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Sensitivity investigation of 100-MeV proton irradiation to SiGe HBT single event effect

Chinese Physics B 2024年第1期33卷 554-562页

作者：冯亚辉郭红霞刘益维欧阳晓平张晋新马武英张凤祁白如雪马晓华郝跃 State Key Laboratory of Wide Bandgap Semiconductor Devices School of MicroelectronicsXidian UniversityXi'an 710071China School of Materials Science and Engineering Xiangtan UniversityXiangtan 411105China School of Space Science and Technology Xidian UniversityXi'an 710071China State Key Laboratory of Experimental Simulation and Effects of Strong Pulse Radiation Northwest Institute of Nuclear TechnologyXi'an 710024China

The single event effect(SEE) sensitivity of silicon–germanium heterojunction bipolar transistor(Si Ge HBT) irradiated by 100-Me V proton is investigated. The simulation results indicate that the most sensitive position of the Si Ge HBT device is the emitter center, where the protons pass through the larger collector-substrate(CS) junction. Furthermore, in this work the experimental studies are also carried out by using 100-Me V proton. In order to consider the influence of temperature on SEE, both simulation and experiment are conducted at a temperature of 93 K. At a cryogenic temperature, the carrier mobility increases, which leads to higher transient current peaks, but the duration of the current decreases ***, at the same proton flux, there is only one single event transient(SET) that occurs at 93 K. Thus, the radiation hard ability of the device increases at cryogenic temperatures. The simulation results are found to be qualitatively consistent with the experimental results of 100-Me V protons. To further evaluate the tolerance of the device, the influence of proton on Si Ge HBT after gamma-ray(^(60)Coγ) irradiation is investigated. As a result, as the cumulative dose increases, the introduction of traps results in a significant reduction in both the peak value and duration of the transient currents.

关键词： silicon–germanium heterojunction bipolar transistor(Si Ge HBT) 100-Me V proton technology computer-aided design(TCAD) single event effect(SEE)

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Research on reactor power prediction of nuclear power plant based on multivariate optimization GRU model

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International Journal of Advanced nuclear Reactor Design and technology 2024年第2期6卷 78-89页

作者： Tan, Canyi Wang, Bo Li, Jiangkuan Chen, Jie Liang, Biao Zheng, Shangcai Han, Rui Tian, Ruifeng Tan, Sichao College of Nuclear Science and Technology Harbin Engineering University Harbin150001 China Heilongjiang Provincial Key Laboratory of Nuclear Power System & Equipment Harbin Engineering University Harbin150001 China Nuclear Power Institute of China Chengdu610213 China

In the operation of nuclear power plants, the accurate prediction of power change trends is crucial for ensuring safety and stability. In this work, a ML-GRU-RS method, based on model-agnostic meta-learning (MAML), gate recurrent unit (GRU), and random search optimization, is proposed for the long-term prediction of key parameters of nuclear power plants. This method combines the fast adaptability of MAML, the time series data processing capability of GRU, and the optimization efficiency of random search to achieve high-precision predictions under varying power conditions. The results demonstrate that this method can effectively predict the future trends of key parameters in nuclear power plants. The ability of operators to anticipate these trends has been significantly enhanced, contributing to the overall safety of the nuclear power plants. © 2024 Xi'an Jiaotong University

关键词： Prediction models

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Fake Face Detection Based on Fusion of Spatial Texture and High-Frequency Noise

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Chinese Journal of Electronics 2025年第1期34卷 212-221页

作者： Dengyong Zhang Feifan Qi Jiahao Chen Jiaxin Chen Rongrong Gong Yuehong Tian Lebing Zhang Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication Engineering Changsha University of Science and Technology School of Computer and Communication Engineering Changsha University of Science and Technology Changsha Social Work College Changkuangao Beijing Technology Co. Ltd. School of Computer and Artificial Intelligence Huaihua University

The rapid development of the Internet has led to the widespread dissemination of manipulated facial images, significantly impacting people's daily lives. With the continuous advancement of Deepfake technology, the generated counterfeit facial images have become increasingly challenging to distinguish. There is an urgent need for a more robust and convincing detection method. Current detection methods mainly operate in the spatial domain and transform the spatial domain into other domains for analysis. With the emergence of transformers, some researchers have also combined traditional convolutional networks with transformers for detection. This paper explores the artifacts left by Deepfakes in various domains and, based on this exploration, proposes a detection method that utilizes the steganalysis rich model to extract high-frequency noise to complement spatial features. We have designed two main modules to fully leverage the interaction between these two aspects based on traditional convolutional neural networks. The first is the multi-scale mixed feature attention module, which introduces artifacts from high-frequency noise into spatial textures, thereby enhancing the model's learning of spatial texture features. The second is the multi-scale channel attention module, which reduces the impact of background noise by weighting the features. Our proposed method was experimentally evaluated on mainstream datasets, and a significant amount of experimental results demonstrate the effectiveness of our approach in detecting Deepfake forged faces, outperforming the majority of existing methods.

关键词： Deepfakes Adaptation models Attention mechanisms Noise Transforms Transformers Feature extraction Internet Convolutional neural networks Faces

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Effects of Hydrogen Charging Time and Pressure on the Hydrogen Embrittlement Susceptibility of X52 Pipeline Steel Material

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Acta Metallurgica Sinica(English Letters) 2024年第2期37卷 293-307页

作者： Hong-Jiang Wan Xiao-Qi Wu Hong-Liang Ming Jian-Qiu Wang En-Hou Han School of Materials Science and Engineering University of Science and Technology of ChinaShenyang110016China CAS Key Laboratory of Nuclear Materials and Safety Assessment Institute of Metal ResearchChinese Academy of SciencesShenyang110016China School of Materials Science and Engineering Northeastern UniversityShenyang110819China Institute of Corrosion Science and Technology Guangzhou510530China

The effects of hydrogen charging time and pressure on the hydrogen embrittlement(HE)susceptibility of X52 pipeline steel material are studied by slow strain rate tensile *** fracture morphologies of the specimens are observed by scanning electron *** HE susceptibility of the X52 pipeline steel material increases with an increase in both hydrogen charging time and hydrogen *** a charging time of 96 h,the HE susceptibility index reaches 45.86%,approximately 3.6 times that at a charging time of 0 ***,a charging pressure of 4 MPa results in a HE susceptibility index of 31.61%,approximately 2.5 times higher than that at a charging pressure of 0.3 MPa.

关键词： Hydrogen embrittlement X52 pipeline steel material Tubular specimen Hydrogen charging time Hydrogen charging pressure

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Effects of Aging at 550℃ on α'-Martensitic Transformation of High Si-Bearing Metastable Austenitic Stainless Steel Weld Metal

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Acta Metallurgica Sinica(English Letters) 2024年第9期37卷 1467-1479页

作者： Yakui Chen Shitong Wei Dong Wu Shanping Lu Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang110016China School of Materials Science and Engineering University of Science and Technology of ChinaShenyang110016China CAS Key Laboratory of Nuclear Materials and Safety Assessment Institute of Metal ResearchChinese Academy of SciencesShenyang110016China

The high Si-bearing 15Cr-9Ni-Nb metastable austenitic stainless steel weld metal was prepared via gas tungsten arc welding and then processed by stabilized heat treatment(SHT)at 850℃ for 3 *** effects of 550℃ aging on the α'-martensitic transformation of the as-welded and the SHT weld metals were *** results showed that the weld metal had poor thermal stability of *** precipitation of NbC during the 850℃ SHT made the thermal stability of the local matrix decrease and led to the formation of a large amount of C-depleted α'-*** precipitation of coarse σ-phase at the δ-ferrite led to the Cr-depleted zone and the formation of Cr-depleted α'-martensite at the early stage of 550℃ *** homogenized diffusion of C and Cr in the matrix during 550℃ aging led to the restoration of austenitic thermal stability and the decrease of α'-martensite *** C-depleted α'-martensite content in the SHT weld metal decreased rapidly at the early stage of aging due to the fast diffusion rate of the C atom in the matrix,while the Cr-depleted α'-martensite decreased at the later stage of aging due to the decreased diffusion rate of the Cr.

关键词： Metastable austenitic stainless steel weld metal α'-martensitic transformation δ-ferrite σ-phase

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DECRL: A Deep Evolutionary Clustering Jointed Temporal Knowledge Graph Representation Learning Approach 38

DECRL: A Deep Evolutionary Clustering Jointed Temporal Knowl...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Chen, Qian Chen, Ling State Key Laboratory of Blockchain and Data Security College of Computer Science and Technology Zhejiang University China

Temporal Knowledge Graph (TKG) representation learning aims to map temporal evolving entities and relations to embedded representations in a continuous low-dimensional vector space. However, existing approaches cannot capture the temporal evolution of high-order correlations in TKGs. To this end, we propose a Deep Evolutionary Clustering jointed temporal knowledge graph Representation Learning approach (DECRL). Specifically, a deep evolutionary clustering module is proposed to capture the temporal evolution of high-order correlations among entities. Furthermore, a cluster-aware unsupervised alignment mechanism is introduced to ensure the precise one-to-one alignment of soft overlapping clusters across timestamps, thereby maintaining the temporal smoothness of clusters. In addition, an implicit correlation encoder is introduced to capture latent correlations between any pair of clusters under the guidance of a global graph. Extensive experiments on seven real-world datasets demonstrate that DECRL achieves the state-of-the-art performances, outperforming the best baseline by an average of 9.53%, 12.98%, 10.42%, and 14.68% in MRR, Hits@1, Hits@3, and Hits@10, respectively. © 2024 Neural information processing systems foundation. All rights reserved.

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Vector meson’s spin alignments in high energy reactions

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science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 1-16页

作者： Jin-Hui Chen Zuo-Tang Liang Yu-Gang Ma Xin-Li Sheng Qun Wang Key Laboratory of Nuclear Physics and Ion-beam Application(MoE) Institute of Modern PhysicsFudan UniversityShanghai 200433China Institute of Frontier and Interdisciplinary Science Key Laboratory of Particle Physics and Particle Irradiation(MOE)Shandong UniversityQingdao 266237China INFN-Firenze Sesto Fiorentino FI 50019Italy Department of Modern Physics University of Science and Technology of ChinaHefei 230026China School of Mechanics and Physics Anhui University of Science and TechnologyHuainan 232001China

The global spin alignment of vector mesons has been observed by the STAR collaboration at the Relativistic Heavy Ion Collider(RHIC)at Brookhaven National laboratory(BNL).It provides a unique opportunity to probe the correlation between the po-larized quark and antiquark in the strongly coupled quark-gluon plasma(sQGP)produced in relativistic heavy ion collisions,opening a new window to explore the properties of *** addition,spin alignments of vector mesons have also been observed in other high-energy particle collisions such as e^(+)e^(−)annihilations at high energies where hadron production is dominated by quark fragmentation *** results obtained are quite different from those obtained in heavy ion collisions where quark coalescence/combination mechanism dominates suggesting strong dependence on hadronization *** comprehensive studies in different hadronization processes are *** this article,we present a brief review of theoretical and experimen-tal advances in the study of vector meson’s spin alignments in a variety of high-energy particle collisions,with emphasis on hadronization mechanisms.

关键词： vector meson spin alignment global polarization relativistic heavy ion collisions fragmentation

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Research on differential pressure measurement technology of nuclear power plant based on optical fiber Fabry-Perot sensing 4

Research on differential pressure measurement technology of ...

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4th International Computational Imaging Conference, CITA 2024

作者： He, Zhengxi Li, Zhuoyue Zhu, Biwei Xu, Tao Deng, Zhiguang Qin, Yue Liu, Danhui Wang, Hailin Ran, Zengling University of Electronic Science and Technology of China Chengdu611731 China National Key Laboratory of Nuclear Reactor Technology Nuclear Power Institute of China Chengdu610213 China

ISBN: (纸本)9781510688834

Differential pressure is an important parameter for the safe operation of nuclear power plants. Due to its own principle, traditional instruments have certain limitations in their application in nuclear power plants. In this paper, a new optical fiber sensing differential pressure measurement method is proposed for the differential pressure measurement in the nuclear environment. The method adopts the principle of optical fiber Fabry-Perot (FP) sensing, uses fiber and pressure-sensitive diaphragm to form an FP cavity, and obtains the differential pressure by analyzing the interference light in the FP cavity. The displacement of the pressure-sensitive diaphragm is theoretically analyzed and verified by experiments. The experimental results show that the sensitivity of the sensor is 162.88 μm/MPa, which is basically consistent with the theoretical value, and has a good linearity of 0.9997. In the future, the accuracy and reliability of the differential pressure sensor can be further improved by optimizing the size of the pressure-sensitive diaphragm and improving the processing technology. This study verifies the feasibility of the optical fiber FP differential pressure measurement method, which is not only suitable for nuclear environments, but also can be extended to other fields. © 2025 SPIE.

关键词： Fabry-Perot interferometers

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Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting 38

Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Shang, Zongjiang Chen, Ling Wu, Binqing Cui, Dongliang State Key Laboratory of Blockchain and Data Security College of Computer Science and Technology Zhejiang University China

Although transformer-based methods have achieved great success in multi-scale temporal pattern interaction modeling, two key challenges limit their further development: (1) Individual time points contain less semantic information, and leveraging attention to model pair-wise interactions may cause the information utilization bottleneck. (2) Multiple inherent temporal variations (e.g., rising, falling, and fluctuating) entangled in temporal patterns. To this end, we propose Adaptive Multi-Scale Hypergraph Transformer (Ada-MSHyper) for time series forecasting. Specifically, an adaptive hypergraph learning module is designed to provide foundations for modeling group-wise interactions, then a multi-scale interaction module is introduced to promote more comprehensive pattern interactions at different scales. In addition, a node and hyperedge constraint mechanism is introduced to cluster nodes with similar semantic information and differentiate the temporal variations within each scales. Extensive experiments on 11 real-world datasets demonstrate that Ada-MSHyper achieves state-of-the-art performance, reducing prediction errors by an average of 4.56%, 10.38%, and 4.97% in MSE for long-range, short-range, and ultra-long-range time series forecasting, respectively. Code is available at https://***/shangzongjiang/Ada-MSHyper. © 2024 Neural information processing systems foundation. All rights reserved.

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Negation Triplet Extraction with Syntactic Dependency and Semantic Consistency 30

Negation Triplet Extraction with Syntactic Dependency and Se...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Shi, Yuchen Yang, Deqing Liu, Jingping Xiao, Yanghua Wang, Zongyu Xu, Huimin School of Data Science Fudan University Shanghai Key Laboratory of Data Science Shanghai China East China University of Science and Technology Shanghai China Meituan China

ISBN: (纸本)9782493814104

Previous works of negation understanding mainly focus on negation cue detection and scope resolution, without identifying negation subject which is also significant to the downstream tasks. In this paper, we propose a new negation triplet extraction (NTE) task which aims to extract negation subject along with negation cue and scope. To achieve NTE, we devise a novel Syntax&Semantic-Enhanced Negation Extraction model, namely SSENE, which is built based on a generative pretrained language model (PLM) of Encoder-Decoder architecture with a multi-task learning framework. Specifically, the given sentence's syntactic dependency tree is incorporated into the PLM's encoder to discover the correlations between the negation subject, cue and scope. Moreover, the semantic consistency between the sentence and the extracted triplet is ensured by an auxiliary task learning. Furthermore, we have constructed a high-quality Chinese dataset NegComment based on the users' reviews from the real-world platform of Meituan, upon which our evaluations show that SSENE achieves the best NTE performance compared to the baselines. Our ablation and case studies also demonstrate that incorporating the syntactic information helps the PLM's recognize the distant dependency between the subject and cue, and the auxiliary task learning is helpful to extract the negation triplets with more semantic consistency. We further demonstrate that SSENE is also competitive on the traditional CDSR task. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Extraction

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