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SSRN 2023年

作者： Wu, Juping Xv, Huikai Jin, Min Gong, Guoliang Chen, Gang Mao, Wenyu Lu, Huaxiang Chen, Tianxiang Institute of Semiconductors CAS Beijing100083 China University of Chinese Academy of Sciences Beijing China Semiconductor Neural Network Intelligent Perception and Computing Technology Beijing Key Laboratory Beijing China Collage of Microelectronics University of Chinese Academy of Sciences Beijing China Materials and Optoelectronics Research Center University of Chinese Academy of Sciences Beijing China Tianjin University of Science and Technology Tianjin300457 China College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu610059 China

High impedance fault(HIF), especially tree contact single-phase-to-ground fault(TSF), often occurs in resonant grounding systems and are difficult to detect. Therefore, there is an urgent need for an effective TSF detection technology. In this paper, by analyzing the equivalent circuits of different impedance faults in resonant grounding system, and analyzing the transient zero-sequence components of underdamped state and overdamped state under different impedance, the conclusion is drawn: When a TSF occurs, the transient zero-sequence voltage will have a unique " Beat frequency " characteristic, and the problem of covering this phenomenon due to the imbalance of distribution network is effectively solved by fast independent component analysis(FastICA). Based on this conclusion, A fault detection method for TSF based on FastICA is proposed. Finally, the study conducted real experiments using two different impedance trees, bamboo and pine, to verify the proposed detection method. The results of the experiment found clear support for that the detection method is accurate and effective. © 2023, The Authors. All rights reserved.

关键词： Fault detection

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The complementary role of carbon dioxide removal: A catalyst for advancing the COP28 pledges towards the 1.5 °C Paris Agreement target

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Science of the Total Environment 2024年 947卷 174302页

作者： Acen, Caroline Bamisile, Olusola Cai, Dongsheng Ukwuoma, Chiagoziem C. Obiora, Sandra Huang, Qi Uzun Ozsahin, Dilber Adun, Humphrey College of Nuclear Science and Automation Engineering Sichuan Industrial Internet Intelligent Monitoring and Application Research Center Chengdu University of Technology Sichuan Chengdu China Centre for Environmental Policy Imperial College London United Kingdom Leeds Business School Leeds Beckett University LeedsLS1 3HE United Kingdom Electrical Engineering Department Southwest University of Science and Technology Sichuan Maiyang China Department of Medical Diagnostic Imaging College of Health Science University of Sharjah Sharjah United Arab Emirates Research Institute for Medical and Health Sciences University of Sharjah Sharjah United Arab Emirates Operational Research Centre in Healthcare Near East University TRNC Nicosia Mersin 1099138 Turkey Energy and Environmental Science Division University of Dundee Scotland United Kingdom

As the imperative to address climate change becomes more pressing, there is an increasing focus on limiting global temperature increase to 1.5 °C by the end of the century relative to pre-industrial levels. During the recent Conference of Parties (COP28), nations committed to tripling renewable energy generation to a minimum of 11,000 GW by 2030 and increasing the global annual energy efficiency from 2 % to 4 % annually until 2030. Additionally, the Food and Agricultural Organization (FAO) introduced a roadmap to transition the Agri-food system from a net emitter to a carbon sink. The role of carbon dioxide removal (CDR) is important;first to accelerate the near-term reduction in net emissions, counterbalance residual emissions at the point of net-zero by mid-century, and sustain large net negative emissions beyond mid-century to return warming to safe levels after decades of temporal overshoot. This paper assesses the impact of the COP 28 agreements, alongside the complementary role of CDR on emission levels, energy structure, land use, and global warming temperature. The findings indicate that implementing the COP28 pledges and FAO roadmap leads to a warming temperature of 2 °C, falling short of the ambitious 1.5 °C temperature limit. Likewise, more stringent actions on transitioning away from fossil plants is a high-priority mitigation action which drives significant emissions reduction. The modelled result shows that Agricultural soil carbon and biochar contribute 47–58 % share of the total CDR deployed in the stylized scenarios. In conclusion, CDR can expedite climate goals but must complement emission reduction efforts;hence, the transition away from fossil fuels should prompt the development of detailed roadmaps. Also, more global efforts should be placed on nature-based CDR methods, as they offer diverse co-benefits. © 2024 Elsevier B.V.

关键词： Global warming

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Data-driven modeling fast-slow coupling delayed dynamics using noisy data and sparse enhancement

Data-driven modeling fast-slow coupling delayed dynamics usi...

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International Conference on Industrial Artificial Intelligence (IAI)

作者： Huifang Tang Yuqiang Wu Yingming Dong Cheng Cheng Xiuting Li College of Science Huazhong Agricultural University Wuhan China School of Artificial Intelligence and Automation Huazhong University of Science and Techonology Wuhan China Yunnan Key Laboratory of Mechatronics Applied Technology Yunnan Mechanical Research and Design Institute of Machinery Research Institute Group Yunnan China Autonomous Intelligent Unmanned System Engineering Research Center Ministry of Education of China Huazhong University of Science and Technology Wuhan China

In this work, we focus on fast-slow delayed dynamical systems, which are usually described by coupled delayed differential equations with two-time scales. The purpose of this article is to propose a data-driven discovery method to identify the fast-slow delayed differential equations from noisy measurements. The proposed method blends delay dictionary-based sparse identification of nonlinear dynamics (SINDy) framework and a fixed interval sampling strategy. Specifically, we leverage the SINDy methodology to describe the fast-slow delayed differential equations by a few active terms of a large dictionary containing the delay terms and many candidate nonlinear basis functions. To identify the active terms and the corresponding coefficients, a sequential thresholded re-weighted ℓ 2 least squares algorithm is used to solve the resulting sparse regression problem to enhance the sparsity. Once a sparse model with fixed delay is selected, the proposed method further estimates the delayed time by calculating the reconstruction error from the sparse model until the one that makes the reconstruction error minimum. We verify the effectiveness of the proposed method with several classical fast-slow coupling delayed systems. The experimental results show that the proposed method can well automate the fast-slow delayed differential equations from noisy data and the delayed terms also can be detected accurately.

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Structural and functional imaging of brains

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Science China Chemistry 2023年第2期66卷 324-366页

作者： Zhichao Liu Ying Zhu Liming Zhang Weiping Jiang Yawei Liu Qiaowei Tang Xiaoqing Cai Jiang Li Lihua Wang Changlu Tao Xianzhen Yin Xiaowei Li Shangguo Hou Dawei Jiang Kai Liu Xin Zhou Hongjie Zhang Maili Liu Chunhai Fan Yang Tian Shanghai Key Laboratory of Green Chemistry and Chemical Processes School of Chemistry and Molecular EngineeringEast China Normal UniversityShanghai200241China Interdisciplinary Research Center Shanghai Synchrotron Radiation FacilityZhangjiang LaboratoryShanghai Advanced Research InstituteChinese Academy of SciencesUniversity of Chinese Academy of SciencesShanghai201210China State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Chinese Academy of SciencesWuhan National Laboratory for OptoelectronicsWuhan430071China State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchun130022China Department of Chemistry Tsinghua UniversityBeijing100084China School of Chemistry and Chemical Engineering Frontiers Science Center for Transformative MoleculesInstitute of Translational MedicineShanghai Jiao Tong UniversityShanghai200240China Interdisciplinary Center for Brain Information Brain Cognition and Brain Disease InstituteShenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research InstitutionsFaculty of Life and Health SciencesShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518055China Lingang Laboratory Shanghai201602China School of Biomedical Engineering Shanghai Jiao Tong UniversityShanghai200240China Institute of Systems and Physical Biology Shenzhen Bay LaboratoryShenzhen518055China Department of Nuclear Medicine Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan430022China

Analyzing the complex structures and functions of brain is the key issue to understanding the physiological and pathological *** neuronal morphology and local distribution of neurons/blood vessels in the brain have been known,the subcellular structures of cells remain challenging,especially in the live *** addition,the complicated brain functions involve numerous functional molecules,but the concentrations,distributions and interactions of these molecules in the brain are still poorly *** this review,frontier techniques available for multiscale structure imaging from organelles to the whole brain are first overviewed,including magnetic resonance imaging(MRI),computed tomography(CT),positron emission tomography(PET),serial-section electron microscopy(ss EM),light microscopy(LM)and synchrotron-based X-ray microscopy(XRM).Specially,XRM for three-dimensional(3D)imaging of large-scale brain tissue with high resolution and fast imaging speed is ***,the development of elegant methods for acquisition of brain functions from electrical/chemical signals in the brain is *** particular,the new electrophysiology technologies for neural recordings at the single-neuron level and in the brain are also *** also focus on the construction of electrochemical probes based on dual-recognition strategy and surface/interface chemistry for determination of chemical species in the brain with high selectivity and long-term stability,as well as electrochemophysiological microarray for simultaneously recording of electrochemical and electrophysiological signals in the ***,the recent development of brain MRI probes with high contrast-to-noise ratio(CNR)and sensitivity based on hyperpolarized techniques and multi-nuclear chemistry is ***,multiple optical probes and instruments,especially the optophysiological Raman probes and fiber Raman photometry,for imaging and biosensing in live brain are emphas

关键词： brain structure brain function brain chemistry chemical signal biosensing and bioimaging

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Study on Energy calibration of LaBr3(Ce) Scintillation Detector

Study on Energy calibration of LaBr3(Ce) Scintillation Detec...

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International Conference on Electronic Measurement and Instruments, ICEMI

作者： Zheng Jiang Siming Guo Tao Yu Xiaoyu Qie Jinjie Wu Wanchang Lai The College of Nuclear Technology and Automation Engineering Chengdu University of Technology Chengdu China Division of Ionizing Radiation Metrology National Institute of Metrology (NIM) Beijing China School of Science Hebei University of Science and Technology Shijiazhuang China

ISBN: (纸本)9781665444927

The energy calibration of LaBr3(Ce) detector is carried out by using the experimental methods of standard radioactive source, K fluorescence X-rays source and crystal diffraction monochromatic X-rays source, and the energy calibration curve is given. The calibration results using K fluorescence X-rays source and crystal diffraction monochromatic X-rays source are close to the calibration results of standard radioactive source, which verifies the rationality and reliability of the two experimental methods for the detector energy linear calibration. Using the fitting formula obtained by K fluorescence X-rays source and crystal diffraction monochromatic X-rays source, the relative error between the energy fitting value and the real value of Pb-210, Am-241, Cd-109 and Co-57 radioactive sources is less than 3.5%. For the detection of the energy range of (30–120) keV, the LaBr3(Ce) detector can basically determine the energy of the measured ray.

关键词： Diffraction Fitting X-rays Detectors Crystals Fluorescence X-ray diffraction

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Detecting and Exploiting Unit Commitment Structures in MIPs

Detecting and Exploiting Unit Commitment Structures in MIPs

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International Conference on Power and Energy technology (ICPET)

作者： Zhao-Gang Su Sheng-Jie Chen Yu-Fei Li Liang Chen Caixia Kou Zhi Cai Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China Institute of Applied Mathematics Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China College of Sciences Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology China Electric Power Research Institute Beijing China

ISBN: (数字)9798350375855

ISBN: (纸本)9798350375862

The unit commitment (UC) problem has been extensively researched in the literature, which is typically formulated as a mixed integer programming (MIP) problem. However, current studies lack effective methods to identify potential UC problem structures within a general MIP problem, making it challenging to leverage well-established valid inequalities for UC problems to accelerate the solution process. In this paper, we present a novel detection method that automatically identifies UC structures within an MIP problem by analyzing the relationships between variables and constraints. Moreover, we enhance the MIP formulation by incorporating three well-studied classes of valid inequalities as cutting planes, based on the identified UC structures. Our experiments demonstrate that our proposed UC detection method greatly improves computational efficacy of a standard MIP solver compared to the default setting.

关键词： Integer programming Production Generators Time factors Standards

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Quantum LiDAR with Frequency Modulated Continuous Wave

arXiv

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arXiv 2023年

作者： Huang, Ming-Da Jiang, Zhan-Feng Chen, Hong-Yi Zuo, Ying Hu, Xiao-Peng Yuan, Hai-Dong Zhang, Li-Jian Qin, Qi State Key Laboratory of Radio Frequency Heterogeneous Integration Shenzhen University Shenzhen518060 China Shenzhen Institute for Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China International Quantum Academy Shenzhen518048 China Guangdong Provincial Key Laboratory of Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China National Laboratory of Solid State Microstructures College of Engineering and Applied Sciences Nanjing University Nanjing210093 China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong

The range and speed of a moving object can be ascertained using the sensing technique known as light detection and ranging (LiDAR). It has recently been suggested that quantum LiDAR, which uses entangled states of light, can enhance the capabilities of LiDAR. Entangled pulsed light is used in prior quantum LiDAR approaches to assess both range and velocity at the same time using the pulses’ time of flight and Doppler shift. The entangled pulsed light generation and detection, which are crucial for pulsed quantum LiDAR, are often inefficient. Here, we study a quantum LiDAR that operates on a frequency-modulated continuous wave (FMCW), as opposed to pulses. We first outline the design of the quantum FMCW LiDAR using entangled frequency-modulated photons in a Mach-Zehnder interferometer, and we demonstrate how it can increase accuracy and resolution for range and velocity measurements by √n and n, respectively, with n entangled photons. We also demonstrate that quantum FMCW LiDAR may perform simultaneous measurements of the range and velocity without the need for quantum pulsed compression, which is necessary in pulsed quantum LiDAR. Since the generation of entangled photons is the only inefficient nonlinear optical process needed, the quantum FMCW LiDAR is better suited for practical implementations. Additionally, most measurements in the quantum FMCW LiDAR can be carried out electronically by down-converting optical signal to microwave region. Copyright © 2023, The Authors. All rights reserved.

关键词： Photons

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Recent Advances in Triboelectric Nanogenerators: From Technological Progress to Commercial Applications

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ACS Nano 2023年第12期17卷 11087-11219页

作者： Choi, Dongwhi Lee, Younghoon Lin, Zong-Hong Cho, Sumin Kim, Miso Ao, Chi Kit Soh, Siowling Sohn, Changwan Jeong, Chang Kyu Lee, Jeongwan Lee, Minbaek Lee, Seungah Ryu, Jungho Parashar, Parag Cho, Yujang Ahn, Jaewan Kim, Il-Doo Jiang, Feng Lee, Pooi See Khandelwal, Gaurav Kim, Sang-Jae Kim, Hyun Soo Song, Hyun-Cheol Kim, Minje Nah, Junghyo Kim, Wook Menge, Habtamu Gebeyehu Park, Yong Tae Xu, Wei Hao, Jianhua Park, Hyosik Lee, Ju-Hyuck Lee, Dong-Min Kim, Sang-Woo Park, Ji Young Zhang, Haixia Zi, Yunlong Guo, Ru Cheng, Jia Yang, Ze Xie, Yannan Lee, Sangmin Chung, Jihoon Oh, Il-Kwon Kim, Ji-Seok Cheng, Tinghai Gao, Qi Cheng, Gang Gu, Guangqin Shim, Minseob Jung, Jeehoon Yun, Changwoo Zhang, Chi Liu, Guoxu Chen, Yufeng Kim, Suhan Chen, Xiangyu Hu, Jun Pu, Xiong Guo, Zi Hao Wang, Xudong Chen, Jun Xiao, Xiao Xie, Xing Jarin, Mourin Zhang, Hulin Lai, Ying-Chih He, Tianyiyi Kim, Hakjeong Park, Inkyu Ahn, Junseong Huynh, Nghia Dinh Yang, Ya Wang, Zhong Lin Baik, Jeong Min Choi, Dukhyun Kyung Hee University Gyeonggi Yongin17104 Korea Republic of Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Department of Mechanical Engineering Soft Robotics Research Center Seoul National University Seoul08826 Korea Republic of Department of Mechanical Engineering Gachon University Seongnam13120 Korea Republic of Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Hsinchu30013 Taiwan School of Advanced Materials Science & Engineering Sungkyunkwan University Suwon16419 Korea Republic of Sungkyunkwan University 2066 Seobu-ro Gyeonggi Suwon16419 Korea Republic of Department of Chemical and Biomolecular Engineering National University of Singapore 4 Engineering Drive 4 117585 Singapore Division of Advanced Materials Engineering Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Department of Physics Inha University 100 Inha-ro Incheon22212 Korea Republic of School of Materials Science & Engineering Yeungnam University Gyeongbuk Gyeongsan38541 Korea Republic of 291 Daehak-ro Daejeon34141 Korea Republic of School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore Institute of Flexible Electronics Technology of Tsinghua Zhejiang Jiaxing314000 China Nanomaterials and System Lab Major of Mechatronics Engineering Faculty of Applied Energy System Jeju National University Jeju632-43 Korea Republic of School of Engineering University of Glasgow GlasgowG128QQ United Kingdom Seoul02792 Korea Republic of Department of Physics Inha University Incheon22212 Korea Republic of Suwon16419 Korea Republic of Department of

Serious climate changes and energy-related environmental problems are currently critical issues in the world. In order to reduce carbon emissions and save our environment, renewable energy harvesting technologies will serve as a key solution in the near future. Among them, triboelectric nanogenerators (TENGs), which is one of the most promising mechanical energy harvesters by means of contact electrification phenomenon, are explosively developing due to abundant wasting mechanical energy sources and a number of superior advantages in a wide availability and selection of materials, relatively simple device configurations, and low-cost processing. Significant experimental and theoretical efforts have been achieved toward understanding fundamental behaviors and a wide range of demonstrations since its report in 2012. As a result, considerable technological advancement has been exhibited and it advances the timeline of achievement in the proposed roadmap. Now, the technology has reached the stage of prototype development with verification of performance beyond the lab scale environment toward its commercialization. In this review, distinguished authors in the world worked together to summarize the state of the art in theory, materials, devices, systems, circuits, and applications in TENG fields. The great research achievements of researchers in this field around the world over the past decade are expected to play a major role in coming to fruition of unexpectedly accelerated technological advances over the next decade. © 2023 The Authors. Published by American Chemical Society

关键词： Nanogenerators

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Quantum-corrected thickness-dependent thermal conductivity in amorphous silicon predicted by machine learning molecular dynamics simulations

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Physical Review B 2023年第5期107卷 054303-054303页

作者： Yanzhou Wang Zheyong Fan Ping Qian Miguel A. Caro Tapio Ala-Nissila Beijing Advanced Innovation Center for Materials Genome Engineering Department of Physics University of Science and Technology Beijing Beijing 100083 China Department of Applied Physics QTF Center of Excellence Aalto University FIN-00076 Aalto Espoo Finland College of Physical Science and Technology Bohai University Jinzhou 121013 China Department of Electrical Engineering and Automation Aalto University FIN-02150 Espoo Finland Department of Chemistry and Materials Science Aalto University FIN-02150 Espoo Finland Interdisciplinary Centre for Mathematical Modelling and Department of Mathematical Sciences Loughborough University Loughborough Leicestershire LE11 3TU United Kingdom

Amorphous silicon (a-Si) is an important thermal-management material and also serves as an ideal playground for studying heat transport in strongly disordered materials. Theoretical prediction of the thermal conductivity of a-Si in a wide range of temperatures and sample sizes is still a challenge. Herein we present a systematic investigation of the thermal transport properties of a-Si by employing large-scale molecular dynamics (MD) simulations with an accurate and efficient machine learned neuroevolution potential (NEP) trained against abundant reference data calculated at the quantum-mechanical density-functional-theory level. The high efficiency of NEP allows us to study the effects of finite size and quenching rate in the formation of a-Si in great detail. We find that a simulation cell up to 64000 atoms (a cubic cell with a linear size of 11 nm) and a quenching rate down to 1011 K s−1 are required for almost convergent thermal conductivity. Structural properties, including short- and medium-range order as characterized by the pair-correlation function, angular-distribution function, coordination number, ring statistics, and structure factor are studied to demonstrate the accuracy of NEP and to further evaluate the role of quenching rate. Using both the heterogeneous and homogeneous nonequilibrium MD methods and the related spectral decomposition techniques, we calculate the temperature- and thickness-dependent thermal conductivity values of a-Si and show that they agree well with available experimental results from 10 K to room temperature. Our results also highlight the importance of quantum effects in the calculated thermal conductivity and support the quantum-correction method based on the spectral thermal conductivity.

关键词： Thermal conductivity Amorphous materials Machine learning Molecular dynamics

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Future Networks 2030: Challenges in Intelligent Transportation Systems 8

Future Networks 2030: Challenges in Intelligent Transportati...

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8th IEEE International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2020

作者： Pop, Madalin-Dorin Pandey, Jitendra Ramasamy, Velmani University of Timioara Automation and Applied Informatics Timioara Romania Middle East College Department of Computing Muscat Oman Siddhartha Institute of Technology and Sciences Department of Electronics and Communication Engineering Narapally Hyderabad India

ISBN: (纸本)9781728170169

Many cities around the world implement the Intelligent Transportation Systems (ITS) concept to reduce road traffic congestion. This concept implies the usage of Internet of Things (IoT) technologies to ensure a better traffic flow, especially in crowded urban areas. Sensors networks became part of road infrastructure and have as main responsibilities to collect real-time traffic data and to send them to Traffic Management Centres (TMCs) which control further the traffic lights timings. Today's technologies meet some limitations in terms of efficiency. This paper starts with an overview of these limitations to create a path for discussing the challenges that the development of ITS will meet in the context of Future Networks (FN) 2030 concept. Based on this development path, the identification of current limitations and possible future challenges consists of an important step of this research. Further, the main contribution in this research is to show how the ITS shall adapt to meet the requirements of FN 2030 by providing an architecture for Future ITS 2030 that meets the general ITS needs. © 2020 IEEE.

关键词： Internet of things

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