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Separation of the ionospheric and thermospheric contributions in the data from the Triple Ionosophere Photo Meter onboard the Feng-Yun 3E satellite

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Science China Earth Sciences 2025年第1期68卷 172-184页

作者： Fang JIANG Tian MAO Jin-Song WANG Xiu-Qing HU Xiao-Xin ZHANG liping fu Nan JIA Tianfang WANG National Space Science Center Chinese Academy of Sciences Beijing Key Laboratory of Space Environment Exploration Key Laboratory of Environmental Space Situation Awareness Technology National Satellite Meteorological Center China Meteorological Administration

The Triple Ionosphere Photo Meter （TRIPM） is a far ultraviolet nadir-view photometer that is onboard the secondgeneration,polar-orbiting Chinese meteorological satellite Feng-Yun 3E （FY-3E）,which was launched on July 5,*** has three channels,and each is used to measure different types of emissions:（1） 135.6 nm airglow produced by the recombination of the O+ions and electrons in the absence of sunlight （nighttime channel）;（2） 135.6 nm airglow from the OI when sunlight is present （daytime/dusk-dawn 135.6 nm channel）;and （3） Airglow in the N2LBH of the TRIPM （daytime/dusk-dawn N2LBH channel）.FY-3E is a satellite operating in the early morning ***,the data are mostly distributed on the dawndusk side or at times when the solar zenith angle is relatively *** this study,combined with simulation calculations,the data are *** further explore the application value of the data products,a model is used to separate the ionospheric radiative recombination contribution from the thermosphere photoelectron impact excitation contribution in the data from the daytime/dusk-dawn 135.6 nm *** approach not only improves the accuracy of O/N2derived from the 135.6 nm channel and N2LBH channel but also provides the ionospheric 135.6 nm radiance at the same time as the *** results show that the 135.6 nm radiance originating from the combination of O+and electrons extracted from the measurement data exhibits similar equatorial anomaly peak structure characteristics and seasonal variations as the corresponding GPS total electron content （TEC） *** the other hand,the separated 135.6 nm radiance generated from the thermosphere photoelectron collision excitation does not contain radiative recombination contributions;thus,the ionosphere influence is greatly avoided when the O/N2is obtained.

关键词： Far ultraviolet 135.6 nm emission intensity Photoelectron impact excitation Radiative recombination excitation

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Road Safety Performance function Analysis With Visual Feature Importance of Deep Neural Nets

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IEEE/CAA Journal of Automatica Sinica 2020年第3期7卷 735-744页

作者： Guangyuan Pan liping fu Qili Chen Ming Yu Matthew Muresan Department of Civil and Environmental Engineering University of WaterlooON N2L5G1Canada Faculty of Information Technology Beijing University of TechnologyBeijing 100124China Electronic Engineering the Chinese University of Hong KongHong Kong 999077China

Road safety performance function(SPF) analysis using data-driven and nonparametric methods, especially recent developed deep learning approaches, has gained increasing achievements. However, due to the learning mechanisms are hidden in a"black box" in deep learning, traffic features extraction and intelligent importance analysis are still unsolved and hard to *** paper focuses on this problem using a deciphered version of deep neural networks(DNN), one of the most popular deep learning models. This approach builds on visualization, feature importance and sensitivity analysis, can evaluate the contributions of input variables on model's "black box" feature learning process and output decision. Firstly, a visual feature importance(Vi FI) method that describes the importance of input features is proposed by adopting diagram and numerical-analysis. Secondly,by observing the change of weights using Vi FI on unsupervised training and fine-tuning of DNN, the final contributions of input features are calculated according to importance equations for both steps that we proposed. Sequentially, a case study based on a road SPF analysis is demonstrated, using data collected from a major Canadian highway, Highway 401. The proposed method allows effective deciphering of the model's inner workings and allows the significant features to be identified and the bad features to be eliminated. Finally, the revised dataset is used in crash modeling and vehicle collision prediction, and the testing result verifies that the deciphered and revised model achieves state-of-theart performance.

关键词： Deep learning deep neural network(DNN) feature importance road safety performance function

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Effects of winter weather on traffic operations and optimization of signalized intersections

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Journal of Traffic and Transportation Engineering(English Edition) 2019年第2期6卷 196-208页

作者： Zhengyang Lu Tae J.Kwon liping fu Big Data Research Center Jianghan University Department of Civil and Environmental Engineering University of Alberta Department of Civil and Environmental Engineering University of Waterloo Intelligent Transportation Systems Research Center Wuhan University of Technology

Adverse winter weather has always been a cause of traffic congestion and road *** mitigate the negative impacts of winter weather, transportation agencies are under increasing pressure to introduce weather responsive traffic management ***, most traffic signal control systems are designed for normal weather conditions and are therefore suboptimal regarding efficiency and safety for controlling traffic during winter snow events due to changes in traffic patterns and driver behaviors. The main objective of this research is to explore how to modify pre-timed traffic signal control parameters under adverse weather conditions to increase traffic efficiency and road *** research consists of two main components. First, we examine the impacts of winter weather on three key traffic parameters, i.e., saturation flow rate, start-up lost time, and free flow speed. Secondly, we investigate the potential benefits of implementing weatherspecific signal control plans for uncoordinated intersections as well as coordinated corridors. Two case studies are conducted, each with varying levels of traffic demand and winter event severity, to compare the performance of different signal plans. Evaluation results from both Synchro and VISSIM show that implementing such signal plans is most beneficial for intersection with a medium level of traffic demand. It is also found that the benefit of implementing weather-responsive plans was more compelling at a coordinatedcorridor level than at an uncoordinated-intersection level.

关键词： Signal optimization Inclement weather Traffic simulation Signal coordination

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Delay recovery model for high-speed trains with compressed train dwell time and running time

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Railway Engineering Science 2020年第4期28卷 424-434页

作者： Yafei Hou Chao Wen Ping Huang liping fu Chaozhe Jiang National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong UniversityChengdu 610031China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong UniversityChengdu 610031China Intelligent Transport Systems Center Wuhan University of TechnologyWuhan 430070China

Modeling the application of train operation adjustment actions to recover from delays is of great importance to supporting the decision-making of *** this study,the effects of two train operation adjustment actions on train delay recovery were explored using train operation records from scheduled and actual train ***,the modeling data were sorted to extract the possible influencing factors under two typical train operation adjustment actions,namely the compression of the train dwell time at stations and the compression of the train running time in *** regression methods were then employed to determine the importance of the influencing factors corresponding to the train delay recovery time,namely the delay time,the scheduled supplement time,the running interval,the occurrence time,and the place where the delay occurred,under the two train operation adjustment ***,the gradient-boosted regression tree(GBRT)algorithm was applied to construct a delay recovery model to predict the delay recovery effects of the train operation adjustment actions.A comparison of the prediction results of the GBRT model with those of a random forest model confirmed the better performance of the GBRT prediction model.

关键词： High-speed train Delay recovery Train operation adjustment actions Gradient-boosted regression tree

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Evaluation of alternative criteria for determining the optimal location of RWIS stations

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Journal of Modern Transportation 2013年第1期21卷 17-27页

作者： Tae J. Kwon liping fu Department of Civil and Environmental Engineering University of Waterloo200 University Ave WestWaterlooON N2L 6P4USA School of Transportation and Logistics Southwest Jiaotong University

This article presents a comprehensive framework for determining the location of road weather information system （RWIS） stations over a regional road network. In the proposed methodology, the region is divided into a grid of equal-sized zones which are considered as the minimum spatial unit for allocating a candidate set of RWIS stations. These zones are ranked according to a set of pre-specified criteria that reflect the needs for, and potential benefits from, real-time RWIS, including road surface temperature variability, precipitation, network traffic, and collision patterns. A case study based on the existing RWIS network in the province of Ontario was conducted to illustrate the major features of the proposed method and evaluate the implications of alternative loca- tion selection criteria. The findings of the study suggest that it is feasible to develop a systematic process for locating RWIS stations using an integrated location criterion to capture multiple factors being considered in prac- tice. The study has also revealed the need to establish quantitative models for estimating the benefit of real-time information from RWIS stations, which is the foundation of a cost-benefit-based RWIS location optimization model.

关键词： RWIS Road surface temperature Accidentrate Traffic volume Location selection criteria

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Multicomponent Domino [4＋1＋1] Carbocyclization Providing an Efficient and Regioselective Strategy to Fluoren-9-ones

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Chinese Journal of Chemistry 2013年第6期31卷 737-744页

作者： Ying Li Haiwei Xu liping fu Qingqing Shi Bo Jiang Shujiang Tu School of Chemistry and Chemical Engineering Laboratory of Green Synthetic Chemistry for Functional Materials Jiangsu Normal University Xuzhou Jiangsu 221116 China

Concise and efficient three-component domino [4＋ 1 ＋ 1] carbocyclization to highly substituted fluoren-9-one derivatives promoted by K2CO3 has been developed under microwave irradiation conditions. The direct bis-cyanation and aryl amination residing in fluoren-9-one framework were achieved in a one-pot operation. The reaction proceeds at fast rates and can be finished within 30 min, which makes workup convenient to give good to excellent chemical yields.

关键词： fluoren-9-one synthesis multicomponent reactions carbocyclization regioselectivity microwaveheating

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Vertical microbial profiling of water column reveals prokaryotic communities and distribution features of Antarctic Peninsula

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Acta Oceanologica Sinica 2023年第9期42卷 90-100页

作者： Jiang Li Luying Zhao Xiaoqian Gu Chengxuan Li Qian Zhang liping fu Ao Zhang Marine Biological Resources and Environment Center First Institute of OceanographyMinistry of Natural ResourcesQingdao 266061China Ministry of Natural Resources Key Labatary for Science&Technology of Marine Ecosystems Qingdao 266061China CAS and Shandong Province Key Laboratory of Experimental Marine Biology Center for Ocean Mega-ScienceInstitute of OceanologyChinese Academy of SciencesQingdao 266071China College of Chemical Engineering Qingdao University of Science&TechnologyQingdao 266042China

Prokaryotic diversity and community composition in the water column of eight stations(63 samples) around the Antarctic Peninsula of the Southern Ocean were investigated. Through pyrosequencing of the V3–V4hypervariable regions of the 16S ribosomal RNA gene, we characterized 4 720 089 valid reads representing 48 188operational taxonomic units(OTUs, 97% similarity). The community was dominated by the phyla Pseudomonadota(original name: Proteobacteria, 47%), Oxyphotobacteria(26%), and Bacteroidota(original name: Bacteroidetes, 18%), which comprised an average of 91% of the total OTUs in all samples. The prokaryotic community composition varied vertically within the water column. Water column prokaryotic communities exhibited a clear depth profile, with higher microbial richness and higher diversity observed with increasing water depth. Cluster analysis of the community composition of water column samples exhibited a similar trend with depth. Correlation with environmental factors suggested distinct variation in prokaryotic community composition with changes in depth, salinity, temperature and dissolved oxygen levels. functional prediction showed presence of active nitrogen, sulphur and methane metabolic cycles along the vertical transect of the studied region. These results will improve our knowledge of prokaryotic diversity and community composition at different depth of water column for better understanding of the microbial ecology and nutrient cycles in Antarctic Peninsula region of the Southern Ocean.

关键词： prokaryotic diversity 16S rRNA high-throughput sequencing(HTS) Southern Ocean

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Identification of crash hotspots using kernel density estimation and kriging methods:a comparison

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Journal of Modern Transportation 2015年第2期23卷 93-106页

作者： Lalita Thakali Tae J.Kwon liping fu Department of Civil & Environmental Engineering University of Waterloo School of Transportation and Logistics Southwest Jiaotong University

This paper presents a study aimed at comparing the outcome of two geostatistical-based approaches, namely kernel density estimation （KDE） and kriging, for identifying crash hotspots in a road network. Aiming at locating high-risk locations for potential intervention, hotspot identification is an integral component of any comprehensive road safety management programs. A case study was conducted with historical crash data collected between 2003 and 2007 in the Hennepin County of Min- nesota, U.S. The two methods were evaluated on the basis of a prediction accuracy index （PAI） and a comparison in hotspot ranking. It was found that, based on the PAI measure, the kriging method outperformed the KDE method in its ability to detect hotspots, for all four tested groups of crash data with different times of day. further- more, the lists of hotspots identified by the two methods were found to be moderately different, indicating the im- portance of selecting the right geostatistical method for hotspot identification. Notwithstanding the fact that the comparison study presented herein is limited to one case study, the findings have shown the promising perspective of the kriging technique for road safety analysis.

关键词： Crash hotspots Kernel density Kriging Performance measures

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Injury severity analysis： comparison of multilevel logistic regression models and effects of collision data aggregation

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Journal of Modern Transportation 2016年第1期24卷 73-87页

作者： Taimur Usman liping fu Luis F.Miranda-Moreno Department of Civil & Environmental Engineering University of Waterloo Waterloo ON N2L 3GI Canada School of Transportation and Logistics Southwest Jiaotong University Chengdu 610031 China Department of Civil Engineering & Applied Mechanics McGill University Montreal QC H3A 2K6 Canada

This paper describes an empirical study aiming at identifying the main differences between different logistic regression models and collision data aggregation methods that are commonly applied in road safety literature for modeling collision severity. In particular, the research compares three popular multilevel logistic models （i.e., sequential binary logit models, ordered logit models, and multinomial logit models） as well as three data aggregation methods （i.e., occupant based, vehicle based, and collision based）. Six years of collision data （2001-2006） from 31 highway routes from across the province of Ontario, Canada were used for this analysis. It was found that a multilevel multinomial logit model has the best fit to the data than the other two models while the results obtained from occupant-based data are more reliable than those from vehicle- and collision-based data. More importantly, while generally consistent in terms of factors that were found to be significant between different models and data aggregation methods, the effect size of each factor differ sub- stantially, which could have significant implications forevaluating the effects of different safety-related policies and countermeasures.

关键词： Injury severity - Multilevel logistic regressionmodels Collision data aggregation

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Photometric Redshift Estimates using Bayesian Neural Networks in the CSST Survey

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Research in Astronomy and Astrophysics 2022年第11期22卷 190-206页

作者： Xingchen Zhou Yan Gong Xian-Min Meng Xuelei Chen Zhu Chen Wei Du liping fu Zhijian Luo National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China Science Center for China Space Station Telescope National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China Key Laboratory of Computational Astrophysics National Astronomical ObservatoriesChinese Academy of SciencesBeijing 100101China Center for High Energy Physics Peking UniversityBeijing 100871China Shanghai Key Lab for Astrophysics Shanghai Normal UniversityShanghai 200234China

Galaxy photometric redshift(photoz)is crucial in cosmological studies,such as weak gravitational lensing and galaxy angular clustering *** this work,we try to extract photoz information and construct its probability distribution function(PDF)using the Bayesian neural networks from both galaxy flux and image data expected to be obtained by the China Space Station Telescope(CSST).The mock galaxy images are generated from the Hubble Space Telescope-Advanced Camera for Surveys(HST-ACS)and COSMOS catalogs,in which the CSST instrumental effects are carefully *** addition,the galaxy flux data are measured from galaxy images using aperture *** construct a Bayesian multilayer perceptron(B-MLP)and Bayesian convolutional neural network(B-CNN)to predict photoz along with the PDFs from fluxes and images,*** combine the B-MLP and B-CNN together,and construct a hybrid network and employ the transfer learning techniques to investigate the improvement of including both flux and image *** galaxy samples with signal-to-noise ratio(SNR)>10 in g or i band,we find the accuracy and outlier fraction of photoz can achieve σ_(NMAD)=0.022 and η=2.35% for the B-MLP using flux data only,and σ_(NMAD)=0.022 and η=1.32% for the B-CNN using image data *** Bayesian hybrid network can achieve σ_(NMAD)=0.021 and η=1.23%,and utilizing transfer learning technique can improve results to σ_(NMAD)=0.019 and η=1.17%,which can provide the most confident predictions with the lowest average uncertainty.

关键词： (cosmology:)large-scale structure of universe methods:statistical techniques:image processing

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