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Prospects of the Multi-channel Photometric Survey Telescope in the Cosmological Application of Type Ia Supernovae

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Research in Astronomy and Astrophysics 2024年第4期24卷 183-191页

作者： zhenyu wang Jujia Zhang Xinzhong Er Jinming Bai Yunnan Observatories Chinese Academy of SciencesKunming 650216China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory for the Structure and Evolution of Celestial Objects Chinese Academy of SciencesKunming 650216China International Centre of Supernovae Yunnan Key LaboratoryKunming 650216China South-Western Institute for Astronomy Research Yunnan UniversityKunming 650500China

The Multi-channel Photometric Survey Telescope(Mephisto)is a real-time,three-color photometric system designed to capture the color evolution of stars and transients *** telescope system can be crucial in cosmological distance measurements of low-redshift(low-z,z■0.1)Type Ia supernovae(SNe Ia).To optimize the capabilities of this instrument,we perform a comprehensive simulation study before its official operation is scheduled to *** considering the impact of atmospheric extinction,weather conditions,and the lunar phase at the observing site involving the instrumental features,we simulate light curves of SNe Ia obtained by *** best strategy in the case of SN Ia cosmology is to take the image at an exposure time of 130 s with a cadence of 3 *** this condition,Mephisto can obtain hundreds of high-quality SNe Ia to achieve a distance measurement better than 4.5%.Given the on-time spectral classification and monitoring of the Lijiang 2.4 m Telescope at the same observatory,Mephisto,in the whole operation,can significantly enrich the well-calibrated sample of supernovae at low-z and improve the calibration accuracy of high-z SNe Ia.

关键词： (stars:)supernovae:general (cosmology:)cosmological parameters telescopes

Implementation of integrated nonlocal sensing for object shape and rotational speed

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Science China(Physics,Mechanics & Astronomy) 2024年第7期67卷 6-12页

作者： zhenyu Guo Yunlong wang Zehong Chang Jiawei wang Junliang Jia Pei Zhang Ministry of Education Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter Shaanxi Province Key Laboratory of Quantum Information and Quantum Optoelectronic DevicesSchool of PhysicsXi’an Jiaotong UniversityXi’an 710049China

The expeditious acquisition of information pertaining to objects through the utilization of quantum technology has been a perennial issue of *** far,the efficient utilization of information from dynamic objects with limited resources remains a significant ***,we realize a nonlocal integrated sensing of the object's amplitude and phase information by combining digital spiral imaging with the correlated orbital angular momentum *** amplitude information is utilized for object identification,while the phase information enables us to determine the rotational *** demonstrate the nonlocal identification of a rotating object's shape,irrespective of its rotational symmetry,and introduce the concept of the correlated rotational Doppler effect,establishing a fundamental connection between this effect and the classical rotational Doppler effect,i.e.,that both rely on extracting crucial information from the spiral spectrum of *** present study highlights a promising pathway towards the realization of quantum remote sensing and imaging.

关键词： digital spiral imaging orbital angular momentum correlated rotational Doppler effect

An Information-Based Elite-Guided Evolutionary Algorithm for Multi-Objective Feature Selection

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 264-266页

作者： Ziqian wang Shangce Gao zhenyu Lei Masaaki Omura the Faculty of Engineering University of ToyamaToyama-shi 930-8555Japan IEEE

Dear Editor, This letter is concerned with the evolution strategy for addressing multi-objective feature selection problems in classification. Previous methods suffer from limitations such as being trapped in local optima and lacking stability. To overcome them, we propose a novel eliteguided mechanism based on information theory. Firstly, an elite solution is generated through a dimension reduction strategy and incorporated to the initialization population.

关键词： stability theory overcome

Reductive lipid nanoparticles loaded with vinorelbine inhibit chemotherapy-induced invasion of cancer cells by modulating ENPP2

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Nano Research 2024年第4期17卷 2886-2898页

作者： Xiaoqi Zhao Xuemeng Guo Mei Pang Weigen Qiu zhenyu Luo Qing Lin Yichao Lu Hang yin Sijie wang Huihui Liu Junlei Zhang Lihua Luo Jian You College of Pharmaceutical Sciences Zhejiang University866 Yuhangtang RoadHangzhou 310058China Hangzhou Institute of Innovative Medicine Zhejiang UniversityHangzhou 310058China

Cancer is a predominant culprit behind worldwide death and accounts for up to 10 million deaths every *** is the primary therapeutic method employed for cancer in clinical settings and is essential in controlling tumor *** the advances in this field,tumor invasion and metastasis during treatment remain a significant cause of treatment ***,the underlying mechanisms involving such a disappointing phenomenon are still not fully ***(VNB)extends the lifespan of many cancer patients in the clinic as an emerging chemotherapy drug approved by Food and Drug Administration(FDA).However,VNB-induced tumor metastasis is still an intractable problem,which may be closely related to the abnormal oxidative stress generated during VNB-mediated ***,the study aims to construct a reductive nanosystem loaded with VNB,called VNB-VNP,to improve cancer cure rates and reduce tumor *** the reductive component vitamin E,VNB-VNP can effectively reduce oxidative stress and significantly outperform free VNB in preventing tumor *** transcriptome analysis shows that VNB-VNP can alleviate the over-expression of ectonucleotide pyrophosphatase/phosphodiesterase 2(ENPP2),which may be the main reason why VNB-VNP can inhibit tumor invasion and ***,the research designs a new platform for VNB treatment,which demonstrates promising efficacy in inhibiting neoplastic progression and identifies a new mechanism associated with VNB-induced tumor metastasis,which may offer several valuable references for enhancing chemotherapy efficacy in clinical anti-tumor therapy.

关键词： chemotherapy vinorelbine tumor Invasion lysophosphatidic acid ectonucleotide pyrophosphatase/phosphodiesterase 2(ENPP2)

Deep Learning Social Network Access Control Model Based on User Preferences

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 1029-1044页

作者： Fangfang Shan Fuyang Li zhenyu wang Peiyu Ji Mengyi wang Huifang Sun School of Computer Science Zhongyuan University of TechnologyZhengzhou450007China Henan Key Laboratory of Cyberspace Situation Awareness Zhengzhou450001China

A deep learning access controlmodel based on user preferences is proposed to address the issue of personal privacy leakage in social ***,socialusers andsocialdata entities are extractedfromthe social networkandused to construct homogeneous and heterogeneous ***,a graph neural networkmodel is designed based on user daily social behavior and daily social data to simulate the dissemination and changes of user social preferences and user personal preferences in the social ***,high-order neighbor nodes,hidden neighbor nodes,displayed neighbor nodes,and social data nodes are used to update user nodes to expand the depth and breadth of user ***,a multi-layer attention network is used to classify user nodes in the homogeneous graph into two classes:allow access and deny *** fine-grained access control problem in social networks is transformed into a node classification problem in a graph neural *** model is validated using a dataset and compared with other methods without losing *** model improved accuracy by 2.18%compared to the baseline method GraphSAGE,and improved F1 score by 1.45%compared to the baseline method,verifying the effectiveness of the model.

关键词： Graph neural networks user preferences access control social network

Intelligent fault diagnosis methods toward gas turbine: A review

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Chinese Journal of Aeronautics 2024年第4期37卷 93-120页

作者： Xiaofeng LIU yingjie CHEN Liuqi XIONG jianhua wang Chenshuang LUO Liming ZHANG Kehuan wang School of Transportation Science and Engineering Beihang UniversityBeijing 100191China Systems Engineering Research Institute China State Shipbuilding CorporationBeijing 100094China

Fault diagnosis plays a significant role in conducting condition-based maintenance and health management for gas turbines(GTs) to improve reliability and reduce costs. Various diagnosis methods developed by modeling engine systems or certain components implement faults detection and diagnosis based on the measurement of systemic parameters deviations. However, these conventional model-based methods are hindered by limitations of inability to handle the nonlinear nature, measurement uncertainty, fault coupling and other implementing problems. Recently, the development of artificial intelligence algorithms has provided an effective solution to the above problems, triggering broad researches for data-driven fault diagnosis methods with better accuracy,dynamic performance, and universality. This paper presents a systematic review of recently proposed intelligent fault diagnosis methods for GT engines, according to the classification of shallow learning methods, deep learning methods and hybrid intelligent methods. Moreover, the principle of typical algorithms, the evolution of enhanced methods, and the assessment of pros and cons are summarized to conclude the present status and look forward to the future in the field of GT fault diagnosis. Possible directions for development in method validation, information fusion, and interpretability of intelligent diagnosis methods are concluded in the end to provide insightful concepts for scholars in related fields.

关键词： Fault diagnosis Health management Gas turbine Artificial intelligence Intelligent diagnosis method

Fake News Detection Based on Cross-Modal Message Aggregation and Gated Fusion Network

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Computers, Materials & Continua 2024年第7期80卷 1521-1542页

作者： Fangfang Shan Mengyao Liu Menghan Zhang zhenyu wang College of Computer Zhongyuan University of TechnologyZhengzhou450007China Henan Key Laboratory of Cyberspace Situation Awareness Zhengzhou450001China

Social media has become increasingly significant in modern society,but it has also turned into a breeding ground for the propagation of misleading information,potentially causing a detrimental impact on public opinion and daily *** to pure text content,multmodal content significantly increases the visibility and share ability of *** has made the search for efficient modality representations and cross-modal information interaction methods a key focus in the field of multimodal fake news *** effectively address the critical challenge of accurately detecting fake news on social media,this paper proposes a fake news detection model based on crossmodal message aggregation and a gated fusion network(MAGF).MAGF first uses BERT to extract cumulative textual feature representations and word-level features,applies Faster Region-based ConvolutionalNeuralNetwork(Faster R-CNN)to obtain image objects,and leverages ResNet-50 and Visual Geometry Group-19(VGG-19)to obtain image region features and global *** image region features and word-level text features are then projected into a low-dimensional space to calculate a text-image affinity matrix for cross-modal message *** gated fusion network combines text and image region features to obtain adaptively aggregated *** interaction matrix is derived through an attention mechanism and further integrated with global image features using a co-attention mechanism to producemultimodal ***,these fused features are fed into a classifier for news *** were conducted on two public datasets,Twitter and *** show that the proposed model achieves accuracy rates of 91.8%and 88.7%on the two datasets,respectively,significantly outperforming traditional unimodal and existing multimodal models.

关键词： Fake news detection cross-modalmessage aggregation gate fusion network co-attention mechanism multi-modal representation

Sustainable all-weather CO2 utilization by mimicking natural photosynthesis in a single material

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National Science Review 2024年第2期11卷 177-187页

作者： Xianjin Shi Yu Huang Ran Long zhenyu wang Liqin wang Junji Cao Gangqiang Zhu Yujie Xiong State Key Laboratory of Loess and Quaternary Geology(SKLLQG) Key Laboratory of Aerosol Chemistry and Physics Institute of Earth EnvironmentChinese Academy of Sciences Center of Excellence in Quaternary Science and Global Change Chinese Academy of Sciences University of Chinese Academy of Sciences Hefei National Research Center for Physical Sciences at the Microscale School of Chemistry and Materials Science and National Synchrotron Radiation Laboratory University of Science and Technology of China Institute of Atmospheric Physics Chinese Academy of Sciences School of Physics and Information Technology Shaanxi Normal University

Solar-driven CO2conversion into hydrocarbon fuels is a sustainable approach to synchronously alleviating the energy crisis and achieving net ***,the dependence of the conversion process on solar illumination hinders its practical application due to the intermittent availability of sunlight at night and on cloudy or rainy ***,we report a model material of Pt-loaded hexagonal tungsten trioxide（Pt/h-WO3） for decoupling light and dark reaction processes,demonstrating the sustainable CO2conversion under dark conditions for the first *** such a material system,hydrogen atoms can be produced by photocatalytic water splitting under solar illumination,stored together with electrons in the h-WO3through the transition of W6+to W5+and spontaneously released to trigger catalytic CO2reduction under dark ***,we demonstrate using natural light that CH4production can persist at night and on rainy days,proving the accomplishment of all-weather CO2conversion via a sustainable way.

关键词： sustainable CO2 utilization artificial photosynthesis all-weather application charge storage

Distributed Matching Theory-Based Task Re-Allocating for Heterogeneous Multi-UAV Edge Computing

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China Communications 2024年第1期21卷 260-278页

作者： Yangang wang Xianglin Wei Hai wang Yongyang Hu Kuang Zhao jianhua Fan College of Communications Engineering Army Engineering University of PLANanjing 210007China The Sixty-Third Research Institute National University of Defense TechnologyNanjing 210007China

Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge ***,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not been fully considered ***,most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function(SF).In this backdrop,this paper formulates the task scheduling problem as a multi-objective task scheduling problem,which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks’completion time and energy *** three coupled goals in a realtime manner with the dynamic arrival of tasks hinders us from adopting existing methods,like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process,or heuristic-based ones that usually incur a long decision-making *** tackle this problem in a distributed manner,we establish a matching theory framework,in which three conflicting goals are treated as the preferences of tasks,SFs and ***,a Distributed Matching Theory-based Re-allocating(DiMaToRe)algorithm is put *** formally proved that a stable matching can be achieved by our *** simulation results show that Di Ma To Re algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.

关键词： edge computing heterogeneity matching theory service function unmanned aerial vehicle