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MXenes@Te as a composite material for high-performance aluminum batteries

Science China Materials 2022年第1期65卷 85-94页

作者： Xiaogeng Huo Xiaoxu Wang Jianling Li Bao Zhang Yu Zhang Te Qin Feiyu Kang State Key Laboratory of Advanced Metallurgy School of Metallurgical and Ecological EngineeringUniversity of Science and Technology BeijingBeijing 100083China Beijing computing center Beijing Academy of Science and TechnologyBeijing 100094China Laboratory of Advanced Materials School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China

The emerging two-dimensional(2D)materials,MXenes,play an important role in various fields of energy storage and exhibit excellent electrochemical ***,we prepared few-layered MXenes(F-Ti_(3)C_(2)T_(x))and loaded Te on the surface of F-Ti_(3)C_(2)T_(x) by using a simple hightemperature evaporation *** addition,the electrochemical performance of the aluminum battery with F-Ti_(3)C_(2)T_(x) as support material was *** initial charge/discharge specific capacities are 987/1096mAh g^(-1)at 0.2Ag^(-1).An obvious discharge voltage plateau of about 1.3V appears at various current *** specific capacity is about 258mAh g^(-1)with MXenes@Te as the active material in the aluminum battery,which benefits from the excellent electronic conductivity of the MXenes and their 2D layered *** functional theory calculations were carried out to explore the ***_(3)C_(2)O_(2)@Te is more inclined to adsorb[AlCl_(4)]^(-) than Ti_(3)C_(2)O_(2).Furthermore,the valence change behavior of element Te was studied by using thermodynamic calculation(FactSage 7.1).X-ray photoelectron spectroscopy results show that when the battery is fully charged to 2.4V element Te and Ti ions(Ti^(3+),Ti^(2+))are oxidized to Te^(4+)and Ti^(4+).In contrast to the charging process,the high-valence Te^(4+)and Ti^(4+)are reduced again during *** Te is reduced to lower-valence Te^(2-)when the discharge voltage is lower than 0.6 V,and a higher charge voltage(2.56 V)is required for Te to be oxidized to Te^(6+).

关键词： MXenes@Te aluminum batteries specific capacity density functional theory

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A riemannian exponential augmented lagrangian method for computing the projection robust Wasserstein distance 23

A riemannian exponential augmented lagrangian method for com...

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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Bo Jiang Ya-Feng Liu Ministry of Education Key Laboratory of NSLSCS School of Mathematical Sciences Nanjing Normal University Nanjing China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

Projection robust Wasserstein (PRW) distance is recently proposed to efficiently mitigate the curse of dimensionality in the classical Wasserstein distance. In this paper, by equivalently reformulating the computation of the PRW distance as an optimization problem over the Cartesian product of the Stiefel manifold and the Euclidean space with additional nonlinear inequality constraints, we propose a Riemannian exponential augmented Lagrangian method (REALM) for solving this problem. Compared with the existing Riemannian exponential penalty-based approaches, REALM can potentially avoid too small penalty parameters and exhibit more stable numerical performance. To solve the subproblems in REALM efficiently, we design an inexact Riemannian Barzilai-Borwein method with Sinkhorn iteration (iRBBS), which selects the stepsizes adaptively rather than tuning the step-sizes in efforts as done in the existing methods. We show that iRBBS can return an ε-stationary point of the original PRW distance problem within O(ε-3) iterations, which matches the best known iteration complexity result. Extensive numerical results demonstrate that our proposed methods outperform the state-of-the-art solvers for computing the PRW distance.

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The positive mass theorem for asymptotically flat manifolds with isolated conical singularities Dedicated to Professor Weiping Zhang on the Occasion of His 60th Birthday

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Science China Mathematics 2025年第7期 1671-1686页

作者： Xianzhe Dai Yukai Sun Changliang Wang Department of Mathematics University of CaliforniaSanta Barbara Key Laboratory of Pure and Applied Mathematics School of Mathematical SciencesPeking University School of Mathematical Sciences and Institute for Advanced Study Key Laboratory of Intelligent Computing and Applications (Ministry of Education)Tongji University

We prove the positive mass theorem for asymptotically flat(AF for short) manifolds with finitely many isolated conical singularities. We do not impose the spin condition. Instead, we use the conformal blow-up techniqu...

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Multikernel:Operating system solution to generalized functional safety

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Security and Safety 2023年第2期2卷 30-43页

作者： Yijing Song Huasheng Dai Jinhu Jiang Weihua Zhang School of Computer Science Fudan UniversityShanghai 200433China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125China Institute of Big Data Fudan UniversityShanghai 200433China Parallel Processing Institute Fudan UniversityShanghai 200433China

With the trend of digitalization,intelligence,and networking sweeping the world,functional safety and cyber security are increasingly intertwined and overlapped,evolving into the issue of generalized functional *** system reliability technology and network defense technology cannot provide quantifiable design implementation theories and *** the cornerstone of software systems,operating systems in particular are in need of efficient safety *** DHR architecture is a mature and comprehensive solution,and it is necessary to implement an OS-level DHR architecture,for which the multi-kernel operating system is a good *** multi-kernel operating system takes the kernel as the processing scenario element and constructs redundancy,heterogeneity,and dynamism on the kernel,so it has the generalized robustness of the DHR *** article analyzes the significance and requirements of OS-level DHR architecture,and systematically explains how the multi-kernel operating system responds to the requirements of OS-level DHR architecture by analyzing the technical routes of multi-kernel operating systems and develops an operating system solution idea for the generalized functionally safety.

关键词： Metaverse New infrastructure Security base Highly trusted network Trusted identiry Trusted circulation of data

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A Versatile Framework for Multi-scene Person Re-identification

arXiv

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arXiv 2024年

作者： Zheng, Wei-Shi Yan, Junkai Peng, Yi-Xing The School of Computer Science and Engineering Sun Yat-sen University Guangzhou510275 China The Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education 510006 China

Person Re-identification (ReID) has been extensively developed for a decade in order to learn the association of images of the same person across non-overlapping camera views. To overcome significant variations between images across camera views, mountains of variants of ReID models were developed for solving a number of challenges, such as resolution change, clothing change, occlusion, modality change, and so on. Despite the impressive performance of many ReID variants, these variants typically function distinctly and cannot be applied to other challenges. To our best knowledge, there is no versatile ReID model that can handle various ReID challenges at the same time. This work contributes to the first attempt at learning a versatile ReID model to solve such a problem. Our main idea is to form a two-stage prompt-based twin modeling framework called VersReID. Our VersReID firstly leverages the scene label to train a ReID Bank that contains abundant knowledge for handling various scenes, where several groups of scene-specific prompts are used to encode different scene-specific knowledge. In the second stage, we distill a V-Branch model with versatile prompts from the ReID Bank for adaptively solving the ReID of different scenes, eliminating the demand for scene labels during the inference stage. To facilitate training VersReID, we further introduce the multi-scene properties into self-supervised learning of ReID via a multi-scene prioris data augmentation (MPDA) strategy. Through extensive experiments, we demonstrate the success of learning an effective and versatile ReID model for handling ReID tasks under multi-scene conditions without manual assignment of scene labels in the inference stage, including general, low-resolution, clothing change, occlusion, and cross-modality scenes. Codes and models are available at https://***/iSEE-laboratory/VersReID. Copyright © 2024, The Authors. All rights reserved.

关键词： Cameras

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A Survey on Neural Machine Translation Applied to Sign Language Generation 3

A Survey on Neural Machine Translation Applied to Sign Langu...

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3rd International Conference on Applied Machine Learning, ICAML 2021

作者： Zhang, Yue Cao, Lihong State Key Laboratory of Media Convergence and Communication Communication University of China Beijing100024 China Neuroscience and Intelligent Media Institute Communication University of China Beijing100024 China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi214125 China

ISBN: (纸本)9781665421256

Sign languages are the primary medium of communication for the deaf and hearing-impaired community, and the number of human beings with hearing impairment is increasing at a rapid rate. There is a signifîcant communication barrier between the hearing-impaired and normal-hearing communities. One solution to this issue is to offload the effort of text imderstanding for the deaf and hearing-impaired community in the form of Sign Language Generation (SLG). In this paper, first of all, we systematically review the mainstream Neural Machine Translation (NMT)based SLG approaches. Specifically, according to their model architectures, we divide them into two categories: the Recurrent Neural Networks (RNNs)-based and Transformer-based models, and discuss their advantages and limitations. Next, we introduce the existing publicly available datasets and the data pre pros ses sing methods in the field of SLG. Then, we summarize the performance evaluation methods for NMT-based SLG models. Finally, we offer two possible future research directions for better development in the field of SLG. © 2021 IEEE

关键词： Neural machine translation

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Integrating Artificial Intelligence into Operating Systems: A Comprehensive Survey on Techniques, Applications, and Future Directions

arXiv

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arXiv 2024年

作者： Zhang, Yifan Zhao, Xinkui Li, Ziying Yin, Jianwei Zhang, Lufei Chen, Zuoning School of Software Technology Zhejiang University Zhejiang Ningbo315048 China College of Computer Science and Technology Zhejiang University Zhejiang Hangzhou310058 China State Key Laboratory of Mathematical Engineering and Advanced Computing Jiangsu Wuxi214125 China Chinese Academy of Engineering Beijing100088 China

In the era of the Internet of Everything, operating systems (OSs) face unprecedented challenges posed by an evolving application landscape and increasingly heterogeneous hardware ecosystems. This shift toward increasingly dynamic and unpredictable operational contexts presents significant challenges for both OS developers and users. Against this backdrop, the fusion of Artificial Intelligence (AI) with Operating Systems emerges as a critical frontier for innovation. This survey delves into the intricate interplay between AI and OSs, illustrating how existing OS mechanisms combined with AI significantly elevate the performance, security, and efficiency of modern operating systems. We investigate a range of AI methodologies applied to optimize core OS functionalities and clarify the correlation to related studies. Our analysis touches on the existing hurdles and prospective avenues in this interdisciplinary domain, underscoring the imperative for robust and seamless integration of AI capabilities into OS architectures. Through an examination of illustrative case studies and cutting-edge developments, we offer a thorough review of the current status of AI-OS integration, accentuating its pivotal role in steering the evolution of advanced computing paradigms. We also envision the promising prospects of Intelligent Operating Systems, debating how groundbreaking OS designs will usher in novel possibilities and highlight the central role that AI will assume in propelling these next-generation systems forward. This forward-thinking outlook illuminates the profound influence of AI on the foundational elements of computing, heralding the advent of a new epoch characterized by intelligent, self-adapting, and highly adaptive software ecosystems. Copyright © 2024, The Authors. All rights reserved.

关键词： Artificial intelligence

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Revealing distribution discrepancy by sampling transfer in unlabeled data 24

Revealing distribution discrepancy by sampling transfer in u...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Zhilin Zhao Longbing Cao Xuhui Fan Wei-Shi Zheng School of Computing Macquarie University Australia and School of Computer Science and Engineering Sun Yat-sen University China School of Computing Macquarie University Australia School of Computer Science and Engineering Sun Yat-sen University China and Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education China

ISBN: (纸本)9798331314385

There are increasing cases where the class labels of test samples are unavailable, creating a significant need and challenge in measuring the discrepancy between training and test distributions. This distribution discrepancy complicates the assessment of whether the hypothesis selected by an algorithm on training samples remains applicable to test samples. We present a novel approach called Importance Divergence (I-Div) to address the challenge of test label unavailability, enabling distribution discrepancy evaluation using only training samples. I-Div transfers the sampling patterns from the test distribution to the training distribution by estimating density and likelihood ratios. Specifically, the density ratio, informed by the selected hypothesis, is obtained by minimizing the Kullback-Leibler divergence between the actual and estimated input distributions. Simultaneously, the likelihood ratio is adjusted according to the density ratio by reducing the generalization error of the distribution discrepancy as transformed through the two ratios. Experimentally, I-Div accurately quantifies the distribution discrepancy, as evidenced by a wide range of complex data scenarios and tasks.

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Pre-Equalization Aided Grant-Free Massive Access in Massive MIMO System

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IEEE Transactions on Vehicular Technology 2025年第6期74卷 9979-9984页

作者： Wang, Yueqing Mei, Yikun Gao, Zhen Wan, Ziwei Ning, Boyu Mi, De Muhaidat, Sami School of Information and Electronics Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology MIIT Key Laboratory of Complex-Field Intelligent Sensing Beijing100081 China Yangtze Delta Region Academy Jiaxing314019 China Beijing Institute of Technology Advanced Technology Research Institute Jinan250307 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Birmingham City University School of Computing and Digital Technology BirminghamB55JU United Kingdom Khalifa University KU 6 G Research Center Department of Computer and Information Engineering Abu Dhabi United Arab Emirates

The spatial diversity and multiplexing advantages of massive multi-input-multi-output (mMIMO) can significantly improve the capacity of massive non-orthogonal multiple access (NOMA) in machine type communications. However, state-of-the-art grant-free massive NOMA schemes for mMIMO systems require accurate estimation of random access channels to perform activity detection and the following coherent data demodulation, which suffers from excessive pilot overhead and access latency. To address this, we propose a pre-equalization aided grant-free massive access scheme for mMIMO systems, where an iterative detection scheme is conceived. Specifically, the base station (BS) firstly activates one of its antennas (i.e., beacon antenna) to broadcast a beacon signal, which facilitates the user equipment (UEs) to perform downlink channel estimation and pre-equalize the uplink random access signal with respect to the channels associated with the beacon antenna. During the uplink transmission stage, the BS detects UEs' activity and data by using the proposed iterative detection algorithm, which consists of three modules: coarse data detection (DD), data-aided channel estimation (CE), and fine DD. In the proposed algorithm, the joint activity and DD is firstly performed based on the signals received by the beacon antenna. Subsequently, the DD is further refined by iteratively performing data-aided CE module and fine DD module using signals received by all BS antennas. Our simulation results demonstrate that the proposed scheme outperforms state-of-the-art mMIMO-based grant-free massive NOMA schemes with the same access latency. © 1967-2012 IEEE.

关键词： Channel estimation

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Using deep learning to denoise and detect gravitational waves

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Physical Review D 2024年第6期110卷 063010页

作者： CunLiang Ma ShuoQiu Li Zhoujian Cao Mingzhen Jia School of Information Engineering Jiangxi Province Key Laboratory of Multidimensional Intelligent Perception and Control Ganzhou 341000 China Institute of Applied Mathematics School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced Study

We have upgraded the MSNRnet framework to MSNRnet-2 by refining the training strategy, drawing inspiration from generative adversarial networks for data generation. The astrophysical discrimination network enforces constraints on the denoising output, ensuring that the “signal+noise” case conforms to an astrophysical-origin shape, while limiting the denoised output of the “noise” case to a nonastrophysical origin shape. This improvement has led to enhanced denoising and astrophysical discrimination performance in most scenarios. For the analysis of confident events, we observed a 1.3% increase in the detection rate. Remarkably, no false triggers were generated during the analysis of the data jointly processed by the Hanford and Livingston interferometers in O3b (about five months of data). These findings suggest that the denoising-discrimination-matched filtering framework holds promising potential for gravitational wave searches in the future.

关键词： Classical black holes General relativity Gravitational waves

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