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Progress in measurements of fission cross sections and total cross sections at CSNS Back-n white neutron source

Nuclear Analysis 2023年第2期2卷

作者： Liu, Rong Yang, Yiwei Ren, Zhizhou Wen, Zhongwei Wen, Jie Liu, Xingyan Chen, Yonghao Yi, Han Han, Zijie Chen, Qiping Bao, Jie An, Qi Bai, Huaiyong Cao, Ping Cheng, Pinjing Cui, Zengqi Fan, Ruirui Feng, Changqing Gu, Minhao Guo, Fengqin Han, Changcai He, Guozhu He, Yongcheng He, Yuefeng Huang, Hanxiong Huang, Weiling Huang, Xiru Ji, Xiaolu Ji, Xuyang Jiang, Haoyu Jiang, Wei Jing, Hantao Kang, Ling Kang, Mingtao Li, Bo Li, Lun Li, Qiang Li, Xiao Li, Yang Liu, Shubin Luan, Guangyuan Ma, Yinglin Ning, Changjun Qi, Binbin Ren, Jie Ruan, Xichao Song, Zhaohui Sun, Hong Sun, Xiaoyang Sun, Zhijia Tan, Zhixin Tang, Hongqing Tang, Jingyu Wang, Pengcheng Wang, Qi Wang, Taofeng Wang, Yanfeng Wang, Zhaohui Wang, Zheng Wu, Qingbiao Wu, Xiaoguang Wu, Xuan Xie, Likun Yu, Li Yu, Tao Yu, Yongji Zhang, Guohui Zhang, Jing Zhang, Linhao Zhang, Liying Zhang, Qingmin Zhang, Qiwei Zhang, Xianpeng Zhang, Yuliang Zhang, Zhiyong Zhao, Yingtan Zhou, Liang Zhou, Zuying Zhu, Danyang Zhu, Kejun Zhu, Peng Institute of Nuclear Physics and Chemistry China Academy of Engineering Physics Mianyang 621900 China Department of Modern Physics University of Science and Technology of China Hefei 230026 China Institute of High Energy Physics Chinese Academy of Sciences (CAS) Beijing 100049 China Spallation Neutron Source Science Center Dongguan 523803 China Key Laboratory of Nuclear Data China Institute of Atomic Energy Beijing 102413 China State Key Laboratory of Particle Detection and Electronics University of Science and Technology of China Heifei 230026 China State Key Laboratory of Nuclear Physics and Technology School of Physics Peking University Beijing 100871 China School of Nuclear Science & Technology University of Science and Technology of China Hefei 230026 China University of South China Hengyang 421001 China Sate Key Laboratory of Particle Detection and Electronics Institute of High Energy Physics Chinese Academy of Sciences Beijing 100049 China Northwest Institute of Nuclear Technology Xi'an 710024 China Department of Engineering and Applied Physics University of Science and Technology of China Hefei 230026 China School of Physics Beihang University Beijing 100083 China Xi'an Jiaotong University Xi'an 710049 China

The neutron-induced cross sections are of great significance for the design of nuclear devices and advanced reactors for the nuclear energy production. At CSNS Back-n white neutron source, new measurements of the fission cross sections and total cross sections are performed with two sets of Day-one spectrometers based on the multi-cell fast fission ionization chamber (FIC). The neutron-induced ^236,238U fission cross sections relative to ²³⁵U from the fission threshold energy to 200 MeV were measured by using the TOF method and the Fast Ionization Chamber Spectrometer for Fission Cross Section Measurement (FIXM) in the single/double bunch mode of Back-n. The experimental uncertainties are analyzed in detail, and the results from the two modes are consistent. The measured ^236,238U/²³⁵U fission cross section ratios are compared with previous experiments and evaluations. The ^236,238U(n,f) cross sections are obtained based on the standard ²³⁵U fission cross section. The neutron total cross sections of carbon and aluminum in the energy region from 1 eV to 20 MeV have been measured by using the TOF method and transmission method based on the Neutron Total Cross Section Spectrometer (NTOX) in the double bunch mode. The total cross section results after unfolding are in good agreement with the previous measurements as well as the broadening of the ENDF/B-Ⅷ.0 evaluation with Gaussian function within the experimental uncertainty. The present results provide the experimental data for further measurements, relevant evaluations and the design of nuclear system. © 2023 The Authors

关键词： CSNS Back-n data analysis Fission cross section Multi-cell fast fission chamber Total cross section

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A knowledge-driven generative model for multi-implication Chinese medical procedure entity normalization

A knowledge-driven generative model for multi-implication Ch...

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2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020

作者： Yan, Jinghui Wang, Yining Xiang, Lu Zhou, Yu Zong, Chengqing School of Computer Science and Information Technology Beijing Key Lab of Traffic Data Analysis and Mining Beijing Jiaotong University Beijing China National Laboratory of Pattern Recognition Institute of Automation CAS Beijing China University of Chinese Academy of Sciences Beijing China CAS Center for Excellence in Brain Science and Intelligence Technology Beijing China Beijing Fanyu Technology Co. Ltd China

ISBN: (纸本)9781952148606

Medical entity normalization, which links medical mentions in the text to entities in knowledge bases, is an important research topic in medical natural language processing. In this paper, we focus on Chinese medical procedure entity normalization. However, nonstandard Chinese expressions and combined procedures present challenges in our problem. The existing strategies relying on the discriminative model are poorly to cope with normalizing combined procedure mentions. We propose a sequence generative framework to directly generate all the corresponding medical procedure entities. we adopt two strategies: category-based constraint decoding and category-based model refining to avoid unrealistic results. The method is capable of linking entities when a mention contains multiple procedure concepts and our comprehensive experiments demonstrate that the proposed model can achieve remarkable improvements over existing baselines, particularly significant in the case of multi-implication Chinese medical procedures. © 2020 Association for Computational Linguistics

关键词： Natural language processing systems

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Decoding error probability of random parity-check matrix ensemble over the erasure channel

arXiv

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arXiv 2021年

作者： Chan, Chin Hei Fu, Fang-Wei Xiong, Maosheng Mathematics Department Hong Kong University of Science and Technology Clear Water Bay Hong Kong Chern Institute of Mathematics and LPMC The Tianjin Key Laboratory of Network and Data Security Technology Nankai University Tianjin300071 China

Using tools developed in a work by Shen and the second author, in this paper we carry out an in-depth study on the average decoding error probability of the random parity-check matrix ensemble over the erasure channel under three decoding principles, namely unambiguous decoding, maximum likelihood decoding and list decoding. We obtain explicit formulas for the average decoding error probabilities of the random parity-check matrix ensemble under these three decoding principles and compute the error exponents. Moreover, for unambiguous decoding, we compute the variance of the decoding error probability of the random parity-check matrix ensemble and the error exponent of the variance, which implies a strong concentration result, that is, roughly speaking, the ratio of the decoding error probability of a random linear code in the ensemble and the average decoding error probability of the ensemble converges to 1 with high probability when the code length goes to *** Codes 94A40, 94B70 Copyright © 2021, The Authors. All rights reserved.

关键词： Decoding

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Toripalimab plus chemotherapy as second-line treatment in previously EGFR-TKI treated patients with EGFR-mutant-advanced NSCLC:a multicenter phase-II trial

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Signal Transduction and Targeted Therapy 2021年第11期6卷 3295-3303页

作者： Tao Jiang Pingyang Wang Jie Zhang Yanqiu Zhao Jianying Zhou Yun Fan Yongqian Shu Xiaoqing Liu Helong Zhang Jianxing He Guanghui Gao Xiaoqian Mu Zhang Bao Yanjun Xu Renhua Guo Hong Wang Lin Deng Ningqiang Ma Yalei Zhang Hui Feng Sheng Yao Jiarui Wu Luonan Chen Caicun Zhou Shengxiang Ren Shanghai Pulmonary Hospital Tongji University School of MedicineShanghaiChina State Key Laboratory of Cell Biology Innovation Center for Cell Signaling NetworkCAS Center for Excellence in Molecular Cell ScienceShanghai Institute of Biochemistry and Cell BiologyChinese Academy of SciencesUniversity of Chinese Academy of SciencesShanghaiChina Henan Cancer Hospital ZhengzhouChina The First Affiliated Hospital of Zhejiang University HangzhouChina Zhejiang Cancer Hospital HangzhouChina Jiangsu Province Hospital NanjingChina The Fifth Medical Center of PLA General Hospital BeijingChina Tangdu Hospital Fourth Military Medical UniversityXi’anChina The First Affiliated Hospital of Guangzhou Medical University GuangzhouChina Shanghai Junshi Biosciences Co.Ltd ShanghaiChina Key Laboratory of Systems Health Science of Zhejiang Province Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhouChina School of Life Science and Technology ShanghaiTech UniversityShanghaiChina

This multicenter phase-II trial aimed to investigate the efficacy,safety,and predictive biomarkers of toripalimab plus chemotherapy as second-line treatment in patients with EGFR-mutant-advanced *** who failed from first-line EGFR-TKIs and did not harbor T790M mutation were *** plus carboplatin and pemetrexed were administrated every three weeks for up to six cycles,followed by the maintenance of toripalimab and *** primary endpoint was objective-response rate(ORR).Integrated biomarker analysis of PD-L1 expression,tumor mutational burden(TMB),CD8+tumor-infiltrating lymphocyte(TIL)density,whole-exome,and transcriptome sequencing on tumor biopsies were also *** patients were enrolled with an overall ORR of 50.0%and disease-control rate(DCR)of 87.5%.The median progression free survival(PFS)and overall survival were 7.0 and 23.5 months,*** most common treatment-related adverse effects were leukopenia,neutropenia,anemia,ALT/AST elevation,and *** analysis showed that none of PD-L1 expression,TMB level,and CD8+TIL density could serve as a predictive *** analysis of whole-exome and transcriptome sequencing data revealed that patients with DSPP mutation had a decreased M2 macrophage infiltration and associated with longer PFS than those of wild *** plus chemotherapy showed a promising anti-tumor activity with acceptable safety profiles as the second-line setting in patients with EGFR-mutant *** mutation might serve as a potential biomarker for this combination.A phase-III trial to compare toripalimab versus placebo in combination with chemotherapy in this setting is ongoing(NCT03924050).

关键词： NSCLC chemotherapy treatment

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Low Complexity SLM for OFDMA System with Implicit Side Information

Low Complexity SLM for OFDMA System with Implicit Side Infor...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Shicheng Hu Miao Yang Kai Kang Hua Qian School of Information Science and Technology Shanghai Tech University Shanghai China Shanghai Advanced Research Institute Chinese Academy of Sciences (CAS) Shanghai China University of Chinese Academy of Sciences Beijing China Key Laboratory of Wireless Sensor Network Communication CAS China

Selected mapping (SLM) is an efficient peak-to-average-power-ratio (PAPR) reduction algorithm for orthogonal frequency division multiplexing (OFDM) systems. Conventional SLM requires extra resources for side information transmission. If the side information is transmitted implicitly, significantly high computation overhead is imposed to the receiver at the user equipment (UE) side. In the orthogonal frequency division multiple access (OFDMA) system, the SLM can not be directly applied since the UE does not have access to the signal of other UEs. In this paper, we propose a novel SLM algorithm for the OFDMA system that requires no side information transmission. With the proposed SLM algorithm, each UE can receive its own data without the knowledge of other UEs. The SLM demapping at the UE side is much simplified. Besides, detection of the implicit side information with the proposed algorithm is more robust than existing SLM algorithms. Numerical results validate the theoretical performance of the proposed algorithm.

关键词： Signal processing algorithms Peak to average power ratio Information processing Receivers Signal processing Frequency conversion Complexity theory

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Label-consistency based graph neural networks for semi-supervised node classification

arXiv

引用

arXiv 2020年

作者： Xu, Bingbing Huang, Junjie Hou, Liang Shen, Huawei Gao, Jinhua Cheng, Xueqi CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences China School of Computer and Control Engineering University of Chinese Academy of Sciences China

Graph neural networks (GNNs) achieve remarkable success in graph-based semi-supervised node classification, leveraging the information from neighboring nodes to improve the representation learning of target node. The success of GNNs at node classification depends on the assumption that connected nodes tend to have the same label. However, such an assumption does not always work, limiting the performance of GNNs at node classification. In this paper, we propose label-consistency based graph neural network (LC-GNN), leveraging node pairs unconnected but with the same labels to enlarge the receptive field of nodes in GNNs. Experiments on benchmark datasets demonstrate the proposed LC-GNN outperforms traditional GNNs in graph-based semi-supervised node classification. We further show the superiority of LC-GNN in sparse scenarios with only a handful of labeled nodes. Copyright © 2020, The Authors. All rights reserved.

关键词： Graph neural networks

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Side-channel-free quantum key distribution with practical devices

arXiv

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arXiv 2022年

作者： Jiang, Cong Yu, Zong-Wen Hu, Xiao-Long Wang, Xiang-Bin Jinan Institute of Quantum Technology Shandong Jinan250101 China State Key Laboratory of Low Dimensional Quantum Physics Department of Physics Tsinghua University Beijing100084 China Data Communication Science and Technology Research Institute Beijing100191 China School of Physics State Key Laboratory of Optoelectronic Materials and Technologies Sun Yat-sen University Guangzhou510275 China Shanghai Branch CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai201315 China Shenzhen Institute for Quantum Science and Engineering Physics Department Southern University of Science and Technology Shenzhen518055 China Frontier Science Center for Quantum Information Beijing China

Based on the idea that there is no side channel in the vacuum state, the side-channel-free quantum key distribution (SCFQKD) protocol was proposed, which is immune to all attacks in the source side-channel space and all attacks in the detectors. In the original SCFQKD protocol, an important assumption is that Alice and Bob can produce the perfect vacuum pulses. But due to the finite extinction ratio of the intensity modulators, the perfect vacuum pulse is impossible in practice. In this paper, we solve this problem and make the quantum key distribution side-channel secure with real source device which does not emit perfect vacuum pulses. Our conclusion only depends on the upper bounds of the intensities of the sources. No other assumptions such as stable sources and stable side channels are needed. The numerical results show that, comparing with the results of SCFQKD protocol with perfect vacuum sources, the key rates and secure distance are only slightly decreased if the upper bound of the intensity of the imperfect vacuum source is less than 10−8 which can be achieved in experiment by two-stage intensity modulator. We also show that the two-way classical communication can be used to the data post-processing of SCFQKD protocol to improve the key rate. Specially, the active odd-parity pairing method can improve the key rates in all distances by about two times and the secure distance by about 40 km. Give that the side channel security based on imperfect vacuum, this work makes it possible to realize side channel secure QKD with real devices. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum cryptography

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Sending-or-Not-Sending Twin-Field Quantum key Distribution with Redundant Space

arXiv

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arXiv 2022年

作者： Xu, Hai Hu, Xiao-Long Jiang, Cong Yu, Zong-Wen Wang, Xiang-Bin State Key Laboratory of Low Dimensional Quantum Physics Department of Physics Tsinghua University Beijing100084 China Frontier Science Center for Quantum Information Beijing China School of Physics State Key Laboratory of Optoelectronic Materials and Technologies Sun Yat-sen University Guangzhou510275 China Jinan Institute of Quantum technology SAICT Jinan250101 China Data Communication Science and Technology Research Institute Beijing100191 China Shanghai Branch CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai201315 China Shenzhen Institute for Quantum Science and Engineering Physics Department Southern University of Science and Technology Shenzhen518055 China

We propose to adopt redundant space such as polarization mode in the sending-or-not-sending Twin-Field quantum key distribution (TF-QKD) in the Fock space. With the help of redundant space such as photon polarization, we can post-select events according to the outcome of the observation to the additional quantity. This compresses the bit-flip error rate in the post-selected events of the SNS protocol. The calculation shows that the method using redundant space can greatly improve the performance in practical TF-QKD, especially when the total number of pulses is small. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum cryptography

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A lightweight privacy-preserving scheme using label-based pixel block mixing for image classification in deep learning

arXiv

引用

arXiv 2021年

作者： Xiang, Yuexin Li, Tiantian Ren, Wei Zhu, Tianqing Raymond Choo, Kim-Kwang School of Computer Science China University of Geosciences Wuhan China Henan Key Laboratory of Network Cryptography Technology Zhengzhou China Key Laboratory of Network Assessment Technology CAS Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China Department of Information Systems and Cyber Security University of Texas at San Antonio San AntonioTX78249-0631 United States

To ensure the privacy of sensitive data used in the training of deep learning models, a number of privacy-preserving methods have been designed by the research community. However, existing schemes are generally designed to work with textual data, or are not efficient when a large number of images is used for training. Hence, in this paper we propose a lightweight and efficient approach to preserve image privacy while maintaining the availability of the training set. Specifically, we design the pixel block mixing algorithm for image classification privacy preservation in deep learning. To evaluate its utility, we use the mixed training set to train the ResNet50, VGG16, InceptionV3 and DenseNet121 models on the WIKI dataset and the CNBC face dataset. Experimental findings on the testing set show that our scheme preserves image privacy while maintaining the availability of the training set in the deep learning models. Additionally, the experimental results demonstrate that we achieve good performance for the VGG16 model on the WIKI dataset and both ResNet50 and DenseNet121 on the CNBC dataset. The pixel block algorithm achieves fairly high efficiency in the mixing of the images, and it is computationally challenging for the attackers to restore the mixed training set to the original training set. Moreover, data augmentation can be applied to the mixed training set to improve the training’s *** Codes 68T07 Copyright © 2021, The Authors. All rights reserved.

关键词： Image classification

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Adaptive Fine-grained Access Control Method in Social Internet of Things

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International Journal of network Security 2021年第1期23卷 42-48页

作者： Zhang, Hongbin Ma, Pengcheng Liu, Bin School of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang China Hebei Key Laboratory of Network and Information Security Hebei Normal China School of Economics and Management Hebei University of Science China Technology Research Center of Big Data and Social Computing Hebei University of Science China

Social Internet of Things (SloT), as a new carrier of integration of social and Internet of Things, applies the research results of social networks from different aspects of the Internet of Things. Different types of connected intelligent objects interact socially, compared with random data access between them, access control technology is more stringent. This paper integrates social attributes into attributebased access control of Internet of Things, initializes relational attribute tags, and labels social interest attributes for different objects, then quantifes tag similarity and implements initial access control authorization, integrates social attributes into game theory to dynamically adjust access control policies, so the adaptive finegrained division of access control under the Social Internet of Things is effectively realized. The experimental results show that our method can not only effectively carry out initial authorization according to tag similarity, but also further adaptively adjust the permission policy according to social attributes, and further meet the finegrained partition requirements of access control, which is ensure the effective implementation of access control under the Social Internet of things. © 2021. All Rights Reserved.

关键词： Game theory

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