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Cognition-driven multimodal personality classification

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Science China(Information Sciences) 2022年第10期65卷 164-177页

作者： Xiaoya GAO Jingjing WANG shoushan li Min ZHANG Guodong ZHOU School of Computer Science and Technology Soochow University

In this paper, we address a novel task, namely, cognition-driven multimodal personality classification(CMPC), aiming to infer personality traits(e.g., romantic, humorous, and gloomy) shown in real time by a human being from the perspective of cognitive psychology. Specifically, this task is motivated by a cognitive difference phenomenon that humans with different personality traits tend to give different personality-oriented textual descriptions when observing an image. In particular, to tackle the inherent noise challenges in this CMPC task, we propose a tailored reinforcement learning approach, namely, multi-agent Select Net, aiming to integrate the opinion-word and image-region selection strategies to select informative opinion-word and image-region features for CMPC. To justify the effectiveness of our approach, we construct six kinds of multimodal personality classification datasets and conduct extensive experiments on the datasets.Experimental results demonstrate that our approach can significantly outperform other strong competitors,including the state-of-the-art unimodal and multimodal approaches.

关键词： cognitive psychology personality classification multimodal analysis multi-agent reinforcement learning agent-sharing mechanism

Leaching kinetics of fluorine during the aluminum removal from spent li-ion battery cathode materials

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Journal of Environmental Sciences 2024年第4期138卷 312-325页

作者： Shengjie li Jianxin Zhu Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China University of Chinese Academy of Sciences Beijing 100049China

The high content of aluminum(Al)impurity in the recycled cathode powder seriously affects the extraction efficiency of Nickel,Cobalt,Manganese,and lithium resources and the actual commercial value of recycled materials,so Al removal is crucially important to conform to the industrial standard of spent li-ion battery cathode materials.In this work,we systematically investigated the leaching process and optimum conditions associated with Al removal from the cathode powder materials collected in a wet cathode-powder peeling and recycling production line of spent li-ion batteries(liBs).Moreover,we specifically studied the leaching of fluorine(F)synergistically happened along with the removal process of Al,which was not concerned about in other studies,but one of the key factors affecting pollution prevention in the recovery process.The mechanism of the whole process including the leaching of Al and F from the cathode powder was indicated by using NMR,FTIR,and XPS,and a defluoridation process was preliminarily investigated in this study.The leaching kinetics of Al could be successfully described by the shrinking core model,controlled by the diffusion process and the activation energy was 11.14 kJ/mol.While,the leaching of F was attributed to the dissolution of liPF6and decomposition of PVDF,and the kinetics associated was described by Avrami model.The interaction of Al and F is advantageous to realize the defluoridation to some degree.It is expected that our investigation will provide theoretical support for the large-scale recycling of spent liBs.

关键词： Al removal F leaching Cathode powder Heating alkali leaching Leaching kinetics

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Additives strategies to improving cycling stability of li metal batteries by modifying electrode electrolyte interphases

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Progress in Natural Science:Materials International 2024年第2期34卷 338-344页

作者： Yuan li Pengfei Huang Chunyu Cui Xiaoyuan Ma li Chen Zekun li linhai li Yuhong Tian School of Biological and Chemical Engineering Guangxi University of Science and Technology School of College of Chemistry and Chemical Engineering Hunan University Isky Future Energy Institute

li metal batteries（LMBs） have attracted much attention due to the ultra-high theoretical capacity of the li metal anode（LMA）.However,the uncontrollable dendrites growth and low coulombic efficiency hinder their practical application.Here,we explore 3,5-difluoropyridine（2F-BD） as a novel electrolyte additive to enable highperformance LMBs.The 2F-BD additive participates in and modifies the solvation structure of li ions by reducing the coordinated number of PF6-at the electrode surface,leading to the formation of a liF and li3N-rich solid electrolyte interphase（SEI）.The liF component increases the robustness of SEI and suppresses the formation of li dendrites,while the li3N component facilitates the transportation and reaction kinetics of li ions.As a result,the li‖li symmetric cell presents a stable cycling performance of up to 500 h at a current density of 1 mA cm-2.After coupling with liFePO4cathode,the obtained full cell achieves high specific capacities of 106.06 mA h g-1and 84.98 mA h g-1at 2.55 mA cm-2and 5.10 mA cm-2,respectively,and maintains a high capacity retention of84.0% after 1000 cycles at 0.13 mA cm-2,with an average cycling CE of 99.58%.

关键词： Electrolyte additive li dendrites li metal batteries liF and li3N-Rich electrode-electrolyte interphase liFePO4 cathode

Personal summarization from profile networks

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Frontiers of Computer Science 2017年第6期11卷 1085-1097页

作者： Zhongqing WANG shoushan li Guodong ZHOU Natural Language Processing Lab School of Computer Science and Technology Soochow University Suzhou 215006 China

Personal profile information on social media like *** and *** is at the core of many inter- esting applications, such as talent recommendation and con- textual advertising. However, personal profiles usually lack consistent organization confronted with the large amount of available information. Therefore, it is always a challenge for people to quickly find desired information from them. In this paper, we address the task of personal profile summarization by leveraging both textual information and social connection information in social networks from both unsupervised and supervised learning paradigms. Here, using social connec- tion information is motivated by the intuition that people with similar academic, business or social background （e.g., co- major, co-university, and co-corporation） tend to have similar experiences and should have similar summaries. For unsu- pervised learning, we propose a collective ranking approach, called SocialRank, to combine textual information in an in- dividual profile and social context information from relevant profiles in generating a personal profile summary. For super- vised learning, we propose a collective factor graph model, called CoFG, to summarize personal profiles with local tex- tual attribute functions and social connection factors. Exten- sive evaluation on a large dataset from *** demon- strates the usefulness of social connection information in per- sonal profile summarization and the effectiveness of our pro- posed unsupervised and supervised learning approaches.

关键词： natural language processing machine learning,social networks personal profile summarization

Highly-chlorinated inert and robust interphase without mineralization of oxide enhancing high-rate li metal batteries

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Chinese Chemical Letters 2024年第6期35卷 239-243页

作者： Long li Kang Yang Chenpeng Xi Mengchao li Borong li Gui Xu Yuanbin Xiao Xiancai Cui Zhiliang liu lingyun li Yan Yu Chengkai Yang Key Laboratory of Advanced Materials Technologies International(HongKong Macao and Taiwan)Joint Laboratory on Advanced Materials TechnologiesSchool of Materials Science and EngineeringFuzhou UniversityFuzhou 350108China College of Material Sciences and Chemical Engineering Harbin Engineering UniversityHarbin 150001China

Side reactions and dendrite growth triggered by the unstable interface and inhomogeneous deposition have become the biggest obstacle to the commercialization for lithium metal batteries.In this study,a highly-chlorinated organic-inorganic hybrid interfacial protective layer is developed by rationally tuning the interfacial passivation and robustness to achieve the convenient and efficient li metal anode.The polyvinyl chloride(PVC)can effectively resist water and oxygen,which is confirmed by density functional theory.The organic-dominant solid electrolyte interphases(SEI)with lithium chloride are investigated by the X-ray photoelectron spectroscopy(XPS)with little mineralization of oxide,such as li_(2)O and li_(2)CO_(3).With such artificial SEI,a uniform and dense lithium deposition morphology are formed and an ultra-long stable cycle of over 500 h are achieved even at an ultra-high current density of 10 m A/cm^(2).Moreover,the simple and convenient protected anode also exhibits excellent battery stability when paired with the liNi_(0.8)Co_(0.1)Mn_(0.1)O_(2)(NCM811)and liFePO_(4)(LFP)cathode,showing great potential for the commercial application of lithium metal batteries.

关键词： Highly-chlorinated Water/oxygen resistance Stable interphase Dendrite-free lithium metal batteries High-rate

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Accelerating lithium-sulfur battery reaction kinetics and inducing 3D deposition of li2S using interactions between Fe3Se4 and lithium polysulfides

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Journal of Energy Chemistry 2024年第8期95卷 540-553页

作者： Yihan lin liheng li Longjie Tan Yongliang li Xiangzhong Ren Peixin Zhang Chuanxin He lingna Sun College of Chemistry and Environmental Engineering Shenzhen University

Although lithium-sulfur batteries（LSBs） exhibit high theoretical energy density,their practical application is hindered by poor conductivity of the sulfur cathode,the shuttle effect,and the irreversible deposition of li2S.To address these issues,a novel composite,using electrospinning technology,consisting of Fe3Se4and porous nitrogen-doped carbon nanofibers was designed for the interlayer of LSBs.The porous carbon nanofiber structure facilitates the transport of ions and electrons,while the Fe3Se4material adsorbs lithium polysulfides（liPSs） and accelerates its catalytic conversion process.Furthermore,the Fe3Se4material interacts with soluble liPSs to generate a new polysulfide intermediate,lixFeSycomplex,which changes the electrochemical reaction pathway and facilitates the three-dimensional deposition of li2S,enhancing the reversibility of LSBs.The designed LSB demonstrates a high specific capacity of1529.6 mA h g-1in the first cycle at 0.2 C.The rate performance is also excellent,maintaining an ultra-high specific capacity of 779.7 mA h g-1at a high rate of 8 C.This investigation explores the mechanism of the interaction between the interlayer and liPSs,and provides a new strategy to regulate the reaction kinetics and li2S deposition in LSBs.

关键词： Adsorption Catalysis Electrostatic spinning Interlayers li2S electrodeposition lithium-sulfur batteries Polysulfide intermediates

Erratum to:Influences of chemical reactions on polysulfide reduction reaction process on promotor surface in li-S batteries

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Nano Research 2024年第5期17卷 4643-4643页

Erratum to Nano Research,2024,17(4):2712-2718 https://***/10.1007/s12274-023-6129-5 The affiliation of the author,Wenhui Duan,is“2 Department of Physics,Tsinghua University,Beijing 100084,China”,instead of“1 Tsinghua-Foxconn Nanotechnology Research Center,Tsinghua University,Beijing 100084,China;2 Department of Physics,Tsinghua University,Beijing 100084,China”.And the affiliation of the author,Wenhui Duan,in the online version and the ESM file of this paper has been corrected.

关键词： sulfide corrected tor

Stance detection via sentiment information and neural network model

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Frontiers of Computer Science 2019年第1期13卷 127-138页

作者： Qingying SUN Zhongqing WANG shoushan li Qiaoming ZHU Guodong ZHOU Natural Language Processing Lab Soochow UniversitySuzhou 215006China Huaiyin Normal University Huai'an 223300China

Stance detection aims to automatically determine whether the author is in favor of or against a given target.In principle,the sentiment information of a post highly influences the stance.In this study,we aim to leverage the sentiment information of a post to improve the performance of stance detection.However,conventional discrete models with sentimental features can cause error propagation.We thus propose a joint neural network model to predict the stance and sentiment of a post simultaneously,because the neural network model can learn both representation and interaction between the stance and sentiment collectively.Specifically, we first learn a deep shared representation between stance and sentiment information,and then use a neural stacking model to leverage sentimental information for the stance detection task.Empirical studies demonstrate the effectiveness of our proposed joint neural model.

关键词： natural language processing machine learning stance detectionStance detection

Ultrathin organic solvent nanofiltration membrane with polydopamine-HKUST-1 interlayer for organic solvent separation

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Journal of Environmental Sciences 2024年第7期141卷 182-193页

作者： Haike li Xindong li Guozai Ouyang lijinhong Huang Lang li Wenhao li Wanfu Huang Duokun li Ganzhou Key Laboratory of Basin Pollution Simulation and Control Jiangxi University of Science and TechnologyGanzhou 341000China Innovation Center for Water Quality Security Technology at Ganjiang River Basin Jiangxi University of Science and TechnologyGanzhou 341000China School of Architecture and Design Jiangxi University of Science and TechnologyGanzhou 341000China WA School of Mines:Minerals Energy and Chemical EngineeringCurtin UniversityWA 6845Australia School of Materials Science and Engineering Tiangong UniversityTianjin 300387China

Polydopamine(PDA)and metal-organic skeleton HKUST-1 were co-deposited on the base membrane of hexamethylenediamine(HDA)-crosslinked polyetherimide(PEI)ultrafiltration membrane as the interlayer,and high-throughput organic solvent nanofiltration membrane(OSN)was prepared by interfacial polymerization and solvent activation reaction.The polyamide(PA)layer surface roughness from 28.4 nm in PA/PEI to 78.3 nm in PA/PDA-HKUST-10.6/PEI membrane,reduced the thickness of the separation layer from 79 to 14 nm,and significantly improved the hydrophilic,thermal and mechanical properties.The flux of the PA/PDA-HKUST-10.6/PEI membrane in a 0.1 g/L Congo Red(CR)ethanol solution at 0.6 MPa test pressure reached 21.8 L/(m^(2)·hr)and the rejection of CR was 92.8%.Solvent adsorption test,N,N-dimethylformamide(DMF)immersion experiment,and long-term operation test in ethanol showed that the membranes had high solvent tolerance.The solvent flux test demonstrated that,under the test pressure of 0.6 MPa,the flux of different solvents ranked as follows:methanol(56.9 L/(m^(2)·hr))>DMF(39.6 L/(m^(2)·hr))>ethanol(31.2 L/(m^(2)·hr))>IPA(4.5 L/(m^(2)·hr))>N-hexane(1.9 L/(m^(2)·hr)).The ability of the membranes to retain dyes in IPA/water dyes solution was also evaluated.The flux of the membrane was 30.4 L/(m^(2)·hr)and the rejection of CR was 91.6%when the IPA concentration reached 50%.This OSN membrane-making strategy is economical,environment-friendly and efficient,and has a great application prospect in organic solvent separation systems.

关键词： Interfacial polymerization Organic solvent nanofiltration Interlayer Metal-organic frameworks Polydopamine

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