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Nitrogen-doped microporous graphite-enhanced copper plasmonic effect for solar evaporation

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Carbon Energy 2024年第3期6卷 215-223页

作者： Xintao Wu Chengcheng Li Ziqi Zhang Yang Cao Jieqiong Wang Xinlong Tian Zhongxin Liu Yijun Shen Mingxin Zhang Wei Huang School of Marine Science and Engineering School of Chemistry and Chemical EngineeringHainan UniversityHaikouHainanChina Key laboratory of Child cognition and Behavior Development of Hainan Province Qiongtai Normal UniversityHaikouHainanChina

Water scarcity is a global challenge,and solar evaporation technology offers a promising and eco-friendly solution for freshwater production.Photothermal conversion materials(PCMs)are crucial for solar evaporation.Improving photothermal conversion efficiency and reducing water evaporation enthalpy are the two key strategies for the designing of PCMs.The desired PCMs that combine both of these properties remain a challenging task,even with the latest advancements in the field.Herein,we developed copper nanoparticles(NPs)with different conjugated nitrogen-doped microporous carbon coatings(Cu@C–N)as PCMs.The microporous carbon enveloping layer provides a highly efficient pathway for water transport and a nanoconfined environment that protects Cu NPs and facilitates the evaporation of water clusters,reducing the enthalpy of water evaporation.Meanwhile,the conjugated nitrogen nodes form strong metal-organic coordination bonds with the surface of copper NPs,acting as an energy bridge to achieve rapid energy transfer and provide high solar-to-vapor conversion efficiency.The Cu@C–N exhibited up to 89.4%solar-to-vapor conversion efficiency and an evaporation rate of 1.94 kgm^(−2) h^(−1) under one sun irradiation,outperforming conventional PCMs,including carbon-based materials and semiconductor materials.These findings offer an efficient design scheme for high-performance PCMs essential for solar evaporators to address global water scarcity.

关键词： nanoconfinement photothermal conversion materials plasmonic resonance seawater desalination solar evaporation

Pyramid-resolution person restoration for cross-resolution person re-identification

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Science China(Information Sciences) 2024年第6期67卷 451-452页

作者： Chunlei PENG Bo WANG Decheng LIU Nannan WANG Xinbo GAO State Key laboratory of Integrated Services Networks Xidian University School of Cyber Engineering Xidian University School of Telecommunications Engineering Xidian University Chongqing Key laboratory of Image cognition Chongqing University of Posts and Telecommunications

Person images captured by surveillance cameras are typically with various resolutions and are susceptible to pose changes,occlusion and background variations,thus affecting the performance of person Re ID.Existing approaches[1,2]either use an image restoration model to restore the lowresolution images to obtain a corresponding high-resolution image,

关键词： Restoration

On the Probability of Generating a Primitive Matrix

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Journal of Systems Science & Complexity 2024年第4期37卷 1755-1771页

作者： CHEN Jingwei FENG Yong LIU Yang WU Wenyuan Chongqing Key laboratory of Automated Reasoning and cognition Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing College University of Chinese Academy of Sciences Key laboratory of Advanced Manufacturing Technology of Ministry of Education Guizhou Universityy Information Science and Engineering Chongqing Jiaotong University

Given a k × n integer primitive matrix A（i.e., a matrix can be extended to an n × n unimodular matrix over the integers） with the maximal absolute value of entries ‖A‖ bounded by an integer λ from above, the authors study the probability that the m × n matrix extended from A by appending other m-k row vectors of dimension n with entries chosen randomly and independently from the uniform distribution over {0, 1, · · ·, λ-1} is still primitive. The authors present a complete and rigorous proof of a lower bound on the probability, which is at least a constant for fixed m in the range[k + 1, n-4]. As an application, the authors prove that there exists a fast Las Vegas algorithm that completes a k × n primitive matrix A to an n × n unimodular matrix within expected ?（nωlog ‖A‖） bit operations, where ? is big-O but without log factors, ω is the exponent on the arithmetic operations of matrix multiplication.

关键词： Integer matrix matrix completion probabilistic algorithm unimodular matrix

Factor Structure and Longitudinal Invariance of the CES-D across Diverse Residential Backgrounds in Chinese Adolescents

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International Journal of Mental Health Promotion 2024年第4期26卷 261-269页

作者： Yanjing Cao Chenchen Xu Qi Li Shan Lu Jing Xiao Beijing Key laboratory of Learning and cognition and Department of Psychology Capital Normal UniversityBeijing100048China Center for Child Development Capital Normal UniversityBeijing100048China

Background:Valid and reliable measures of depressive symptoms are crucial for understanding risk factors,outcomes,and interventions across rural and urban settings.Despite this need,the longitudinal invariance of these measures over time remains understudied.This research explores the structural components of the Center for Epidemiological studies Depression Scale(CES-D)and examines its consistency across various living environments and temporal stability in a cohort of Chinese teenagers.Method:In the initial phase,1,042 adolescents furnished demographic details and undertook the CES-D assessment.After a three-month interval,967 of these participants repeated the CES-D evaluation.The study employed Confirmatory factor analysis(CFA)to scrutinize the scale’s structural integrity.We investigated factorial invariance by conducting a twopronged CFA:one comparing urban vs.rural backgrounds,and another contrasting the results from the initial assessment with those from the follow-up.Results:The CES-D demonstrated adequate reliability in both rural and urban high school student samples.The preliminary four-factor model applied to the CES-D demonstrated a good fit with the collected data.Invariance tests,including multigroup analyses comparing rural and urban samples and longitudinal assessments,confirmed the scale’s invariance.Conclusions:The results suggest that the CES-D serves as a reliable instrument for evaluating depressive symptoms among Chinese adolescents.Its applicability is consistent across different living environments and remains stable over time.

关键词： Depression factor structure measurement invariance Chinese adolescent longitudinal invariance

Why people should run after positive affective experiences instead of health benefits

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Journal of Sport and Health Science 2024年第4期13卷 445-450页

作者： Silvio Maltagliati Philippe Sarrazin Layan Fessler Mael Lebreton Boris Cheval University of Grenoble Alpes SENSGrenoble 38000France Paris School of Economics Paris 75014France Swiss Center for Affective Sciences University of GenevaGeneva 1202Switzerland laboratory for Behavioral Neurology and Imaging of cognition Department of Fundamental NeurosciencesUniversity of GenevaGeneva 1202Switzerland laboratory for the Study of Emotion Elicitation and Expression(E3Lab) Department of PsychologyUniversity of GenevaGeneva 1202Switzerland

Over time,physical activity(PA)has shifted from being a necessity to being an alternative.As a result,levels of PA have sharply decreased.1 Today,we are facing a worldwide pandemic of physical inactivity,with one death every 6 s attributed to insufficient PA.2 To counteract this trend,a tremendous effort is being made to promote regular PA across the lifespan,mainly through the dissemination of knowledge about the health benefits of accumulating sufficient PA.

关键词： sharply benefits attributed

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Neuronomodulation of Excitable Neurons

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Neuroscience Bulletin 2024年第1期40卷 103-112页

作者： Yizhang Chen Lin Xiao Jian Qiu Institute of Neuroscience Second Military Medical UniversityShanghai 200433China Institute for Brain Research and Rehabilitation Key Laboratory of BrainCognition and Education Sciences of Ministry of EducationSouth China Normal UniversityGuangzhou 510631China Department of Chemical Physiology and Biochemistry Oregon Health and Science UniversityPortlandOR 97239USA

Neuronomodulation refers to the modulation of neural conduction and synaptic transmission(i.e.,the conduction process involved in synaptic transmission)of excitable neurons via changes in the membrane potential in response to chemical substances,from spillover neuro-transmitters to paracrine or endocrine hormones circulating in the blood.Neuronomodulation can be direct or indirect,depending on the transduction pathways from the ligand binding site to the ion pore,either on the same molecule,i.***.the ion channel,or through an intermediate step on different molecules.The major players in direct neurono-modulation are ligand-gated or voltage-gated ion channels.The key process of direct neuronomodulation is the binding and chemoactivation of ligand-gated or voltage-gated ion channels,either orthosterically or allosterically,by various ligands.Indirect neuronomodulation involves metabotropic receptor-mediated slow potentials,where steroid hormones,cytokines,and chemokines can implement these actions.Elucidating neuronomodulation is of great significance for understanding the physiological mechanisms of brain function,and the occurrence and treatment of diseases.

关键词： Neuron Membrane potential Excitability Chemoactivation Neuronomodulation

Mitigating set-stuck failure in 3D phase change memory: substituting square pulses with surge pulses

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Science China(Information Sciences) 2024年第5期67卷 295-301页

作者： Ninghua LI Wang CAI Jun XIANG Hao TONG Weiming CHENG Xiangshui MIAO School of Integrated Circuits Huazhong University of Science and Technology Hubei Yangtze memory Laboratories Hubei Institute of Measurement and Testing Technology

In the devices that integrate phase change memory(PCM) and ovonic threshold switching(OTS),the OTS threshold voltage often surpasses the RESET operation voltage of PCM. The conventional application of square pulses hinders the successful completion of the SET operation in these integrated devices. To address this challenge, a novel pulse called the surge pulse is introduced, which comprises a high amplitude pulse for OTS activation and a low amplitude pulse for PCM operation. By employing COMSOL simulation,the operational effectiveness of both square pulses and surge pulses is validated. Test results reveal that using a square pulse to operate the integrated device accelerates the occurrence of SET-stuck failure(SSF).In contrast, the surge pulse enables the integrated device to operate for at least 1000 cycles while preserving the essential cyclic characteristics. Additionally, an investigation into the overshoot component of the surge pulse is conducted, revealing that an increase in overshoot amplitude and pulse width also accelerates the emergence of SSF. By applying the theory of ion migration induced by the electric field, the root cause of SSF in integrated devices is explained, and the accuracy of the theory is validated through the application of a reverse pulse. In summary, this study elucidates the rationality of replacing the square pulse with a surge pulse, presenting a superior approach for operating PCM and OTS integrated devices.

关键词： surge pulse phase change memory (PCM) integration SET-stuck failure (SSF) square pulse

Deep Broad Learning for Emotion Classification in Textual Conversations

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Tsinghua Science and Technology 2024年第2期29卷 481-491页

作者： Sancheng Peng Rong Zeng Hongzhan Liu Lihong Cao Guojun Wang Jianguo Xie Center for Linguistics and Applied Linguistics and Laboratory of Language Engineering and ComputingGuangdong University of Foreign StudiesGuangzhou 510006China Guangdong Provincial Key laboratory of Nanophotonic Functional Materials and Devices South China Normal UniversityGuangzhou 510006China School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou 510006China Modern Education Technology Center Guangdong University of Foreign StudiesGuangzhou 510006China

Emotion classification in textual conversations focuses on classifying the emotion of each utterance from textual conversations.It is becoming one of the most important tasks for natural language processing in recent years.However,it is a challenging task for machines to conduct emotion classification in textual conversations because emotions rely heavily on textual context.To address the challenge,we propose a method to classify emotion in textual conversations,by integrating the advantages of deep learning and broad learning,namely DBL.It aims to provide a more effective solution to capture local contextual information(i.e.,utterance-level)in an utterance,as well as global contextual information(i.e.,speaker-level)in a conversation,based on Convolutional Neural Network(CNN),Bidirectional Long Short-Term memory(Bi-LSTM),and broad learning.Extensive experiments have been conducted on three public textual conversation datasets,which show that the context in both utterance-level and speaker-level is consistently beneficial to the performance of emotion classification.In addition,the results show that our proposed method outperforms the baseline methods on most of the testing datasets in weighted-average F1.

关键词： emotion classification textual conversation Convolutional Neural Network(CNN) Bidirectional Long Short-Term memory(Bi-LSTM) broad learning

LKPNR: Large Language Models and Knowledge Graph for Personalized News Recommendation Framework

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Computers, Materials & Continua 2024年第6期79卷 4283-4296页

作者： Hao Chen Runfeng Xie Xiangyang Cui Zhou Yan Xin Wang Zhanwei Xuan Kai Zhang State Key laboratory of Communication Content cognition People’s Daily OnlineBeijing100733China

Accurately recommending candidate news to users is a basic challenge of personalized news recommendation systems.Traditional methods are usually difficult to learn and acquire complex semantic information in news texts,resulting in unsatisfactory recommendation results.Besides,these traditional methods are more friendly to active users with rich historical behaviors.However,they can not effectively solve the long tail problem of inactive users.To address these issues,this research presents a novel general framework that combines Large Language Models(LLM)and Knowledge Graphs(KG)into traditional methods.To learn the contextual information of news text,we use LLMs’powerful text understanding ability to generate news representations with rich semantic information,and then,the generated news representations are used to enhance the news encoding in traditional methods.In addition,multi-hops relationship of news entities is mined and the structural information of news is encoded using KG,thus alleviating the challenge of long-tail distribution.Experimental results demonstrate that compared with various traditional models,on evaluation indicators such as AUC,MRR,nDCG@5 and nDCG@10,the framework significantly improves the recommendation performance.The successful integration of LLM and KG in our framework has established a feasible way for achieving more accurate personalized news recommendation.Our code is available at https://***/Xuan-ZW/LKPNR.

关键词： Large language models news recommendation knowledge graphs(KG)