As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limite...As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.展开更多
In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed p...In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed panel data from the Yellow River(YR)region from 2013 to 2021 and discovered notable spatial variances in the composite index and coupling coordination of the two systems.Specifically,the downstream region exhibited the highest coupling coordination,while the upstream region had the lowest.We identified that favorable factors such as economic development,innovation,industrial upgrading,and government intervention can bolster the coupling.Our findings provide a valuable framework for promoting DE and HQD in the YR region.展开更多
Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address ...Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.展开更多
This paper investigates the spatial-temporal cooperative guidance problem for multiple flight vehicles without relying on time-to-go information.First,a two-stage cooperative guidance strategy,namely the cooperative g...This paper investigates the spatial-temporal cooperative guidance problem for multiple flight vehicles without relying on time-to-go information.First,a two-stage cooperative guidance strategy,namely the cooperative guidance and the Proportional Navigation Guidance(PNG)stage strategy,is developed to realize the spatial-temporal constraints in two dimensions.At the former stage,two controllers are designed and superimposed to satisfy both impact time consensus and impact angle constraints.Once the convergent conditions are satisfied,the flight vehicles will switch to the PNG stage to ensure zero miss distance.To further extend the results to three dimensions,a planar pursuit guidance stage is additionally imposed at the beginning of guidance.Due to the inde-pendence of time-to-go estimation,the proposed guidance strategy possesses great performance in satisfying complex spatial-temporal constraints even under flight speed variation.Finally,several numerical simulations are implemented to verify the effectiveness and advantages of the proposed results under different scenarios.展开更多
Forest fires pose a significant threat to human life and property,so the utilization of unmanned aircraft systems provides new ways for forest firefighting.Given the constrained load capacities of these aircraft,aeria...Forest fires pose a significant threat to human life and property,so the utilization of unmanned aircraft systems provides new ways for forest firefighting.Given the constrained load capacities of these aircraft,aerial refueling becomes crucial to extend their operational time and range.In order to address the complexities of firefighting missions involving multi-receiver and multi-tanker deployed from various airports,first,a fuel consumption calculation model for aerial refueling scheduling is established based on the receiver path.Then,two distinct methods,including an integrated one and a decomposed one,are designed to address the challenges of establishing refueling airspace and allocating tasks for tankers.Both methods aim to optimize total fuel consumption of the receivers and tankers within the aerial refueling scheduling framework.The optimization problem is established as nonlinear optimization models along with restrictions.The integrated method seamlessly combines refueling rendezvous point scheduling and tanker task allocation into unified process.It has a complete solution space and excels in optimizing total fuel consumption.The decomposed method,through the separation of rendezvous point scheduling and task allocation,achieves a reduced computational complexity.However,this comes at the cost of sacrificing optimality by excluding specific feasible solutions.Finally,numerical simulations are carried out to verify the feasibility and effectiveness of the proposed methods.These simulations yield insights crucial for the practical engineering application of both the integrated and decomposed methods in real-world scenarios.This comprehensive approach aims to enhance the efficiency of forest firefighting operations,mitigating the risks posed by forest fires to human life and property.展开更多
In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.A...In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.展开更多
The spatial and temporal variation of green economic efficiency and its driving factors are of great significance for the construction of high-efficiency and low-consumption green development model and sustainable soc...The spatial and temporal variation of green economic efficiency and its driving factors are of great significance for the construction of high-efficiency and low-consumption green development model and sustainable socio-economic development.The research focused on the Yangtze River Economic Belt(YREB)and employed the miniumum distance to strong efficient frontier DEA(MinDs)model to measure the green economic efficiency of the municipalities in the region between 2008 and 2020.Then,the spatial autocorrelation model was used to analyze the evolution characteristics of its spatial pattern.Finally,Geodetector was applied to reveal the drivers and their interactions on green economic efficiency.It is found that:1)the overall green economic efficiency of the YREB from 2008 to 2020 shows a W-shaped fluctuating upward trend,green economic efficiency is greater in the downstream and smallest in the upstream;2)the spatial distribution of green economic efficiency shows clustering characteristics,with multi-core clustering based on‘city clusters-central cities'becoming more obvious over time;the High-High agglomeration type is mainly clustered in Jiangsu and Zheji-ang,while the Low-Low agglomeration type is clustered in the western Sichuan Plateau area and southwestern Yunnan;3)from input-output factors,whether it is the YREB as a whole or the upper,middle and lower reaches regions,the economic development level,labor input,and capital investment are the leading factors in the spatial-temporal evolution of green economic efficiency,with the com-prehensive influence of economic development level and pollution index being the most important interactive driving factor;4)from so-cio-economic factors,information technology drivers such as government intervention,transportation accessibility,information infra-structure,and Internet penetration are always high impact influencers and dominant interaction factors for green economic efficiency in the YREB and the three major regions in the upper,middle and lower reaches.Accordingly,the article puts forward relevant policy re-commendations in terms of formulating differentiated green transformation strategies,strengthening network leadership and informa-tion technology construction and coordinating multi-factor integrated development,which could provide useful reference for promoting synergistic green economic efficiency in the YREB.展开更多
To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to...To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to measure the resilience of each city from 2003 to 2020.The spatial-temporal evolution characteristics were analyzed using Kernel density estimation,standard deviation ellipse,and spatial Markov chain analysis,and the spatial Tobit model was introduced to discover the influencing factors.The results indicate the following:①Urban resilience in the Chengdu-Chongqing Economic Circle displays an upward trend,with the center of gravity moving to the southwest,and the polarization phenomenon intensifying.②The urban resilience level in a region has certain spatial and geographical dependence,while the probability of urban resilience transfer differs in adjacent cities with different resilience levels.③Urban centrality,economic scale,openness level,and financial development promote urban resilience,whereas government scale significantly inhibits it.Finally,this paper proposes countermeasures and suggestions to improve the urban resilience of the Chengdu-Chongqing Economic Circle.展开更多
The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries an...The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other fields.Furthermore,it is important to construct a digital twin system.However,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted accuracy.In this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)layer.Specifically,we fuse the spatial-temporal graph based on the interrelationship of spatial graphs.Simultaneously,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding methods.Subsequently,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)module.The module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like data.AFSTGCN dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted accuracy.Experiments on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models.展开更多
With the rapid development ofmobile Internet,spatial crowdsourcing has becomemore andmore popular.Spatial crowdsourcing consists of many different types of applications,such as spatial crowd-sensing services.In terms ...With the rapid development ofmobile Internet,spatial crowdsourcing has becomemore andmore popular.Spatial crowdsourcing consists of many different types of applications,such as spatial crowd-sensing services.In terms of spatial crowd-sensing,it collects and analyzes traffic sensing data from clients like vehicles and traffic lights to construct intelligent traffic prediction models.Besides collecting sensing data,spatial crowdsourcing also includes spatial delivery services like DiDi and Uber.Appropriate task assignment and worker selection dominate the service quality for spatial crowdsourcing applications.Previous research conducted task assignments via traditional matching approaches or using simple network models.However,advanced mining methods are lacking to explore the relationship between workers,task publishers,and the spatio-temporal attributes in tasks.Therefore,in this paper,we propose a Deep Double Dueling Spatial-temporal Q Network(D3SQN)to adaptively learn the spatialtemporal relationship between task,task publishers,and workers in a dynamic environment to achieve optimal allocation.Specifically,D3SQNis revised through reinforcement learning by adding a spatial-temporal transformer that can estimate the expected state values and action advantages so as to improve the accuracy of task assignments.Extensive experiments are conducted over real data collected fromDiDi and ELM,and the simulation results verify the effectiveness of our proposed models.展开更多
Highly evolved granite is an important sign of the mature continent crust and closely associated with deposits of rare metals.In this work,the authors undertake systematically zircon U-Pb ages and whole rock elemental...Highly evolved granite is an important sign of the mature continent crust and closely associated with deposits of rare metals.In this work,the authors undertake systematically zircon U-Pb ages and whole rock elemental data for highly evolved granitic intrusions from the Great Xing’an Range(GXR),NE China,to elucidate their discriminant criteria,spatial-temporal distribution,differentiation and geodynamic mecha-nism.Geochemical data of these highly evolved granites suggest that high w(SiO_(2))(>70%)and differentiation index(DI>88)could be quantified indicators,while strong Eu depletion,high TE_(1,3),lowΣREE and low Zr/Hf,Nb/Ta,K/Rb could only be qualitative indicators.Zircon U-Pb ages suggest that the highly evolved gran-ites in the GXR were mainly formed in Late Mesozoic,which can be divided into two major stages:Late Ju-rassic-early Early Cretaceous(162-136 Ma,peak at 138 Ma),and late Early Cretaceous(136-106 Ma,peak at 126 Ma).The highly evolved granites are mainly distributed in the central-southern GXR,and display a weakly trend of getting younger from northwest to southeast,meanwhile indicating the metallogenic potential of rare metals within the central GXR.The spatial-temporal distribution,combined with regional geological data,indicates the highly evolved Mesozoic granites in the GXR were emplaced in an extensional environ-ment,of which the Late Jurassic-early Early Cretaceous extension was related to the closure of the Mongol-Okhotsk Ocean and roll-back of the Paleo-Pacific Plate,while the late Early Cretaceous extension was mainly related to the roll-back of the Paleo-Pacific Plate.展开更多
Considering the nonlinear structure and spatial-temporal correlation of traffic network,and the influence of potential correlation between nodes of traffic network on the spatial features,this paper proposes a traffic...Considering the nonlinear structure and spatial-temporal correlation of traffic network,and the influence of potential correlation between nodes of traffic network on the spatial features,this paper proposes a traffic speed prediction model based on the combination of graph attention network with self-adaptive adjacency matrix(SAdpGAT)and bidirectional gated recurrent unit(BiGRU).First-ly,the model introduces graph attention network(GAT)to extract the spatial features of real road network and potential road network respectively in spatial dimension.Secondly,the spatial features are input into BiGRU to extract the time series features.Finally,the prediction results of the real road network and the potential road network are connected to generate the final prediction results of the model.The experimental results show that the prediction accuracy of the proposed model is im-proved obviously on METR-LA and PEMS-BAY datasets,which proves the advantages of the pro-posed spatial-temporal model in traffic speed prediction.展开更多
As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wet...As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wetland,the Xianghai Wetland,and the Danjiang Wetland in Jilin Province.The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space,and the intensification of land salinization.Zhenlai County and Da an City in the Nenjiang River Basin have sufficient surface water resources,with surface water as the drinking water source.Baicheng City and Tongyu County have scarce surface water resources,and both use groundwater as their domestic water source.The main polluted section in the basin is the Xianghai Reservoir,and the annual water quality evaluation is Class V.However,the water quality of the Tao er River,the main stream of the Nenjiang River,is significantly better than that of the Xianghai Reservoir.In order to better study the water environmental pollution situation in the Nenjiang River basin,monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality.This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development,agricultural pattern transformation,and the promotion of water ecological civilization construction.展开更多
Objective:This study aimed to examine the reliability and validity of the Chinese version of the Behavioral Inhibition System/Behavioral Activation System(BIS/BAS)scales among stroke survivors.Methods:The cross-sectio...Objective:This study aimed to examine the reliability and validity of the Chinese version of the Behavioral Inhibition System/Behavioral Activation System(BIS/BAS)scales among stroke survivors.Methods:The cross-sectional study was conducted at four comprehensive hospitals in Taizhou,Jiangsu,China.A sample of 232 first-ever stroke survivors were recruited from June to August 2023.Validity was examined using face validity and construct validity,which used confirmatory factor analysis(CFA)and known-group analysis.Reliability was evaluated by internal consistency and test-retest reliability.Results:The BIS/BAS scales demonstrated satisfactory face validity.The findings of CFAs supported the original four-factor structure of BAS-reward,BAS-drive,BAS-fun seeking,and BIS with acceptable model fit indices.Discriminative validity,assessed via known-group analysis,indicated that stroke survivors with probable depression had significantly lower mean BAS-reward,BAS-drive,and BAS-fun seeking scores(P<0.001)and a higher mean BIS score(P=0.028)compared to those without probable depression.The internal consistency,measured by Cronbach’s a coefficients for the subscales,ranged from 0.669 to 0.964.Test-retest reliability,assessed using intra-class correlation coefficients,ranged from 0.61 to 0.93.Conclusions:The Chinese version of the BIS/BAS scales could be a reliable and valid instrument for measuring behavioral activation among stroke survivors.展开更多
Since the pioneering work by Broca and Wernicke in the 19th century,who examined individuals with brain lesions to associate them with specific behaviors,it was evident that behaviors are complex and cannot be fully a...Since the pioneering work by Broca and Wernicke in the 19th century,who examined individuals with brain lesions to associate them with specific behaviors,it was evident that behaviors are complex and cannot be fully attributable to specific brain areas alone.Instead,they involve connectivity among brain areas,whether close or distant.At that time,this approach was considered the optimal way to dissect brain circuitry and function.These pioneering efforts opened the field to explore the necessity or sufficiency of brain areas in controlling behavior and hence dissecting brain function.However,the connectivity of the brain and the mechanisms through which various brain regions regulate specific behaviors,either individually or collaboratively,remain largely elusive.Utilizing animal models,researchers have endeavored to unravel the necessity or sufficiency of specific brain areas in influencing behavior;however,no clear associations have been firmly established.展开更多
Magnesium matrix composites with both high strength and ductility have been achieved by introducing pure Ti particles.However,the properties of the surfaces of the composites need to be improved by surface technology,...Magnesium matrix composites with both high strength and ductility have been achieved by introducing pure Ti particles.However,the properties of the surfaces of the composites need to be improved by surface technology,such as micro-arc oxidation(MAO).In this study,we investigated the influence of the Ti-reinforcement phase on coating growth and evolution by subjecting both AZ91 alloy and AZ91/Ti composite to MAO treatment using silicate-based and phosphate-based electrolytes.Results revealed that the Ti-reinforcement phase influenced the MAO process,altering discharge behavior,and leading to a decreased cell voltage.The vigorous discharge of the Ti-reinforcement phase induced the formation of coating discharge channels,concurrently dissolving and oxidizing Ti-reinforcement to produce a composite ceramic coating with TiO2.The MAO coating on the AZ91/Ti composite exhibited a dark blue macromorphology and distinctive local micromorphological anomalies.In silicate electrolyte,a“volcano-like”localized morphology centered on the discharge channel emerged.In contrast,treatment in phosphate-based electrolyte resulted in a coating morphology similar to typical porous ceramic coatings,with visible radial discharge micropores at the reinforcement phase location.Compared to the AZ91 alloy,the coating on the AZ91/Ti composite exhibited lower thickness and higher porosity.MAO treatment reduced the self-corrosion current density of the AZ91/Ti surface by two orders of magnitude.The silicate coating demonstrated better corrosion resistance than the phosphate coating,attributed to its lower porosity.The formation mechanism of MAO coatings on AZ91/Ti composites in phosphate-based and silicate-based electrolytes was proposed.展开更多
The performance of Mg alloys is significantly influenced by the concentrations and solid solution behavior of the alloying elements.In this work,the solid solution behavior of 20 alloying elements in 190 ternary Mg al...The performance of Mg alloys is significantly influenced by the concentrations and solid solution behavior of the alloying elements.In this work,the solid solution behavior of 20 alloying elements in 190 ternary Mg alloy systems at 500℃are systematically investigated.The solid solution behavior of a set of two different alloying elements in Mg alloy systems are suggested to be classified into three categories:inclusivity,exclusivity and proportionality.Inclusivity classification indicates that the two alloying elements are inclusive inα-Mg,increasing the joint solubility of both elements.Exclusivity classification suggests that the two alloying elements have a low joint solid solubility inα-Mg,since they prefer to form stable second phases.For the proportionality classification,the solubility curve of the ternary Mg alloy systems is a straight line connecting the solubility points of the two sub-binary systems.The proposed classification theory was validated by key experiments and the calculation of formation energies.The interaction effects between alloying elements and the preference of formation of second phases are the main factors determining the solid solution behavior classifications.Based on the observed solid solution features of multi-component Mg alloys,principles for alloy design of different types of high-performance Mg alloys were proposed in this work.展开更多
Efficient lubrication of magnesium alloys is a highly challenging topic in the field of tribology.In this study,magnesium silicate hydroxide(MSH)nanotubes with serpentine structures were synthesized.The tribological b...Efficient lubrication of magnesium alloys is a highly challenging topic in the field of tribology.In this study,magnesium silicate hydroxide(MSH)nanotubes with serpentine structures were synthesized.The tribological behavior of AZ91D magnesium alloy rubbed against GCr15 steel was studied under lubricating oil with surface-modified MSH nanotubes as additives.The effects of the concentration,applied load,and reciprocating frequency on the friction and wear of the AZ91D alloy were studied using an SRV-4 sliding wear tester.Results show a decrease of 18.7–68.5%in friction coefficient,and a reduction of 19.4–54.3%in wear volume of magnesium alloy can be achieved by applying the synthetic serpentine additive under different conditions.A suspension containing 0.3 wt.%MSH was most efficient in reducing wear and friction.High frequency and medium load were more conducive to improving the tribological properties of magnesium alloys.A series of beneficial physical and chemical processes occurring at the AZ91D alloy/steel interface can be used to explain friction and wear reduction based on the characterization of the morphology,chemical composition,chemical state,microstructure,and nanomechanical properties of the worn surface.The synthetic MSH,with serpentine structure and nanotube morphology,possesses excellent adsorbability,high chemical activity,and good self-lubrication and catalytic activity.Therefore,physical polishing,tribochemical reactions,and physicalchemical depositions can occur easily on the sliding contacts.A dense tribolayer with a complex composition and composite structure was formed on the worn surface.Its high hardness,good toughness and plasticity,and prominent lubricity resulted in the improvement of friction and wear,making the synthetic MSH a promising efficient oil additive for magnesium alloys under boundary and mixed lubrication.展开更多
This study aims to explore the characteristics of novice teachers’inappropriate behaviors in classroom teaching and their intervention strategies.With the continuous improvement of education quality,novice teachers f...This study aims to explore the characteristics of novice teachers’inappropriate behaviors in classroom teaching and their intervention strategies.With the continuous improvement of education quality,novice teachers face increasing challenges in teaching practice.Their inappropriate behaviors not only affect the classroom atmosphere but may also negatively impact students’learning outcomes.Therefore,researching the characteristics of novice teachers’inappropriate behaviors and their intervention strategies holds significant scientific and social value.This study employs a combination of quantitative and qualitative methods to analyze the behavioral patterns of novice teachers in classroom teaching and proposes corresponding intervention strategies.The results indicate that novice teachers’inappropriate behaviors mainly manifest as poor classroom management,monotonous teaching methods,and insufficient interaction with students.Based on these findings,the study proposes a series of effective intervention strategies,including enhancing teacher training,optimizing teaching design,and promoting positive interactions between teachers and students.The conclusions of the study not only provide practical guidance for educational practice but also point out directions for future research,emphasizing the crucial role of teacher professional development in improving teaching quality.展开更多
The pre-weld heat treatment was carried out to obtain different initial microstructures of the GH4169 superalloy,and then Linear Friction Welding(LFW)was performed.The effect of the pre-weld heat treatment on the micr...The pre-weld heat treatment was carried out to obtain different initial microstructures of the GH4169 superalloy,and then Linear Friction Welding(LFW)was performed.The effect of the pre-weld heat treatment on the microstructure evolution and mechanical properties of the joint was analyzed,and the joint electrochemical corrosion behavior as well as the hot corrosion behavior was studied.The results show that the joint hardness of Base Metal(BM)increases after pre-weld heat treatment,and the strengthening phasesγ′andγ″further precipitate.However,the precipitation phases dissolve significantly in the Weld Zone(WZ)due to the thermal process of LFW.The corrosion resistance in BM is reduced after the pre-weld heat treatment,while it is similar in WZ with a slight decrease.The surface morphology of the BM and WZ can be generally divided into a loose and porous matrix and a scattered oxide particle layer after hot corrosion.The joint cross section exhibits a Cr-depleted zone with the diffusion of Cr to form an oxide film.The corrosion product mainly consists of Fe_(2)O_(3)/Fe_(3)O_(4) as the outer layer and Cr_(2)O_(3) as the inner layer.展开更多
基金supported by the National Natural Science Foundation of China(Nos.U19A2044,42105132,42030609,41975037,and 42105133)the National Key Research and Development Program of China(No.2022YFC3703502)+1 种基金the Plan for Anhui Major Provincial Science&Technology Project(No.202203a07020003)Hefei Ecological Environment Bureau Project(No.2020BFFFD01804).
文摘As a significant city in the Yangtze River Delta regions,Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion.However,there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants.To address this,this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022.The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data.Temporally,there were pronounced seasonal variations in air pollutants.Spatially,high concentration of HCHO and NO_(2)were closely associated with traffic congestion on roadways,while heightened SO_(2)levels were attributed to winter heating and industrial emissions.The study also revealed that with the implementation of road policies,the average vehicle speed increased by 95.4%,while the NO concentration decreased by 54.4%.In the estimation of urban NO_(x)emission flux,it was observed that in temporal terms,compared with inventory data,the emissions calculated viamobile measurements exhibitedmore distinct seasonal patterns,with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer.In spatial terms,the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city’s primary NO_(x)emission sources in the area between these two rings.This study offers data support for formulating the next phase of air pollution control measures in urban areas.
基金supported by the National Office for Philosophy and Social Sciences(grant reference 22&ZD067).
文摘In the current situation of decelerating economic expansion,examining the digital economy(DE)as a novel economic model is beneficial for the local economy’s sustainable and high-quality development(HQD).We analyzed panel data from the Yellow River(YR)region from 2013 to 2021 and discovered notable spatial variances in the composite index and coupling coordination of the two systems.Specifically,the downstream region exhibited the highest coupling coordination,while the upstream region had the lowest.We identified that favorable factors such as economic development,innovation,industrial upgrading,and government intervention can bolster the coupling.Our findings provide a valuable framework for promoting DE and HQD in the YR region.
基金supported by the National Natural Science Foundation of China(Grant Nos.62472149,62376089,62202147)Hubei Provincial Science and Technology Plan Project(2023BCB04100).
文摘Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a T-GCN module. Thirdly, a transformer layer is introduced to learn the long-term dependence in time. A position embedding mechanism is introduced to label position information for all traffic sequences. Thus, this multi-head self-attention mechanism can recognize the sequence order and allocate weights for different time nodes. Experimental results on four real-world datasets show that the MSSTGCN performs better than the baseline methods and can be successfully adapted to traffic prediction tasks.
基金the National Science Fund for Distinguished Young Scholars of China (No.62025301)the National Natural Science Foundation of China (Nos.62273043 and 62373055)+1 种基金the China National Postdoctoral Program for Innovative Talents (No.BX20230461)the China Postdoctoral Science Foundation (No.2023M740249)。
文摘This paper investigates the spatial-temporal cooperative guidance problem for multiple flight vehicles without relying on time-to-go information.First,a two-stage cooperative guidance strategy,namely the cooperative guidance and the Proportional Navigation Guidance(PNG)stage strategy,is developed to realize the spatial-temporal constraints in two dimensions.At the former stage,two controllers are designed and superimposed to satisfy both impact time consensus and impact angle constraints.Once the convergent conditions are satisfied,the flight vehicles will switch to the PNG stage to ensure zero miss distance.To further extend the results to three dimensions,a planar pursuit guidance stage is additionally imposed at the beginning of guidance.Due to the inde-pendence of time-to-go estimation,the proposed guidance strategy possesses great performance in satisfying complex spatial-temporal constraints even under flight speed variation.Finally,several numerical simulations are implemented to verify the effectiveness and advantages of the proposed results under different scenarios.
基金This work was supported by the National Natural Science Foundation of China(Nos.61833013,61473012 and 62103335)Key Research Program of Jiangxi Province in China(No.20192BBEL50005).
文摘Forest fires pose a significant threat to human life and property,so the utilization of unmanned aircraft systems provides new ways for forest firefighting.Given the constrained load capacities of these aircraft,aerial refueling becomes crucial to extend their operational time and range.In order to address the complexities of firefighting missions involving multi-receiver and multi-tanker deployed from various airports,first,a fuel consumption calculation model for aerial refueling scheduling is established based on the receiver path.Then,two distinct methods,including an integrated one and a decomposed one,are designed to address the challenges of establishing refueling airspace and allocating tasks for tankers.Both methods aim to optimize total fuel consumption of the receivers and tankers within the aerial refueling scheduling framework.The optimization problem is established as nonlinear optimization models along with restrictions.The integrated method seamlessly combines refueling rendezvous point scheduling and tanker task allocation into unified process.It has a complete solution space and excels in optimizing total fuel consumption.The decomposed method,through the separation of rendezvous point scheduling and task allocation,achieves a reduced computational complexity.However,this comes at the cost of sacrificing optimality by excluding specific feasible solutions.Finally,numerical simulations are carried out to verify the feasibility and effectiveness of the proposed methods.These simulations yield insights crucial for the practical engineering application of both the integrated and decomposed methods in real-world scenarios.This comprehensive approach aims to enhance the efficiency of forest firefighting operations,mitigating the risks posed by forest fires to human life and property.
基金This work is partly supported by the National Key Research and Development Program of China(Grant No.2020YFB1805403)the National Natural Science Foundation of China(Grant No.62032002)the 111 Project(Grant No.B21049).
文摘In the Industrial Internet of Things(IIoT),sensors generate time series data to reflect the working state.When the systems are attacked,timely identification of outliers in time series is critical to ensure security.Although many anomaly detection methods have been proposed,the temporal correlation of the time series over the same sensor and the state(spatial)correlation between different sensors are rarely considered simultaneously in these methods.Owing to the superior capability of Transformer in learning time series features.This paper proposes a time series anomaly detection method based on a spatial-temporal network and an improved Transformer.Additionally,the methods based on graph neural networks typically include a graph structure learning module and an anomaly detection module,which are interdependent.However,in the initial phase of training,since neither of the modules has reached an optimal state,their performance may influence each other.This scenario makes the end-to-end training approach hard to effectively direct the learning trajectory of each module.This interdependence between the modules,coupled with the initial instability,may cause the model to find it hard to find the optimal solution during the training process,resulting in unsatisfactory results.We introduce an adaptive graph structure learning method to obtain the optimal model parameters and graph structure.Experiments on two publicly available datasets demonstrate that the proposed method attains higher anomaly detection results than other methods.
基金Under the auspices of the National Natural Science Foundation of China(No.71974070)‘CUG Scholar'Scientific Research Funds at China University of Geosciences(Wuhan)(No.2022005)。
文摘The spatial and temporal variation of green economic efficiency and its driving factors are of great significance for the construction of high-efficiency and low-consumption green development model and sustainable socio-economic development.The research focused on the Yangtze River Economic Belt(YREB)and employed the miniumum distance to strong efficient frontier DEA(MinDs)model to measure the green economic efficiency of the municipalities in the region between 2008 and 2020.Then,the spatial autocorrelation model was used to analyze the evolution characteristics of its spatial pattern.Finally,Geodetector was applied to reveal the drivers and their interactions on green economic efficiency.It is found that:1)the overall green economic efficiency of the YREB from 2008 to 2020 shows a W-shaped fluctuating upward trend,green economic efficiency is greater in the downstream and smallest in the upstream;2)the spatial distribution of green economic efficiency shows clustering characteristics,with multi-core clustering based on‘city clusters-central cities'becoming more obvious over time;the High-High agglomeration type is mainly clustered in Jiangsu and Zheji-ang,while the Low-Low agglomeration type is clustered in the western Sichuan Plateau area and southwestern Yunnan;3)from input-output factors,whether it is the YREB as a whole or the upper,middle and lower reaches regions,the economic development level,labor input,and capital investment are the leading factors in the spatial-temporal evolution of green economic efficiency,with the com-prehensive influence of economic development level and pollution index being the most important interactive driving factor;4)from so-cio-economic factors,information technology drivers such as government intervention,transportation accessibility,information infra-structure,and Internet penetration are always high impact influencers and dominant interaction factors for green economic efficiency in the YREB and the three major regions in the upper,middle and lower reaches.Accordingly,the article puts forward relevant policy re-commendations in terms of formulating differentiated green transformation strategies,strengthening network leadership and informa-tion technology construction and coordinating multi-factor integrated development,which could provide useful reference for promoting synergistic green economic efficiency in the YREB.
基金supported by the Graduate Research and Innovation Project of Chongqing Normal University[Grant No.YKC23035],comprehensive evaluation,and driving factors of urban resilience in the Chengdu-Chongqing Economic Circle.
文摘To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to measure the resilience of each city from 2003 to 2020.The spatial-temporal evolution characteristics were analyzed using Kernel density estimation,standard deviation ellipse,and spatial Markov chain analysis,and the spatial Tobit model was introduced to discover the influencing factors.The results indicate the following:①Urban resilience in the Chengdu-Chongqing Economic Circle displays an upward trend,with the center of gravity moving to the southwest,and the polarization phenomenon intensifying.②The urban resilience level in a region has certain spatial and geographical dependence,while the probability of urban resilience transfer differs in adjacent cities with different resilience levels.③Urban centrality,economic scale,openness level,and financial development promote urban resilience,whereas government scale significantly inhibits it.Finally,this paper proposes countermeasures and suggestions to improve the urban resilience of the Chengdu-Chongqing Economic Circle.
基金supported by the China Scholarship Council and the CERNET Innovation Project under grant No.20170111.
文摘The prediction for Multivariate Time Series(MTS)explores the interrelationships among variables at historical moments,extracts their relevant characteristics,and is widely used in finance,weather,complex industries and other fields.Furthermore,it is important to construct a digital twin system.However,existing methods do not take full advantage of the potential properties of variables,which results in poor predicted accuracy.In this paper,we propose the Adaptive Fused Spatial-Temporal Graph Convolutional Network(AFSTGCN).First,to address the problem of the unknown spatial-temporal structure,we construct the Adaptive Fused Spatial-Temporal Graph(AFSTG)layer.Specifically,we fuse the spatial-temporal graph based on the interrelationship of spatial graphs.Simultaneously,we construct the adaptive adjacency matrix of the spatial-temporal graph using node embedding methods.Subsequently,to overcome the insufficient extraction of disordered correlation features,we construct the Adaptive Fused Spatial-Temporal Graph Convolutional(AFSTGC)module.The module forces the reordering of disordered temporal,spatial and spatial-temporal dependencies into rule-like data.AFSTGCN dynamically and synchronously acquires potential temporal,spatial and spatial-temporal correlations,thereby fully extracting rich hierarchical feature information to enhance the predicted accuracy.Experiments on different types of MTS datasets demonstrate that the model achieves state-of-the-art single-step and multi-step performance compared with eight other deep learning models.
基金supported in part by the Pioneer and Leading Goose R&D Program of Zhejiang Province under Grant 2022C01083 (Dr.Yu Li,https://zjnsf.kjt.zj.gov.cn/)Pioneer and Leading Goose R&D Program of Zhejiang Province under Grant 2023C01217 (Dr.Yu Li,https://zjnsf.kjt.zj.gov.cn/).
文摘With the rapid development ofmobile Internet,spatial crowdsourcing has becomemore andmore popular.Spatial crowdsourcing consists of many different types of applications,such as spatial crowd-sensing services.In terms of spatial crowd-sensing,it collects and analyzes traffic sensing data from clients like vehicles and traffic lights to construct intelligent traffic prediction models.Besides collecting sensing data,spatial crowdsourcing also includes spatial delivery services like DiDi and Uber.Appropriate task assignment and worker selection dominate the service quality for spatial crowdsourcing applications.Previous research conducted task assignments via traditional matching approaches or using simple network models.However,advanced mining methods are lacking to explore the relationship between workers,task publishers,and the spatio-temporal attributes in tasks.Therefore,in this paper,we propose a Deep Double Dueling Spatial-temporal Q Network(D3SQN)to adaptively learn the spatialtemporal relationship between task,task publishers,and workers in a dynamic environment to achieve optimal allocation.Specifically,D3SQNis revised through reinforcement learning by adding a spatial-temporal transformer that can estimate the expected state values and action advantages so as to improve the accuracy of task assignments.Extensive experiments are conducted over real data collected fromDiDi and ELM,and the simulation results verify the effectiveness of our proposed models.
基金Supported by projects of the National Natural Science Foundation of China(Nos.92062216,41888101).
文摘Highly evolved granite is an important sign of the mature continent crust and closely associated with deposits of rare metals.In this work,the authors undertake systematically zircon U-Pb ages and whole rock elemental data for highly evolved granitic intrusions from the Great Xing’an Range(GXR),NE China,to elucidate their discriminant criteria,spatial-temporal distribution,differentiation and geodynamic mecha-nism.Geochemical data of these highly evolved granites suggest that high w(SiO_(2))(>70%)and differentiation index(DI>88)could be quantified indicators,while strong Eu depletion,high TE_(1,3),lowΣREE and low Zr/Hf,Nb/Ta,K/Rb could only be qualitative indicators.Zircon U-Pb ages suggest that the highly evolved gran-ites in the GXR were mainly formed in Late Mesozoic,which can be divided into two major stages:Late Ju-rassic-early Early Cretaceous(162-136 Ma,peak at 138 Ma),and late Early Cretaceous(136-106 Ma,peak at 126 Ma).The highly evolved granites are mainly distributed in the central-southern GXR,and display a weakly trend of getting younger from northwest to southeast,meanwhile indicating the metallogenic potential of rare metals within the central GXR.The spatial-temporal distribution,combined with regional geological data,indicates the highly evolved Mesozoic granites in the GXR were emplaced in an extensional environ-ment,of which the Late Jurassic-early Early Cretaceous extension was related to the closure of the Mongol-Okhotsk Ocean and roll-back of the Paleo-Pacific Plate,while the late Early Cretaceous extension was mainly related to the roll-back of the Paleo-Pacific Plate.
基金the National Natural Science Foundation of China(No.61461027,61762059)the Provincial Science and Technology Program supported the Key Project of Natural Science Foundation of Gansu Province(No.22JR5RA226)。
文摘Considering the nonlinear structure and spatial-temporal correlation of traffic network,and the influence of potential correlation between nodes of traffic network on the spatial features,this paper proposes a traffic speed prediction model based on the combination of graph attention network with self-adaptive adjacency matrix(SAdpGAT)and bidirectional gated recurrent unit(BiGRU).First-ly,the model introduces graph attention network(GAT)to extract the spatial features of real road network and potential road network respectively in spatial dimension.Secondly,the spatial features are input into BiGRU to extract the time series features.Finally,the prediction results of the real road network and the potential road network are connected to generate the final prediction results of the model.The experimental results show that the prediction accuracy of the proposed model is im-proved obviously on METR-LA and PEMS-BAY datasets,which proves the advantages of the pro-posed spatial-temporal model in traffic speed prediction.
文摘As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wetland,the Xianghai Wetland,and the Danjiang Wetland in Jilin Province.The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space,and the intensification of land salinization.Zhenlai County and Da an City in the Nenjiang River Basin have sufficient surface water resources,with surface water as the drinking water source.Baicheng City and Tongyu County have scarce surface water resources,and both use groundwater as their domestic water source.The main polluted section in the basin is the Xianghai Reservoir,and the annual water quality evaluation is Class V.However,the water quality of the Tao er River,the main stream of the Nenjiang River,is significantly better than that of the Xianghai Reservoir.In order to better study the water environmental pollution situation in the Nenjiang River basin,monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality.This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development,agricultural pattern transformation,and the promotion of water ecological civilization construction.
文摘Objective:This study aimed to examine the reliability and validity of the Chinese version of the Behavioral Inhibition System/Behavioral Activation System(BIS/BAS)scales among stroke survivors.Methods:The cross-sectional study was conducted at four comprehensive hospitals in Taizhou,Jiangsu,China.A sample of 232 first-ever stroke survivors were recruited from June to August 2023.Validity was examined using face validity and construct validity,which used confirmatory factor analysis(CFA)and known-group analysis.Reliability was evaluated by internal consistency and test-retest reliability.Results:The BIS/BAS scales demonstrated satisfactory face validity.The findings of CFAs supported the original four-factor structure of BAS-reward,BAS-drive,BAS-fun seeking,and BIS with acceptable model fit indices.Discriminative validity,assessed via known-group analysis,indicated that stroke survivors with probable depression had significantly lower mean BAS-reward,BAS-drive,and BAS-fun seeking scores(P<0.001)and a higher mean BIS score(P=0.028)compared to those without probable depression.The internal consistency,measured by Cronbach’s a coefficients for the subscales,ranged from 0.669 to 0.964.Test-retest reliability,assessed using intra-class correlation coefficients,ranged from 0.61 to 0.93.Conclusions:The Chinese version of the BIS/BAS scales could be a reliable and valid instrument for measuring behavioral activation among stroke survivors.
基金supported by ANID Fondecyt Iniciacion 11180540(to FJB)ANID PAI 77180077(to FJB)+2 种基金UNAB DI-02-22/REG(to FJB)Exploración-ANID 13220203(to FJB)ANID-MILENIO(NCN2023_23,to FJB)。
文摘Since the pioneering work by Broca and Wernicke in the 19th century,who examined individuals with brain lesions to associate them with specific behaviors,it was evident that behaviors are complex and cannot be fully attributable to specific brain areas alone.Instead,they involve connectivity among brain areas,whether close or distant.At that time,this approach was considered the optimal way to dissect brain circuitry and function.These pioneering efforts opened the field to explore the necessity or sufficiency of brain areas in controlling behavior and hence dissecting brain function.However,the connectivity of the brain and the mechanisms through which various brain regions regulate specific behaviors,either individually or collaboratively,remain largely elusive.Utilizing animal models,researchers have endeavored to unravel the necessity or sufficiency of specific brain areas in influencing behavior;however,no clear associations have been firmly established.
基金supported by the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2020B0301030006).
文摘Magnesium matrix composites with both high strength and ductility have been achieved by introducing pure Ti particles.However,the properties of the surfaces of the composites need to be improved by surface technology,such as micro-arc oxidation(MAO).In this study,we investigated the influence of the Ti-reinforcement phase on coating growth and evolution by subjecting both AZ91 alloy and AZ91/Ti composite to MAO treatment using silicate-based and phosphate-based electrolytes.Results revealed that the Ti-reinforcement phase influenced the MAO process,altering discharge behavior,and leading to a decreased cell voltage.The vigorous discharge of the Ti-reinforcement phase induced the formation of coating discharge channels,concurrently dissolving and oxidizing Ti-reinforcement to produce a composite ceramic coating with TiO2.The MAO coating on the AZ91/Ti composite exhibited a dark blue macromorphology and distinctive local micromorphological anomalies.In silicate electrolyte,a“volcano-like”localized morphology centered on the discharge channel emerged.In contrast,treatment in phosphate-based electrolyte resulted in a coating morphology similar to typical porous ceramic coatings,with visible radial discharge micropores at the reinforcement phase location.Compared to the AZ91 alloy,the coating on the AZ91/Ti composite exhibited lower thickness and higher porosity.MAO treatment reduced the self-corrosion current density of the AZ91/Ti surface by two orders of magnitude.The silicate coating demonstrated better corrosion resistance than the phosphate coating,attributed to its lower porosity.The formation mechanism of MAO coatings on AZ91/Ti composites in phosphate-based and silicate-based electrolytes was proposed.
基金financially supported by National Natural Science Foundation of China(grant numbers:52171100,U20A20234)National Key R&D Program of China(grant number:2021YFB3701100)。
文摘The performance of Mg alloys is significantly influenced by the concentrations and solid solution behavior of the alloying elements.In this work,the solid solution behavior of 20 alloying elements in 190 ternary Mg alloy systems at 500℃are systematically investigated.The solid solution behavior of a set of two different alloying elements in Mg alloy systems are suggested to be classified into three categories:inclusivity,exclusivity and proportionality.Inclusivity classification indicates that the two alloying elements are inclusive inα-Mg,increasing the joint solubility of both elements.Exclusivity classification suggests that the two alloying elements have a low joint solid solubility inα-Mg,since they prefer to form stable second phases.For the proportionality classification,the solubility curve of the ternary Mg alloy systems is a straight line connecting the solubility points of the two sub-binary systems.The proposed classification theory was validated by key experiments and the calculation of formation energies.The interaction effects between alloying elements and the preference of formation of second phases are the main factors determining the solid solution behavior classifications.Based on the observed solid solution features of multi-component Mg alloys,principles for alloy design of different types of high-performance Mg alloys were proposed in this work.
基金support from the National Natural Science Foundation of China(grant number 52075544)Innovation Funds of Jihua Laboratory(X220971UZ230)+1 种基金Basic and Applied Basic Research Foundation of Guangdong Province(2022A1515110649)Funds from Research Platforms of Guangdong Higher Education Institutes(2022ZDJS038).
文摘Efficient lubrication of magnesium alloys is a highly challenging topic in the field of tribology.In this study,magnesium silicate hydroxide(MSH)nanotubes with serpentine structures were synthesized.The tribological behavior of AZ91D magnesium alloy rubbed against GCr15 steel was studied under lubricating oil with surface-modified MSH nanotubes as additives.The effects of the concentration,applied load,and reciprocating frequency on the friction and wear of the AZ91D alloy were studied using an SRV-4 sliding wear tester.Results show a decrease of 18.7–68.5%in friction coefficient,and a reduction of 19.4–54.3%in wear volume of magnesium alloy can be achieved by applying the synthetic serpentine additive under different conditions.A suspension containing 0.3 wt.%MSH was most efficient in reducing wear and friction.High frequency and medium load were more conducive to improving the tribological properties of magnesium alloys.A series of beneficial physical and chemical processes occurring at the AZ91D alloy/steel interface can be used to explain friction and wear reduction based on the characterization of the morphology,chemical composition,chemical state,microstructure,and nanomechanical properties of the worn surface.The synthetic MSH,with serpentine structure and nanotube morphology,possesses excellent adsorbability,high chemical activity,and good self-lubrication and catalytic activity.Therefore,physical polishing,tribochemical reactions,and physicalchemical depositions can occur easily on the sliding contacts.A dense tribolayer with a complex composition and composite structure was formed on the worn surface.Its high hardness,good toughness and plasticity,and prominent lubricity resulted in the improvement of friction and wear,making the synthetic MSH a promising efficient oil additive for magnesium alloys under boundary and mixed lubrication.
文摘This study aims to explore the characteristics of novice teachers’inappropriate behaviors in classroom teaching and their intervention strategies.With the continuous improvement of education quality,novice teachers face increasing challenges in teaching practice.Their inappropriate behaviors not only affect the classroom atmosphere but may also negatively impact students’learning outcomes.Therefore,researching the characteristics of novice teachers’inappropriate behaviors and their intervention strategies holds significant scientific and social value.This study employs a combination of quantitative and qualitative methods to analyze the behavioral patterns of novice teachers in classroom teaching and proposes corresponding intervention strategies.The results indicate that novice teachers’inappropriate behaviors mainly manifest as poor classroom management,monotonous teaching methods,and insufficient interaction with students.Based on these findings,the study proposes a series of effective intervention strategies,including enhancing teacher training,optimizing teaching design,and promoting positive interactions between teachers and students.The conclusions of the study not only provide practical guidance for educational practice but also point out directions for future research,emphasizing the crucial role of teacher professional development in improving teaching quality.
基金supported by the National Natural Science Foundation of China(Nos.52074228,52305420 and 51875470)the Practice and Innovation Funds for Graduate Students of Northwestern Polytechnical University,China(No.PF2024053)the Xi’an Beilin District Science and Technology Planning Project,China(No.GX2349).
文摘The pre-weld heat treatment was carried out to obtain different initial microstructures of the GH4169 superalloy,and then Linear Friction Welding(LFW)was performed.The effect of the pre-weld heat treatment on the microstructure evolution and mechanical properties of the joint was analyzed,and the joint electrochemical corrosion behavior as well as the hot corrosion behavior was studied.The results show that the joint hardness of Base Metal(BM)increases after pre-weld heat treatment,and the strengthening phasesγ′andγ″further precipitate.However,the precipitation phases dissolve significantly in the Weld Zone(WZ)due to the thermal process of LFW.The corrosion resistance in BM is reduced after the pre-weld heat treatment,while it is similar in WZ with a slight decrease.The surface morphology of the BM and WZ can be generally divided into a loose and porous matrix and a scattered oxide particle layer after hot corrosion.The joint cross section exhibits a Cr-depleted zone with the diffusion of Cr to form an oxide film.The corrosion product mainly consists of Fe_(2)O_(3)/Fe_(3)O_(4) as the outer layer and Cr_(2)O_(3) as the inner layer.
