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Effect of nanosized NbC precipitates on hydrogen-induced cracking of high-strength low-alloy steel

International Journal of Minerals,Metallurgy and Materials 2021年第2期28卷 249-256页

作者： En-dian Fan Shi-qi Zhang Dong-han Xie Qi-yue Zhao Xiao-gang Li Yun-hua Huang Institution for Advanced Materials and Technology University of Science and Technology BeijingBeijing 100083China Key Laboratory of Advanced Materials(MOE) School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China Ningbo Institute of Material Technology&Engineering Chinese Academy of SciencesNingbo 315201China

We investigated the effect of nanosized NbC precipitates on hydrogen-induced cracking(HIC)of high-strength low-alloy steel by conducting slow-strain-rate tensile tests(SSRT)and performing continuous hydrogen charging and fracture *** results reveal that the HIC resistance of Nb-bearing steel is obviously superior to that of Nb-free steel,with the fractured Nb-bearing steel in the SSRT exhibiting a smaller ratio of elongation reduction(Iδ).However,as the hydrogen traps induced by NbC precipitates approach hydrogen saturation,the effect of the precipitates on the HIC resistance *** speculate that the highly dispersed nanosized NbC precipitates act as irreversible hydrogen traps that hinder the accumulation of hydrogen at potential crack nucleation *** addition,much like Nb-free steel,the Nb-bearing steel exhibits both H-solution strengthening and the resistance to HIC.

关键词： nanosized NbC precipitates high-strength low-alloy steel hydrogen-induced cracking slow-strain-rate tensile,hydrogen charging

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Self-Powered Intelligent Human-Machine Interaction for Handwriting Recognition

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Research 2021年第1期2021卷 226-234页

作者： Hang Guo Ji Wan Haobin Wang Hanxiang Wu Chen Xu Liming Miao Mengdi Han Haixia Zhang National Key Laboratory of Science and Technology on Micro/Nano Fabrication Peking UniversityBeijing 100871China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijing 100871China

Handwritten signatures widely exist in our daily *** main challenge of signal recognition on handwriting is in the development of approaches to obtain information *** mechanical signals can be easily detected by triboelectric nanogenerators which can provide immediate opportunities for building new types of active sensors capable of recording handwritten *** this work,we report an intelligent human-machine interaction interface based on a triboelectric *** the horizontal-vertical symmetrical electrode array,the handwritten triboelectric signal can be recorded without external energy *** with supervised machine learning methods,it can successfully recognize handwritten English letters,Chinese characters,and Arabic *** principal component analysis algorithm preprocesses the triboelectric signal data to reduce the complexity of the neural network in the machine learning ***,it can realize the anticounterfeiting recognition of writing habits by controlling the samples input to the neural *** results show that the intelligent human-computer interaction interface has broad application prospects in signature security and humancomputer interaction.

关键词： signature writing recording

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Conducting a study on the classification of EEG signals in the high-risk population of schizophrenia using the 1DCNN-LSTM algorithm

Conducting a study on the classification of EEG signals in t...

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2024 International Conference on Future of Medicine and Biological Information Engineering, MBIE 2024

作者： Ying, Shenghui Luo, Yutong Zhao, Yuesheng Wang, Ya Wang, Xiaoling School of Automation Guangxi University of Science and Technology Liuzhou545006 China Student Mental Health Education Center Guangxi University of Science and Technology Liuzhou545006 China School of Psychology Capital Normal University Beijing100089 China CAS Key Laboratory of Mental Health Institute of Psychology Chinese Academy of Sciences Beijing100101 China

ISBN: (纸本)9781510682825

The research employs EEG in combination with the 1DCNN-LSTM algorithm for the purposes of identifying and classifying people with varying risks of schizophrenia. This collection of data for schizophrenia's high-risk and low-risk groups comprises EEG signals from 98 people, the division was made between a group of 50 with normal EEG signals and another group of 48 with high-risk indicators for schizophrenia. The duration of measurement for every participant stood at 12 minutes. The data set was processed in advance, encompassing tasks like channel exclusion, re-referencing, dividing the dataset, performing independent component analysis (ICA), windowing, normalizing, and segregating it into the testing, training, and validation sets. Subsequently, the processed EEG data was integrated into the 1DCNN-LSTM classification model, where post-extensive learning, the model's weights were derived. The categorization system attained a 94.26% precision rate in the identification of the complete-channel EEG data collection. This research utilized the 1DCNN-LSTM algorithm to classify and identify high-risk and low-risk groups for schizophrenia, showcasing an adequate recognition capability that satisfies real-world application criteria. The system precisely categorizes populations at varying risk levels for schizophrenia through comprehensive EEG data, thus facilitating precise schizophrenia detection and offering prompt diagnosis and treatment for those at high risk for the condition. © 2024 SPIE.

关键词： Risk assessment

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Gesture Builder: Flexible Gesture Customization and Efficient Recognition on VR Devices

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Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2025年第2期9卷 1-37页

作者： Yang Zou Yanguang Wan Yonghao Zhang Xiao Zhou Jian Cheng Cuixia Ma Chun Yu Xiaoming Deng Hongan Wang Institute of Software Chinese Academy of Sciences Beijing China and University of Chinese Academy of Sciences Beijing China Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Institute of Software Chinese Academy of Sciences Beijing China School of Computer Science and Technology and University of Chinese Academy of Sciences Beijing China Key Laboratory of System Software Chinese Academy of Sciences) and State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Department of Computer Science and Technology Tsinghua University Beijing China Institute of Software Chinese Academy of Sciences Beijing China

In the realm of VR/MR interactions, gestures serve as a critical bridge between users and interfaces, with custom gestures enhancing creativity and providing a personalized immersive experience. We introduce a novel gesture definition and recognition framework that allows users to customize a wide array of gestures by demonstrating them just three times. A major challenge lies in effectively representing gestures computationally. To address this, we have pre-trained a hand posture representation model using a Vector Quantized Variational Autoencoder (VQ-VAE) with a codebook of adaptive size, allowing hand postures defined by 23 joint positions of the hand to be projected into a latent space. In this space, different postures are formed into clusters, and a testing posture can be assigned to a cluster by a specific distance metric. The dynamic gestures are then represented as sequences of discrete hand postures and wrist positions. Employing a straightforward sequence matching algorithm, our framework achieves highly efficient recognition with minimal computational demands. We evaluated this system through a user study that includes 16 pre-defined gestures and 106 user-defined gestures. The results confirm that our system can provide robust real-time gesture recognition and effectively supports the customization of gestures according to user preferences. Our approach surpasses previous methods by enhancing gesture diversity and reducing constraints on gesture customization. Project page: https://***/GestureBuilder/.

关键词： Gesture customization Virtual Reality

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The Cissus quadrangularis genome reveals its adaptive features in an arid habitat

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园艺研究（英文） 2024年第4期11卷 77-90页

作者： Qingyun Li Yi Wang Huimin Zhou Yuanshuang Liu Duncan Kiragu Gichuki Yujun Hou Jisen Zhang Rishi Aryal Guangwan Hu Tao Wan Sara Getachew Amenu Robert Wahiti Gituru Haiping Xin Qingfeng Wang CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture Core Botanical Gardens/Wuhan Botanical GardenChinese Academy of SciencesWuhan 430074China Sino-Africa Joint Research Center Chinese Academy of SciencesWuhan 430074China University of Chinese Academy of Sciences Beijing 100049China CAS Key Laboratory of Plant Resources Institute of BotanyChinese Academy of ScienceBeijing 100093China CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture Core Botanical Gardens/Wuhan Botanical GardenChinese Academy of SciencesWuhan 430074China University of Chinese Academy of Sciences Beijing 100049China Key Lab for Conservation and Utilization of Subtropical AgroBiological Resources and Guangxi Key Lab for Sugarcane Biology Guangxi UniversityNanning 530004China Department of Horticultural Science North Carolina State UniversityRaleighNC 27695USA CAS Key Laboratory of Plant Germplasm Enhancement and Specialty Agriculture Core Botanical Gardens/Wuhan Botanical GardenChinese Academy of SciencesWuhan 430074China Sino-Africa Joint Research Center Chinese Academy of SciencesWuhan 430074China Department of Botany Jomo Kenyatta University of Agriculture and Technology62000-00200NairobiKenya

Cissus quadrangularis is a tetraploid species belonging to the Vitaceae family and is known for the Crassulacean acid metabolism(CAM)pathway in the succulent stem,while the leaves perform C3 ***,we report a high-quality genome of *** comprising a total size of 679.2 Mb which was phased into two *** annotation identified 51857 protein-coding genes,while approximately 47.75％of the genome was composed of repetitive *** expression ratios of two subgenomes demonstrated that the sub-A genome as the dominant subgenome played a vital role during the drought *** divergence analysis suggests that the tetraploidization event occurred around 8.9 million years *** data revealed that pathways related to cutin,suberine,and wax metabolism were enriched in the stem during drought treatment,suggesting that these genes contributed to the drought ***,a subset of CAM-related genes displayed diurnal expression patterns in the succulent stems but not in leaves,indicating that stem-biased expression of existing genes contributed to the CAM *** findings provide insights into the mechanisms of drought adaptation and photosynthesis transition in plants.

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Research on Construction Method of science and technology Service Domain Knowledge Map

Research on Construction Method of Science and Technology Se...

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IEEE Advanced Information technology, Electronic and Automation Control Conference (IAEAC)

作者： Jiaqi Qian School of Information Science and Technology North China University of Technology Beijing China Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream Data Beijing China

With the development of the science and technology service industry, there is an urgent need to effectively organize multi-source and heterogeneous science and technology resources to meet the personalized needs of science and technology services in different industrial fields, that is, to provide various services to different industrial fields according to industry perspectives. Required scientific and technological resources, including scientific and technological project resources and scientific and technological consulting resources, etc. Effective organization and management of scientific and technological resources can be completed by building a domain knowledge map for industrial industry scientific and technological services. However, these resource fields have a large number of data types, are highly professional, and have complex businesses. How to obtain useful data, information, and business knowledge from massive data and store it in a graph database to complete the construction of a knowledge graph is the subject of this article. Concerns. Therefore, this article proposes a set of methods that integrate data preprocessing and knowledge modeling based on structured data processing and ontology technology to complete the construction of domain knowledge graphs.

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MeshCNN-based BREP to CSG conversion algorithm for 3D CAD models and its application

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Nuclear science and Techniques 2022年第6期33卷 75-88页

作者： Yue-Tong Luo Hua Du Yi-Man Yan Hefei University of Technology Hefei 230009China University of Science and Technology of China Hefei 230027China Institute of Plasma Physics Hefei Institutes of Physical ScienceChinese Academy of SciencesHefei 230031China State Power Investment Corporation Research Institute National Energy Key Laboratory of Nuclear Power SoftwareBeijing 102209China

In the field of neutronics analysis, it is imperative to develop computer-aided modeling technology for Monte Carlo codes to address the increasing complexity of reactor core components by converting 3D CAD model(boundary representation, BREP) to MC model(constructive solid geometry, CSG). Separation-based conversion from BREP to CSG is widely used in computer-aided modeling MC codes because of its high efficiency, reliability, and easy implementation. However, the current separation-based BREP-CSG conversion is poor for processing complex CAD models, and it is necessary to divide a complex model into several simple models before applying the separation-based conversion algorithm, which is time-consuming and tedious. To avoid manual segmentation, this study proposed a MeshCNN-based 3D-shape segmentation algorithm to automatically separate a complex model. The proposed 3D-shape segmentation algorithm was combined with separation-based BREP-CSG conversion algorithms to directly convert complex *** proposed algorithm was integrated into the computeraided modeling software cosVMPT and validated using the Chinese fusion engineering testing reactor model. The results demonstrate that the MeshCNN-based BREP-CSG conversion algorithm has a better performance and higher efficiency, particularly in terms of CPU time, and the conversion result is more intuitive and consistent with the intention of the modeler.

关键词： BREP to CSG conversion Computer-aided modeling cosVMPT Intelligent pre-segmentation MeshCNN

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Breath-by-breath measurement of exhaled ammonia by acetonemodifier positive photoionization ion mobility spectrometry via online dilution and purging sampling

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Journal of Pharmaceutical analysis 2023年第4期13卷 412-420页

作者： Lu Wang Dandan Jiang Lei Hua Chuang Chen Dongming Li Weiguo Wang Yiqian Xu Qimu Yang Haiyang Li Song Leng CAS Key Laboratory of Separation Science for Analytical Chemistry Dalian Institute of Chemical PhysicsChinese Academy of SciencesDalian116023China Health Management Center The Second Affiliated Hospital of Dalian Medical UniversityDalian116023China University of Chinese Academy of Sciences Beijing100049China Dalian Key Laboratory for Online Analytical Instrumentation Dalian116023China Dalian Engineering Research Center of Breath Diagnostic Technology Dalian116023China

Exhaled ammonia(NH_(3))is an essential noninvasive biomarker for disease *** this study,an acetone-modifier positive photoionization ion mobility spectrometry(AM-PIMS)method was developed for accurate qualitative and quantitative analysis of exhaled NH_(3)with high selectivity and *** was introduced into the drift tube along with the drift gas as a modifier,and the characteristic NH_(3)product ion peak of(C_(3)H_(6)O)_(4)NH_(4)^(+)(K_(0)=1.45 cm^(2)/V·s)was obtained through the ion-molecule reaction with acetone reactant ions(C_(3)H_(6)O)_(2)H^(+)(K_(0)=1.87 cm^(2)/V·s),which significantly increased the peak-to-peak resolution and improved the accuracy of exhaled NH_(3)qualitative ***,the interference of high humidity and the memory effect of NH_(3)molecules were significantly reduced via online dilution and purging sampling,thus realizing breath-by-breath *** a result,a wide quantitative range of 5.87-140.92μmol/L with a response time of 40 ms was achieved,and the exhaled NH_(3)profile could be synchronized with the concentration curve of exhaled CO_(2).Finally,the analytical capacity of AM-PIMS was demonstrated by measuring the exhaled NH_(3)of healthy subjects,demonstrating its great potential for clinical disease diagnosis.

关键词： Photoionization ion mobility spectrometry Acetone modifier Exhaled ammonia Breath analysis

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Assimilating FY-4A AGRI Radiances with a Channel-Sensitive Cloud Detection Scheme for the analysis and Forecasting of Multiple Typhoons

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Advances in Atmospheric sciences 2024年第5期41卷 937-958页

作者： Feifei SHEN Aiqing SHU Zhiquan LIU Hong LI Lipeng JIANG Tao ZHANG Dongmei XU Key Laboratory of Meteorological Disaster Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing 210044China Shanghai Typhoon Institute China Meteorological AdministrationShanghai 200030China China Meteorological Administration Basin Heavy Rainfall Key Laboratory/Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research Institute of Heavy RainChina Meteorological AdministrationWuhan 430205China National Center for Atmospheric Research Boulder 80307COUSA State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China National Meteorological Information Center Beijing 100081China Fujian Key Laboratory of Severe Weather and Key Laboratory of Straits Severe Weather China Meteorological AdministrationFuzhou 350001China

This paper presents an attempt at assimilating clear-sky FY-4A Advanced Geosynchronous Radiation Imager(AGRI)radiances from two water vapor channels for the prediction of three landfalling typhoon events over the West Pacific Ocean using the 3DVar data assimilation(DA)method along with the WRF model.A channel-sensitive cloud detection scheme based on the particle filter(PF)algorithm is developed and examined against a cloud detection scheme using the multivariate and minimum residual(MMR)algorithm and another traditional cloud mask–dependent cloud detection *** show that both channel-sensitive cloud detection schemes are effective,while the PF scheme is able to reserve more pixels than the MMR scheme for the same *** general,the added value of AGRI radiances is confirmed when comparing with the control experiment without AGRI ***,it is found that the analysis fields of the PF experiment are mostly improved in terms of better depicting the typhoon,including the temperature,moisture,and dynamical *** typhoon track forecast skill is improved with AGRI radiance DA,which could be explained by better simulating the upper *** impact of assimilating AGRI radiances on typhoon intensity forecasts is *** the other hand,improved rainfall forecasts from AGRI DA experiments are found along with reduced errors for both the thermodynamic and moisture fields,albeit the improvements are limited.

关键词： FY-4A AGRI radiance particle filter multiple typhoons data assimilation numerical weather prediction

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DiffLight: A Partial Rewards Conditioned Diffusion Model for Traffic Signal Control with Missing Data

arXiv

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arXiv 2024年

作者： Chen, Hanyang Jiang, Yang Guo, Shengnan Mao, Xiaowei Lin, Youfang Wan, Huaiyu School of Computer Science and Technology Beijing Jiaotong University China Beijing Key Laboratory of Traffic Data Analysis and Mining Beijing China

The application of reinforcement learning in traffic signal control (TSC) has been extensively researched and yielded notable achievements. However, most existing works for TSC assume that traffic data from all surrounding intersections is fully and continuously available through sensors. In real-world applications, this assumption often fails due to sensor malfunctions or data loss, making TSC with missing data a critical challenge. To meet the needs of practical applications, we introduce DiffLight, a novel conditional diffusion model for TSC under data-missing scenarios in the offline setting. Specifically, we integrate two essential sub-tasks, i.e., traffic data imputation and decision-making, by leveraging a Partial Rewards Conditioned Diffusion (PRCD) model to prevent missing rewards from interfering with the learning process. Meanwhile, to effectively capture the spatial-temporal dependencies among intersections, we design a Spatial-Temporal transFormer (STFormer) architecture. In addition, we propose a Diffusion Communication Mechanism (DCM) to promote better communication and control performance under data-missing scenarios. Extensive experiments on five datasets with various data-missing scenarios demonstrate that DiffLight is an effective controller to address TSC with missing data. The code of DiffLight is released at https://***/lokol5579/DiffLight-release. © 2024, CC BY.

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