3,676 results on '"Wang, Zhou"'
Search Results
2. Exploring New Physics with PandaX-4T Low Energy Electronic Recoil Data
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PandaX Collaboration, Zeng, Xinning, Bo, Zihao, Chen, Wei, Chen, Xun, Chen, Yunhua, Cheng, Zhaokan, Cui, Xiangyi, Fan, Yingjie, Fang, Deqing, Gao, Zhixing, Geng, Lisheng, Giboni, Karl, Guo, Xunan, Guo, Xuyuan, Guo, Zichao, Han, Chencheng, He, Ke HanChangda, He, Jinrong, Huang, Di, Huang, Houqi, Huang, Junting, Hou, Ruquan, Hou, Yu, Ji, Xiangdong, Ji, Xiangpan, Ju, Yonglin, Li, Chenxiang, Li, Jiafu, Li, Mingchuan, Li, Shuaijie, Li, Tao, Li, Zhiyuan, Lin, Qing, Liu, Jianglai, Lu, Congcong, Lu, Xiaoying, Luo, Lingyin, Luo, Yunyang, Ma, Wenbo, Ma, Yugang, Mao, Yajun, Meng, Yue, Ning, Xuyang, Pang, Binyu, Qi, Ningchun, Qian, Zhicheng, Ren, Xiangxiang, Shan, Dong, Shang, Xiaofeng, Shao, Xiyuan, Shen, Guofang, Shen, Manbin, Sun, Wenliang, Tao, Yi, Wang, Anqing, Wang, Guanbo, Wang, Hao, Wang, Jiamin, Wang, Lei, Wang, Meng, Wang, Qiuhong, Wang, Shaobo, Wang, Siguang, Wang, Wei, Wang, Xiuli, Wang, Xu, Wang, Zhou, Wei, Yuehuan, Wu, Weihao, Wu, Yuan, Xiao, Mengjiao, Xiao, Xiang, Xiong, Kaizhi, Xu, Yifan, Yao, Shunyu, Yan, Binbin, Yan, Xiyu, Yang, Yong, Ye, Peihua, Yu, Chunxu, Yuan, Ying, Yuan, Zhe, Yun, Youhui, Zhang, Minzhen, Zhang, Peng, Zhang, Shibo, Zhang, Shu, Zhang, Tao, Zhang, Wei, Zhang, Yang, Zhang, Yingxin, Zhang, Yuanyuan, Zhao, Li, Zhou, Jifang, Zhou, Jiaxu, Zhou, Jiayi, Zhou, Ning, Zhou, Xiaopeng, Zhou, Yubo, and Zhou, Zhizhen
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High Energy Physics - Experiment - Abstract
New particles beyond the Standard Model of particle physics, such as axions, can be effectively searched through their interactions with electrons. We use the large liquid xenon detector PandaX-4T to search for novel electronic recoil signals induced by solar axions, neutrinos with anomalous magnetic moment, axion-like particles, dark photons, and light fermionic dark matter. A detailed background model is established with the latest datasets with 1.54 $\rm tonne \cdot year$ exposure. No significant excess above the background has been observed, and we have obtained competitive constraints for axion couplings, neutrino magnetic moment, and fermionic dark matter interactions.
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- 2024
3. Dark Matter Search Results from 1.54 Tonne$\cdot$Year Exposure of PandaX-4T
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PandaX Collaboration, Bo, Zihao, Chen, Wei, Chen, Xun, Chen, Yunhua, Cheng, Zhaokan, Cui, Xiangyi, Fan, Yingjie, Fang, Deqing, Gao, Zhixing, Geng, Lisheng, Giboni, Karl, Guo, Xunan, Guo, Xuyuan, Guo, Zichao, Han, Chencheng, Han, Ke, He, Changda, He, Jinrong, Huang, Di, Huang, Houqi, Huang, Junting, Hou, Ruquan, Hou, Yu, Ji, Xiangdong, Ji, Xiangpan, Ju, Yonglin, Li, Chenxiang, Li, Jiafu, Li, Mingchuan, Li, Shuaijie, Li, Tao, Li, Zhiyuan, Lin, Qing, Liu, Jianglai, Lu, Congcong, Lu, Xiaoying, Luo, Lingyin, Luo, Yunyang, Ma, Wenbo, Ma, Yugang, Mao, Yajun, Meng, Yue, Ning, Xuyang, Pang, Binyu, Qi, Ningchun, Qian, Zhicheng, Ren, Xiangxiang, Shan, Dong, Shang, Xiaofeng, Shao, Xiyuan, Shen, Guofang, Shen, Manbin, Sun, Wenliang, Tao, Yi, Wang, Anqing, Wang, Guanbo, Wang, Hao, Wang, Jiamin, Wang, Lei, Wang, Meng, Wang, Qiuhong, Wang, Shaobo, Wang, Siguang, Wang, Wei, Wang, Xiuli, Wang, Xu, Wang, Zhou, Wei, Yuehuan, Wu, Weihao, Wu, Yuan, Xiao, Mengjiao, Xiao, Xiang, Xiong, Kaizhi, Xu, Yifan, Yao, Shunyu, Yan, Binbin, Yan, Xiyu, Yang, Yong, Ye, Peihua, Yu, Chunxu, Yuan, Ying, Yuan, Zhe, Yun, Youhui, Zeng, Xinning, Zhang, Minzhen, Zhang, Peng, Zhang, Shibo, Zhang, Shu, Zhang, Tao, Zhang, Wei, Zhang, Yang, Zhang, Yingxin, Zhang, Yuanyuan, Zhao, Li, Zhou, Jifang, Zhou, Jiaxu, Zhou, Jiayi, Zhou, Ning, Zhou, Xiaopeng, Zhou, Yubo, and Zhou, Zhizhen
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High Energy Physics - Experiment - Abstract
In this letter, we report the dark matter search results from the commissioning run and the first science run of the PandaX-4T experiment. A blind analysis is carried out on the entire data set. The data processing is improved compared to previous work, unifying the low-level signal reconstruction in a wide energy range up to 120 keV. With a total exposure of 1.54 tonne$\cdot$year, no significant excess of nuclear recoil events is found. The lowest 90% confidence level exclusion on the spin-independent cross section is $1.6 \times 10^{-47} \mathrm{cm}^2$ at a dark matter mass of 40 GeV$/c^2$. Our results represent the most stringent constraint for a dark matter mass above 100 GeV$/c^2$.
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- 2024
4. First Measurement of Solar $^8$B Neutrino Flux through Coherent Elastic Neutrino-Nucleus Scattering in PandaX-4T
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PandaX Collaboration, Bo, Zihao, Chen, Wei, Chen, Xun, Chen, Yunhua, Cheng, Zhaokan, Cui, Xiangyi, Fan, Yingjie, Fang, Deqing, Gao, Zhixing, Geng, Lisheng, Giboni, Karl, Guo, Xunan, Guo, Xuyuan, Guo, Zichao, Han, Chencheng, Han, Ke, He, Changda, He, Jinrong, Huang, Di, Huang, Houqi, Huang, Junting, Hou, Ruquan, Hou, Yu, Ji, Xiangdong, Ji, Xiangpan, Ju, Yonglin, Li, Chenxiang, Li, Jiafu, Li, Mingchuan, Li, Shuaijie, Li, Tao, Li, Zhiyuan, Lin, Qing, Liu, Jianglai, Lu, Congcong, Lu, Xiaoying, Luo, Lingyin, Luo, Yunyang, Ma, Wenbo, Ma, Yugang, Mao, Yajun, Meng, Yue, Ning, Xuyang, Pang, Binyu, Qi, Ningchun, Qian, Zhicheng, Ren, Xiangxiang, Shan, Dong, Shang, Xiaofeng, Shao, Xiyuan, Shen, Guofang, Shen, Manbin, Sun, Wenliang, Tao, Yi, Wang, Anqing, Wang, Guanbo, Wang, Hao, Wang, Jiamin, Wang, Lei, Wang, Meng, Wang, Qiuhong, Wang, Shaobo, Wang, Siguang, Wang, Wei, Wang, Xiuli, Wang, Xu, Wang, Zhou, Wei, Yuehuan, Wu, Weihao, Wu, Yuan, Xiao, Mengjiao, Xiao, Xiang, Xiong, Kaizhi, Xu, Yifan, Yao, Shunyu, Yan, Binbin, Yan, Xiyu, Yang, Yong, Ye, Peihua, Yu, Chunxu, Yuan, Ying, Yuan, Zhe, Yun, Youhui, Zeng, Xinning, Zhang, Minzhen, Zhang, Peng, Zhang, Shibo, Zhang, Shu, Zhang, Tao, Zhang, Wei, Zhang, Yang, Zhang, Yingxin, Zhang, Yuanyuan, Zhao, Li, Zhou, Jifang, Zhou, Jiaxu, Zhou, Jiayi, Zhou, Ning, Zhou, Xiaopeng, Zhou, Yubo, and Zhou, Zhizhen
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High Energy Physics - Experiment ,Astrophysics - Solar and Stellar Astrophysics ,Nuclear Experiment - Abstract
The PandaX-4T liquid xenon detector at the China Jinping Underground Laboratory is used to measure the solar $^8$B neutrino flux by detecting neutrinos through coherent scattering with xenon nuclei. Data samples requiring the coincidence of scintillation and ionization signals (paired), as well as unpaired ionization-only signals (US2), are selected with energy threshold of approximately 1.1 keV (0.33 keV) nuclear recoil energy. Combining the commissioning run and the first science run of PandaX-4T, a total exposure of 1.25 and 1.04 tonne$\cdot$year are collected for the paired and US2, respectively. After unblinding, 3 and 332 events are observed with an expectation of 2.8$\pm$0.5 and 251$\pm$32 background events, for the paired and US2 data, respectively. A combined analysis yields a best-fit $^8$B neutrino signal of 3.5 (75) events from the paired (US2) data sample, with $\sim$37\% uncertainty, and the background-only hypothesis is disfavored at 2.64$\sigma$ significance. This gives a solar $^8$B neutrino flux of ($8.4\pm3.1$)$\times$10$^6$ cm$^{-2}$s$^{-1}$, consistent with the standard solar model prediction. This is the first indication of solar $^8$B neutrino ``fog'' in a dark matter direct detection experiment.
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- 2024
5. Large reversible magnetocaloric effect of the EuAl3Si single crystal
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Zeng, Hai, Zou, Shuo, Wang, Zhou, Li, Ziyu, Luo, Kangjian, and Luo, Yongkang
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Condensed Matter - Strongly Correlated Electrons - Abstract
The magnetic properties, magnetocaloric effect and magnetoresistance of EuAl3Si single crystal have been investigated. A giant reversible magnetocaloric effect was observed around TC = 14.5 K. For the low magnetic field changes of 0-2 T, the maximum values of magnetic entropy change and refrigerant capacity are 13.4 J/kg K, and 166 J/kg,respectively, with the corresponding adiabatic temperature of 7.2 K.These excellent magnetocaloric parameters suggest EuAl3Si as a promising candidate for magnetic refrigeration application around liquid hydrogen temperature.
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- 2024
6. Perceptual Crack Detection for Rendered 3D Textured Meshes
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Sarvestani, Armin Shafiee, Zhou, Wei, and Wang, Zhou
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Computational Geometry ,Computer Science - Multimedia - Abstract
Recent years have witnessed many advancements in the applications of 3D textured meshes. As the demand continues to rise, evaluating the perceptual quality of this new type of media content becomes crucial for quality assurance and optimization purposes. Different from traditional image quality assessment, crack is an annoying artifact specific to rendered 3D meshes that severely affects their perceptual quality. In this work, we make one of the first attempts to propose a novel Perceptual Crack Detection (PCD) method for detecting and localizing crack artifacts in rendered meshes. Specifically, motivated by the characteristics of the human visual system (HVS), we adopt contrast and Laplacian measurement modules to characterize crack artifacts and differentiate them from other undesired artifacts. Extensive experiments on large-scale public datasets of 3D textured meshes demonstrate effectiveness and efficiency of the proposed PCD method in correct localization and detection of crack artifacts. %Specifically, We propose a full-reference crack artifact localization method that operates on a pair of input snapshots of distorted and reference 3D objects to generate a final crack map. Moreover, to quantify the performance of the proposed detection method and validate its effectiveness, we propose a simple yet effective weighting mechanism to incorporate the resulting crack map into classical quality assessment (QA) models, which creates significant performance improvement in predicting the perceptual image quality when tested on public datasets of static 3D textured meshes. A software release of the proposed method is publicly available at: https://github.com/arshafiee/crack-detection-VVM, Comment: Accepted by IEEE QoMEX 2024
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- 2024
7. Efficient Online Set-valued Classification with Bandit Feedback
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Wang, Zhou and Qiao, Xingye
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Statistics - Machine Learning ,Computer Science - Machine Learning - Abstract
Conformal prediction is a distribution-free method that wraps a given machine learning model and returns a set of plausible labels that contain the true label with a prescribed coverage rate. In practice, the empirical coverage achieved highly relies on fully observed label information from data both in the training phase for model fitting and the calibration phase for quantile estimation. This dependency poses a challenge in the context of online learning with bandit feedback, where a learner only has access to the correctness of actions (i.e., pulled an arm) but not the full information of the true label. In particular, when the pulled arm is incorrect, the learner only knows that the pulled one is not the true class label, but does not know which label is true. Additionally, bandit feedback further results in a smaller labeled dataset for calibration, limited to instances with correct actions, thereby affecting the accuracy of quantile estimation. To address these limitations, we propose Bandit Class-specific Conformal Prediction (BCCP), offering coverage guarantees on a class-specific granularity. Using an unbiased estimation of an estimand involving the true label, BCCP trains the model and makes set-valued inferences through stochastic gradient descent. Our approach overcomes the challenges of sparsely labeled data in each iteration and generalizes the reliability and applicability of conformal prediction to online decision-making environments.
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- 2024
8. Generated Contents Enrichment
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Naseri, Mahdi, Qiu, Jiayan, and Wang, Zhou
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning - Abstract
In this paper, we investigate a novel artificial intelligence generation task, termed as generated contents enrichment (GCE). Different from conventional artificial intelligence contents generation task that enriches the given textual description implicitly with limited semantics for generating visually real content, our proposed GCE strives to perform content enrichment explicitly on both the visual and textual domain, from which the enriched contents are visually real, structurally reasonable, and semantically abundant. Towards to solve GCE, we propose a deep end-to-end method that explicitly explores the semantics and inter-semantic relationships during the enrichment. Specifically, we first model the input description as a semantic graph, wherein each node represents an object and each edge corresponds to the inter-object relationship. We then adopt Graph Convolutional Networks on top of the input scene description to predict the enriching objects and their relationships with the input objects. Finally, the enriched description is fed into an image synthesis model to carry out the visual contents generation. Our experiments conducted on the Visual Genome dataset exhibit promising and visually plausible results.
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- 2024
9. Search for cosmic-ray boosted sub-MeV dark matter-electron scatterings in PandaX-4T
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Shang, Xiaofeng, Abdukerim, Abdusalam, Bo, Zihao, Chen, Wei, Chen, Xun, Cheng, Chen, Cheng, Zhaokan, Cui, Xiangyi, Fan, Yingjie, Fang, Deqing, Geng, Lisheng, Giboni, Karl, Guo, Xuyuan, Han, Chencheng, Han, Ke, He, Changda, He, Jinrong, Huang, Di, Huang, Junting, Huang, Zhou, Hou, Ruquan, Hou, Yu, Ji, Xiangdong, Ju, Yonglin, Li, Chenxiang, Li, Jiafu, Li, Mingchuan, Li, Shuaijie, Li, Tao, Lin, Qing, Liu, Jianglai, Lu, Congcong, Lu, Xiaoying, Luo, Lingyin, Luo, Yunyang, Ma, Wenbo, Ma, Yugang, Mao, Yajun, Meng, Yue, Ning, Xuyang, Pang, Binyu, Qi, Ningchun, Qian, Zhicheng, Ren, Xiangxiang, Shaheed, Nasir, Shao, Xiyuan, Shen, Guofang, Si, Lin, Sun, Wenliang, Tan, Andi, Tao, Yi, Wang, Anqing, Wang, Meng, Wang, Qiuhong, Wang, Shaobo, Wang, Siguang, Wang, Wei, Wang, Xiuli, Wang, Xu, Wang, Zhou, Wei, Yuehuan, Wu, Mengmeng, Wu, Weihao, Wu, Yuan, Xiao, Mengjiao, Xiao, Xiang, Yan, Binbin, Yan, Xiyu, Yang, Yong, Yu, Chunxu, Yuan, Ying, Yuan, Zhe, Yun, Youhui, Zeng, Xinning, Zhang, Minzhen, Zhang, Peng, Zhang, Shibo, Zhang, Shu, Zhang, Tao, Zhang, Wei, Zhang, Yang, Zhang, Yingxin, Zhang, Yuanyuan, Zhao, Li, Zhou, Jifang, Zhou, Ning, Zhou, Xiaopeng, Zhou, Yong, Zhou, Yubo, Zhou, Zhizhen, Ge, Shao-Feng, and Xia, Chen
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High Energy Physics - Experiment ,High Energy Physics - Phenomenology - Abstract
We report the first search for the elastic scatterings between cosmic-ray boosted sub-MeV dark matter and electrons in the PandaX-4T liquid xenon experiment. Sub-MeV dark matter particles can be accelerated by scattering with electrons in the cosmic rays and produce detectable electron recoil signals in the detector. Using the commissioning data from PandaX-4T of 0.63~tonne$\cdot$year exposure, we set new constraints on DM-electron scattering cross sections for DM masses ranging from 10~eV/$c^2$ to 3~keV/$c^2$., Comment: 6 pages, 3 figures
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- 2024
10. Detecting Neutrinos from Supernova Bursts in PandaX-4T
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Pang, Binyu, Abdukerim, Abdusalam, Bo, Zihao, Chen, Wei, Chen, Xun, Cheng, Chen, Cheng, Zhaokan, Cui, Xiangyi, Fan, Yingjie, Fang, Deqing, Fu, Changbo, Fu, Mengting, Geng, Lisheng, Giboni, Karl, Gu, Linhui, Guo, Xuyuan, Han, Chencheng, Han, Ke, He, Changda, He, Jinrong, Huang, Di, Huang, Yanlin, Huang, Junting, Huang, Zhou, Hou, Ruquan, Hou, Yu, Ji, Xiangdong, Ju, Yonglin, Li, Chenxiang, Li, Jiafu, Li, Mingchuan, Li, Shuaijie, Li, Tao, Lin, Qing, Liu, Jianglai, Lu, Congcong, Lu, Xiaoying, Luo, Lingyin, Luo, Yunyang, Ma, Wenbo, Ma, Yugang, Mao, Yajun, Meng, Yue, Ning, Xuyang, Qi, Ningchun, Qian, Zhicheng, Ren, Xiangxiang, Shaheed, Nasir, Shang, Xiaofeng, Shao, Xiyuan, Shen, Guofang, Si, Lin, Sun, Wenliang, Tan, Andi, Tao, Yi, Wang, Anqing, Wang, Meng, Wang, Qiuhong, Wang, Shaobo, Wang, Siguang, Wang, Wei, Wang, Xiuli, Wang, Zhou, Wei, Yuehuan, Wu, Mengmeng, Wu, Weihao, Xia, Jingkai, Xiao, Mengjiao, Xiao, Xiang, Xie, Pengwei, Yan, Binbin, Yan, Xiyu, Yang, Jijun, Yang, Yong, Yao, Yukun, Yu, Chunxu, Yuan, Ying, Yuan, Zhe, Zeng, Xinning, Zhang, Dan, Zhang, Minzhen, Zhang, Peng, Zhang, Shibo, Zhang, Shu, Zhang, Tao, Zhang, Wei, Zhang, Yang, Zhang, Yingxin, Zhang, Yuanyuan, Zhao, Li, Zheng, Qibin, Zhou, Jifang, Zhou, Ning, Zhou, Xiaopeng, Zhou, Yong, and Zhou, Yubo
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High Energy Physics - Experiment ,Physics - Instrumentation and Detectors - Abstract
Neutrinos from core-collapse supernovae are essential for the understanding of neutrino physics and stellar evolution. The dual-phase xenon dark matter detectors can provide a way to track explosions of galactic supernovae by detecting neutrinos through coherent elastic neutrino-nucleus scatterings. In this study, a variation of progenitor masses as well as explosion models are assumed to predict the neutrino fluxes and spectra, which result in the number of expected neutrino events ranging from 6.6 to 13.7 at a distance of 10 kpc over a 10-second duration with negligible backgrounds at PandaX-4T. Two specialized triggering alarms for monitoring supernova burst neutrinos are built. The efficiency of detecting supernova explosions at various distances in the Milky Way is estimated. These alarms will be implemented in the real-time supernova monitoring system at PandaX-4T in the near future, providing the astronomical communities with supernova early warnings., Comment: 9 pages,6 figures
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- 2024
11. Signal Response Model in PandaX-4T
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Luo, Yunyang, Bo, Zihao, Zhang, Shibo, Abdukerim, Abdusalam, Cheng, Chen, Chen, Wei, Chen, Xun, Chen, Yunhua, Cheng, Zhaokan, Cui, Xiangyi, Fan, Yingjie, Fang, Deqing, Fu, Changbo, Fu, Mengting, Geng, Lisheng, Giboni, Karl, Gu, Linhui, Guo, Xuyuan, Han, Chencheng, Han, Ke, He, Changda, He, Jinrong, Huang, Di, Huang, Yanlin, Huang, Zhou, Hou, Ruquan, Ji, Xiangdong, Ju, Yonglin, Li, Chenxiang, Li, Jiafu, Li, Mingchuan, Li, Shu, Li, Shuaijie, Lin, Qing, Liu, Jianglai, Lu, Xiaoying, Luo, Lingyin, Ma, Wenbo, Ma, Yugang, Mao, Yajun, Shaheed, Nasir, Meng, Yue, Ning, Xuyang, Qi, Ningchun, Qian, Zhicheng, Ren, Xiangxiang, Shang, Changsong, Shang, Xiaofeng, Shen, Guofang, Si, Lin, Sun, Wenliang, Tan, Andi, Tao, Yi, Wang, Anqing, Wang, Meng, Wang, Qiuhong, Wang, Shaobo, Wang, Siguang, Wang, Wei, Wang, Xiuli, Wang, Zhou, Wei, Yuehuan, Wu, Mengmeng, Wu, Weihao, Xia, Jingkai, Xiao, Mengjiao, Xiao, Xiang, Xie, Pengwei, Yan, Binbin, Yan, Xiyu, Yang, Jijun, Yang, Yong, Yu, Chunxu, Yuan, Jumin, Yuan, Ying, Yuan, Zhe, Zeng, Xinning, Zhang, Dan, Zhang, Minzhen, Zhang, Peng, Zhang, Shu, Zhang, Tao, Zhang, Yingxin, Zhang, Yuanyuan, Zhao, Li, Zheng, Qibin, Zhou, Jifang, Zhou, Ning, Zhou, Xiaopeng, Zhou, Yong, and Zhou, Yubo
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Physics - Instrumentation and Detectors ,High Energy Physics - Experiment - Abstract
PandaX-4T experiment is a deep-underground dark matter direct search experiment that employs a dual-phase time projection chamber with a sensitive volume containing 3.7 tonne of liquid xenon. The detector of PandaX-4T is capable of simultaneously collecting the primary scintillation and ionization signals, utilizing their ratio to discriminate dark matter signals from background sources such as gamma rays and beta particles. The signal response model plays a crucial role in interpreting the data obtained by PandaX-4T. It describes the conversion from the deposited energy by dark matter interactions to the detectable signals within the detector. The signal response model is utilized in various PandaX-4T results. This work provides a comprehensive description of the procedures involved in constructing and parameter-fitting the signal response model for the energy range of approximately 1 keV to 25 keV for electronic recoils and 6 keV to 90 keV for nuclear recoils. It also covers the signal reconstruction, selection, and correction methods, which are crucial components integrated into the signal response model.
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- 2024
12. PandaX-xT: a Multi-ten-tonne Liquid Xenon Observatory at the China Jinping Underground Laboratory
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PandaX Collaboration, Abdukerim, Abdusalam, Bo, Zihao, Chen, Wei, Chen, Xun, Cheng, Chen, Cheng, Zhaokan, Cui, Xiangyi, Fan, Yingjie, Fang, Deqing, Geng, Lisheng, Giboni, Karl, Gu, Linhui, Guo, Xunan, Guo, Xuyuan, Guo, Zhichao, Han, Chencheng, Han, Ke, He, Changda, He, Jinrong, Huang, Di, Huang, Junting, Huang, Zhou, Hou, Ruquan, Hou, Yu, Ji, Xiangdong, Ju, Yonglin, Li, Chenxiang, Li, Jiafu, Li, Mingchuan, Li, Shuaijie, Li, Tao, Lin, Qing, Liu, Jianglai, Lu, Congcong, Lu, Xiaoying, Luo, Lingyin, Luo, Yunyang, Ma, Wenbo, Ma, Yugang, Mao, Yajun, Meng, Yue, Ning, Xuyang, Pang, Binyu, Qi, Ningchun, Qian, Zhicheng, Ren, Xiangxiang, Shaheed, Nasir, Shang, Xiaofeng, Shao, Xiyuan, Shen, Guofang, Si, Lin, Sun, Wenliang, Tao, Yi, Wang, Anqing, Wang, Meng, Wang, Qiuhong, Wang, Shaobo, Wang, Siguang, Wang, Wei, Wang, Xiuli, Wang, Xu, Wang, Zhou, Wei, Yuehuan, Wu, Mengmeng, Wu, Weihao, Wu, Yuan, Xiao, Mengjiao, Xiao, Xiang, Yan, Binbin, Yan, Xiyu, Yang, Yong, Yu, Chunxu, Yuan, Ying, Yuan, Zhe, Yun, Youhui, Zeng, Xinning, Zhang, Minzhen, Zhang, Peng, Zhang, Shibo, Zhang, Shu, Zhang, Tao, Zhang, Wei, Zhang, Yang, Zhang, Yingxin, Zhang, Yuanyuan, Zhao, Li, Zhou, Jifang, Zhou, Ning, Zhou, Xiaopeng, Zhou, Yong, Zhou, Yubo, and Zhou, Zhizhen
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High Energy Physics - Experiment ,Astrophysics - Cosmology and Nongalactic Astrophysics ,High Energy Physics - Phenomenology - Abstract
We propose a major upgrade to the existing PandaX-4T experiment in the China Jinping Underground Laboratory. The new experiment, PandaX-xT, will be a multi-ten-tonne liquid xenon, ultra-low background, and general-purpose observatory. The full-scaled PandaX-xT contains a 43-tonne liquid xenon active target. Such an experiment will significantly advance our fundamental understanding of particle physics and astrophysics. The sensitivity of dark matter direct detection will be improved by nearly two orders of magnitude compared to the current best limits, approaching the so-called "neutrino floor" for a dark matter mass above 10 GeV/$c^2$, providing a decisive test to the Weakly Interacting Massive Particle paradigm. By searching for the neutrinoless double beta decay of $^{136}$Xe isotope in the detector, the effective Majorana neutrino mass can be measured to a [10 -- 41] meV/$c^2$ sensitivity, providing a key test to the Dirac/Majorana nature of neutrino s. Astrophysical neutrinos and other ultra-rare interactions can also be measured and searched for with an unprecedented background level, opening up new windows of discovery. Depending on the findings, PandaX-xT will seek the next stage upgrade utilizing isotopic separation on natural xenon.
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- 2024
13. Measurement of Solar $pp$ Neutrino Flux using Electron Recoil Data from PandaX-4T Commissioning Run
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PandaX Collaboration, Lu, Xiaoying, Abdukerim, Abdusalam, Bo, Zihao, Chen, Wei, Chen, Xun, Chen, Yunhua, Cheng, Chen, Cheng, Zhaokan, Cui, Xiangyi, Fan, Yingjie, Fang, Deqing, Geng, Lisheng, Giboni, Karl, Guo, Xuyuan, Han, Chencheng, Han, Ke, He, Changda, He, Jinrong, Huang, Di, Huang, Junting, Huang, Zhou, Hou, Ruquan, Hou, Yu, Ji, Xiangdong, Ju, Yonglin, Li, Chenxiang, Li, Jiafu, Li, Mingchuan, Li, Shuaijie, Li, Tao, Lin, Qing, Liu, Jianglai, Lu, Congcong, Luo, Lingyin, Luo, Yunyang, Ma, Wenbo, Ma, Yugang, Mao, Yajun, Meng, Yue, Ning, Xuyang, Pang, Binyu, Qi, Ningchun, Qian, Zhicheng, Ren, Xiangxiang, Shaheed, Nasir, Shang, Xiaofeng, Shao, Xiyuan, Shen, Guofang, Shen, Manbin, Si, Lin, Sun, Wenliang, Tao, Yi, Wang, Anqing, Wang, Meng, Wang, Qiuhong, Wang, Shaobo, Wang, Siguang, Wang, Wei, Wang, Xiuli, Wang, Xu, Wang, Zhou, Wei, Yuehuan, Wu, Mengmeng, Wu, Weihao, Wu, Yuan, Xiao, Mengjiao, Xiao, Xiang, Xiong, Kaizhi, Yan, Binbin, Yan, Xiyu, Yang, Yong, Yu, Chunxu, Yuan, Ying, Yuan, Zhe, Yun, Youhui, Zeng, Xinning, Zhang, Minzhen, Zhang, Peng, Zhang, Shibo, Zhang, Shu, Zhang, Tao, Zhang, Wei, Zhang, Yang, Zhang, Yingxin, Zhang, Yuanyuan, Zhao, Li, Zhou, Jifang, Zhou, Ning, Zhou, Xiaopeng, Zhou, Yubo, and Zhou, Zhizhen
- Subjects
High Energy Physics - Experiment - Abstract
The proton-proton ($pp$) fusion chain dominates the neutrino production from the Sun. The uncertainty of the predicted $pp$ neutrino flux is at the sub-percent level, whereas that of the best measurement is $\mathcal{O}(10\%)$. In this paper, we present the first result to measure the solar $pp$ neutrinos in the electron recoil energy range from 24 to 144 keV, using the PandaX-4T commissioning data with 0.63 tonne$\times$year exposure. The $pp$ neutrino flux is determined to be $(8.0 \pm 3.9 \,{\rm{(stat)}} \pm 10.0 \,{\rm{(syst)}} )\times 10^{10}\, $$\rm{s}^{-1} \rm{cm}^{-2}$, consistent with Standard Solar Model and existing measurements, corresponding to a flux upper limit of $23.3\times 10^{10}\, $$\rm{s}^{-1} \rm{cm}^{-2}$ at 90\% C.L.., Comment: 6 pages, 5 figures
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- 2024
14. Radon Removal Commissioning of the PandaX-4T Cryogenic Distillation System
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Cui, Xiangyi, Wang, Zhou, Li, Jiafu, Li, Shuaijie, Si, Lin, Ju, Yonglin, Ma, Wenbo, Liu, Jianglai, Zhao, Li, Ji, Xiangdong, Yan, Rui, Sha, Haidong, Huang, Peiyao, Wang, Xiuli, and Liu, Huaxuan
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Physics - Instrumentation and Detectors - Abstract
The PandaX-4T distillation system, designed for the removal of krypton and radon from xenon, is evaluated for its radon removal efficiency using a $^{222}$Rn source during the online distillation process. The PandaX-4T dark matter detector is employed to monitor the temporal evolution of radon activity. To determine the radon reduction factor, the experimental data of radon atoms introduced into and bypassed the distillation system is compared. The results indicate that the PandaX-4T distillation system achieves a radon reduction factor exceeding 190 at the flow rate of 10 slpm and the reflux ratio of 1.44. Gas-only online distillation process of a flow rate of 20 slpm is also conducted without observing significant reduction of radon levels in the detector. This observation suggests that the migration flow of radon atoms from the liquid phase to the gas phase is limited, and the flow rate of gas circulation and duration of the process are insignificant compared to the total xenon mass of 5.6 tons in the detector. This study provides the experimental data to support the efficient removal of radon at $\sim$Bq level using the PandaX-4T distillation system, which is the prerequisite of the radon background control in the detector. The further operation with higher flow rate will be applied for the upcoming science run in PandaX-4T., Comment: 14 pages, 9 figures
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- 2024
15. Searching for Two-Neutrino and Neutrinoless Double Beta Decay of $^{134}$Xe with the PandaX-4T Experiment
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PandaX Collaboration, Yan, Xiyu, Cheng, Zhaokan, Abdukerim, Abdusalam, Bo, Zihao, Chen, Wei, Chen, Xun, Cheng, Chen, Cui, Xiangyi, Fan, Yingjie, Fang, Deqing, Fu, Changbo, Fu, Mengting, Geng, Lisheng, Giboni, Karl, Gu, Linhui, Guo, Xuyuan, Han, Chencheng, Han, Ke, He, Changda, He, Jinrong, Huang, Di, Huang, Yanlin, Huang, Junting, Huang, Zhou, Hou, Ruquan, Hou, Yu, Ji, Xiangdong, Ju, Yonglin, Li, Chenxiang, Li, Jiafu, Li, Mingchuan, Li, Shuaijie, Li, Tao, Lin, Qing, Liu, Jianglai, Lu, Xiaoying, Lu, Congcong, Luo, Lingyin, Luo, Yunyang, Ma, Wenbo, Ma, Yugang, Mao, Yajun, Meng, Yue, Ning, Xuyang, Pang, Binyu, Qi, Ningchun, Qian, Zhicheng, Ren, Xiangxiang, Shaheed, Nasir, Shang, Xiaofeng, Shao, Xiyuan, Shen, Guofang, Si, Lin, Sun, Wenliang, Tan, Andi, Tao, Yi, Wang, Anqing, Wang, Meng, Wang, Qiuhong, Wang, Shaobo, Wang, Siguang, Wang, Wei, Wang, Xiuli, Wang, Zhou, Wei, Yuehuan, Wu, Mengmeng, Wu, Weihao, Xia, Jingkai, Xiao, Mengjiao, Xiao, Xiang, Xie, Pengwei, Yan, Binbin, Yang, Jijun, Yang, Yong, Yao, Yukun, Yu, Chunxu, Yuan, Ying, Yuan, Zhe, Zeng, Xinning, Zhang, Dan, Zhang, Minzhen, Zhang, Peng, Zhang, Shibo, Zhang, Shu, Zhang, Tao, Zhang, Wei, Zhang, Yang, Zhang, Yingxin, Zhang, Yuanyuan, Zhao, Li, Zheng, Qibin, Zhou, Jifang, Zhou, Ning, Zhou, Xiaopeng, Zhou, Yong, and Zhou, Yubo
- Subjects
Nuclear Experiment - Abstract
$^{134}$Xe is a candidate isotope for neutrinoless double beta decay~($0\nu\beta\beta$) search. In addition, the two-neutrino case ($2\nu\beta\beta$) allowed by the Standard Model of particle physics has not yet been observed. Utilizing the 10.4% of $^{134}$Xe in the natural xenon in the PandaX-4T detector and its first 94.9-day exposure, we have established the most stringent constraints on $2\nu\beta\beta$ and $0\nu\beta\beta$ of $^{134}$Xe half-lives, with limits of $2.8\times10^{22}$ yr and $3.0\times10^{23}$ yr at 90% confidence level, respectively. The $2\nu\beta\beta$ ($0\nu\beta\beta$) limit surpasses the previously reported best result by a factor of 32 (2.7), highlighting the potential of large monolithic natural xenon detectors.
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- 2023
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16. Waveform Simulation in PandaX-4T
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Li, Jiafu, Abdukerim, Abdusalam, Cheng, Chen, Bo, Zihao, Chen, Wei, Chen, Xun, Chen, Yunhua, Cheng, Zhaokan, Cui, Xiangyi, Fan, Yingjie, Fang, Deqing, Fu, Changbo, Fu, Mengting, Geng, Lisheng, Giboni, Karl, Gu, Linhui, Guo, Xuyuan, Han, Chencheng, Han, Ke, He, Changda, He, Jinrong, Huang, Di, Huang, Yanlin, Huang, Zhou, Hou, Ruquan, Ji, Xiangdong, Ju, Yonglin, Li, Chenxiang, Li, Mingchuan, Li, Shu, Li, Shuaijie, Lin, Qing, Liu, Jianglai, Lu, Xiaoying, Luo, Lingyin, Luo, Yunyang, Ma, Wenbo, Ma, Yugang, Mao, Yajun, Shaheed, Nasir, Meng, Yue, Ning, Xuyang, Qi, Ningchun, Qian, Zhicheng, Ren, Xiangxiang, Shang, Changsong, Shang, Xiaofeng, Shen, Guofang, Si, Lin, Sun, Wenliang, Tan, Andi, Tao, Yi, Wang, Anqing, Wang, Meng, Wang, Qiuhong, Wang, Shaobo, Wang, Siguang, Wang, Wei, Wang, Xiuli, Wang, Zhou, Wei, Yuehuan, Wu, Mengmeng, Wu, Weihao, Xia, Jingkai, Xiao, Mengjiao, Xiao, Xiang, Xie, Pengwei, Yan, Binbin, Yan, Xiyu, Yang, Jijun, Yang, Yong, Yu, Chunxu, Yuan, Jumin, Yuan, Ying, Yuan, Zhe, Zeng, Xinning, Zhang, Dan, Zhang, Minzhen, Zhang, Peng, Zhang, Shibo, Zhang, Shu, Zhang, Tao, Zhang, Yingxin, Zhang, Yuanyuan, Zhao, Li, Zheng, Qibin, Zhou, Jifang, Zhou, Ning, Zhou, Xiaopeng, Zhou, Yong, and Zhou, Yubo
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High Energy Physics - Experiment ,Physics - Instrumentation and Detectors - Abstract
Signal reconstruction through software processing is a crucial component of the background and signal models in the PandaX-4T experiment, which is a multi-tonne dark matter direct search experiment. The accuracy of signal reconstruction is influenced by various detector artifacts, including noise, dark count of photomultiplier, impurity photoionization in the detector, and other relevant considerations. In this study, we present a detailed description of a semi-data-driven approach designed to simulate the signal waveform. This work provides a reliable model for the efficiency and bias of the signal reconstruction in the data analysis of PandaX-4T. By comparing critical variables which relate to the temporal shape and hit pattern of the signals, we demonstrate a good agreement between the simulation and data.
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- 2023
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17. Novel small multidrug resistance protein Tmt endows the Escherichia coli with triphenylmethane dyes bioremediation capability
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Wang, Zhou, Zhou, Haoqiang, Cheng, Yilan, An, Lijin, Yan, Dazhong, Chao, Hongjun, and Wu, Jing
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- 2024
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18. Selective sintering of magnesia–calcia materials by utilizing hot spots during induction sintering process
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Dong, Yun-jie, Wang, Zhou-fu, Liu, Hao, Ma, Yan, Wang, Xi-tang, Yi, Nian, Xia, Zhong-feng, Zhu, Yu-xuan, Deng, Cheng-ji, and Zhang, Ling
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- 2024
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19. Growth rate determines the superior xylem growth of Siberian spruce over Siberian larch in the southern Altai Mountains, Northwest China
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Wang, Wenjin, Huang, Jian-Guo, Yang, Feiyu, Zhou, Peng, Wang, Zhou, and Rossi, Sergio
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- 2024
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20. Study of photophysical properties in bronsted acids for nitrogen atoms with different hybrid (sp, sp2, sp3) orbitals
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Wang, Zhou, Hu, Kaibo, Lu, Chichong, and Jin, Guofan
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- 2024
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21. In-situ SEM characterization of fracture mechanism of TiB/Ti-2Al-6Sn titanium matrix composites after electroshocking treatment
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Wu, Ya-Ya, Zhou, Jian, Han, Guo-Lei, Wen, Yan, Wang, Zhou, Wang, Li-Qiang, Lv, Wei-Jie, Xie, Le-Chun, and Hua, Lin
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- 2024
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22. Influence of in situ formed spinel in bonding phase on mechanical properties and air permeability of magnesia–chrome porous purging materials
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An, Yi, Liu, Hao, Wang, Zhou-fu, Ma, Yan, and Wang, Xi-tang
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- 2024
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23. Reduced implication-bias logic loss for neuro-symbolic learning
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He, Hao-Yuan, Dai, Wang-Zhou, and Li, Ming
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- 2024
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24. Preparation of yttrium oxide coating with enhanced thermal shock resistance on refractories used for titanium alloy melting and casting
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Chen, Ao, Ma, Yan, Wang, Zhou-fu, Liu, Hao, Wang, Xi-tang, Chen, Sen-na, Zhang, Chen-xin, Tang, Zi-yi, Fu, Wei-dong, and Cheng, Wei
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- 2024
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25. AutoML for Large Capacity Modeling of Meta's Ranking Systems
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Yin, Hang, Liu, Kuang-Hung, Sun, Mengying, Chen, Yuxin, Zhang, Buyun, Liu, Jiang, Sehgal, Vivek, Panchal, Rudresh Rajnikant, Hotaj, Eugen, Liu, Xi, Guo, Daifeng, Zhang, Jamey, Wang, Zhou, Jiang, Shali, Li, Huayu, Chen, Zhengxing, Chen, Wen-Yen, Yang, Jiyan, and Wen, Wei
- Subjects
Computer Science - Information Retrieval ,Computer Science - Artificial Intelligence - Abstract
Web-scale ranking systems at Meta serving billions of users is complex. Improving ranking models is essential but engineering heavy. Automated Machine Learning (AutoML) can release engineers from labor intensive work of tuning ranking models; however, it is unknown if AutoML is efficient enough to meet tight production timeline in real-world and, at the same time, bring additional improvements to the strong baselines. Moreover, to achieve higher ranking performance, there is an ever-increasing demand to scale up ranking models to even larger capacity, which imposes more challenges on the efficiency. The large scale of models and tight production schedule requires AutoML to outperform human baselines by only using a small number of model evaluation trials (around 100). We presents a sampling-based AutoML method, focusing on neural architecture search and hyperparameter optimization, addressing these challenges in Meta-scale production when building large capacity models. Our approach efficiently handles large-scale data demands. It leverages a lightweight predictor-based searcher and reinforcement learning to explore vast search spaces, significantly reducing the number of model evaluations. Through experiments in large capacity modeling for CTR and CVR applications, we show that our method achieves outstanding Return on Investment (ROI) versus human tuned baselines, with up to 0.09% Normalized Entropy (NE) loss reduction or $25\%$ Query per Second (QPS) increase by only sampling one hundred models on average from a curated search space. The proposed AutoML method has already made real-world impact where a discovered Instagram CTR model with up to -0.36% NE gain (over existing production baseline) was selected for large-scale online A/B test and show statistically significant gain. These production results proved AutoML efficacy and accelerated its adoption in ranking systems at Meta., Comment: Hang Yin and Kuang-Hung Liu contribute equally
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- 2023
26. Generating by Understanding: Neural Visual Generation with Logical Symbol Groundings
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Peng, Yifei, Jin, Yu, Luo, Zhexu, Ding, Yao-Xiang, Dai, Wang-Zhou, Ren, Zhong, and Zhou, Kun
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Computer Science - Artificial Intelligence ,Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Graphics - Abstract
Despite the great success of neural visual generative models in recent years, integrating them with strong symbolic reasoning systems remains a challenging task. There are two levels of symbol grounding problems among the core challenges: the first is symbol assignment, i.e. mapping latent factors of neural visual generators to semantic-meaningful symbolic factors from the reasoning systems by learning from limited labeled data. The second is rule learning, i.e. learning new rules that govern the generative process to enhance the symbolic reasoning systems. To deal with these two problems, we propose a neurosymbolic learning approach, Abductive visual Generation (AbdGen), for integrating logic programming systems with neural visual generative models based on the abductive learning framework. To achieve reliable and efficient symbol grounding, the quantized abduction method is introduced for generating abduction proposals by the nearest-neighbor lookup within semantic codebooks. To achieve precise rule learning, the contrastive meta-abduction method is proposed to eliminate wrong rules with positive cases and avoid less informative rules with negative cases simultaneously. Experimental results show that compared to the baseline approaches, AbdGen requires significantly less labeled data for symbol assignment. Furthermore, AbdGen can effectively learn underlying logical generative rules from data, which is out of the capability of existing approaches. The code is released at this link: https://github.com/candytalking/AbdGen.
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- 2023
27. Perceptual Quality Assessment of 360$^\circ$ Images Based on Generative Scanpath Representation
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Sui, Xiangjie, Zhu, Hanwei, Liu, Xuelin, Fang, Yuming, Wang, Shiqi, and Wang, Zhou
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Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Despite substantial efforts dedicated to the design of heuristic models for omnidirectional (i.e., 360$^\circ$) image quality assessment (OIQA), a conspicuous gap remains due to the lack of consideration for the diversity of viewing behaviors that leads to the varying perceptual quality of 360$^\circ$ images. Two critical aspects underline this oversight: the neglect of viewing conditions that significantly sway user gaze patterns and the overreliance on a single viewport sequence from the 360$^\circ$ image for quality inference. To address these issues, we introduce a unique generative scanpath representation (GSR) for effective quality inference of 360$^\circ$ images, which aggregates varied perceptual experiences of multi-hypothesis users under a predefined viewing condition. More specifically, given a viewing condition characterized by the starting point of viewing and exploration time, a set of scanpaths consisting of dynamic visual fixations can be produced using an apt scanpath generator. Following this vein, we use the scanpaths to convert the 360$^\circ$ image into the unique GSR, which provides a global overview of gazed-focused contents derived from scanpaths. As such, the quality inference of the 360$^\circ$ image is swiftly transformed to that of GSR. We then propose an efficient OIQA computational framework by learning the quality maps of GSR. Comprehensive experimental results validate that the predictions of the proposed framework are highly consistent with human perception in the spatiotemporal domain, especially in the challenging context of locally distorted 360$^\circ$ images under varied viewing conditions. The code will be released at https://github.com/xiangjieSui/GSR, Comment: 12 pages, 5 figures
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- 2023
28. Rapid Detection of Heavy Metal Ions Co3+, Cu2+, Ni2+, and Zn2+ in Wastewater By Pyrimidine–Thiourea Ligand
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Wang, Zhou and Jin, Feng
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- 2024
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29. Human Comprehensible Active Learning of Genome-Scale Metabolic Networks
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Ai, Lun, Liang, Shi-Shun, Dai, Wang-Zhou, Hallett, Liam, Muggleton, Stephen H., and Baldwin, Geoff S.
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Computer Science - Artificial Intelligence ,Computer Science - Machine Learning ,Quantitative Biology - Molecular Networks ,Quantitative Biology - Quantitative Methods - Abstract
An important application of Synthetic Biology is the engineering of the host cell system to yield useful products. However, an increase in the scale of the host system leads to huge design space and requires a large number of validation trials with high experimental costs. A comprehensible machine learning approach that efficiently explores the hypothesis space and guides experimental design is urgently needed for the Design-Build-Test-Learn (DBTL) cycle of the host cell system. We introduce a novel machine learning framework ILP-iML1515 based on Inductive Logic Programming (ILP) that performs abductive logical reasoning and actively learns from training examples. In contrast to numerical models, ILP-iML1515 is built on comprehensible logical representations of a genome-scale metabolic model and can update the model by learning new logical structures from auxotrophic mutant trials. The ILP-iML1515 framework 1) allows high-throughput simulations and 2) actively selects experiments that reduce the experimental cost of learning gene functions in comparison to randomly selected experiments., Comment: Invited presentation for AAAI Spring Symposium Series 2023 on Computational Scientific Discovery
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- 2023
30. Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees
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Tao, Lue, Huang, Yu-Xuan, Dai, Wang-Zhou, and Jiang, Yuan
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Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
Neuro-symbolic hybrid systems are promising for integrating machine learning and symbolic reasoning, where perception models are facilitated with information inferred from a symbolic knowledge base through logical reasoning. Despite empirical evidence showing the ability of hybrid systems to learn accurate perception models, the theoretical understanding of learnability is still lacking. Hence, it remains unclear why a hybrid system succeeds for a specific task and when it may fail given a different knowledge base. In this paper, we introduce a novel way of characterising supervision signals from a knowledge base, and establish a criterion for determining the knowledge's efficacy in facilitating successful learning. This, for the first time, allows us to address the two questions above by inspecting the knowledge base under investigation. Our analysis suggests that many knowledge bases satisfy the criterion, thus enabling effective learning, while some fail to satisfy it, indicating potential failures. Comprehensive experiments confirm the utility of our criterion on benchmark tasks.
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- 2023
31. Search for Dark-Matter-Nucleon Interactions with a Dark Mediator in PandaX-4T
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Huang, Di, Abdukerim, Abdusalam, Bo, Zihao, Chen, Wei, Chen, Xun, Chen, Yunhua, Cheng, Chen, Cheng, Zhaokan, Cui, Xiangyi, Fan, Yingjie, Fang, Deqing, Fu, Changbo, Fu, Mengting, Geng, Lisheng, Giboni, Karl, Gu, Linhui, Guo, Xuyuan, Han, Chencheng, Han, Ke, He, Changda, He, Jinrong, Huang, Yanlin, Huang, Zhou, Hou, Ruquan, Ji, Xiangdong, Ju, Yonglin, Li, Chenxiang, Li, Jiafu, Li, Mingchuan, Li, Shu, Li, Shuaijie, Lin, Qing, Liu, Jianglai, Lu, Xiaoying, Luo, Lingyin, Luo, Yunyang, Ma, Wenbo, Ma, Yugang, Mao, Yajun, Meng, Yue, Ning, Xuyang, Qi, Ningchun, Qian, Zhicheng, Ren, Xiangxiang, Shaheed, Nasir, Shang, Changsong, Shang, Xiaofeng, Shen, Guofang, Si, Lin, Sun, Wenliang, Tan, Andi, Tao, Yi, Wang, Anqing, Wang, Meng, Wang, Qiuhong, Wang, Shaobo, Wang, Siguang, Wang, Wei, Wang, Xiuli, Wang, Zhou, Wei, Yuehuan, Wu, Mengmeng, Wu, Weihao, Xia, Jingkai, Xiao, Mengjiao, Xiao, Xiang, Xie, Pengwei, Yan, Binbin, Yan, Xiyu, Yang, Jijun, Yang, Yong, Yao, Yukun, Yu, Chunxu, Yuan, Jumin, Yuan, Ying, Yuan, Zhe, Zeng, Xinning, Zhang, Dan, Zhang, Minzhen, Zhang, Peng, Zhang, Shibo, Zhang, Shu, Zhang, Tao, Zhang, Yang, Zhang, Yingxin, Zhang, Yuanyuan, Zhao, Li, Zheng, Qibin, Zhou, Jifang, Zhou, Ning, Zhou, Xiaopeng, Zhou, Yong, Zhou, Yubo, Huo, Ran, and Yu, Hai-Bo
- Subjects
High Energy Physics - Experiment ,High Energy Physics - Phenomenology - Abstract
We report results of a search for dark-matter-nucleon interactions via a dark mediator using optimized low-energy data from the PandaX-4T liquid xenon experiment. With the ionization-signal-only data and utilizing the Migdal effect, we set the most stringent limits on the cross section for dark matter masses ranging from 30~$\rm{MeV/c^2}$ to 2~$\rm{GeV/c^2}$. Under the assumption that the dark mediator is a dark photon that decays into scalar dark matter pairs in the early Universe, we rule out significant parameter space of such thermal relic dark-matter model., Comment: 6 pages, 4 figures
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- 2023
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32. DEPDC1 as a metabolic target regulates glycolysis in renal cell carcinoma through AKT/mTOR/HIF1α pathway
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Si-chen Di, Wen-jin Chen, Wei Yang, Xiang-min Zhang, Ke-qin Dong, Yi-jun Tian, Ye Sun, Cheng Qian, Jia-xin Chen, Zi-chang Liu, Zi-xuan Gong, Jian Chu, Wang Zhou, Xiu-wu Pan, and Xin-gang Cui
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Cytology ,QH573-671 - Abstract
Abstract Renal cell carcinoma (RCC) is considered a “metabolic disease” characterized by elevated glycolysis in patients with advanced RCC. Tyrosine kinase inhibitor (TKI) therapy is currently an important treatment option for advanced RCC, but drug resistance may develop in some patients. Combining TKI with targeted metabolic therapy may provide a more effective approach for patients with advanced RCC. An analysis of 14 RCC patients (including three needle biopsy samples with TKI resistance) revealed by sing-cell RNA sequencing (scRNA-seq) that glycolysis played a crucial role in poor prognosis and drug resistance in RCC. TCGA-KIRC and glycolysis gene set analysis identified DEPDC1 as a target associated with malignant progression and drug resistance in KIRC. Subsequent experiments demonstrated that DEPDC1 promoted malignant progression and glycolysis of RCC, and knockdown DEPDC1 could reverse TKI resistance in RCC cell lines. Bulk RNA sequencing (RNA-seq) and non-targeted metabolomics sequencing suggested that DEPDC1 may regulate RCC glycolysis via AKT/mTOR/HIF1α pathway, a finding supported by protein-level analysis. Clinical tissue samples from 98 RCC patients demonstrated that DEPDC1 was associated with poor prognosis and predicted RCC metastasis. In conclusion, this multi-omics analysis suggests that DEPDC1 could serve as a novel target for TKI combined with targeted metabolic therapy in advanced RCC patients with TKI resistance.
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- 2024
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33. Enhancing Cross-Modal Understanding for Audio Visual Scene-Aware Dialog Through Contrastive Learning.
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Feifei Xu, Wang Zhou, Guangzhen Li, Zheng Zhong, and Yingchen Zhou
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- 2024
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34. Safe Abductive Learning in the Presence of Inaccurate Rules.
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Xiaowen Yang, Jie-Jing Shao, Wei-Wei Tu, Yufeng Li 0008, Wang-Zhou Dai, and Zhi-Hua Zhou
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- 2024
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35. Knowledge-Enhanced Historical Document Segmentation and Recognition.
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En-Hao Gao, Yu-Xuan Huang, Wen-Chao Hu, Xin-Hao Zhu, and Wang-Zhou Dai
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- 2024
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36. Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees.
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Lue Tao, Yu-Xuan Huang, Wang-Zhou Dai, and Yuan Jiang 0001
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- 2024
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37. A Coarse and Fine Grained Masking Approach for Video-Grounded Dialogue.
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Feifei Xu, Wang Zhou, Tao Sun, Jiahao Lu, Ziheng Yu, and Guangzhen Li
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- 2024
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38. Photo-Thermo Catalytic Conversion of CO2: What, Why, How and Future Perspectives
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Wang, Zhou-jun, Song, Hui, Xie, Guiming, Wang, Xiaorui, Ye, Jinhua, He, Liang-Nian, Series Editor, Tundo, Pietro, Series Editor, Zhang, Z. Conrad, Series Editor, Zhang, Guoliang, editor, Bogaerts, Annemie, editor, Ye, Jingyun, editor, and Liu, Chang-jun, editor
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- 2024
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39. Research on the Acid Fracturing Technology of Asphaltic Reservoir
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Fu, Yan, Li, Li, Yang, Miao, Wang, Zhou-yang, Li, Jin-sui, Jia, Yu-cheng, Wu, Wei, Series Editor, and Lin, Jia'en, editor
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- 2024
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40. Fracture Extension Law and Process Optimization of Lianggaoshan Formation Shale Reservoir in Sichuan Basin
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Lv, Ze-fei, Li, Wen-zhe, Wang, Yang, Chen, Wei-hua, Wang, Zhou-yang, He, Rui, Wu, Wei, Series Editor, and Lin, Jia'en, editor
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- 2024
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41. Experimental Evaluation of the Succession Sequence During Commingled Production in a Tight Gas Reservoir
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Yang, Hong-nan, Yue, Ping, Wang, Zhou-hua, Wang, Mu-tong, Chen, Yuan-yong, Zhou, Yong-yi, Qu, Si-min, Wu, Wei, Series Editor, and Lin, Jia'en, editor
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- 2024
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42. An efficiency calibration method of segmented gamma scanning in reconstructing radioactive waste drum activity
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Zheng, Honglong, Tuo, Xianguo, Wang, Zhou, Gou, Rui, Liu, Qi, Li, Qiang, Shi, Rui, and Yang, Guang
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- 2024
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43. Blind Omnidirectional Image Quality Assessment: Integrating Local Statistics and Global Semantics
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Zhou, Wei and Wang, Zhou
- Subjects
Computer Science - Multimedia ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Omnidirectional image quality assessment (OIQA) aims to predict the perceptual quality of omnidirectional images that cover the whole 180$\times$360$^{\circ}$ viewing range of the visual environment. Here we propose a blind/no-reference OIQA method named S$^2$ that bridges the gap between low-level statistics and high-level semantics of omnidirectional images. Specifically, statistic and semantic features are extracted in separate paths from multiple local viewports and the hallucinated global omnidirectional image, respectively. A quality regression along with a weighting process is then followed that maps the extracted quality-aware features to a perceptual quality prediction. Experimental results demonstrate that the proposed S$^2$ method offers highly competitive performance against state-of-the-art methods.
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- 2023
44. Design, construction and commissioning of the PandaX-30T liquid xenon management system
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Wang, Xiuli, Lei, Zhuoqun, Ju, Yonglin, Liu, Jianglai, Zhou, Ning, Chen, Yu, Wang, Zhou, Cui, Xiangyi, Meng, Yue, and Zhao, Li
- Subjects
Physics - Instrumentation and Detectors - Abstract
The PandaX-30T is a proposed next-generation experiment to study dark matter and neutrinos using a dual-phase time projection chamber with \textasciitilde30 tons of liquid xenon. An innovative xenon handling subsystem of the PandaX-30T, the First-X, is described in this paper. The First-X is developed to handle liquid xenon safely and efficiently, including liquefying and long-term storing xenon without losses or contamination, and transferring cryogenic liquid xenon between the storage module and the detector safely and effectively without venting out. The storage module of the First-X is five specially designed double-walled cylindrical vessels (Center Tanks) equipped with three heat exchangers each for pressure and temperature regulation. Each Center Tank is designed with a vacuum and multi-layer insulation and a maximum allowable working pressure of 7.1 MPa, allowing 6 tons of xenon to be stored at 165--178 K at 0.1--0.2 MPa in the liquid phase or up to 300 K and up to 6.95 MPa in the supercritical phase. High-pressure storage (\textgreater0.2 MPa) only occurs in case of long-term detector shutdown or lack of nitrogen, ensuring no-loss storage of 6 tons of xenon in the range 178--300 K. In this paper, the thermophysical performances of the First-X and innovative scenarios to conduct non-vented cryogen transportation were experimentally conducted and reported using liquid argon. The non-vented cryogenic liquid filling and pump-assisted cryogenic liquid recovery have been conducted with liquid argon at a mass flow rate of 1390 kg/h, corresponding to a xenon mass flow rate of 2140 kg/h. Compared with the PandaX-4T, the transportation of xenon between the detector and the storage module is conducted in the liquid phase rather than in the gaseous phase, and the filling rate and the recovery rate are increased by approximately 50 times and 30 times, respectively., Comment: 25 pages, 17 figures
- Published
- 2023
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45. Search for light dark matter from atmosphere in PandaX-4T
- Author
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Ning, Xuyang, Abdukerim, Abdusalam, Bo, Zihao, Chen, Wei, Chen, Xun, Chen, Yunhua, Cheng, Chen, Cheng, Zhaokan, Cui, Xiangyi, Fan, Yingjie, Fang, Deqing, Fu, Changbo, Fu, Mengting, Geng, Lisheng, Giboni, Karl, Gu, Linhui, Guo, Xuyuan, Han, Chencheng, Han, Ke, He, Changda, He, Jinrong, Huang, Di, Huang, Yanlin, Huang, Zhou, Hou, Ruquan, Ji, Xiangdong, Ju, Yonglin, Li, Chenxiang, Li, Jiafu, Li, Mingchuan, Li, Shu, Li, Shuaijie, Lin, Qing, Liu, Jianglai, Lu, Xiaoying, Luo, Lingyin, Luo, Yunyang, Ma, Wenbo, Ma, Yugang, Mao, Yajun, Meng, Yue, Qi, Ningchun, Qian, Zhicheng, Ren, Xiangxiang, Shaheed, Nasir, Shang, Changsong, Shang, Xiaofeng, Shen, Guofang, Si, Lin, Sun, Wenliang, Tan, Andi, Tao, Yi, Wang, Anqing, Wang, Meng, Wang, Qiuhong, Wang, Shaobo, Wang, Siguang, Wang, Wei, Wang, Xiuli, Wang, Zhou, Wei, Yuehuan, Wu, Mengmeng, Wu, Weihao, Xia, Jingkai, Xiao, Mengjiao, Xiao, Xiang, Xie, Pengwei, Yan, Binbin, Yan, Xiyu, Yang, Jijun, Yang, Yong, Yao, Yukun, Yu, Chunxu, Yuan, Jumin, Yuan, Ying, Yuan, Zhe, Zeng, Xinning, Zhang, Dan, Zhang, Minzhen, Zhang, Peng, Zhang, Shibo, Zhang, Shu, Zhang, Tao, Zhang, Yang, Zhang, Yingxin, Zhang, Yuanyuan, Zhao, Li, Zheng, Qibin, Zhou, Jifang, Zhou, Ning, Zhou, Xiaopeng, Zhou, Yong, Zhou, Yubo, Su, Liangliang, and Wu, Lei
- Subjects
High Energy Physics - Experiment - Abstract
We report a search for light dark matter produced through the cascading decay of $\eta$ mesons, which are created as a result of inelastic collisions between cosmic rays and Earth's atmosphere. We introduce a new and general framework, publicly accessible, designed to address boosted dark matter specifically, with which a full and dedicated simulation including both elastic and quasi-elastic processes of Earth attenuation effect on the dark matter particles arriving at the detector is performed. In the PandaX-4T commissioning data of 0.63 tonne$\cdot$year exposure, no significant excess over background is observed. The first constraints on the interaction between light dark matter generated in the atmosphere and nucleus through a light scalar mediator are obtained. The lowest excluded cross-section is set at $5.9 \times 10^{-37}{\rm cm^2}$ for dark matter mass of $0.1$ MeV$/c^2$ and mediator mass of 300 MeV$/c^2$. The lowest upper limit of $\eta$ to dark matter decay branching ratio is $1.6 \times 10^{-7}$., Comment: 6 pages, 3 figures
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- 2023
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46. Identification of prognostic stemness-related genes in kidney renal papillary cell carcinoma
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Yifan Liu, Yuntao Yao, Yu Zhang, Chengdang Xu, Tianyue Yang, Mingyu Qu, Bingnan Lu, Xu Song, Xiuwu Pan, Wang Zhou, and Xingang Cui
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Kidney renal papillary cell carcinoma (KIRP) ,Stemness-related gene ,mRNA expression-based stemness index ,Notch signaling pathway ,Prognosis ,Target drugs ,Internal medicine ,RC31-1245 ,Genetics ,QH426-470 - Abstract
Abstract Background Kidney renal papillary cell carcinoma (KIRP) is the second most prevalent malignant cancer originating from the renal epithelium. Nowadays, cancer stem cells and stemness-related genes (SRGs) are revealed to play important roles in the carcinogenesis and metastasis of various tumors. Consequently, we aim to investigate the underlying mechanisms of SRGs in KIRP. Methods RNA-seq profiles of 141 KIRP samples were downloaded from the TCGA database, based on which we calculated the mRNA expression-based stemness index (mRNAsi). Next, we selected the differentially expressed genes (DEGs) between low- and high-mRNAsi groups. Then, we utilized weighted gene correlation network analysis (WGCNA) and univariate Cox analysis to identify prognostic SRGs. Afterwards, SRGs were included in the multivariate Cox regression analysis to establish a prognostic model. In addition, a regulatory network was constructed by Pearson correlation analysis, incorporating key genes, upstream transcription factors (TFs), and downstream signaling pathways. Finally, we used Connectivity map analysis to identify the potential inhibitors. Results In total, 1124 genes were characterized as DEGs between low- and high-RNAsi groups. Based on six prognostic SRGs (CCKBR, GPR50, GDNF, SPOCK3, KC877982.1, and MYO15A), a prediction model was established with an area under curve of 0.861. Furthermore, among the TFs, genes, and signaling pathways that had significant correlations, the CBX2-ASPH-Notch signaling pathway was the most significantly correlated. Finally, resveratrol might be a potential inhibitor for KIRP. Conclusions We suggested that CBX2 could regulate ASPH through activation of the Notch signaling pathway, which might be correlated with the carcinogenesis, development, and unfavorable prognosis of KIRP.
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- 2024
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47. Covalency competition induced selective bond breakage and surface reconstruction in manganese cobaltite towards enhanced electrochemical charge storage
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Peng Gao, Pei Tang, Ying Mo, Peitao Xiao, Wang Zhou, Shi Chen, Hongliang Dong, Ziwei Li, Chaohe Xu, and Jilei Liu
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Manganese cobaltite ,Tetrahedrally-coordinated Co2+ leaching ,Selective bond breakage ,Surface reconstruction ,Charge storage mechanisms ,Renewable energy sources ,TJ807-830 ,Ecology ,QH540-549.5 - Abstract
Manganese cobaltite (MnCo2O4) is a promising electrode material because of its attractive redox chemistry and excellent charge storage capability. Our previous work demonstrated that the octahedrally-coordinated Mn are prone to react with the hydroxyl ions in alkaline electrolyte upon electrochemical cycling and separates on the surface of spinel to reconstruct into δ-MnO2 nanosheets irreversibly, thus results in a change of the reaction mechanism with K+ ion intercalation. However, the low capacity has greatly limited its practical application. Herein, we found that the tetrahedrally-coordinated Co2+ ions were leached when MnCo2O4 was equilibrated in 1 mol L−1 HCl solution, leading to the formation of layered CoOOH on MnCo2O4 surface which is originated from the covalency competition induced selective breakage of the CoT–O bond in CoT–O–CoO and subsequent rearrangement of free CoO6 octahedra. The as-formed CoOOH is stable upon cycling in alkaline electrolyte, exhibits conversion reaction mechanism with facile proton diffusion and is free of massive structural evolution, thus enables utilization of the bulk electrode material and realizes enhanced specific capacity as well as facilitated charge transfer and ion diffusion. In general, our work not only offers a feasible approach to deliberate modification of MnCo2O4's surface structure, but also provides an in-depth understanding of its charge storage mechanism, which enables rational design of the spinel oxides with promising charge storage properties.
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- 2024
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48. Adsorption Performances and Electrochemical Characteristic of Methyl Blue onto Magnetic MgxCu(1-x)Fe2O4 Nanoparticles Prepared via the Rapid Combustion Process
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He, Nan, Lv, Zhixiang, Wang, Zhou, Zhang, Haoda, Wu, Shaobo, Li, Yongjin, and Zhang, Xianjun
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- 2024
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49. Semi-quantum private comparison and its generalization to the key agreement, summation, and anonymous ranking
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Ye, Chong-Qiang, Li, Jian, Chen, Xiu-Bo, Hou, Yanyan, and Wang, Zhou
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Quantum Physics - Abstract
Semi-quantum protocols construct connections between quantum users and ``classical'' users who can only perform certain ``classical'' operations. In this paper, we present a new semi-quantum private comparison protocol based on entangled states and single particles, which does not require pre-shared keys between the ``classical'' users to guarantee the security of their private data. By utilizing multi-particle entangled states and single particles, our protocol can be easily extended to multi-party scenarios to meet the requirements of multiple ``classical'' users who want to compare their private data. The security analysis shows that the protocol can effectively prevent attacks from outside eavesdroppers and adversarial participants. Besides, we generalize the proposed protocol to other semi-quantum protocols such as semi-quantum key agreement, semi-quantum summation, and semi-quantum anonymous ranking protocols. We compare and discuss the proposed protocols with previous similar protocols. The results show that our protocols satisfy the demands of their respective counterparts separately. Therefore, our protocols have a wide range of application scenarios., Comment: 19 pages 5 tables
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- 2022
50. Learning Acceptance Regions for Many Classes with Anomaly Detection
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Wang, Zhou and Qiao, Xingye
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Statistics - Machine Learning ,Computer Science - Machine Learning - Abstract
Set-valued classification, a new classification paradigm that aims to identify all the plausible classes that an observation belongs to, can be obtained by learning the acceptance regions for all classes. Many existing set-valued classification methods do not consider the possibility that a new class that never appeared in the training data appears in the test data. Moreover, they are computationally expensive when the number of classes is large. We propose a Generalized Prediction Set (GPS) approach to estimate the acceptance regions while considering the possibility of a new class in the test data. The proposed classifier minimizes the expected size of the prediction set while guaranteeing that the class-specific accuracy is at least a pre-specified value. Unlike previous methods, the proposed method achieves a good balance between accuracy, efficiency, and anomaly detection rate. Moreover, our method can be applied in parallel to all the classes to alleviate the computational burden. Both theoretical analysis and numerical experiments are conducted to illustrate the effectiveness of the proposed method.
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- 2022
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