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An intrinsically self-healing and anti-freezing molecular chains induced polyacrylamide-based hydrogel electrolytes for zinc manganese dioxide batteries

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Journal of Energy Chemistry 2024年第2期89卷 565-578,I0013页

作者： Haiyang Liao Wenzhao Zhong Chen Li Jieling Han Xiao Sun Xinhui Xia Ting Li Abolhassan Noori Mir F.Mousavi Xin Liu Yongqi Zhang institute of Fundamental and frontier Sciences University of Electronic Science and Technology of ChinaChengdu 611731SichuanChina School of Mechanical Engineering Hunan University of TechnologyZhuzhou 412007HunanChina School of Materials Science and Engineering Zhejiang University of TechnologyHangzhou 310014ZhejiangChina Department of Chemistry Faculty of Basic SciencesTarbiat Modares UniversityTehran 14117-13116Iran State Key Laboratory of New Textile Materials and Advanced Processing technologies Wuhan Textile UniversityWuhan 430200HubeiChina

The anti-freezing strategy of hydrogels and their self-healing structure are often contradictory,it is vital to break through the molecular structure to design and construct hydrogels with intrinsic anti-freezing/self-healing for meeting the rapid development of flexible and wearable devices in diverse service ***,we design a new hydrogel electrolyte(AF/SH-Hydrogel)with intrinsic anti-freezing/self-healing capabilities by introducing ethylene glycol molecules,dynamic chemical bonding(disulfide bond),and supramolecular interaction(multi-hydrogen bond)into the polyacrylamide molecular *** to the exceptional freeze resistance(84%capacity retention at-20℃)and intrinsic self-healing capabilities(95%capacity retention after 5 cutting/self-healing cycles),the obtained AF/SH-Hydrogel makes the zinc||manganese dioxide cell an economically feasible battery for the state-of-the-art *** Zn||AF/SH-Hydrogel||MnO_(2)device offers a near-theoretical specific capacity of 285 m A h g^(-1)at 0.1 A g^(-1)(Coulombic efficiency≈100%),as well as good self-healing capability and mechanical flexibility in an ice *** work provides insight that can be utilized to develop multifunctional hydrogel electrolytes for application in next generation of self-healable and freeze-resistance smart aqueous energy storage devices.

关键词： Flexible aqueous battery Hydrogel electrolyte Anti-freezing Self-healing Dual-dynamic reversible bond

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Progress and Implications from Genetic Studies of Bipolar Disorder

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Neuroscience Bulletin 2024年第8期40卷 1160-1172页

作者： Lingzhuo Kong Yiqing Chen Yuting Shen Danhua Zhang Chen Wei Jianbo Lai Shaohua Hu Department of Psychiatry the First Affiliated HospitalZhejiang University School of MedicineHangzhou310003China The Key Laboratory of Mental Disorder Management in zhejiang Province Hangzhou310003China Brain Research institute of zhejiang university Hangzhou310003China zhejiang Engineering Center for Mathematical Mental Health Hangzhou310003China Department of Neurobiology NHC and CAMS Key Laboratory of Medical NeurobiologySchool of Brain Science and Brian Medicineand MOE Frontier Science Center for Brain Science and Brain-machine IntegrationZhejiang University School of MedicineHangzhou310003China

With the advancements in gene sequencing technologies,including genome-wide association studies,polygenetic risk scores,and high-throughput sequencing,there has been a tremendous advantage in mapping a detailed blueprint for the genetic model of bipolar disorder(BD).To date,intriguing genetic clues have been identified to explain the development of BD,as well as the genetic association that might be applied for the development of susceptibility prediction and pharmacogenetic *** genes of BD,such as CACNA1C,ANK3,TRANK1,and CLOCK,have been found to be involved in various pathophysiological processes correlated with *** the specific roles of these genes have yet to be determined,genetic research on BD will help improve the prevention,therapeutics,and prognosis in clinical *** latest preclinical and clinical studies,and reviews of the genetics of BD,are analyzed in this review,aiming to summarize the progress in this intriguing field and to provide perspectives for individualized,precise,and effective clinical practice.

关键词： Bipolar disorder Genetics Risk gene Genome-wide association study Sequencing technology

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Iris:a multi-constraint graphic layout generation system

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frontiers of Information Technology & Electronic Engineering 2024年第7期25卷 968-987页

作者： Liuqing CHEN Qianzhi JING Yixin TSANG Tingting ZHOU College of Computer Science and Technology Zhejiang UniversityHangzhou 310030China zhejiang–Singapore Innovation and AI joint Research Lab Hangzhou 310058China alibaba Group Hangzhou 310034China

In graphic design,layout is a result of the interaction between the design elements in the foreground and background ***,prevalent research focuses on enhancing the quality of layout generation algorithms,overlooking the interaction and controllability that are essential for designers when applying these methods in realworld *** paper proposes a user-centered layout design system,Iris,which provides designers with an interactive environment to expedite the workflow,and this environment encompasses the features of user-constraint specification,layout generation,custom editing,and final *** satisfy the multiple constraints specified by designers,we introduce a novel generation model,multi-constraint LayoutVQ-VAE,for advancing layout generation under intra-and inter-domain *** and quantitative experiments on our proposed model indicate that it outperforms or is comparable to prevalent state-of-the-art models in multiple *** studies on Iris further demonstrate that the system significantly enhances design efficiency while achieving human-like layout designs.

关键词： Graphic layout generation Deep generative model Layout design system

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Unsupervised feature selection via joint local learning and group sparse regression

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frontiers of Information Technology & Electronic Engineering 2019年第4期20卷 538-553页

作者： Yue WU Can WANG Yue-qing ZHANG Jia-jun BU zhejiang Provincial Key Laboratory of Service Robot College of Computer Science and Technology Zhejiang University alibaba-zhejiang university joint institute of frontier technologies

Feature selection has attracted a great deal of interest over the past decades. By selecting meaningful feature subsets, the performance of learning algorithms can be effectively improved. Because label information is expensive to obtain, unsupervised feature selection methods are more widely used than the supervised ones. The key to unsupervised feature selection is to find features that effectively reflect the underlying data distribution. However,due to the inevitable redundancies and noise in a dataset, the intrinsic data distribution is not best revealed when using all features. To address this issue, we propose a novel unsupervised feature selection algorithm via joint local learning and group sparse regression(JLLGSR). JLLGSR incorporates local learning based clustering with group sparsity regularized regression in a single formulation, and seeks features that respect both the manifold structure and group sparse structure in the data space. An iterative optimization method is developed in which the weights finally converge on the important features and the selected features are able to improve the clustering results. Experiments on multiple real-world datasets(images, voices, and web pages) demonstrate the effectiveness of JLLGSR.

关键词： Unsupervised Local learning Group sparse regression Feature selection

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DataV:Data Visualization on large high-resolution displays

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Visual Informatics 2020年第3期4卷 12-23页

作者： Honghui Mei Huihua Guan Chengye Xin Xiao Wen Wei Chen alibaba Group China State Key Lab of CAD&CG Zhejiang UniversityChina joint institute of frontier technologies Alibaba-Zhejiang UniversityChina

In recent years,the technology and applications of visualizations on large high-resolution displays(LHDs)have received widespread attention because of its perceptual benefits and improved produc***,existing work on LHD visualization lacks both comprehensive guidance for design requirements and tools developed for its specific usage *** this paper,we present the scenarios,design,and implementation of DataV,a Software-as-a-Service(SaaS)visual deployment tool that enables rapid construction and cross-platform publishing of interactive visualization on *** framework can support rich components for the high-performance rendering of multisource heterogeneous *** provides a full-fledged toolchain to help the user efficiently specify layout and *** present its accessibility and impressive visual effects with examples and comparison with Tableau,Power BI,VisComposer,and *** also report the performance of using DataV for 3D map rendering by comparing it with ***.

关键词： Information visualization Large high-resolution displays Interactive design Software-as-a-service

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Theoretical analysis of persistent fault attack

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Science China(Information Sciences) 2020年第3期63卷 234-239页

作者： Fan ZHANG Guorui XU Bolin YANG Ziyuan LIANG Kui REN College of Information Science and Electronic Engineering Zhejiang University State Key Laboratory of Cryptology School of Cyber Science and Technology Zhejiang University alibaba-zhejiang university joint institute of frontier technologies

Dear editor,Persistent fault attack is a new type of fault attack that was proposed in CHES 2018 [1]. Its success relies on the so-called persistent fault which persists from one encryption to another and disappears w... 详细信息

关键词： Theoretical analysis of persistent fault attack

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Finding map regions with high density of query keywords

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frontiers of Information Technology & Electronic Engineering 2017年第10期18卷 1543-1555页

作者： Zhi YU Can WANG Jia-jun BU Xia HU Zhe WANG Jia-he JIN alibaba-zhejiang university joint institute of frontier technologies Zhejiang Provincial Key Laboratory of Service Robot College of Computer Science and Technology Zhejiang University Hangzhou 310027 China Hangzhou Science and Technology Information Research institute Hangzhou 310001 China

We consider the problem of finding map regions that best match query keywords. This region search problem can be applied in many practical scenarios such as shopping recommendation, searching for tourist attractions, and collision region detection for wireless sensor networks. While conventional map search retrieves isolate locations in a map, users frequently attempt to find regions of interest instead, e.g., detecting regions having too many wireless sensors to avoid collision, or finding shopping areas featuring various merchandise or tourist attractions of different styles. Finding regions of interest in a map is a non-trivial problem and retrieving regions of arbitrary shapes poses particular challenges. In this paper, we present a novel region search algorithm, dense region search(DRS), and its extensions, to find regions of interest by estimating the density of locations containing the query keywords in the region. Experiments on both synthetic and real-world datasets demonstrate the effectiveness of our algorithm.

关键词： Map search Region search Region recommendation Spatial keyword search Geographic information system Location-based service

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AI for organic and polymer synthesis

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Science China Chemistry 2024年第8期67卷 2461-2496页

作者： Xin Hong Qi Yang Kuangbiao Liao Jianfeng Pei Mao Chen Fanyang Mo Hua Lu Wen-Bin Zhang Haisen Zhou Jiaxiao Chen Lebin Su Shuo-Qing Zhang Siyuan Liu Xu Huang Yi-Zhou Sun Yuxiang Wang Zexi Zhang Zhunzhun Yu Sanzhong Luo Xue-Feng Fu Shu-Li You Center of Chemistry for frontier technologies Department of ChemistryZhejiang UniversityHangzhou 310027China Center of Basic Molecular Science Department of ChemistryTsinghua UniversityBeijing 100084China Guangzhou National Laboratory Guangzhou 510005China Center for Quantitative Biology Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijing 100871China State Key Laboratory of Molecular Engineering of Polymers Department of Macromolecular ScienceFudan UniversityShanghai 200433China School of Materials Science and Engineering Peking UniversityBeijing 100871China Beijing National Laboratory for Molecular Sciences Center for Soft Matter Science and EngineeringKey Laboratory of Polymer Chemistry and Physics of Ministry of EducationCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China AI for Science(AI4S)-Preferred Program Shenzhen Graduate SchoolPeking UniversityShenzhen 518055China State Key Laboratory of Chemical Biology Shanghai Institute of Organic ChemistryUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200032China Department of Chemical Sciences National Natural Science Foundation of ChinaBeijing 100085China State Key Laboratory of Organometallic Chemistry Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghai 200032China

Recent years have witnessed the transformative impact from the integration of artificial intelligence with organic and polymer synthesis. This synergy offers innovative and intelligent solutions to a range of classic problems in synthetic chemistry. These exciting advancements include the prediction of molecular property, multi-step retrosynthetic pathway planning, elucidation of the structure-performance relationship of single-step transformation, establishment of the quantitative linkage between polymer structures and their functions, design and optimization of polymerization process, prediction of the structure and sequence of biological macromolecules, as well as automated and intelligent synthesis platforms. Chemists can now explore synthetic chemistry with unprecedented precision and efficiency, creating novel reactions, catalysts, and polymer materials under the datadriven paradigm. Despite these thrilling developments, the field of artificial intelligence(AI) synthetic chemistry is still in its infancy, facing challenges and limitations in terms of data openness, model interpretability, as well as software and hardware support. This review aims to provide an overview of the current progress, key challenges, and future development suggestions in the interdisciplinary field between AI and synthetic chemistry. It is hoped that this overview will offer readers a comprehensive understanding of this emerging field, inspiring and promoting further scientific research and development.

关键词： organic synthesis polymer synthesis machine learning prediction chemical database automated synthesis

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Two-dimensional materials for future information technology: status and prospects

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Science China(Information Sciences) 2024年第6期67卷 1-147页

作者： Hao QIU Zhihao YU Tiange ZHAO Qi ZHANG Mingsheng XU Peifeng LI Taotao LI Wenzhong BAO Yang CHAI Shula CHEN Yiqi CHEN Hui-Ming CHENG Daoxin DAI Zengfeng DI Zhuo DONG Xidong DUAN Yuhan FENG Yu FU Jingshu GUO Pengwen GUO Yue HAO Jun HE Xiao HE Jingyi HU Weida HU Zehua HU Xinyue HUANG Ziyang HUANG Ali IMRAN Ziqiang KONG Jia LI Qian LI Weisheng LI Lei LIAO Bilu LIU Can LIU Chunsen LIU Guanyu LIU Kaihui LIU Liwei LIU Sheng LIU Yuan LIU Donglin LU Likuan MA Feng MIAO Zhenhua NI Jing NING Anlian PAN Tian-Ling REN Haowen SHU Litao SUN Yue SUN Quanyang TAO Zi-Ao TIAN Dong WANG Hao WANG Haomin WANG Jialong WANG Junyong WANG Wenhui WANG Xingjun WANG Yeliang WANG Yuwei WANG Zhenyu WANG Yao WE... School of Electronic Science and Engineering Nanjing University School of Integrated Circuits Interdisciplinary Research Center for Future Intelligent Chips (Chip-X)Nanjing University School of Integrated Circuit Science and Engineering Nanjing University of Posts and Telecommunications State Key Laboratory of Infrared Physics Shanghai Institute of Technical Physics Chinese Academy of Sciences School of Physics and Key Lab of Quantum Materials and Devices of the Ministry of Education School of Electronic Science & EngineeringSoutheast University College of Integrated Circuits State Key Laboratory of Silicon and Advanced Semiconductor MaterialsZhejiang University Suzhou Laboratory State Key Laboratory of Integrated Chips and Systems School of MicroelectronicsFudan University Shaoxin Laboratory Department of Applied Physics The Hong Kong Polytechnic University Key Laboratory for Micro-Nano Physics and Technology of Hunan Province College of Materials Science and EngineeringHunan University College of Integrated Circuits Zhejiang University Shenzhen Geim Graphene Center Shenzhen Key Laboratory of Layered Materials for Value-Added ApplicationsTsinghua-Berkeley Shenzhen Institute & Institute of Materials ResearchTsinghua Shenzhen International Graduate SchoolTsinghua University State Key Laboratory of Extreme Photonics and Instrumentation College of Optical Science and EngineeringInternational Research Center for Advanced PhotonicsZijingang CampusZhejiang University National Key Laboratory of Materials for Integrated Circuits Shanghai Institute of Microsystem and Information TechnologyChinese Academy of Sciences CAS Key Laboratory of Nanophotonic Materials and Devices & Key Laboratory of Nanodevices and Applications i-LabSuzhou Institute of Nano-Tech and Nano-Bionics (SINANO)Chinese Academy of Sciences College of Chemistry and Chemical Engineering Hunan University Key Laboratory of Quantum State Construction and Manipulation (Ministry of Education) Department of PhysicsRenmin University of China School

Over the past 70 years, the semiconductor industry has undergone transformative changes,largely driven by the miniaturization of devices and the integration of innovative structures and materials. Two-dimensional(2D) materials like transition metal dichalcogenides(TMDs) and graphene are pivotal in overcoming the limitations of silicon-based technologies, offering innovative approaches in transistor design and functionality, enabling atomic-thin channel transistors and monolithic 3D integration. We review the important progress in the application of 2D materials in future information technology, focusing in particular on microelectronics and optoelectronics. We comprehensively summarize the key advancements across material production, characterization metrology, electronic devices, optoelectronic devices, and heterogeneous integration on silicon. A strategic roadmap and key challenges for the transition of 2D materials from basic research to industrial development are outlined. To facilitate such a transition, key technologies and tools dedicated to 2D materials must be developed to meet industrial standards, and the employment of AI in material growth, characterizations, and circuit design will be essential. It is time for academia to actively engage with industry to drive the next 10 years of 2D material research.

关键词： two-dimensional (2D) materials information technology production technology standardization of characterization microelectronicdevices optoelectronic devices multi-functional integration

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Single-cell omics:experimental workflow,data analyses and applications

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Science China Life Sciences 2024年

作者： Fengying Sun Haoyan Li Dongqing Sun Shaliu Fu Lei Gu Xin Shao Qinqin Wang Xin Dong Bin Duan Feiyang Xing Jun Wu Minmin Xiao Fangqing Zhao Jing-Dong J.Han Qi Liu Xiaohui Fan Chen Li Chenfei Wang Tieliu Shi Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biology the Institute of Biomedical Sciences and School of Life Sciences East China Normal University Beijing institutes of Life Science Chinese Academy of Sciences Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary Studies Center for Quantitative Biology (CQB) Peking University zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases Women’s Hospital Zhejiang University School of Medicine Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University Shanghai 200062 China Department of Clinical Laboratory the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City) Pharmaceutical Informatics institute College of Pharmaceutical Sciences Zhejiang University Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji university) Ministry of Education Orthopaedic Department Tongji Hospital Bioinformatics Department School of Life Sciences and Technology Tongji University frontier Science Center for Stem Cells School of Life Sciences and Technology Tongji University Translational Medical Center for Stem Cell Therapy and institute for Regenerative Medicine Shanghai East Hospital Bioinformatics Department School of Life Sciences and Technology Tongji University Research institute of Intelligent Computing Zhejiang Lab Shanghai Research institute for Intelligent Autonomous Systems Center for Single-cell Omics School of Public Health Shanghai Jiao Tong University School of Medicine National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River Delta Zhejiang University

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome,proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial scRNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field,offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

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