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Research progress on intelligent operation and maintenance of bridges

Journal of Traffic and Transportation Engineering(English Edition) 2024年第2期11卷 173-187页

作者： Wanshui Han Gan Yang Shizhi Chen Kai Zhou xin xu School of Highway Chang'an UniversityXi'an 710064China

In the context of the increasing scale of bridges and the increasing service life of bridges,it is very important to carry out efficient,accurate and intelligent bridge operation and maintenance.In recent years,advanced equipment,technology and intelligent algorithms have developed rapidly.It is necessary to apply advanced equipment and algorithms to bridge operation and maintenance business to facilitate the digitalization and intelligence of bridge operation and maintenance.To grasp the research progress on the bridge intelligent operation and maintenance,this paper summarizes the research progress in recent years from the aspects of intelligent detection equipment and technology,intelligent monitoring equipment and technology,intelligent data analysis,intelligent evaluation and early warning,and intelligent repair and maintenance.According to the review,more and more smart devices have been used to replace human beings to detect dangerous and hidden bridge components.At the same time,image processing,radar and other technologies have been used to analyze component damage more objectively and quantitatively.To solve the shortcomings of traditional sensors such as short life and low robustness,more non-contact measurement methods have been proposed.Scholars have proposed various intelligent algorithms to process the massive amount of bridge health monitoring data to improve the quality of the data.To achieve the rapid perception of bridge status and timely early warning of structural abnormalities,different from traditional theoretical calculations,scholars have tried to use data-driven methods to intelligently evaluate and early warning of bridge structural status.In terms of intelligent repair and maintenance,more intelligent algorithms have been used to optimize structural maintenance strategies and determine the best maintenance time by integrating multisource heterogeneous data.All these provide strong support for the automation,digitization and intelligence of bridge operation and maintenance.

关键词： Bridge engineering Bridge intelligent operation and maintenance Intelligent equipment Technology and algorithms

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Regulation of AMPK activation by extracellular matrix stiffness in pancreatic cancer

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Genes & Diseases 2024年第3期11卷 338-350页

作者： xin xu Yuan Fang Somaira Nowsheen Ye-Xiong Li Zhenkun Lou Min Deng State Key Laboratory of Molecular Oncology and Department of Radiation Oncology National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China Department of General Surgery Shanghai General HospitalShanghai Jiaotong University School of MedicineShanghai 200080China Department of General Surgery Zhongshan HospitalFudan UniversityShanghai 200032China Department of Dermatology University of California San DiegoSan DiegoCA 92093USA Department of Oncology Mayo ClinicRochesterMN 55905USA

The adenosine monophosphate(AMP)-activated protein kinase(AMPK)sits at a cen-tral node in the regulation of energy metabolism and tumor progression.AMPK is best known to sense high cellular ADP or AMP levels,which indicate the depletion of energy stores.Previous studies have shown that the low expression of phosphorylated AMPK is associated with a poor prognosis of pancreatic cancer.In this study,we report that AMPK is also highly sensitive to extracellular matrix(ECM)stiffness.We found that AMPK is activated in cells when cultured under low ECM stiffness conditions and is functionally required for the metabolic switch induced by ECM stiffness.This regulation of AMPK requires the Hippo kinases but not LKB1/CaMKKp.Hippo kinases directly phosphorylate AMPKa at Thr172 to activate AMPK at low ECM stiffness.Furthermore,we found AMPK activity is inhibited in patients with pancreatic ductal adenocarcinoma(PDAC)with high ECM stiffness and is associated with a poor survival outcome.The activation of Hippo kinases by ROCK inhibitor Y-27632 in combination with the mitochondrial inhibitor metformin synergistically activates AMPK and dramatically inhibits PDAC growth.Together,these findings establish a novel model for AMPK regulation by the mechanical properties of ECMs and provide a rationale for simultaneously targeting the ECM stiffness-Hippo kinases-AMPK signaling and low glucose-LKB1-AMPK signaling pathways as an effective therapeutic strategy against PDAC.

关键词： AMPKactivity Cellularmetabolic switch ECM stiffness Hippokinase signaling Pancreaticductal adenocarcinoma

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A deep Koopman operator-based modelling approach for long-term prediction of dynamics with pixel-level measurements

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 178-196页

作者： Yongqian Xiao Zixin Tang xin xu xinglong Zhang Yifei Shi College of Intelligence Science and Technology National University of Defense TechnologyChangshaChina

Although previous studies have made some clear leap in learning latent dynamics from high-dimensional representations,the performances in terms of accuracy and inference time of long-term model prediction still need to be improved.In this study,a deep convolutional network based on the Koopman operator(CKNet)is proposed to model non-linear systems with pixel-level measurements for long-term *** adopts an autoencoder network architecture,consisting of an encoder to generate latent states and a linear dynamical model(i.e.,the Koopman operator)which evolves in the latent state space spanned by the encoder.The decoder is used to recover images from latent states.According to a multi-step ahead prediction loss function,the system matrices for approximating the Koopman operator are trained synchronously with the autoencoder in a mini-batch manner.In this manner,gradients can be synchronously transmitted to both the system matrices and the autoencoder to help the encoder self-adaptively tune the latent state space in the training process,and the resulting model is time-invariant in the latent space.Therefore,the proposed CKNet has the advantages of less inference time and high accuracy for long-term prediction.Experiments are per-formed on OpenAI Gym and Mujoco environments,including two and four non-linear forced dynamical systems with continuous action spaces.The experimental results show that CKNet has strong long-term prediction capabilities with sufficient precision.

关键词： deep neural networks image motion analysis image sequences sequential estimation

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Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 157-169页

作者： Rui Wang Zhiming Zhou Kaiwen Li Tao Zhang Ling Wang xin xu Xiangke Liao IEEE the Xiangjiang Laboratory and the College of Systems Engineering National University of Defense TechnologyChangsha 410073China the Institute of Automation Chinese Academy of SciencesBeijing 100190China the College of Systems Engineering National University of Defense TechnologyChangsha 410073 the Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology Changsha 410073China the Department of Automation Tsinghua UniversityBeijing 100084China the College of Intelligence Science and Technology National University of Defense TechnologyChangsha 410073China the College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China

Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex problems.Given the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.

关键词： Branch-and-bound(B&B) combinatorial optimization deep learning graph neural network imitation learning

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TP-PROFILE: Monitoring the Thermodynamic Structure of the Troposphere over the Third Pole

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Advances in Atmospheric Sciences 2024年第6期41卷 1264-1277页

作者： xuelong CHEN Yajing LIU Yaoming MA Weiqiang MA Xiangde xu xinghong CHENG Luhan LI xin xu Binbin WANG Land-Atmosphere Interaction and its Climatic Effects Group State Key Laboratory of Tibetan Plateau Earth SystemEnvironment and Resources(TPESER)Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China National Observation and Research Station for Qomolongma Special Atmospheric Processes and Environmental Changes Dingri 858200China China-Pakistan Joint Research Center on Earth Sciences Chinese Academy of SciencesIslamabad 45320Pakistan College of Atmospheric Science Lanzhou UniversityLanzhou 730000China Kathmandu Center of Research and Education Chinese Academy of SciencesBeijing 100101China State Key Laboratory of Disastrous Weather China Academy of Meteorological SciencesBeijing 100081China

Ground-based microwave radiometers(MWRs)operating in the K-and V-bands(20–60 GHz)can help us obtain temperature and humidity profiles in the troposphere.Aside from some soundings from local meteorological observatories,the tropospheric atmosphere over the Tibetan Plateau(TP)has never been continuously observed.As part of the Chinese Second Tibetan Plateau Scientific Expedition and Research Program(STEP),the Tibetan Plateau Atmospheric Profile(TPPROFILE)project aims to construct a comprehensive MWR troposphere observation network to study the synoptic processes and environmental changes on the TP.This initiative has collected three years of data from the MWR network.This paper introduces the data information,the data quality,and data downloading.Some applications of the data obtained from these MWRs were also demonstrated.Our comparisons of MWR against the nearest radiosonde observation demonstrate that the TP-PROFILE MWR system is adequate for monitoring the thermal and moisture variability of the troposphere over the TP.The continuous temperature and moisture profiles derived from the MWR data provide a unique perspective on the evolution of the thermodynamic structure associated with the heating of the TP.The TP-PROFILE project reveals that the low-temporal resolution instruments are prone to large uncertainties in their vapor estimation in the mountain valleys on the TP.

关键词： microwave radiometer thermodynamic structure vertical profile Tibetan Plateau

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Production traits and fertility of reciprocal hybrids between Argopecten irradians irradians and A.i.concentricus

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Journal of Oceanology and Limnology 2024年第1期42卷 304-315页

作者： Jinjing WANG Junhao NING Xia LU Min CHEN Guilong LIU xin xu Quanchao WANG He xu Chunde WANG Research and Development Center for Efficient Utilization of Coastal Bioresources Yantai Institute of Coastal Zone ResearchChinese Academy of SciencesYantai 264003China College of Marine Science and Engineering Qingdao Agricultural UniversityQingdao 266109China University of Chinese Academy of Sciences Beijing 100049China Yantai Spring-Sea AquaSeed Co. Ltd.Yantai 264006China Jiangsu Baoyuan Biotechnology Co. Ltd.Lianyungang 222144China Jiangsu Haitai MariTech Co. Ltd.Lianyungang 222144China

The two bay scallop subspecies,Argopecten irradians irradians(NN)and A.i.concentricus(SS),are fast growing and major cultured bivalves in China.However,their relatively small sizes and decreasing production traits caused by long-term inbreeding have been major concerns to the industry in the last two decades.Hybridization between the two bay scallop subspecies may provide a new approach to breed a new variety with superior production traits for the industry.For this end,in this study,we hybridized the two bay scallop subspecies in order to obtain a new strain that incorporates the genes of both subspecies.No significant difference was found in fertilization rate,hatching rate and metamorphosis rate between the purebred and crossbred cohorts(NN♀×SS♂,denoted as NS;SS♀×NN♂,denoted as SN).Both mating strategy(intra-vs.inter-population crosses)and egg origin had significant effects on growth and survival at the larval stage.Heterosis was observed in the crossbred and was more pronounced in older stages.Genetic diversity of the reciprocal hybrids,especially that of SN,was increased compared with the purebred cohorts.Almost all hybrids were completely fertile and able to reproduce by selffertilization or by backcrossing with either parent.Apparently,male sterile individuals whose gonads were fully occupied by the ovary part at mature stage were found in the hybrids for the first time.The hybrids,especially SN,may provide precious germplasm resources for the production of ternary hybrids with the Peruvian scallop,A.purpuratus.

关键词： bay scallop hybridization growth survival heterosis fertility ternary hybrids

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Experimental Study on the Performance of ORC System Based on Ultra-Low Temperature Heat Sources

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Energy Engineering 2024年第1期121卷 145-168页

作者： Tianyu Zhou Liang Hao xin xu Meng Si Lian Zhang College of Mechanical Engineering Tianjin University of Science&TechnologyTianjin300222China School of Energy Engineering Tianjin Sino-German University of Applied SciencesTianjin300350China Tianjin“The Belt and Road”Joint Laboratory Tianjin Sino-German University of Applied SciencesTianjin300350China

This paper discussed the experimental results of the performance of an organic Rankine cycle(ORC)system with an ultra-low temperature heat source.The low boiling point working medium R134a was adopted in the system.The simulated heat source temperature(SHST)in this work was set from 39.51°C to 48.60°C by the simulated heat source module.The influence of load percentage of simulated heat source(LPSHS)between 50%and 70%,the rotary valve opening(RVO)between 20%and 100%,the resistive load between 36Ωand 180Ωor the no-load of the generator,as well as the autumn and winter ambient temperature on the system performance were studied.The results showed that the stability of the system was promoted when the generator had a resistive load.The power generation(PG)and generator speed(GS)of the system in autumn were better than in winter,but the expander pressure ratio(EPR)was lower than in winter.Keep RVO unchanged,the SHST,the mass flow rate(MFR)of the working medium,GS,and the PG of the system increased with the increasing of LPSHS for different generator resistance load values.When the RVO was 60%,LPSHS was 70%,the SHST was 44.15°C and the resistive load was 72Ω,the highest PG reached 15.11 W.Finally,a simulation formula was obtained for LPSHS,resistance load,and PG,and its correlation coefficient was between 0.9818 and 0.9901.The formula can accurately predict the PG.The experimental results showed that the standard deviation between the experimental and simulated values was below 0.0792,and the relative error was within±5%.

关键词： ORC load percentage of simulated heat source resistive load rotary valve opening power generation

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Deep reinforcement learning using least-squares truncated temporal-difference

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 425-439页

作者： Junkai Ren Yixing Lan xin xu Yichuan Zhang Qiang Fang Yujun Zeng College of Intelligence Science and Technology National University of Defense TechnologyChangshaChina State Key Laboratory of Astronautic Dynamics Xi'an Satellite Control CenterXi'anChina

Policy evaluation(PE)is a critical sub-problem in reinforcement learning,which estimates the value function for a given policy and can be used for policy improvement.However,there still exist some limitations in current PE methods,such as low sample efficiency and local convergence,especially on complex tasks.In this study,a novel PE algorithm called Least-Squares Truncated Temporal-Difference learning(LST2D)is proposed.In LST2D,an adaptive truncation mechanism is designed,which effectively takes advantage of the fast convergence property of Least-Squares Temporal Difference learning and the asymptotic convergence property of Temporal Difference learning(TD).Then,two feature pre-training methods are utilised to improve the approximation ability of LST2D.Furthermore,an Actor-Critic algorithm based on LST2D and pre-trained feature representations(ACLPF)is proposed,where LST2D is integrated into the critic network to improve learning-prediction efficiency.Comprehensive simulation studies were conducted on four robotic tasks,and the corresponding results illustrate the effectiveness of LST2D.The proposed ACLPF algorithm outperformed DQN,ACER and PPO in terms of sample efficiency and stability,which demonstrated that LST2D can be applied to online learning control problems by incorporating it into the actor-critic architecture.

关键词： Deep reinforcement learning policy evaluation temporal difference value function approximation

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Expert consensus on irrigation and intracanal medication in root canal therapy

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International Journal of Oral Science 2024年第1期16卷 26-35页

作者： Xiaoying Zou xin Zheng Yuhong Liang Chengfei Zhang Bing Fan Jingping Liang Junqi Ling Zhuan Bian Qing Yu Benxiang Hou Zhi Chen Xi Wei Lihong Qiu Wenxia Chen Wenxi He xin xu Liuyan Meng Chen Zhang Liming Chen Shuli Deng Yayan Lei Xiaoli Xie Xiaoyan Wang Jinhua Yu Jin Zhao Song Shen xuedong Zhou Lin Yue Department of Cariology and Endodontology Peking University School and Hospital of Stomatology&National Center of Stomatology&National Clinical Research Center for Oral Diseases&National Engineering Laboratory for Digital and Material Technology of Stomatology&Beijing Key Laboratory of Digital Stomatology&Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health&NMPA Key Laboratory for Dental MaterialsBeijingChina Center of Stomatology Peking University HospitalBeijingChina State Key Laboratory of Oral Diseases&National Center for Stomatology&National Clinical Research Center for Oral Diseases&West China Hospital of Stomatology Sichuan UniversityChengduChina Department of Emergency Peking University School and Hospital of Stomatology&National Center of Stomatology&National Clinical Research Center for Oral Diseases&National Engineering Laboratory for Digital and Material Technology of Stomatology&Beijing Key Laboratory of Digital Stomatology&Research Center of Engineering and Technology for Computerized Dentistry Ministry of Health&NMPA Key Laboratory for Dental MaterialsBeijingChina Restorative Dental Sciences EndodonticsFaculty of DentistryThe University of Hong KongPok Fu LamHong Kong SARChina State Key Laboratory of Oral&Maxillofacial Reconstruction and Regeneration Key Laboratory of Oral Biomedicine Ministry of EducationHubei Key Laboratory of StomatologySchool&Hospital of StomatologyWuhan UniversityWuhanChina Department of Endodontics Shanghai Ninth People’s HospitalShanghai Jiao Tong University School of MedicineCollege of StomatologyShanghai Jiao Tong UniversityNational Clinical Research Center for Oral DiseasesNational Center for StomatologyShanghai Key Laboratory of StomatologyShanghaiChina Department of Operative Dentistry and Endodontics Hospital of StomatologyGuanghua School of StomatologySun Yat-Sen University&Guangdong Provincial Key Laboratory of StomatologyGuangzhouChina State Key Laboratory of Oral&Maxillofacial Reconstruction and R

Chemical cleaning and disinfection are crucial steps for eliminating infection in root canal treatment. However, irrigant selection or irrigation procedures are far from clear. The vapor lock effect in the apical region has yet to be solved, impeding irrigation efficacy and resulting in residual infections and compromised treatment outcomes.

关键词： treatment irrigation Expert

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Munabulake ophiolitic mélange:Implication for the evolution history of the north branch of the Proto-Tethys ocean

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Geoscience Frontiers 2024年第1期15卷 354-373页

作者： Changfeng Liu Wencan Liu Baoying Ye Zixian Zhao He Su xin xu China University of Geosciences(Beijing) Beijing 100083China Experimental School of Beijing Ritan High School Beijing 100123China The Key Laboratory of Orogenic Belts and Crustal Evolution Ministry of EducationSchool of Earth and Space SciencesPeking UniversityBeijing 100871China

One of the ophiolites that record the Proto-Tethys Ocean’s episodic closure is the Munabulake ophiolitic mélange,which is situated in the middle of the Kunlun-Qaidam and Altun-Qilian blocks.Detailed field mapping revealed that the Munabulake ophiolitic mélange comprises local(ultramafic rocks,basalts,andesites,gabbros,diorites,and plagiogranites)and exotic(marble,gneiss,schist,and amphibolite)blocks,many of which are in the schist matrix(Qimantage Group).Based on geochronological,geochemical,and petrological observations,the mafic rocks in the Munabulake ophiolitic mélange can be categorized into three categories:498-Ma OIB-like gabbros,468-Ma Hawaiian alkaline basalt-like dolerite and pillow basaltic slices,and 428 Ma massive SSZ-like ultramafic rocks.The 501-452 Ma I-type granites exhibit arc affinities due to the oceanic crust subduction.These findings,along with spatial relationships,suggest that the Early Paleozoic ophiolite complex,island arc rocks,and accretionary complex generated as an intra-oceanic arc system as a result of obduction of the south Altun Ocean’s onto the Central Altun block within a north-directed subduction event.A dextral strike-slip was evident throughout the Early Paleozoic oceanic crust subduction based on the whole set of planar and linear structural data,and the subduction polarity was likely to the north.According to the ophiolitic mélange’s youngest rocks and the existence of 413 Ma granite dykes that are widely exposed in the Munabulake ophiolitic mélange,the Munabulake ophiolitic mélange was most likely emplaced during the Middle Silurian.This Munabulake ophiolitic mélange is similar in age and petrochemical characteristics to the other ophiolites in the South Altun subduction-collision belt,indicating that the Manabulak ophiolite mélange is a westward extension of the Apa-Mangya subduction-collision belt,which formed during the northward subduction of the South Altun Ocean slab during the Early Paleozoic.Thus,the final closing time of the South Altun Ocean is between 413 and 4

关键词： Altun orogenic belt Munabulake Ophiolitic mé lange Early Paleozoic North-dipping subduction

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