paoloni, Alessandro, Parmeggiano, Sergio, Petrucci, Fabrizio, Previtali, Ezio, Ranucci, Gioacchino, Re, Alessandra Carlotta, Ricci, Barbara, Romani, Aldo, Saggese, Paolo, Sanfilippo, Simone, Sirignano, Chiara, Sisti, Monica, Stanco, Luca, Strati, Virginia, Tortorici, Francesco, Tuvé, Cristina, Venettacci, Carlo, Verde, Giuseppe, and Votano, Lucia

Published
2023
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9. 基于Kano模型的车厢服务配置效用评价.

Author

MAO Xinde, YAN Ziyue, and LIU Yingjie

Abstract

[Objective] Aiming at enhancing the comprehensive experience for passengers during travel, it is necessary to investigate and analyze compartment service demands, optimize compartment service facility configurations. [Method] By studying the passenger service demands for compartment service configuration, a typical passenger service demand space is constructed. Utilizing Kano model as the core, a demand evaluation model is established, and combined with satisfaction calculation methods, perceptual cognitions are quantified to analyze passenger demand for utility levels of compartment service configuration. [Result & Conclusion] Based on the Kano model and combined with Better-Worse coefficient analysis, a list of compartment service configuration demands is summarized, including 6 charm attributes, 4 expectation attributes, 2 indifference attributes, and 7 essential attributes. This method clearly demonstrates the importance of various demands, proposing design strategies such as installing charging facilities in compartments for long-distance trains, deploying foldable seats in compartments for high-traffic routes, and equipping luggage racks in compartments for airport routes. [ABSTRACT FROM AUTHOR]

Published
2024
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10. Hydrodynamic control of silicone elastomers on between porous media.

Author

Ma, Zhengyuan, Chen, Ruoyang, Qu, Yixiao, Kong, Yuan, Hu, Kami, Zhou, Qin, Xu, Siye, Yan, Ziyue, Yang, Yunchu, and He, Hui

Subjects
POROUS materials, ELASTICITY, NON-Newtonian fluids, STRAIN sensors, SILICONES, SILICONE rubber, NANOWIRES, ELASTOMERS, PSEUDOPLASTIC fluids
Abstract

Silicone elastomers, for example, polydimethylsiloxane (PDMS), have been widely used as cross-linkers for fabrication of flexible strain sensors. They not only lend strong adhesion to adjacent materials, for example, porous fabrics, but also tune their elastic property. Silicone elastomer precursors, which are typical non-Newtonian fluids, can easily penetrate into porous fabrics, driven by the capillary effects of fibers. Unfortunately, such a penetration has negative effects on both adhesion strength and elastic property of PDMS, thus limiting their applications. Here we report a facile method for preparing uniform silicone elastomer films, that is, PDMS, on between porous media via controlling the hydrodynamics of elastomer precursors. Our experiments show that the hydrodynamics of elastomer precursors can be easily controlled by modulating the pre-curing time of PDMS precursors to prevent them from penetration into porous media but keep their high adhesion. Based on this hydrodynamic modulation of PDMS precursors, we firmly adhere conductive silver nanowires (AgNWs) onto knitted fabrics, and further combine composites with common clothing from the point of view of ergonomics, showing the possibility of applying such a modulation to the fabrication of wearable strain sensors. Our findings not only present an understanding of liquid transport in porous media, but also provide a novel method of controlling the hydrodynamics of elastomer precursors in porous media for achieving the effective wearable sensors. [ABSTRACT FROM AUTHOR]

Published
2024
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11. Enhancement of Hydration Activity and Microstructure Analysis of γ-C 2 S.

Author

Yan, Ziyue, Jiang, Yaqing, Yin, Kangting, Wang, Limeng, and Pan, Tinghong

Subjects
*DISCONTINUOUS precipitation, *X-ray diffraction, *POTASSIUM salts, *MICROSTRUCTURE, *SODIUM salts, *POLYMERIZATION
Abstract

This paper investigated the combined effect of chemical activators and nano-SiO2 on the hydration reaction and the microstructure of γ-C2S. The hydration reaction of γ-C2S slurry activated with chemical activators (NaHCO3, NaOH, K2CO3, and KOH at 1 mol/L) was enhanced by 1% nano-SiO2. The hydrate reaction rate was determined by isothermal calorimetry, and the hydrated samples were characterized by XRD, TGA/DTG, SEM-EDS, and 29Si MAS/NMR. The results revealed a substantial enhancement in the hydration activity of γ-C2S due to the presence of the alkaline activator. Furthermore, nano-SiO2 did not alter the composition of γ-C2S hydration products, instead providing nucleation sites for the growth of hydration products. Incorporating nano-SiO2 promoted the formation of C-(R)-S-H gel with a low calcium-to-silica ratio and increased its polymerization levels, resulting in more favorable structures. Among all the activators used in this study, potassium salts had a better activation effect than sodium salts. After 28 days of curing, the degree of hydration reaction in the KC+Si group was 48% and about 37% for the NHC+Si group. Whereas, the KH+Si and NH+Si groups only reached approximately 20% after the same hydration duration. [ABSTRACT FROM AUTHOR]

Published
2023
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12. Noninvasive detection of brain gliomas using plasma cell‐free DNA 5‐hydroxymethylcytosine sequencing.

Author

Zhang, Shuxin, Zhang, Jun, Hu, Xinlei, Yin, Senlin, Yuan, Yunbo, Xia, Lin, Cao, Feng, Yan, Xiaoqin, Yan, Ziyue, Mao, Qing, Xie, Dan, and Liu, Yanhui

Subjects
CELL-free DNA, CIRCULATING tumor DNA, GLIOMAS, DNA sequencing, SOMATIC mutation, ISOCITRATE dehydrogenase, BRAIN tumors
Abstract

Liquid biopsy techniques based on deep sequencing of plasma cell‐free DNA (cfDNA) could detect the low‐frequency somatic mutations and provide an accurate diagnosis for many cancers. However, for brain gliomas, reliable performance of these techniques currently requires obtaining cfDNA from patients' cerebral spinal fluid, which is cumbersome and risky. Here we report a liquid biopsy method based on sequencing of plasma cfDNA fragments carrying 5‐hydroxymethylcytosine (5hmC) using selective chemical labeling (hMe‐Seal). We first constructed a dataset including 180 glioma patients and 229 non‐glioma controls. We found marked concordance between cfDNA hydroxymethylome and the aberrant transcriptome of the underlying gliomas. Functional analysis also revealed overrepresentation of the differentially hydroxymethylated genes (DhmGs) in oncogenic and neural pathways. After splitting our dataset into training and test cohort, we showed that a penalized logistic model constructed with training set DhmGs could distinguish glioma patients from healthy controls in both our test set (AUC = 0.962) and an independent dataset (AUC = 0.930) consisting of 111 gliomas and 111 controls. Additionally, the DhmGs between gliomas with mutant and wild‐type isocitrate dehydrogenase (IDH) could be used to train a cfDNA predictor of the IDH mutation status of the underlying tumor (AUC = 0.816), and patients with predicted IDH mutant gliomas had significantly better outcome (P =.01). These results indicate that our plasma cfDNA 5hmC sequencing method could obtain glioma‐specific signals, which may be used to noninvasively detect these patients and predict the aggressiveness of their tumors. [ABSTRACT FROM AUTHOR]

Published
2023
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14. A Weighted Fidelity and Regularization-Based Method for Mixed or Unknown Noise Removal From Images on Graphs.

Author

Wang, Cong, Yan, Ziyue, Pedrycz, Witold, Zhou, MengChu, and Li, Zhiwu

Subjects
*IMAGE denoising, *EUCLIDEAN domains, *BURST noise, *COMPUTER vision, *NOISE, *WAVELET transforms
Abstract

Image denoising technologies in a Euclidean domain have achieved good results and are becoming mature. However, in recent years, many real-world applications encountered in computer vision and geometric modeling involve image data defined in irregular domains modeled by huge graphs, which results in the problem on how to solve image denoising problems defined on graphs. In this paper, we propose a novel model for removing mixed or unknown noise in images on graphs. The objective is to minimize the sum of a weighted fidelity term and a sparse regularization term that additionally utilizes wavelet frame transform on graphs to retain feature details of images defined on graphs. Specifically, the weighted fidelity term with $\ell _{1}$ -norm and $\ell _{2}$ -norm is designed based on a analysis of the distribution of mixed noise. The augmented Lagrangian and accelerated proximal gradient methods are employed to achieve the optimal solution to the problem. Finally, some supporting numerical results and comparative analyses with other denoising algorithms are provided. It is noted that we investigate image denoising with unknown noise or a wide range of mixed noise, especially the mixture of Poisson, Gaussian, and impulse noise. Experimental results reported for synthetic and real images on graphs demonstrate that the proposed method is effective and efficient, and exhibits better performance for the removal of mixed or unknown noise in images on graphs than other denoising algorithms in the literature. The method can effectively remove mixed or unknown noise and retain feature details of images on graphs. It delivers a new avenue for denoising images in irregular domains. [ABSTRACT FROM AUTHOR]

Published
2020
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