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engineering strong spin-frustration at the surface of three-dimensional graphene

science Bulletin 2024年第18期69卷 2816-2819页

作者： Wenjing Li Ken Chen Menglei Li Huiying Gao Jize Zhao Fawei Zheng Wenhui Duan Center for Quantum Physics Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement(MOE)School of PhysicsBeijing Institute of TechnologyBeijing 100081China Beijing Key Lab of Nanophotonics&Ultrafine Optoelectronic Systems School of PhysicsBeijing Institute of TechnologyBeijing 100081China School of Physical Science and Technology Key Laboratory of Quantum Theory and Applications of MOELanzhou UniversityLanzhou 730000China Lanzhou Center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu ProvinceLanzhou UniversityLanzhou 730000China Department of Physics Capital Normal UniversityBeijing 100048China State Key Laboratory of Low Dimensional Quantum Physics Department of PhysicsTsinghua UniversityBeijing 100084China Institute for Advanced Study Tsinghua UniversityBeijing 100084China Frontier Science Center for Quantum Information Beijing 100084China Beijing Academy of Quantum Information Sciences Beijing 100193China

Since the first successful fabrication in 2004[1],graphene has received tremendous attention due to its extremely simple atomic structure and alluring physical *** example,its massless low energy excitations have a linear dispersion and thus its transport property is governed by Dirac equation instead of Schr?dinger *** special electronic structures suppress the intra-valley and inter-valley backscatterings,leading to the half-integer and fractional quantum Hall effect[2]under magnetic field and the relativistic quantum tunneling described by the Klein paradox[3].

关键词： properties equation quantum

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Attention-Based Deep Learning Model for Image Desaturation of SDO/AIA

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Research in Astronomy and Astrophysics 2023年第8期23卷 92-102页

作者： Xinze Zhang Long Xu Zhixiang Ren Xuexin Yu Jia Li State Key Laboratory of Space Weather National Space Science CenterChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Peng Cheng Laboratory Shenzhen 518000China Department of Automation Tsinghua UniversityBeijing 100084China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

The Atmospheric Imaging Assembly(AIA)onboard the Solar Dynamics Observatory(SDO)captures full-disk solar images in seven extreme ultraviolet wave *** a violent solar flare occurs,incoming photoflux may exceed the threshold of an optical imaging system,resulting in regional saturation/overexposure of ***,the lost signal can be partially retrieved from non-local unsaturated regions of an image according to scattering and diffraction principle,which is well consistent with the attention mechanism in deep ***,an attention augmented convolutional neural network(AANet)is proposed to perform image desaturation of SDO/AIA in this *** is built on a U-Net backbone network with partial convolution and adversarial *** addition,a lightweight attention model,namely criss-cross attention,is embedded between each two convolution layers to enhance the backbone *** results validate the superiority of the proposed AANet beyond state-of-the-arts from both quantitative and qualitative comparisons.

关键词： techniques image processing-Sun atmosphere-Sun flares

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Simulation of the Ecosystem Productivity Responses to Aerosol Diffuse Radiation Fertilization Effects over the Pan-Arctic during 2001–19

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Advances in Atmospheric sciences 2024年第1期41卷 84-96页

作者： Zhiding ZHANG Xu YUE Hao ZHOU Jun ZHU Yadong LEI Chenguang TIAN Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science&Technology(NUIST)Nanjing 210044China Climate Change Research Center Institute of Atmospheric Physics(IAP)Chinese Academy of Sciences(CAS)Beijing 100029China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Severe Weather&Key Laboratory of Atmospheric Chemistry of CMA Chinese Academy of Meteorological SciencesBeijing 100081China

The pan-Arctic is confronted with air pollution transported from lower *** have shown that aerosols help increase plant photosynthesis through the diffuse radiation fertilization effects(DRFEs).While such DRFEs have been explored at low to middle latitudes,the aerosol impacts on pan-Arctic ecosystems and the contributions by anthropogenic and natural emission sources remain less ***,we perform regional simulations at 0.2o×0.2ousing a well-validated vegetation model(Yale Interactive terrestrial Biosphere,YIBs)in combination with multi-source of observations to quantify the impacts of aerosol DRFEs on the net primary productivity(NPP)in the pan-Arctic during *** show that aerosol DRFEs increase pan-Arctic NPP by 2.19 Pg C(12.8%)yr^(-1)under clear-sky conditions,in which natural and anthropogenic sources contribute to 8.9% and 3.9%,*** all-sky conditions,such DRFEs are largely dampened by cloud to only 0.26 Pg C(1.24%)yr^(-1),with contributions of 0.65% by natural and 0.59% by anthropogenic *** aerosols cause a positive NPP trend of 0.022% yr^(-1)following the increased fire activities in the *** contrast,anthropogenic aerosols induce a negative trend of-0.01% yr^(-1)due to reduced emissions from the middle *** trends in aerosol DRFEs show a turning point in the year of 2007 with more positive NPP trends by natural aerosols but negative NPP trends by anthropogenic aerosols *** affected by modeling uncertainties,this study suggests a likely increasing impact of aerosols on terrestrial ecosystems in the pan-Arctic under global warming.

关键词： diffuse radiation fertilization effects anthropogenic aerosols natural aerosols pan-Arctic net primary productivity

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Fine-Tuning Whisper for Speech Translation: A Case Study on Translating Darija to Arabic

Fine-Tuning Whisper for Speech Translation: A Case Study on ...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Labied, Maria Belangour, Abdessamad Banane, Mouad Laboratory of Information Technology and Modeling Ben m'Sik Faculty of Sciences LTIM Hassan II University Casablanca Morocco Laboratory of Artificial Intelligence & Complex Systems Engineering Faculty of Legal Economic and Social Sciences Hassan II University Casablanca Morocco

ISBN: (纸本)9798350369106

The task of translating Darija, a dialect of Arabic, into Modern Standard Arabic (MSA) presents significant challenges due to linguistic variations and the lack of representation in major models. Traditional speech recognition and translation systems, like Whisper, are generally trained on more standardized languages and often struggle with dialects like Darija. To address this issue, we fine-tuned the small version of Whisper on the Darija-C corpus for speech-to-text translation into MSA. Our approach involved adapting Whisper's translation capabilities by fine-tuning the model with 5000 training steps and evaluating its performance using the BLEUmetric. The fine-tuned model achieved a BLEU score of 0.65, reflecting a marked improvement over the baseline. This research demonstrates the effectiveness of fine-tuning models for dialectal translation tasks, offering insights into how underrepresented dialects like Darija can be better supported by advanced speech translation systems. © 2024 IEEE.

关键词： Darija-C Fine-Tuning Moroccan Darija Speech Translation Whisper

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Heavy-Traffic Optimal Size-and State-Aware Dispatching

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Performance Evaluation Review 2024年第1期52卷 7-8页

作者： Xie, Runhan Grosof, Isaac Scully, Ziv Department of Industrial Engineering and Operations Research University of California Berkeley BerkeleyCA United States Carnegie Mellon University Computer Science Department PittsburghPA United States Georgia Institute of Technology School of Industrial and Systems Engineering AtlantaGA United States School of Operations Research and Information Engineering Cornell University IthacaNY United States

We study the problem of dispatching jobs to multiple FCFS (First-Come, First-Served) queues. We consider the case where the dispatcher is size-aware, meaning it learns the size (i.e. service time) of each job as it arrives;and state-aware, meaning it always knows the amount of work (i.e. total remaining service time) at each queue. While size-and state-aware dispatching to FCFS queues has been extensively studied, little is known about optimal dispatching for the objective of minimizing mean delay. In this work, we propose the first size-and state-aware dispatching policy, called CARD (Controlled Asymmetry Reduces Delay), that provably minimizes mean delay in heavy traffic. This work summarizes our full paper. © 2024 Owner/Author.

关键词： Queueing theory

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Plant-derived natural products improve disease: Focus on gut-brain axis

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Food science and Human Wellness 2025年

作者： Chen Song Wenjing Lang Li Meng Wenxiang Ping Jingping Ge Engineering Research Center of Agricultural Microbiology Technology， Ministry of Education & Heilongjiang Provincial Key Laboratory of Ecological Restoration and Resource Utilization for Cold Region & School of Life Sciences， Heilongjiang University Heilongjiang Provincial Key Laboratory of Plant Genetic Engineering and Biological Fermentation Engineering for Cold Region & Key Laboratory of Microbiology， College of Heilongjiang Province， Heilongjiang University Key Laboratory of Science and Engineering for the Multi-modal Prevention and Control of Major Chronic Diseases， Ministry of Industry and Information Technology

Dysbiosis of the gut microbiota may lead to a wide range of metabolic， neurological， intestinal and cardiovascular disorders and even to tumorigenesis. Evidence suggests that the gut-brain axis (GBA) plays a crucial role in the treatment of these diseases. Many plant-derived natural actives modulate the gut microbiota and its metabolites， gut hormones and neurotransmitters through a variety of mechanisms， and these actions contribute to the alleviation of irritable bowel syndrome， type 2 diabetes mellitus， cancer， and brain disorders. This review focuses on how natural products act through GBA to protect the central nervous system， regulate metabolism and promote apoptosis in cancer cells. The role of gut microbiota metabolites and neurotransmitter release in modulating inflammation-related factors， promoting or reducing oxidative stress， and activating or inhibiting related signaling pathways is also discussed. This comprehensive overview of the complex GBA mechanisms deepens the understanding of how natural products can target GBA to treat disease， providing valuable insights into the development and utilization of these natural interventions.

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Zero-shot industrial image denoising with lightweight network

Zero-shot industrial image denoising with lightweight networ...

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2024 International Workshop on Automation, Control, and Communication engineering, IWACCE 2024

作者： Zhou, Chengxu Fan, Xiaojie Wang, Simeng Liu, Hongyan Gu, Ke School of Information Science and Technology Beijing University of Technology Beijing China Engineering Research Center of Intelligent Perception and Autonomous Control of Ministry of Education China Beijing Laboratory of Smart Environmental Protection China Beijing Artificial Intelligence Institute China School of Electronic & Information Engineering Liaoning University of Technology Liaoning China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology China

ISBN: (数字)9781510685420

ISBN: (纸本)9781510685413

Industrial images are often captured under full-time and full-weather conditions, leading to inevitable noise during the imaging process, which can impact subsequent detection algorithms. In recent years, image denoising with neural networks has been the rapid development. However, training such networks typically requires a large dataset, which is scarce in publicly available industrial image databases. In this paper, we propose a novel approach termed Zero-Shot Industrial Image Lightweight Denoising (ZSILD) network, which effectively denoises single noisy industrial image without the need for datasets. First, we sample the paired neighbour pixels of a random noisy industrial image, which are then utilized to train a lightweight denoising network. Second, we design a lightweight depthwise convolutions network based on bottleneck residual structure with shortcut connections. Finally, this network is trained on the sampled pairs using a novel loss function aimed at enhancing denoising performance. Our experiments conduct on real-world industrial ambient noise demonstrate that our ZSILD method outperforms existing denoising techniques, all while requiring comparatively minimal computational resources. © 2024 SPIE. All rights reserved.

关键词： Image denoising

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A Quantum Temporal Difference Learning Method Based on Quantum World Model

A Quantum Temporal Difference Learning Method Based on Quant...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Zeng, Peigen He, Ying Yu, F. Richard Du, Jianbo Shenzhen University College of Computer Science and Software Engineering Shenzhen China Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Xi'an China Carleton University School of Information Technology Ottawa Canada

ISBN: (纸本)9798350351255

Based on quantum parallelism theory and quantum phenomena such as superposition and entanglement, quantum reinforcement learning (QRL) has the potential to surpass classical reinforcement learning (RL). Although some excellent works have been done on QRL, existing RL methods encounter chanllenges when performing in environments with sparse rewards. In this paper, we provide a new perspective on conducting temporal difference (TD) learning in quantum computing, which can eliminate redundant exploration steps compared to classical methods. Specifically, we first use environment information to construct a world model with quantum circuits, enabling it to interact in a quantum way. Then, we perform the learning process by using the quantum world model and Grover's algorithm to query backwards how to reach the recorded states with high TD-errors. Simulation results show that our proposed method has superior performance compared to classical RL algorithms. © 2024 IEEE.

关键词： Adversarial machine learning

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A Novel Steerable Catheter for Vascular Interventional Surgery 20

A Novel Steerable Catheter for Vascular Interventional Surge...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Yan, Yonggan Guo, Shuxiang Lyu, Chuqiao Zhao, Duohao Lin, Zhijun Beijing Institute of Technology Key Laboratory of Convergence Biomedical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology Beijing100081 China Southern University of Science and Technology The Department of Electronic and Electrical Engineering Guangdong Shenzhen518055 China

ISBN: (纸本)9798350320831

To improve the operation success rate, the steerable catheter is theoretically significant and practically valuable to design. However, it is still difficult for most existing catheters to realize this function. In this paper, to steer the catheter head, a novel spring-based tendon-drive structure was proposed with a diameter of 1.5mm. To obtain precise tip poses, based on the local force analysis, it is demonstrated that the contact force at each point between the tendon and spring is equal. And under the premise of frictionless, the curvature at each point of the tendon is equal, which is only related to the tension of the tendon. Then the proposed structure is simplified to a cantilever beam only subjected to bending moment. And the deformation of the catheter tip with the control parameters is expressed. Finally, the experimental setup is established and the experimental results showed that the proposed spring-based tendon-driven catheter deflected in a circular. And the results justified the feasibility of the cantilever beam assumption and the correctness of the deformation formulas. The proposed tendon-driven catheter has the potential in improving the success rate of the vascular approach and operation safety. © 2023 IEEE.

关键词： Tendons

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No-Reference Image Quality Assessment via Multibranch Convolutional Neural Networks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第1期4卷 148-160页

作者： Pan, Zhaoqing Yuan, Feng Wang, Xu Xu, Long Shao, Xiao Kwong, Sam the School of Electrical and Information Engineering Tianjin University Tianjin300072 China the College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China the Key Laboratory of Solar Activity National Astronomical Observatories Chinese Academy of Sciences Beijing100012 China the School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China the Department of Computer Science City University of Hong Kong Hong Kong

No-reference image quality assessment (NR-IQA) aims to evaluate image quality without using the original reference images. Since the early NR-IQA methods based on distortion types were only applicable to specific distortion scenarios, and lack of practicality, it is challenging to designing a universal NR-IQA method. In this article, a multibranch convolutional neural network (MB-CNN) based NR-IQA method is proposed, which includes a spatial-domain feature extractor, a gradient-domain feature extractor, and a weight mechanism. The spatial-domain feature extractor aims to extract the distortion features from the spatial domain. The gradient-domain feature extractor is used to guide the spatial-domain feature extractor to pay more attention to the distortions of the structure information. Particularly, the spatial-domain feature extractor uses the hierarchical feature merge module to realize multiscale feature representation, and the gradient-domain feature extractor uses pyramidal convolution to extract the multiscale structure information of the distorted image. In addition, a position vector is proposed to build the weight mechanism by considering the position relationships between patches and its entire image for improving the final prediction performance. We conduct the experiments on five representative databases: LIVE, TID2013, CSIQ, LIVE MD and Waterloo Exploration Database, and the experimental results show that the proposed NR-IQA method achieves the state-of-the-art performance, which demonstrate the effectiveness of our proposed NR-IQA method. The code ofthe proposed MB-CNN will be released at https://***/NUIST-Videocoding/MB-CNN. © 2020 IEEE.

关键词： Neural networks

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