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A Low SAR, Small size, High gain, Circularly polarized Antenna for Wearable Application

Journal of Physics: Conference Series 2020年第1期1651卷

作者： Chao Wang Liang Zhang Yi Cheng XueMei Li Xianliang Wu Key Lab of Ministry of Education of Intelligent Computing & Signal Processing Anhui University Hefei Anhui 230601 China AnHui Province Key Laboratory of simulation and design for Electronic information system Hefei Normal university Hefei Anhui 230601 China

A planar, small size, high gain, low specific absorption rate (SAR) and circularly-polarized (CP) wearable antenna is proposed in this paper. The antenna is fabricated on a substrate with a dielectric constant of 3.5 with a thickness of 0.5 mm and sized at 42×42 mm only. Both the simulation results show that the overlap bandwidth of impedance and axial ratio of the proposed antenna is 13.7% (5.15-5.91 GHz). To isolate the antenna against the influence of the human body, a artificial magnetic conductor (AMC) plane is added on the reverse side of the radiator. The AMC structure effectively isolates the human body from the radiation of the antenna and reduces the specific absorption rate (SAR) of it by more than 96.1% at 5.5 GHz, which improves the antenna gain and the peak gain reaches 5.09 dBi at 5.5 GHz. The wearable performance of the antenna was analyzed, and it is observed that it can sustain good performance even under human body loading. Beside, the antenna has a small size, which makes it ideal for wearable applications.

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Cathodic titania nanotube arrays as anode material for lithium-ion batteries

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Journal of Materials Science 2016年第8期52卷 4323-4332页

作者： Tauseef Anwar Wang Li Rizwan Ur Rehman Sagar Farhat Nosheen Rajan Singh Hasnain Mehdi Jafri Khurram Shehzad Liang Tongxiang State Key Lab of New Ceramic and Fine Processing Institute of Nuclear and New Energy Technology Tsinghua University Beijing People’s Republic of China Nanshan District Key Lab for Biopolymer and Safety Evaluation College of Material Science & Engineering and Department of Optoelectronic Engineering Shenzhen University Shenzhen People’s Republic of China Sulaiman Bin-Abdullah Aba Al-Khail-Centre of Interdisciplinary Research in Basic Sciences (SA-CIRBS) International Islamic University Islamabad Pakistan Laboratory of Advanced Materials School of Materials Science and Engineering Tsinghua University Beijing People’s Republic of China Department of Physics University of Science and Technology Beijing Beijing People’s Republic of China College of Information Science and Electronic Engineering and State Key Laboratory of Silicon Materials Zhejiang University Hangzhou People’s Republic of China

The titanium dioxide nanotube arrays (TNAs) have been synthesized at cathode and anode via standard electrochemical method for their subsequent use as anode material for lithium-ion batteries (LIBs). The TNAs fabricated at cathode have higher Ti3+ in comparison to TNAs at anode, which was confirmed using X-ray photoelectron spectroscopy and Raman spectrometry. Moreover, the lattice parameters of cathodic TNAs are estimated via Rietveld refinement of X-ray diffraction, which also conform to Ti3+ doping and insertion of protons (H+). The electrochemical impedance spectroscopy hints an increment in the electronic conductivity of TNAs fabricated at cathode. As a result, high reversible areal–specific capacity (~385.5 µAh cm−2 at 100 µA cm−2) with excellent rate capability is acquired by utilizing TNAs fabricated at cathode as anode material in LIBs.

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Customized Conversational Recommender Systems

arXiv

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arXiv 2022年

作者： Li, Shuokai Zhu, Yongchun Xie, Ruobing Tang, Zhenwei Zhang, Zhao Zhuang, Fuzhen He, Qing Xiong, Hui Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China WeChat Search Application Department Tencent China King Abdullah University of Science and Technology Thuwal Saudi Arabia Institute of Artificial Intelligence Beihang University Beijing100191 China Sklsde School of Computer Science Beihang University Beijing100191 China Artificial Intelligence Thrust The Hong Kong University of Science and Technology Guangzhou China The Key Lab of Intelligent Information Processing of Chinese Academy of Sciences China

Conversational recommender systems (CRS) aim to capture user's current intentions and provide recommendations through real-time multi-turn conversational interactions. As a human-machine interactive system, it is essential for CRS to improve the user experience. However, most CRS methods neglect the importance of user experience. In this paper, we propose two key points for CRS to improve the user experience: (1) Speaking like a human, human can speak with different styles according to the current dialogue context. (2) Identifying fine-grained intentions, even for the same utterance, different users have diverse finegrained intentions, which are related to users' inherent preference. Based on the observations, we propose a novel CRS model, coined Customized Conversational Recommender System (CCRS), which customizes CRS model for users from three perspectives. For human-like dialogue services, we propose multi-style dialogue response generator which selects context-aware speaking style for utterance generation. To provide personalized recommendations, we extract user's current fine-grained intentions from dialogue context with the guidance of user's inherent preferences. Finally, to customize the model parameters for each user, we train the model from the meta-learning perspective. Extensive experiments and a series of analyses have shown the superiority of our CCRS on both the recommendation and dialogue service. © 2022, CC BY-SA.

关键词： Recommender systems

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GoSum: Extractive Summarization of Long Documents by Reinforcement Learning and Graph Organized discourse state

arXiv

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arXiv 2022年

作者： Bian, Junyi Huang, Xiaodi Zhou, Hong Zhu, Shanfeng School of Computer Science Fudan University Shanghai200433 China School of Computing and Mathematics Charles Sturt University AlburyNSW2640 Australia Atypon Systems LLC United Kingdom Institute of Science and Technology for Brain-Inspired Intelligence Fudan University China Ministry of Education Shanghai200433 China MOE Frontiers Center for Brain Science Fudan University Shanghai200433 China Zhangjiang Fudan International Innovation Center Shanghai200433 China Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai200433 China

Extracting summaries from long documents can be regarded as sentence classification using the structural information of the documents. How to use such structural information to summarize a document is challenging. In this paper, we propose GoSum, a novel graph and reinforcement learning based extractive model for long-paper summarization. In particular, GoSum encodes sentence states in reinforcement learning by building a heterogeneous graph for each input document at different discourse levels. An edge in the graph reflects the discourse hierarchy of a document for restraining the semantic drifts across section boundaries. We evaluate GoSum on two datasets of scientific articles summarization: PubMed and arXiv. The experimental results have demonstrated that GoSum achieve state-of-the-art results compared with strong baselines of both extractive and abstractive models. The ablation studies further validate that the performance of our GoSum benefits from the use of discourse information. Copyright © 2022, The Authors. All rights reserved.

关键词： Reinforcement learning

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Drug3D-DTI: Improved Drug-target Interaction Prediction by Incorporating Spatial information of Small Molecules

Drug3D-DTI: Improved Drug-target Interaction Prediction by I...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Zhirui Liao Xiaodi Huang Hiroshi Mamitsuka Shanfeng Zhu School of Computer Science Fudan University Shanghai China Institute of Artificial Intelligence Biomedicine Nanjing University Nanjing China School of Computing Mathematics and Engineering Charles Sturt University Albury NSW Australia Bioinformatics Center Institute for Chemical Research Kyoto University Uji Kyoto Japan Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) Ministry of Education China MOE Frontiers Center for Brain Science Fudan University Shanghai China Zhangjiang Fudan International Innovation Center Shanghai China Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai China

ISBN: (纸本)9781665429825

A number of machine learning (ML) approaches for drug discovery have been available that rely only on sequential (1D) and planar (2D) information without effectively using the 3D information for generating features of drugs. However, 3D information of small molecules can reflect relative position of atoms more directly, which affects molecular properties. In this work, we present a new deep learning model called Drug3D-DTI for drug-target interaction prediction. Drug3D-DTI takes advantage of molecular spatial information, i.e., atom proximity in three-dimensional (3D) structures. We comprehensively evaluated the performance of Drug3D-DTI on two datasets with two tasks of regression and classification. In particular, we compared Drug3D-DTI with several existing methods including the two cutting-edge methods for compound-protein interaction prediction. From the experimental results, Drug3D-DTI clearly outperformed other methods under all settings. Further, this performance improvement was validated by ablation experiments and a case study. The implementation of Drug3D-DTI is available at (https://***/zhiruiliao/Drug3D-DTI).

关键词： Drugs Proteins Deep learning Solid modeling Three-dimensional displays Conferences Predictive models

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KADEL: Knowledge-Aware Denoising Learning for Commit Message Generation

arXiv

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arXiv 2024年

作者： Tao, Wei Zhou, Yucheng Wang, Yanlin Zhang, Hongyu Wang, Haofen Zhang, Wenqiang Shanghai Engineering Research Center of AI and Robotics Academy for Engineering and Technology Fudan University Shanghai China State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau China School of Software Engineering Sun Yat-sen University Guangdong Zhuhai519082 China School of Big Data and Software Engineering Chongqing University Chongqing China College of Design and Innovation Tongji University Shanghai China Engineering Research Center of AI and Robotics Ministry of Education Academy for Engineering and Technology Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University 220 Handan Road Shanghai200433 China

Commit messages are natural language descriptions of code changes, which are important for software evolution such as code understanding and maintenance. However, previous methods are trained on the entire dataset without considering the fact that a portion of commit messages adhere to good practice (i.e., good-practice commits), while the rest do not. On the basis of our empirical study, we discover that training on good-practice commits significantly contributes to the commit message generation. Motivated by this finding, we propose a novel knowledge-aware denoising learning method called KADEL. Considering that good-practice commits constitute only a small proportion of the dataset, we align the remaining training samples with these good-practice commits. To achieve this, we propose a model that learns the commit knowledge by training on good-practice commits. This knowledge model enables supplementing more information for training samples that do not conform to good practice. However, since the supplementary information may contain noise or prediction errors, we propose a dynamic denoising training method. This method composes a distribution-aware confidence function and a dynamic distribution list, which enhances the effectiveness of the training process. Experimental results on the whole MCMD dataset demonstrate that our method overall achieves state-of-the-art performance compared with previous methods. © 2024, CC BY.

关键词： Sampling

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Giant power output in lead-free ferroelectrics by shock-induced phase transition

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Physical Review Materials 2019年第3期3卷 035401-035401页

作者： Zhipeng Gao Wei Peng Bin Chen Simon A. T. Redfern Ke Wang Baojin Chu Qiang He Yi Sun Xuefeng Chen Hengchang Nie Wen Deng Lingkong Zhang Hongliang He Genshui Wang Xianlin Dong National Key Laboratory of Shock Wave and Detonation Physics Institute of Fluid Physics China Academy of Engineering Physics Mianyang 621900 China CAS Key Laboratory of Inorganic Functional Materials and Devices Shanghai Institute of Ceramics Chinese Academy of Sciences Shanghai 200050 China Center for High Pressure Science and Technology Advanced Research Shanghai 201203 China Department of Earth Sciences University of Cambridge Cambridge CB2 3EQ United Kingdom State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing 100084 China Information and Quantum Physics University of Science and Technology of China Hefei 230026 China The State Key Lab of High Performance and Superfine Microstructure Shanghai Institute of Ceramics Chinese Academy of Sciences Shanghai 200050 China

The force-electric effect in ferroelectrics is characterized by the release of bound charge during pressure/shock-induced depolarization. In contrast to other electrical energy storage systems, the charge-storage/release by the force-electric effect of ferroelectrics is determined by polarization switching or polar-nonpolar phase transition. This offers a further set of options for materials design in the realm of energy conversion, especially for the high power density applications. Here, we report that a ferroelectric ceramic, Na0.5Bi0.5TiO3 (NBT), can generate a high power output (3.04×108W/kg) under shock compression, which is one of the highest values achieved by the force-electric effect. The in situ synchrotron x-ray diffraction studies reveal that this power output mainly arises from a polar-nonpolar phase transition (rhombohedral-orthorhombic). First-principles calculations show that this is a first-order phase transition that undergoes two-step structure changes. These results extend the application of the force-electric effect and are a key step in understanding the phase transition behaviors of NBT under high pressure.

关键词： Ferroelectricity Phase transitions Pressure effects

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Foundation PIT deformation measurement technique based on ground-based interferometric radar

Foundation PIT deformation measurement technique based on gr...

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IET International Radar Conference (IRC 2023)

作者： Changjun Wang Hanpu Zhou Jian Wang Jiake Gao Yunkai Deng Weiming Tian Beijing Building Research Institute Co. Ltd. of CSCEC Beijing 100076 People's Republic of China Radar Research Lab School of lnformation and Electronics Beijing lnstitute of Technology Beijing People's Republic of China Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing People's Republic of China Chongqing Innovation Center Beijing Institute of Technology People's Republic of China Advanced Technology Research Institute Beijing Institute of Technology Jinan 250300 People's Republic of China

ISBN: (数字)9781837240982

The deformation monitoring data of foundation pit is an important criterion for forecasting and strengthening measures in the field of building safety. During the construction period, the foundation pit will be affected by load, temperature change, random disturbance and other effects to produce deformation. Due to the complex deformation process of foundation pit, it is hard to accurately describe and separate the load trend deformation and elastic thermal deformation by mathematical expression. Excessive thermal deformation may cause cracks in the surrounding pavement and affect the judgment of load deformation. This paper first introduces the deformation measurement method of foundation pit based on differential interferometry technology using ground-based interferometric radar. Based on the obtained deformation type, the simulation verifies the separation effect of wavelet transform on different deformation trends and periodic components. Through the foundation pit deformation monitoring experiment of Tongzhou infrastructure project, the wavelet transform method is used to decompose the foundation pit deformation curve, and the extracted periodic component has good consistency with the temperature information.

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猕猴脑网络组图谱:包含分区、连接和组织学的多层面全新大脑地图

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Science Bulletin 2024年第14期69卷 2241-2259页

作者：陆玉恒崔玥曹龙董振伟程禄祺吴雯王昌硕刘新异刘有通张宝贵李德莹赵舶凯王海艳李开心马亮时维阳李雯马亚伟杜宗昌张佳琪熊辉罗娜刘妍妍侯肖逍韩景路孙洪吉蔡涛彭强冯琳清王骄健 George Paxinos 杨正宜樊令仲蒋田仔 Brainnetome Center Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China University of Chinese Academy of Sciences Beijing 100049China Henan Key Laboratory of Imaging and Intelligent Processing PLA Strategic Support Force Information Engineering UniversityZhengzhou 450001China Neuroscience Research Australia and The University of New South Wales Sydney NSW 2031Australia Key Laboratory for NeuroInformation of the Ministry of Education School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengdu 610054China State Key Laboratory of Primate Biomedical Research Institute of Primate Translational MedicineKunming University of Science and TechnologyKunming 650500China School of Mechanical and Power Engineering Harbin University of Science and TechnologyHarbin 150080China School of Life and Environmental Sciences Guilin University of Electronic TechnologyGuilin 541004China Sino-Danish College University of Chinese Academy of ScienceBeijing 100049China Research Center for Augmented Intelligence Zhejiang LabHangzhou 311100China Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital Yongzhou 425000China

The rhesus macaque(Macaca mulatta)is a crucial experimental animal that shares many genetic,brain organizational,and behavioral characteristics with humans.A macaque brain atlas is fundamental to biomedical and evolutionary ***,even though connectivity is vital for understanding brain functions,a connectivity-based whole-brain atlas of the macaque has not previously been *** this study,we created a new whole-brain map,the Macaque Brainnetome Atlas(MacBNA),based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI *** new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional *** parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained *** a demonstrative application,the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain *** resulting resource includes:(1)the thoroughly delineated Macaque Brainnetome Atlas(MacBNA),(2)regional connectivity profiles,(3)the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset(Brainnetome-8),and(4)multi-contrast MRI,neuronal-tracing,and histological images collected from a single *** can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and ***,it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.

关键词： Macaca mulatta Brain atlas Connectivity-based parcellation Diffusion MRI Cytoarchitecture Cross-species comparison

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Elastic and Efficient Virtual Network Provisioning for Cloud-Based Multi-tier Applications

Elastic and Efficient Virtual Network Provisioning for Cloud...

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International Conference on Parallel processing (ICPP)

作者： Meng Shen Ke Xu Fan Li Kun Yang Liehuang Zhu Lei Guan Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing Institute of Technology P. R. China Department of Computer Science Tsinghua University P. R. China School of Computer Science & Electronic Engineering University of Essex UK The ISN National Key Lab XiDian University P. R. China School of Management & Economics Beijing Institute of Technology P. R. China

ISBN: (纸本)9781467375887

The multi-tier architecture is prevalently adopted by cloud applications, such as the three-tier web application. It is highly desirable for both tenants and providers to provide virtual networks in an efficient and elastic way, where tenant applications can automatically scale in or out with varying workloads and providers can accommodate as many requests as possible in the underlying network. However, due to potential conflicts between efficiency and elasticity, it is challenging to achieve these two goals simultaneously in abstracting tenant requirements and designing corresponding provisioning algorithms. In this paper, we propose an efficient and elastic virtual network provisioning solution called Easy Alloc, which is comprised of an elasticity-aware abstraction model and a virtual network provisioning algorithm. To accurately capture the tenant requirement and maintain the provisioning simplicity for providers, the elasticity-aware model enables two types of decoupling, i.e., Always-on VMs for normal load and on-demand VMs for dynamic scaling, and the bandwidth requirement of each VM for intra- and inter-tier communications. Then we formulate the virtual network provisioning as an overhead minimization problem, where the objective simultaneously considers the bandwidth and elasticity overhead. Due to the NP-completeness of this problem, we leverage two heuristics, slot reservation and tier iteration, to obtain an efficient algorithm. Extensive simulation results show that compared with a typical elasticity-agnostic method under a heavy load, Easy Alloc enables a 9% increase of request acceptance rate and a 16.8% improvement of the successful extension rate. To the best of our knowledge, this is the first work targeting at the elastic virtual network provisioning.

关键词： Bandwidth Elasticity Cloud computing Algorithm design and analysis Load modeling Resource management

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