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arXiv 2025年

作者： Yang, Kun Zhang, Chao Wu, Chengwei Du, Qian Li, Bingzhi Fang, Zhen Li, Liang Wu, Jianbo Wu, Tianru Wang, Hui Deng, Tao Gao, Wenpei State Key Laboratory of Metal Matrix Composites School of Materials Science and Engineering Future Material Innovation Center Zhangjiang Institute for Advanced Study Shanghai Jiao Tong University Shanghai200240 China School of Physics and Electronics Hunan Key Laboratory of Super Microstructure and Ultrafast Process State Key Laboratory of Powder Metallurgy Central South University Changsha410083 China Research Center for Scientific Data Hub Zhejiang Lab Hangzhou310000 China SKLPPC Shanghai200240 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China

Accurate, non-contact temperature measurement with high spatial resolution is essential for understanding thermal behavior in integrated nanoscale devices and heterogeneous interfaces. However, existing techniques are often limited by the need for physical contact or insufficient spatial resolution for the measurement of local temperature and mapping its distribution. Here, we showcase the direct temperature measurement of graphene with nanometer spatial resolution in transmission electron microscopy. In experiments, combining a scanning nanobeam with precession electron diffraction offers the collection of kinemetic diffraction from a local area at the nanometer scale. In analysis, we use a pre-calculated, sample-specific structure-factor-based correction method to enable the linear fitting of the diffraction intensities, allowing the determination of the Debye-Waller factor as a function of temperature at the precision of 10-4Å2/C. With the high spatial resolution and measurement precision, the temperature and thermal vibration mapping further reveal the influence of graphene lattice parameters and thickness on the Debye-Waller factor, providing valuable insights into the vibrational properties impacted by temperature, lattice structure, and graphene layer thickness. Copyright © 2025, The Authors. All rights reserved.

关键词： Crystal lattices

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A Force – Voltage Responsivity Stabilization Method for Piezoelectric Touch Panels in the Internet of Things

A Force – Voltage Responsivity Stabilization Method for Pie...

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IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)

作者： Shuo Gao Mingqi Shao Rong Guo Arokia Nathan School of Instrumentation Science and Optoelectronic Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang University Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China Cambridge Touch Technologies Inc. 154 Cambridge Science Park Milton Rd Milton Cambridge UK

ISBN: (数字)9781728152783

ISBN: (纸本)9781728152790

Piezoelectric force touch panels are attractive as human-machine interfaces and 3-dimensional touch sensing in internet of things (IoT) applications. The piezoelectric material has the intrinsic ability to convert mechanical to electrical signals. But the force responsivity issue induced by different touch orientations can be unstable. This paper presents a piezoelectric touch panel that is sensitive to both capacitive and force stimulation. A touch orientation classification technique is developed to calibrate the detected force amplitude by training a machine learning model with finger induced capacitive information. A high and stable force voltage responsivity of 87.5% is achieved experimentally, demonstrating its potential significance in force touch based human-machine interactivity.

关键词： Training Force Tactile sensors User experience Sensors Internet of Things Man-machine systems

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Collusion-Proof Result Inference in Crowdsourcing

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Journal of Computer science & Technology 2018年第2期33卷 351-365页

作者： Peng-Peng Chen Hai-Long Sun Yi-Li Fang Jin-Peng Huai State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang University Beijing 100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing 100191 China

In traditional crowdsourcing, workers are expected to provide independent answers to tasks so as to ensure the diversity of answers. However, recent studies show that the crowd is not a collection of independent workers, but instead that workers communicate and collaborate with each other. To pursue more rewards with little effort, some workers may collude to provide repeated answers, which will damage the quality of the aggregated results. Nonetheless, there are few efforts considering the negative impact of collusion on result inference in crowdsourcing. In this paper, we are specially concerned with the Collusion-Proof result inference problem for general crowdsourcing tasks in public platforms. To that end, we design a metric, the worker performance change rate, to identify the colluded answers by computing the difference of the mean worker performance before and after removing the repeated answers. Then we incorporate the collusion detection result into existing result inference methods to guarantee the quality of the aggregated results even with the occurrence of collusion behaviors. With real-world and synthetic datasets, we conducted an extensive set of evaluations of our approach. The experimental results demonstrate the superiority of our approach in comparison with the state-of-the-art methods.

关键词： crowdsourcing quality control collusion collaborative crowdsourcing result inference

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Simultaneous Determination of the Spin Polarizations of Noble-Gas and Alkali-Metal Atoms Based on the Dynamics of the Spin Ensembles

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Physical Review Applied 2020年第4期13卷 044027-044027页

作者： Kai Wei Tian Zhao Xiujie Fang Hairong Li Yueyang Zhai Bangcheng Han Wei Quan School of Instrumentation and Optoelectronic Engineering Beihang University Beijing 100191 China Quantum Sensing Center Zhejiang Laboratory Hangzhou 310000 China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang University Beijing 100191 China Research Institute of Frontier Science Beihang University Beijing 100191 China Beijing Academy of Quantum Information Sciences Beijing 100193 China

We demonstrate a method for simultaneously measuring the spin polarizations of noble-gas and alkali-metal atoms. Under a low magnetic field, the polarized alkali-metal and noble-gas spin ensembles exhibit novel dynamics in the self-compensation and resonance regimes, which can be used to measure the polarizations. We perform this method on a K-Rb-21Ne comagnetometer with various operation temperatures and pump-light intensities. The polarization of alkali-metal electrons from 0.245 to 0.964 and the polarization of noble-gas nuclear spins from 0.01 to 0.065 are measured with relative uncertainties less than 12.4%. The measured polarizations are consistent with the theoretical model and are also verified by the traditional polarization-measurement method.

关键词： Atomic & molecular processes in external fields Magneto-optical effect Metrology Nuclear & electron resonance Optical pumping Spin dynamics Spin polarization Atomic gases

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Sending-or-not-sending twin-field quantum key distribution: Breaking the direct transmission key rate

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Physical Review A 2020年第4期101卷 042330-042330页

作者： Hai Xu Zong-Wen Yu Cong Jiang Xiao-Long Hu Xiang-Bin Wang State Key Laboratory of Low Dimensional Quantum Physics Department of Physics Tsinghua University Beijing 100084 China Data Communication Science and Technology Research Institute Beijing 100191 China Shanghai Branch CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of China Shanghai 201315 People's Republic of China Jinan Institute of Quantum Technology SAICT Jinan 250101 China Shenzhen Institute for Quantum Science and Engineering and Physics Department Southern University of Science and Technology Shenzhen 518055 China

We present improved results of sending-or-not-sending twin-field quantum key distribution by using error rejection through two-way classical communications. Our error rejection method, especially our method of actively odd-parity pairing (AOPP) can drastically improve the performance of sending-or-not-sending twin-field protocol in both secure distance and key rate. Taking a typical experimental parameter setting, our method here improves the secure distance by 70 km to more than 100 km in comparison with the prior art results. Comparative study also shows advantageous in key rates at regime of long distance and large misalignment error rate for our method here. The numerical results show that our method here can significantly exceed the absolute limit of direct transmission key rate, and also have an advantageous key rates higher than various prior art results by 10 to 20 times.

关键词： Quantum communication Quantum cryptography

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Energy calibration of HPGe detector using the high-energy characteristic γ rays in 13C formed in 6Li + 12C reaction

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Nuclear science and Techniques 2020年第5期31卷 57-63页

作者： Jia-Tai Li Xue-Dou Su Gao-Long Zhang Guang-Xin Zhang Shi-Peng Hu Jing-Bin Lu Yi-Feng Lv Hui-Bin Sun Huan-Qiao Zhang D.Testov P.R.John J.J.Valiente-Dobon A.Goasduff M.Siciliano F.Galtarossa F.Recchia D.Mengoni D.Bazzacco School of Physics Beihang UniversityBeijing 100191China Shenyuan Honors College Beihang UniversityBeijing 100191China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine and EngineeringBeihang University and Key Laboratory of Big Data-Based Precision Medicine(Beihang University)Ministry of Industry and Information TechnologyBeihang UniversityBeijing 100191China Dipartimento di Fisica Astronomia dell’Universit'a di PadovaPaduaItaly Istituto Nazionale di Fisica Nucleare Sezione di PadovaPaduaItaly College of Physics Science and Technology Shenzhen UniversityShenzhen 518060China College of Physics Jilin UniversityChangChun 130012China China Institute of Atomic Energy Beijing 102413China Laboratori Nazionali di Legnaro INFNLegnaroPaduaItaly Irfu/CEA Universit de Paris-SaclayGif-sur-YvetteFrance

An 6 Li+89Y experiment was conducted at the Laboratori Nazinali di Legnaro,INFN,*** 550μg/cm^2 thick^89Y target was backed on a 340μg/cm^2 thick 12C *** severalγrays in the experiment with energies higher than 3000 keV can most likely be ascribed to the transitions in the 13C nuclei,which can be formed through various interactions between the 6 Li beam and the 12C *** high-energy properties ofγrays in 13C are employed for energy calibrating HPGe detectors,especially for the>3000 keV region,which is impossible to reach by common standard sources(152Eu,133Ba,etc.).Furthermore,γ-γand particle-γcoincidence measurements were performed to investigate the formation of 13C.

关键词： Energy calibration Coincidence measurement Weakly bound nuclei Reaction mechanism

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Gut microbiota and diabetes: From correlation to causality and mechanism

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World Journal of Diabetes 2020年第7期11卷 293-308页

作者： Wei-Zheng Li Kyle Stirling Jun-Jie Yang Lei Zhang Microbiome-X Beijing Advanced Innovation Center for Big Data-Based Precision MedicineSchool of Medicine and EngineeringKey Laboratory of Big Data-Based Precision MedicineBeihang UniversityBeijing 100191China School of Biological Science and Medical Engineering Beihang UniversityBeijing 100191China Luddy School of Informatics Computing and EngineeringIndiana UniversityBloomingtonIN 47408United States The Crisis Technologies Innovation Lab Indiana UniversityThe Information Technology Services and the Pervasive Technology InstituteBloomingtonIN 47408United States Shandong Institute of Industrial Technology for Health Sciences and Precision Medicine Jinan 250000Shandong ProvinceChina College of Life Science Qilu Normal UniversityJinan 250000Shandong ProvinceChina Microbiome Research Center Shandong Institutes for Food and Drug ControlJinan 250000Shandong ProvinceChina Shandong Children’s Microbiome Center Qilu Children's Hospital of Shandong UniversityJinan 250000Shandong ProvinceChina Microbiological Laboratory Lin Yi People’s HospitalLinyi 276000Shandong ProvinceChina Qingdao Human Microbiome Center The Affiliated Central Hospital of Qingdao UniversityQingdao 266000Shandong ProvinceChina Institute for Medical Dataology Cheeloo College of MedicineShandong UniversityJinan 250000Shandong ProvinceChina Department of Biostatistics School of Public HealthCheeloo College of MedicineShandong UniversityJinan 250000Shandong ProvinceChina Shandong Children’s Microbiome Center Research Institute of PediatricsQilu Children's HospitalCheeloo College of MedicineShandong Universityand Jinan Children's HospitalJinan 250022Shandong ProvinceChina

In this review,we summarize the recent microbiome studies related to diabetes disease and discuss the key findings that show the early emerging potential causal roles for *** a global scale,diabetes causes a significant negative impact to the health status of human *** review covers type 1 diabetes and type 2 *** examine promising studies which lead to a better understanding of the potential mechanism of microbiota in diabetes *** appears that the human oral and gut microbiota are deeply interdigitated with *** is that *** studies of the human microbiome are capturing the attention of scientists and healthcare practitioners worldwide by focusing on the interplay of gut microbiome and *** studies focus on the role and the potential impact of intestinal microflora in *** paint a clear picture of how strongly microbes are linked and associated,both positively and negatively,with the fundamental and essential parts of diabetes in *** microflora seems to have an endless capacity to impact and transform *** conclude that there is clear and growing evidence of a close relationship between the microbiota and diabetes and this is worthy of future investments and research efforts.

关键词： Diabetes Microbiota Causality Mechanism Type 1 diabetes Type 2 diabetes Insulin resistance Inflammation Metabolites

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Giant Isolated Attosecond Pulses from Two-Color Laser-Plasma Interactions

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Physical Review Letters 2020年第11期124卷 114802-114802页

作者： Y. X. Zhang S. Rykovanov Mingyuan Shi C. L. Zhong X. T. He B. Qiao M. Zepf Center for Applied Physics and Technology HEDPS SKLNPT and School of Physics Peking University Beijing 100871 China Helmholtz Institute Jena 07743 Jena Germany Laser Fusion Research Center China Academy of Engineering Physics Mianyang 621900 China Center for Computational and Data-Intensive Science and Engineering Skolkovo Institute of Science and Technology 121205 Moscow Russia Collaborative Innovation Center of IFSA Shanghai Jiao Tong University Shanghai 200240 China Institute of Applied Physics and Computational Mathematics Beijing 100094 China Institute of Optics and Quantum Electronics Friedrich Schiller University 07743 Jena Germany

A new regime in the interaction of a two-color (ω,2ω) laser with a nanometer-scale foil is identified, resulting in the emission of extremely intense, isolated attosecond pulses—even in the case of multicycle lasers. For foils irradiated by lasers exceeding the blow-out field strength (i.e., capable of fully separating electrons from the ion background), the addition of a second harmonic field results in the stabilization of the foil up to the blow-out intensity. This is then followed by a sharp transition to transparency that essentially occurs in a single optical cycle. During the transition cycle, a dense, nanometer-scale electron bunch is accelerated to relativistic velocities and emits a single, strong attosecond pulse with a peak intensity approaching that of the laser field.

关键词： Fast particle effects in plasmas High-energy-density plasmas High-order harmonic generation Laser-plasma interactions Radiation & particle generation in plasmas Radiation pressure acceleration X-ray generation in plasmas

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基于大语言模型的糖尿病管理:潜力与展望

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science Bulletin 2024年第5期69卷 583-588页

作者：盛斌管洲榆 Lee-Ling Lim 江泽铧 Nestoras Mathioudakis 李佳佳刘茹涵包玉倩 Yong Mong Bee 王亚星郑颖丰 Gavin Siew Wei Tan 纪宏伟 Josip Car 王海波 David C.Klonoff 李华婷覃宇宗黄天荫贾伟平 Shanghai International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and EngineeringSchool of ElectronicInformationand Electrical EngineeringShanghai Jiao Tong UniversityDepartment of Endocrinology and MetabolismShanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai Diabetes InstituteShanghai Clinical Center for DiabetesShanghai 200240China MOE Key Laboratory of Artificial Intelligence Artificial Intelligence InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Medicine Faculty of MedicineUniversity of MalayaKuala Lumpur 50603Malaysia Department of Medicine and Therapeutics The Chinese University of Hong KongHong KongChina Asia Diabetes Foundation Hong KongChina Tsinghua Medicine of Tsinghua University Beijing 100084China School of Clinical Medicine Beijing Tsinghua Changgung HospitalBeijing 102218China Division of Endocrinology Diabetes&MetabolismJohns Hopkins University School of MedicineBaltimoreMD 21211USA Department of Endocrinology Singapore General HospitalSingapore 169608Singapore Beijing Institute of Ophthalmology Beijing Tongren HospitalCapital University of Medical ScienceBeijing Ophthalmology and Visual Sciences Key LaboratoryBeijing 100730China State Key Laboratory of Ophthalmology Zhongshan Ophthalmic CenterSun Yat-sen UniversityGuangdong Provincial Key Laboratory of Ophthalmology and Visual ScienceGuangzhou 510060China Singapore Eye Research Institute Singapore National Eye CentreSingapore 168751Singapore Department of Cardiology the Affiliated Hospital of Qingdao UniversityQingdao 266011China Centre for Population Health Sciences Lee Kong Chian School of MedicineNanyang Technological University SingaporeSingapore 639798Singapore Department of Primary Care and Public Health School of Public HealthImperial College LondonLondon SW72BUUK Clinical Trial Unit Research Centre of Big Data and Artificial Intelligence in Medicine

The increasing prevalence of diabetes has become a global public health concern in the 21st *** 2021,it was estimated that 537 million people had diabetes,and this number is projected to reach 643 million by 2030,and 783 million by 2045[1].Such a huge burden of diabetes brings great challenges in its prevention and management,including early diagnosis,timely interventions,and regular monitoring of risk factor control and complications *** self-care support and patient empowerment can enhance clinical and psychobehavioural outcomes[2],although these require additional resources including manpower,infrastructure(hard and technology),and *** emergence of digital health technologies(DHTs),especially artificial intelligence(AI),may help address these obstacles and alleviate the burden of diabetes[3].Large language models(LLMs),a generative AI that can accept image and text inputs and produce text outputs,have shown promise in various aspects of medical care.

关键词： prevention diagnosis finance

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MBLLEn: Low-light image/video enhancement using CNNs 29

MBLLEn: Low-light image/video enhancement using CNNs

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29th British Machine Vision Conference, BMVC 2018

作者： Lv, Feifan Lu, Feng Wu, Jianhua Lim, Chongsoon State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine Beihang University Beijing China Panasonic R and D Center Singapore Singapore City Singapore

We present a deep learning based method for low-light image enhancement. This problem is challenging due to the difficulty in handling various factors simultaneously including brightness, contrast, artifacts and noise. To address this task, we propose the multi-branch low-light enhancement network (MBLLEN). The key idea is to extract rich features up to different levels, so that we can apply enhancement via multiple subnets and finally produce the output image via multi-branch fusion. In this manner, image quality is improved from different aspects. Through extensive experiments, our proposed MBLLEN is found to outperform the state-of-art techniques by a large margin. We additionally show that our method can be directly extended to handle low-light videos. © 2018. The copyright of this document resides with its authors.

关键词： Image enhancement

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