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A 2-bit graphene encoder based on the plasmon-induced transparency effect and its sensing characteristics

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Results in Physics 2024年 59卷

作者： Zhu, Aijun Li, Zongteng Hou, Weigang Yang, Xinghua Cheng, Lei Hu, Cong Qiao, Fei Mahapatra, Rabi Guangxi Key Laboratory of Automatic Detecting Technology and Instruments Guilin University of Electronic Technology Guilin 541004 China Shanxi Key Laboratory of Advanced Semiconductor Optoelectronic Devices and Integrated Systems Jincheng Shanxi 048000 China Institute of Intelligent Communication and Network Security Chongqing University of Posts and Telecommunications Chongqing 400000 China College of Science Beijing Forestry University Beijing 100083 China Jincheng Research Institute of Opto-mechatronics Industry Jincheng Shanxi 048000 China Guangxi Key Laboratory of Brain-inspired Computing and Intelligent Chips Guangxi Normal University Guilin 541004 China Department of Electronic Engineering Tsinghua University Beijing 100084 China Department of Computer Science and Engineering Texas A&M University College Station 77843-3112 TX United States

A 2-bit encoder based on the plasmon-induced transparency (PIT) effect was proposed and investigated in the range from 2 to 7 THz. The Lorentz oscillation coupling model was utilized to confirm the simulation. By tuning the Fermi levels of cross1 and cross2, the 2-bit encoder was achieved. And the minimum MD was 94.73 %, the minimum ER was 12.77 dB, and the maximum IL was 0.32 dB. As a sensor, the structure had a sensitivity of up to 2.33 THz/RIU. In addition, due to the insensitivities to incidence angle and polarization angle, the encoder could be utilized to complex environments. Therefore, these results reveals that our work is significant in terahertz encoders, optical switches, sensors, slow light devices, and modulators. © 2024 The Author(s)

关键词： 2-bit encoder Metamaterial Plasmon-induced transparency (PIT) effect Plasmonic-graphene Terahertz (THz)

Transition Metal-Vacancy Point Defects in Zinc Oxide as Deep-Level Spin Qubits

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arXiv 2025年

作者： Zhang, Shimin Park, Taejoon Perez, Erik Li, Kejun Wang, Xingyi Wang, Yanyong Vega Bazantes, Jorge D. Zhang, Ruiqi Sun, Jianwei Fu, Kai-Mei C. Seo, Hosung Ping, Yuan Department of Materials Science and Engineering University of Wisconsin-Madison 53706 United States SKKU Advanced Institute of Nanotechnology Sungkyunkwan University Gyeonggi Suwon16419 Korea Republic of Department of Energy Systems Research Department of Physics Ajou University Gyeonggi Suwon16499 Korea Republic of Department of Physics University of California Santa CruzCA95064 United States Department of Electrical and Computer Engineering University of Washington SeattleWA98195 United States School of Science & Engineering Tulane University 6823 St Charles Ave New OrleansLA70118 United States Department of Physics University of Washington SeattleWA98195 United States Physical Sciences Division Pacific Northwest National Laboratory RichlandWA99352 United States Department of Quantum Information Engineering Sungkyunkwan University Gyeonggi Suwon16419 Korea Republic of Center for Quantum Information Korea Institute of Science and Technology Seoul02792 Korea Republic of Department of Physics University of Wisconsin-Madison 53706 United States Department of Chemistry University of Wisconsin-Madison 53706 United States

Wide band gap oxides are promising host materials for spin defect qubits, offering unique advantages such as a dilute nuclear spin environment. Zinc oxide (ZnO), in particular, can achieve exceptional high purity, which enables long spin coherence time. In this work, we theoretically search for deep-level point defects in ZnO with optimal physical properties for optically-addressable spin qubits. Using first-principles calculations, we predict the Molybdenum-vacancy complex defect (MoZnvO)2+ in ZnO to own promising spin and optical properties, including spin-triplet ground state, optical transition in the visible to near-infrared range with high quantum yield, allowed intersystem crossings with a sizable optically-detected magnetic resonance contrast, and long spin T2 and T∗2. Notably, we find the Huang-Rhys factor of the defect to be around 5, which is significantly smaller than the typical range of 10-30 for most known defects in ZnO. Furthermore, we compare the spin decoherence driven by the nuclear spin bath and paramagnetic impurity baths. We find that the paramagnetic impurities are very effective in causing spin decoherence even with very low concentrations, implying that they can likely dominate the spin decoherence in ZnO even after isotopic purification. Using the computed excited-state energies and kinetic rates as inputs, we predict the ODMR contrast and propose a new protocol for spin qubit initialization and readout, which could be generalized to other systems with forbidden axial intersystem crossings. © 2025, CC BY.

关键词： Zinc oxide

Estimating axon radius using diffusion-relaxation MRI: Calibrating a surface-based relaxation model with histology

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arXiv 2023年

作者： Barakovic, Muhamed Pizzolato, Marco Tax, Chantal M.W. Rudrapatna, Umesh Magon, Stefano Dyrby, Tim B. Granziera, Cristina Thiran, Jean-Philippe Jones, Derek K. Canales-Rodríguez, Erick J. Basel Department of Biomedical Engineering University Hospital Basel University of Basel Basel Switzerland Department of Neurology University Hospital Basel Switzerland Cardiff University Brain Research Imaging Centre Cardiff University Wales Cardiff United Kingdom Lausanne Switzerland Roche Pharma Research & Early Development Neuroscience and Rare Diseases Roche Innovation Center Basel Switzerland Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby Denmark Image Sciences Institute University Medical Center Utrecht Netherlands Danish Research Centre for Magnetic Resonance Centre for Functional and Diagnostic Imaging and Research Copenhagen University Hospital Amager & Hvidovre Hvidovre Denmark University Hospital Basel University of Basel Basel Switzerland Radiology Department Centre Hospitalier Universitaire Vaudois University of Lausanne Lausanne Switzerland EPFL Lausanne Switzerland

Axon radius is a potential biomarker for brain diseases and a crucial tissue microstructure parameter that determines the speed of action potentials. Diffusion MRI (dMRI) allows non-invasive estimation of axon radius, but accurately estimating the radius of axons in the human brain is challenging. Most axons in the brain have a radius below one micrometre, which falls below the sensitivity limit of dMRI signals even when using the most advanced human MRI scanners. Therefore, new MRI methods that are sensitive to small axon radii are needed. In this proof-of-concept investigation, we examine whether a surface-based axonal relaxation process could mediate a relationship between intra-axonal T2 and T1 times and inner axon radius, as measured using postmortem histology. A unique in vivo human diffusion-T1-T2 relaxation dataset was acquired on a 3T MRI scanner with ultra-strong diffusion gradients, using a strong diffusion-weighting (i.e., b=6000 s/mm2) and multiple inversion and echo times. A second reduced diffusion-T2 dataset was collected at various echo times to evaluate the model further. The intra-axonal relaxation times were estimated by fitting a diffusion-relaxation model to the orientation-averaged spherical mean signals. Our analysis revealed that the proposed surface-based relaxation model effectively explains the relationship between the estimated relaxation times and the histological axon radius measured in various corpus callosum regions. Using these histological values, we developed a novel calibration approach to predict axon radius in other areas of the corpus callosum. Notably, the predicted radii and those determined from histological measurements were in close agreement. © 2023, CC BY-NC-ND.

关键词： Magnetic resonance imaging

Gas–solid interface charge characterisation techniques for HVDC GIS/GIL insulators

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High Voltage 2020年第2期5卷 95-109页

作者： Lei Zhang Chuanjie Lin Chuanyang Li Simone Vincenzo Suraci Geng Chen Uwe Riechert Tohid Shahsavarian Masayuki Hikita Youping Tu Zhousheng Zhang Davide Fabiani Jinliang He School of Electrical Engineering Shanghai University of Electric PowerChangyang Road#2588Shanghai200090People's Republic of China State Key Laboratory of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing100084People's Republic of China Department of Electrical Electronicand Information Engineering‘Guglielmo Marconi’University of BolognaViale Risorgimento 2Bologna40136Italy Beijing Area Major Laboratory of High Voltage and Electromagnetic Compatibility North China Electric Power UniversityBeijing 102206People's Republic of China ABB Switzerland Ltd High Voltage ProductsZurichSwitzerland Electrical Insulation Research Center Institute of Materials ScienceElectrical and Computer EngineeringUniversity of ConnecticutStorrsCT 06269USA Kyushu Institute of Technology KitakyushuJapan

Surface charge accumulation on the spacers is one of the key issues restraining the development of HVDC GIS/*** precise measurement of surface charge properties provides the basis for further study of the surface charge transport mechanism as well as the charge-induced flashover mechanism under DC *** this study,the authors discuss their perspective on the current status,development needs and potential developing orientation of surface charge characterisation *** surface potential measurement methods and charge inversion algorithms are reviewed regarding the previous studies and future research *** and outlooks of surface charge measurement techniques are also discussed with the background of laboratory experiment results and on-site *** is hopefully that this study can serve as a useful guide reference for researchers within the same research *** importantly,it is authors’hope that this study can inspire some novel ideas for readers into developing of more accurate and scientific interface charge characterisation techniques.

关键词： GIL charge interface

Blockchain-based Edge Computing Service with Dynamic Entry and Exit Mechanism

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IEEE Transactions on Mobile Computing 2025年

作者： He, Qiang Feng, Zheng Fang, Hui Wang, Xingwei Zhao, Liang Yu, Keping Choo, Kim-Kwang Raymond Northeastern University College of Medicine and Biological Information Engineering China Shanghai University of Finance and Economics Research Institute for Interdisciplinary Science School of Information Management and Engineering China Northeastern University College of Computer Science and Engineering Shenyang110169 China Shenyang Aerospace University College of Computer Science and Engineering Shenyang110136 China Hosei University Graduate School of Science and Engineering Tokyo184-8584 Japan University of Texas at San Antonio Department of Information Systems and Cyber Security San AntonioTX78249 United States

With the widespread application of 5G and artificial intelligence (AI) technology, the Internet of Things (IoT) has been expanding and integrated into various aspects of our daily lives. However, this also poses challenges such as the ubiquitous demand for communication and computing resources, and data privacy issues. Considering its flexible deployment, high security, and ease of scalability, blockchain-enabled edge computing IoT network (BECIN) has become a promising solution to provide secure and fast communication and computing services. However, existing research on computation offloading in edge computing largely overlooks the stochastic arrival of computational tasks and the potential variability in the number, locations, and resource provisions of edge computing service providers. Therefore, we propose a dynamic, self-adjusting BECIN framework aimed at providing long-term stable, efficient, and secure edge computing data offloading services for ground users in a specific region. This framework supports the dynamic entry and exit of edge computing service providers. Additionally, we introduce a novel dynamic Dueling DDQN approach to update the offloading and resource management policies based on changes in resource provisioning. Experimental results demonstrate the feasibility and superior performance of our framework on system cost and system latency. © 2002-2012 IEEE.

关键词： Reinforcement learning

Joint analysis of the Portuguese and Spanish NECP for 2021-2030

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Joint analysis of the Portuguese and Spanish NECP for 2021-2...

International Conference on European Electricity Market, EEM

作者： André Rodrigues de Oliveira José Villar Collado João Abel Peças Lopes João Paulo Tomé Saraiva Nuno Soares Fonseca Salvador Doménech Fco. Alberto Campos INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal Institute for Research in Technology Comillas Pontifical University c/ Santa Cruz de Marcenado Madrid Spain

ISBN: (数字)9781728169194

ISBN: (纸本)9781728169200

The European Union (EU) energy strategy towards decarbonization led EU countries to elaborate their corresponding National Energy and Climate Plans (NECP) for the period 2021 to 2030. This paper analyzes the Portuguese and Spanish NECPs concerning their power systems. CEVESA, a model for the long-term planning and operation of the Iberian electricity system, is used. The analysis is based on simulating the reference NECP scenario, as well as other alternative scenarios with different solar and wind generation shares, CO2 prices and fuel costs. Results provide insights on the MIBEL electricity market evolution under the current decarbonization national strategies.

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Relationship among state reopening policies, health outcomes and economic recovery through first wave of the COVID-19 pandemic in the U.S

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arXiv 2021年

作者： Ligo, Alexandre K. Mahoney, Emerson Cegan, Jeffrey Trump, Benjamin D. Jin, Andrew S. Kitsak, Maksim Keenan, Jesse Linkov, Igor US Army Corps of Engineers Engineer Research and Development Center ConcordMA United States University of Virginia Department of Engineering Systems and Environment CharlottesvilleVA United States Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft Netherlands Carnegie Mellon University Department of Engineering and Public Policy PittsburghPA United States Tulane University School of Architecture New OrleansLA United States

State governments in the U.S. have been facing difficult decisions involving tradeoffs between economic and health-related outcomes during the COVID-19 pandemic. Despite evidence of the effectiveness of government-mandated restrictions mitigating the spread of contagion, these orders are stigmatized due to undesirable economic consequences. This tradeoff resulted in state governments employing mandates at widely different ways. We compare the different policies states implemented during periods of restriction ("lockdown") and reopening with indicators of COVID-19 spread and consumer card spending at each state during the first "wave" of the pandemic in the U.S. between March and August 2020. We find that while some states enacted reopening decisions when the incidence rate of COVID-19 was minimal or sustained in its relative decline, other states relaxed socioeconomic restrictions near their highest incidence and prevalence rates experienced so far. Nevertheless, all states experienced similar trends in consumer card spending recovery, which was strongly correlated with reopening policies following the lockdowns and relatively independent from COVID-19 incidence rates at the time. Our findings suggest that consumer card spending patterns can be attributed to government mandates rather than COVID-19 incidence in the states. We estimate the recovery in states that reopened in late April was more than the recovery in states that did not reopen in the same period – 15% for consumer card spending and 18% for spending by high income households. This result highlights the important role of state policies in minimizing health impacts while promoting economic recovery and helps planning effective interventions in subsequent waves and immunization efforts. © 2021, CC BY.

关键词： SARS

Joint satellite gateway placement and routing for integrated satellite-terrestrial networks

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arXiv 2020年

作者： Torkzaban, Nariman Gholami, Anousheh Papagianni, Chrysa Baras, John S. Department of Electrical and Computer Engineering Institute for Systems Research University of Maryland College ParkMD20742 United States Nokia Bell Labs Antwerp Belgium

With the increasing attention to the integrated satellite-terrestrial networks (ISTNs), the satellite gateway placement problem becomes of paramount importance. The resulting network performance may vary depending on the different design strategies. In this paper a joint satellite gateway placement and routing strategy for the terrestrial network is proposed to minimize the overall cost of gateway deployment and traffic routing, while adhering to the average delay requirement for traffic demands. Although traffic routing and gateway placement can be solved independently, the dependence between the routing decisions for different demands makes it more realistic to solve an aggregated model instead. We develop a mixed integer linear program (MILP) formulation for the problem. We relax the integrality constraints to achieve a linear program (LP) which reduces time-complexity at the expense of a sub-optimal solution. We further propose a variant of the proposed model to balance the load between the selected gateways. Copyright © 2020, The Authors. All rights reserved.

关键词： Integer programming

A Scalable Data Processing Model for Big Data Analysis of Enterprise Technology Innovation

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A Scalable Data Processing Model for Big Data Analysis of En...

International Conference on Virtual Reality and Intelligent systems (ICVRIS)

作者： Zhixin Li Bin Liu Yang Chen School of Computer Technology and Engineering Changchun Institute Of Technology Changchun China Research and Development Center Changchun UP Optotech Co. Ltd. Changchun China

In many areas such as enterprise technology innovation, the volume of data to be analyzed grows rapidly. In order to analyze and use these huge data resources, we must rely on effective data analysis technology. However, the traditional data processing technology has encountered certain obstacles in scalability. A Scalable Data Processing Model (SDPM) was proposed in this study to solve problems concerning innovative services of enterprises. The model performed formal analysis and description of SDPM, and through this model, it implemented the clustering analysis and incremental computing algorithm of enterprise technology innovation application data. research results demonstrate the potential of the proposed model can effectively analyze enterprise technology innovation data, and have similar performance in incremental computing for different sizes of data sets. The query response time is less than 1 second on average. The research results of this study show that the SDPM can adapt to the service needs of enterprise technology innovation data and improve the efficiency of data processing. This proposed model provided technical and theoretical support for big data processing.

关键词： Technological innovation Solid modeling Analytical models Adaptation models Computational modeling Virtual reality Big Data