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Facile Fabrication of Ag Nanocrystals Encapsulated in Nitrogen-doped Fibrous Carbon as an Efficient Catalyst for Lithium Oxygen Batteries

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Energy & Environmental Materials 2021年第2期4卷 239-245页

作者： Lili Liu Tianyi Ma Weiwei Fang Yuqing Liu Kostantin Konstantinov Jiazhao Wang Hua-Kun Liu School of Energy and Institute for Advanced Materials Nanjing Tech UniversityJiangsu ProvinceNanjing 211816China Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources Jiangsu Provincial Key Lab for the Chemistry and Utilization of Agro-Forest BiomassCollege of Chemical EngineeringNanjing Forestry University(NFU)Nanjing 210037China State Key Laboratory of Electronic Thin Film and Integrated Devices University of Electronic Science and Technology of ChinaChengdu 610054China Intelligent Polymer Research Institute University of WollongongWollongong NSW 2522Australia Institute for Superconducting and Electronic Materials University of WollongongWollongong NSW 2522Australia

A facile synthesis of Ag nanocrystals encapsulated in nitrogen-doped carbon fiber(NCF)is proposed,based on the simultaneous reaction between pyrrole and Ag^(+)ions in an aqueous solvent followed by a heat *** as-prepared Ag/NCF demonstrated superior catalytic behavior toward ORR and *** improved cycling stability,a much lower discharge/charge gap of 0.89 V(vs Li/Li^(+))compared with 1.38 V for NCF cathode with a fixed capacity of 500 m Ah g^(-1)was obtained in lithium oxygen *** introduction of Ag crystals into NCF facilitates the oxygen reduction reaction/oxygen evolution reaction kinetics.X-ray diffraction analysis coupled with Raman spectroscopy confirmed that Ag/NCF cathode could reversibly catalyze Li_(2)O_(2)formation and *** NCF matrix offers a conductive network to realize rapid mass transfer and the encapsulated Ag nanocrystals supplied effective catalytic active *** combined action between both contributes to the superior electrocatalytic performance.

关键词： Ag nanocrystals Li_(2)O_(2) Li–O_(2)batteries N-carbon fiber overpotential

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A Low SAR, Small size, High gain, Circularly polarized Antenna for Wearable Application 2

A Low SAR, Small size, High gain, Circularly polarized Anten...

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2020 2nd International Conference on Artificial Intelligence Technologies and Application, ICAITA 2020

作者： Wang, Chao Zhang, Liang Cheng, Yi Li, XueMei Wu, Xianliang Key Lab of Ministry of Education of Intelligent Computing and Signal Processing Anhui University Hefei Anhui230601 China AnHui Province Key Laboratory of Simulation and Design for Electronic Information System Hefei Normal University Hefei Anhui230601 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. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Wearable antennas

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Multi-granulation variable precision rough set based on limited tolerance relation

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2021年第3期83卷 63-74页

作者： Wan, Renxia Yao, Yonghong Kumar, Hussain School of Mathematics and Information Science North Minzu University Ningxia750021 China HongYang Institute for Big Data in Health Fuzhou Fujian350028 China School of Mathematical Sciences Tiangong University Tianjin300387 China The Key Laboratory of Intelligent Information and Data Processing of NingXia Province North Minzu University and Health Big Data Research Institute of North Minzu University Yinchuan750021 China Machine vision and pattern recognition lab University of Regina ReginaSKS4S0A2 Canada

In this paper, the combination of the variable precision rough set and the limited tolerance relation under multi-granularity is explored. As an extension of rough set model, Multi-granularity variable precision limited tolerance rough set model is con-structed. Properties of upper and lower approximation operator and detailed structure of object class through threshold are discussed. Theoretical proofs are given to show the rationality and superiority of the proposed model. © 2021, Politechnica University of Bucharest. All rights reserved.

关键词： Granulation

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A Brain-To-Brain Interface with a Flexible Neural Probe for Mouse Turning Control by Human Mind 22

A Brain-To-Brain Interface with a Flexible Neural Probe for ...

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22nd International Conference on Solid-State Sensors, Actuators and Microsystems, Transducers 2023

作者： Ye, Yifei Wang, Zhenyu Tian, Ye Wang, Han Zhou, Cunkai Hu, Honglin Zhou, Ting Zhou, Zhitao Wei, Xiaoling Zhao, Jianlong Tao, Tiger H. Sun, Liuyang State Key Laboratory Of Transducer Technology Shanghai Institute Of Microsystem And Information Technology Chinese Academy Of Sciences Shanghai China Intelligent Communication Lab Shanghai Advanced Research Institute Chinese Academy Of Sciences Shanghai China 2020 X-Lab Shanghai Institute Of Microsystem And Information Technology Chinese Academy Of Sciences Shanghai China School Of Graduate Study University Of Chinese Academy Of Sciences Beijing China School Of Microelectronics Shanghai University Shanghai China Center Of Materials Science And Optoelectronics Engineering University Of Chinese Academy Of Sciences Beijing China School Of Physical Science And Technology ShanghaiTech University Shanghai China Center For Excellence In Brain Science And Intelligence Technology Chinese Academy Of Sciences Shanghai China Jiangxi Nanchang China Guangdong Institute Of Intelligence Science And Technology Zhuhai Guangdong Hengqin China Tianqiao And Chrissy Chen Institute For Translational Research Shanghai China

ISBN: (纸本)9784886864352

We proposed a brain-to-brain interface (B2BI) that enabled effective control of mouse turning behavior by human mind using an implantable, ultra-flexible neural probe. The neural probe was capable of writing in neural signals to the mouse brain, with effective electrical stimulation observed at a low current of 5 μA. Additionally, a wireless EEG device was developed for the remote transmission of human brain signals, which were decoded by the canonical correlation analysis (CCA) method with an accuracy rate of up to 98.6%. These results demonstrate the potential of B2BI technology to enable communication and control between humans and animals. © 2023 IEEJ.

关键词： Brain computer interface Brain-to-brain interface Canonical correlation analysis Flexible probe

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Author classification using transfer learning and predicting stars in co-author networks

Author classification using transfer learning and predicting...

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作者： Abbasi, Rashid Kashif Bashir, Ali Chen, Jianwen Mateen, Abdul Piran, Jalil Amin, Farhan Luo, Bin School of Information and Communication Engineering University of Electronics Science and Technology of China Chengdu China Department of Computing and Mathematics Manchester Metropolitan University Manchester United Kingdom Department of Computer Science Federal Urdu University of Arts Science and Technology Islamabad Pakistan Computer Engineering Department Sejong University Yeungnam Korea Republic of Department of Information and Communication engineering Yeungnam University Yeungnam Korea Republic of Key Lab of Intelligent Computing and Signal Processing of MOE & School of Computer and Technology Anhui University China

The vast amount of data is key challenge to mine a new scholar that is plausible to be star in the upcoming period. The enormous amount of unstructured data raise every year is infeasible for traditional learning;consequently, we need a high quality of preprocessing technique to expand the performance of traditional learning. We have persuaded a novel approach, Authors classification algorithm using Transfer Learning (ACTL) to learn new task on target area to mine the external knowledge from the source domain. Comprehensive experimental outcomes on real-world networks showed that ACTL, Node-based Influence Predicting Stars, Corresponding Authors Mutual Influence based on Predicting Stars, and Specific Topic Domain-based Predicting Stars enhanced the node classification accuracy as well as predicting rising stars to compared with contemporary baseline methods. © 2020 John Wiley & Sons Ltd

关键词： Stars

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Article Reranking by Memory-Enhanced key Sentence Matching for Detecting Previously Fact-Checked Claims

arXiv

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arXiv 2021年

作者： Sheng, Qiang Cao, Juan Zhang, Xueyao Li, Xirong Zhong, Lei Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China Key Lab of Data Engineering and Knowledge Engineering Renmin University of China China

False claims that have been previously fact-checked can still spread on social media. To mitigate their continual spread, detecting previously fact-checked claims is indispensable. Given a claim, existing works retrieve fact-checking articles (FC-articles) for detection and focus on reranking candidate articles in the typical two-stage retrieval framework. However, their performance may be limited as they ignore the following characteristics of FC-articles: (1) claims are often quoted to describe the checked events, providing lexical information besides semantics;and (2) sentence templates to introduce or debunk claims are common across articles, providing pattern information. In this paper, we propose a novel reranker, MTM (Memoryenhanced Transformers for Matching), to rank FC-articles using key sentences selected using event (lexical and semantic) and pattern information. For event information, we propose to finetune the Transformer with regression of ROUGE. For pattern information, we generate pattern vectors as a memory bank to match with the parts containing patterns. By fusing event and pattern information, we select key sentences to represent an article and then predict if the article fact-checks the given claim using the claim, key sentences, and patterns. Experiments on two real-world datasets show that MTM outperforms existing methods. Human evaluation proves that MTM can capture key sentences for explanations. The code and the dataset are at https://***/ICTMCG/MTM. © 2021, CC BY-SA.

关键词： Semantics

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CASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic Response Generation

arXiv

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arXiv 2022年

作者： Zhou, Jinfeng Zheng, Chujie Wang, Bo Zhang, Zheng Huang, Minlie The CoAI Group DCST Institute for Artificial Intelligence State Key Lab of Intelligent Technology and Systems China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China College of Intelligence and Computing Tianjin University Tianjin China

Empathetic conversation is psychologically supposed to be the result of conscious alignment and interaction between the cognition and affection of empathy. However, existing empathetic dialogue models usually consider only the affective aspect or treat cognition and affection in isolation, which limits the capability of empathetic response generation. In this work, we propose the CASE model for empathetic dialogue generation. It first builds upon a commonsense cognition graph and an emotional concept graph and then aligns the user's cognition and affection at both the coarse-grained and fine-grained levels. Through automatic and manual evaluation, we demonstrate that CASE outperforms state-of-the-art baselines of empathetic dialogues and can generate more empathetic and informative responses. © 2022, CC BY.

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Modulating p-type doping of two-dimensional material palladium diselenide

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Nano research 2024年第4期17卷 3232-3244页

作者： Jiali Yang Yu Liu En-Yang Wang Jinbo Pang Shirong Huang Thomas Gemming Jinshun Bi Alicja Bachmatiuk Hao Jia Shu-Xian Hu Chongyun Jiang Hong Liu Gianaurelio Cuniberti Weijia Zhou Mark H Rümmeli Institute for Advanced Interdisciplinary Research(iAIR) University of JinanJinan 250022China Institute for Materials Chemistry Leibniz Institute for Solid State and Materials Research Dresden(IFW Dresden)20 Helmholtz StrasseDresden 01069Germany State Key Lab of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China College of Energy Soochow Institute for Energy and Materials Innovations Soochow UniversitySuzhou 215006China Key Laboratory of Advanced Carbon Materials and Wearable Energy Technologies of Jiangsu Province Soochow UniversitySuzhou 215006China School of Integrated Circuits University of Chinese Academy of SciencesBeijing 101408China Institute of Microelectronics of Tianjin Binhai New Area Tianjin 300451China Institute of Microelectronics Chinese Academy of SciencesBeijing 100029China Lukasiewicz Research Network PORT Polish Center for Technology DevelopmentStablowicka 147Wroclaw 54-066Poland School of Mathematics and Physics University of Science and Technology BeijingBeijing 100083China College of electronic information and optical engineering Nankai UniversityTianjin 300350China Centre of Polymer and Carbon Materials Polish Academy of SciencesM.Curie Sklodowskiej 34Zabrze 41-819Poland Center for Energy and Environmental Technologies VŠB-Technical University of Ostrava17.Listopadu 15Ostrava 70833Czech Republic State Key Laboratory of Crystal Materials Center of Bio&Micro/Nano Functional MaterialsShandong UniversityJinan 250100China Dresden Center for Computational Materials Science Technische Universität DresdenDresden 01062Germany Dresden Center for Intelligent Materials(GCL DCIM) Technische Universität DresdenDresden 01062Germany Institute for Materials Science and Max Bergmann Center of Biomaterials Technische Universität DresdenDresden 01069Germany Center for Advancing Electronics Dresden Technische Universität DresdenDresden 01069Germany

The van der Waals heterostructures have evolved as novel materials for complementing the Si-based semiconductor ***-10 noble metal dichalcogenides(e.g.,PtS_(2),PtSe_(2),PdS_(2),and PdSe_(2))have been listed into two-dimensional(2D)materials toolkit to assemble van der Waals *** them,PdSe_(2) demonstrates advantages of high stability in air,high mobility,and wide tunable ***,the regulation of p-type doping of PdSe_(2) remains unsolved problem prior to fabricating p–n junction as a fundamental platform of semiconductor ***,a quantitative method for the controllable doping of PdSe_(2) is yet to be *** this study,the doping level of PdSe_(2) was correlated with the concentration of Lewis acids,for example,SnCl_(4),used for *** the transfer characteristics,the threshold voltage(the gate voltage corresponding to the minimum drain current)increased after SnCl_(4) soaking ***_(2) transistors were soaked in SnCl_(4) solutions with five different *** threshold voltages from the as-obtained transfer curves were extracted for linear fitting to the threshold voltage versus doping concentration correlation *** study provides in-depth insights into the controllable p-type doping of PdSe_(2).It may also push forward the research of the regulation of conductivity behaviors of 2D materials.

关键词： two-dimensional(2D)materials Lewis acid treatment p-type doping field-effect transistors transfer characteristic

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HTtext: A TextCNN-based pre-silicon detection for hardware Trojans

HTtext: A TextCNN-based pre-silicon detection for hardware T...

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IEEE International Conference on Big Data and Cloud computing (BdCloud)

作者： Yi Xu Zhenyi Chen Binhong Huang Ximeng Liu Chen Dong College of Computer and Data Science Fuzhou University Fuzhou China University of South Floride Tampa USA Key Lab of Information Security of Network Systems (Fuzhou University) Fujian Key Laboratory of Network Computing and Intelligent Information Processing (Fuzhou University)

With the advent of the intelligence era, the usage and investment for chips have risen year by year, causing the demand for chip security. Machine learning (ML) analysis has made progress as a pre-silicon hardware Trojan (HT) detection technology. Whereas the performance of existing methods almost relies on the accuracy of multi-feature representation, moreover, it is difficult to extract features manually and easily cause unstable classifier performance (namely uncertainty). In this paper, an automatic feature extraction detecting model is first proposed, named HTtext, which generates simple path sentences from chip netlists and employs TextCNN, a deep learning algorithm, to distinguish HT circuits. The pre-training for TextCNN only uses the automatic single-feature calculation to avoid the uncertainty problem. Additionally, the model can obtain non-repetitive HT component information expression, which satisfies the stable detection performance. To measure the efficiency and balance of the model, the paper proposes the concept of the Stability Efficiency Index (SEI). In the experimental results for the benchmark netlists, not only the average accuracy (ACC) in TextCNN is as high as 99.26%, but also its SEI value ranks first in all comparison classifiers, which proves that the proposed HTtext model has high stability in generality.

关键词： Ports (computers) Semiconductor device measurement Uncertainty Stability criteria Feature extraction Hardware Circuit stability

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A Unified Generalization Analysis of Re-Weighting and Logit-Adjustment for Imbalanced Learning

arXiv

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arXiv 2023年

作者： Wang, Zitai Xu, Qianqian Yang, Zhiyong He, Yuan Cao, Xiaochun Huang, Qingming SKLOIS Institute of Information Engineering CAS China School of Cyber Security University of Chinese Academy of Sciences China Key Lab. of Intelligent Information Processing Institute of Computing Tech. CAS China School of Computer Science and Tech. University of Chinese Academy of Sciences China Alibaba Group China School of Cyber Science and Tech. Shenzhen Campus Sun Yat-sen University China BDKM University of Chinese Academy of Sciences China

Real-world datasets are typically imbalanced in the sense that only a few classes have numerous samples, while many classes are associated with only a few samples. As a result, a naïve ERM learning process will be biased towards the majority classes, making it difficult to generalize to the minority classes. To address this issue, one simple but effective approach is to modify the loss function to emphasize the learning on minority classes, such as re-weighting the losses or adjusting the logits via class-dependent terms. However, existing generalization analysis of such losses is still coarse-grained and fragmented, failing to explain some empirical results. To bridge this gap, we propose a novel technique named data-dependent contraction to capture how these modified losses handle different classes. On top of this technique, a fine-grained generalization bound is established for imbalanced learning, which helps reveal the mystery of re-weighting and logit-adjustment in a unified manner. Furthermore, a principled learning algorithm is developed based on the theoretical insights. Finally, the empirical results on benchmark datasets not only validate the theoretical results but also demonstrate the effectiveness of the proposed method. © 2023, CC BY.

关键词： Learning algorithms

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