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A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

Geodesy and Geodynamics 2024年第1期15卷 100-105页

作者： fei Ye Yunbin yuan State Key Laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan 430077China BeiDou High-precision Satellite Navigation and Location Service Hunan Engineering Research Center Hunan Institute of Geomatics Sciences and TechnologyChangsha 410007China Hunan Continuously Operating Reference Stations(HNCORS)Data Center Hunan Institute of Geomatics Sciences and TechnologyChangsha 410007China

Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

关键词： Stochastic model LS+AR Short-term prediction The earth rotation parameter(ERP) Observation model

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Impairment of Autophagic Flux After Hypobaric Hypoxia Potentiates Oxidative Stress and Cognitive Function Disturbances in Mice

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Neuroscience Bulletin 2024年第1期40卷 35-49页

作者： Shuhui Dai yuan Feng Chuanhao Lu Hongchen Zhang Wenke Ma Wenyu Xie Xiuquan Wu Peng Luo Lei Zhang fei fei zhou fei Xia Li Department of Neurosurgery Xijing HospitalFourth Military Medical UniversityXi'an 710000China National Translational Science Center for Molecular Medicine and Department of Cell Biology Fourth Military Medical UniversityXi'an 710000China Department of Neurosurgery The Central Hospital of BaojiBaoji 721000China Department of Ophthalmology Xijing HospitalFourth Military Medical UniversityXi'an 710000China

Acute hypobaric hypoxic brain damage is a potentially fatal high-altitude sickness.Autophagy plays a critical role in ischemic brain injury,but its role in hypo-baric hypoxia(HH)remains unknown.Here we used an HH chamber to demonstrate that acute HH exposure impairs autophagic activity in both the early and late stages of the mouse brain,and is partially responsible for HH-induced oxidative stress,neuronal loss,and brain damage.The autophagic agonist rapamycin only promotes the initiation of autophagy.By proteome analysis,a screen showed that protein dynamin2(DNM2)potentially regulates autophagic flux.Overexpression of DNM2 significantly increased the formation of autolysosomes,thus maintaining autophagic flux in combination with rapamycin.Furthermore,the enhancement of autophagic activity attenuated oxidative stress and neurological deficits after HH exposure.These results contribute to evidence supporting the conclusion that DNM2-mediated autophagic flux represents a new therapeutic target in HH-induced brain damage.

关键词： Autophagy-Proteomics Oxidative stress Hypobaric hypoxia-Brain injury

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Progress of semitransparent emerging photovoltaics for building integrated applications

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Green Energy & Environment 2024年第6期9卷 992-1015页

作者： Zhisheng zhou Zhangyu yuan Zhipeng Yin Qifan Xue Ning Li fei Huang State Key Laboratory of Luminescent Materials and Devices School of Materials Science and EngineeringSouth China University of TechnologyGuangzhou510640China Pazhou Lab Guangzhou510320China

With the rapid development of emerging photovoltaics technology in recent years,the application of building-integrated photovoltaics(BIPVs)has attracted the research interest of photovoltaic communities.To meet the practical application requirements of BIPVs,in addition to the evaluation indicator of power conversion efficiency(PCE),other key performance indicators such as heat-insulating ability,average visible light transmittance(AVT),color properties,and integrability are equally important.The traditional Si-based photovoltaic technology is typically limited by its opaque properties for application scenarios where transparency is required.The emerging PV technologies,such as organic and perovskite photovoltaics are promising candidates for BIPV applications,owing to their advantages such as high PCE,high AVT,and tunable properties.At present,the PCE of semitransparent perovskite solar cells(ST-PSCs)has attained 14%with AVT of 22–25%;for semitransparent organic solar cells(ST-OSCs),the PCE reached 13%with AVT of almost 40%.In this review article,we summarize recent advances in material selection,optical engineering,and device architecture design for high-performance semitransparent emerging PV devices,and discuss the application of optical modeling,as well as the challenges of commercializing these semitransparent solar cells for building-integrated applications.

关键词： Building integrated photovoltaics Emerging photovoltaics Semitransparent solar cells Perovskite solar cells Organic solar cells

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Southern Hemisphere Volcanism Triggered Multi-year La Niñas during the Last Millennium

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Advances in Atmospheric Sciences 2024年第4期41卷 587-592页

作者： Shangrong zhou fei LIU School of Atmospheric Sciences Sun Yat-Sen University Key Laboratory of Tropical Atmosphere-Ocean System Ministry of Educationand Southern Marine Science and Engineering Guangdong LaboratoryZhuhai 519082China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD) Nanjing University of Information Science and TechnologyNanjing 210044China

To explain the recent three-year La Niña event from 2020 to 2022,which has caused catastrophic weather events worldwide,Fasullo et al.(2023)demonstrated that the increase in biomass aerosol resulting from the 2019-20 Australian wildfire season could have triggered this multi-year La Niña.Here,we present compelling evidence from paleo-proxies,utilizing a substantial sample size of 26 volcanic eruptions in the Southern Hemisphere(SH),to support the hypothesis that ocean cooling in the SH can lead to a multi-year La Niña event.This research highlights the importance of focusing on the Southern Ocean,as current climate models struggle to accurately simulate the Pacific response driven by the Southern Ocean.

关键词： volcanic eruptions multi-year La Niñas Australian wildfire southern ocean cooling

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Deep-reinforcement-learning-based UAV autonomous navigation and collision avoidance in unknown environments

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Chinese Journal of Aeronautics 2024年第3期37卷 237-257页

作者： fei WANG Xiaoping ZHU zhou zhou Yang TANG School of Astronautics Northwestern Polytechnical UniversityXi’an 710072China School of Aeronautics Northwestern Polytechnical UniversityXi’an 710072China

In some military application scenarios,Unmanned Aerial Vehicles(UAVs)need to perform missions with the assistance of on-board cameras when radar is not available and communication is interrupted,which brings challenges for UAV autonomous navigation and collision avoidance.In this paper,an improved deep-reinforcement-learning algorithm,Deep Q-Network with a Faster R-CNN model and a Data Deposit Mechanism(FRDDM-DQN),is proposed.A Faster R-CNN model(FR)is introduced and optimized to obtain the ability to extract obstacle information from images,and a new replay memory Data Deposit Mechanism(DDM)is designed to train an agent with a better performance.During training,a two-part training approach is used to reduce the time spent on training as well as retraining when the scenario changes.In order to verify the performance of the proposed method,a series of experiments,including training experiments,test experiments,and typical episodes experiments,is conducted in a 3D simulation environment.Experimental results show that the agent trained by the proposed FRDDM-DQN has the ability to navigate autonomously and avoid collisions,and performs better compared to the FRDQN,FR-DDQN,FR-Dueling DQN,YOLO-based YDDM-DQN,and original FR outputbased FR-ODQN.

关键词： Faster R-CNN model Replay memory Data Deposit Mechanism(DDM) Two-part training approach Image-based Autonomous Navigation and Collision Avoidance(ANCA) Unmanned Aerial Vehicle(UAV)

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Translation machinery: the basis of translational control

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Journal of Genetics and Genomics 2024年第4期51卷 367-378页

作者： Shu yuan Guilong zhou Guoyong Xu State Key Laboratory of Hybrid Rice Institute for Advanced Studies(IAS)Wuhan UniversityWuhanHubei 430072China Hubei Hongshan Laboratory WuhanHubei 430070China

Messenger RNA(mRNA)translation consists of initiation,elongation,termination,and ribosome recycling,carried out by the translation machinery,primarily including tRNAs,ribosomes,and translation factors(TrFs).Translational regulators transduce signals of growth and development,as well as biotic and abiotic stresses,to the translation machinery,where global or selective translational control occurs to modulate mRNA translation efficiency(TrE).As the basis of translational control,the translation machinery directly determines the quality and quantity of newly synthesized peptides and,ultimately,the cellular adaption.Thus,regulating the availability of diverse machinery components is reviewed as the central strategy of translational control.We provide classical signaling pathways(e.g.,integrated stress responses)and cellular behaviors(e.g.,liquideliquid phase separation)to exemplify this strategy within different physiological contexts,particularly during hostemicrobe interactions.With new technologies developed,further understanding this strategy will speed up translational medicine and translational agriculture.

关键词： Translational control Ribosome tRNA Translation machinery uORF Phase separation Immune response

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Programmable synthetic receptors:the next-generation of cell and gene therapies

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Signal Transduction and Targeted Therapy 2024年第2期9卷 376-400页

作者： fei Teng Tongtong Cui Li zhou Qingqin Gao Qi zhou Wei Li University of Chinese Academy of Sciences Beijing 101408China State Key Laboratory of Stem Cell and Regenerative Biology Institute of ZoologyChinese Academy of SciencesBeijing 100101China Institute for Stem Cell and Regeneration Chinese Academy of SciencesBeijing 100101China Beijing Institute for Stem Cell and Regenerative Medicine Beijing 100101China

Cell and gene therapies hold tremendous promise for treating a range of difficult-to-treat diseases.However,concerns over the safety and efficacy require to be further addressed in order to realize their full potential.Synthetic receptors,a synthetic biology tool that can precisely control the function of therapeutic cells and genetic modules,have been rapidly developed and applied as a powerful solution.Delicately designed and engineered,they can be applied to finetune the therapeutic activities,i.e.,to regulate production of dosed,bioactive payloads by sensing and processing user-defined signals or biomarkers.This review provides an overview of diverse synthetic receptor systems being used to reprogram therapeutic cells and their wide applications in biomedical research.With a special focus on four synthetic receptor systems at the forefront,including chimeric antigen receptors(CARs)and synthetic Notch(synNotch)receptors,we address the generalized strategies to design,construct and improve synthetic receptors.Meanwhile,we also highlight the expanding landscape of therapeutic applications of the synthetic receptor systems as well as current challenges in their clinical translation.

关键词： synthetic landscape payload

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Homer1a reduces inflammatory response after retinal ischemia/reperfusion injury

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Neural Regeneration Research 2024年第7期19卷 1608-1617页

作者： Yanan Dou Xiaowei fei Xin He Yu Huan Jialiang Wei Xiuquan Wu Weihao Lyu zhou fei Xia Li fei fei Department of Neurosurgery Xijing HospitalAir Force Military Medical UniversityXi’anShaanxi ProvinceChina Department of Ophthalmology Xijing HospitalAir Force Military Medical UniversityXi’anShaanxi ProvinceChina

Elevated intraocular pressure(IOP)is one of the causes of retinal ischemia/reperfusion injury,which results in NRP3 inflammasome activation and leads to visual damage.Homerla is repo rted to play a protective role in neuroinflammation in the cerebrum.However,the effects of Homerla on NLRP3inflammasomes in retinal ischemia/reperfusion injury caused by elevated IOP remain unknown.In our study,animal models we re constructed using C57BL/6J and Homer1^(flox/-)/Homerla^(+/-)/Nestin-Cre^(+/-)mice with elevated IOP-induced retinal ischemia/repe rfusion injury.For in vitro expe riments,the oxygen-glucose deprivation/repe rfusion injury model was constructed with M uller cells.We found that Homerla ove rexpression amelio rated the decreases in retinal thickness and Muller cell viability after ischemia/reperfusion injury.Furthermore,Homerla knockdown promoted NF-κB P65^(Ser536)activation via caspase-8,NF-κB P65 nuclear translocation,NLRP3 inflammasome formation,and the production and processing of interleukin-1βand inte rleukin-18.The opposite results we re observed with Homerla ove rexpression.Finally,the combined administration of Homerla protein and JSH-23 significantly inhibited the reduction in retinal thickness in Homer1^(flox/-)Homer1a^(+/-)/Nestin-Cre^(+/-)mice and apoptosis in M uller cells after ischemia/reperfusion injury.Taken together,these studies demonstrate that Homer1a exerts protective effects on retinal tissue and M uller cells via the caspase-8/NF-KB P65/NLRP3 pathway after I/R injury.

关键词： caspase-8 Homer1a interleukin-18 interleukin-1β intraocular pressure ischemia/reperfusion injury JSH-23 Müller cells NLRP3 nuclear factor-kB p65 retina

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Photonic neuromorphic architecture for tens-of-task lifelong learning

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Light(Science & Applications) 2024年第3期13卷 519-530页

作者： yuan Cheng Jianing Zhang Tiankuang zhou Yuyan Wang Zhihao Xu Xiaoyun yuan Lu Fang Sigma Laboratory Department of Electronic EngineeringTsinghua UniversityBeijing 100084China Beijing National Research Center for Information Science and Technology(BNRist) Beijing 100084China Institute for Brain and Cognitive Science Tsinghua University(THUIBCS)Beijing 100084China

Scalable,high-capacity,and low-power computing architecture is the primary assurance for increasingly manifold and large-scale machine learning tasks.Traditional electronic artificial agents by conventional power-hungry processors have faced the issues of energy and scaling walls,hindering them from the sustainable performance improvement and iterative multi-task learning.Referring to another modality of light,photonic computing has been progressively applied in high-efficient neuromorphic systems.Here,we innovate a reconfigurable lifelong-learning optical neural network(L2 ONN),for highly-integrated tens-of-task machine intelligence with elaborated algorithm-hardware codesign.Benefiting from the inherent sparsity and parallelism in massive photonic connections,L2 ONN learns each single task by adaptively activating sparse photonic neuron connections in the coherent light field,while incrementally acquiring expertise on various tasks by gradually enlarging the activation.The multi-task optical features are parallelly processed by multi-spectrum representations allocated with different wavelengths.Extensive evaluations on freespace and on-chip architectures confirm that for the first time,L2 ONN avoided the catastrophic forgetting issue of photonic computing,owning versatile skills on challenging tens-of-tasks(vision classification,voice recognition,medical diagnosis,etc.)with a single model.Particularly,L2 ONN achieves more than an order of magnitude higher efficiency than the representative electronic artificial neural networks,and 14×larger capacity than existing optical neural networks while maintaining competitive performance on each individual task.The proposed photonic neuromorphic architecture points out a new form of lifelong learning scheme,permitting terminal/edge AI systems with light-speed efficiency and unprecedented scalability.

关键词： life neural versatile

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Improved LS+MAR hybrid method to UT1-UTC ultra-short-term prediction by using first-order-difference UT1-UTC

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Geodesy and Geodynamics 2024年第4期15卷 379-385页

作者： fei Ye Yunbin yuan Bei Dou High-precision Satellite Navigation and Location Service Hunan Engineering Research Center Hunan Institute of Geomatics Sciences and Technology State Key Laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and Technology Chinese Academy of Sciences HNCORS Data Center Hunan Institute of Geomatics Sciences and Technology

Accurate ultra-short-term prediction of the Earth rotation parameters(ERP) holds paramount importance for real-time applications, particularly in reference frame conversion. Among them, diurnal rotation(UT1-UTC) which cannot be directly estimated through Global Navigation Satellite System(GNSS)techniques, significantly affects the rapid and ultra-rapid orbit determination of GNSS satellites. Presently, the traditional LS(least squares) + AR(autoregressive) and LS + MAR(multivariate autoregressive)hybrid methods stand as primary approaches for UT1-UTC ultra-short-term predictions(1-10 days). The LS + MAR hybrid method relies on the UT1-UTC and LOD(length of day) series. However, the correlation between LOD and first-order-difference UT1-UTC is stronger than that between LOD and UT1-UTC. In light of this, and with the aid of the first-order-difference UT1-UTC, we propose an enhanced LS + MAR hybrid method to UT1-UTC ultra-short-term prediction. By using the UT1-UTC and LOD data series of the IERS(International Earth Rotation and Reference Systems Service) EOP 14 C04 product, we conducted a thorough analysis and evaluation of the improved method's prediction performance compared to the traditional LS + AR and LS + MAR hybrid methods. According to the numerical results over more than210 days, they demonstrate that, when considering the correlation information between the LOD and the first-order-difference UT1-UTC, the mean absolute errors(MAEs) of the improved LS + MAR hybrid method range from 21 to 934 μs in 1-10 days predictions. In comparison to the traditional LS + AR hybrid method, the MAEs show a reduction of 7-53 μs in 1-10 days predictions, with corresponding improvement percentages ranging from 1 to 28%. Similarly, when compared to the traditional LS + MAR hybrid method, the MAEs have a reduction of 5-42 μs in 1-10 days predictions, with corresponding improvement percentages ranging from 4-20%. Additionally, when aided by GNSS-derived LOD data series, the MAEs of improved LS + MAR hybrid method experience fu

关键词： UT1-UTC ultra-short-term prediction Rapid and ultra-rapid products LS+AR and LS+MAR Correlation First-order-difference UT1-UTC

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