Fertilization or atmospheric deposition of nitrogen(N)and phosphorus(P)to terrestrial ecosystems can alter soil N(P)availability and the nature of nutrient limitation for plant growth.Changing the allocation of leaf P...Fertilization or atmospheric deposition of nitrogen(N)and phosphorus(P)to terrestrial ecosystems can alter soil N(P)availability and the nature of nutrient limitation for plant growth.Changing the allocation of leaf P fractions is potentially an adaptive strategy for plants to cope with soil N(P)availability and nutrient-limiting conditions.However,the impact of the interactions between imbalanced anthropogenic N and P inputs on the concentrations and allocation proportions of leaf P fractions in forest woody plants remains elusive.We conducted a metaanalysis of data about the concentrations and allocation proportions of leaf P fractions,specifically associated with individual and combined additions of N and P in evergreen forests,the dominant vegetation type in southern China where the primary productivity is usually considered limited by P.This assessment allowed us to quantitatively evaluate the effects of N and P additions alone and interactively on leaf P allocation and use strategies.Nitrogen addition(exacerbating P limitation)reduced the concentrations of leaf total P and different leaf P fractions.Nitrogen addition reduced the allocation to leaf metabolic P but increased the allocation to other fractions,while P addition showed opposite trends.The simultaneous additions of N and P showed an antagonistic(mutual suppression)effect on the concentrations of leaf P fractions,but an additive(summary)effect on the allocation proportions of leaf P fractions.These results highlight the importance of strategies of leaf P fraction allocation in forest plants under changes in environmental nutrient availability.Importantly,our study identified critical interactions associated with combined N and P inputs that affect leaf P fractions,thus aiding in predicting plant acclimation strategies in the context of intensifying and imbalanced anthropogenic nutrient inputs.展开更多
Population migration data derived from location-based services has often been used to delineate population flows between cities or construct intercity relationship networks to reveal and explore the complex interactio...Population migration data derived from location-based services has often been used to delineate population flows between cities or construct intercity relationship networks to reveal and explore the complex interaction patterns underlying human activities.Nevertheless,the inherent heterogeneity in multimodal migration big data has been ignored.This study conducts an in-depth comparison and quantitative analysis through a comprehensive lens of spatial association.Initially,the intercity interactive networks in China were constructed,utilizing migration data from Baidu and AutoNavi collected during the same time period.Subsequently,the characteristics and spatial structure similarities of the two types of intercity interactive networks were quantitatively assessed and analyzed from overall(network)and local(node)perspectives.Furthermore,the precision of these networks at the local scale is corroborated by constructing an intercity network from mobile phone(MP)data.Results indicate that the intercity interactive networks in China,as delineated by Baidu and AutoNavi migration flows,exhibit a high degree of structure equivalence.The correlation coefficient between these two networks is 0.874.Both networks exhibit a pronounced spatial polarization trend and hierarchical structure.This is evident in their distinct core and peripheral structures,as well as in the varying importance and influence of different nodes within the networks.Nevertheless,there are notable differences worthy of attention.Baidu intercity interactive network exhibits pronounced cross-regional effects,and its high-level interactions are characterized by a“rich-club”phenomenon.The AutoNavi intercity interactive network presents a more significant distance attenuation effect,and the high-level interactions display a gradient distribution pattern.Notably,there exists a substantial correlation between the AutoNavi and MP networks at the local scale,evidenced by a high correlation coefficient of 0.954.Furthermore,the“spatial dislocations”phenomenon was observed within the spatial structures at different levels,extracted from the Baidu and AutoNavi intercity networks.However,the measured results of network spatial structure similarity from three dimensions,namely,node location,node size,and local structure,indicate a relatively high similarity and consistency between the two networks.展开更多
Online interactive learning plays a crucial role in improving online education quality.This grounded theory study examines:(1)what key factors shape EFL learners’online interactive learning,(2)how these factors form ...Online interactive learning plays a crucial role in improving online education quality.This grounded theory study examines:(1)what key factors shape EFL learners’online interactive learning,(2)how these factors form an empirically validated model,and(3)how they interact within this model,through systematic analysis of 9,207 discussion forum posts from a Chinese University MOOC platform.Results demonstrate that learning drive,course structure,teaching competence,interaction behavior,expected outcomes,and online learning context significantly influence EFL online interactive learning.The analysis reveals two key mechanisms:expected outcomes mediate the effects of learning drive(β=0.45),course structure,teaching competence,and interaction behavior(β=0.35)on learning outcomes,while online learning context moderates these relationships(β=0.25).Specifically,learning drive provides intrinsic/extrinsic motivation,whereas course structure,teaching competence,interaction behavior,and expected outcomes collectively enhance interaction quality and sustainability.These findings,derived through rigorous grounded theory methodology involving open,axial,and selective coding of large-scale interaction data,yield three key contributions:(1)a comprehensive theoretical model of EFL online learning dynamics,(2)empirical validation of mediation/moderation mechanisms,and(3)practical strategies for designing scaffolded interaction protocols and adaptive feedback systems.The study establishes that its theoretically saturated model(achieved after analyzing 7,366 posts with 1,841 verification cases)offers educators evidence-based approaches to optimize collaborative interaction in digital EFL environments.展开更多
Measurement-while-drilling(MWD)and guidance technologies have been extensively deployed in the exploitation of oil,natural gas,and other energy resources.Conventional control approaches are plagued by challenges,inclu...Measurement-while-drilling(MWD)and guidance technologies have been extensively deployed in the exploitation of oil,natural gas,and other energy resources.Conventional control approaches are plagued by challenges,including limited anti-interference capabilities and the insufficient generalization of decision-making experience.To address the intricate problem of directional well trajectory control,an intelligent algorithm design framework grounded in the high-level interaction mechanism between geology and engineering is put forward.This framework aims to facilitate the rapid batch migration and update of drilling strategies.The proposed directional well trajectory control method comprehensively considers the multi-source heterogeneous attributes of drilling experience data,leverages the generative simulation of the geological drilling environment,and promptly constructs a directional well trajectory control model with self-adaptive capabilities to environmental variations.This construction is carried out based on three hierarchical levels:“offline pre-drilling learning,online during-drilling interaction,and post-drilling model transfer”.Simulation results indicate that the guidance model derived from this method demonstrates remarkable generalization performance and accuracy.It can significantly boost the adaptability of the control algorithm to diverse environments and enhance the penetration rate of the target reservoir during drilling operations.展开更多
In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operati...In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.展开更多
The multi-dimensional interactive teaching model significantly enhances the effectiveness of college English instruction by emphasizing dynamic engagement between teachers and students,as well as among students themse...The multi-dimensional interactive teaching model significantly enhances the effectiveness of college English instruction by emphasizing dynamic engagement between teachers and students,as well as among students themselves.This paper explores practical strategies for implementing this model,focusing on four key aspects:deepening teachers’understanding of the model through continuous learning,innovating interactive methods such as questioning techniques and practical activities,leveraging modern technology to integrate resources and track learning progress,and establishing a communication platform that centers on student participation.By adopting these approaches,the model fosters a student-centered classroom environment,improves comprehensive English application skills,and optimizes overall teaching quality.展开更多
Software defect prediction aims to use measurement data of code and historical defects to predict potential problems,optimize testing resources and defect management.However,current methods face challenges:(1)Coarse-g...Software defect prediction aims to use measurement data of code and historical defects to predict potential problems,optimize testing resources and defect management.However,current methods face challenges:(1)Coarse-grained file level detection cannot accurately locate specific defects.(2)Fine-grained line-level defect prediction methods rely solely on local information of a single line of code,failing to deeply analyze the semantic context of the code line and ignoring the heuristic impact of line-level context on the code line,making it difficult to capture the interaction between global and local information.Therefore,this paper proposes a telecontext-enhanced recursive interactive attention fusion method for line-level defect prediction(TRIA-LineDP).Firstly,using a bidirectional hierarchical attention network to extract semantic features and contextual information from the original code lines as the basis.Then,the extracted contextual information is forwarded to the telecontext capture module to aggregate the global context,thereby enhancing the understanding of broader code dynamics.Finally,a recursive interaction model is used to simulate the interaction between code lines and line-level context,passing information layer by layer to enhance local and global information exchange,thereby achieving accurate defect localization.Experimental results from within-project defect prediction(WPDP)and cross-project defect prediction(CPDP)conducted on nine different projects(encompassing a total of 32 versions)demonstrated that,within the same project,the proposed methods will respectively recall at top 20%of lines of code(Recall@Top20%LOC)and effort at top 20%recall(Effort@Top20%Recall)has increased by 11%–52%and 23%–77%.In different projects,improvements of 9%–60%and 18%–77%have been achieved,which are superior to existing advanced methods and have good detection performance.展开更多
With the development of globalization,intercultural communicative competence has become one of the core qualities of modern college students.As an important platform to cultivate students’language skills and cultural...With the development of globalization,intercultural communicative competence has become one of the core qualities of modern college students.As an important platform to cultivate students’language skills and cultural literacy,the innovation of college English teaching mode is essential.Based on this,this paper mainly discusses methods to effectively cultivate students’intercultural communicative competence in college English teaching from the perspective of multimodal interactive teaching mode,hoping to provide references for improving the quality of college English teaching and students’comprehensive quality.展开更多
Objective:To analyze the nursing effect of implementing continuous nursing combined with knowledge,attitude,and practice(KAP)intervention under the guidance of interactive goal-setting theory for patients with gestati...Objective:To analyze the nursing effect of implementing continuous nursing combined with knowledge,attitude,and practice(KAP)intervention under the guidance of interactive goal-setting theory for patients with gestational diabetes mellitus(GDM).Methods:A total of 68 patients with GDM who were admitted to the hospital between December 2021 and December 2023 were selected and randomly divided into two groups using a random number table.The combined group(34 cases)received continuous nursing combined with KAP intervention under the premise of interactive goal-setting theory,while the conventional group(34 cases)received routine nursing care.Blood glucose control,health behavior scores,and other indicators were compared between the two groups.Results:After nursing,the blood glucose level in the combined group was lower than that in the conventional group,and the scores for health behavior and self-management ability were higher than those in the conventional group(P<0.05).Conclusion:Combined nursing can improve blood glucose control in patients with GDM,standardize their health behaviors,and cultivate their self-management skills.展开更多
Objective To assess the independent and combined effects of air pollutants,meteorological factors,and greenspace exposure on new tuberculosis(TB)cases.Methods TB case data from Shanghai(2013–2018)were obtained from t...Objective To assess the independent and combined effects of air pollutants,meteorological factors,and greenspace exposure on new tuberculosis(TB)cases.Methods TB case data from Shanghai(2013–2018)were obtained from the Shanghai Center for Disease Control and Prevention.Environmental data on air pollutants,meteorological variables,and greenspace exposure were obtained from the National Tibetan Plateau Data Center.We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases.Results Increased TB risk was linked to PM_(2.5),PM_(10),and rainfall,whereas NO_(2),SO_(2),and air pressure were associated with a reduced risk.Specifically,the strongest cumulative effects occurred at various lags:PM_(2.5)(RR=1.166,95%CI:1.026–1.325)at 0–19 weeks;PM_(10)(RR=1.167,95%CI:1.028–1.324)at 0–18 weeks;NO_(2)(RR=0.968,95%CI:0.938–0.999)at 0–1 weeks;SO_(2)(RR=0.945,95%CI:0.894–0.999)at 0–2 weeks;air pressure(RR=0.604,95%CI:0.447–0.816)at 0–8 weeks;and rainfall(RR=1.404,95%CI:1.076–1.833)at 0–22 weeks.Green space exposure did not significantly impact TB cases.Additionally,low temperatures amplified the effect of PM_(2.5)on TB.Conclusion Exposure to PM_(2.5),PM_(10),and rainfall increased the risk of TB,highlighting the need to address air pollutants for the prevention of TB in Shanghai.展开更多
In an aging society,the interface design of smart home products is crucial to the quality of life of the elderly.This paper combines Quality Function Deployment(QFD)and Human-Computer Interaction(HCI)theories,taking s...In an aging society,the interface design of smart home products is crucial to the quality of life of the elderly.This paper combines Quality Function Deployment(QFD)and Human-Computer Interaction(HCI)theories,taking smart washing machines as an example,to explore new paths for the interface design of smart home products for the elderly.An interdisciplinary approach is adopted to construct a design process centered on elderly users,introduce the Kano model to classify requirements,realize the mapping and sorting of requirements to design parameters,and adopt the PUGH model for comprehensive evaluation.This study provides practical and theoretical support for the interface design of smart home products for the elderly.展开更多
The efficient development of the urban economy is a major concern of scholars in the fields of geography and urban science.In the context of globalization,informatization,industrialization,and urbanization,the externa...The efficient development of the urban economy is a major concern of scholars in the fields of geography and urban science.In the context of globalization,informatization,industrialization,and urbanization,the external relationships of China's cities are experiencing the joint action of urban scale hierarchies and connection networks(“hierarchy-network”).However,under the interactive effect of the two,the mechanism of urban economic efficiency(UEE)is unclear.Therefore,based on Baidu migration data,the regionalization with dynamically constrained agglomerative clustering and partitioning(REDCAP)method,and a spatial simultaneous equation model,this paper analyzes the UEE spatial pattern and mechanism in China.The results indicate that:(1)the urban economy has a superlinear relationship with the population size.However,the benefit of this superlinear growth is in marginal decline.(2)The UEE shows a pattern of differentiation between China's eastern,then central,and then western region.Also,local differences are found within the three major sub-regions.(3)The increase of urban network centrality can promote UEE,while the impact of urban scale is negative.(4)There is regional heterogeneity of the interactive effect of“hierarchy-network”on UEE.This study reveals the influencing mechanism of UEE and also provides policy implications for the development of UEE.展开更多
Getting insight into the spatiotemporal distribution patterns of knowledge innovation is receiving increasing attention from policymakers and economic research organizations.Many studies use bibliometric data to analy...Getting insight into the spatiotemporal distribution patterns of knowledge innovation is receiving increasing attention from policymakers and economic research organizations.Many studies use bibliometric data to analyze the popularity of certain research topics,well-adopted methodologies,influential authors,and the interrelationships among research disciplines.However,the visual exploration of the patterns of research topics with an emphasis on their spatial and temporal distribution remains challenging.This study combined a Space-Time Cube(STC)and a 3D glyph to represent the complex multivariate bibliographic data.We further implemented a visual design by developing an interactive interface.The effectiveness,understandability,and engagement of ST-Map are evaluated by seven experts in geovisualization.The results suggest that it is promising to use three-dimensional visualization to show the overview and on-demand details on a single screen.展开更多
The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided diagnosis.However,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are ...The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided diagnosis.However,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are unbalanced.To solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung images.The pixel dependence relationship is established in local and non-local fields to improve the model perception ability.Secondly,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained features.Thirdly,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic features.Finally,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image datasets.The results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this paper.This method has positive significance for the detection of lung tumors.展开更多
In this paper, the online parameter identification problem of the mathematical model of an unmanned surface vehicle (USV) considering the characteristics of the actuator is studied. A data-driven mathematical model of...In this paper, the online parameter identification problem of the mathematical model of an unmanned surface vehicle (USV) considering the characteristics of the actuator is studied. A data-driven mathematical model of motion is very meaningful to realize trajectory prediction and adaptive motion control of the USV. An interactive identification algorithm (ESO–MILS, extended state observer–multi-innovation least squares) based on ESO is proposed. The robustness of online identification is improved by expanding the state observer to estimate the current disturbance without making artificial assumptions. Specifically, the three-degree-of-freedom dynamic equation of the double propeller propulsion USV is constructed. A linear model for online identification is derived by parameterization. Based on the least square criterion function, it is proved that the interactive identification method with disturbance estimation can improve the identification accuracy from the perspective of mathematical expectation. The extended state observer is designed to estimate the unknown disturbance in the model. The online interactive update improves the disturbance immunity of the identification algorithm. Finally, the effectiveness of the interactive identification algorithm is verified by simulation experiment and real ship experiment.展开更多
The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The bas...The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The basic parameters of sandstone are determined through a series of static and dynamic tests,including uniaxial compression,Brazilian disc,triaxial compression under varying confining pressures,hydrostatic compression,and dynamic compression and tensile tests with a split Hopkinson pressure bar.Based on the sandstone test results from this study and previous research,a step-by-step procedure for parameter calibration is outlined,which accounts for the categories of the strength surface,equation of state(EOS),strain rate effect,and damage.The calibrated parameters are verified through numerical tests that correspond to the experimental loading conditions.Consistency between numerical results and experimental data indicates the precision and reliability of the calibrated parameters.The methodology presented in this study is scientifically sound,straightforward,and essential for improving the TSID model.Furthermore,it has the potential to contribute to other rock constitutive models,particularly new user-defined models.展开更多
During the robot-assisted pelvic fracture reduction,the needle-tissue interactive deformation characteristic is not clear,which affects the accuracy of robotic surgery.In this paper,a layered rig-id-flexible coupling ...During the robot-assisted pelvic fracture reduction,the needle-tissue interactive deformation characteristic is not clear,which affects the accuracy of robotic surgery.In this paper,a layered rig-id-flexible coupling model is proposed,and the needle-tissue interactive deformation under the load-ing is analyzed by the Rayleigh-Ritz method,in accordance with the principle of minimum potential energy.The pelvic musculoskeletal tissue is reversely reconstructed,and the structure of the bone is segmented into cancellous bone and cortical bone.The Mooney-Rivlin five-parameter hyperelastic model is used to simulate muscle,and the Ogden hyperelastic model is used to simulate adipose tis-sue.Finite element simulation is performed by loading different magnitudes of forces.The accuracy of the rigid-flexible coupling model is 0.432 mm,which indicates the correctness of the needle-tis-sue interactive deformation theory analysis.展开更多
The Balise Transmission Module(BTM)unit of the on-board train control system is a crucial component.Due to its unique installation position and complex environment,this unit has a higher fault rate within the on-board...The Balise Transmission Module(BTM)unit of the on-board train control system is a crucial component.Due to its unique installation position and complex environment,this unit has a higher fault rate within the on-board train control system.To conduct fault prediction for the BTM unit based on actual fault data,this study proposes a prediction method combining reliability statistics and machine learning,and achieves the fusion of prediction results from different dimensions through multi-method interactive validation.Firstly,a method for predicting equipment fault time targeting batch equipment is introduced.This method utilizes reliability statistics to construct a model of the remaining faultless operating time distribution considering uncertainty,thereby predicting the remaining faultless operating probability of the BTM unit.Secondly,considering the complexity of the BTM unit’s fault mechanism,the small sample size of fault cases,and the potential presence of multiple fault features in fault text records,an individual-oriented fault prediction method based on Bayesian-optimized Gradient Boosting Regression Tree(Bayes-GBRT)is proposed.This method achieves better prediction results compared to linear regression algorithms and random forest regression algorithms,with an average absolute error of only 0.224 years for predicting the fault time of this type of equipment.Finally,a multi-method interactive validation approach is proposed,enabling the fusion and validation of multi-dimensional results.The results indicate that the predicted fault time and the actual fault time conform to a log-normal distribution,and the parameter estimation results are basically consistent,verifying the accuracy and effectiveness of the prediction results.The above research findings can provide technical support for the maintenance and modification of BTM units,effectively reducing maintenance costs and ensuring the safe operation of high-speed railway,thus having practical engineering value for preventive maintenance.展开更多
In many Eastern and Western countries,falling birth rates have led to the gradual aging of society.Older adults are often left alone at home or live in a long-term care center,which results in them being susceptible t...In many Eastern and Western countries,falling birth rates have led to the gradual aging of society.Older adults are often left alone at home or live in a long-term care center,which results in them being susceptible to unsafe events(such as falls)that can have disastrous consequences.However,automatically detecting falls fromvideo data is challenging,and automatic fall detection methods usually require large volumes of training data,which can be difficult to acquire.To address this problem,video kinematic data can be used as training data,thereby avoiding the requirement of creating a large fall data set.This study integrated an improved particle swarm optimization method into a double interactively recurrent fuzzy cerebellar model articulation controller model to develop a costeffective and accurate fall detection system.First,it obtained an optical flow(OF)trajectory diagram from image sequences by using the OF method,and it solved problems related to focal length and object offset by employing the discrete Fourier transform(DFT)algorithm.Second,this study developed the D-IRFCMAC model,which combines spatial and temporal(recurrent)information.Third,it designed an IPSO(Improved Particle Swarm Optimization)algorithm that effectively strengthens the exploratory capabilities of the proposed D-IRFCMAC(Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller)model in the global search space.The proposed approach outperforms existing state-of-the-art methods in terms of action recognition accuracy on the UR-Fall,UP-Fall,and PRECIS HAR data sets.The UCF11 dataset had an average accuracy of 93.13%,whereas the UCF101 dataset had an average accuracy of 92.19%.The UR-Fall dataset had an accuracy of 100%,the UP-Fall dataset had an accuracy of 99.25%,and the PRECIS HAR dataset had an accuracy of 99.07%.展开更多
基金supported by the National Natural Science Foundation of China(No.41473068)supported by China Postdoctoral Science Foundation(No.2022M722667)。
文摘Fertilization or atmospheric deposition of nitrogen(N)and phosphorus(P)to terrestrial ecosystems can alter soil N(P)availability and the nature of nutrient limitation for plant growth.Changing the allocation of leaf P fractions is potentially an adaptive strategy for plants to cope with soil N(P)availability and nutrient-limiting conditions.However,the impact of the interactions between imbalanced anthropogenic N and P inputs on the concentrations and allocation proportions of leaf P fractions in forest woody plants remains elusive.We conducted a metaanalysis of data about the concentrations and allocation proportions of leaf P fractions,specifically associated with individual and combined additions of N and P in evergreen forests,the dominant vegetation type in southern China where the primary productivity is usually considered limited by P.This assessment allowed us to quantitatively evaluate the effects of N and P additions alone and interactively on leaf P allocation and use strategies.Nitrogen addition(exacerbating P limitation)reduced the concentrations of leaf total P and different leaf P fractions.Nitrogen addition reduced the allocation to leaf metabolic P but increased the allocation to other fractions,while P addition showed opposite trends.The simultaneous additions of N and P showed an antagonistic(mutual suppression)effect on the concentrations of leaf P fractions,but an additive(summary)effect on the allocation proportions of leaf P fractions.These results highlight the importance of strategies of leaf P fraction allocation in forest plants under changes in environmental nutrient availability.Importantly,our study identified critical interactions associated with combined N and P inputs that affect leaf P fractions,thus aiding in predicting plant acclimation strategies in the context of intensifying and imbalanced anthropogenic nutrient inputs.
基金National Natural Science Foundation of China,No.42361040。
文摘Population migration data derived from location-based services has often been used to delineate population flows between cities or construct intercity relationship networks to reveal and explore the complex interaction patterns underlying human activities.Nevertheless,the inherent heterogeneity in multimodal migration big data has been ignored.This study conducts an in-depth comparison and quantitative analysis through a comprehensive lens of spatial association.Initially,the intercity interactive networks in China were constructed,utilizing migration data from Baidu and AutoNavi collected during the same time period.Subsequently,the characteristics and spatial structure similarities of the two types of intercity interactive networks were quantitatively assessed and analyzed from overall(network)and local(node)perspectives.Furthermore,the precision of these networks at the local scale is corroborated by constructing an intercity network from mobile phone(MP)data.Results indicate that the intercity interactive networks in China,as delineated by Baidu and AutoNavi migration flows,exhibit a high degree of structure equivalence.The correlation coefficient between these two networks is 0.874.Both networks exhibit a pronounced spatial polarization trend and hierarchical structure.This is evident in their distinct core and peripheral structures,as well as in the varying importance and influence of different nodes within the networks.Nevertheless,there are notable differences worthy of attention.Baidu intercity interactive network exhibits pronounced cross-regional effects,and its high-level interactions are characterized by a“rich-club”phenomenon.The AutoNavi intercity interactive network presents a more significant distance attenuation effect,and the high-level interactions display a gradient distribution pattern.Notably,there exists a substantial correlation between the AutoNavi and MP networks at the local scale,evidenced by a high correlation coefficient of 0.954.Furthermore,the“spatial dislocations”phenomenon was observed within the spatial structures at different levels,extracted from the Baidu and AutoNavi intercity networks.However,the measured results of network spatial structure similarity from three dimensions,namely,node location,node size,and local structure,indicate a relatively high similarity and consistency between the two networks.
文摘Online interactive learning plays a crucial role in improving online education quality.This grounded theory study examines:(1)what key factors shape EFL learners’online interactive learning,(2)how these factors form an empirically validated model,and(3)how they interact within this model,through systematic analysis of 9,207 discussion forum posts from a Chinese University MOOC platform.Results demonstrate that learning drive,course structure,teaching competence,interaction behavior,expected outcomes,and online learning context significantly influence EFL online interactive learning.The analysis reveals two key mechanisms:expected outcomes mediate the effects of learning drive(β=0.45),course structure,teaching competence,and interaction behavior(β=0.35)on learning outcomes,while online learning context moderates these relationships(β=0.25).Specifically,learning drive provides intrinsic/extrinsic motivation,whereas course structure,teaching competence,interaction behavior,and expected outcomes collectively enhance interaction quality and sustainability.These findings,derived through rigorous grounded theory methodology involving open,axial,and selective coding of large-scale interaction data,yield three key contributions:(1)a comprehensive theoretical model of EFL online learning dynamics,(2)empirical validation of mediation/moderation mechanisms,and(3)practical strategies for designing scaffolded interaction protocols and adaptive feedback systems.The study establishes that its theoretically saturated model(achieved after analyzing 7,366 posts with 1,841 verification cases)offers educators evidence-based approaches to optimize collaborative interaction in digital EFL environments.
基金supported by the National Key R&D Program of China(No.2019YFA0708304)the CNPC Innovation Fund(No.2022DQ02-0609)the Scientific research and technology development Project of CNPC(No.2022DJ4507).
文摘Measurement-while-drilling(MWD)and guidance technologies have been extensively deployed in the exploitation of oil,natural gas,and other energy resources.Conventional control approaches are plagued by challenges,including limited anti-interference capabilities and the insufficient generalization of decision-making experience.To address the intricate problem of directional well trajectory control,an intelligent algorithm design framework grounded in the high-level interaction mechanism between geology and engineering is put forward.This framework aims to facilitate the rapid batch migration and update of drilling strategies.The proposed directional well trajectory control method comprehensively considers the multi-source heterogeneous attributes of drilling experience data,leverages the generative simulation of the geological drilling environment,and promptly constructs a directional well trajectory control model with self-adaptive capabilities to environmental variations.This construction is carried out based on three hierarchical levels:“offline pre-drilling learning,online during-drilling interaction,and post-drilling model transfer”.Simulation results indicate that the guidance model derived from this method demonstrates remarkable generalization performance and accuracy.It can significantly boost the adaptability of the control algorithm to diverse environments and enhance the penetration rate of the target reservoir during drilling operations.
基金the Talent Fund of Beijing Jiaotong University(Grant No.2024XKRC055).
文摘In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.
文摘The multi-dimensional interactive teaching model significantly enhances the effectiveness of college English instruction by emphasizing dynamic engagement between teachers and students,as well as among students themselves.This paper explores practical strategies for implementing this model,focusing on four key aspects:deepening teachers’understanding of the model through continuous learning,innovating interactive methods such as questioning techniques and practical activities,leveraging modern technology to integrate resources and track learning progress,and establishing a communication platform that centers on student participation.By adopting these approaches,the model fosters a student-centered classroom environment,improves comprehensive English application skills,and optimizes overall teaching quality.
基金supported by National Natural Science Foundation of China(no.62376240).
文摘Software defect prediction aims to use measurement data of code and historical defects to predict potential problems,optimize testing resources and defect management.However,current methods face challenges:(1)Coarse-grained file level detection cannot accurately locate specific defects.(2)Fine-grained line-level defect prediction methods rely solely on local information of a single line of code,failing to deeply analyze the semantic context of the code line and ignoring the heuristic impact of line-level context on the code line,making it difficult to capture the interaction between global and local information.Therefore,this paper proposes a telecontext-enhanced recursive interactive attention fusion method for line-level defect prediction(TRIA-LineDP).Firstly,using a bidirectional hierarchical attention network to extract semantic features and contextual information from the original code lines as the basis.Then,the extracted contextual information is forwarded to the telecontext capture module to aggregate the global context,thereby enhancing the understanding of broader code dynamics.Finally,a recursive interaction model is used to simulate the interaction between code lines and line-level context,passing information layer by layer to enhance local and global information exchange,thereby achieving accurate defect localization.Experimental results from within-project defect prediction(WPDP)and cross-project defect prediction(CPDP)conducted on nine different projects(encompassing a total of 32 versions)demonstrated that,within the same project,the proposed methods will respectively recall at top 20%of lines of code(Recall@Top20%LOC)and effort at top 20%recall(Effort@Top20%Recall)has increased by 11%–52%and 23%–77%.In different projects,improvements of 9%–60%and 18%–77%have been achieved,which are superior to existing advanced methods and have good detection performance.
文摘With the development of globalization,intercultural communicative competence has become one of the core qualities of modern college students.As an important platform to cultivate students’language skills and cultural literacy,the innovation of college English teaching mode is essential.Based on this,this paper mainly discusses methods to effectively cultivate students’intercultural communicative competence in college English teaching from the perspective of multimodal interactive teaching mode,hoping to provide references for improving the quality of college English teaching and students’comprehensive quality.
文摘Objective:To analyze the nursing effect of implementing continuous nursing combined with knowledge,attitude,and practice(KAP)intervention under the guidance of interactive goal-setting theory for patients with gestational diabetes mellitus(GDM).Methods:A total of 68 patients with GDM who were admitted to the hospital between December 2021 and December 2023 were selected and randomly divided into two groups using a random number table.The combined group(34 cases)received continuous nursing combined with KAP intervention under the premise of interactive goal-setting theory,while the conventional group(34 cases)received routine nursing care.Blood glucose control,health behavior scores,and other indicators were compared between the two groups.Results:After nursing,the blood glucose level in the combined group was lower than that in the conventional group,and the scores for health behavior and self-management ability were higher than those in the conventional group(P<0.05).Conclusion:Combined nursing can improve blood glucose control in patients with GDM,standardize their health behaviors,and cultivate their self-management skills.
基金supported by the National Key Research and Development Program of China[2023YFC2307305]Shenzhen Medical Research Fund[B2303003]+3 种基金the Zhujiang Innovation and Entrepreneurship Talents Program[2021ZT09Y544]the Shenzhen Science and Technology Program[ZDSYS20230626091203007]Shanghai CDC(Shanghai three-year(2023–2025)action plan to strengthen the public health system[GWVI–11.1–05])Top Young Talents in Shanghai。
文摘Objective To assess the independent and combined effects of air pollutants,meteorological factors,and greenspace exposure on new tuberculosis(TB)cases.Methods TB case data from Shanghai(2013–2018)were obtained from the Shanghai Center for Disease Control and Prevention.Environmental data on air pollutants,meteorological variables,and greenspace exposure were obtained from the National Tibetan Plateau Data Center.We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases.Results Increased TB risk was linked to PM_(2.5),PM_(10),and rainfall,whereas NO_(2),SO_(2),and air pressure were associated with a reduced risk.Specifically,the strongest cumulative effects occurred at various lags:PM_(2.5)(RR=1.166,95%CI:1.026–1.325)at 0–19 weeks;PM_(10)(RR=1.167,95%CI:1.028–1.324)at 0–18 weeks;NO_(2)(RR=0.968,95%CI:0.938–0.999)at 0–1 weeks;SO_(2)(RR=0.945,95%CI:0.894–0.999)at 0–2 weeks;air pressure(RR=0.604,95%CI:0.447–0.816)at 0–8 weeks;and rainfall(RR=1.404,95%CI:1.076–1.833)at 0–22 weeks.Green space exposure did not significantly impact TB cases.Additionally,low temperatures amplified the effect of PM_(2.5)on TB.Conclusion Exposure to PM_(2.5),PM_(10),and rainfall increased the risk of TB,highlighting the need to address air pollutants for the prevention of TB in Shanghai.
文摘In an aging society,the interface design of smart home products is crucial to the quality of life of the elderly.This paper combines Quality Function Deployment(QFD)and Human-Computer Interaction(HCI)theories,taking smart washing machines as an example,to explore new paths for the interface design of smart home products for the elderly.An interdisciplinary approach is adopted to construct a design process centered on elderly users,introduce the Kano model to classify requirements,realize the mapping and sorting of requirements to design parameters,and adopt the PUGH model for comprehensive evaluation.This study provides practical and theoretical support for the interface design of smart home products for the elderly.
基金National Natural Science Foundation of China,No.42371222,No.41971167Fundamental Scientific Research Funds of Central China Normal University,No.CCNU24ZZ120,No.CCNU22JC026。
文摘The efficient development of the urban economy is a major concern of scholars in the fields of geography and urban science.In the context of globalization,informatization,industrialization,and urbanization,the external relationships of China's cities are experiencing the joint action of urban scale hierarchies and connection networks(“hierarchy-network”).However,under the interactive effect of the two,the mechanism of urban economic efficiency(UEE)is unclear.Therefore,based on Baidu migration data,the regionalization with dynamically constrained agglomerative clustering and partitioning(REDCAP)method,and a spatial simultaneous equation model,this paper analyzes the UEE spatial pattern and mechanism in China.The results indicate that:(1)the urban economy has a superlinear relationship with the population size.However,the benefit of this superlinear growth is in marginal decline.(2)The UEE shows a pattern of differentiation between China's eastern,then central,and then western region.Also,local differences are found within the three major sub-regions.(3)The increase of urban network centrality can promote UEE,while the impact of urban scale is negative.(4)There is regional heterogeneity of the interactive effect of“hierarchy-network”on UEE.This study reveals the influencing mechanism of UEE and also provides policy implications for the development of UEE.
文摘Getting insight into the spatiotemporal distribution patterns of knowledge innovation is receiving increasing attention from policymakers and economic research organizations.Many studies use bibliometric data to analyze the popularity of certain research topics,well-adopted methodologies,influential authors,and the interrelationships among research disciplines.However,the visual exploration of the patterns of research topics with an emphasis on their spatial and temporal distribution remains challenging.This study combined a Space-Time Cube(STC)and a 3D glyph to represent the complex multivariate bibliographic data.We further implemented a visual design by developing an interactive interface.The effectiveness,understandability,and engagement of ST-Map are evaluated by seven experts in geovisualization.The results suggest that it is promising to use three-dimensional visualization to show the overview and on-demand details on a single screen.
基金funded by National Natural Science Foundation of China No.62062003Ningxia Natural Science Foundation Project No.2023AAC03293.
文摘The precise detection and segmentation of tumor lesions are very important for lung cancer computer-aided diagnosis.However,in PET/CT(Positron Emission Tomography/Computed Tomography)lung images,the lesion shapes are complex,the edges are blurred,and the sample numbers are unbalanced.To solve these problems,this paper proposes a Multi-branch Cross-scale Interactive Feature fusion Transformer model(MCIF-Transformer Mask RCNN)for PET/CT lung tumor instance segmentation,The main innovative works of this paper are as follows:Firstly,the ResNet-Transformer backbone network is used to extract global feature and local feature in lung images.The pixel dependence relationship is established in local and non-local fields to improve the model perception ability.Secondly,the Cross-scale Interactive Feature Enhancement auxiliary network is designed to provide the shallow features to the deep features,and the cross-scale interactive feature enhancement module(CIFEM)is used to enhance the attention ability of the fine-grained features.Thirdly,the Cross-scale Interactive Feature fusion FPN network(CIF-FPN)is constructed to realize bidirectional interactive fusion between deep features and shallow features,and the low-level features are enhanced in deep semantic features.Finally,4 ablation experiments,3 comparison experiments of detection,3 comparison experiments of segmentation and 6 comparison experiments with two-stage and single-stage instance segmentation networks are done on PET/CT lung medical image datasets.The results showed that APdet,APseg,ARdet and ARseg indexes are improved by 5.5%,5.15%,3.11%and 6.79%compared with Mask RCNN(resnet50).Based on the above research,the precise detection and segmentation of the lesion region are realized in this paper.This method has positive significance for the detection of lung tumors.
基金supported by the National Natural Science Foundation of China(No.52271367).
文摘In this paper, the online parameter identification problem of the mathematical model of an unmanned surface vehicle (USV) considering the characteristics of the actuator is studied. A data-driven mathematical model of motion is very meaningful to realize trajectory prediction and adaptive motion control of the USV. An interactive identification algorithm (ESO–MILS, extended state observer–multi-innovation least squares) based on ESO is proposed. The robustness of online identification is improved by expanding the state observer to estimate the current disturbance without making artificial assumptions. Specifically, the three-degree-of-freedom dynamic equation of the double propeller propulsion USV is constructed. A linear model for online identification is derived by parameterization. Based on the least square criterion function, it is proved that the interactive identification method with disturbance estimation can improve the identification accuracy from the perspective of mathematical expectation. The extended state observer is designed to estimate the unknown disturbance in the model. The online interactive update improves the disturbance immunity of the identification algorithm. Finally, the effectiveness of the interactive identification algorithm is verified by simulation experiment and real ship experiment.
基金funded by the National Natural Science Foundation of China(Grant No.12272247)National Key Project(Grant No.GJXM92579)Major Research and Development Project of Metallurgical Corporation of China Ltd.in the Non-Steel Field(Grant No.2021-5).
文摘The tensile-shear interactive damage(TSID)model is a novel and powerful constitutive model for rock-like materials.This study proposes a methodology to calibrate the TSID model parameters to simulate sandstone.The basic parameters of sandstone are determined through a series of static and dynamic tests,including uniaxial compression,Brazilian disc,triaxial compression under varying confining pressures,hydrostatic compression,and dynamic compression and tensile tests with a split Hopkinson pressure bar.Based on the sandstone test results from this study and previous research,a step-by-step procedure for parameter calibration is outlined,which accounts for the categories of the strength surface,equation of state(EOS),strain rate effect,and damage.The calibrated parameters are verified through numerical tests that correspond to the experimental loading conditions.Consistency between numerical results and experimental data indicates the precision and reliability of the calibrated parameters.The methodology presented in this study is scientifically sound,straightforward,and essential for improving the TSID model.Furthermore,it has the potential to contribute to other rock constitutive models,particularly new user-defined models.
基金the National Key R&D Program of China(No.2020YFB1313803).
文摘During the robot-assisted pelvic fracture reduction,the needle-tissue interactive deformation characteristic is not clear,which affects the accuracy of robotic surgery.In this paper,a layered rig-id-flexible coupling model is proposed,and the needle-tissue interactive deformation under the load-ing is analyzed by the Rayleigh-Ritz method,in accordance with the principle of minimum potential energy.The pelvic musculoskeletal tissue is reversely reconstructed,and the structure of the bone is segmented into cancellous bone and cortical bone.The Mooney-Rivlin five-parameter hyperelastic model is used to simulate muscle,and the Ogden hyperelastic model is used to simulate adipose tis-sue.Finite element simulation is performed by loading different magnitudes of forces.The accuracy of the rigid-flexible coupling model is 0.432 mm,which indicates the correctness of the needle-tis-sue interactive deformation theory analysis.
基金supported by the Integrated Rail Transit Dispatch Control and Intermodal Transport Service Technology Project(Grant No.2022YFB4300500).
文摘The Balise Transmission Module(BTM)unit of the on-board train control system is a crucial component.Due to its unique installation position and complex environment,this unit has a higher fault rate within the on-board train control system.To conduct fault prediction for the BTM unit based on actual fault data,this study proposes a prediction method combining reliability statistics and machine learning,and achieves the fusion of prediction results from different dimensions through multi-method interactive validation.Firstly,a method for predicting equipment fault time targeting batch equipment is introduced.This method utilizes reliability statistics to construct a model of the remaining faultless operating time distribution considering uncertainty,thereby predicting the remaining faultless operating probability of the BTM unit.Secondly,considering the complexity of the BTM unit’s fault mechanism,the small sample size of fault cases,and the potential presence of multiple fault features in fault text records,an individual-oriented fault prediction method based on Bayesian-optimized Gradient Boosting Regression Tree(Bayes-GBRT)is proposed.This method achieves better prediction results compared to linear regression algorithms and random forest regression algorithms,with an average absolute error of only 0.224 years for predicting the fault time of this type of equipment.Finally,a multi-method interactive validation approach is proposed,enabling the fusion and validation of multi-dimensional results.The results indicate that the predicted fault time and the actual fault time conform to a log-normal distribution,and the parameter estimation results are basically consistent,verifying the accuracy and effectiveness of the prediction results.The above research findings can provide technical support for the maintenance and modification of BTM units,effectively reducing maintenance costs and ensuring the safe operation of high-speed railway,thus having practical engineering value for preventive maintenance.
基金supported by the National Science and Technology Council under grants NSTC 112-2221-E-320-002the Buddhist Tzu Chi Medical Foundation in Taiwan under Grant TCMMP 112-02-02.
文摘In many Eastern and Western countries,falling birth rates have led to the gradual aging of society.Older adults are often left alone at home or live in a long-term care center,which results in them being susceptible to unsafe events(such as falls)that can have disastrous consequences.However,automatically detecting falls fromvideo data is challenging,and automatic fall detection methods usually require large volumes of training data,which can be difficult to acquire.To address this problem,video kinematic data can be used as training data,thereby avoiding the requirement of creating a large fall data set.This study integrated an improved particle swarm optimization method into a double interactively recurrent fuzzy cerebellar model articulation controller model to develop a costeffective and accurate fall detection system.First,it obtained an optical flow(OF)trajectory diagram from image sequences by using the OF method,and it solved problems related to focal length and object offset by employing the discrete Fourier transform(DFT)algorithm.Second,this study developed the D-IRFCMAC model,which combines spatial and temporal(recurrent)information.Third,it designed an IPSO(Improved Particle Swarm Optimization)algorithm that effectively strengthens the exploratory capabilities of the proposed D-IRFCMAC(Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller)model in the global search space.The proposed approach outperforms existing state-of-the-art methods in terms of action recognition accuracy on the UR-Fall,UP-Fall,and PRECIS HAR data sets.The UCF11 dataset had an average accuracy of 93.13%,whereas the UCF101 dataset had an average accuracy of 92.19%.The UR-Fall dataset had an accuracy of 100%,the UP-Fall dataset had an accuracy of 99.25%,and the PRECIS HAR dataset had an accuracy of 99.07%.
