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Neural Regeneration Research 2024年第4期19卷 887-894页

作者： Yifang Wu Jun sun qi Lin Dapeng Wang Jian Hai Department of Neurosurgery Tongji HospitalSchool of MedicineTongji University Department of Pharmacy Institute of Medical SciencesShanghai Jiao Tong University School of Medicine

Upregulation of vascular endothelial growth factor A/basic fibroblast growth factor(VEGFA/b FGF)expression in the penumbra of cerebral ischemia can increase vascular volume,reduce lesion volume,and enhance neural cell proliferation and differentiation,thereby exerting neuroprotective ***,the beneficial effects of endogenous VEGFA/b FGF are limited as their expression is only transiently *** this study,we generated multilayered nanofiber membranes loaded with VEGFA/b FGF using layer-by-layer self-assembly and electrospinning *** found that a membrane containing 10 layers had an ideal ultrastructure and could efficiently and stably release growth factors for more than 1 *** 10-layered nanofiber membrane promoted brain microvascular endothelial cell tube formation and proliferation,inhibited neuronal apoptosis,upregulated the expression of tight junction proteins,and improved the viability of various cellular components of neurovascular units under conditions of oxygen/glucose ***,this nanofiber membrane decreased the expression of Janus kinase-2/signal transducer and activator of transcription-3(JAK2/STAT3),Bax/Bcl-2,and cleaved ***,this nanofiber membrane exhibits a neuroprotective effect on oxygen/glucose-deprived neurovascular units by inhibiting the JAK2/STAT3 pathway.

关键词： brain ischemia brain microvascular endothelial cell nanofiber membrane neurovascular unit

Deep learning to estimate ocean subsurface salinity structure in the Indian Ocean using satellite observations

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Journal of Oceanology and Limnology 2024年第2期42卷 377-389页

作者： Jifeng qi Guimin sun Bowen XIE Delei LI Baoshu YIN CAS Key Laboratory of Ocean Circulation and Waves Institute of OceanologyChinese Academy of SciencesQingdao 266071China University of Chinese Academy of Sciences Beijing 100049China School of Mathematics and Physics Qingdao University of Science and TechnologyQingdao 266061China CAS Engineering Laboratory for Marine Ranching Institute of OceanologyChinese Academy of SciencesQingdao 266071China

Accurately estimating the ocean subsurface salinity structure(OSSS)is crucial for understanding ocean dynamics and predicting climate *** present a convolutional neural network(CNN)model to estimate the OSSS in the Indian Ocean using satellite data and Argo *** evaluated the performance of the CNN model in terms of its vertical and spatial distribution,as well as seasonal variation of OSSS *** demonstrate that the CNN model accurately estimates the most significant salinity features in the Indian Ocean using sea surface data with no significant differences from Argo-derived ***,the estimation accuracy of the CNN model varies with depth,with the most challenging depth being approximately 70 m,corresponding to the halocline *** of the CNN model’s accuracy in estimating OSSS in the Indian Ocean are also conducted by comparing Argo observations and CNN model estimations along two selected sections and four selected *** results show that the CNN model effectively captures the seasonal variability of salinity,demonstrating its high performance in salinity estimation using sea surface *** analysis reveals that sea surface salinity has the strongest correlation with OSSS in shallow layers,while sea surface height anomaly plays a more significant role in deeper *** preliminary results provide valuable insights into the feasibility of estimating OSSS using satellite observations and have implications for studying upper ocean dynamics using machine learning techniques.

关键词： machine learning convolutional neural network(CNN) ocean subsurface salinity structure(OSSS) Indian Ocean satellite observations

A novel method for determining the resistivity of compressed superconducting materials

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Matter and Radiation at Extremes 2024年第4期9卷 1-3页

作者： Liling sun qi Wu Shu Cai Yang Ding Ho-kwang Mao Center for High Pressure Science and Technology Advanced Research Beijing 100094China Institute of Physics Chinese Academy of SciencesBeijing 100190China

The measurement of resistivity in a compressed material within a diamond anvil cell presents significant *** high-pressure exper-imental setup makes it difficult to directly measure the size changes induced by pressure in the three crystallographic directions of the *** this study,we introduce a novel and effective method that addresses these technical *** method is anticipated to offer a valuable foundation for high-pressure investigations on quantum materials,particularly those with anisotropic layered structures.

关键词： resistivity method foundation

Exploring deep learning for landslide mapping:A comprehensive review

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China Geology 2024年第2期7卷 330-350页

作者： Zhi-qiang Yang Wen-wen qi chong Xu Xiao-yi Shao College of Surveying and Geo-Informatics Tongji UniversityShanghai 200092China National Institute of Natural Hazards Ministry of Emergency ManagementBeijing 100085China Key Laboratory of Compound and Chained Natural Hazards Dynamics Ministry of Emergency Management of ChinaBeijing 100085China

A detailed and accurate inventory map of landslides is crucial for quantitative hazard assessment and land *** methods relying on change detection and object-oriented approaches have been criticized for their dependence on expert knowledge and subjective *** advancements in highresolution satellite imagery,coupled with the rapid development of artificial intelligence,particularly datadriven deep learning algorithms(DL)such as convolutional neural networks(CNN),have provided rich feature indicators for landslide mapping,overcoming previous *** this review paper,77representative DL-based landslide detection methods applied in various environments over the past seven years were *** study analyzed the structures of different DL networks,discussed five main application scenarios,and assessed both the advancements and limitations of DL in geological hazard *** results indicated that the increasing number of articles per year reflects growing interest in landslide mapping by artificial intelligence,with U-Net-based structures gaining prominence due to their flexibility in feature extraction and ***,we explored the hindrances of DL in landslide hazard research based on the above research *** such as black-box operations and sample dependence persist,warranting further theoretical research and future application of DL in landslide detection.

关键词： Landslide Mapping Quantitative hazard assessment Deep learning Artificial intelligence Neural network Big data Geological hazard survery engineering

Triphenylphosphine-Assisted Exsolution Engineering on Ruddlesden-Popper Perovskites for Promoting Oxygen Evolution

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Energy & Environmental Materials 2024年第4期7卷 433-441页

作者： Juan Bai Jing Shang Jun Mei Dongchen qi Ting Liao Ziqi sun School of Chemistry and Physics Queensland University of Technology Centre for Materials Science Queensland University of Technology School of Materials Science and Engineering Shaanxi University of Science and Technology School of Mechanical Medical and Process Engineering Queensland University of Technology

Metal exsolution engineering has been regarded as a promising strategy for activating intrinsically inert perovskite oxide catalysts toward efficient oxygen evolution *** metal exsolution processes on perovskites are often achieved by using the reducing hydrogen gas; however,this is not effective for the relatively stable phase,such as Ruddlesden-Popper perovskite oxides.

关键词： exsolution oxygen evolution perovskite reconstruction Ruddlesden–Popper

Study of three-dimensional spatial diffuse discharge in contact electrode structure applied to air purification

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Plasma Science and Technology 2024年第10期26卷 73-81页

作者： Shuai XU Wenzheng LIU Jiaying qiN Yiwei sun Xitao JIANG qi qi School of Electrical Engineering Beijing Jiaotong UniversityBeijing 100044People’s Republic of China

In this work,based on the role of pre-ionization of the non-uniform electric field and its effect of reducing the collisional ionization coefficient,a diffuse dielectric barrier discharge plasma is formed in the open space outside the electrode structure at a lower voltage by constructing a three-dimensional non-uniform spatial electric field using a contact electrode *** air purification study is also carried ***,a contact electrode structure is constructed using a three-dimensional wire *** distribution characteristics of the spatial electric field formed by this electrode structure are analyzed,and the effects of the non-uniform electric field and the different angles of the vertical wire on the generation of three-dimensional spatial diffuse discharge are ***,the copper foam contact electrode structure is constructed using copper foam material,and the effects of different mesh sizes on the electric field distribution are *** results show that as the mesh size of the copper foam becomes larger,a strong electric field region exists not only on the surface of the insulating layer,but also on the surface of the vertical wires inside the copper foam,i.e.,the strong electric field region shows a three-dimensional ***,as the mesh size increases,the area of the vertical strong electric field also ***,the electric field strength on the surface of the insulating layer gradually ***,the appropriate mesh size can effectively increase the discharge area,which is conducive to improving the air purification ***,a highly permeable stacked electrode structure of multilayer wire-copper foam is *** combination with an ozone treatment catalyst,an air purification device is fabricated,and the air purification experiment is carried out.

关键词： dielectric barrier discharge three-dimensional spatial discharge atmospheric pressure air diffusion discharge air purification

Fracture sealing performance of granular lost circulation materials at elevated temperature:A theoretical and coupled CFD-DEM simulation study

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Petroleum Science 2024年第1期21卷 567-581页

作者： chong Lin qi-Cong Xu Lie-Xiang Han Gao Li Hai He Hong-Ling Zhou Ji-Ping She CCDC Drilling&Production Technology Research Institute Guanghan618300SichuanChina State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation Southwest Petroleum UniversityChengdu610500SichuanChina College of Materials Science and Engineering Chongqing UniversityChongqing400044China State Key Lab of Oil and Gas Reservoir Geology and Exploitation(Chengdu University of Technology) Chengdu610059SichuanChina College of Energy Chengdu University of TechnologyChengdu610059SichuanChina

Lost circulation is a common downhole problem of drilling in geothermal and high-temperature,high-pressure(HTHP)*** circulation material(LCM)is a regular preventive and remedial measure for lost ***,conventional LCMs seem ineffective in high-temperature *** may be due to the changes in the mechanical properties of LCMs and their sealing performance under high-temperature *** understand how high temperature affects the fracture sealing performance of LCMs,we developed a coupled computational fluid dynamics-discrete element method(CFD-DEM)model to simulate the behavior of granular LCMs in *** summarized the literature on the effects of high temperature on the mechanical properties of LCMs and the rheological properties of drilling *** conducted sensitivity analyses to investigate how changing LCM slurry properties affected the fracture sealing efficiency at increasing *** results show that high temperature reduces the size,strength,and friction coefficient of LCMs as well as the drilling fluid ***,softer,and less frictional LCM particles have lower bridging probability and slower bridging *** particles tend to form dual-particle bridges rather than single-particle *** result in a deeper,tighter,but unstable sealing *** drilling fluid viscosity leads to faster and shallower sealing zones.

关键词： Geothermal well drilling HTHP formationLost circulation material CFD-DEM Fracture sealing

Bionic immunoactivator copresenting autophagy promoting and costimulatory molecules for synergistic cancer immunotherapy

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Nano Research 2024年第3期17卷 1710-1724页

作者： Yiwei Peng Yiliang Yang Zhenzhen Yang Datong Gao Jiajia Li qi sun Yitian Du Meng Lin Xianrong qi Beijing Key Laboratory of Molecular Pharmaceutics and New Drug Delivery System School of Pharmaceutical SciencesPeking UniversityBeijing 100191China

Immunotherapy has great promise in improving malignant tumor ***,the efficacy of existing strategies is often limited by the immunosuppressive ***,we demonstrate an in situ bionic immunoactivator,PLT-Bec1/DTA-1,with possessed natural advantages of platelets for tumor recruitment and activation,on which DTA-1(CD357 monoclonal antibody)and Bec1 were tethered as combined immune ***-Bec1/DTA-1,as a self-triggered release repository,can deliver the pre-tethered Bec1 and DTA-1 deeply through the secretion of platelet microparticles(PMPs),thereby cooperate tacitly and exhibit superiority in immune activation of dendritic cells(DCs)and T cells via autophagy inducibility,coupled with glucocorticoid-induced tumor necrosis factor receptor(GITR)-triggered T_(Reg) suppression,remodeled the immunosuppressive network of tumor ***-Bec1/DTA-1 promoted antigen presentation and T cell proliferation,and alleviated the low activity state of bone marrow-derived dendritic cells(BMDCs)in tumor suppressive ***-Bec1/DTA-1 inhibited tumor recurrence(5-and 13-fold lower of control group in tumor volume)and CD8^(+)T/T_(Reg) ratio(6.3-and 8.8-fold *** group)in mouse tumor model after intravenous or subcutaneous ***,PLT-Bec1/DTA-1 prevented tumor colonization in lung through in situ immune activation,and was slightly superior to the combined of Bec1 and *** findings highlight the promise of delivering immunostimulatory payloads via bionic carriers,eliciting automatic in situ activation of effector immune cells in tumor microenvironment for tumor *** these results provide promising prospects into the application of immunoactivator in improving cancer synergistic immunotherapy to overcome the bottlenecks in clinic.

关键词： in situ bionic immunoactivator autophagy glucocorticoid-induced tumor necrosis factor receptor(GITR)agonist platelets and platelet microparticles cancer immunotherapy

Recent advances in switchable surfactants for heavy oil production:A review

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Energy Geoscience 2024年第4期5卷 75-88页

作者： qi Li Lingfei Liu Dejun sun Zhenghe Xu Key Laboratory of Colloid and Interface Chemistry Ministry of EducationSchool of Chemistry and Chemical EngineeringShandong UniversityJinanShandong250100PR China Shenzhen Key Laboratory of Interfacial Science and Engineering of Materials Department of Materials Science and EngineeringSouthern University of Science and TechnologyShenzhenGuangdong518055PR China Key Laboratory of Tertiary Oil Recovery and Oilfield Chemistry PetroChina Dagang Oilfield CompanyTianjin300280PR China

Surfactants are extensively employed in the cold production of heavy ***,producing heavy oil emulsions using conventional surfactants poses a challenge to spontaneous demulsification,necessitating the addition of demulsifiers for oil-water *** inevitably increases the exploitation cost and environmental pollution *** surfactants have garnered much attention due to their dual capabilities of underground heavy oil emulsification and surface *** study focuses on the fundamental working principles and classification of novel switchable surfactants for oil displacement developed in recent *** offers a comprehensive overview of the latest advances in the applications of switchable surfactants in the fields of enhanced oil recovery(EOR),oil sand washing,and oil-water ***,it highlights the existing challenges and future development directions of switchable surfactants for heavy oil recovery.

关键词： Heavy oil Switchable surfactant Cold production Emulsification Demulsification

Efficient and robust CNN-LSTM prediction of flame temperature aided light field online tomography

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Science China(Technological Sciences) 2024年第1期67卷 271-284页

作者： NIU ZhiTian qi Hong sun AnTai REN YaTao HE MingJian GAO BaoHai School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China Key Laboratory of Aerospace Thermophysics Ministry of Industry and Information TechnologyHarbin 150001China

Light field tomography,an optical combustion diagnostic technology,has recently attracted extensive attention due to its easy implementation and ***,the conventional iterative methods are high data throughput,low efficiency and time-consuming,and the existing machine learning models use the radiation spectrum information of the flame to realize the parameter field measurement at the current *** is still an offline measurement and cannot realize the online prediction of the instantaneous structure of the actual turbulent combustion *** this work,a novel online prediction model of flame temperature instantaneous structure based on deep convolutional neural network and long short-term memory(CNN-LSTM)is *** method uses the characteristics of local perception,shared weight,and pooling of CNN to extract the threedimensional(3D)features of flame temperature and outgoing radiation ***,the LSTM is used to comprehensively utilize the ten historical time series information of high dynamic combustion flame to accurately predict 3D temperature at three future moments.A chaotic time-series dataset based on the flame radiation forward model is built to train and validate the performance of the proposed CNN-LSTM *** is proven that the CNN-LSTM prediction model can successfully learn the evolution pattern of combustion flame and make accurate predictions.

关键词： temperature prediction convolutional neural network long short-term memory light field imaging online tomography